Chelonoidis duncanensis; n = 25 and 149 individuals, respectively) endemic to a single island in the Galapagos. Pinzón giant tortoises had a historically large population size that was reduced to just 150–200 individuals in the mid 20th century. Since then, Pinzón's tortoise population has recovered through an ex situ head‐start programme in which eggs or pre‐emergent individuals were collected from natural nests on the island, reared ex situ in captivity until they were 4–5 years old and subsequently repatriated. We found that the extent and distribution of genetic variation in the historical and contemporary samples were very similar, with the latter group not exhibiting the characteristic genetic patterns of recent population decline. No population structure was detected either spatially or temporally. We estimated an effective population size (Ne) of 58 (95% CI = 50–69) for the postbottleneck population; no prebottleneck Ne point estimate was attainable (95% CI = 39–infinity) likely due to the sample size being lower than the true Ne. Overall, the historical sample provided a valuable benchmark for evaluating the head‐start captive breeding programme, revealing high retention of genetic variation and no skew in representation despite the documented bottleneck event. Moreover, this work demonstrates the effectiveness of head‐starting in rescuing the Pinzón giant tortoise from almost certain extinction.Population genetic theory related to the consequences of rapid population decline is well‐developed, but there are very few empirical studies where sampling was conducted before and after a known bottleneck event. Such knowledge is of particular importance for species restoration, given links between genetic diversity and the probability of long‐term persistence. To directly evaluate the relationship between current genetic diversity and past demographic events, we collected genome‐wide single nucleotide polymorphism data from prebottleneck historical (c.1906) and postbottleneck contemporary (c.2014) samples of Pinzón giant tortoises ( We then used this SNP data set to directly investigate changes in genome‐wide diversity over time. Additionally, given that the majority of the tortoises in the contemporary sample are the product of the head‐start programme, we evaluated the degree to which genetic variation has been impacted by this conservation intervention.22.12.1.1Blood samples from 150 individuals  and large  data sets to assess the impact of the number of loci on the results.We used the genotypic data to calculate standard measures of within‐population genetic diversity for the contemporary and historical samples separately, including heterozygosity and Ne) of the contemporary and historical sample groups were calculated using the bias‐corrected measure of linkage disequilibrium  cut‐off of 0.05 and viewed the results in R.Effective population sizes  from one to four, with ten iterations of each. The most likely number of clusters was determined by plotting the log probability of the data (ln Pr(X|K)) across the range of K values tested and selecting the K where the value of ln Pr(X|K) plateaued, as suggested in the STRUCTURE manual.The evidence for substructure within the combined sample  was assessed using Bayesian clustering analysis, as implemented in STRUCTURE 2.3.4 . The chosen value of K was based on the minimum number of clusters after which the BIC decreased by a negligible amount.We also used the model‐free discriminant analysis of principal components . The age classes were “adult” samples, those with a curved carapace length >65 cm (n = 82), and “young” samples, those with carapace lengths <35 cm and >15 cm (n = 29). Individuals <15 cm were excluded because they are wild‐born hatchlings that were not part of the head‐start programme. Admittedly, these age classes are somewhat arbitrary, but were chosen to represent nonoverlapping segments of the contemporary sample group that was head‐started either in the early years of the programme (“adults”) or very recently (“young”). This grouping allowed comparisons of levels of diversity within each time point and of the patterns of pairwise relatedness within and among the two temporal sample groups.To assess whether there were differences in the genetic diversity captured in the head‐start programme over time, we used carapace size as a proxy for age of sampled individuals in order to divide samples from the contemporary sample group into two age classes and repeated the calculation of diversity metrics  were used in this analysis to exclude recently repatriated cohorts that have not yet had time to disperse away from the release sites  representatively sampled from across the island to identify polymorphic SNPs and flanking sequences that could be used to design targeted capture baits for use with the historical samples (collected c.1906). The details of the sequencing output and processing resulting from the RAD‐seq and captures can be found in the Supporting Information Supplementary Results in Appendix Our data set for population genetic analysis consisted of 2,218 SNP loci, genotyped in 25 historical and 149 contemporary individuals . Simulations using subsets of different sample sizes indicated that sample sizes <30 often have very broad jackknife confidence intervals  or more recent head‐start cohorts (“young”). Heterozygosity was slightly higher, and measures of inbreeding, up Table . Mean reup Table , with laup Table b. All Phow Table . There wow Table . These row Table .44.1PhiST values  endemic to Volcano Alcedo on Isabela Island, which revealed distinctive signatures of a population bottleneck   precluded accurately estimating Ne  based on microsatellite genotypic data for 24 individuals  of 536 based on the Frankham (Ne = 0.11 Nc), which more closely approximates the number of different individuals that were encountered (n = 420) during a population survey conducted concurrently with our sample collection in 2014.Population genetic theory predicts a decrease in e Table . Our sime Figure . This coe Figure , who fouFrankham  ratio (NGIS, not significantly different from zero (Table One persistent pattern found in all previous studies of Pinzón giant tortoises using microsatellites has been heterozygote deficit relative to Hardy–Weinberg expectations and significantly positive inbreeding coefficients (Beheregaray, Ciofi, Caccone, Gibbs, & Powell, ro Table . These pro Table . At leasro Table . Althougro Table , moving ro Table , should 4.2The demographic recovery of the Pinzón giant tortoise species was achieved via a head‐start programme. However, this action carried the possibility of skewing genetic contributions to subsequent generations due to unequal representation of the surviving individuals. Even if all 150–200 adults on the island immediately following the bottleneck (MacFarland et al., PhiST value (Table In the current study, we were able to more fully assess how successful the head‐start programme has been in maintaining the extent and distribution of genetic diversity by calculating pairwise relatedness among individuals in the contemporary and historical samples and comparing the distributions of relatedness values. As individuals in the historical sample were naturally reproducing, they serve as a benchmark for the typical distribution of relatedness prior to the bottleneck and establishment of the head‐start programme. We found that the distribution of pairwise relatedness in the contemporary sample matched the distribution for the historical sample Figure a, indicaue Table . These pue Table , suggest4.3C. duncanensis maintains higher levels of genetic variation, particularly in the mitochondrial genome, than most of the other extant species, despite having gone through a substantial bottleneck (MacFarland et al., In this study, we had the benefit of historical samples to provide context for interpreting levels of diversity observed in the contemporary population. Prebottleneck sampling of multiple individuals is unavailable for most species of conservation concern, and so indirect estimates of the severity and genetic impacts of bottlenecks must be relied upon. In some cases, the bottlenecked population can be compared to a stable population of the same species (Whitehouse & Harley, Although the study design used here provides unique insights, methods for collecting and analysing population genomic data from historical specimens, in the context of a temporal study, are still maturing. In Appendix 5Over the past several decades, considerable attention has been given to documenting the genetic consequences of population declines (Frankham, None declared.https://doi.org/10.5061/dryad.7tp3sg0.The data sets generated in this manuscript are available from the Dryad Digital Repository:  Click here for additional data file. Click here for additional data file. Click here for additional data file.


The 2011 Tohoku earthquake drastically changed human activities in some regions of Fukushima Prefecture, Japan. The subsequent tsunami damage and radioactive pollution from the Fukushima Daiichi nuclear power plant resulted in the evacuation of humans, and abandonment of agricultural lands, allowing population expansion of wildlife into areas formally inhabited by domesticated livestock. Unintentional escape of domesticated pigs into wildlife inhabited environments also occurred. In this study, we tested the possibility of introgression between wild boar and domesticated pigs in Fukushima and neighboring prefectures. We analyzed mitochondrial DNA sequences of 338 wild boar collected from populations in the Tohoku region between 2006 and 2018. Although most boar exhibited Asian boar mitochondrial haplotypes, 18 boar, phenotypically identified as wild boar, had a European domesticated pig haplotype. Frequencies of this haplotype have remained stable since first detection in 2015. This result infers ongoing genetic pollution in wild boar populations from released domesticated pigs. In 2018, this haplotype was detected outside of evacuated areas, suggesting migration and successful adaptation. The natural and anthropocentric disasters at Fukushima gave us the rare opportunity to study introgression processes of domestic genes into populations of wild boar. The present findings suggest a need for additional genetic monitoring to document the dispersal of domestic genes within wild boar stock. The removal of humans and associated rewilding of nature allows exchange of individuals from different populations, resulting in positive attributes such as increased gene flow, abundant wildlife populations, mitigation of inbreeding and enhanced viability of wildlife populations3. However, there is also the potential hybridization or introgression of escaped domesticated livestock with wildlife4. Research of genetic contamination through introgression of released domesticated animals has been reported in multiple mammal populations6. Genetic contamination is a threat to natural biodiversity and needs to be monitored to help prevent future genetic contamination in mammal populations9.The 2011 Tohoku earthquake, tsunami, and nuclear accidents in Fukushima Prefecture, Japan, drastically changed human activities in areas close to the disaster sites. Humans were required to evacuate a 20-km radius around the Fukushima Daiichi Nuclear Power Plant (FDNPP) and this altered some 650 kmSus scrofa), which are widely distributed geographically including large areas in Asia, Europe, and North Africa12, are known to reproduce with their domestic relative13. Due to little reproductive isolation between pig and boar, the introgression of introduced pigs into wild boar populations may alter genetic components of local wild boar populations14. Potential introgression occurred following the FDNPP accident when some of an estimated 31,500 domesticated pigs left behind in the evacuation zone escaped into the wild15. This dispersal of released pigs into nearby environments may have long term ecological consequences by altering traits like reproduction rate or immunology of current wild boar populations17. Thus, there is a need to monitor potential hybridization within wild boar subpopulations within and nearby the evacuated areas  of Tohoku, Japan.Wild boar  of wild boar in Fukushima, Yamagata, and Miyagi Prefectures with the aims to: (1) study possible changes in mtDNA genetic composition of wild boar following the FDNPP disaster, and (2) determine if the frequency of escaped domestic pig mtDNA occurrence in wild boar populations is stable, increasing or declining within Fukushima’s evacuated zones or neighboring Prefectures.21. The frequencies of individuals observed in haplotypes J10, J3, and J5 were 319 (92%), 5 (1.4%), and 3 (1.0%), respectively. All J3 individuals were detected within evacuation zones in 2015. J5 individuals were detected outside of evacuation areas in 2009, 2016 and 2017.Comparative analyses among 338 sequences 713-bp) were obtained in the Tohoku region, which revealed transitional substitutions at 21 nucleotide substitution sites. Nucleotide variation of Japanese wild boar and domestic pig haplotypes are provided in Table 3-bp wereThe observed frequency of domestic pig haplotype H1) was 5.3%  amongst all samples. Haplotype network analysis suggests these 18 individuals were of European domesticated pigs, and thus H1 haplotypes were identified as a lineage that has at least one female ancestor of European domestic pigs  suggesting higher genetic diversity than that of the 338 wild boar samples obtained for this study. One such pig sample’s haplotype was identical to that of H1, further suggesting that H1 boar has a domestic pig ancestor in their maternal lineage. Additionally, alignment with GenBank sequences showed two domestic pig sample sequences (P5 and P6) had mtDNA sequences similar to those found in wild boar populations , a result similar to what was found in Ibaraki Prefecture, Fukushima’s southern neighbor21, where the study’s population was 100% J10. Dominance of J10 haplotype in nearby areas suggest a strong similarity of genetic diversity and are most likely due to a stochastic effect within these areas of Japan.Genetic diversity for wild boar from this area of the Tohoku region  was analogous to that of wild boar in other regions of Japan26 and detection of hybridization between wild boar populations with released domestic pigs has occurred in numerous regions outside and within Japan28. Data presented here show genetic introgression from European domestic pigs into Japanese wild boar populations, which suggests the occurrence of hybridization. The 18 observed identical domestic pig mtDNA haplotypes in these individuals support a scenario of introgression from domestic pig lineages into the wild. Additionally, one mtDNA haplotype from a pig sample collected from a Fukushima slaughterhouse was identical to that found in released domesticated pigs (H1). Therefore, genetic introgression in this region could be a direct result from abandoned agriculture lands and the unintentional release of domestic pigs following the FDNPP accident. Release of domestic livestock is an inevitable consequence following a natural disaster, therefore management actions to monitor hybridization and introgression of these populations over time should be considered to understand their impact on wildlife populations.Wild animal hybridization is a matter of worldwide attention32. Our findings are in contrast to these previous studies. There may be specific factors in the Fukushima area preventing other domestic pig lineages from surviving, such as a difficulty of colonization within the local environment and/or severe competition from native wild boar9.Only a single haplotype was detected for escaped domesticated pigs and the mtDNA sequences obtained from ten pig samples showed genetic variation Table , which i16. Detection of H1haplotype has remained stable within the evacuation areas since 2015 . If offspring of crossbred domesticated pigs and wild boar are spreading to other areas, continued monitoring of crossbred individuals will provide more knowledge on their migration patterns and dispersal into other regions.Introgression and spread of released domesticated pigs can alter the genetic population structure of native wild boarOur results suggest that uncontrolled dispersal of released domestic pig populations, and consequences of drastic evironmental changes , is leading to introgressive hybridization of local natural wild boar populations. However, mtDNA data can only infer about female lineages . Thus, our study may be underestimating the introgression or possibility of hybrid occurrences. Our findings suggest the need for microsatellite marker genetic analyses to obtain more complete information on genetic hybrids, and to better understand the consequences of escaped domesticated livestock. Additionally, future genetic studies could provide data on migration patterns and the rare opportunity to better understand invasive introgression processes of domestic gene influx into wild populations following a large-scale disaster.Bicep femoris) samples were collected from 338 Japanese wild boar captured in multiple municipalities within Tohoku, Japan  from 2006 to 2018  and date were recorded and are provided in supplemental information. No animals were killed specifically for this research. All animals were legally culled by licensed hunters, and this entire study was approved by Fukushima University’s Institutional Animal Care and Use Committee. All experiments were performed in accordance with relevant guidelines and regulations.Muscle tissue  in L strand of threonine tRNA and mitH106 (5′-ACGTGTACGCACGTGTACGC-3′) in the H strand of the control region were used to amplify the mitDNA as described by Watanobe et al. 1999. PCR amplification was done in an 8 μl reaction mixture containing 2 to 30 ng of extracted DNA, 4 μL of QIAGEN Multiplex PCR Master Mix, and 0.2 μL of each 10 μM primer. Thermal cycling conditions used in T100 thermal cycler  included: initial DNA denaturation at 95 °C for 15 min, heat denaturation at 94 °C for 30 sec, annealing at 60 °C for 1 min 30 sec, extension reaction at 72 °C for 1 min. The cycle was repeated 30 times followed by the final extension at 60 °C for 30 min. The amplified DNA fragments were subjected to electrophoresis on a 1.5% agarose gel and later purified. Amplified PCR products were purified using illustra ExoStar . Sequence reaction was performed on the purified product with ABI BigDye Terminator Cycle Sequencing Kit ver. 3.1 (Applied Biosystems). As described in Watanobe et al. 2003, additional primers mitL120 (5′-ACCGCCATTAGATCACGAGAC-3′) and mitH124 (5′-ATGGCTGAGTCCAAGCATCC-3′) were added for DNA sequencing of the mtDNA control region. The nucleotide sequence was determined with ABI PRISM 3130 Genetic Analyzer (Applied Biosystems).Total genomic DNA was extracted using Gentra Puregene Tissue Kit (QIAGEN), according to manufacturer’s instructions. Approximately 1 μl of extracted DNA was used to amplify the base sequence control region by polymerase chain reaction (PCR) as described by Watanobe 34 with gaps treated as missing data  were identified.The mtDNA control region of 338 samples were successfully amplified using PCR with primer pair L3/H106 or L120/H124. Using PCR product-direct sequencing with each of four internal primers , partial sequences (713-bp) were determined from all samples. DNA sequencing data was viewed from FinchTV chromatogram viewer version 1.5.0 (Geospiza Inc.). Based on aligned sequences, a parsimony network of all haplotypes was created using results from TCS 1.21Due to the possible environmental impact on wild boar populations within evacuated zones following the FDNPP accident, our results of haplotype occurrence were reviewed based on samples before and after the accident Table . AdditioDetected hybrid  DNA sequence has been deposited at GenBank under accession code MK801664.GPS Location and date of samples


Hordeum exo-hydrolase HvExoI isolated from seedlings reveals that non-covalently trapped glucose forms a stable enzyme-product complex. Here, we report that the alkyl β-d-glucoside and methyl 6-thio-β-gentiobioside substrate analogues perfused in crystalline HvExoI bind across the catalytic site after they displace glucose, while methyl 2-thio-β-sophoroside attaches nearby. Structural analyses and multi-scale molecular modelling of nanoscale reactant movements in HvExoI reveal that upon productive binding of incoming substrates, the glucose product modifies its binding patterns and evokes the formation of a transient lateral cavity, which serves as a conduit for glucose departure to allow for the next catalytic round. This path enables substrate-product assisted processive catalysis through multiple hydrolytic events without HvExoI losing contact with oligo- or polymeric substrates. We anticipate that such enzyme plasticity could be prevalent among exo-hydrolases.Substrates associate and products dissociate from enzyme catalytic sites rapidly, which hampers investigations of their trajectories. The high-resolution structure of the native  Enzyme substrates and products often diffuse too rapidly to assess the catalytic implications of these movements. Here, the authors characterise the structural basis of product and substrate diffusion for an exo-hydrolase and discover a substrate-product assisted processive catalytic mechanism. Enzymes use protein architectures to precisely position a set of amino acid residues to catalyse inter-conversions of substrates into products. This structure-based view is supported by thermodynamic and kinetic models that treat enzymes in complex with substrates and transition states in succession3. Only rarely these models consider substrate and product diffusion as a part of their catalytic mechanisms, as these processes proceed rapidly, although on occasions products are seen entrapped in active sites4. Yet, the lack of descriptions of substrate associative and product dissociative pathways creates a knowledge gap5.Enzymes are biological catalysts that are fundamental to life. Enzymes afford enormous accelerations to chemical reactions compared to uncatalysed reactions. It has become increasingly recognised that the largest contribution to the enzyme catalytic power arises from the electrostatic environment of polar active sitesd-glucan glucohydrolase, isoenzyme ExoI (HvExoI) isolated from barley seedlings, was that the glucose (Glc) product released from β-d-glucoside substrates remains entrapped in the enzyme active site until an incoming substrate binds9, presumably lowering the energy barrier to facilitate Glc displacement. At this stage, the mechanism of Glc displacement and how it is linked to the catalytic cycle of HvExoI remained unanswered. Notably, no other native GH3 structures with entrapped Glc are available, because these recombinant enzymes not exposed to presumably high enough Glc concentration, do not entrap Glc during protein maturation and secretion. However, several GH3 enzyme complexes with in crystallo-perfused Glc11 or Glc-derivatives13 are available. Additionally, the native GH78 α-l-rhamnosidase with a deep pocket-shaped active site also holds the entrapped Glc molecule, which was not perfused in crystals14.A vital conclusion drawn from the structural studies with the native β-d-glucoside dislodge Glc from the −1 subsite and form stable cyclitol esters via an α-anomeric linkage with Asp2857. Similarly, transition-state ion-like gluco-phenylimidazole mimics displace Glc and bind in the −1 subsite with their Glc component distorted in the 4E envelope conformation16. Non-hydrolysable S-glycoside analogues also remove Glc from the −1 subsite and bind across the active site17. Because HvExoI hydrolyses various positional isomers of β-d-glucosides, we rationalised this observation by the non-reducing Glc moiety being locked into a fixed position via hydrogen bonds (H-bonds) with the residues in the −1 subsite, whereas the reducing-end moiety is free to adopt multiple orientations in the +1 subsite. This allows the remainder of the saccharide substrates beyond the +1 subsite to project unencumbered17.We have previously observed that mechanism-based inhibitors conduritol B epoxide and 2′,4′-dinitrophenyl 2-deoxy-2-fluoro-β-6 that belongs to the glycoside hydrolase (GH) family 318, serves as one of the archetypal models for hydrolysis of oligo- and polysaccharides. Structural information of GH3 enzymes is available through 36 unique entries in the Protein Data Bank (PDB) from all phyla, although there is only one plant structure available (that of HvExoI), notably in complex with a variety of oligosaccharide substrate analogues and mimics9. HvExoI folds in an (α/β)8 barrel (domain 1) and an (α/β)6 sandwich (domain 2) that at their interface cradle a 13 Å-deep pocket- or crater-shaped active site. This site accommodates the catalytic nucleophile Asp285 and catalytic acid/base Glu491 in the −1 subsite, while the aromatic clamp of Trp286 and Trp434 indole moieties constitutes the neighbouring +1 subsite9. HvExoI releases a single Glc from non-reducing termini of oligo- and polymeric β-d-glucosides to support seed germination and plant development9.The fundamental function of hydrolysis of oligo- and polysaccharides is essential for the understanding of the global carbon cycle, which forms the basis of a multibillion-dollar biotechnological industry. In this context, the HvExoI enzyme19, Molecular dynamics (MD) simulations, Genetic Algorithms with Unrestricted Descriptors for Intuitive Molecular Modelling (GaudiMM)20 and Protein Energy Landscape Exploration (PELE)21 calculations, to reveal the Glc product displacement route, and to extract how each hydrolytic event including Glc release is precisely coordinated with the incoming substrate association and hydrolysis. This leads us to generate a variant enzyme and probe it for Glc entrapment and the S-glycoside analogue binding. Along this journey with HvExoI, we observe a remarkable phenomenon, coin the term ‘substrate-product assisted processive catalysis’, and describe how product and substrate trajectories are coordinated via this mechanism during catalysis. We discover that through chemical signalling, the incoming substrate evokes the formation of an autonomous and transient lateral cavity that serves as a conduit for the Glc product displacement from the active site. Crucially, these co-operative reactant pathways, where polymeric substrates never dissociate from the enzyme, sustain consecutive relocations of substrates and products via dedicated routes, ensuring that this exo-hydrolase adopts processive catalysis.In this work, we examine product and substrate pathways along the catalytic cycle of a plant exo-hydrolase HvExoI, and how this enzyme utilises its plasticity and that of glycoside substrates. We use the high-resolution X-ray crystallography supported with enzyme kinetics, mass spectrometry, nuclear magnetic resonance (NMR) spectroscopy, multi-scale molecular modelling employing docking22, crystallised23 and chemically analysed crystals to reconcile our structural observations with Glc entrapment in native HvExoI purified from barley seedlings9. Several crystals removed from the mother liquor were extracted and fractionated by normal-phase high performance liquid chromatography (HPLC) with evaporative light scattering detection . Mass fragmentation spectra of these materials  resolution showed a single Glc molecule bound in the −1 subsite8. In the current work we refined native HvExoI at 1.65 Å resolution (synchrotron data), revealing that Glc is bound at 0.5 occupancy at each −1 and +1 subsites in the 4C1 chair conformation, suggesting that it may be mobile between both subsites  and 1S3 skew boat (occupancy 0.2) conformations with classical Cremer–Pople ring-puckering parameters26. In the −1 subsite, we detected the network of 12–13 mono- and co-operative bi- and tri-dentate H-bonds28; of interest were those forming short H-bonds of 2.5–2.7 Å between Oδ1 and Oδ2 of Asp95, and the C6-OH and C4-OH groups of the Glc moiety. We attempted to position into the electron density other skew boat conformers of Glc  with various occupancies, however, convergence in the refinement was reached with those of 4C1 and 1S3. We concluded that during maturation in P. pastoris, Glc cannot be entrapped and thus observed, because the intracellular concentration in this host is not high enough during enzyme maturation or secretion. To demonstrate that Glc was not displaced from the active site by the cryoprotectant, data were collected from recombinant crystals at ambient temperatures without applying vitrification solutions. Here, no Glc was observed in the active site, but was readily observable after perfusion of crystals with Glc.Although Glc has always been detected in the native enzyme isolated from barley seedlingsxoI Fig. . However29KD value of 0.008 × 10–3 M for G6SG-OMe revealed that it bound tighter than the Glc hydrolytic product (KD of 0.16 × 10–3 M) , we used the recombinant HvExoI enzyme. The steady-state affinityKD value of 0.16 × 10–3 M (Table 1H saturation transferred difference (STD)30 and transferred nuclear Overhauser effect spectroscopy (trNOESY)31 in solution NMR. STD spectra recorded with Glc in a 60-fold excess relative to HvExoI detected Glc bound non-covalently. As only STDs for protons of β-anomeric Glc (and not for α-form) were observed, while one would expect an α:β anomeric ratio of ~2:3 in solution equilibrium, we concluded that the enzyme specifically binds β-anomeric Glc  or 4C1 chair and B3,O (+1 subsite) distorted skew boat/boat conformations  metadynamics simulations were performed to asses Conformational Free Energy Landscape (FEL) maps of β-xoI Fig. . These a6. To assess the strength of inhibition, we determined dissociation constants of enzyme-inhibitor complexes (Ki) for 3-deoxy-glucose (3dGlc), 4-deoxy-glucose (4dGlc), n-octyl β-d-glucopyranoside (octyl-O-Glc), n-octyl 1-thio-β-d-glucopyranoside (octyl-S-Glc), a hydrophilic polymer polyethylene glycol  and the thio-analogue methyl 2-thio-β-sophoroside (G2SG-OMe). All inhibitors showed competitive inhibition with Ki values between 9.8 × 10–3 M and 0.13 × 10–3 M  and alkyl-glucoside derivatives, and substrate mimics that could potentially displace GlcTo test the hypothetical Glc displacement route by using dGlc derivatives, crystals were perfused with saturating concentrations of 3dGlc Fig.  and 4dGld-glucosides with tighter Ki values  or recombinant Glc-perfused HvExoI  - and 1,2)-linked substrate thio-analogues displace the Glc product from the active site, we perfused recombinant crystals of HvExoI and observed that the sugars adopted different poses Fig. . It is w,6- and (M) Table , and thaM) Table . For G6SM) Table . In the -linked s19 and MD simulations, followed by GaudiMM20 and PELE21 pathway calculations.We considered the HvExoI in complex with G2SG-OMe (PDB 6MD6) Fig.  to embodd-glucopyranosyl--d-glucose (G2OG) or β-d-glucopyranosyl--d-glucose (G3OG) substrates into HvExoI:G2OG-OMe or HvExoI:Glc complexes, combined with MD simulations indicated that the existence of ternary HvExoI:Glc:G2OG or HvExoI:Glc:G3OG complexes (designated 1–6) was plausible, where Glc was bound in the −1 subsite, and G2OG or G3OG were attached at +1 and putative +2 subsites -d-glucose (G6OG) disaccharide substrates at the −1 and +1 subsites, predicted binding with higher affinities , when the Glc product was absent in the −1 subsite. However, when the Glc product was included in the −1 subsite, docking of G2OG, G3OG and G6OG in the +1 and putative +2 subsites predicted binding with lower affinities . These data indicated that bound Glc lowered binding energies for incoming substrates as they had no access to the higher affinity −1 subsite.To find out if binding of substrates by HvExoI lacking the bound Glc product would lead to tighter or weaker binding than that with Glc included, we carried out further calculations and compared binding affinities. Docking calculations of G2OG, G3OG and β-20 to reveal potential Glc exit routes from the active site into the bulk solvent, whereby we considered steric clashes. The initial set of simulations was performed with the HvExoI:Glc:G2OG ternary complex 1, based on the coordinates of HvExoI in complex with G2SG-OMe and Glc docked in the −1 subsite. No exit path was detected in this case, as Glc never overcame steric clashes to vacate the −1 subsite  were evaluated and accepted or rejected according to a Metropolis criterion at a given temperature. Using this approach, the HvExoI:Glc:G2OG and HvExoI:Glc:G3OG complexes 1–3 converged, and revealed that Glc egressed from the −1 subsite to the adjacent lateral cavity that was enlarged after Tyr253 rotated. This cavity was defined by an ensemble of 14 residues: Trp156, Arg158, His207, Phe208-backbone, Asp211, Asn219, Glu220, Ser252, Tyr253-backbone, Ser254, Asp285, Arg291, Glu491 and Thr492 -β-d-Glc-S--β-d-Glc-14–22 polymeric substrate46, but we did not observe potential binding sites beyond the −1 and +1 subsites.As mentioned above, despite the plethora of structural data for HvExoI19, MD simulations, QM/MM, GaudiMM20 and PELE21, that provided the first clear view of succession of events during Glc displacement. This approach also hinted that trapped Glc may play a surprising role in catalysis and led to the discovery of processivity by this exo-hydrolase. In the light of this discovery we coin the term ‘substrate-product assisted processive catalysis’, due to the key role that a substrate and a product play in the evocation of the catalytic pathway.The time-space averaged vision of crystal structures presented here was supported by the multi-scale molecular modelling, based on dockingWe demonstrate that the substrate binding and product displacement routes proceed through stages that are carefully orchestrated in succession Fig. . We suggd-glucosyl residues19, through processive catalysis. Here, (step 1) after Glc (blue square) is cleaved off from the polysaccharide, (step 2) the Glc product (yellow square) remains bound at the −1 subsite, while the remainder of the polysaccharide (grey squares) stay attached at the +1 and putative +2 subsites. As the Glc product (red square) exits (arrow) through the lateral cavity , the polysaccharide can advance to the −1 and +1 subsites, such that an uninterrupted hydrolysis of the polymer continues until it is completely hydrolysed. In both instances, after Glc egresses -β-d-glucans contained in plant cell walls51, this finding is unsurprising, as the enzyme’s efficient hydrolysis is the prerequisite for seed germination and the development of a plant embryo51. Processive catalysis  has been accepted for endo-acting hydrolases with cleft- or groove-shaped catalytic sites, such as - and -β-d-glucan endohydrolases52, and -β-d-glucan endohydrolases53, and for exo-acting chitinases50 and cellobiohydrolases54 with ridge- or tunnel-shaped sites. Conversely, β-d-glucosidases and exo-acting hydrolases with funnel-, crater- or pocket-shaped55 active sites are deemed to be non-processive49.To our knowledge, this type of processive catalysis9 is associated with chemical signalling, where entrapped products, bound substrates and enzymes co-operatively create pathways dedicated to product dissociation. The hallmark and advantage of processive catalysis is a high efficiency, where oligo- or polysaccharides are directionally threaded without the catalyst losing contact with substrates to keep binding entropic cost low, while performing multiple hydrolytic events on the same substrate molecule. While this work was focussed on a plant GH3 hydrolase, we suggest that substrate-product assisted processive catalysis may be more prevalent among exo-hydrolases with pocket-shaped active sites, irrespective of their substrate specificity. To this end, our findings could promote further investigations of enzymes involved in biomass degradation, where one of the challenges is to circumvent the bottleneck of product inhibition, a problem that could be addressed through the better understanding of enzyme catalytic cycles. More broadly, substrate-product assisted processive catalysis in enzymes with pocket-shaped catalytic sites is likely to have significance in other enzymes due to the plasticity of protein structures. It is exactly this plasticity that accounts in HvExoI for product dissociation, although in other enzymes the atomic details of reactants movements may be different.Our concept of substrate and product processive co-operative routes with pocket-shaped exo-hydrolases18 , will now allow the study of evolution of this catalytic mechanism. Preliminary analyses of 500 sequences related to HvExoI revealed that the residues underlying this mechanism are conserved in land plants, but absent in red and green algae, suggesting that this mechanism is rather ancient and has evolved in land plants about 470 million years ago.The discovery of substrate-product assisted processive catalysis in HvExoI prompts investigations of the evolutionary origin of this mechanism. The availability of the presented experimental and computational tools alongside a rich source of information for the GH3 family enzymes that originate from all phyllaWe conclude that through the descriptions of associative and dissociative reactant trajectories that we explored using our inter-disciplinary approach, we are now in a better position to understand how reactants advance in active sites, and how to improve enzyme catalytic rates, stability, product inhibition and drug discovery.d-glucopyranoside (octyl-O-Glc) and n-octyl 1-thio-β-d-glucopyranoside (octyl-S-Glc) were from Anatrace Inc. . 4-Nitrophenyl β-d-glucopyranoside (4NPGlc), glycerol, myo-inositol and other chemicals were obtained from Sigma-Aldrich (USA) or as described previously17. CH3CN was from BDH Laboratory Supplies (UK), and polyethylene glycol 400  was from Fluka Biochemica (Germany).3-Deoxy-glucose (3dGlc) and 4-deoxy-glucose (4dGlc) were obtained from Glycoteam GmbH . N-octyl β-The synthesis proceeded in two steps as follows.O-acetyl-1-thio-β-d-glucopyranose 56, 1,4-dithioerythritol  and cysteamine  were successively added to a solution of methyl 2,3,4-tri-O-acetyl-6-deoxy-6-iodo-β-d-glucopyranoside  in hexamethylphosphoramide (HMPA) (7 mL)57. The mixture was kept for 1 h at room temperature then precipited into ice-water (100 mL). The solid was collected on Celite, washed with water and then dissolved in CH2Cl2. The organic phase was washed with water, dried over Na2SO4 and concentrated. Column chromatography in silica gel (EtOAc-light petroleum 1:1) afforded methyl 6-thio-β-gentiobioside heptaacetate . [α]3); ESI-HRMS(+) calcd for C27H38O17NaS 689.17219; found 689.17081; 1H NMR (CDCl3): δ 5.16 , 5.15 , 5.0 , 4.95 , 4.93 , 4.88 , 4.65 , 4.39 , 4.22 , 4.12 , 3.65 , 3.51 , 2.79 , 2.08–1.97 ; 13C NMR (CDCl3): δ 169.6–169.3, 101.6, 83.9, 76.0, 74.4, 73.8, 72.7, 71.9, 71.3, 70.2, 68.2, 62.1, 57.1, 31.2, 20.77–20.72.First, methyl 6-thio-β-gentiobioside heptaacetate  . [α]2O); ESI-HRMS( + ) calcd for C13H24O10NaS 395.09824; found 395.09750; 1H NMR (D2O): δ 4.69 , 4.43 , 3.94 , 3.75 , 3.68 , 3.62 , 3.54–3.24 , 2.97 ; 13C NMR (D2O): δ 103.3, 86.0, 79.8, 77.2, 76.0, 75.5, 73.2, 72.5, 72.4, 69.5, 60.9, 57.4, 31.3.Second, methyl 6-The synthesis proceeded in three steps as follows.O-acetyl-2-O-trifluoromethanesulfonyl-β-d-mannopyranoside  in anhydrous CH2Cl2 (3 mL). The mixture was stirred at 0 °C for 30 min and at room temperature for 1 h. The solution was diluted with water and extracted with CH2Cl2. The organic phase was washed with aqueous KHSO4 , saturated aqueous NaHCO3, dried over anhydrous Na2SO4 and concentrated. The crude triflate (84 mg) was obtained in a quantitative yield and directly used without purification.First, methyl 3,4,6-tri-O-acetyl-2-S--2-thio-β-d-glucopyranoside (methyl 2-thio-β-sophoroside heptaacetate) , to which crude methyl 3,4,6-tri-O-acetyl-2-O-trifluoromethanesulfonyl-β-d-mannopyranoside  in anhydrous DMF (10 mL) was added. The mixture was stirred overnight at room temperature and then concentrated. A solution of the residue in CH2Cl2 was washed in water, dried over anhydrous Na2SO4 and concentrated. Flash chromatography on silica gel  afforded methyl 2-thio-β-sophoroside heptaacetate . Analytical data agreed with those reported previously60. ESI-MS: m/z = 689 [M+Na]+; 1H NMR (CDCl3) δ 5.12 , 5.04 , 4.97 , 4.73 , 4.36 , 4.30 , 4.26 , 4.13 , 3.66 , 3.56 , 3.06 , 2.08–1.99 ; 13C NMR (CDCl3) δ 170.57–169.22 (CO), 103.79, 83.79, 76.03, 74.02, 73.11, 71.77, 71.48, 69.51, 68.25, 62.25, 62.15, 57.40, 49.90, 20.86–20.77 (CH3).Second, methyl 3,4,6-tri-S-β-d-glucopyranosyl-2-thio-β-d-glucopyranoside  . [α]D −15.02 , ESI-MS: m/z = 395 [M+Na]+; 1H NMR (CDCl3) δ 4.76 , 4.57 , 3.96 , 3.78 , 3.66 , 3.61 , 3.56–3.33 , 2.85 ; 13C NMR (CDCl3) δ 102.36, 84.43, 79.76, 77.02, 75.61, 74.97, 72.82, 70.63, 69.32, 60.77 (2 C), 57.23, 51.26.Third, methyl 2-n = 5–10); (380–420 g) were performed using Surface Plasmon Resonance (SPR) at 25 °C using the Biacore X100 V2.0.1 instrument  equipped with the plus package. Purified recombinant HvExoI at 99% homogeneity (detected by SDS-PAGE) was covalently attached to a CM5 chip  in 10 mM sodium acetate buffer, pH 5.0. The carboxymethyl groups present on the dextran layer of the CM5 chip were activated with 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) . Any unoccupied reactive sites were blocked by a 7 min injection of 1 M ethanolamine hydrochloride-NaOH, pH 8.5. A ligand density of ~15.000 RU of recombinant HvExoI was achieved. Due to the fast rate constants of interactions, it was impossible to obtain individual rate constants ka and kd. Hence equilibrium analyses were performed for all protein-analyte interactions. For each interaction serial dilutions of analytes covering the 10 ·KD − 0.1 ·KD concentration ranges were prepared in 10 mM HEPES-NaOH buffer, pH 7.4 with 150 mM NaCl. Samples were injected onto the surface of a chip at a rate of 30 µl/min for 90 s, after which the formed enzyme/analyte complexes could dissociate for 90 s. As all analytes dissociated completely from the surface of the recombinant enzyme immobilised on a chip, no regeneration steps were needed. All responses were double referenced using a blank-immobilised reference surface (NHS + EDC-activated/deactivated) and a series of blank injections conducted to account for the system and injection artefacts. For each analyte at least one concentration was injected in duplicate. Triplicate experiments were performed, and the double-referenced data were globally fitted using a 1:1 equilibrium interaction model and the Biacore T200 v2.0 analysis software . Steady-state affinity binding constants KD , G6SG-OMe 372.4 g) and PEG  + S] equation to calculate Ki constant; Ki is defined as a dissociation constant of the enzyme-inhibitor complex. The enzyme activity was monitored at 410 nm and Dixon plots were used to determine Ki under the pseudo-first-order rate limiting conditions by a non-linear regression analysis, as described previously22.HvExoI cDNA . The R158A/E161A variant  and variant HvExoI were crystallised via a hanging-drop vapour-diffusion method, using macro- and cross-seeding with WT native crystal seeds. The fully-grown crystals of recombinant HvExoI reached up to 500 × 250 × 375 μm sizes after 5 to 14 days and were used for diffraction25.The optimised n = 5–10) and 1.7 M ammonium sulphate (solution A), where 3-deoxy-glucose (3dGlc), 4-deoxy-glucose (4dGlc), n-octyl β-d-glucopyranoside (octyl-O-Glc), n-octyl 1-thio-β-d-glucopyranoside (octyl-S-Glc), methyl 2-thio-β-sophoroside (G2SG-OMe), methyl 6-thio-β-gentiobioside (G6SG-OMe) or Glc were supplied during ligand perfusions. The final concentrations of ligands were between 5–20 mM and perfusion proceeded during 5–720 min. Alternatively, the crystals were deposited in a solution A with the concentration of PEG increased to the 35% (v/v). After various perfusion times at 4 ± 2 °C crystals were cryo-protected with 15% (v/v) glycerol in the solution A and mounted on a synchrotron goniometer in a stream of N2 gas at 100 K . X-ray diffraction data  were collected on the undulator beamline BioCARS 14-ID-B at the University of Chicago Advanced Photon Source (USA) equipped with a bent cylindrical Si-mirror (Rh coating) Diamond(111) double-bounce monochromator and focussing to the MARCCD-165 detector. X-ray diffraction data sets of crystals with PEG and with octyl-O-Glc and octyl-S-Glc were collected using the multipole wiggler beamline BL5 at the Photon Factory (Japan), which was fitted with a collimating mirror, double-crystal Si(111) monochromator and a focusing to the ADSC Quantum 315 CCD detector. X-ray diffraction data from recombinant WT and variants were collected at the MX1 and MX2 beamlines of the Australian Synchrotron  at 100 K (Oxford Instruments) or at ambient temperature (291 K) with a collimating mirror, double-crystal Si(111) monochromator 03BM1 dipole/bending magnet and ADSC Quantum 210r Detector. In the latter case, crystals were mounted using transparent polymer capillaries from the RT Screening kit (MiTeGen). All data were collected at 0.5–1° oscillations throughout 180–720°. Data were processed using the DENZO/SCALEPACK HKL 2000 suite of programmes61. Autoindexing determined that space group P43212 of crystals were consistent with the tetragonal space group P43212 in all instances. The structures of the enzyme-ligand complexes were refined using CCP4 REFMAC562 and PHENIX63. We used the solved structures  without ligands, ions, glycerol and water molecules, as starting models for refinements of HvExoI in complex with ligands17. The iterative model building using XtalView/MIFIT64, Coot65 and refinements with REFMAC562 allowed tracing of all the residues. Following convergence in a standard refinement, a further improvement of about 2% in the Rwork/Rfree factors ratio was achieved by refining domain 1, (residues 1–357) and domain 2, (residues 374–559), as two independent anisotropic entities with translation-libration-screw (TLS) motion67. Electron densities for the ligands were well-defined in the active site regions at 3σ level in m|Fo|-|Fc| maps and water molecules were located automatically with CCP4 ARP at levels higher than 3σ. Water molecules were retained if they satisfied H-bond criteria and if their 2 m|Fo|-D|Fc| electron density maps were confirmed after refinements, where m is the figure of merit and D is an estimated coordinate error. During model building and refinement, 5% of the data were flagged for cross-validation to monitor the progress of refinements, using Rfree statistics69. The PROCHECK programme69 was used to check the geometrical quality of the models. Ramachandran plots71 of all structures showed that 99.8% of residues were found in the most favourable, additionally allowed and generously allowed regions of the plot, with well-defined electron density for Ile432, the only residue located in disallowed regions. Data collection, cell parameters and refinement statistics of all structures are summarised in Supplementary Tables Enzyme crystals with lengths of up to 400 μm in the longest dimensions were transferred in 100 mM HEPES-NaOH buffer, pH 7.0, containing 1.2% (w/v) PEG  and dissolved in 100 μl of 90% (v/v) ethanol. The mixture was treated for 5 min at 80–85 °C, held on ice for 1 h and centrifuged . The supernatant was recovered, the pellet washed twice in 100 μl of re-distilled water (conductance 24 μS), and the supernatants were combined and freeze dried. The extract obtained from crystals, a freeze-dried mother liquor, and a mother liquor with authentic Glc (100 ng) being added, were dissolved in 25 μl 65% (v/v) CH3CN and separated by high performance liquid chromatography (HPLC) coupled with the Evaporative Light Scattering Detector . The samples were eluted isocratically with 65% (v/v) CH3CN at a flow rate of 0.6 ml/min. The fractions eluting between 6–7.3 min were collected and freeze dried. A model 1090 HPLC liquid system controlled by ChemStation software (Agilent Technologies) was used for chromatography, and separation was carried out on a Prevail Carbohydrate ES column, 5 μm, 250 × 4.6 mm (Alltech Associates Inc.). The column temperature during separations was 21 °C. The column eluent was split in 6.5 (collect): 1 (detector) ratio. The detector drift tube was at 40 °C, the nitrogen inlet pressure was 1.5 bars and the signal GAIN setting was set at 4. The HPLC-eluted fractions (6–7.3 min) were reduced with 1 M NaBD4 in 2 M NH4OH for 18 h at 4 °C and acetylated with acetic anhydride. Myo-inositol (20 ng) was added as an internal standard. Acetylated alditols were analysed on a low polarity 25 m × 0.25 mm  Chrompack Capillary Column CP-Sil 5 CB LB/MS  using He as a gas flow with a Hewlett-Packard 6890 Series GC System and a Hewlett-Packard 5973 mass selective detector (Agilent Technologies)72.Six crystals of native HvExoI with well-defined edges in a longest axis dimension of ~80–120 μm were collected from a hanging drop in a cat whisker, deposited in a test tube, washed in solution A, pelleted by low speed centrifugation  was diluted to 40 µM in the same buffer in D2O, and 60 equivalents (2.4 mM) of Glc from a stock solution in D2O were added. For transferred Nuclear Overhauser Effect Spectroscopy (trNOESY) experiments, the same recombinant enzyme stock solution was diluted to 57 µM with a deuterated 20 mM sodium acetate buffer, pH 5.25, to which five equivalents of Glc (0.285 mM) were added followed by 300 msec mixing time. In a separate experiment, to the 57 µM recombinant enzyme stock solution, five equivalents of Glc and three equivalents of thiocellobiose (0.171 mM) were added, both from a stock solution in D2O, followed by 300 msec mixing time. STD spectra were acquired with 2048 scans, using 30 ms Gaussian shaped pulses for selective protein saturation at 0.65 ppm; the reference spectrum employed off-resonant saturation at 100 ppm. Different saturation times  were used. Prior to Free Induction Decay acquisition, an excitation sculpting double echo for water suppression and a T2 filter (100 ms XY16 with 500 μs echo times to minimise dephasing from JHH coupling evolution) protein signal suppression was inserted. STD spectra for free Glc were acquired under the same conditions to show that no direct ligand saturation occurred. trNOESY spectra were acquired with 64 scans, 4 K points in the direct dimension, 256 points in the indirect dimension and 300 ms mixing time. For water suppression we employed a WATERGATE scheme using 3–9–19 binomial pulses. 1H signal assignments of ligands were derived from two-dimensional TOtal Correlation SpectroscopY (TOCSY), NOESY and 13C-Heteronuclear Single Quantum Coherence (HSQC) spectra. The NOESY spectrum of free thiocellobiose was acquired at 313 K with 700 ms mixing time to obtain positive NOEs. A NOESY spectrum acquired under the conditions used for the trNOESY spectrum  yielded no observable NOEs, indicating NOE zero-crossing for thiocellobiose (for τc = 1.12/ω0).NMR spectra were acquired at 283 K on the Bruker AVANCE III 600 MHz and 800 MHz spectrometers . For Saturation Transfer Difference (STD) experiments, a stock solution of recombinant HvExoI deglycosylated by endoglycosidase Hd-glucopyranose) (PDB 3WLH) with occupancy 0.5 for −1 and +1 subsites, suggests that the two subsites are alternatively occupied. We set up two enzyme-product complexes, with Glc bound in the −1 subsite, whereas the +1 subsite was occupied by water molecules, and vice versa. The protonation state of the titratable residues was selected based on their hydrogen bonding environment. Namely, all Arg, Lys, Asp and Glu residues were in ionised form, except for the acid-base residue Glu491, which was protonated (i.e. non-ionised) to represent the catalytic acid/base form required in the first step of the reaction, and the predominant form at the optimal pH of the enzyme. Histidine residues 98, 111, 234, 331, 419, 487 and 586 were considered as Nε-protonated and His207, His262 and His377 as Nδ-protonated. Assigned titration states agreed with pKa values predicted by PROPKA3.1 and with the optimised hydrogen placement algorithm of MolProbity. Disulfide bridges were considered between Cys151 and Cys159, and between Cys513 and Cys518. Three sodium ions were included to achieve neutrality, in addition to 150 mM NaCl to mimic the physiological ionic strength. The system size consisted of approximately 150,000 atoms. The initial structures were equilibrated by classical MD simulations. Protein and Glc were described via the parm99SB73 and the Glycam0674 force fields, respectively, whereas the TIP3P model70 was used for water molecules and Åqvist parameters for the sodium and chloride ions. The classical MD simulations were performed with NAMD2.977. The SHAKE/RATTLE78 algorithm was used to constrain the bonds involving hydrogen atoms in both the solvent and the solute. Multiple time step integration was carried out in r-RESPA; the production simulations used a base time step of 2 fs and a secondary time step of 4 fs for long-range interactions. Non-bonded interactions were computed at every step with a cut-off separation of 9 Å. Periodic boundary conditions and the particle mesh Ewald method were employed to evaluate long-range electrostatic interactions. Simulations were carried out in the NPT  ensemble, with a Nosé-Hoover thermostat and a Langevin piston Nosé-Hoover barostat80 to maintain the temperature at 300 K and the pressure at 1 atm, respectively. Each of the two enzyme-product complex simulations was run for 40 ns without restraints, ensuring that the system reached equilibrium. Analyses of trajectories used VMD and in-house scripts. One representative snapshot from the last time window (≈5 ns) of each simulation was taken as the starting structure for further QM/MM MD simulations. Crystallographically observed 4C1 Glc conformations and protein-sugar interactions were consistently maintained during classical MD.The structure of native HvExoI in complex with Glc , whereas the remainder of the protein and solvent were in the MM region. The MM system was treated with the Amber force field, for consistency with the previous classical MD simulations. The QM system was treated with Density Functional Theory (DFT), using a plane wave (PW) basis set with a kinetic energy cut-off of 70 Ry, Martins-Troullier pseudopotentials83 and the Perdew-Burke-Ernzerhoff (PBE) exchange-correlation functional84; this is at the same level theory as that described for sugar conformational Free Energy Landscapes (FELs)34. The QM system was enclosed in an isolated orthorhombic box of size 14.0 Å × 13.2 Å × 13.5 Å (−1 subsite) or 12.0 Å × 15.3 Å × 13.2 Å (+1 subsite). The electronic fictitious was set at 700 au and the simulation time step was at 0.12 fs. Both complexes were equilibrated at 300 K for around 5 ps before starting metadynamics simulations of Glc conformational FEL. A similar procedure was used in previous studies of conformational preferences of sugars in carbohydrate-active enzymes34.Classical MD snapshots of two enzyme-product complexes were submitted to QM/MM MD simulations to re-equilibrate the system within the QM/MM Hamiltonian. The method by Laio and co-workers86 simulations were performed to explore the conformational FEL of Glc bound in the −1 or the +1 subsites. We employed the metadynamics driver provided by the Plumed2 plugin, combined with the well-tempered metadynamics approach87. Ring-puckering coordinates qx and qy were used as collective variables, as described for isolated Glc33. Metadynamics parameters were selected from the analysis of evolution of the puckering coordinates during the unbiased QM/MM MD simulation and from expected energy barrier heights based on our previous work on both isolated Glc and a β-d-glucoside bound in the active site of 1,3;1,4-β-d-glucanase34. The height and the width of Gaussian terms were initially set at 1 kcal mol−1 and 0.1 Å, respectively, and a bias factor of ɣ = 10 was used for the well-tempered approach. The deposition time was set at 24 fs (200 MD steps). The same set up was used for both enzyme-product complexes. Simulations were stopped after adding 7,668 Gaussians (enzyme-product complex with Glc bound in the −1 subsite) and 7725 Gaussians (Glc bound in +1 subsite). Analyses of evolution of puckering coordinates and FEL showed that the metadynamics simulation reached a diffusive regime and that the energy differences converged.QM/MM metadynamics88 through PDB2PQR version 2.0.089. In this complex, Glu491 was modelled in a non-ionised form; this is the required protonation state for the acid/base catalyst in substrate/product complexes of retaining GH3 enzymes that catalyse hydrolysis by the generally accepted double-displacement reaction mechanism22. The entire system was solvated in a water box of 103.0 × 88.0 × 101.0 Å3 volume, which ensured that there was a 5 Å thick layer of water molecules in each direction from any atom. Sodium ions were added to neutralise the total charge of the system forming a fully solvated model of 83,428 atoms. The system was energy-minimised to remove steric clashes and heated through 4 ns equilibration (integration steps of 2 fs) until reaching the temperature of 300 K at 1 Bar. This process also involved the application of positional restraints on the protein and ligand atoms that were gradually released until the whole system was fully equilibrated. Equilibration of the system was stopped when root-mean-square deviation (RMSD) values of the main chain reached the stable value lower than 1.60 Å. Two independent simulations of 100 ns each were run under NPT conditions, whereas temperature and pressure were controlled through Langevin dynamics and the Nosé-Hoover algorithm combined with the Langevin piston method80, respectively. Periodic boundary conditions were applied, and the SHAKE algorithm78 was used to adjust O-H separations of water molecules. The cut-off value of 12 Å was used for non-bonded interactions. All calculations were carried out with NAMD2.977 using the CHARMM22 force field85, for the protein and TIP3P for water molecules75, while the CHARMM36 all-atom carbohydrate force field90 was used for Glc.MD simulations in complex with Glc trapped in the −1 subsite (PDB 3WLH) proceeded as follows. Hydrogen atoms were added and protonation states of titrable residues at pH 7.0 were assigned with PROPKA3.1d-glucopyranosyl--d-glucose (G2OG) or β-d-glucopyranosyl--d-glucose (G3OG) to HvExoI for selected protein structures were performed with Gold5.291 applying a search cavity of the 20 Å radius and using the Goldscore scoring function. Side-chain flexibility for Glu491 was allowed, whereas Trp434 and Trp286 were flexible as specified below. Complex 1 was generated by docking Glc to the HvExoI:G2OG complex derived from the HvExoI:G2SG-OMe crystal structure (PDB 6MD6). Complex 2 was generated by docking G2OG to the HvExoI:Glc complex derived from the native HvExoI crystal structure (PDB 3WLH). Both complexes contain Glc bound at the −1 subsite and G2OG at +1 and putative +2 subsites. Complexes 3–6 were obtained by docking G2OG or G3OG to the HvExoI:Glc structure (PDB 3WLH) subjected to MD simulations, with the major conformation of Trp434 . MD simulations were carried out under periodic boundary conditions of NPT ensembles, as described for MD simulations of HvExoI in complex with Glc. Docking of G2OG, G3OG and β-d-glucopyranosyl--d-glucose (G6OG) lacking the Glc product in the active site was carried out as described above.Molecular docking calculations of Glc and β-20 (https://github.com/insilichem/gaudi), a recently developed modular multi-objective genetic algorithm platform allows conformational exploration of defined genes (defined below) with multiple evaluation operators of fitness or objectives. The GPathFinder extension was used, defining as genes protein and substrates molecules, rotational bonds of ligands and rotamers of the protein, and as objectives, minimisation of van der Waals contacts and maximisation of separations between Glc geometric centres at the −1 subsite. This afforded the low-cost computational pre-identification of putative exit channels. The ProDy (Protein Dynamics)92 Normal Mode Algorithm (NMA) was used to generate alternative starting structures for the GPathFinder. Normal mode calculations were performed with Tangram implementation on the UCSF Chimera suite93, using residues grouped in clusters of 100 (to avoid protein distortion and achieve acceptable conformations), generating 10 modes with a cut-off of 15.0 Å and a Gamma LJ of 1.0. In the case of the crystal structure (PDB 3WLH), the second frame of the mode with frequency 31.2 cm−1 was chosen, while the second frame of the mode with frequency 28.7 cm−1 was selected for complex 3. In both cases, the displacement parameter in the Tangram interface was set to 150.Ternary complexes 1–3 before MD simulation (as described above) and complex 3 after MD simulation with substrates bound in a productive mode, were used as starting points to investigate Glc displacement pathways from the −1 subsite of HvExoI. The protein contained Glc at the −1 subsite, and G2OG or G3OG attached at +1 and putative +2 subsites. GaudiMMhttps://pele.bsc.es)94 was used to simulate Glc displacement and to identify the Glc migration route from the −1 subsite. PELE is a Monte Carlo based algorithm that generates configurations along a path through a sequential ligand and protein geometric perturbation scheme, side-chain conformational prediction and minimisation steps. The ligand (Glc) is perturbed by random translations and rotations, and by internal rotations of protein rotatable bonds, while Cα carbons of the protein are displaced following one of the six lowest Anisotropic Normal Modes95. The algorithm optimally arranges sidechains surrounding perturbed atoms using a rotameric library side-chain optimisation and energy minimisation with the OPLS-AA force field96. The move of the system is accepted, defining a minimum, or rejected according to a Metropolis criterion for a given temperature. The PELE scheme performs an effective exploration of the protein energy landscape99. Here, the exit path is defined by separations between the centre of masses of Glc molecules at the beginning (−1 subsite) and at the end of simulations (in solvent). Complexes 1–3 with Glc at the −1 subsite and G2OG or G3OG at +1 and putative +2 subsites were selected from MD simulations to identify potential exit pathways. One representative structure from each MD simulation of complexes 1–3 was selected as these complexes show G2OG or G3OG bound in the productive modes for subsequent catalysis. PELE simulations were terminated, when respective separations between centres of masses and C4-OH groups of Glc molecules in initial and final structures were above 15 Å.The PELE software (Further information on experimental design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Reporting Summary


Eschweilera ovata in five forest remnants in southern Bahia, Brazil using nuclear simple sequence repeat (nSSR) and plastid simple sequence repeat (cpSSR) microsatellite markers. cpSSR marker analysis revealed the domains of four haplotypes, showing that 80% of the individuals had only four maternal origins, reflecting a founder effect and/or genetic bottleneck. The results of cpSSR and nSSR analyses indicated moderate genetic diversity, particularly in conservation units with full protection, which showed the best parameters of all areas evaluated. Another indication of the susceptibility of these populations to forest loss and fragmentation was the strong genetic bottleneck observed. In contrast, genetic structure analyses  revealed gene pool sharing between the subpopulations, which may reflect the historical gene flow that occurred before forest fragmentation.Forest loss and fragmentation are the main threats to the maintenance of the Atlantic Forest, an important global biodiversity hotspot. Because of the current critical level of deforestation, ecological corridors are needed to facilitate species dispersion and gene flow among fragments. This study was conducted to investigate the genetic variability and gene pool sharing of  The Atlantic Forest in the east of Brazil is an important center of endemism associated with high species richness of several taxa, particularly tree species .Considering the conservation scope and current state of the reduction and fragmentation of the Atlantic Forest, it is important to establish ecological corridors between forest remnants  to allowIn the last few decades, genetic studies using a conservationist approach have mainly employed molecular markers such as microsatellites to evaluate the variability and distribution of the genetic diversity of tree species (Eschweilera ovata (Cambess.) Mart. ex Miers (Lecythidaceae), in five forest remnants in southern Bahia, Brazil, using cpSSR and nSSR markers. These remnants are in a region with high endemism and plant richness where efforts are underway to implement ecological corridors that connect forest fragments and conservation units  and shows a zoochoric syndrome of seed dispersal and pollen. Additionally, it was suggested that this species can be used to promote the recovery of degraded areas. E. ovata is also economically exploited to make the berimbau, a musical instrument used in capoeira orchestras, a cultural symbol of the state of Bahia, Brazil  The subpopulations still share a gene pool, reflecting functional connectivity prior to forest loss and fragmentation.Because of the current critical state of the reduction and fragmentation of the Atlantic Forest, we evaluated the genetic variability and gene pool sharing of a tree species, , Brazil . In thisThe study was conducted in five areas in southern Bahia, Brazil, a portion of the Atlantic Forest that is considered a priority for conservation actions due to its biological importance . Four ofE. ovata adult individuals for genetic analysis and georeferenced the trees using GPS . Sampling was performed to cover as much of each area as possible while avoiding the sampling of individuals geographically close to each other to reduce the chances of kinship between them and to sample the genetic pool of each collection area . Estimates of the population genetics parameters are influenced by number and frequency of informative alleles (frequency ≥ 0.05)  . If the DNA was obtained according to the CTAB protocol  and the 8 and (GT)8 biotinylated probes, and positive fragments for the microsatellites were amplified and sequenced on an ABI 3100 genetic analyzer . We used Primer3 software (An enriched library was obtained by hybridization with (CT)To characterize the new nuclear microsatellite marker set (nSSR) and perform genetic analysis of the populations, we used individual DNA sampled from four subpopulations  for a total of 60 trees. PCR samples contained 7.5 ng of genomic DNA, 10 μL of Top Taq Master Mix kit (Qiagen), 0.8 μM of primer reverse, 0.4 μM of forward primer, and 0.16 μM of M13 tail (CAC GACGTTGTAAAACGA) labeled with a fluorochrome . The amplification reaction was run in a Veriti 96-Well Thermal Cycler (Applied Biosystems). It consisted of an initial denaturation step at 94 °C for 1 min followed by 30 cycles of an denaturation step at 94 °C for 1 min, annealing step at the specific annealing temperature for 45 s, and extension step at 72 °C for 1 min; 8 cycles for M13 tail amplification at 94 °C for 1 min, 53 °C for 45 s, and 72 °C for 1 min; followed by a final extension step at 72 °C for 10 min. The amplified fragments were subjected to capillary electrophoresis in a multiload system using an ABI 3500 genetic analysis (Applied Biosystems). Peaks were analyzed using GeneMarker software 2.6.2 .-1 of genomic DNA; 0.325 mM of each dNTP ; 1.3X PCR buffer (Invitrogen); 4.0 mM MgCl2; 0.325 mgμL-1 BSA (Invitrogen); 0.2 mM forward primer with the M13 tail; 0.4 mM reverse primer; 0.06 mM M13 complementary primer with the fluorophore; 1 U Taq DNA polymerase (Invitrogen), and MilliQ water to complete the final volume. PCR was performed under the following conditions: denaturation at 94 °C for 2 min followed by 30 cycles of denaturation at 94 °C for 1 min, annealing over a temperature gradient of 48 °C to 62 °C for each primer pair for 1 min, and extension at 72 °C for 1 min. The second PCR step was programmed for 8 cycles as follows: denaturation at 94 °C for 1 min, annealing at 53 °C (specified for the tail primers) for 1 min, extension at 72 °C for 1 min, and final extension at 72 °C for 7 min. Genotyping of the PCR products was performed on a multiload system , and GSLIZ500 was used as a size fragment standard (Applied Biosystems). To analyze the electropherograms and obtain the genotypes, GeneMarker version 2.2.0 software was used.Ten loci were amplified in all sampled individuals (75 trees) from the five subpopulations  using chloroplastidial microsatellites (cpSSR)  with an E), observed heterozygosity (HO), and inbreeding coefficient (f). The confidence interval of HE, HO, and f at 95% was calculated using divBasic function with 10,000 bootstraps. To plot the results of these analysis, the ggplot2 package was used in R software , probability of exclusion of paternity (Q), and identity index (I), we used the CERVUS 3.0.6 program  influenced the genetic distance between populations (FST), simple linear regression analysis was performed in R software (http://www.r-project.org/). To identify the number of clusters, we used the find.clusters function, retaining all main components, and the best fit cluster number was inferred through the Bayesian information criterion (BIC), selecting the lowest BIC as the ideal cluster. To describe the relationships between the identified clusters, the generic function DAPC was used, retaining the number of principal components that incorporated 80% of the cumulative variance  and number of discriminant functions  to maximize variation between groups. In the graphical representation of the results obtained in DAPC analysis, we used the scatter function to assign individuals to clusters according to their gene pool and compoplot function to produce a diagram representing the genetic pool of the individuals associated with clusters of the subpopulations.Analysis of molecular variance (AMOVA) was conducted using GenAlex 6.5 . To evalH), number of unique haplotypes (PH), number of effective haplotypes (HNe), haplotype richness (H), haplotypic diversity (HE), total genetic differentiation (FST) between areas, and average genetic distance between individuals (D2sh). Linear regression analysis was performed in R software (http://www.r-project.org/) to detect associations between the pairwise genetic (FST) and geographical distances (km).To analyze the cpSSR loci, we used Haplotype Analysis software version 1.04  to calcuTo verify the existence of genetic bottlenecks in the subpopulations, we conducted the Wilcoxon test in software BOTTLENECK version 1.2.02 02 . As recoa priori a cluster of individuals or populations, we used the EDENetworks program (ST was used as distance with the automatic threshold (0.42). In the network at the individual level, allele sharing was used as a distance with automatic thresholding (0.14).To visualize and analyze the genetic relationships without assuming E. ovata which had (i) an average of 5.6 alleles, (ii) HO of 0.214–1.000, (iii) HE of 0.198–0.878, and (iv) a fixation index (F) of -0.333–0.4763 (see Tables S1 and S2). The combined probability of exclusion (Q) of these 13 loci was 0.9 10-9 and identity index (I) was 3 28-10. The sequence, allele amplitude, and annealing temperature for each primer are shown in Table S1.We developed 13 new nuclear primer pairs for Figures S1 and S2). The four subpopulations showed low numbers of effective alleles , low allelic richness . DAPC revealed that for the four sampling areas form three genetic clusters , a group was formed by MM and ReBio and the other two groups formed separately in areas AR and CAP  and four were polymorphic , with an average of three alleles per locus and 14 haplotypes. Of these haplotypes, four were found exclusively in PMBE , two were exclusively found in ReBio (H3 and H4), one in AR (H5), and another was exclusively found in Cap (H11). In contrast, six of the 14 haplotypes  were shared by two or more study areas. Dominance of the four haplotypes  was observed in these areas, with 80% of the analyzed individuals presenting only four maternal origins (Table S3). In intra-population analysis, we detected an average of five haplotypes. The PMBE subpopulation contained the highest number (7) of haplotypes, while the RPPN Cap subpopulation had the lowest (3) (Seven of the 10 cpSSR primers tested in west (3) . When wewest (3) .ST) was low in all subpopulations, with the lowest value in PMBE  and, consequently, low levels within subpopulations (HS), with higher values in PMBE and ReBio than in the other locations . Additio in PMBE .ST analysis revealed that subpopulations had low genetic differentiation . In network analysis at the population level, sharing of the gene pool was observed, reflecting the connection between subpopulations  showing only four haplotypes. This finding suggests that these subpopulations of ttleneck . In contE. ovata subpopulations have low average haplotypic diversity compared to other plants species  estimates similar to those found in rare and overexploited palm and tree species from the Atlantic Forest in southern Bahia, such as Euterpe edulis Mart. (HE = 0.64 and HO = 0.58) and Melanoxylon brauna Schott (HE = 0.57 and HO = 0.53) (Licania hypoleuca Benth. (HE = 0.84 and HO = 0.71)  values were negative in all subpopulations, strongly indicating that preferential crosses occurred between unrelated individuals. We used the Wilcoxon test to evaluate whether this excess in HO was also the result of a genetic bottleneck in E. ovata subpopulations. The genetic bottleneck may cause the development of an excess of transient heterozygosity after a recent change in the effective population size when heterozygotes have a selective advantage, resulting in a higher HO than HE . Genetic variability plays an important role in natural selection by maintaining the ability of populations to adapt to their habitats over time (The results obtained with the two sets of markers (nSSR and cpSSR) showed convergence, with the results of AMOVA (nSSRs) and haplotype diversity analysis (cpSSR) revealing that diversity within the subpopulations contributed more to the overall composition than genetic variation among the subpopulations. This is likely the consequence of allele sharing and ancestral haplotype lineages that founded these populations . Additiover time . Even smST) revealed that the studied subpopulations exhibited very low genetic structuring when analyzed with both markers, and this genetic pattern was not influenced by geographic distance. However, DAPC analysis revealed that the four collection areas formed three genetic clusters. However, many individuals from an a priori subpopulation are inserted into ellipses of other subpopulations, and there are overlaps of ellipses between subpopulations, supporting the observed low FST values. Additionally, there is a large mixture of the gene pool in individuals of different clusters, reinforcing the results obtained in FST analysis and showing that genetic diversity is mainly contained among individuals, as indicated by AMOVA.Genetic structure analysis , formed by individuals from different subpopulations. Importantly, the connections between individuals from the two groups demonstrated that although the individuals belonged to a specific group (green or gray), they also had genetic similarities with individuals from the other group. Thus, although two groups were observed, they are genetically connected, which may reflect allele sharing among individuals in these groups. Overall, the same patterns in the results were observed by DAPC (nSSR), network analysis (cpSSR), and Fst analyses with both markers revealing that these subpopulations are functionally connected by the dispersion of pollen and seeds. However, even with gene pool sharing, it is possible that gene flow among these subpopulations is currently impaired because of fragmentation of the forest in this specific landscape (see details in


HSF-1) is a component of the heat shock response pathway that is induced by cytoplasmic proteotoxic stress. In addition to its role in stress response, HSF-1 also acts as a key regulator of the rate of organismal aging. Overexpression of HSF-1 promotes longevity in C. elegans via mechanisms that remain less understood. Moreover, genetic ablation of a negative regulator of HSF-1, termed as heat shock factor binding protein 1 (HSB-1), results in hsf-1-dependent life span extension in animals. Here we show that in the absence of HSB-1, HSF-1 acquires increased DNA binding activity to its genomic target sequence. Using RNA-Seq to compare the gene expression profiles of the hsb-1 mutant and hsf-1 overexpression strains, we found that while more than 1,500 transcripts show ≥1.5-fold upregulation due to HSF-1 overexpression, HSB-1 inhibition alters the expression of less than 500 genes in C. elegans. Roughly half of the differentially regulated transcripts in the hsb-1 mutant have altered expression also in hsf-1 overexpressing animals, with a strongly correlated fold-expression pattern between the two strains. In addition, genes that are upregulated via both HSB-1 inhibition and HSF-1 overexpression include numerous DAF-16 targets that have known functions in longevity regulation. This study identifies how HSB-1 acts as a specific regulator of the transactivation potential of HSF-1 in non-stressed conditions, thus providing a detailed understanding of the role of HSB-1/HSF-1 signaling pathway in transcriptional regulation and longevity in C. elegans.Heat shock factor 1 ( C. elegans and Drosophila have a sole ortholog of HSF1 , undergoes oligomerization, translocates to the nucleus and shows increased binding to its target sequences in the genome termed as heat shock elements (HSE)  family, which function as molecular chaperones to assist in the folding of nascent polypeptides and prevent the toxic aggregation of misfolded cytosolic proteins  signaling and food deprivation   . Direct  elegans . In contkaryotes , the funHSB-1 regulation, heat shock factor acquires an altered transactivation profile, which results in extensive changes to the C. elegans transcriptome. Genetic ablation of hsb-1 induces increased in vitro DNA binding activity of the HSF-1 transcription factor similar to that observed in an HSF-1 overexpression strain, even though HSF-1 protein level is not elevated in the hsb-1 mutant. Roughly 45% of the genes that are differentially expressed in the hsb-1(-) strain also constitute a subset of the altered transcriptome in hsf-1 overexpressing animals, but the global transcriptional changes associated with HSB-1 inhibition are distinct from that induced via overexpression of HSF-1. We further show that the subset of genes that are differentially expressed in both hsb-1(-) and hsf-1 overexpressing animals have a strongly correlated expression pattern in the two strains. Overall, our findings collectively suggest that HSB-1 controls the expression of a small subset of the HSF-1-regulated transcriptome, which might be essential for mediating the longevity promoting effects of HSF-1 in normal physiological conditions.Here we show that in the absence of C. elegans strains used in this study were maintained at 20° on nematode growth medium (NGM) plates seeded with E. coliOP50 strain using the standard method. Animals were maintained for at least three generations without starvation before they were used for experiments. The following strains were used in this study: N2: Wild-type, EQ150: hsb-1(cg116) IV – CH116 outcrossed 4x to wild-type N2, and EQ140: iqIs37[pAH76(hsf-1p::myc-hsf-1) + pRF4(rol-6p::su1006)rol-6]. Wild-type (N2) and CH116 strains were obtained from Caenorhabditis Genetics Center . All experiments in this study were performed using day 1 adult animals that were obtained after age-synchronization of unhatched eggs.All 12-18 primer (Thermo Fisher) using SuperScript III reverse transcriptase (Thermo Fisher). Quantitative PCR was performed with Power SYBR Green PCR master mix (Thermo Fisher) and PCR primers listed in Table S3 using a CFX96 Real-Time PCR detection system (Bio-Rad). Primers were designed using the Primer3Plus online tool. Comparative Ct method was used to measure relative transcript levels while using the housekeeping gene cdc-42 as an internal control for normalization  was used to extract total RNA using the manufacturer’s protocol and TURBO DNA-free kit (Themo Fisher) was used to perform DNase-treatment. cDNA was synthesized from 5 µg RNA with 0.5 µg of oligo(dT)∼10,000 age-synchronized young adults grown on HG plates were collected in M9 buffer containing 0.01% Triton X-100 and were immediately washed three times with M9 buffer. Pellets were suspended in three times the volume of 6x Sample Buffer  diluted to 2X final concentration and were snap-frozen in liquid nitrogen for 30 sec. Samples were subsequently boiled for 10 min, vortexed for 15 sec, centrifuged at 16,000 × g for 30 min and subjected to SDS-PAGE on a SE 250 mini-vertical unit . Proteins were transferred to Immobilon-P PVDF membrane (Millipore Sigma) at 400 mA for 40 min on a Trans-blot SD semi-dry transfer cell (Bio-Rad) and the PVDF membrane was blocked in 5% non-fat dry milk-based blocking-grade blocker (Bio-Rad) for 1 hr at room temperature. Primary antibody incubation was performed for 12–16 hr at 4° using the following antibodies: HSF-1 – Abnova custom-made  lot no. F4271-3E11 and β-actin – Abcam ab8227 . The PVDF membrane was washed four times with TBS buffer containing 0.1% Tween 20 (TBS-T) for 5 min per wash, incubated with HRP-conjugated secondary antibody for 1 hr at room temperature and washed again four times with TBS-T buffer for 5 min per wash. Blots were developed using Immobilon Western Chemiluminescent HRP Substrate (Millipore Sigma) and visualized by autoradiography.2, 0.1 mM EDTA, 0.5 mM EGTA, 44 mM sucrose, 1 mM dithiothreitol, protease inhibitors, phosphatase inhibitors) containing 0.25% NP-40 and 0.1% Triton X-100. Animals were homogenized by 20 strokes of pestle B of the Kontes Dounce tissue grinder. The homogenized samples were centrifuged at 4,000 × g for 5 min and the nuclear pellet was washed two times with NPB buffer containing 0.25% NP-40 and 0.1% Triton X-100. Nuclei were extracted in four times the volume of HEG buffer  at 4° for 1 hr. The nuclear fraction was collected by centrifugation at 14,000 × g for 15 min. Protein concentrations were determined by Bradford assay.∼4,000 age-synchronized young adults grown on NGM plates were collected in M9 buffer containing 0.01% Triton X-100 and were immediately washed three times with M9 buffer. Samples were frozen in liquid nitrogen and thawed on ice for two freeze-thaw cycles. Pellets were resuspended in 10 times the volume of NPB buffer  using a previously described protocol (hsp-16.1 gene. The DNA-bound nuclear extracts were resolved using native 3.5% polyacrylamide gel electrophoresis and were transferred to Immobilon-Ny+ charged nylon membrane (Millipore Sigma) at 400 mA for 1 hr on a Trans-blot SD semi-dry transfer cell (Bio-Rad). The HSF-1-HSE DNA complexes were visualized by autoradiography using LightShift Chemiluminescent EMSA kit (Thermo Fisher).Binding of N2, EQ150 and EQ140 strains  using the manufacturer’s protocol and DNase-treatment was performed using TURBO DNA-free kit (Themo Fisher). mRNA was isolated from the DNase-treated total RNA using oligo(dT) and cDNA was synthesized by reverse transcription using TruSeq RNA Library Prep Kit v2 (Illumina). The samples were subsequently end-repaired, poly(A)-tailed, ligated to barcoded oligo adapters (Illumina) and PCR-amplified using Apollo 324 library preparation system (Wafergen Bio-systems) to prepare non-stranded poly(A)-based cDNA libraries with 120 bp insert size. All samples were multiplexed for 50 bp single-end sequencing on a HiSeq 2500 platform (Illumina).TRIzol reagent (Thermo Fisher) was used to extract total RNA from ∼1,000 age-synchronized young adults of https://github.com/FelixKrueger/TrimGalore) (C. elegans reference transcriptome (WS260 release) using STAR version 2.6.0c  and pairwise distance analysis, counts with variance stabilizing transformation (VST) were used. Venn diagrams for differentially expressed genes were generated using Venn Diagram Plotter . For each genotype, the genes differentially expressed relative to wild-type were annotated with Gene Ontology (GO) terms from NCBI and the Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to identify significantly enriched functional categories from the overrepresented GO terms  . TrimmedP values for each experiment are included in the figure legends.GraphPad Prism 8 was used to perform statistical analyses and graphing. Hypergeometric tests were performed in R. Details of statistical tests used, number of biological replicates and hsb-1(-) mutant and hsf-1 overexpression strains ; and DNA sequences of oligonucleotide primers used in EMSA and quantitative PCR experiments (Table S3). All C. elegans strains used in this study are available upon request. Supplemental material available at Figshare: https://doi.org/10.25387/g3.7648832.Raw RNA-Seq reads have been deposited at the NCBI Gene Expression Omnibus (GEO) under the accession number GSE119993. Supplemental materials uploaded to the GSA figshare portal include: list of differentially expressed genes in C. elegans via increasing the gene dosage of hsf-1 or genetic ablation of hsb-1 , hsb-1(-) and a previously described long-lived hsf-1 overexpression strain  animals compared to wild-type  animals did not have increased HSF-1 protein level compared to wild-type (HSB-1 inhibition has been shown to extend C. elegans life span in an hsf-1-dependent manner (hsf-1 in the long-lived hsb-1(-) strain. Incidentally, HSF-1 activation in the presence of heat stress also does not involve transcriptional upregulation of hsf-1  and hsf-1 overexpressing animals showed ∼80% increase in in vitro HSE binding activity compared to that in wild-type animals  and hsf-1 overexpression strains  strain was more similar to that of wild-type animals, rather than to the expression pattern in the hsf-1 overexpression strain  animals  upregulated or downregulated with an FDR-adjusted P value of less than 0.05 were identified as being differentially expressed. With these two criteria, we found 1,662 genes to be differentially expressed in the hsf-1 overexpression strain  strain, though interestingly, roughly 45% of these overlapped with the differentially expressed gene list in the hsf-1 overexpression strain (hsb-1(-) animals, the pattern of differential expression was slightly different to that in hsf-1 overexpressing animals, with ∼78% of genes being upregulated and remaining ∼22% being downregulated (hsb-1(-) strain also showed significant upregulation in the hsf-1 overexpression strain, but this overlap was less than 18% for downregulated genes  and hsf-1 overexpressing animals, we used pathway enrichment analysis using GO databases to determine functional categories associated with the genes that were differentially expressed in these two strains. Inhibition of HSB-1 and overexpression of HSF-1 affected expression of genes representing overlapping biological functions (hsb-1(-) and hsf-1 overexpression strains  family genes that were found to be significantly upregulated in both hsb-1(-) and hsf-1 overexpression strains (Tables S1 and S2). Previous studies performed in mice have indicated an essential role of Hsf1 and Hsf2 genes in spermatogenesis (hsb-1(-) and hsf-1 overexpression strains in C. elegans represented multiple GO terms corresponding to sperm function (HSF-1 transcription factor in spermatogenesis (hsb-1(-) and hsf-1 overexpression strains  and hsf-1 overexpression strains (Tables S1 and S2). Interestingly, a recent study has shown a major role of tir-1 in mediating the life span extension associated with activation of p38 MAPK pathway in C. elegans  mutant (Tables S1 and S2). Previous studies have shown that ctl-2 activity is required for the longevity induced via reduced insulin/IGF-1-like signaling in C. elegans -specific upregulation of multiple members of the Skp1-related (skr) gene family (Table S1). The skr genes encode components of the proteasomal E3 ubiquitin ligase complex and have a role in mediating life span extension in insulin/IGF-1-like signaling mutants  strain, while class II DAF-16 targets are downregulated in these animals (hsb-1(-) or hsf-1 overexpression strains  or hsf-1 overexpression strains  was significantly higher than that expected by chance (P < 1.4 X 10−19 in hypergeometric test) (DAF-16 targets in hsb-1(-)-specific downregulated genes  was also significantly higher than that expected by chance alone (P < 5.45 X 10−5 in hypergeometric test) -specific upregulated genes and genes upregulated or downregulated in both strains) were not found to be significantly higher than that expected by chance (P > 0.05 in hypergeometric tests)  . In addiic test) . The numc tests)  and 7B.HSF-1 activity affected the expression of known longevity-regulating genes in C. elegans. For this comparison, we tested whether the genes identified to be differentially expressed in our RNA-Seq analysis have been previously annotated with longevity-related phenotypes on Wormbase (https://www.wormbase.org). We found that among the 1,784 genes that were upregulated in hsb-1(-) or hsf-1 overexpressing animals, 64 genes, i.e., ∼3.6% have known longevity-regulating functions . However, this higher proportion of known longevity genes among DAF-16 transcriptional targets might be because in C. elegans, the longevity-promoting roles of insulin/IGF-1-like signaling have been more extensively characterized compared to other less-studied life span regulating pathways. To account for this potentially confounding factor, we performed this comparison only within gene lists that solely comprised of DAF-16 targets. We found that after accounting for the increased proportion of life span-regulating genes among DAF-16 transcriptional targets, the percentage of such longevity genes was not significantly higher in either hsf-1 overexpression-specific or hsb-1(-)-specific upregulated genes (P > 0.05 in hypergeometric tests). In both these categories, only 6.25% of the class I DAF-16 targets had known life span-regulating functions in C. elegans (DAF-16 targets that were upregulated in both hsb-1(-) mutant and hsf-1 overexpressing animals (DAF-16 targets were found to be upregulated via both HSF-1 overexpression and HSB-1 inhibition (DAF-16 targets was taken into consideration (P < 0.001 in hypergeometric test). In summary, we found that increased HSF-1 activity resulted in transcriptional upregulation of numerous DAF-16 target genes that have life span-regulatory functions in C. elegans , genes that are at least partially required for the life span extension phenotype in daf-2 mutant animals  and hsf-1 overexpressing animals (Tables S1 and S2), but is not required for the long life span of daf-2 mutant animals  mutant animals have known longevity-related functions  and hsf-1 overexpression strains relative to wild-type animals  and hsf-1 overexpression strains by using two independent biological replicates of N2 for normalization. Using this method, we found that 191 out of the 214 genes were either significantly upregulated (172 genes) or significantly downregulated (19 genes) in both hsb-1(-) and hsf-1 overexpression strains relative to wild-type , indicating the presence of common regulatory mechanisms for these genes in hsb-1(-) and hsf-1 overexpressing animals.We speculated that genes that are differentially expressed in the same direction by both  animals  and 8A.  animals . Howevervariates . Hence, ild-type . In conthe other . The prohsb-1(-) and hsf-1 overexpressing strains, we found a strongly correlated expression pattern even when two independent wild-type control datasets were used for normalization  (hsb-1(-) animals relative to wild-type as observed in our RNA-Seq data  measured using quantitative RT-PCR did not precisely represent the value determined from RNA-Seq (hsb-1(-) strain was the same irrespective of whether RNA-Seq or quantitative RT-PCR was used to measure transcript abundance  . As desc 0.0001) , more th 0.0001) . Finally 0.0001) . Among tSeq data . For som RNA-Seq . This isbundance . Hence, HSB-1 as an evolutionarily conserved negative regulator of HSF-1 that physically binds to the HSF-1 protein and sequesters it in an inhibitory complex  and hsf-1 overexpression strains (HSF-1 protein level is not elevated in hsb-1(-) animals (in vitro HSE binding induced via HSF-1 overexpression is presumably due to the elevated HSF-1 protein level in that strain (in vitro HSE binding phenotype observed in hsb-1(-) animals can possibly be a consequence of yet unknown factors such as increased nuclear localization of HSF-1, acquisition of PTMs that favor DNA binding, or a combination of both  mutant and hsf-1 overexpression strains have a strongly correlated expression pattern  and hsf-1 overexpression strains in our quantitative RT-PCR experiments . We found that this was due to very low sequencing read counts for the hsp genes across all the samples. Quantitative RT-PCR data indicated that the expression levels of these hsp genes were ∼10,000-fold lower than that of housekeeping genes in non-stressed conditions (data not shown). Hence, higher sequencing depth can potentially identify the difference in transcript levels of C. elegans genes that have extremely low basal expression in normal physiological conditions. Among the genes identified in our transcriptomic analysis, it remains to be determined which of those are causally linked to the life span extension phenotype in the hsb-1(-) mutant. It will be informative to estimate the extent to which inactivation of individual genes affects the life span of hsb-1(-) animals. However, the longevity phenotype associated with HSB-1 inhibition is most likely an additive effect of the contributions of numerous HSF-1 target genes identified in this study and might also involve epistatic interactions between those downstream targets. Moreover, it is possible that certain differentially expressed transcripts in the hsb-1(-) strain are regulated in an HSF-1-independent manner. Characterization of how HSF-1 genomic occupancy is altered in hsb-1(-) animals will help to identify loci that are directly under the control of HSB-1/HSF-1 pathway.Our transcriptomic analyses show that a sizeable fraction of differentially expressed genes in the  pattern  and 8C, eriments  and 2E, mtl-1, dod-3, lys-7 and pha-4, that are upregulated in the HSF-1-dependent long-lived strains  mutant strain (HSF-1 target genes. A recent transcriptome-wide study has reported that HSF-1 regulates the expression of more than 2,000 genes independently of the heat shock response in C. elegans (HSF-1-regulated transcripts do not overlap with a gene expression dataset for aging-induced transcriptional changes in C. elegans (HSF-1 activation might inadvertently affect numerous biological pathways in addition to the ones involved in longevity regulation. Since mammalian HSF1 has been shown to support progression of highly malignant cancers (Nonetheless, our RNA-Seq analysis has identified several known longevity-promoting genes, such as  animals  and 5B. t strain  and 5B, In summary, our study provides a better understanding of the function and regulation of heat shock factor in non-stressed physiological conditions. The findings from this study can potentially guide the design of targeted therapies to exploit the untapped potential of this evolutionarily conserved longevity-promoting factor in delaying age-associated physiological decline in complex organisms.