By analyzing almost 120 000 dinucleotides in over 2000 nonredundant nucleic acid crystal structures, we define 96+1 diNucleotide Conformers, NtCs, which describe the geometry of RNA and DNA dinucleotides. NtC classes are grouped into 15 codes of the structural alphabet CANA  to simplify symbolic annotation of the prominent structural features of NAs and their intuitive graphical display. The search for nontrivial patterns of NtCs resulted in the identification of several types of RNA loops, some of them observed for the first time. Over 30% of the nearly six million dinucleotides in the PDB cannot be assigned to any NtC class but we demonstrate that up to a half of them can be re-refined with the help of proper refinement targets. A statistical analysis of the preferences of NtCs and CANA codes for the 16 dinucleotide sequences showed that neither the NtC class AA00, which forms the scaffold of RNA structures, nor BB00, the DNA most populated class, are sequence neutral but their distributions are significantly biased. The reported automated assignment of the NtC classes and CANA codes available at dnatco.org provides a powerful tool for unbiased analysis of nucleic acid structures by structural and molecular biologists. Large folded RNA molecules and plastic but more uniform DNA duplexes are strikingly different and this structural diversity reflects variability of their biological functions. The overall architecture of DNA is characterized by its helicity locked in by the dominant canonical Watson–Crick base pairing and van der Waals stacking while topologically more complicated features such as hairpins, bulges or quadruplexes form more or less local disruptions. In contrast, RNA molecules display complex 3D architectures with an abundance of non-canonical base pairing motifs. These noticeable differences between the molecular architecture of RNA and DNA molecules are however much less obvious when we analyze structural behavior of these molecules at a local level, for instance as distributions of the backbone torsion angles. The scattergrams of the torsion distributions at the phosphodiester bonds O3′-P and P-O5′, and at bonds P-O5′and O5′-C5′ Figure  show ovestructural alphabets since the late eighties , Thermus , and Sae . To comli (5afi  and 5mdzli (5afi ) and fros . The euae (6s47  and 5mreae (6s47 ) and fros .We analyzed the same near-dinucleotide fragment as previously  that covhclust of the R software processing, a beforehand calculated circularity aware distance matrix. The search for new clusters was performed on steps which were so far unassigned. The initial step of the process was generating a temporary golden set, which was constructed from potential classes containing at least eight members, and new members with the best geometry fit to the current members were added.Both old and new NtC conformational classes were newly defined using the 12 geometrical parameters as depicted in Figure The addition of the three new geometry parameters into the fragment definition required only slight modifications of the assignment protocol relative to its previous version , shown sThe assignment protocol was used to generate a self-consistent golden set using the previously derived golden set combined with the temporary golden set. The resulting golden set consisting of 6870 dinucleotide steps defined 96 NtC classes of both DNA and RNA. It was based on the analysis of 114 645 steps, ∼50% of them RNA and 50% DNA, from 2118 crystal structures. The geometry and concise annotation of the 96 NtC classes is in To assess the structural similarity between the analyzed step and a particular NtC class we have previously introduced the confal score . The scoTo be able to assign dinucleotide conformer classes to the first and last bases of tetraloops, we identified all hexanucleotides with sequences N-GNRA-N and N-UNCG-N in our RNA set. We found 3424 such hexanucleotides and analyzed patterns of five NtC codes assigned to them. We found 1316 hexanucleotides with other than double helix forming AAxx, BBxx, ABxx or BAxx NtC classes. Some of these non-trivial repeating patterns of NtCs form tetraloops and other loops of similar size and are reported in Results.consensus RNA conformers published by the RNA Ontology Consortium earlier (The newly defined ensemble of the NtC (diNucleotide Conformer) classes version 3.5 is based on the dinucleotide training set derived from both RNA and DNA crystal structures and describes local dinucleotide structures by an automated stringently geometric assignment protocol. The protocol recognizes 96 NtC classes with defined geometries and one class, NANT, for geometrically unclassified steps; all NtC classes can be browsed at the dnatco.org website. Since our previous analysis , 52 clas earlier . The NtC earlier  were allC2′-endo pucker. Among the unusual conformers, open OP20 links two strands in DNA or RNA, typically in four-way junctions; IC01 has intercalated either a base  or a drug aromatic ring in DNA. The classes found solely in DNA are all B-like conformers, which are sterically nearly impossible in RNA, also several A–B and B–A classes occur significantly more in DNA than in RNA. RNA is more prone to occur in A-like conformers and several new A-like conformational classes occur only in RNA structures, including the frequent AA08. NtC classes with the most atypical torsion combinations and geometry, which are incompatible with the double helical arrangement, are labeled OPxx. Unsurprisingly, they dominate in RNA.Of the 96+1 NtC classes, 31 occur almost solely in DNA structures (defined as <5% of RNA in a given NtC class), and 28 occur mostly in RNA structures. In 15 classes, DNA and RNA occur at comparable frequencies (measured as at least 10% of RNA or DNA dinucleotides in an NtC class). Some of these ‘amphibious’ NtC classes are quite frequent: (i) clearly the most important is the canonical A-form AA00 but some other highly populated A-like conformers, such as AA01 are also observed often. The NtC AB05 is in fact the most frequent RNA conformer with ribose in the intercalated. When the bases are unstacked, not parallel, and/or in another unusual mutual orientation we use letters OP for open. The last two positions of the NtC code are sequentially assigned numbers or the letter S for the first or second base in the syn orientation.Both NtC classes and CANA codes carry a limited mnemonic content but they are primarily formal identifiers. NtCs are labeled by four-letter names. When the bases are stacked, the first letter A, B or Z characterizes the combination of the sugar pucker and glycosidic torsion χ of the first nucleotide, similarly the second letter describes the second nucleotide. For the NtCs with unstacked but parallel bases, we use letters IC for The assignment protocol as currently implemented relies on the standard nomenclature for the atoms defining the analyzed torsions Figure , not on A strictly geometric classification into the NtC classes is a powerful tool for computer-based automated structure annotation. To help a more intuitive understanding of the main structural features of the analyzed structures and to allow their graphical representation, we categorized the NtC classes into fewer groups that define the structural alphabet CANA  .endo sugar pucker, and a high anti glycosidic torsion angle, but some other torsions acquire atypical values. The ICL CANA code includes NtCs with approximately parallel bases that can be intercalated by another base, drug, or amino acid residue. The code OPN contains all NtCs with bases that are not stacked, cannot be intercalated, are often distant, and point to different directions.Many newly identified NtC classes required redefinition of the original CANA codes to reflect the complexities of the RNA architectures and to unify the way how the B and A form conformers are grouped into the CANA codes. The current version 2.3 of the CANA alphabet uses 15 three-letter codes  or by aOPN: the CANA code for ‘open’ dinucleotidescomprises NtCs with variable geometries, which share a common attribute of being ‘open’, having non-stacked and often very distant bases. The OPxx NtCs are rare but they occur in regions critical for DNA and especially RNA folding and allow their formal and unbiased annotation. The geometries of the OPN conformers have unusual torsion angle combinations often far from the energetically optimal values observed in the most populated classes. OPN conformers can therefore be expected to be flexible and generally more influenced by their surroundings. This causes problems with the NtC assignment when wide distributions of the easiest-to-deform descriptors, torsions χ and three parameters measuring the mutual position of both bases, NN, C’C’, and μ, do not allow the unequivocal assignment of any NtC. The assignment protocol may need some modifications to account for the peculiar behavior of the OPN NtCs.OP03 and OP04 are frequent and structurally similar OPN classes occurring often in tetraloops. Of 221 OP03 occurrences in the RNA set, it was found 165 times in the GN step of the GNRA tetraloops; analogical numbers for OP04 are 98 GN steps of 306 occurrences. OP04 also appears in longer motifs OP04-AAxx-ICxx-OPxx or OP04-AAxx-ICxx-NANT interacting with other loops as in the case of the OP04-AA00-IC01-OP14 sequence of residues G1389-A1393 in chain 0 of structure 1vq8 . Anotheranti-orientation. Therefore, it does not occur in the left handed double helices but as an isolated step where the RNA backbone makes a sharp turn, such as step C213–A214 from chain A of 1et4  in the PDB, over 30% remain unassigned as NANT class. It raises a question if such a large fraction of unclassified dinucleotides reflects (a) an inappropriate classification protocol, (b) conformationally unique steps or (c) an incompletely refined dinucleotide geometry. In the following paragraph, we aim to show that the latter option (iii) above is the most likely answer to most cases of the unassigned dinucleotides.(a) Does the assignment protocol miss a large portion of step geometries? We are convinced that it does not. In our previous analysis of the DNA geometry  Do the unassigned steps represent unique conformers? The NtC classes can be seen as a reflection of the free energy hypersurface of nucleic acids because they are identified based on their recurrent occurrence. Therefore, it seems unlikely if not impossible that more than one fifth of the steps in the ensemble of the analyzed structures acquire high energy states with unique geometries that are not classifiable based on the known conformer classes.(c) Could the unassigned dinucleotides represent incompletely refined fragments of nucleic acid structures? To look closer at the geometries of the unassigned steps we calculated how close their geometries are to geometries of the closest NtC class and how well they fit into electron density. The geometric fit was calculated as the root mean square deviation (rmsd) between the investigated dinucleotide and the geometrically closest dinucleotide from the golden set. We calculated two rmsd values, one between the torsions describing the dinucleotide fragment  present a more complicated picture. For the higher resolution structures, more than half of the unassigned dinucleotides fit well into the electron density (RSCC > 0.8) and at the same time have rmsd in both Cartesian and torsion spaces reasonably low; they are in the lower right quadrant. The corresponding percentage for the lower resolution structures is still >30%. By being close to a known NtC class geometrically and by fitting well into the electron density, these unassigned dinucleotides represent just incompletely refined portions of the nucleic acid structures. We believe that these nucleic acid portions can be re-refined with the help of proper refinement targets and sensibly adjusted restraints.In contrast, dinucleotides in the upper left corner, which fit poorly to both electron density and NtC geometry, need complete refitting. However, they are rare in the higher resolution structures and represent well <20% of the unassigned dinucleotides for the lower resolution structures. These poorly fitting dinucleotides represent <5% of all dinucleotides with electron density available. The dinucleotides in the upper right quadrant, which fit well into electron density but poorly to geometries of the NtC classes as we know them now, present a challenge for the current NtC assignment algorithm. Some of these dinucleotides may represent unique conformations, others may form yet undefined NtC classes.The scattergrams in Figure Some NtC classes have a specific structural role and clearly prefer certain sequences. This is especially the case for rare classes, some of which have been discussed above; for example, BBS1 builds up almost exclusively GG steps in DNA and RNA quadruplexes. However, a fundamental question with biological consequences is whether frequent classes building up the main architectural blocks of nucleic acids are sequence-neutral or prefer certain sequences. To answer this question, we calculated the standardized Pearson residuals (SPR)  of the iFigure syn SYN, and Z-like ZZZ dinucleotides make the interpretation of sequence preferences easier for the RNA than DNA steps  and a thin population of unstacked AAu, intercalated ICL, s Figure . The AAALooking into incidences of the main component of the RNA architecture, AA00 class, we observe even more pronounced deviations in sequence preferences than for AAA: it is underpopulated in AA, AC, AG, AU, GA, UA, UG, UU and overpopulated in CC, CG, CU, GC, GG . In otheFor the open conformers under the OPN code, we noticed an interesting relationship between the overpopulated GA and underpopulated GG (and CC) steps. The structural meaning of these preferences is not immediately obvious but it could be related to a high propensity of G and C to form more stable double helices than A and T and therefore being more likely to form double helical than open fragments of RNA molecules.The CANA codes or NtC classes assigned to the DNA dinucleotides reveal a complicated pattern of their under- or overpopulation in the 16 sequences as measured by the SPR. The most important and in our opinion surprising are large over- and under-populations in the BI form classes BB00 and BB01 (CANA BBB). These two NtCs are preferred in A/T rich AA, TT, and TC steps and strongly underrepresented in CG but also in CA, GC, GG. The prevailing B-DNA conformation, BI, is therefore not neutral to dinucleotide sequences as was the case for the A form in RNA.The BII form described by CANA code BB2 disfavors the NY steps and prefers NR ones including CA and TA. The preference for the TA sequence is important in the light of two previous reports about the sequence and structure behavior of the histone-bound DNA: the TA periodicity statistically inferred from the genomic data  and the Some less populated B form-related NtC classes show sequence preferences . For insIn contrast to the SPR indicated sequence preferences of unassigned steps in RNA, which mirror the A form preferences, the SPR values in DNA show only mild sequence dependencies with the exception of overpopulated CG and TT. This means that geometries of incompletely or incorrectly refined steps are not a function of the sequence in DNA structures.followed by the rare A-like AA05, occasionally AA08 or it is unassigned so that the motif GNRA-N can be summarized by the NtC sequence OP03/OP04-AAxx-AAxx-AA05, which was observed in 84 cases  and is followed by dinucleotides in AAxx classes. The three NtCs assigned to the GNRA sequence are often s Figure . It is lpreceding the GNRA tetraloop sequence. It is usually followed by AAxx classes with bases stacked to the last bases of the motif. This N-GNRA motif can be generalized as OP05-AAxx-AAxx-AAxx  SPR values indicate an over-population (under-population) of a given NtC in the active site relative to the rest of the molecule. Table e  riboswiet al. grouped several ribozyme types under the L-platform or L-scaffold (Gaines scaffold  that shoscaffold  2oue (67scaffold  2oue (69scaffold ) and onescaffold ) is showscaffold  confirmiWe analyzed three ribosome structures, 4ybb , 4v90 3 and 4v88We compared frequencies of the NtC classes in the three ribosome crystal structures and selected cryo-EM structures to look at possible differences in the refinement strategies of crystal and cryo-EM data. Table By analyzing sequentially nonredundant RNA and DNA crystal structures, we formulated a set of 96+1 dinucleotide conformer classes, NtC. The 96 NtCs describe the local geometry of both RNA and DNA, the last class is reserved for the geometrically unassigned dinucleotides. The automated procedure assigning the NtC classes is a substantial update of the previously published algorithm . The geoAbout 30% of almost six million steps found currently (December 2019) in the whole PDB cannot be assigned to any NtC class Table . HoweverThe 96+1 NtC classes are grouped into 14+1 codes of the structural alphabet CANA  allowed for a statistical analysis of the sequence preferences of highly populated NtC classes and CANA codes. Calculation of the standardized Pearson residuals (SPR) brought surprising and statistically significant results Figure ,58.The reported automated assignment of NtC classes and CANA codes to dinucleotides in any RNA or DNA structure, which is available with many other functionalities at the dnatco.org web service, provides a powerful tool for an unbiased annotation and validation of nucleic acids with a potential to improve their refinement. It opens new ways to discover and classify nucleic acid structural motifs and enables simple, intuitive graphical representation of the nucleic acid structure and we believe it is of general use for the experts in structural biology as well for molecular biologists and bioinformaticians.gkaa383_Supplemental_FileClick here for additional data file.


Artoviridae was created in 2018 for the established monospecific genus Peropuvirus and six new species of invertebrate viruses that had all been discovered by high-throughput sequencing. Artoviruses have negative-sense RNA genomes of about 12 kb and produce enveloped, spherical particles that are 100–130 nm in diameter. Hosts include parasitoid wasps, barnacles, pillworms, woodlice, copepods and odonates. This is a summary of the International Committee on Taxonomy of Viruses (ICTV) Report on the family Artoviridae, which is available at www.ictv.global/report/artoviridae.The family  Virions of Pteromalus puparum negative-strand RNA virus 1 are enveloped and spherical .Spherically shaped Pteromalus puparum negative-strand RNA virus 1 particles are present in follicular cells of the ovaries of infected parasitoid wasps . SimilarArtovirus negative-sense RNA genomes are of up to 12 kb. All known artoviruses have unsegmented genomes . The PteKnowledge of artovirus replication is limited.Pteromalus puparum ]. The virus is present in various tissues and life stages of the parasitoid and is transmitted vertically through females and males. Virus infection increases adult longevity and impairs several fitness parameters of the wasp, but has no influence on successful parasitism, although it moderates the offspring sex ratio by decreasing female offspring numbers [Pteromalus puparum negative-strand RNA virus 1 was originally isolated from a laboratory parasitoid strain of a pteromalid wasp [Mononegavirales [Bornaviridae, Lispiviridae, Mymonaviridae and Nyamiviridae. Like most other mononegaviruses, artoviruses (i) have unsegmented, negative-sense RNA genomes; (ii) encode proteins with high sequence identity; (iii) have five conserved motifs (A–E) in the amino acid sequence of their RNA-directed RNA polymerases; (iv) produce enveloped virions; and (v) do not rely on cap-snatching but instead cap their own mRNAs.Artoviruses form a family in the haploviricotine order avirales . Within Artoviridae: www.ictv.global/report/artoviridae.Full ICTV Report on the family


One of the major targets of K-Rta is a long non-coding nuclear RNA, PAN RNA (polyadenylated nuclear RNA), a lncRNA that accumulates to exceedingly high levels in the nucleus during viral reactivation. K-Rta directly binds to the PAN RNA promoter and robustly activates PAN RNA expression. Although PAN RNA has been known for over 20 years, its role in viral replication is still incompletely understood. In this perspective, we will briefly review the current understanding of PAN RNA and then describe our current working model of this RNA. The model is based on our observations concerning events that occur during KSHV lytic reactivation including (i) a marked accumulation of RNA Pol II at the PAN promoter, (ii) genomic looping emanating from the PAN locus, (iii) interaction of a second viral lytic protein (ORF57) with K-Rta, PAN RNA and RNA Pol II, (iv) the essential requirement for PAN RNA expression in cis for optimal transcriptional execution needed for the entire lytic program, and (v) ORF57 recruitment of RNA Pol II to the PAN genomic locus. Together our results generate a model in which the PAN locus serves as a hub for sequestration/trapping of the cellular transcriptional machinery proximal to viral episomes. Sequestration at the PAN locus facilitates high levels of viral transcription throughout the viral genome during lytic replication. ORF57 acts as a transcription-dependent transactivator at the PAN locus by binding to both Rta and PAN to locally trap RNA Pol II. The resulting accumulation of high levels of nuclear PAN RNA created by this process is an inducible enhancer-derived (eRNA) by-product that litters the infected cell nucleus.Kaposi’s sarcoma-associated herpesvirus (KSHV), also designated human herpesvirus 8 (HHV-8), has been linked to Kaposi’s sarcoma, as well as to primary effusion lymphoma (PEL), and a subset of multicentric Castleman’s disease. KSHV genomes are maintained as episomes within infected cells and the virus exhibits a biphasic life cycle consisting of a life-long latent phase during which only a few viral genes are expressed and no viral progeny are produced and a transient lytic reactivation phase, in which a full repertoire of ~ 80 lytic genes are activated in a temporally regulated manner culminating in the release of new virions. Lytic replication is initiated by a single viral protein, K-Rta (ORF50), which activates more than 80 viral genes from multiple resident viral episomes (i.e. Alphaherpesvirinae, Betaherpesvirinae, and gammaherpesvirinae [Herpesviruses are large, enveloped, double-stranded DNA viruses that infect a wide range of species. These viruses are classified into three subfamilies: svirinae . The estsvirinae –29.TablKSHV is a member of the gamma-herpesvirus family with a ~ 150 kb ds DNA genome. Recent comprehensive functional genomic approaches , 31 as w5 copies per cell in infected PEL cell lines [PAN RNA is either expressed at low levels or non-expressed during latency but highly expressed during lytic reactivation with early kinetics , 30, 31 ll lines , 45. PANll lines . The PANll lines , 48. ConPAN RNA expression is an essential requirement for KSHV late gene expression and virus production , 15, 49.in cis for optimal transcriptional execution needed for the entire lytic program and (v) ORF57 recruitment of RNA Pol II to the PAN genomic locus. We will detail each of these pieces of evidence in the sections that follow. The model is also inspired by the new convergence of cellular biophysics and transcription that has emerged from recent studies of subcellular compartments which suggest a role for liquid-liquid phase separation (LLPS) as a way to sequester specific proteins within both cytoplasmic and nuclear compartments that are not separated by membranes [Our model is based on studies combining molecular virology, capture Hi-C, RNA-seq, RNA-FISH and immunofluorescent imaging. We combine the following observations taken from the first ~ 24 h following reactivation to propose our working model as perspective, including (i) a marked accumulation of RNA Pol II at the PAN promoter (ii) genomic looping emanating from the PAN locus (iii) interaction of a second viral lytic protein ORF57) with K-Rta, PAN RNA and RNA Pol II (iv) the requirement for PAN RNA expression embranes , 53. Theembranes , 55. IDRembranes , 56 with with K-Rembranes . In manyembranes , 60. In embranes . SEs conembranes . Recent embranes  and LLPSFor KSHV, the expression of one viral protein  is sufficient to trigger the entire viral lytic program. In addition to viral lytic transcriptional activity, additional changes are also observed on the KSHV genome during early reactivation including histone modifications  occupancWe recently adapted RNA-FISH approaches to study KSHV transcription in situ and to probe KSHV gene expression in the nuclei of infected host cells . RNA-FISCapture Hi-C analyses , 75 wereRapid Immunoprecipitation Mass spectrometry of Endogenous protein (RIME) [While the mechanisms underlying genomic structural changes remain poorly understood, genomic 3D structure re-organization is known to be very important in many biological aspects such as tissue-specific gene expression , 76–79. n (RIME) . This men (RIME) , 82. Accn (RIME) , 83. Ourn (RIME)  and recrn (RIME) .in trans could rescue the defective lytic gene expression that exists in these cells. PAN Mu cells were transfected with a PAN expression vector 48 h prior to reactivation. This transfection raised the level of PAN RNA 3000-fold above the level present in reactivated PAN mutant cells transfected with an empty vector and was ~equivalent to the PAN RNA level obtained when wild-type BAC16 containing cells are reactivated. Despite this high level of ectopic PAN RNA complementation, lytic viral gene expression remained dramatically defective relative to reactivated cells containing wild-type BAC16. This lack of rescue suggests that activation of the PAN promoter and/or active transcription of PAN RNA is important for transactivation of many other viral lytic genes.We have previously developed a series of PAN mutants  using reEnhancement of distal promoter activation strongly indicates that ORF57 not only stabilizes PAN RNA post-transcriptionally but may also contribute to increased recruitment of RNA Pol II either through interaction with K-Rta and/or nascent RNA molecules. To examine our model, we performed ChIP assays with recombinant BAC16 containing HA-tagged ORF57 wild-type or HA-tagged ORF-57Stop cells that produce a N-terminal truncated ORF57 protein. The results showed that in the absence of full-length ORF57 protein, recruitment of RNA Pol II to the PAN RNA coding region was significantly impaired. This is also in good agreement with RT-qPCR analyses, which showed decreased PAN RNA expression in the absence of ORF57. In addition, IFA visualization and quantification of RNA Pol II foci during reactivation demonstrated that ORF57 expression correlated with larger-sized aggregates Fig.  Based onOur working model is depicted in Fig. in trans [Would the stabilized presence of the PAN locus 5′ and 3′ ends be sufficient to facilitate transcriptional re-initiation? There are several reports describing this type of interaction in yeast –89. Indein trans , a requiin trans  showing in trans , thus PAin trans , 105. Fu


RNA editing is a relatively unexplored process in which transcribed RNA is modified at specific nucleotides before translation, adding another level of regulation of gene expression. Cephalopods use it extensively to increase the regulatory complexity of their nervous systems, and mammals use it too, but less prominently. Nevertheless, little is known about the specifics of RNA editing in most of the other clades and the relevance of RNA editing from an evolutionary perspective remains unknown. Here we analyze a key element of the editing machinery, the ADAR (adenosine deaminase acting on RNA) gene family, in an animal with a key phylogenetic position at the root of chordates: the cephalochordate amphioxus. We show, that as in cephalopods, ADAR genes in amphioxus are predominantly expressed in the nervous system; we identify a number of RNA editing events in amphioxus; and we provide a newly developed method to identify RNA editing events in highly polymorphic genomes using orthology as a guide. Overall, our work lays the foundations for future comparative analysis of RNA-editing events across the metazoan tree. Changes in the regulation of gene functions are at the basis of morphological evolution, from the simplest metazoans to the possessors of amazingly complex nervous systems. Contemporary textbook examples of mechanisms that allow exquisite fine-tuning of this regulation are alternative splicing in vertebrates and RNA gene editing in cephalopods ,2,3. BotMus musculus. Mouse embryos lacking ADAR will die before birth due to stress-induced apoptosis [in silico. This is partially due to the difficulty of detecting bona fide RNA-editing events in enough species, which ideally requires the sequencing of both DNA and RNA from the same individual [Although increasing the levels of regulation and the diversity of the proteome has clear benefits, the evolutionary implications of RNA-editing are yet to be discovered. The role of the ADAR family itself is well known in vertebrates and cephalopods . Its rempoptosis  and micepoptosis . In humapoptosis . Severalpoptosis ,15,16; hdividual . This isdividual . In thisBranchiostoma lanceolatum, and propose a method to deal with its highly polymorphic genome when identifying in silico RNA-editing sites, that can be used with any organism with genomic and RNA-seq data available. This novel method, combined with an original pipeline, allows the identification of orthologous editing events between two species. Overall, our work lays the foundations for future comparative analysis of RNA-editing events across the metazoan tree.Here, we present for the first time the characterization of the ADAR family and its expression through the development of the amphioxus Ziziphus jujuba and Prunus persica.We selected the following sequences from NCBI: NP_001180424.1, NP_001344887, ALX72798.1, XP_031746878, XP_026690338.1, NP_571671.2, XP_030849200.1, NP_001103.1, NP_001020008, NP_001104544.1, NP_001096190.1, XP_021334694.1, AAF78094.1, NP_443209.2, XP_418563.4, XP_031759801.1, XP_686426.5, XP_781832.1, XP_002128212.1, XP_015888627.1, XP_020412580.1, XP_019848877.1, XP_003387867.1 for alignment with MAFFT (v7.307) [Adar), BL01761 (Adarb), BL13719 (Prox1), and BL11117 (Elav) from the transcriptome produced by Marletaz et al. [We followed the third generation in situ Hybridization Chain Reaction protocol, which has been recently optimized for amphioxus . We usedz et al. .B. lanceolatum genome [In the first step of our pipeline, we used bowtie2 (v2.3.5.1)  to alignm genome  and thenm genome  to perfoWe repeated the previous steps with the DNA reads (accession PRJEB13665) instead of the RNA-seq reads in order to get the confirmed SNPs. In this step we did not use the depth cut-off. We then filtered out the candidate list of SNVs that appeared as confirmed SNPs in order to get the putative RNA-editing events. We then made an aggregative analysis of all the tissue and stage putative events.The analyzed sequences were blasted against the RefSeq protein database and run through InterProScan. Then, the blasted sequences were mapped and annotated using Blast2GO  and mergFrom the candidate list and a human RNA-editing database  we usedFor the curation of the events in window size 0, class 1, we manually evaluated the quality of the alignment within the local region to the putative events. We also used the genomic sequence of the annotated genes to get the full pre-mRNA sequence of all the isoforms that include the putative events. We then got the predicted secondary structure of the pre-mRNA molecules using linearfold . We consB. lanceolatum [Adar and Adarb  and the increase of Adar expression at pre-metamorphic stages.We further exploited available RNA-seq datasets to characterize the expression profile of  tissues B and dur tissues C,C’. ForB. lanceolatum, on two developmental stages: mid-neurula and larva.We next took advantage of the high sensitivity of the hybridization chain reaction (HCR) method, to detect in situ the low levels of expression of the two Adar genes during the development of Adar and Adarb , hence not perceived as polymorphisms. This yielded a total of 184,163 unique putative RNA-editing events within 23,406 coding loci  with a mean 7, 87 SNVs per locus where more than half  would result in a synonymous editing. A complete GO analysis of the genes harboring SNVs can be found in For each RNA-seq dataset, after looking for single nucleotide variants (SNVs) matching A-to-G (as inosine is detected as a guanosine by synthesis-based sequencing methods) or T-to-C (in the reverse strand) transitions, we filtered them using the genomic reads leaving only the SNVs that were not supported by the genomic reads available at the The A-to-I SNV predictions, while being filtered by the genomic reads, could still harbor false positives that were not a result of RNA-editing events, but were due to genomic polymorphisms. We thus performed an orthology-based approach (see methods) to better infer the genuine RNA-editing events, identifying the changes that were conserved between two very distinct species (in this case human and amphioxus). As the homologous amino acid position can vary depending on the quality of the alignment, we implemented a window of homology and tested it at size 0, 1, 5, and infinite amino acids of aligned distance between the two edited amino acids. As the window size increases, so does the permissiveness of the approach, yielding more putative orthologous RNA-editing events. In addition, we separated the events into the following classes: class 0, when the editing resulted in a synonymous change in both interrogated species; class 1, where both the pre-edited and the edited amino acids were conserved between the interrogated species; class 2, where the pre-edited amino acids were not conserved between the interrogated species, but the edited ones were; class 3, where the pre-edited amino acids were conserved between the interrogated species, but the edited ones were not; class 4, where neither the pre-edited nor the edited amino acids were conserved between the interrogated species . All theA detailed list of selected class 1 events at window size 0 is also available . We checAdar knockout mice were shown to be embryonically lethal and mice lacking Adarb1 died in a few days after birth due to the lack of editing in GluR-B receptor [B. lanceolatum RNA-seq dataset [Adar was highly expressed in the neural tube, whereas Adarb was found ubiquitously expressed at low levels in a variety of adult tissues. In vertebrates, however, Adarb1 was expressed more significantly in the neural and muscle tissues, Adarb2 was predominantly expressed in neural tissue, and Adar seemed to have a more pervasive expression [WDR37 and ADARB2, the tissue expression distribution seemed to not be conserved. It was remarkable how from the expected up to four vertebrate paralogs for each gene, Adar had only one ortholog without any clear synteny conserved with amphioxus, and Adarb had two, but one of them was enzymatically inactive. This could mean that an excess of A-to-I editing can be deleterious as very few organisms had more than two enzymatically active ADAR proteins [The most prominent cases of ADAR-dependent A-to-I editing have been reported in the nervous system and the brain of mammals and other vertebrates. Specifically, editing targets were found in key mediators of synaptic transmission . More rereceptor ,12,30. A dataset  (Figure pression . Althougproteins .Octopus bimaculoides, and in vertebrates such as mouse or human. Altogether, this suggests that RNA-editing regulation might have been instrumental for nervous system evolution.The in situ data shown here was the first report of ADAR family expression in amphioxus during development, using the highly sensitive technique of in situ HCR , a recenAdar and Adarb were both expressed in the developing neural tube and were initially co-expressed with Elav and Prox1. Both genes have established roles during neurogenesis: Elav is a well-known pan-neural marker [Prox1 is a homeobox gene involved in many developmental processes, including neural progenitor differentiation and exit from the cell cycle [Elav and Prox1 at the mid-neurula stage suggests that RNA editing might play a role in neurogenesis in amphioxus. Interestingly, Takahashi and collaborators [Prox1, which can act as a tumour suppressor, experienced RNA-editing and loses tumour-suppressive functions in a subset of human cancers. This indicated that in the neural tube and muscles, where ADAR paralogues are co-expressed with Prox1, Adar may be editing Prox1, meaning that the edited isoform of Prox1 could have a role during the development of these particular tissues and cells.Our results show that l marker  and was l marker ,37, whilll cycle ,38,39. Tborators  demonstrbona-fide editing events, we chose to follow an orthology-based approach, taking advantage of the RNA-editing data of a distant but related species, the human [The first report of an amphioxus genome, already indicated  that thehe human , and thehe human ,34. Our Although more analysis must be done to ensure that each of these putative RNA-editing events were not false positives, and problems, like the loss of non-conserved genes in the analysis need to be solved for a proper evolutionary analysis of the RNA-editing, we developed a tool that can be used between any two species to infer putative RNA-editing sites by homology. This method only required that data of RNA-editing exists for the reference species, and genomic and RNA-seq data is needed for the species interrogated.Adar and Adarb in B. lanceolatum embryos, showing that both were expressed in the neural tube and muscles. We used a genomic filter for countering the polymorphic amphioxus genome and detected 184,163 unique cases of A-to-G and T-to-C variants that are putative RNA-editing events in several adult tissues and during embryonic development. Finally, we developed a pipeline for the assessment of RNA-editing conservation in which the astringency can be adjusted, and widely used with any species having RNA-seq and genomic datasets available.We characterized experimentally for the first time the expression of the core RNA editing genes,


Drosophila are affected by whether flies are provided a choice of different nutrients or a single, complete medium, largely independent of the amount of nutrients that are consumed. Meal choice elicits a rapid metabolic reprogramming that indicates a potentiation of TCA cycle and amino acid metabolism, which requires serotonin 2A receptor. Knockdown of glutamate dehydrogenase, a key TCA pathway component, abrogates the effect of dietary choice on lifespan. Our results reveal a mechanism of aging that applies in natural conditions, including our own, in which organisms continuously perceive and evaluate nutrient availability to promote fitness and well-being.It has been recognized for nearly a century that diet modulates aging. Despite early experiments suggesting that reduced caloric intake augmented lifespan, accumulating evidence indicates that other characteristics of the diet may be equally or more influential in modulating aging. We demonstrate that behavior, metabolism, and lifespan in  Drosophila melanogaster, choose their foods. The effects of these choices can affect health via a chemical in the brain called serotonin. This chemical interacts with proteins called serotonin 2A receptors in the brain, which then likely primes the body to process nutrients.The foods we eat can affect our lifespan, but it is also possible that thinking about food may have effects on our health. Choosing what to eat is one of the main ways we think about food, and most animals, including the fruit fly To understand how serotonin affected the lifespan and health of fruit flies, Lyu et al. compared flies that were offered a single food to those that could choose between several foods. The flies that had a choice of foods lived shorter lives and produced more serotonin, but these effects were reversed when Lyu et al. limited the amount of a protein called glutamate dehydrogenase, which helps cells process nutrients.These results suggest that choosing what we eat can impact lifespan, ageing and health. Human and fly brains share many similarities, but human brain chemistry is more complex, as is our experience of food. This work demonstrates that food choices can affect lifespan. More research into this phenomenon may shed further light onto how our thoughts and decision-making impact our health. For nearly all metazoans, many aspects of biology are continuously influenced by information about nutrient availability. Interest in the nutritional determinants of aging date back to the early 1900s, as experiments in fruit flies  and rodeResearch over the past century on the effects of DR has revealed how food characteristics influence healthy aging . For manDrosophila  during the adult stage is required for many of the effects caused by dietary choice, including a 5-HT2A-dependent metabolic reprogramming that is consistent with a significant upregulation of the tricarboxylic acid (TCA) cycle and amino acid metabolism when nutrients were presented separately. Transgenic knockdown of a key enzyme, glutamate dehydrogenase (GDH), which is predicted to diminish the metabolic changes induced by a choice diet, abrogated its effects on lifespan. Future research may elucidate the downstream targets through which neuronal 5-HT2A signals acts as a potent modulator of aging and physiology in an environment much like our own, where animals must constantly choose between different nutrients.Here we present a series of experimental results that indicate that dietary choice elicits significant changes in the physiology and lifespan of male D. melanogaster reared in a conventional laboratory setting is normally provided with a homogenous, complete media that meets all of its nutritional needs. For flies, this medium is comprised predominantly of a source of protein and micronutrients  and a carbohydrate source . In natural conditions, however, a complete food source is unlikely to be found, and animals must seek out and identify nutritionally complementary foods  have only modest effects , much smry sugar , but it ry sugar . TogetheAlthough protein intake was not different in flies fed different diets, it seemed possible that dietary choice improved protein absorption, which might be important considering the influential role of this macronutrient in reducing lifespan . EvidencP-element insertion in the promoter region of serotonin receptor 2A (PL000525-HT2A), which creates a putative loss of function mutation in this gene  and strongly reduced the effect in the second . Behavioral classification of the movements during this time . From these data we concluded that diet-dependent changes in locomotion are not causal to changes in lifespan.DR, and the extended lifespan that accompanies it, are associated with increased locomotion behavior in several species , presumahis time  revealedhis time . As with5-HT2A mutant flies did not exhibit a difference in ethanol food interactions based on previous diet , would persist in the two strains. We also chose to sample flies 48 hr after a dietary switch because this period was sufficient to significantly affect mortality rates see  and becay choice  above, iy choice . We ther5-HT2A mutant flies, suggesting that the metabolites that load strongly on these axes exhibit slow, persistent changes in response to differences in nutrient presentation that are not associated with changes in mortality. Finally, a single PC in both heads and bodies (represented by PC6 in both data sets) distinguished acute responses to dietary switch in both tissues that were abrogated in 5-HT2A mutant animals , we identified three principal components (PCs) in each of the tissue samples by which metabolome profiles effectively separated genotypic effects from those caused by nutrient presentation  and a non-significant diet × genotype interaction (pDiet*Genotype>0.05). Of the 103 and 125 metabolites that were detected in each tissue sample, respectively, we found that 45 (heads) and 46 (bodies) satisfied these criteria (The PCA results suggested that nutrient presentation influenced two processes: (A) a relatively stable 5-HT2A-independent metabolic network that responded slowly to dietary environment and that accounted for a significant amount of metabolome variation (10.2–11.2%) and (B) a dynamic 5-HT2A-dependent metabolic network that accounted for a smaller component of variation (2.0–2.2%) that responded quickly to dietary choice and that was associated with mortality. Using generalized linear models, we identified individual metabolites that exhibited statistically significant changes consistent with membership in each of these two groups . In this case, six of seven of the metabolites that were present in both groups  coupled with UAS-GDH-RNAi blocked the lifespan differences between two dietary environments (tub-GS-GAL4 coupled with UAS-GFP) responded as expected to dietary choice when RU486 was presented  and allowing the animals to behaviorally structure their own diet, we found that lifespan was significantly shortened in both male and female flies. In addition, changes in activity, stress resistance, lipid metabolism, and critical metabolic processes were also elicited by dietary choice. Flies carrying a loss-of-function mutation in serotonin receptor 5A (5-HT2A), with RNAi-mediated neuronal knockdown of 5-HT2A expression, or fed the putative receptor antagonist pirenperone, exhibited no differences in lifespan between choice and fixed diets, indicating that serotonin signaling through this receptor plays an essential role in the effect of nutrient presentation on aging.Here we studied the effects of meal presentation on aging and physiology in dFoxo, which is an essential effector of dietary sugar on aging  the effect of dietary choice on lifespan is significantly larger than that caused by even the most extreme carbohydrate-rich fixed diets  after which time mortality rates in cohorts provided a fixed or choice diet were indistinguishable. This was true regardless of whether the flies had been presented with a dietary choice starting at eclosion or starting at 20 days of age, and these effects required serotonin receptor 5-HT2A. The effects of dietary choice on demographic aging, therefore, do not appear to accumulate, and they are simply absent in older flies, perhaps because of an age-dependent reduction in serotonin signaling, a lack of consequences of such signaling in older animals, or the manifestation of demographic heterogeneity . These mC. elegans, it has been reported that αKG modulates longevity by inhibiting TOR signaling . Δ94dFoxo were backcrossed into Dahomeyw prior to the lifespan experiments. Two isofemale lines  were gifts from P. Schmidt . Tub-GS-GAL4 was obtained from R. Davis . elav-GAL4 (BDSC#458) and UAS transgenic lines, including TRiPUAS-5-HT2A-RNAi (BDSC#31882), KKUAS-5-HT2A-RNAi (VDRC#102105), UAS-GDH-RNAi (BDSC#51473), and UAS-eGFP (BDSC#79025), were purchased from either the Bloomington Drosophila Stock Center or the Vienna Drosophila Resource Center.The standard laboratory stocks lication , 5-HT2APAll fly stocks were maintained on a standard cornmeal-based larval growth medium (produced by LabScientific Inc and purchased from Fisher Scientific) and in a controlled environment  with a 12:12 hr light:dark cycle. We controlled the developmental larval density by manually aliquoting 32 µl of collected eggs into individual bottles containing 25 ml of food. Following eclosion, mixed-sex flies were kept on SY10 (10% [w/v] sucrose and 10% [w/v] yeast) medium for 2–3 days until they were used for experiments. Pioneer table sugar  and MP Biomedicals Brewer’s Yeast (purchased from Fisher Scientific) were used in our study.To study the lifespan, behavior, and physiology of flies that have a dietary choice, we created food wells that were divided in the middle . This alWe purchased all drugs from Sigma-Aldrich. In the pirenperone experiment, drug was initially dissolved in 100% dimethyl sulfoxide (DMSO) at 10 mM concentration, aliquoted and stored at −20°C. Prior to the experiment, 200 µM pirenperone and the same dilution of DMSO (control vehicle) were made. Then, 50 µl of the diluted drug or control vehicle was added to each food well. After the liquid evaporated (~2 hr), the food plates were ready for use as described in Survival assays.In the GeneSwitch experiment, RU486 (mifepristone) was first dissolved in 80% (v/v) ethanol at 10 mM concentration, marked by blue dye , and stored at −20°C. For experimental food, 200 µM RU486 or the same dilution of control vehicle (80% [v/v] ethanol) was made from the stock and added to the food. To ensure flies consumed the same amount of RU486 between the choice diet and the fixed diet, drug was only administrated in the yeast portion of the choice diet, since the yeast intake on a choice diet is indistinguishable from the sugar–yeast intake on the fixed diet . LifespaLifespans were measured using established protocols . NormallWe used the protocol described previously . Experim2. We synchronized the feeding state prior to loading flies onto the FLIC system. Flies were removed from their food environment to kimwipes with 2 ml of water 2 hr before their natural breakfast time. At the peak of their normal breakfast meal (lights on), we flipped flies back onto their respective choice or fixed diets and let them feed for 2 hr. Following breakfast feeding, flies were briefly fasted for 3 hr on a wet kimwipe with 2 ml of water. We began the FLIC recording software before aspirating flies into the system and analyzed food or ethanol interactions for 6 hr. Flies were anesthetized briefly on ice and manually aspirated into the Drosophila feeding monitors (DFMs). Each DFM was loaded with flies from at least two treatment groups to reduce technical bias from the DFM signals. FLIC data were analyzed using custom R code, which is available at wikiflic.com. Default thresholds were used for analysis except for the following: minimum feeding threshold = 20, minimum events = 1, and tasting threshold = . Flies that had zero feeding events over the testing interval were removed from the analysis.Flies were tested on the Fly Liquid-Food Interaction Counter (FLIC) system as previously described to monitor ethanol feeding  after exExperimental males were reared on SY10 food for 2–3 days shortly after eclosion. We aspirated individual flies into the two-choice food arenas  and let them adapt to the environment for 1 day. Then, 6 hr video recording  was taken and analyzed with DTrack, a video analysis package developed in the Pletcher Laboratory. Using the same speed threshold published before , we clas2 anesthesia, after which they were allowed to recover for 30 min. We used an automated process in which flies were dropped from 24’. After freefall, which effectively knocked the flies to the bottom of the chamber, a video camera was triggered and individual fly movements were tracked for 10 s using the DDrop software developed in our laboratory. From the tracking data, we were able to calculate, for each male, the total distance traveled up in 10 s.After the designated exposure to the choice or fixed diet for 10 days (food was changed every 2–3 days), male flies were transferred to the negative geotaxis apparatus using brief COAfter the designated exposure to the choice or fixed diet for 2 or 3 weeks (food was changed every 2–3 days), experimental flies were quickly frozen, collected into groups of five, weighed, and then homogenized in 200 μl of cold phosphate-buffered saline containing 0.1% Triton X-100 (IBI Scientific) for 30 s at 30 Hz using a QIAGEN TissueLyser. For TAG quantification, the homogenate (20 μl) was added into 200 μl of Infinity Triglyceride Reagent (Thermo Electron Corp.) and incubated at 37°C for 10 min with constant agitation. TAG concentrations were determined by the absorbance at 520 nm and estimated by a known triglyceride standard. For protein measurement, 5 μl of fly homogenate was incubated with 200 μl of (1:50) 4% (w/v) cupric sulfate/bicinchoninic acid solution (Novagen) at room temperature for 30 min. Protein concentrations were estimated by the absorbance at 562 nm through the comparison with bovine serum albumin standards. Average weight, TAG, and protein values were based on at least six independent biological replicates (of five flies each) from multiple vials.After the designated exposure to the choice or fixed diet for 20 days (food was changed every 2–3 days), flies were transferred to fresh vials containing 1% (w/v) agar. The number of dead flies was recorded approximately every 2–5 hr using DLife system.1118w males on choice diet was roughly 70%), flies were transferred to S30 (30% [w/v] sucrose) food with 2.5% (w/v) blue dye  for 24 hr. A fly was counted as a Smurf when blue was observed outside of the digestive tract , and following eclosion, males and females were allowed to mate on SY10 food for 48–72 hr. Eight females and eight males were then sorted into individual vials, which contained either a choice or a fixed diet. Egg counts were taken on days 1, 2, 5, and 8 after sorting. Flies were transferred to fresh SY food 24 hr prior to the counting.After exposure to the choice or fixed diet for 20 days, experimental flies were flash frozen in liquid nitrogen. Heads and bodies were separated using a metal sieve on dry ice, and 10 heads were pooled for each biological replicate. Heads were first pulverized to a fine powder using a plastic pestle on dry ice. Protein extraction was carried out on ice using RIPA buffer (Sigma–Aldrich) supplemented with protease inhibitor cocktail (Sigma), phosphatase inhibitor cocktail (Sigma), sodium orthovanadate , and sodium fluoride . Ice cold buffer (105µl) was added to heads followed by immediate homogenization with a motorized pestle for 10 s on ice. Lysates were incubated on ice for 10 min followed by 15 s of sonication and centrifugation at 16,000 × g at 4°C for 10 min. Supernatants were recovered, and protein concentration was determined using the Pierce BCA Protein Assay Kit (Fisher Scientific). Thirty micrograms of protein lysate was added to 2× protein sample buffer  and denatured at 95°C for 10 min. Protein was separated by SDS–polyacrylamide gel electrophoresis on a 4–12% gel (Bio-Rad) at 200 V for 30 min, followed by electrophoretic transfer to PVDF membrane at 70 V for 1 hr. Blots were incubated in 5% milk in 1% TBS-T at room temperature for 1 hr, followed by overnight incubation with primary antibodies overnight at 4°C . Membranes were washed with 1% TBS-T and incubated with HRP-conjugated secondary antibodies (Abcam) at room temperature for 4 hr. Membranes were washed again with 1% TBS-T and then incubated briefly in ECL substrate  before imaging.Male flies were exposed to the choice or fixed diet for 20 days (food was changed every 2–3 days) and then switched to the other diet  or the same diet (control groups). Heads were removed via vortexing and manually separated from the bodies. Heads or bodies were then homogenized for 20 s in 200 μl of a 1:4 (v:v) water:MeOH solvent mixture using the Fast Prep 24 . Following the addition of 800 μl of methanol, the samples were incubated for 30 min on dry ice, then homogenized again. The mixture was spun at 13,000 RPM for 5 min at 4°C, and the soluble extract was collected into vials. This extract was then dried in a speedvac at 30°C for approximately 3 hr. Using a liquid chromatography triple quadrupole tandem mass spectrometry (LC–QQQ–MS) machine in the multiple reaction monitoring (MRM) mode, we targeted 205 metabolites in 25 important metabolic pathways, in both positive MS and negative MS modes.k-nearest neighbor algorithm with the impute package of R Bioconductor (http://www.bioconductor.org). We then normalized the data to the standard normal distribution . PCA was performed using the made4 package of R Bioconductor.After removing any metabolites missing from more than 8 of 76 head samples (10.5%) and 8 of 78 body samples (10.3%), we were left with 103 head metabolites and 125 body metabolites. Metabolite abundance for remaining missing values in this data set were log-transformed and imputed using the -dependent, fast-responding metabolic network that is associated with aging despite only accounting for a small number of variation in the metabolomes (2.0–2.2%) and (2) a 5-HT2A-independent, stable metabolic component that accounts for a significant amount of metabolome variation (10.2–11.2%). To distinguish these two groups of metabolites, we used a linear model to analyze the variance attributed to diet, genotype, and interaction of the two for each metabolite:Our PCA results suggest the choice diet can elicit two processes: (1) a 5-HT2AMetabolite abundance (Y) = Diet + Genotype + Diet * Genotype.-dependent manner (Diet*Genotype≤0.05). To identify 5-HT2A independent change, we searched for metabolites that have a diet effect (pDiet≤ 0.05) but did not show a diet–genotype interaction (pDiet*Genotype>0.05). In doing so, we found 45 and 46 metabolites in the head and body, respectively. We plotted a heatmap to illustrate the expression changes of the metabolite upon nutrient presentation using the R package gplots. The metabolites were mapped to biochemical pathways using MetaboAnalystR 3.0  were carried out using the statistical package R within DLife . p‐Valuegithub.com/ylyu-fly/Metabolomics-FlyChoiceDiet; swh:1:rev:86daef110d9a1eb27262bc5310b54cc2d315f7c1).Source data for all quantifications shown in Data  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Drosophila Serotonin 2A receptor signaling coordinates central metabolic processes to modulate aging in response to nutrient choice".Your work highlights the importance of choice making in the regulation of organism lifespan and reveals the crucial role of serotonin signaling in this regulation. We believe that this finding will provide a new angle for us to understand how diet modulates aging and longevity. In addition, in order to provide a clear indication of the biological system under investigation, we would like to suggest a revision of the title, "Decision letter after peer review:eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Jessica Tyler as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: David Walker (Reviewer #2).Thank you for submitting your article "Serotonin 2A receptor signaling coordinates central metabolic processes to modulate aging in response to nutrient choice" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife, either of which would be linked to the original paper.Our expectation is that the authors will eventually carry out the additional experiments and report on how they affect the relevant conclusions either in a preprint on bioRxiv or medRxiv, or if appropriate, as a Research Advance in Summary:Lyu et al. present interesting findings that nutritional choice affects organism physiology and lifespan. They provide compelling evidence to support that such effects are not a simple result of altered nutrient consumed. They further implicated the serotonin receptor 5-HT2A in this regulation by the dietary choice. Through metabolomic analysis, they also revealed changes in the TCA cycle and amino acid metabolism. Although reviewers agree the concept of nutritional choice regulating longevity is novel and will be of great interest to the field of aging, they suggested additional data and edits would help strengthen this claim.Essential revisions:1) The key claim that the observed changes are due to nutritional choice requires additional experiments.a) When macronutrients are provided separately, there might be difference in consumption and absorption, contributing to the observed phenotypes. The authors have assayed consumption, showing flies consuming more sugar and the same amount of yeast on the choice diet. But the change in absorption has not been ruled out. The authors should determine whether consumption and/or absorption of each nutrient is altered in the choice diet when compared to mixed diet and perform this comparison in young and middle-aged files. For example, assessment of fecundity and mTOR signaling will help find possible changes in protein intake.b) The olfactory perception of yeast can be different between the choice diet and the mixed diet. The previous finding from the lab has revealed the importance of yeast smell on fly lifespan. To rule out the smell of yeast as a confounding factor, the olfactory mutants that are smell blind should be subject to the choice diet.GDH RNAi flies eat more under the choice diet.2) The mechanistic follow-up of metabolomic analysis is weak. To strengthen this area, the authors should examine whether protein absorption is altered  and whether 3) Linking 5HT2A receptor to the regulation by the choice diet has added mechanistic insight, which needs to be strengthened by provide sufficient rationale for its selection. Are there other receptors screened? Did any additional receptors exhibit potential interactions?4) There are many changes in the metabolomic data. What is the rationale for focusing on the TCA cycle intermediates? In addition, all metabolomic data (with statistics) should be shown without cherry-picking.5) Statistics should be provided to Figure 2F and G.6) Method description should be revised, including nutrient consumption , Smurf assay for intestinal integrity (adding the missing reference), behavioral analysis .7) Additional discussion should be included to address sex specificity and genetic background difference.Reviewer #1:Lyu et al., present a study in which the main claim is that the choice of different nutrients itself modulates behavior, metabolism and lifespan, rather than AMOUNT of nutrients themselves. The implication of this is that caloric restriction is only one means to modulate metabolism and lifespan; food choice is another. As such, this is an interesting idea. However, several major concerns (see points below) made it unclear whether the observed effects were a true reflection of choice, or of increased sugar consumption. Further, choice of 5HT2A receptor for further study was not seen as a substantial advance, given what is already known. Finally, it was unclear from the data analysis/presentation of the metabolomic data whether TCA cycle changes were the true driver of the observed effects.1) In Figure 1, do they have a measure of how much time the flies spend on each nutrient source in the choice diet? Without this, how do you know the flies are actually making a choice? The whole phenotype/effect could be explained by flies dwelling mostly on the sugary food (which they prefer), which the authors have shown to reduce lifespan.2) Although the authors show in Figure 1 that intestinal integrity and climbing ability are not compromised in a 2-week period on the choice diet, it would be important to show that these measures are not more compromised than the fixed diet in older flies that have been on the choice diet for longer: 10, 20 and 30 days to assess the true effect of CD-based reduced lifespan.3) Are the differences in Figure 2F and G significant? No statistics are provided and the data do not look convincing; correspondingly the conclusion that the diet-dependent changes in locomotion are not causal to changes in lifespan does not seem warranted.4) The rationale for choosing 5HT2A mutants is presented as having reduced protein preference in starved female flies, and increased lifespan under dietary choice. However, it is possible that the effects they observe in the present study are an aspect of the same observation (see point 1).5) In Figure 3, it is important to show all the PCA data in graphic format, not just those that differed amongst the various conditions.6) Many metabolites were altered in the different conditions . What is the rationale for choosing to focus on the TCA cycle intermediates? It appears that there are broader changes to amino acid metabolism. Also, fold changes are not mentioned and cutoffs not given.Reviewer #2:eLife . The concept of nutritional choice impacting organismal physiology and longevity is very interesting.This is an interesting extension of previous work from the Pletcher lab, published in The challenge, of course, is to provide irrefutable evidence that it is the “choice” that causes the observed physiological changes. On the whole, the authors have done an admirable job to exclude potential confounding factors. I have, however, some remaining concerns/suggestions for alternative explanations.I am happy to leave it to the authors as to whether to attempt to address these concerns with additional experiments and/or to discuss in the manuscript.Figure 1:The entire premise of the paper assumes that the observed effects are “largely independent of nutrients consumed”. Technically, the authors have done a very good job, when focusing on nutrient consumption.However, there could be more to this than just food consumption.Is it possible/likely that on the choice diet the flies are absorbing more yeast/protein? Isn't the Figure 1H data consistent with this?i.e. When the macronutrients are provided separately, are there are differences in absorption?In the fixed diet, sugar and yeast are always consumed together.Is consuming yeast without sugar, even for short periods, detrimental to longevity because of “elevated protein uptake”?My (limited) understanding of human nutrition is that it really matters which ingredients are paired together in terms of health benefits, e.g. pairing tomatoes with olive oil.Another potential issue, that given the lab's history is particularly relevant, is the issue of olfaction.Could the smell of yeast be more pronounced when provided separately? If so, could this be a confounding factor?Two suggestions to investigate this hypothesis:1) Assay fecundity, which is linked to protein intake in flies in choice vs. fixed diet2) Assay TOR signaling which is also linked to protein intake3) Examine olfactory mutants (smell blind)If the authors could demonstrate no difference in these parameters, it would strengthen the claims of the paper.Figure 2:1118w really an appropriate control? Precise P element revertant?Figure 2A-E is Canton S in Figure 1, 1118w in Figure 2 and the RNAi strain in Figure 5. In this case , the effects of the choice diet appear to be modest.Not surprisingly, different genotypes appear to have varying degrees of reduced longevity in response to the “choice food”. I.e. 5-HT2A mutants are short-lived on the fixed diet?Can the authors speculate as to why the The metabolic data presented  are interesting, but, there is little in terms of mechanistic understanding provided.It is interesting that amino acid metabolism is upregulated in response to the choice diet. Again, as outlined above, couldn't this reflect elevated protein intake?GDH RNAi experiment is very interesting, but, there appears to be little follow up and/or validation. Some suggestions to validate and/or strengthen the claims:The – Validate that the RNAi line works “as advertised”.GDH RNAi flies also eat more under the choice diet? This would strengthen the claims.– Do – Does neuronal RNAi also alter the response?Reviewer #3:eLife and I am highly supportive of its acceptance for publication.This is an important contribution to the field of aging, nutrition and neuroscience. It will be of great interest to the general scientific audience of Drosophila melanogaster. The authors provide compelling evidence to demonstrate that such effects are independent of the amount of nutrients consumed and that neuronal expression of the serotonin receptor 5-HT2A is required for metabolic changes induced by dietary choice, which include upregulation of the TCA cycle and amino acid metabolism. Based on global metabolic data they identify and show that one key enzyme in these processes (Glutamate Dehydrogenase) is causal in the effect of diet choice in lifespan.In this manuscript, Lyu et al. report that it is how nutrients are presented, or the way that they are eaten, which modulates aging and physiology in the fruit fly, The results are intriguing and, together with previously presented data related to the role of 5-HT2A for evaluating protein demand, these discoveries demonstrate that nutrient assessment per se, and/or the feeding choices that result, have significant biological impact on aging. The effects of dietary calories and composition on aging are well-known and highly studied, and it seems reasonable to consider that specific characteristics of each meal, such as the ways in which they are presented (perhaps involving sensory perception) or the pattern in which nutrients are consumed, are important as well. These mechanisms may also be relevant to understanding the effects of different types of fasting/feeding regimes that have experienced a resurgence of interest in research  and in the general public.The data presented in Lyu et al. are extensive, and the authors do an outstanding job of disentangling the confounding effects of behavior, feeding, and lifespan, from dietary presentation. Most importantly, the authors have provide convincing evidence that changes in lifespan in flies given a choice diet are not caused solely by a change in nutrient intake . They make the extraordinary observation that at least for flies and likely many other organisms, there something of great interest occurring in making choices in the environment that is outside of the standard foci of calories or amount consumed. The support for 5-HT2A receptor in this process is absolutely solid, as is the link to specific metabolic changes through metabolic analysis and genetic manipulation. These are all major strengths of the manuscript. The authors speculate that the psychological effect of choice or the act of decision making itself may somehow be costly, and it is these assertions that while perhaps less-well supported, nonetheless follow from their work and are well appropriate for speculation given their strong data. Essential revisions:1) The key claim that the observed changes are due to nutritional choice requires additional experiments.a) When macronutrients are provided separately, there might be difference in consumption and absorption, contributing to the observed phenotypes. The authors have assayed consumption, showing flies consuming more sugar and the same amount of yeast on the choice diet. But the change in absorption has not been ruled out. The authors should determine whether consumption and/or absorption of each nutrient is altered in the choice diet when compared to mixed diet and perform this comparison in young and middle-aged files. For example, assessment of fecundity and mTOR signaling will help find possible changes in protein intake.We appreciate that reviewers bring up this idea that the process of nutrient integration is complex, it happens at multiple levels and can be regulated by the characteristics of a diet. Here, and in the revised manuscript, we hope to assuage the concern about nutrient absorption by adding the fecundity and TOR data per reviewer’s requests. Indeed, neither these two measures indicate effects of dietary choice. In addition, we highlight the weight and total protein data  to discuss the involvement of protein intake. Together, these data support the interpretation that differences in protein intake/absorption is not the cause of lifespan effects of a choice diet.“Although protein intake was not different in flies fed different diets, it seemed possible that dietary choice improved protein absorption, which might be important considering the influential role of this macronutrient in reducing lifespan . […] Furthermore, molecular and physiological markers that are strongly affected by protein availability, including mTOR activity  and female fecundity  were not altered by dietary choice .”The process and effects of sugar absorption are, however, less clear than that of protein. While of interest, we believe that they are beyond the current scope of the manuscript considering the evidence that lifespan is distinct from molecular and physiological mechanisms of sugar effects, whether they be due to differences in sugar consumption or absorption.b) The olfactory perception of yeast can be different between the choice diet and the mixed diet. The previous finding from the lab has revealed the importance of yeast smell on fly lifespan. To rule out the smell of yeast as a confounding factor, the olfactory mutants that are smell blind should be subject to the choice diet.Our current, ongoing experiment establishes that olfactory-deficient mutants exhibit pronounced lifespan effects of a choice effects, excluding the involvement of yeast smell as a confounding factor. We will be happy to provide the data in the final version if the editors and reviewers feel this is an essential component of this study.GDH RNAi flies eat more under the choice diet.2) The mechanistic follow-up of metabolomic analysis is weak. To strengthen this area, the authors should examine whether protein absorption is altered  and whether GDH knockdown. Neither feeding nor total protein in the fly was affected by GDH knock-down. We revised the text as follows:In addition to new information about protein absorption (see above point 1a), we have provided new data on the effects of GDH knockdown had no effect on nutrient consumption  nor total protein abundance in the fly . Which tissues/cells are critical for the diet-specific lifespan effects that induced by GDH knockdown, and whether such influences are due to changes in “3) Linking 5HT2A receptor to the regulation by the choice diet has added mechanistic insight, which needs to be strengthened by provide sufficient rationale for its selection. Are there other receptors screened? Did any additional receptors exhibit potential interactions?Our choice of the 5-HT2A receptor was based on earlier studies that identified this receptor as a modulator of protein reward and originally documented diet-specific effects on lifespan . Our goal in the manuscript was to expand our understanding of the behavioral, physiological and aging effects of the choice diet, to determine the extent to which this effect was present in males, and to study the underlying mechanisms at play in this pathway. Loss of function in other serotonin receptors had no influence on protein preference , however it remains to be tested whether they might influence the aging processes in a choice environment through unknown mechanisms. We have revised text to the manuscript that clarifies this:“Previously we hypothesized that neuronal mechanisms involved in nutrient evaluation might influence lifespan when macronutrients are presented separately . […] Here we focused on the elucidating the mechanisms underlying the effects of the 5-HT2A receptor and expanded our analysis of its effects on dietary choice and male lifespan.”4) There are many changes in the metabolomic data. What is the rationale for focusing on the TCA cycle intermediates? In addition, all metabolomic data (with statistics) should be shown without cherry-picking.We now include the statistics for all metabolites in the new Supplementary file 3. The rationale for investigating the TCA cycle has been added to the manuscript:“Furthermore, MetaboAnalystR identified related pathways, involving the synthesis of aminoacyl-tRNAs or specific amino acids, which were found either in both tissues or only in the body . […] A closer look into its metabolic map (KEGG ID: map00250) revealed that candidate metabolites are either members of the TCA cycle or are the direct precursors of TCA metabolites, which indicated the modulation of this metabolic process in response to dietary choice.”5) Statistics should be provided to Figure 2F and G.These statistics were provided in the original manuscript, but we realize the difficulty in identifying them. They are now highlighted in pink boxes.6) Method description should be revised, including nutrient consumption , Smurf assay for intestinal integrity (adding the missing reference), behavioral analysis .We have revised the Materials and methods accordingly for nutrient consumption, Smurf assay and for behavioral analysis, and the missing reference has been added now.7) Additional discussion should be included to address sex specificity and genetic background difference.We appreciated the general genetics context that the reviewer provided with us. A new paragraph that focuses on sexual dimorphism and genetic background has now been added in the Discussion:“We found that dietary choice influenced lifespan in both male and female laboratory flies and that 5-HT2A is required for this effect in both sexes , suggesting the mechanisms are at least partially shared between them. […] Future studies that focus on dissecting the role of individual macronutrients in the choice effects or on investigating the involvement of sex-specific nutrient sensing proteins , perhaps with a focus on population genetics of natural populations, will be useful for understanding the nature of sexual dimorphism on lifespan and physiology.”Reviewer #1:Lyu et al., present a study in which the main claim is that the choice of different nutrients itself modulates behavior, metabolism and lifespan, rather than AMOUNT of nutrients themselves. The implication of this is that caloric restriction is only one means to modulate metabolism and lifespan; food choice is another. As such, this is an interesting idea. However, several major concerns (see points below) made it unclear whether the observed effects were a true reflection of choice, or of increased sugar consumption. Further, choice of 5HT2A receptor for further study was not seen as a substantial advance, given what is already known. Finally, it was unclear from the data analysis/presentation of the metabolomic data whether TCA cycle changes were the true driver of the observed effects.1) In Figure 1, do they have a measure of how much time the flies spend on each nutrient source in the choice diet? Without this, how do you know the flies are actually making a choice? The whole phenotype/effect could be explained by flies dwelling mostly on the sugary food (which they prefer), which the authors have shown to reduce lifespan.Our positional preference data were shown in Figure 2E, where we observed that flies (both controls and mutants) spend most of their time on the protein side. Furthermore, the positional preference is 5-HT2A-independent and therefore does not link mechanistically with the lifespan effects.2) Although the authors show in Figure 1 that intestinal integrity and climbing ability are not compromised in a 2-week period on the choice diet, it would be important to show that these measures are not more compromised than the fixed diet in older flies that have been on the choice diet for longer: 10, 20 and 30 days to assess the true effect of CD-based reduced lifespan.It is unclear to us what hypotheses the reviewer is seeking to distinguish. We specifically used these two assays  to directly test whether the choice diet induces acute effects on general health. In our opinion, effects on long term health are more difficult to determine because inference of this sort would be directly confounded by known differences in the rates of aging between diets.3) Are the differences in Figure 2F and G significant? No statistics are provided and the data do not look convincing; correspondingly the conclusion that the diet-dependent changes in locomotion are not causal to changes in lifespan does not seem warranted.P-values from a two-way ANOVA were originally presented above each panel. Recognizing the complexity of this figure, however, we have now highlighted the values in pink boxes.The relevant 5HT2A mutants is presented as having reduced protein preference in starved female flies, and increased lifespan under dietary choice. However, it is possible that the effects they observe in the present study are an aspect of the same observation (see point 1).4) The rationale for choosing Contrary to our previously published work in which flies were purposefully starved, we find no evidence that flies fed a choice diet are starved or nutrient (protein) deprived: they spend most of their time on the yeast food (see response to point #1 above); they exhibit normal levels of egg production and TOR signaling; and they are of normal weight. It is possible that mechanisms of nutrient perception or that cell-nonautonomous effects of perceived protein reward underlie the mechanisms through which lifespan is affected, and if so, that would be a significant advance. Similarly, we document 5-HT2A-dependent metabolic changes in response to dietary choice, among which αKG seems to be causal for effects on lifespan. Whether neuronal and perception effects are common to both phenomena remain to be determined, but either way, in our opinion the data presented in this manuscript highlight new mechanisms of aging.5) In Figure 3, it is important to show all the PCA data in graphic format, not just those that differed amongst the various conditions.The clustering patterns of major PC combinations  or 87% (in body) of the total variance), as well as the proportion of variance for each PC, have been added as Figure 3—figure supplement 1 (for head data) and Figure 3—figure supplement 2 (for body data).6) Many metabolites were altered in the different conditions . What is the rationale for choosing to focus on the TCA cycle intermediates? It appears that there are broader changes to amino acid metabolism. Also, fold changes are not mentioned and cutoffs not given.P-values, not fold-changes as cut-offs:We have added detailed statistics for each metabolite in Supplementary file 3. The full datasets and analyses can also be accessed from GitHub (github.com/ylyu-fly/Metabolomics-FlyChoiceDiet). As noted in the main text, we used PDiet < 0.05) and a non-significant diet x genotype interaction (PDiet * Genotype > 0.05).”“Criteria for inclusion in Group A consisted of a statistically significant effect of diet (PDiet * Genotype ≤ 0.05).”“We identified 18 out of 103 total metabolites in the head and 19 out of 125 total metabolites in the body that were present in this group . The concept of nutritional choice impacting organismal physiology and longevity is very interesting.The challenge, of course, is to provide irrefutable evidence that it is the “choice” that causes the observed physiological changes. On the whole, the authors have done an admirable job to exclude potential confounding factors. I have, however, some remaining concerns/suggestions for alternative explanations.I am happy to leave it to the authors as to whether to attempt to address these concerns with additional experiments and/or to discuss in the manuscript.Figure 1:The entire premise of the paper assumes that the observed effects are “largely independent of nutrients consumed”. Technically, the authors have done a very good job, when focusing on nutrient consumption.However, there could be more to this than just food consumption.Is it possible/likely that on the choice diet the flies are absorbing more yeast/protein? Isn't the Figure 1H data consistent with this?i.e. When the macronutrients are provided separately, are there are differences in absorption?In the fixed diet, sugar and yeast are always consumed together.Is consuming yeast without sugar, even for short periods, detrimental to longevity because of “elevated protein uptake”?My (limited) understanding of human nutrition is that it really matters which ingredients are paired together in terms of health benefits, e.g. pairing tomatoes with olive oil.Another potential issue, that given the lab's history is particularly relevant, is the issue of olfaction.Could the smell of yeast be more pronounced when provided separately? If so, could this be a confounding factor?Two suggestions to investigate this hypothesis:1) Assay fecundity, which is linked to protein intake in flies in choice vs. fixed diet2) Assay TOR signaling which is also linked to protein intake3) Examine olfactory mutants (smell blind)If the authors could demonstrate no difference in these parameters, it would strengthen the claims of the paper.We appreciate the insights and critiques provided by this reviewer, particularly those focused on protein sensing and absorption in the dietary choice effects, as we recognize that many uncharacterized features of diets may modulate aging. We have worked hard during difficult times in the lab to add data from new experiments that address these issues in the revised manuscript:a) Specifically, three new experiments provide insight into the point about the possibility of diet-dependent protein absorption. Briefly, we measured fecundity and TOR activity (based on phosphorylation status of S6K) and neither measure indicated an effect of dietary choice. Furthermore, total protein in the fly was also not affected by protein choice (nor was weight), which also indicates that, given similar amounts of protein intake, protein absorption/utilization is not different between diets. The manuscript has been revised accordingly (Results).b) This reviewer raised an interesting point that the choice effects could be the result of “pairing” different nutrients/foods. We find this (and other effects of patterning in feeding) to be very intriguing, and to our knowledge, it is largely unknown how flies adjust feeding behaviors in complex environments . We believe that the choice diet paradigm (and modifications to it) provides an excellent opportunity to investigate such mechanisms in the future. For now, we are happy to include this possibility in the Discussion, as show below:“Flies housed in a choice environment, for example, are allowed to interact with each macronutrient individually, and this behavior would be expected to result in the sequential activation of sugar and protein sensing pathways. […] The perceived flavor of each macronutrient may be different when yeast and sugar are consumed separately compared to when they are paired together on a fixed diet , and that may also influence lifespan and metabolism .”c) We agree that this would be a good experiment test the role of sensory perception in dietary choice effects. While the characterization of sensory requirements is complex and is well beyond the focus of a single manuscript , our current ongoing experiments clearly indicate that it is not simply a more odorant rich environment that is reducing lifespan upon dietary choice. This experiment is on-going, although the results are clear . We willFigure 2:1118 really an appropriate control? Precise P element revertant?Figure 2A-E is w5-HT2A mutants  together with background-independent RNAi. Precise excision (together with backcrossing) is also a reasonable approach, which we chose not to pursue. The primary reason for this is the potential for unintended genetic effects of excision and the time and effort required to achieve it. We felt the two manipulations described above provided strong inference.We appreciate and recognize the importance of controlling for background effects. We chose in this instance to use extensive backcrossing of Canton-S in Figure 1, 1118w in Figure 2 and the RNAi strain in Figure 5. In this case , the effects of the choice diet appear to be modest.Not surprisingly, different genotypes appear to have varying degrees of reduced longevity in response to the “choice food”. I.e. We acknowledged the observations on the effects of genetic background, where we added a new paragraph in the Discussion on this topic.5-HT2A mutants are short-lived on the fixed diet?Can the authors speculate as to why the Drosophila to name a few, 5-HT2A is involved in circadian rhythms , walking , feeding , and sensory perception of dead conspecifics . All of these effects could potentially contribute to its lifespan effect on a fixed diet. We have added some discussion of this to the revision.A challenge here is that serotonin signaling has many pleotropic effects, although the extent to which some/all are 5-HT2A dependent is unclear. In “Mutant flies were modestly short-lived on the standard, fixed diet, which is likely due to the pleotropic effects of this receptor .”The metabolic data presented  are interesting, but, there is little in terms of mechanistic understanding provided.It is interesting that amino acid metabolism is upregulated in response to the choice diet. Again, as outlined above, couldn't this reflect elevated protein intake?As related to our responses to the point #1, there is no evidence showing that flies on a choice diet have elevated protein intake. The upregulation of amino acid metabolism therefore seems to reflect differences in the way that a fixed amount of amino acids are metabolized .GDH RNAi experiment is very interesting, but, there appears to be little follow up and/or validation. Some suggestions to validate and/or strengthen the claims:The – Validate that the RNAi line works “as advertised”.GDH transcript amount, indicating that either partial knock-down is sufficient to influence lifespan or that the RNAi may function at post-transcriptional levels. We interpret this as implying that this particular pathway is subject to complex regulatory mechanisms . Indeed, our results simply provide one direction forward in identifying specific molecules that are responsible for the aging effect, which we believe is a significant advance. Given the difficulty of laboratory work, we would argue that detailed molecular analyses of multiple components of this pathway are beyond the scope of the current contribution.qPCR data reveal variable knockdown (up to 20% decrease) in GDH RNAi flies also eat more under the choice diet? This would strengthen the claims.– Do GDH RNAi flies. In short, no, neither of these factors seems to contribute to the lifespan effects. Please see our revised text below:We have provided new data on the food intake and protein absorption of GDH knockdown had no effect on nutrient consumption  nor total protein abundance in the fly .”“– Does neuronal RNAi also alter the response?GDH knockdown, but respectively argue that such experiments are best addressed in a follow-up manuscript . Nevertheless, the relevance of this point is now addressed in the revision:We are interested in testing the tissue requirement of GDH knockdown, and whether such influences are due to changes in “Which tissues/cells are critical for the diet-specific lifespan effects that induced by