STAR proteins are evolutionary conserved mRNA-binding proteins that post-transcriptionally regulate gene expression at all stages of RNA metabolism. These proteins possess conserved STAR domain that recognizes identical RNA regulatory elements as YUAAY. Recently reported crystal structures show that STAR domain is composed of N-terminal QUA1, K-homology domain (KH) and C-terminal QUA2, and mRNA binding is mediated by KH-QUA2 domain. Here, we present simulation studies done to investigate binding of mRNA to STAR protein, mammalian Quaking protein (QKI). We carried out conventional MD simulations of STAR domain in presence and absence of mRNA, and studied the impact of mRNA on the stability, dynamics and underlying allosteric mechanism of STAR domain. Our unbiased simulations results show that presence of mRNA stabilizes the overall STAR domain by reducing the structural deviations, correlating the ‘within-domain’ motions, and maintaining the native contacts information. Absence of mRNA not only influenced the essential modes of motion of STAR domain, but also affected the connectivity of networks within STAR domain. We further explored the dissociation of mRNA from STAR domain using umbrella sampling simulations, and the results suggest that mRNA binding to STAR domain occurs in multi-step: first conformational selection of mRNA backbone conformations, followed by induced fit mechanism as nucleobases interact with STAR domain. Well studied examples include Splicing Factor 1 (SF1) mediating the intron recognition during spliceosome assembly4, Src-associated during mitosis 68-kDa protein (SAM 68) regulating alternative splicing in response to extracellular cues8, and Quaking related (QR) proteins12, critical in modulating development processes such as mammalian spermatogenesis (mice QKI), metazoan central nervous system development (GLD-1 in worms)16, sperm-to-oogenesis in hermaphrodites (GLD-1)19, or Drosophila wing development (HOW in flies)22. In humans, QKI proteins have been reported to be associated with numerous human pathologies like cancers23 and neurological disorders such as human inherited ataxia, multiple sclerosis, or schizophrenia25. These recent findings warrant the need to understand the molecular basis of RNA recognition, binding, and regulation by STAR proteins.STAR  family of proteins are mRNA-binding proteins linking signal transduction with post-transcriptional gene regulation at various levels, such as mRNA shuttling, pre-mRNA splicing, and all stages of RNA metabolism24. STAR domain consists of N-terminal dimerization QUA1 domain, followed by mRNA binding extended single heterogeneous nuclear ribonucleoprotein K- Homology (KH) domain28. The latter is a conventional type I KH domain of β1α1α2β2β3α3 topology which recognizes four nucleotides of RNA by van der Waals forces, hydrophobic and electrostatic interactions29. Further downstream 2-3 nucleotides are recognized by fourth helix of C-terminal QUA2 domain28. Due to high sequence similarity, STAR family of proteins bind identical RNA regulatory elements (RREs) YUAAY irrespective of their regulatory consequences32. Structure of the intact QKI STAR domains in complex with in vivo high affinity RNA targets has recently been solved28, revealing relative arrangement of QUA1, KH, and QUA2 domains within each subunit of STAR homodimer. Both KH and QUA2 form an extended interface with bound mRNA  simulations to derive this information by studying the dynamics of intermolecular interactions in mRNA bound complexes of STAR domains of QKI. MD studies have been reliably applied previously to complexes of RNA with U1A protein containing the most abundantly found RNA recognition motif37. Therefore, the current study also aims to expand our understanding of the recognition of RNA elements by the second most occurring recognition fold in protein, K homology fold in STAR proteins.Interestingly, all these proteins share a hallmark STAR domain of ~200 amino acids that recognizes and binds mRNA, and is conserved from yeast to humansA Figure . AuthorsHere, MD simulations have been carried out for STAR domain of Quaking protein in presence and absence of bound mRNA. Since our aim is to investigate influence of mRNA binding onto STAR domain, we have ignored the information of N-terminal dimerization QUA1 domain, and considered only truncated KH-QUA2 domain, as the latter is solely responsible for mRNA binding. We then analyzed the modes of dynamics using principal component anlaysis within the simulated systems and identified allosteric communications within the networks created using contact information and correlation data. Later on, we employed umbrella sampling technique to investigate how mRNA unbinds from pocket of STAR domain.28: 4JVH (residues 69–204). In addition, RNA free conformations of QKI proteins were also simulated by removing mRNA coordinates from these mRNA-bound complexes. Herein, we refer to mRNA bound KH-QUA2 domain as HOLO state, and artificially generated mRNA free KH-QUA2 structure as APO state.Molecular dynamics (MD) simulations of monomers of QKI with bound mRNA were carried out with explicit solvent. As our aim is to understand mRNA recognition and binding, we considered only mRNA binding KH-QUA2 domain for this study. Coordinates for mRNA bound KH-QUA2 domain of QKI were extracted from PDBid38 was used to describe molecular interactions. All simulations were run with NAMD2.1139. The complexes were solvated in a rectangular TIP3P solvent box40 and neutralized with Na+ ions41, resulting in simulation box size of 84Åx83Åx84Å consisting ~60,000 atoms. Additional Na+ and Cl− ions were added at a concentration of 0.15 M NaCl salt. Long-range electrostatic interactions were treated using the Particle Mesh Ewald (PME) technique42 as implemented in NAMD43. A non-bonded cut-off of 12 Å was applied to the Lennard-Jones potential and a cut-off for the direct-space part of the Coulomb forces with a switching function starting at distance 10 Å and reaching zero at 12 Å. A 2 fs time step was used for all MD simulations in combination with SHAKE44 to holonomically constrain bonds involving hydrogens. Rigid water molecules were constrained using the SETTLE algorithm45. The systems were minimized under harmonic restraints of 2 kcal/mol/Å2 in three steps. Initially, the backbone atoms of the protein and RNA were restrained while allowing only the water molecules to reorient for 50,000 steps. Then, restraints on only Cα atoms of protein were applied to allow the protein and RNA to relax during an additional 50,000 steps of minimization. Finally, the restraints were reduced to 1 kcal/mol/Å2 and the structures were minimized further for another 50,000 steps. The minimized structures were heated gradually from 0 K to 300 K at a rate of 30 K/60 ps while still maintaining the restraints. The simulation at 300 K was then continued for 100 ps before gradually releasing the restraints from 1 kcal/mol/Å2 to 0 during another 200 ps. The final structures were then equilibrated for 10 ns under NPT ensemble. The simulation temperature and pressure was maintained at 300 K and 1 atm using Langevin dynamics46 and Nose-Hoover Langevin piston method48, respectively. After equilibration, structures were subjected to NPT simulations. This method was repeated four times with different initial velocity assignments using random seed method to generate four independent production runs. The four runs span different simulation times of 75 ns, 100 ns, 200 ns, and 250 ns; reaching a total simulation time of 0.625 µs for mRNA bound complexes. Similarly, mRNA free APO proteins were simulated three times generating three independent production runs spanning simulation times of 100 ns, 150 ns and 250 ns; resulting in total simulation time of 0.5 µs.The CHARMM36 force field with the CMAP correctionrmscorr command49 in CPPTRAJ50. For RAC calculation, the fit was done over Cα atoms of running average structures of residues 69–204 over the full trajectories calculated at each time interval from 0 ps to 250 ns referenced in the RMS fit to the average structure over the entire trajectory run. For evaluation of native contacts, we calculated for two measures: Q, the fraction of native contacts and Qs, similarity of natively contacting residue pairs to their native distances using carma software51. For Q and Qs calculation, a native contact is defined when Cα atom of one residue interacts with Cα of another residue (excluding the adjacent two neighboring residues) within cutoff distance of 8.0 Å. Qs is similar to Q except that a Gaussian penalty is introduced if the native contact is far from its native distance52. Native contacts between KH-QUA2 domain were calculated for KH-QUA2 domain after pooling in all the conformations sampled at every 2 ps during different trajectory runs. Variations in interactions between mRNA and protein residues within conformation sampled at every 2 ps were analyzed using VMD for different trajectory runs of HOLO state.Trajectory analysis or in particular, structure analyses involving the deviations , intramolecular contacts, native contacts within RNA binding KH domain, protein-mRNA contacts, were carried out using VMD. RMSD and RMSF calculations have been done with reference to crystal structure, and for conformations sampled at every 2 ps during runs. Structural convergence of different runs was assessed based on computation of root mean square average correlation (RAC) of protein KH-QUA2 domain at different time intervals using the 54. A variance-covariance matrix was constructed using Cα atoms after pooling in all the conformations (sampled every ps) from the trajectories, and time-dependent projections of the first three principle components onto the trajectories have been studied. Contact map was constructed for Cα atom of crystal structure using Bio3D package, considering contacts between cutoff of 8 Å, excluding neighboring residue.Principal component analysis has been done with Bio3D package written in R56 of VMD. The dynamical networks were constructed using data from all the trajectories of the protein-RNA complexes sampled every 2 ps. For each molecular system, a network graph was constructed with two nodes for each nucleotide molecule, N1 and N9 atoms were used to define the nodes for the base atoms for pyrimidines and purines, respectively; and phosphorus, P atom was used to define the nodes for the sugar and backbone phosphate atoms. To define nodes for each protein residue, Cα atoms were used. All the conformations were pooled in to calculate the local-contact matrix, where a contact was defined between the two nodes (excluding the neighboring nodes) within 4.5 Å, and observed for at least 75% of the simulation time. The so-constructed contact matrix was then weighed by the correlation values of the two end nodes, where Cij is the correlation matrix calculated as 51, and the shortest paths between two nodes in the network were found using the Floyd-Warshall algorithm57. Characteristic path lengths (CPL), average of all the shortest paths, were calculated as indicative of size of networks for both HOLO and APO states. The community structure was identified by using Girvan-Newman algorithm58, which uses edge betweenness to detect community peripheries. Betweenness of an edge is defined as the number of shortest paths between pairs of nodes that run along it, and is a measure of influence of a node over the flow of information between other nodes. Community detection is a iterative process, where each cycle consists of calculation of betweenness of all edges in the network, followed by removal of edge with the highest betweenness until no edge remain.Allosteric networks within the proteins were identified using the NetworkView plugin61 to investigate the unbinding of mRNA from STAR domain. In order to simulate the unbinding process, distance between the centers of mass defined by group of atoms of STAR domain as well as for mRNA was used as reaction coordinate (RC). For mRNA, the P and O5’ atoms of nucleic backbone of nucleotides 5 to 9 were used to calculate the center of mass. For STAR domain, center of mass was calculated for group of Cα atoms present within 5.0 Å of mRNA in crystal structure. The RC was extended from initial distance of 10.5 Å to 20 Å  was constructed along the RC using Weighted Histogram Analysis Method (WHAM)66, after discarding the first 5 ns as equilibration period. Error bars were calculated with Monte Carlo bootstrap error analysis. RC was separated into 1000 bins for the WHAM calculation, with iteration tolerance value set to 0.0001. Temperature was set to 300 K to keep consistence with the simulation temperature.The aim of this study is to investigate the dissociation of mRNA from STAR domain, and not to calculate the binding free energy. Thus, we did not use the earlier proposed constrained scheme for ligand unbinding67. To investigate the energy profile as mRNA explored different conformations within each US window, we calculated two-dimensional PMF along the rmsd of backbone atoms of mRNA as additional degree of freedom and biased RC. The rmsd values were calculated with respect to crystal structure for backbone atoms of nucleotides 5 to 10 (excluding O1P and O2P oxygen atoms of phosphate backbone moiety) for conformation sampled within each window, and these additional coordinates were added to the biasing coordinates with zero force constant. For obtaining two-dimensional PMF profile along RC and rmsd, the data was binned into 500 bins for 2D-WHAM calculation with tolerance value of 0.0001 and temperature set to 300 K.It is possible to estimate multidimensional PMFs along additional degrees of freedom, whether biased or unbiased, with the assumption that all other degrees of freedom orthogonal to the biasing coordinates were thoroughly sampled68. The backbone pseudo-torsion angles69 were defined as: η: C4′(i-1)-P(i)-C4′(i)-P(i + 1) and θ: P(i)-C4′(i)-P(i + 1)-C4′(i + 1).Backbone conformations sampled by mRNA within each window during umbrella sampling was quantified in detail using two measures: sugar puckering configurations and pseudo-torsion angles. These calculations were performed for mRNA conformation sampled using 3DNA softwareWe have carried out simulations of mRNA bound and mRNA free extended KH (KH-QUA2) domains of QKI proteins. Throughout this manuscript, for convenience and clarity, we will refer these mRNA bound structures as HOLO states and mRNA free structures as APO states.We analyzed changes in root mean square deviations (RMSD) values of the protein backbone atoms of QKI domain with respect to the crystal structure coordinates in response to the presence or absence of mRNA. Figure The root mean square fluctuations (rmsf) is another indicator of the flexibility of certain residue during simulations. We calculated rmsf values of Cα atoms of each protein residue, averaged over all the conformations sampled during different independent simulations runs for both HOLO and APO structures. For comparison with crystal structure, we converted B-factors or temperature factors to rmsf values by using Debye-Waller formula 49. For QKI system, we fit each trajectory to the overall average structure and observed that for both HOLO and APO states: as simulation time increases, RAC slope smoothly decreases nearing zero at 250 ns  average correlation (RAC). A converged trajectory is when slope of RAC values approaches zero, indicating no further changes in the average structure as sampling time increasess Figure . However33 shows significant flexibility in C-terminal QUA2 domain with disordered helical structure and possesses different orientations with respect to α6 of KH domain  for each conformation sampled during all the simulation runs for HOLO and APO states. Plotting the probability distribution functions for Q  and the similarity of natively contacting residue pairs to their native distances  separates conformational space of a system into essential subspaces by filtering global slow motions from the fast motionsWe combined the correlation data obtained from MD simulations with the structure-based network analysis to determine evolution of residue interaction networks in presence or absence of mRNA. Protein structure networks were constructed by incorporating the topology-based residue connectivity in combination with the contact maps of residue cross-correlations obtained from MD simulations. Each residue and nucleotide represents a node in the network, and two nodes are connected by an edge if (a) nodes are non-neighbors, and (b) they are in contact within 4.5 Å of each other for more that 75% of simulation time. The significance of node is determined further by the dynamic information flow through that edge as measured by the correlation between respective nodes. The extent of correlation between the two nodes is depicted by the width of the edge, with wider edges indicating strongly correlated nodes. The weighted dynamical network representations for HOLO and APO states in Fig. We analyzed the variations in the connectivity of networks in response to mRNA by viewing the changes in formation of local communities Fig. . Nodes wet al.54 observed that for allosteric signal transmission in the aaRS:tRNA complex, nucleotides involved in communication significantly increased the edge CPL. Similarly, for STAR-mRNA complex, nucleotides that significantly increased the edge CPL are the ones forming direct interactions with STAR domain: U6, A7, and A8. These residues form part of invariant core sequence observed via genome-wide search of STAR binding element of QKI: NA(A > C)U(A≫C)A32. The stronger correlation of these nucleotides with STAR domain is also reflected in their interaction analyses. These three nucleotides form consistent native interactions with their interaction partners in STAR domain during all simulation runs compared to other nucleotides in the mRNA element  upon edge removal for each nucleotide Fig. . Sethi et Figure .We also analyzed variations in CPL upon complete removal of nodes Figure  and edge71. Another hydrophobic-to-polar mutation I155N showed severe developmental defects in zebrafish72. We analyzed solvent accessible surface area (SASA) values for these residues and observed average values as: I155 (0.06 ± 0.29), V157 (5.93 ± 3.97) for HOLO state, and I155 (0.06 ± 0.25), V157 (5.06 ± 4.05) for APO state simulations. Lower SASA values observed for these residues irrespective of mRNA presence indicate that these residues are buried within the hydrophobic pocket, and suggest that their mutation to polar residues will affect mRNA binding by strongly impairing the protein stability.Deleterious effects have been observed for N-ethyl-N-nitrosourea (ENU)-induced hydrophobic-to-polar point mutation, V157E in KH domain of QKI19. In QKI, these residues are equivalent to: G77, P94, G104, G125, G127, A171, G185, and D187, respectively. Teplova et al.28 investigated in vivo and in vitro RNA-binding affinities with the mutations of key amino acids within the KH and QUA2 domains of QKI contacting specific bases of mRNA. Three double-mutants were identified: K190A/Q193A, N97A/R130A, and K120A/R124A28. As measured by ITC experiments K190A/Q193A mutation resulted in 2-fold reduction in in vitro RRE binding affinities, N97A/R130A mutation drops affinity by 10-fold, and K120A/R124A by 20-fold. Similar trend is observed for in vivo RRE binding quantified with PAR-CLIP. The signal for K190A/Q193A was reduced 5-fold, the signal for N97A/R130A was reduced 10-fold, and the signal for K120A/R124A was reduced 20-fold compared with wild-type protein.In homologous GLD-1 protein, eight missense mutations abolishing essential GLD-1 function in the germline have been identified: G200E, P217L, G227D, G248R, G250R, A294T, G308E, and D310NSpatial organization of these residues in the bound mRNA-STAR domain complex indicates Fig.  that proConventional MD simulations have their limitations when it comes to simulate transition processes involving higher energetic barriers. For instance, simulation of dissociation of mRNA from bound STAR domain may take even more than millisecond of level of conventional simulations. To overcome this problem, we carried out umbrella sampling simulations to investigate unbinding process of mRNA from KH-QUA2 domain of QKI protein. We considered reaction coordinate as separation distance of mRNA from QKI domain, and from initial value of 10.5 Å, the distance was extended to 20 Å. We calculated PMF as a function of this reaction coordinate to determine the energetics of dissociation of mRNA from bound QKI-STAR complex Fig. . The comAs we investigate further the conformational sampling of mRNA along the RC, we calculated two-dimensional PMF along biased reaction coordinate and unbiased coordinate as rmsd of mRNA with respect to crystal structure Fig. . We obseendo and 8–11 are C3′-endo. Looking at the puckering behavior of these residues, we observe that as mRNA dissociates from complex, the nucleotides 4–7 show transitions from C2′-endo to C3′-endo and occasionally to O4′-endo as well. However, nucleotides 8–11 remain primarily as C3′-endo. This similar behavior is reflected in behavior of pseudo-torsions, where η-θ plots are analyzed and compared with crystal structure bound mRNA  domain of STAR mammalian QKI protein. mRNA binds to KH domain by interacting with residues from helices α3, α4, strand β2, conserved GPRG, and loops connecting β2 and α5 of KH domain. The binding is further extended by helix α7 of QUA2 domain. Presence of mRNA lowers the deviations and fluctuations for the interacting regions within KH domain. Single helical QUA2 domain on the other hand is quite flexible irrespective of mRNA presence. Presence of mRNA influences the correlated motions within STAR domain as self-correlation within these binding regions decreases or changes in absence of bound mRNA. The underline reason behind this is attributed to variations in intra-residual contacts in KH-QUA2 domain in presence or absence of mRNA. Total number of intramolecular contacts within KH-QUA2 domain increases in absence of mRNA, though number of contacts within KH domain are less in APO state than in HOLO state. In APO state, flexible C-terminal QUA2 domain is free to have more interactions within itself and with mRNA-free KH domain. On the contrary, native contacts are maintained in presence of bound mRNA throughout the simulations of HOLO state. The first principal mode detected with PCA of APO state showed opening motions for mRNA binding cleft in absence of mRNA, indicating flexibility of KH-QUA2 domain where mRNA bind onto.We further analyzed the KH-QUA2 domain in absence and presence of mRNA as network of interactions between the residues, with residues defined as nodes and interactions within them as edges. These edges were weighed with correlation data, and stronger correlations are observed in presence of mRNA. We further divided the network into local communities, and observed distinct communities in HOLO and APO states. C-terminal QUA2 domain in both HOLO and APO state forms one distinct community. More communities are observed in mRNA binding region of KH domain in APO state than in HOLO state. We computed differences in characteristic path length upon removal of each node or edge in the network. Noteworthy, we found that if we remove nodes or edges consisting nucleotides or residues that are experimentally reported significant for binding and regulation of mRNA by STAR domain in QKI or related STAR proteins, considerable differences in characteristic path length are observed.We further investigated dissociation of mRNA from KH-QUA2 domain using enhanced umbrella sampling simulations. PMF profile calculated along biased reaction coordinate suggested that mRNA dissociation is an energetic unfavorable process, with minima near the bound values of complex. We further explored PMF along rmsd of mRNA with respect to the crystal structure as additional degree of freedom, and observed that even at higher RC values (indicating dissociated mRNA from STAR domain), few minima at lower rmsd values are observed. Mapping mRNA conformations to such regions, we observed that mRNA is able to adopt backbone conformations in absence of bound protein but the nucleobases adopt different conformations. This was further substantiated with calculation of sugar puckering angles and pseudotorsions to define backbone conformations of mRNA sampled within each umbrella sampling simulation window.77 as well. In order to delineate exact mechanism of mRNA binding, more extensive simulation studies are required which are beyond the scope of this research and is a subject of further interest.Based on our analysis on conventional and umbrella sampling simulations, we propose that mRNA binding is multi-step process. In APO state, STAR domain is flexible around mRNA binding cleft region formed by helix α5 on left side of cleft, and rest of KH and C-terminal QUA2 domain on right side of cleft. mRNA in free state is able to adopt multiple conformations, out of which extended backbone conformations similar to crystal structure are binding competent forms. Such conformations successfully interact onto the cleft region, and the nucleotides rearrange to form specific interactions with STAR domain via induced fit mechanism. A multi-step binding mode has very well observed in other biological complex systemsBy using conventional simulations, we have investigated the influence of mRNA binding onto the KH-QUA2 domain of STAR Quaking (QKI) protein. The effect of mRNA binding has been analyzed on the basis of deviations, correlations, intramolecular contacts, and interaction network. Our results mapped with the experimental mutational data reported. We further explored the dissociation of mRNA from STAR domain by employing enhanced umbrella sampling techniques and we observed that binding of mRNA onto STAR domain is an interplay of conformational selection of extended mRNA backbone conformations followed by induced fit of nucleobases to their amino acid partners in STAR domain.Supplementary File


The single molecule force-induced DNA helix-destabilizing activitiesas well as the single- and double-stranded DNA affinities of ΔPR201 and gp32 truncated at residue 295 also fall between full-length protein and *I. Finally, chemical cross-linking of recombinant C-domain and gp32 lacking both N- and C-terminal domains is inhibited by increasing concentrations of a short single-stranded oligonucleotide, and the salt dependence of cross-linking mirrors that expected for the model. Taken together, these results provide the first evidence in support of this model that have been obtained through structural probes.The model single-stranded DNA binding protein of bacteriophage T4, gene 32 protein (gp32) has well-established roles in DNA replication, recombination, and repair. gp32 is a single-chain polypeptide consisting of three domains. Based on thermodynamics and kinetics measurements, we have proposed that gp32 can undergo a conformational change where the acidic C-terminal domain binds internally to or near the single-stranded (ss) DNA binding surface in the core  domain, blocking ssDNA interaction. To test this model, we have employed a variety of experimental approaches and gp32 variants to characterize this conformational change. Utilizing stopped-flow methods, the association kinetics of wild type and truncated forms of gp32 with ssDNA were measured. When the C-domain is present, the log-log plot of  Bacteriophage T4 gene 32 protein is a model single-stranded DNA binding protein (SSB), with well-established roles in DNA replication, recombination, and repair, as well as in the control of its own expression at the translational level.–7 There double-strandedDNA, which is significantly higher for the *I truncate (protein minus the C-domain) relative to intact protein.The C-domain also creates a “kinetic block” to the protein’s thermodynamically-predicted ability to lower the thermal melting temperature (Tm) of natural double-stranded DNAs., 21, 22 +, the acidic C-domain of intact protein blocks the ssDNA binding surface on the core domain, and must dissociate from this site prior to binding nucleic acid , similar to the salt dependence of the affinity of the protein for an isolated single-stranded site (Kss), log Kssvs. log [NaCl] . This reflects the release of Na+ ions from the nucleic acid and Cl- ions from the protein upon formation of the complex. However, a striking discontinuity in this plot was seen at low [NaCl]: between 0.02 and 0.1 M salt, the log k—log [NaCl] plot showed a distinctly positive slope (~ 3). This highly unusual salt dependence was interpreted as the result of electrostatic repulsion between the negatively-charged polynucleotide and the negatively-charged protein (the pI of 32 protein is about 5) plot.[-] is too low to affect binding of these anions to the uncovered core surface, but at higher [NaCl], above 0.2 M, where Cl- ions are bound to this cationic surface, the rate-determining step follows the release of both these Cl- ions as well as Na+ (from DNA) to the bulk solution, and the slope of the log k–log [NaCl] plot is therefore negative. Since at this [NaCl] the protein is already in its open form prior to interacting with the ssDNA, there is no binding or release of Na+ ions at the C-domain.The measured salt dependence of the association rate constant reflected these two binding modes: At high salt concentration, weak binding conditions, the log  about 5), a facto about 5), 35 BeloClearly, the proposed salt-dependent conformational change is a critical factor in the functioning of gene 32 protein. Although there is substantial thermodynamic evidence in favor of this model, all of it is indirect. Here we provide strong evidence for the conformational change, utilizing stopped-flow kinetic, DNA stretching, and cross-linking methods. These experiments employ gene 32 protein variants mutated within the C-domain , as wel5’-AGCTCTGGTAGTTCATCTAGTGCTGATGACCTTTTGAATGACCTT-3’, forward, and 5’-AAGGTCATTCAAAAGGTCATCAGCACTAGATGAACTACCAGAGCT-3’, reverse). The altered plasmids obtained were transformed into E. coli DH5α. Colonies containing the deletions were identified by restriction analysis, and subsequently verified by sequencing. The appropriate fragments were then inserted into digested pYS6. Induction, overexpression, and purification of the mutated protein was performed as described for wild-type and truncated proteins., and applied to a Q Sepharose Fast Flow anion exchange column, equilibrated in the above buffer with 0.1 M NaCl. The column was subjected to a salt gradient, and the CTD was seen (via SDS-PAGE) to elute between 0.25 and 0.30 M NaCl. Fractions containing the CTD were concentrated and further purified via successive runs on Centriprep 30 and Centricon Ultra membranes , which, as observed on SDS-PAGE, eliminated all contaminating polypeptides with molecular weights higher than that of the CTD. The flow-through from the 30 kDa membranes was then applied to Ultra-4s membranes (5 kDa MWCO), and the retentate yielded >95% pure CTD. CTD concentration was determined spectrophotometrically, based on its content of six phenylalanine residues, ε258 = (6 x 190) M-1cm-1. should be linear, with the slopes yielding the second-order association constant, kf, and the y-intercepts providing an estimate of the dissociation constant, kr. This relationship clearly holds for the fast decay of *I, as well as the single exponential decays of *II and *III (The bimolecular association of protein (P) and DNA (D) to form complex (PD), and the dissociation of the complex, can be simply described asand *III . The reskobs (τ-1)for *I and *III are similar. The corresponding relaxation times for *II are significantly longer, and similar to the fast decays of full-length gp32.[As seen in gth gp32.kobsvs. [poly(dT)] plots in kobs ≈ kf[D] for these two truncates. The slopes obtained for the corresponding plots with the intercepts set at 0 vary by only about 10%  at these low salt conditions, where the need to undergo a conformational change involving the blocking C-domain slows down the association rates. This impediment does not exist for *I and *III, which lack the C-domain.The y-intercepts for the kfvs. log [NaCl] plot for *I shows a striking discontinuity between 0.1 and 0.4 M NaCl. At salt levels where the rate determining step is governed by the formation of contiguous protein clusters (> 0.3 M NaCl), the slope of the log kfvs. log [NaCl] (~ -3) for *I is similar to that of the intact protein; the rate constants for *I are about three times greater than for the intact protein. Between 0.02 and 0.1 M NaCl, where the rate determining step is the formation of non-cooperatively bound protein (strong binding conditions), the dependence of the association rate constant on [NaCl] is vastly different for the two proteins. With *I,kf increases moderately with increasing salt concentration; the log kfvs. log [NaCl] plot has a slope of about 0.3. The corresponding slope for intact protein is about five times this value (1.7). Although the magnitude of kf was always larger for *I, the differences were seen to be greatest at 0.02 M NaCl, where the forward rate was thirty-fold greater than for 32 protein.The effect of salt on the fast association rate constant for *I was determined over a wide range of NaCl concentrations  and *III (0.2) are very similar to those of intact 32 protein and *I, respectively. Although the data for *II is an approximation, since the dependence of kobsvs. [poly(dT)]p for this truncate does not yield a y-intercept of 0, the similarity of the [NaCl] dependence of *II and full-length protein is remarkable.The association kinetics of the two forms of the protein that lack the N-domain, *II (core and C-domains) and *III (core domain), were also studied. Since neither of these truncates bind ssDNA cooperatively, we restricted these experiments to “strong” binding conditions, 0.02–0.1 M NaCl. As can be seen in + ions by the C-domain as a consequence of the closed → open conformational change that occurs under these conditions.These results indicate that, under strong binding conditions, the presence of the C-domain in the protein brings about a significant positive slope in the salt dependence, and when it is absent, there is little variation of association rate with salt. Taken together with the corresponding data obtained with intact protein and *I, it is clear that the C-domain has a critical effect on the salt dependence below 0.2 M NaCl. The results are fully consistent with the uptake of Nakf between 15 and 30°C in 0.02 M NaCl, the salt concentration where the association rates among the different forms of the protein are most different; the results are tabulated in kfvs. 1/T plots  than for *I (~-45 kJ/mol). Thus, the much lower values of kf for whole protein relative to *I are due to the significantly more negative value of ΔS‡. The analogous data for the non-cooperatively-binding *II and *III  shows the same trend. There is relatively little variation of rate with temperature (ΔH‡ ~ 25 kJ/mol), and the ΔS‡ values for *II and *III are, respectively, ~-60 kJ/mol and ~-34 kJ/mol. The negative entropies of activation, seen for all the proteins, indicate that the transition states are more ordered than the reactants. The effect is accentuated when the protein possesses the C-domain. Although the values for ΔS‡, obtained by extrapolation, are approximate (and the kinetic data for *II is subject to the caveat discussed in the previous section), there clearly are significant differences in the activation entropies, ΔΔS‡ ~ -50 JK-1mol-1 for whole protein vs. *I, and ~ -25 JK-1mol-1 for *II vs. *III. We further discuss this observation in the Discussion.We measured the variation of /T plots  yielded Additional kinetic evidence for the conformational change involving the C-domain was provided by stopped-flow association kinetics utilizing the ΔPR201 variant of gene 32 protein, where an in-frame 15-nucleotide deletion results in the loss of residues 292–296 (Thr-Asp-Leu-Asp-Asp), and, consequently, three negative charges. Interest+, over a short (~1 min) time scale neither of these proteins showed any effect on the force needed to denature single λ-DNA molecules, whereas*I reduced the this force, the overstretching force, by about 25 pN under. carbodiimide (EDC), coupledwith N-hydroxysuccinimide (NHS). EDC is a powerful coupling agent of carboxylic acid groups (in abundance in the Asp-rich C-domain). Although in principle it will also react with amines (lysines on core domain) the efficiency of this reaction is significantly increased by the addition of NHS.The cross-linking reaction between core and C-domain was optimized by variation of the ratio of the two proteins and the relative concentrations of EDC and NHS (see 7) on the cross-linking reaction reaction , top. Apge model , bottom.k vs. log [NaCl] in + ions when the C-domain is released from its binding site on the core domain (cf. + uptake (or release) associated with the C-domain.In the report, we have provided a variety of evidence for a conformational change involving the C-terminal domain of gene 32 protein when it binds to single-stranded DNA. Under low salt (“strong”) binding conditions, where the rate determining step of the association kinetics is the  formation of a non-cooperatively bound protein-DNA complex, the removal of the C-domain greatly alters the salt dependence of the kinetics. The positive slope plot of the log main cf. . The sam‡, which are all around 15–25 kJ mol-1. However, the ΔS‡ values, which are all negative, are considerably more negative for the forms that possess the C-domain. Thus, in all cases the transition state is more ordered than the reactants, and the presence of the C-domain (in whole protein and *II) very much increases this difference. One possible basis for this effect is that at low salt, the C-domain, while being predominantly in the “closed” conformation  and *II (-60 J K-1 mol-1).The activation parameters obtained at 0.02 M NaCl show a significant dependence on the presence of the C-domain. The variation in rates among the various forms of the protein cannot be attributed to differences in ΔHormation , is kinecf. ‡ value for whole protein relative to *II (whole protein minus the N-domain) suggests that the presence of this domain might be responsible for the difference. Residues 3–6 within the N-domain, Lys-Arg-Lys-Ser-Thr (the “LAST” Motif), are virtually identical to residues 110–114 within the core domain, Lys-Arg-Lys-Thr-Ser.[LAST) residues in the N-domain as it does when it binds to the core domain LAST residues, forming the closed, ssDNA-binding conformer. This additional conformation would lead to a higher net entropy for the unbound protein reactant, and therefore a more negative ΔS‡ .As we have noted, the association rate constants for *II are approximations, since the linear rate dependence of concentration for this truncate does not yield a zero or near-zero y-intercept, -Thr-Ser., 46 ConcThese results may reflect a more general regulatory mechanism for DNA binding. A similar mechanism was reported for the single-stranded DNA binding protein from T7, gp2.5., 47Both E.coli tetrameric SSB polypeptide consists of an intrinsically disordered 56-residue region with an acidic 9 amino acid terminus.[E. coli SSB C-domain is the site of interaction with a large number of proteins that function in replication, recombination, and repair.[Although there has been a suggestion that the C-domain of gene 32 protein can form an ordered α-helical bundle, there isterminus., 50 As id repair.E. coli SSB and the T7 gene 2.5 protein[The presence of an unstructured, acidic C-domain participating in a large number of heterotypic protein-protein interactions essential to DNA metabolism may be a property shared by many SSBs, including the C-domains of the 5 protein. With thExternal and internal protein-protein interactions are likely to involve (different) specific locations on the C-domain. This is well illustrated by the ΔPR201 variant of gp32, where we show that the loss of residues 292–296 in the C-domain significantly alters the ssDNA association kinetics and dsDNA helix-destabilization properties of this protein. A full understanding of the roles of the C-domain of gp32 and other SSBs in DNA metabolism will require delineation of other critical interactive and regulatory sites in these flexible, unstructured regions.


Mycoplasma hyopneumoniae (MYC) and Lawsonia intracellularis (LAW). It was hypothesised that herds purchasing vaccines, use these to prevent disease, and hence reduce their AM consumption, compared to herds purchasing fewer or no vaccines against these pathogens.There is growing concern about development of antimicrobial resistance due to use of antimicrobials (AMs) in livestock production. Identifying efficient alternatives, including vaccination, is a priority. The objective of this study was to compare the herd-level amount of AMs prescribed for weaner pigs, between Danish sow herds using varying combinations of vaccines against Porcine Circovirus Type 2 (PCV2), Data summarised over year 2013 were obtained from the Danish Central Husbandry Register and the Danish VetStat database, in which prescriptions of medication are recorded. All one-site indoor pig herds with >50 sows and >200 weaners were selected. AMs prescribed for weaners was measured in animal daily doses (ADD) and divided according to three indication groups . The analysis was based on three multivariable linear regression models of the herd-level ADD for each indication group. The eight vaccination combinations (2x2x2) were included as one explanatory variable, and herd size, measured as the number of weaner pen places was included in the models as a potential confounder.Out of the 1513 herds in the study, 1415 had AMs prescribed for gastro-intestinal disorders, and 836 for respiratory disorders. PCV2 vaccines were purchased in 880 herds, MYC vaccines in 787 and LAW vaccines in 115 herds. Herds purchasing PCV2 and MYC vaccines had significantly more AMs prescribed than herds not purchasing vaccines or only purchasing LAW vaccines.In the present study, using register data covering 1 year, we found an association between use of vaccination and increased amount of AMs prescribed for weaners. This does not exclude that the vaccines work, just that we were unable to detect this. The findings might be explained by some herds experiencing clinical problems associated with MYC or PCV2 despite use of vaccination. In other herds, it might reflect that vaccines applied to weaners are used for disease prevention in finishers rather than in the weaners. Information about vaccination protocols and herd health status was not available at the time of the study. Hence, further studies are required to investigate causality of the associations between use of AMs, vaccination practices and other confounding on-farm factors. In Denmark, there has been political and public focus on the use of antimicrobials (AMs) in livestock and the risk of development of AM resistance since the 1990s. Focus is in particularly on the Danish pig industry, because it is the largest livestock industry in Denmark; around 28 million pigs are produced annually, and around 10 million of these are exported as weaners  (c) incrTo support the Danish policy, data regarding medical consumption for production animals are collected in a national database called VetStat established mid-2000 . VetStatwww.foedevarestyrelsen.dk. By November 2014, the permit limits were further reduced to 22.9 ADD per 100 weaners per day (Please see www.foedevarestyrelsen.dk for further updates).Between 2008 and the first half of 2010, the AM consumption in pigs increased, leading to a public debate [The introduction of the Yellow Card scheme reflected the political pressure that is forcing Danish pig producers to reduce the usage of AMs on their farms. Therefore, efficient alternatives to routinely applied AMs have become crucial.Vaccines are being considered a potential tool to decrease the burden of animal diseases and also to reduce the need for AMs with therapeutic purposes , 7.Mycoplasma hyopneumoniae (MYC) (36 %), Porcine Circovirus Type 2 (PCV2) (26 %), and Actinobacillus pleuropneumoniae (APP) (8 %), whereas only 3 % of the vaccine doses were prescribed for Lawsonia intracellularis (LAW) and only 2 % for Porcine Reproductive and Respiratory Syndrome (PRRS). These endemic disease agents are representing common production-related diseases in weaners and finishers in modern pig production. We decided to focus on the effect of MYC, PCV2 and LAW. We included MYC and PCV2 because they are the most commonly used vaccines, and we included LAW to have a vaccine with an effect on gastro-intestinal lesions. We excluded PRRS for two reasons: 1) low use and 2) apparently, in Denmark PRRS vaccines are used more commonly in breeding animals than in weaners.According to data from VetStat, the three most commonly used vaccines in Danish pig production is against PCV2 has a causal role in a large number of clinical syndromes, which are collectively named as Porcine Circovirus Diseases (PCVDs) and is highly prevalent worldwide . The mosMYC is the primary agent responsible for swine enzootic pneumonia, which is a chronic respiratory disease that causes significant economic losses worldwide and is highly prevalent in most areas of pig production (present in between 38 to 100 % of the pig farms world-wide) . MYC preLAW is the causative bacterium of proliferative enteropathy, and it is a common high prevalence intestinal infection worldwide including Denmark . This haPCV2, MYC and LAW can be controlled and prevented by different interventions. In Denmark, these include all in/all out production, multisite production, increased hygiene, antibiotic medication and use of vaccination. In Denmark, these vaccines have been used as an alternative to antibiotic medication and to increase productivity in weaners and finishers. The use of these vaccines has increased substantially since 2010. This was observed in particular right after the introduction of the Yellow Card, e.g. the use of vaccines against PCV2 infections increased by 31 % [To explore the potential of using vaccination as an alternative to AMs, the present study was carried out using data from VetStat and the Danish Central Husbandry Register (CHR) from all one-site pig herds with >50 sows and >200 weaners in the year 2013. The objective was to compare the total amount of AMs prescribed for weaning pigs between Danish sow herds using varying combinations of vaccines against PCV2, MYC and LAW that year. It was assumed that year 2013 represented a steady-state in the use of vaccines and AMs. Hence, bias caused by confounding factors related to dynamics in overall health and production conditions including changes in legislation and market forces could be avoided. It was also assumed that the AMs and vaccines prescribed were used in the herd.The median number of sows in the 1513 herds was 435 and the maximum was 3100 sows. For weaners, the median number of pen places was 1500 whereas the maximum was 21,000. Around half (52 %) of the herds also had production of finishing pigs on the same premises.Out of the 1513 herds selected for the study, 1415 herds had AMs prescribed for gastrointestinal disorders in weaners, and 836 herds had AMs prescribed for respiratory disorders, corresponding to 94 and 55 % of the herds, respectively. There were no herds with no AMs prescribed.With respect to total AM consumption (AC-TOTAL), the median use was 10.0 ADD per 100 weaners per day . The herd-level distribution of the total AM consumption was not normal but positively skewed with 58 herds corresponding to 4 % having AM consumption above 28 ADD per 100 weaners per day, which was the initial Yellow Card threshold.The main part (67 %) of the AM consumption for weaners was prescribed for gastro-intestinal disorders. The overall median was 6.9 ADD per 100 weaners per day . The herd-level distribution of AM consumption with gastro-intestinal indication (AC-GI) was not normal, but positively skewed with 20 herds having AM consumption above 28 ADD per 100 weaners per day.The median AM consumption with respiratory indication (AC-RESP) was 2.5 ADD per 100 weaners per day . The herd-level distribution of AM consumption with respiratory indication was not normal; and 17 of the herds had AM consumption above 28 ADD per 100 weaners per day.n = 880) of the herds purchased PCV2 vaccines in 2013. MYC vaccination was purchased in 52 % (n = 787) of the herds, and LAW vaccination was the least used vaccine, with just 8 % (n = 115) of the herds having at least one registered purchase of Enterisol®Ileitis. A total of 380 herds did not have any of these three vaccines prescribed in 2013 . Some degree of confounding between herd size and the vaccine use variable was observed but only for the parameter describing use of PCV2 and LAW (n = 35 herds). The interaction between herd size and vaccine use was non-significant (P = 0.48). A model with vaccine use and herd size only explained 7 % of the variance in the total AM consumption . The highest use was observed in Group 4 (10.3 ADD/100 weaners/day), representing use of MYC and PCV2 vaccination, whereas the lowest consumption was observed in Group 6 (6.0 ADD/100 weaners/day), representing use of MYC and LAW vaccination. Group 1, 2, and 4, representing three different combinations of use of MYC and PCV2 vaccination, were all associated with a statistically higher AM consumption than the use of no vaccine at all (group 0); between 1.8 and 3.7 higher ADD per 100 weaners per day compared with group 0. The remaining vaccine combination groups were not associated with statistically different levels of AM consumption compared to the group not using any of the three vaccines (P > 0.05). Smaller herds had a significantly lower total AM consumption than medium-sized herds (6.6 versus 8.0 ADD/100 weaners/day), which again had a significantly lower consumption than large herds where the mean AM consumption was 9.2 ADD/100 weaners/day . Some degree of confounding between herd size and the vaccine use variable was observed but only for the parameter related to the group using LAW vaccine alone (n = 21 herds). The variable describing the vaccine use had a P-value of 0.2, and the interaction term between herd size and vaccine use had a P-value of 0.37. A model including vaccine use and production size only explained 0.6 % of the variance in the AM consumption   but some confounding between herd size and vaccine use was observed for two of the parameter estimates of the vaccine variable . The interaction term between herd size and vaccine use was non-significant (P = 0.80), whereas the variable describing vaccine use was statistical significant (P < 0.0001), but it only explained 4 % of the variance in the AM consumption . The lowest AM consumption was observed in Group 5, representing the use of PCV2 and LAW vaccination (0.6 ADD/100 weaners/day). However, this was not significantly different from Group 0, statistically speaking (1.6 ADD/100 weaners/day). Group 2 and 4 representing use of MYC vaccination with and without concurrent use of PCV2 vaccination were associated with a statistically higher AM consumption than the use of no vaccines (Group 0) – 3.1 and 3.2 versus 1.6 ADD/100 weaners/day. The changes in AM consumption associated with the rest of the combinations were not statistically significant (P > 0.05).In relation to the AC with respiratory indication Table , herd siAlmost all herds (96 %) had a total AM consumption lower than 28 ADD per 100 weaners per day This implies that the majority of the producers were able to raise weaners while fulfilling the requirements regarding AM consumption set by the Danish veterinary authorities.The statistical analyses showed that in general the pig herds using vaccines against MYC, PCV2 and LAW had a higher – and not as hypothesised a lower AM consumption – in the weaning stage compared to not using vaccination at all. This is in line with results presented by Potsma et al. (2016) . This maControl of PCV2-related diseases has traditionally been based on preventive measures such as: (1) improved management practices in order to control risks or triggering factors, (2) control of concurrent infections and (3) changes of the boar genetic background . CurrentIn the present study, herds using PCV2 vaccination had a statistically significantly higher total AM consumption and AM consumption with respiratory indication compared to herds not using the vaccines – except from the case when LAW vaccination was applied as well Table . This isAs described above, PCV2 has been linked with various clinical syndromes in different organs. This might justify the application of a major amount of AMs , 20. PCVUse of vaccination against MYC has been shown to be associated with reduced clinical signs, fewer treatment costs and with increased average daily weight gain , 22. VacAccording to the results of the multivariable analysis, on average herds using MYC vaccination had a higher total AM consumption and AM consumption with respiratory indication than herds not using the vaccines. This finding may be explained by reverse causality: herds using the vaccines were likely infected with this pathogen – some with clinical problems. Subsequently, these herds were using AMs with respiratory indication to control MYC and, simultaneously using the vaccines to avoid the predisposition of the infected animals to secondary invaders, especially other pulmonary pathogens . Other hIn 2013, only one vaccine was available in Denmark against proliferative enteropathy caused by LAW. It is used for piglets in the last part of lactation or (more commonly) in the first week post weaning. The positive effect of the LAW vaccine has been shown by Bak & Rathkjen, who undertook a study in a Danish Specific Pathogen Free herd . Here, pAs LAW vaccination is used to prevent proliferative enteropathy , it woulWe assumed that the AM and vaccines prescribed in a herd were also used in the same herd. For some countries there may be a difference between prescription and use. However, for Denmark it is the general belief that VetStat data (consisting of prescription data) approximate AM use closely over a longer period of time. One reason is that it is the only legal way to get AM for livestock in Denmark. This was underpinned by a recent report from the Danish veterinary authorities stating that there are no indications of a systematic illegal import of AMs .On average, 36 % of the total amount of AMs used for the production of a pig until slaughter is used during the weaning period  althoughThe multivariable models presented in Tables E. coli to prevent E. coli associated neonatal diarrhea in piglets, could result in higher piglet health at weaning and therefore also affect the medical consumption post weaning. But the contrary is also possible; that herds applying the vaccine do this because they have clinical problems with neonatal diarrhea infections requiring antimicrobial treatment despite the use of vaccination.In this study, we focused on MYC, PCV2 and LAW. One reason for only including these three vaccines in the analysis was to avoid that the number of herds representing different combinations of vaccine use would become very low, because this would result in unstable parameter estimates. We did not take into account PRRS vaccination. Although this vaccine only represents 2 % of the vaccines prescribed for pigs in Denmark, it could have been a confounder in the analyses, and it would therefore be of interest to include this in a subsequent analysis. Similarly, it would have been of interest to include also vaccines with an effect on APP. However, this was not done in this analysis due to the limited use (8 % of the prescribed vaccine doses prescribed to Danish swine). It is also possible that vaccination of breeding animals for This study was a first basic approach to using register data and a cross-sectional design to describe the possible association between vaccinations and AM use in pig herds in Denmark. The vaccine data from VetStat have to the authors’ knowledge not been used in analysis of AM use before. It is not possible to elucidate the directions of these associations. A longitudinal study will enable a better understanding of cause and effect and be able to take into account other factors than just vaccination.More information is needed to assess to which extent vaccinations – and other preventive measures - can in fact reduce the need for the use of AMs. The feasibility of using vaccination as a an alternative to AMs will depend on proper disease diagnostics, the costs of vaccines compared to AM, effectiveness and ease of use . If in tIn general, the sow herds applying MYC and PCV2 vaccination had more AMs prescribed for weaners compared to sow herds not using the three studied vaccines – probably as a result of existing health problems in the herds prior to and/or during the use of vaccination. For LAW vaccine there was a trend towards lower or equal amount of prescribed AMs compared to herds not purchasing any of the three vaccines. These results suggest that vaccination alone does not necessarily come along with a low use of AMs, despite being an asset in many regards.Each herd has its own challenges and several issues need to be taken into account when it concerns alternatives to AM consumption. Further studies need to be carried out to take into consideration other factors regarding prevention of disease, which are of extreme importance, such as biosecurity and management practices within the herds.The data used in this study were obtained from two sources. The first was the VetStat database, which contains information about all prescriptions of AM vaccines destined for livestock. VetStat quantifies the AM prescriptions in food animal using the unit animal daily dose (ADD), which is defined as the average maintenance dose per kg live animal for the main indication of an AM in a specified species . This meThe second source of data was the Danish CHR register, which contains information about location and size of all livestock herds. All pig herds were selected for the study, if they fulfilled the following inclusion criteria: a) one-site indoor herds b) herds with more than 50 sows and c) herds with more than 200 weaners. In total 1518 herds met these three criteria, and data regarding the prescription of AMs for weaners as well as the number of vaccine doses purchased in 2013 were obtained for each of these herds from VetStat.Five herds had erroneous  or missing data records. All cases were most likely caused by an error in VetStat. As all the herds in the dataset were anonymised, it was not possible to assess the reasons for these data errors. Consequently, these five herds were excluded from the analysis.For each of the remaining 1513 herds, a variable was created to estimate the average AM consumption per 100 weaners per day. This variable was calculated using the total administered ADD in weaners in year 2013, dividing it by the standard weight of weaners used by VetStat (15 kg). After this first calculation, to have the number of ADD for each weaner, this total was divided by the number weaners (pen places) in each herd. Finally, this total was divided by 3.65, to show the final values in ADD per 100 animals per day – which corresponds to the unit used by VetStat to impose the official AM consumption limits.Taking into account that weaners may receive more than one type of vaccine, two-way combinations between vaccination groups were constructed to assess the possible association between different vaccinations and AM consumption. Moreover, for the final models, one variable with eight levels was constructed to take into consideration all combinations of use of the three different vaccines within the herds.All data analyses were carried out in R . Univariable analyses were performed for the total AM consumption (AC-TOTAL), AM consumption with gastrointestinal indication (AC-GI) and AM consumption with respiratory indication (AC-RESP) Figs. Initially, a t-test was conducted for each of the three types of vaccination comparing the AM consumption for herds which used the vaccine with herds which did not use the vaccine.For each of the two-way combinations, a t-test and a one-way ANOVA were conducted. Following the one-way ANOVA, a post hoc comparison – using the TUKEY HSD test – was performed to assess the statistical difference between the individual combinations (Data not shown).P-value < 0.05 was used as threshold for statistical significance. As part of model validation, residuals were inspected for normal distribution.Finally, multivariable analyses were conducted for (1) AC-TOTAL, (2) AC-GI and (3) AC-RESP as three separate outputs. The variables herd size and use of vaccine (divided into the eight different combinations of use of the three vaccines) represented the explanatory variables. It was tested whether herd size was significantly associated with the response and whether it acted as a confounder by being associated with the vaccine use. Moreover, a test was made for presence of interaction between herd size and vaccine. A Lawsonia intracellularis; MYC, Mycoplasma hyopneumoniae; PCV2, porcine circovirus type 2; PCVD, porcine circovirus diseases; PMWS, post-weaning multi-systemic wasting syndrome; PRRS, porcine reproductive and respiratory syndromAC-GI, antimicrobial consumption with gastro-intestinal indication; AC-RESP, antimicrobial consumption with respiratory indication; AC-TOTAL, total antimicrobial consumption; ADD, animal daily doses; AM, antimicrobial; CHR, central husbandry register; LAW,


Adenocarcinomas of the pancreatobiliary system are currently classified by their primary anatomical location. In particular, the pathological diagnosis of intrahepatic cholangiocarcinoma is still considered as a diagnosis of exclusion of metastatic adenocarcinoma. Periampullary cancers have been previously classified according to the histological type of differentiation , but overlapping morphological features hinder their differential diagnosis. We performed an integrative immunohistochemical analysis of pancreato-biliary tumors to improve their diagnosis and prediction of outcome.This was a retrospective observational cohort study on patients with adenocarcinoma of the pancreatobiliary system who underwent diagnostic core needle biopsy or surgical resection at a tertiary referral center. 409 tumor samples were analyzed with up to 27 conventional antibodies used in diagnostic pathology. Immunohistochemical scoring system was the percentage of stained tumor cells. Bioinformatic analysis, internal validation, and survival analysis were performed.Hierarchical clustering and differential expression analysis identified three immunohistochemical tumor types  and the discriminant markers between them. Among patients who underwent surgical resection of their primary tumor with curative intent, the intestinal type showed an adjusted hazard ratio of 0.19 for overall survival  compared to the extrahepatic pancreatobiliary type.Integrative immunohistochemical classification of adenocarcinomas of the pancreatobiliary system results in a characteristic immunohistochemical profile for intrahepatic cholangiocarcinoma and intestinal type adenocarcinoma, which helps in distinguishing them from metastatic and pancreatobiliary type adenocarcinoma, respectively. A diagnostic immunohistochemical panel and additional extended panels of discriminant markers are proposed as guidance for their pathological diagnosis. Adenocarcinomas of the pancreatobiliary system are among the most lethal cancers. With a dismal 5-year survival of 6%, ductal th edition)30], and We generated comparative immunohistograms to represent the differences in marker expression between the immunohistochemical tumor types, according to the results of differential expression analysis.A complex network was also built using an alternative, robust clustering approach in which missing data were imputed with random values through 15000 iterations. The network visualization was generated in Gephi  in correctly discriminating between the immunohistochemical tumor types along a suite of classification experiments. Several metrics were considered for evaluation: true positive rate, false positive rate, precision, recall, F-measure, and receiver operating characteristic (ROC) area.A simplified diagnostic immunohistochemical panel was finally developed by summarizing in table format the most discriminant markers and their expected immunoreactivity.We used Kaplan–Meier survival curves, with time to death censored at the end of follow-up (August 2016) as the outcome. Cox proportional hazards models were used to estimate the crude and adjusted hazard ratios and 95% confidence intervals for mortality associated with tumor type by the immunohistochemical and anatomy-based classifications. The adjusted models included pathological tumor stage (pT) and lymph node status (pN) as covariates. The distant metastasis pathological descriptor (pM) was not included, because it could not be assessed microscopically in the majority of cases (pMX) and preoperative detection of distant metastasis often precluded resection of the primary tumor. The Cox model proportional hazards assumption was tested. Survival analysis was performed using R statistical packages “survival” and “rmsDescriptive analysis and handling of missing data: The raw dataset comprised 439 tumor samples and 38 immunohistochemical markers. Histograms for every marker and anatomy-based diagnosis showed discrete distributions of immunohistochemical scoring values. 36% of values in the raw dataset were missing. As this was a retrospective study on diagnostic tumor samples, the individual immunohistochemical panels were in first instance determined by the specific differential diagnoses in consideration and the limited availability of tissue, which precluded the analysis of all samples with the same antibody panel. By the method described above, 11 markers and 30 samples were removed, which reduced the proportion of missing values before imputation to 18%.The final dataset for the analysis was composed of 409 tumor samples (264 core needle biopsies and 145 resection specimens) from 370 individual patients and 27 immunohistochemical markers. For 29 patients, we recorded the results of immunohistochemical analysis on more than one tumor sample (e.g. diagnostic biopsy and resection specimen). Adenocarcinomas from the main anatomical locations were included in this series: ampullary carcinoma (n = 24), ductal pancreatic adenocarcinoma (n = 139), distal bile duct cancer (n = 7), gallbladder cancer (n = 37), perihilar cholangiocarcinoma (n = 27), and intrahepatic cholangiocarcinoma (n = 97). As described in Methods, tumor samples of hepatocellular carcinoma (n = 78) were included as a control group for the evaluation of clustering results.Analysis of confounding factors: First, the set of markers analyzed in the several anatomical tumor types was tested by replacing in each tumor sample the immunohistochemical scores  by a binary constant indicating whether the marker had been analyzed or not. The corresponding plot of principal component analysis (PCA) (is (PCA)  showed aPCA of the immunohistochemical scores labelled by the type of probe (biopsy/resection) showed an admixture of probe types throughout the entire plot , disregaHierarchical clustering  identifiThe complex network  consisteComparative immunohistograms including only the statistically significant markers  illustraIn a first experiment, the reproducibility and robustness of the immunohistochemical tumor types were tested by evaluating their classification using machine-learning models. Three sets of classifications were conducted using the full set of (27) markers: extrahepatic pancreatobiliary vs. intestinal, extrahepatic pancreatobiliary vs. intrahepatic cholangiocarcinoma, and intrahepatic cholangiocarcinoma vs. hepatocellular carcinoma.ROC area value in the classifications was about 0.96.The average true positive rate was around 0.96 across the three sets, while the average false positive rate was around 0.1. The average The second experiment tested the hypothesis that the performance of the machine learning models remained stable when the same pairwise classifications were carried out using only the significant markers, according to the results of differential expression analysis, instead of the whole set of markers.ROC area value was 0.95.The average true positive rate and false positive rate were around 0.96 and 0.12, while the average The full details of machine learning experiments are provided on-line .Finally, we developed based on the results of differential expression analysis and characteristic immunoprofiles  a simpliAs a real-world example, the photomicrographs in Most tumors were locally advanced or/and with metastatic disease at the time of diagnosis. Survival analysis was performed on 86 patients whose primary tumor had been surgically resected with curative intent, of whom 47 were women. Median age was 66 (range 32–83) years. Patients with only diagnostic needle core biopsy had tumors deemed as non-eligible for resection; their generally short survival time  = 6 months; Survival analysis was therefore performed for patients whose primary tumor had been resected with curative intent according to tumor type by both the immunohistochemical and anatomy-based classifications .Lymph node status determined OS in univariate  and multivariate analysis .When considering the immunohistochemical tumor type , we idenBy anatomy-based diagnosis , ductal When comparing extrahepatic cancers of pancreatobiliary and intestinal immunohistochemical type , the intThe Cox model proportional hazards assumption was tested as well in univariate and multivariate analysis . It yielUsing an extended panel of immunohistochemical markers, we derived several tumor types based on their marker profile. To the best of our knowledge, this is the first study to develop an integrative immunohistochemical classification of adenocarcinomas from the main anatomical locations of the pancreatobiliary system. It introduces three distinct subtypes, extrahepatic pancreatobiliary, intestinal, and intrahepatic cholangiocarcinoma, with differences in prognosis, biology, and potentially in response to treatment.th edition) classification[The three immunohistochemical types presented in this study simplify and integrate the six tumor classes in the anatomy-based , intrahepatic cholangiocarcinoma can be very difficult to distinguish from metastatic adenocarcinoma, especially in the presence of multiple radiological tumor nodules in liver.A combination of “generic” adenocarcinoma markers  together with vimentin and a limited number of “pancreatobiliary” markers (MUC1 and CA19-9) defines its characteristic immunohistochemical profile , S2 Fig.The type of probe was not a confounding variable. This supports the adequacy of both core needle biopsy and resection specimen for the immunohistochemical diagnosis of intrahepatic cholangiocarcinoma.The extrahepatic pancreatobiliary immunohistochemical profile is characterized by expression of a considerable number of markers , S2 Fig,This profile was the most common among adenocarcinomas originated in the pancreas and the extrahepatic biliary tract. Half of perihilar cholangiocarcinomas were of the extrahepatic pancreatobiliary type, but only about a third of intrahepatic cholangiocarcinomas. This may be a reflection of the different proportions of large and minor biliary branches that are present in the perihilar and peripheral regions of the liver.Several studies on periampullary adenocarcinomas have demonstrated that the histological type  rather than the primary tumor location determines survival–11. TherIn the present series, the intestinal type expressed CK20, MUC2, and CDX2, which is in agreement with the literature. As repoPrevious studies have pursued the immunohistochemical distinction between the intestinal and pancreatobiliary type,38. HoweWe propose the diagnostic immunohistochemical panel in To the best of our knowledge, this is the first study to employ complex networks  for visuIn the spectrum, from hepatocellular carcinoma to the extrahepatic pancreatobiliary type, tumours showed progressively increasing numbers and levels of marker expression. Between them, the network depicted the intrahepatic cholangiocarcinoma and the intestinal clusters.This model is consistent with the current state of knowledge on the development and carcinogenesis of the pancreatobiliary system. Both the ventral pancreas and the extrahepatic biliary tract arise from a contiguous region of the endoderm and share several developmental transcription factors. Recent studies ,41 have The fact that ductal pancreatic adenocarcinoma and extrahepatic biliary tract cancer present comparable prognostic and clinicopathological features  seems toth edition)[The current ,6 stagin edition)–11. AdvaIn line with other groups,11, we eRegarding subgroup analysis, perihilar cholangiocarcinoma presented in univariate analysis a statistically significant better overall survival compared to ductal pancreatic adenocarcinoma, despite being dominated by the extrahepatic pancreatobiliary immunohistochemical type. This finding warrants further investigation in larger series addressing even the pathways of tumor spread.A semi-supervised approach was pursued to evaluate from the perspective of diagnostic and clinical relevance the hierarchical clustering results and select the clusters of interest. The aim of this part of the work was to reveal the underlying categories (tumor types) in the distribution of the immunohistochemical data. When prior knowledge on the categories is not available, an unsupervised learning needs to be assumed. However, it is recognized in the data analysis field that there is no so called “perfect clustering”. ClusterA semi-supervised approach can provide a limited form of supervision in the clustering process, and align the computational grouping with semantically meaningful classes. In this research, a limited amount of human guidance was provided, enabling the clustering results to become most meaningful from a clinical-diagnostic perspective. Two features enabled the use of the semi-supervised approach in this study, the relatively low number of markers  and the team’s previous knowledge and expertise in the pathological diagnosis of pancreatobiliary tumors.Nonetheless, we have strived to test the proposed clusters  by implementing an alternative, robust complex network approach as well as machine learning-based supervised classification. For the latter, we chose to use several and different reliable classifiers, not with the aim of pursuing the best classification performance, but rather to validate the proposed semi-supervised clustering results. Both techniques, very different algorithmically from hierarchical clustering, reproduced the immunohistochemical tumor groups, which we think supports the robustness of our semi-supervised clustering approach as well as the consistency and reproducibility of the immunohistochemical classification.This study has some limitations. During the study period (2002–2013) not all patients diagnosed at our institution could be included, but all consecutive cases routinely reported by the three consultant pathologists of the hepato-pancreato-biliary team . Still, 36 tumor samples remained as “unclassified” by the semi-supervised approach employed to derive the clusters of interest. Because the methods of investigation determine the study findings, the presented immunohistochemical types do not preclude the existence of further molecular types based on DNA or RNA data, as recently described,44. AlthThis study presents an integrative immunohistochemical classification of adenocarcinomas of the pancreatobiliary system that improves diagnosis and prognostic stratification and has potential therapeutic implications. It defines three immunohistochemical types, extrahepatic pancreatobiliary, intestinal, and intrahepatic cholangiocarcinoma and their discriminant markers.The characteristic immunohistochemical profile of intrahepatic cholangiocarcinoma positively supports its pathological diagnosis, which no longer needs to be regarded as a diagnosis of exclusion (of metastatic adenocarcinoma).The prognostically more favorable intestinal type can be distinguished from the more aggressive pancreatobiliary type.A diagnostic immunohistochemical panel and additional extended panels of discriminant markers are proposed as guidance for the diagnosis of the immunohistochemical tumor types.S1 Fig(PDF)Click here for additional data file.S1 File(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.S3 File(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.