Rhodopseudomonas palustris has emerged as a model microbe for the anaerobic metabolism of p-coumarate, which is an aromatic compound and a primary component of lignin. However, under anaerobic conditions, R. palustris must actively eliminate excess reducing equivalents through a number of known strategies  to avoid lethal redox imbalance. Others had hypothesized that to ease the burden of this redox imbalance, a clonal population of R. palustris could functionally differentiate into a pseudo-consortium. Within this pseudo-consortium, one sub-population would perform the aromatic moiety degradation into acetate, while the other sub-population would oxidize acetate, resulting in a single-genotype syntrophy through acetate sharing. Here, the objective was to test this hypothesis by utilizing microbial electrochemistry as a research tool with the extracellular-electron-transferring bacterium Geobacter sulfurreducens as a reporter strain replacing the hypothesized acetate-oxidizing sub-population. We used a 2 × 4 experimental design with pure cultures of R. palustris in serum bottles and co-cultures of R. palustris and G. sulfurreducens in bioelectrochemical systems. This experimental design included growth medium with and without bicarbonate to induce non-lethal and lethal redox imbalance conditions, respectively, in R. palustris. Finally, the design also included a mutant strain (NifA*) of R. palustris, which constitutively produces H2, to serve both as a positive control for metabolite secretion (H2) to G. sulfurreducens, and as a non-lethal redox control for without bicarbonate conditions. Our results demonstrate that acetate sharing between different sub-populations of R. palustris does not occur while degrading p-coumarate under either non-lethal or lethal redox imbalance conditions. This work highlights the strength of microbial electrochemistry as a tool for studying microbial syntrophy. R. palustris must strategically dispose of excess reducing equivalents. Researchers had in the past hypothesized that a syntrophy may exist within a single culture—cells that convert the monomer into acetate and other cells that further oxidize acetate. However, conclusive proof is elusive. Here, we used a co-culture of R. palustris and Geobacter sulferreducens in a bioelectrochemical system to examine if such a single-genotype syntrophy exists. A 2 × 4 experimental design with several positive controls under both non-lethal and lethal conditions did not identify any evidence for a single-genotype syntrophy strategy by R. palustris, failing to provide support for this hypothesis.Synthrophic microbial relationships are of utmost importance in nature. They resolve important electron flow issues under anaerobic conditions and make microbial life under difficult thermodynamic conditions possible. During the anaerobic breakdown of the electron-rich aromatic ring in monomers of lignin, the photoheterotrophic bacterium Lignin is the most abundant source of organic aromatic compounds, and the second most abundant organic carbon source in the biosphere  in the presence of light  between sub-populations, resulting in a single-genotype syntrophy . In this system, G. sulfurreducens functions as a surrogate for the hypothesized sub-population of R. palustris that is responsible for acetate oxidation, and as a reporter for the magnitude of acetate sharing.Complications in experimentally verifying acetate sharing exist since transcriptomic or proteomic analyses from bulk pure culture studies measure all sub-populations together as an average, and many limitations still exist with bacterial single-cell RNA-seq  in a BES  from the reporter strain G. sulfurreducens serves as a proxy for acetate sharing by the p-coumarate degrading subpopulation of R. palustris. Because of the ability of G. sulfurreducens to channel electrons out of the system via the electrode, and since a buffer would neutralize excess H+, G. sulfurreducens functions as a sink for excess reducing equivalents in the form of acetate or H2. Further, acetate oxidized by G. sulfurreducens can return back to R. palustris in the form of CO2, even when exogenous R. palustris engages in acetate sharing, a BES co-culture between R. palustris and G. sulfurreducens would ease the burden of redox imbalance, and could even rescue growth of R. palustris from conditions that would otherwise induce a lethal redox imbalance  of R. palustris CGA009, which constitutively expresses nitrogenase genes in the presence of 2. H2 production reduces the strain of reducing equivalents in a way to ensure a non-lethal redox imbalance condition even without bicarbonate in the growth medium. It, therefore, serves as a redox-balanced positive control for without bicarbonate experiments  shared by R. palustris  was active and to rule out that a negative result (no current) was indeed an indication for the absence of acetate sharing rather than a problem with the reporter strain or equipment  experiments for Rhodopseuomonas palustris strains CGA009 and NifA*, which were provided by Dr. Caroline Harwood (University of Washington), and Geobacter sulfurreducens were routinely cultivated in filter-sterilized anaerobic fresh water (FW) medium. FW medium consisted of 2.5 g NaHCO3, 0.1 g KCl, 0.25 g NH4Cl, 0.52 NaH2PO4, 10 mL FW Vitamins, and 1 mL FW Minerals per liter, which was neutralized to pH 7.0 .* strains in pure culture with p-coumarate in FW media with and without bicarbonate were incubated in triplicate in an environmental growth chamber . Conditions were maintained at 30.0°C with 80 μmol of photons/s/m2 (photons between 400-700 nm) from both fluorescent and incandescent lamps.Batch serum bottle experiments for the characterization of CGA009 and NifA2. Lids with butyl rubber stoppers were used to maintain gastight conditions while sampling and replacing the medium. Anaerobic conditions were maintained by sparging reactors with either 80:20 N2/CO2 or N2 through sterile filters for conditions with and without bicarbonate, respectively.Two-chamber, H-type reactors were used for all electrochemical experiments. The reactors were constructed out of autoclavable glass with water jackets for temperature control and ports for electrochemical components  30 mM 2 sparging for the conditions without R. palustris. Samples were taken throughout the operating period to monitor OD600, pH, and relevant metabolites. All non-aromatic metabolites were detected via HPLC  with a refractive index detector and an Aminex HPX-87H column . The column was maintained at a temperature of 60°C, and a 5 mM sulfuric acid eluent at a flow rate of 0.6 mL/min was used as the mobile phase. Aromatic metabolites were detected via a Thermo Scientific Ion Chromatograph System  with a Dionex IonPac™ AS22 column (4 × 250 mm) and a Dionex Variable Wavelength Detector set to 285 nm. AS22 eluent was used at a flow rate of 1.2 ml/min. Metabolites were identified by retention times from high purity standards .For co-culture experiments, R. palustris CGA009 and NifA* growing in batch serum bottles containing FW 2 mM p-coumarate with Mid-log phase cultures of R. palustris CGA009 into serum bottles containing anaerobic FW medium with 2 mM p-coumarate with and without the addition of R. palustris CGA009 was only able to degrade p-coumarate and grow when bicarbonate was added to the anaerobic medium to avoid a lethal redox imbalance , which was rapidly degraded by β-oxidation after activation and cleaving the aromatic ring  and demonstrates the drastically different outcomes that these strategies can have on global cellular behavior. This observation further suggests that metabolite sharing could be a viable strategy undertaken by a CO2-fixing pseudo-consortium of R. palustris CGA009 due to the tendency to aggregate, since this aggregating phenotype is abolished when H2 secretion by individual cells is utilized as the primary route to redox balance.To investigate this, digital microscopy of the two cultures revealed that under these conditions CGA009 tended to grow primarily in granule-like aggregations ranging from 20 to 200 μm in width, while NifAR. palustris CGA009 and NifA* were independently inoculated into G. sulfurreducens-pregrown BESs containing 2 mM p-coumarate as the sole carbon source in FW medium with bicarbonate. Because both strains of R. palustris are capable of growing under these conditions, the presence of G. sulfurreducens on the electrode as a potential electron sink is not obligate for growth for either strain under these conditions and any current produced would be through metabolite sharing of either acetate (CGA009 or NifA*) or H2 (limited to NifA*). Since acetate sharing is proposed as a strategy that develops in pure cultures, the R. palustris precultures used to inoculate the electrochemical reactors would already be performing acetate sharing, minimizing any adaptation response upon introduction into the BES and eliminating any lag time before observable current production. In addition, because the electrode is the only terminal electron acceptor for growth of G. sulfurreducens under these conditions, any increase in the planktonic optical density would be attributed to R. palustris.To investigate whether acetate sharing occurs under non-lethal redox conditions, p-coumarate to p-hydroxybenzoate and subsequent consumption occurred at nearly the same rate for both strains between both systems. However, the optical density for both strains was considerably lower in the BESs than when grown in serum bottles . In our BESs with G. sulfurreducens, we provide an efficient electron sink for acetate oxidation with an electrode. Thus, creating an ideal biological test bed in which stringent conditions can be combined with a possible solution to avoid a lethal redox imbalance—but only when acetate sharing is performed by R. palustris. To test this, R. palustris CGA009 and NifA* were separately introduced into G. sulfurreducens-pregrown BESs with 2 mM p-coumarate FW medium without bicarbonate. To maintain a proper pH level and to neutralize H+, we included a 25 mM phosphate buffer. In addition, to provide an opportunity for association between G. sulfurreducens and R. palustris at the electrode, R. palustris CGA009 was pre-grown together with G. sulfurreducens on the electrode before switching to without bicarbonate conditions.It is possible that acetate sharing in R. palustris CGA009 did not exhibit any planktonic growth within the BESs once conditions were switched to without bicarbonate, p-coumarate was rapidly taken up and metabolized to 4-hydroxybenozate after the medium replacement was completed  following the acetate addition, verifying that G. sulfurreducens was active  with G. sulfurreducens. An aggregating phenotype was initially observed for R. palustris CGA009, suggesting a desire to form close cellular interactions under these conditions, whereas NifA* demonstrated no aggregating phenotype. This finding could have supported the acetate-sharing hypothesis, however, no current was produced by G. sulfurreducens through acetate sharing from R. palustris CGA009 within the BES under both non-lethal and lethal redox imbalance conditions. Although CGA009 was capable of complete metabolism of the alkyl side chain of p-coumarate, further metabolism of the aromatic group yielded too many reducing equivalents and quickly resulted in a lethal redox imbalance in BES conditions without bicarbonate. Because G. sulfurreducens functioned as the sole electron sink for oxidizing excess reducing equivalents by conversion of acetate to CO2 without bicarbonate, the absence of an acetate sharing-based electric current strongly indicates that R. palustris does not use acetate sharing to manage the excess of reducing equivalents via a single-genotype syntrophy. It was not expected that additional incubation of the CGA009 BES without bicarbonate would eventually stimulate acetate sharing with G. sulfurreducens, akin to adaptation phases in similar syntrophy evolution studies (Summers et al., The hypothesis that DD and LA designed the study; DD performed the research and sample analysis; DD analyzed the data, and DD and LA wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Toxin–antitoxin (TA) modules regulate metabolism and viability of bacteria and archaea. In type II TA systems these functions are generally thought to be performed by two small proteins. However, evidence is increasing that the toxins are much more diverse and can form multi-domain proteins. Recently, we published a novel type II TA system in which toxin and antitoxin are covalently linked into a single polypeptide chain. In this review we summarize the current knowledge on these elongated toxin homologs and provide perspectives for future study. The authors speculate that the acquisition of additional domains expands the versatility of the mycobacterial VapBC TA systems, which function as posttranscriptional regulators in response to environmental stress (Andrews and Arcus One of the first examples of such long type II toxins is encoded by the Escherichia coli and several related organisms (Rocker and Meinhart N-acetylglucosamine kinase domain that interferes with peptidoglycan synthesis similar to the related toxins from Streptococcous pneumoniae and Streptococcus pyogenes (Mutschler et al. in cis abolishes passive complex diffusion and therefore provides additional possibilities for regulation. Activation could be either achieved by protease cleavage, partial digestion, chaperone binding or protein modification. Moreover, the generally observed recovery of a toxin-poisoned bacterial population by newly synthesized antitoxin until the “point of no return” is not feasible in such systems, as toxin and antitoxin are synthesized in equimolar amounts and are additionally fused. Interestingly, a similar fusion protein TA system has been reported for the Phd antitoxin and a RelE toxin, yb_293189 TA system from Ralstonia eutropha (Loris and Garcia-Pino Another variety of unconventional and previously unrecognized type II TA system is the multi-domain and auto-regulated EzeT system encoded by a variety of different strains from Furthermore, additional evidence for an expansion of toxin functions is provided by domain analyses in the protein family database PFAM (Finn et al. It seems that investigations of elongated toxin proteins still hold unanticipated number of surprising findings as many novel functionalities and regulatory concepts can be acquired by domain fusion, adding to the complexity of TA systems.


Scaffolding proteins serve to assemble protein complexes in dynamic processes by means of specific protein-protein and protein-lipid binding domains. Many of these domains bind either proteins or lipids exclusively; however, it has become increasingly evident that certain domains are capable of binding both. Especially, many PDZ domains, which are highly abundant protein-protein binding domains, bind lipids and membranes. Here we provide an overview of recent large-scale studies trying to generalize and rationalize the binding patterns as well as specificity of PDZ domains towards membrane lipids. Moreover, we review how these PDZ-membrane interactions are regulated in the case of the synaptic scaffolding protein PICK1 and how this might affect cellular localization and function. Scaffolding proteins are essential components required for spatial and temporal regulation of cellular processes, such as synaptic plasticity and cell-cell adhesion. The overall function of scaffolding proteins is characterized by a common ability to (I) bind its interaction partners via specific interactions using relatively short consensus motifs; and (II) bind to other cellular scaffolding proteins, mediators or specific intracellular membrane compartments. To this end, scaffolding proteins rely on both protein-protein interactions (PPIs) and protein-lipid interactions (PLIs), which can be attributed to various distinct domains or posttranslational modification . Canonical examples of PPI domains include SRC homology 2/3 (SH2/3) domains ,2,3,4, WThe (PH) domain is one of the most prominent examples of a domain known to bind both lipid membranes and specific protein motifs ; howeverThe PDZ domain is one of the most common PPI domains found in the mammalian proteome. They were first discovered in 1991 in imaginal discs of Drosophila  and in 10) [The first two studies describing the overall structural basis of PDZ domains were published in 1996. One study reported the crystal structure of the third PDZ domain (PDZ3) of PSD-95 in both a substrate-bound and a substrate-free state, whereas the other reported the substrate-free state of the homologous PDZ3 of SAP102 [0) ,21  and, consequently, the vast majority of PDZ domain ligands have a hydrophobic residue at this position. The size and shape of S0 varies between the different PDZ domains, thereby controlling the preference of S0 towards different hydrophobic residues at P0. Most PDZ domains, however, prefer non-aromatic hydrophobic residues at P0, such as valine, isoleucine or leucine [−1 and P−3 will be solvent-exposed and, therefore, these residues are rarely directly involved in canonical PDZ domain binding , but also several other residues (mostly hydrophobic) from αB and βB, which constitute a secondary binding pocket (S−2). The preference of S-2 towards specific residues at P−2 is much stricter than the residue preference of S0 and, consequently, the classification of PDZ domain ligands have been primarily based on the P−2 residue. Correspondingly, PDZ domains have been classified with respect to the first residue of the α-helix B (αB1) [Upon canonical binding the side-chain of the P leucine ,27,28. A binding b. Some s B (αB1) ,30,31.−2 serine/threonine  using a lipid dot blot assay. This assay revealed that a few domains also have the ability to bind non-phosphorylated lipids. Interestingly, the PIP affinities determined from the SPR experiments was different from affinities obtained using dot blots, suggesting that some of these interactions relies on the presence of intact membranes. In agreement with findings by Chen et al. and adding to the general understanding of PDZ-membrane lipid interactions, it was suggested that high pI (>9) seems to be a common feature of the lipid binding PDZ domains, and that conserved cationic patches are important for PIP specificity and cellular localization [To investigate if the subcellular localization could be explained directly by specificity towards different PIPs, the affinities for liposomes with different PIP contents were quantified using SPR. Out of 19 randomly selected domains, 10 domains displayed micromolar affinities towards tri- or biphosphorylated PIPs. Only one PDZ domain displayed micromolar affinity for monophosphorylated PIPs (DFNB31_1). Importantly, all of the four domains found to respond to cellular lipid modification also displayed PIP specificity. The authors further tested the affinity towards several other membrane lipids , phospatidylcholine (PC), and cholesterol, lization .Though it has become well established that lipid/membrane binding is a common feature shared by several PDZ domains, the molecular mechanisms underlying the binding are still poorly understood. As presented above, attempts to classify the domains according to either their cellular localization, or their cationic properties, have provided a valuable framework for understanding how these interactions might be electrostatically favored. To emphasize how these general properties may relate to regulation by e.g., redox state, ion binding, and posttranslational modifications we review the case of the lipid and membrane binding by the PICK1 PDZ domain below.Protein Interacting with C kinase 1 (PICK1) is ~47 kDa membrane associated scaffolding protein which was first discovered in a yeast two hybrid experiment investigating interaction partners of activated Protein Kinase C (PKC) . The oveFunctionally, PICK1 plays a pivotal role in regulation of synaptic plasticity involving trafficking of the AMPA-type ionotropic glutamate receptors (AMPARs), which is thought to be the neuronal basis for learning and memory . PICK1 ii.e., amphiphysin, arfaptin, and endophilin [et al. suggest that the PDZ domains are associated with the BAR domain and the linker between the adjacent domain forms a permanent helix [At the structural level, PICK1 contains two highly conserved domains; the ~90 aa N-terminal PDZ domain and by a ~210 aa Bin/amphipysin/Rvs (BAR) domain which mediates strong homo-dimerization. PICK1 is the only protein featuring these two domains and they are separated by a ~40 aa linker region capable of forming a four-turn membrane binding amphipatic helix (AH). The domains and are flanked by a ~20 aa acidic N-terminal region (NAR) and a ~50 aa acidic C-terminal region (CAR). The PICK1 homo-dimers adopt, overall, an elongated crescent shape defined by the BAR domain ,60,61 whdophilin ,63,64. Tnt helix ,65,66,67Each monomer of PICK1 contains a single PDZ domain, which is highly conserved between species from mollusks to vertebrates. The PDZ domain of PICK1 interacts with more than 40 different ligands, including GluA2, the dopamine transporter (DAT), mGluR7, Glt1b, and ASIC1a through their respective C-termini ,68,69,700 and S2 (see 0) consists of the G-φ-G-φ motif involving Ile33, Gly34, Ile35 but also a conserved Ile90 at position αB8. A preference for P0 residues of Val > Ile > Leu was previously found for S0 [2) consists of residues at positions αB1, αB4, αB5 and βB3; Lys83, Val86, Ala87, and Ile37. Notably, the αB1 residue is a highly conserved Lysine (Lys83), which is unique for the PICK1 PDZ domain. The amine side-chain of Lys83 can interact with the peptide backbone in P−4 of the ligand, and the aliphatic chain can complement the hydrophobic pocket II to make a favorable environment for a hydrophobic residue at P-2 in class II ligands [The isolated PICK1 PDZ domain has been fully structurally characterized using both X-ray crystallography and NMR spectroscopy, in complex with canonical class II ligands; DAT, GluA2, and EphrinB1. The truncated PDZ domain is only stable upon direct fusion to ligands which can effectively occupy the PDZ binding groove, however, the canonical overall globular fold consisting of six β-strands and two α-helices is conserved ,42,72,73d S2 see a. Hydropd for S0 . Hydroph-7 position, which may favor interaction with this part of the PICK1 PDZ domain. Furthermore, it was demonstrated that the unconventional ligand ASIC1a has a dual binding mode involving a canonical insertion and a non-canonical internal insertion with the two most C-terminal residues (P0 and P-1) forming interactions outside the groove.PICK1 PDZ promiscuity relies on a combination of increased tolerance in the canonical binding pocket and additional non-canonical binding motifs . Thus, tThe first studies of the membrane lipid binding capacities of PICK1 were focused exclusively on the BAR domain and suggested that the involvement of the PDZ domains was primarily to regulate the accessibility of the BAR domain to the membranes ,65,66,67Direct binding studies with the truncated PDZ domain stabilized with the self-binding GluA2 peptide confirmed membrane lipid binding both on dot blots and in context of membranes . Using lIt was previously shown for the lipid binding of the PAR3-PDZ2 domain how a hydrophobic motif was inserted into the cytosolic bilayer of the membrane, thereby stabilizing the interaction . To test1B ATPases, where they localize to the center of the sixth transmembrane helix (TM6) and are directly involved in coordinating both mono- and bivalent cations  during transport [et al. showed that Zn2+ can also bind specifically to the CPC loop of the PICK1 PDZ domain covalently conjugated to the GluA2 C-terminus [5/M. The dK was estimated to be in the lower micromolar range. Although zinc was not found to be necessary for retaining PICK1 PDZ liposome binding, it was found that Zn2+ significantly enhanced the liposome binding capacity of PICK1 PDZ, but that the interaction between liposomes and PICK1 PDZ decreased the ability of PICK1 PDZ to bind zinc. It was hypothesized that the Zn2+-binding might increase liposome binding by stabilization of the interaction itself or by stimulation of a PDZ/PDZ dimer  might also play an important role in regulating the membrane lipid binding of the PICK1 PDZ domain. Ser77, which is part of the proposed lipid-binding motif opposite the binding groove, is particularly interesting. Recently, Ammendrup-Johnsen et al.  the phosIn presence of liposomes the phosphorylation level of Ser77 by PKCα increased a staggering 10-fold. As PKCα is also capable of binding to lipid membranes , it was in vitro  suggesting that the redistribution from punctate PICK1-GluA2 co-clusters into more diffuse cellular co-localization might be controlled by an altered ability of PICK1 T82E to bind specific subcellular compartments  phosphorylation site. The effect of this particular phosphorylation, was recently investigated by using the PICK1 T82E mutation phospho-mimetic . In thisartments d. It is i.e., PIPs), which are prominent in the cytosolic leaflets of cellular membranes. This feature seems to rely on a surface-exposed cationic patch. The positioning of the cationic patch with respect to the peptide-binding groove differs between domains and, therefore, membrane binding also affects PDZ peptide/protein binding very differently. Another mechanism that has not been yet been described in general terms, is the insertion of hydrophobic appendices into the leaflet of the membrane bilayer as seen for the PDZ domain of PICK. Recent findings suggest that such insertion based membrane binding share several common features, including high functional affinity, slow kinetics, and membrane curvature sensing [The work reviewed here suggests that a general consensus regarding the mechanisms underlying lipid/membrane binding by PDZ domains is developing—yet direct structural evidence is still lacking and general conclusions might be compromised by the methodological gap between SPR based approaches, dot-blots and steady state cellular studies using confocal microscopy. The exact binding mechanism is likely to differ between domains; however, we review two prevailing mechanisms that have been shown to facilitate PDZ-membrane lipid interactions. Interestingly, and possibly important for cellular localization, several PDZ domains have different specificity towards negatively charged lipids ( sensing . It will


Although neither of the components is magnetic, magnetic moments emerge at the ferroelectric domain walls of PbTiO3 in these superlattices. Such a twist between ferroelectric domain and local magnetic moment, not only manifests an interesting type of multiferroicity, but also is possible useful to pursuit the electrical-control of magnetism in nanoscale heterostructures.Charge dipole moment and spin moment rarely coexist in single-phase bulk materials except in some multiferroics. Despite the progress in the past decade, for most multiferroics their magnetoelectric performance remains poor due to the intrinsic exclusion between charge dipole and spin moment. As an alternative approach, the oxide heterostructures may evade the intrinsic limits in bulk materials and provide more attractive potential to realize the magnetoelectric functions. Here we perform a first-principles study on LaAlO With the developments of modern thin film technologies, it becomes possible to fabricate and characterize oxide superlattices (SLs) and heterostructures (HSs) down to the atomic level124578910d orbitals while magnetic moments need partially-occupied d orbitals. Therefore, despite the great progress in the past decade, the magnetoelectric performance of most multiferroic bulks remains poor. An alternative route to pursuit magnetoelectricity is to utilize oxide HSs, e.g. a strong FE material plus a strong ferromagnetic (FM) material. The direct advantage of such magnetoelectric HSs is the strong FE and FM signals, however, the magnetoelectric coupling between the FE and FM layers is indirect, which is usually via the strain effect or field effect. Very recently, Rogdakis et al. obtained the FE polarization in the NdMnO3/SrMnO3/LaMnO3 SL3/SrMnO3/LaMnO3 SL is somewhat similar to the so-called type-II multiferroics, in which the FE polarizations are directly driven by magnetic orders and thus the strong magnetoelectric coupling is intrinsically guaranteed13It is the common sense that ferroelectricity (or antiferroelectricity) and ferromagnetism (or antiferromagnetism) are difficult to coexist in one system because in general FE dipoles favor empty 3 (LAO) and PbTiO3 (PTO) is investigated to pursuit the inverse property: the polarization driven magnetism. Both LAO and PTO are well studied perovskites. The choice of PTO and LAO has several reasons. First, LAO is a frequently used substrate with polar terminations [(LaO)+ and (AlO2)−] along the [001] direction, against the charge-neutral layers of PTO [(PbO)0 and (TiO2)0]. Thus the charge polar discontinuity exists in these SLs which may induce the 2DEG, similar to the situation in extensively studied LaAlO3/SrTiO3 (STO)4561516174+ and Pb2+. Thus PTO has a very strong FE polarization along the c-axis ([001] direction), which will be further enhanced by the in-plane compressive strain from LAO. Such a robust ferroelectricity is advantageous to compete with the polar discontinuity and modulate the 2DEG in SLs, while there’s no ferroelectricity involved for 2DEG in LAO/STO cases. Third, LAO is a band insulator with a large band gap (5.6 eV)3 (the latter is magnetic-active), which allows the possibility to “create” magnetic moments in these SLs. Last, despite the non-negligible lattice mismatch, previous experiments have fabricated epitaxial PTO films on the LAO substratesIn this work, another kind of oxide SLs consisting of LaAlOm/(PTO)m SLs. The first one includes both the n-type (LaO)+/(TiO2)0 and p-type (AlO2)−/(PbO)0 interfaces, as shown in n-type (LaO)+/(TiO2)0 interfaces, which can be denoted as n-n type interfaces. The third one is with double p-type (AlO2)−/(PbO)0 interfaces. It is noted that the latter two cases break the stoichiometry of original LAO and PTO, which will bring more carriers (electrons or holes) to the systems. The non-stoichiometry brought by the double p-type interfaces may result in oxygen vacanciesn-p type and n-n type SLs, and leave the double p-type SLs to further investigations. Benefited from the advancement of experimental techniques, it becomes possible to fabricate these superlattices with deserved interfaces  precisely, and the ion vacancies (e.g. oxygen vancanies) can be reduced to a minimal level. In the following studies, each n-p type SL and a double n-type SL are indexed by an integer m and a half integral m respectively.Regarding the interfaces, there are three types in these (LAO)m/(PTO)m SL with either integer or half-integer m have been investigated. Our results show that the double n-type m = 4.5 SL is the most interesting one for the magnetoelectric coupling. For the n-p interface SL at m = 4, it is predicted that the PTO layer become a polarized single-domain, no matter what the initial state of the PTO layer is. In this case, the SLs have no magnetism. However, for the n-n interface SL, several emergent phenomena are predicted. First, the internal electric field arisen from the (LaO) polar layer pointing to the doped electron in TiO2 layers makes PTO favor a head-to-head FE domain if m is no more than 3.5. For m > 3.5, the domain structure of the PTO layers depends on the initial state. More importantly, local magnetism is generated and the maximal moment appears at the domain wall. This feature allows a possible control of the position of magnetism by external electric field via the ferroelectric polarization switching, which may be useful to design a domain-wall memory. Here, an additional magnetoelectric mode accounting for the dot product of the polarization spatial gradient and squared magnetic moment is predicted.The magnetoelectric properties of the (LAO)m = 4 SL which keeps the stoichiometry of LAO and PTO layers, as sketched in n-type interface to the p-type one, as shown in D) of each layer, as shown in E) built by the asymmetric n- and p-type interfaces, as proposed in previous studiesFirst, we start from the simplest case: the E. This is due to the depolarization field of PTO itself, which is even larger than the one from polar terminations. According to our DFT calculation, the polarization of PTO bulk on the LAO substrate is 99.75 μC/cm2, which is equivalent to ~0.9 electron per unit cell surface and larger than the 0.5 electron per n-type termination. Furthermore, this fact can be easily checked by fixing the initial PE structure of PTO (thus no polarization nor depolarization field) in the calculation, then the PDOS shift (not shown here) is in opposite to that in E from the polar interfaces provides a preferred orientation  of each layer, as shown in M) in this SL quench to zero after the electronic self-consistent convergence. In short, this m = 4 SL only owns a single polarized domain and is non-magnetic. This non-magnetic result agrees with d band.All above calculations were done without magnetism. Subsequently, the magnetism is switched on. However, the initial magnetic moments  is lower than the symmetric one  for about 11–28 meV/per Ti. Even though, the symmetric domain remains meta-stable during the structure relaxation, which can play as the transition state connecting the positive/negative asymmetric FE domains.3+ in such a m = 4.5 SL. Both the FM and A-type AFM orders are taken as the initial spin structures together with the PE and FE conditions to do the structure relaxations, while the outputs after the electronic self-consistent convergence favor the FM profile. Interestingly, the involvement of magnetism does not change the displacements of ions too much, which are almost identical to those in the non-magnetic ones, as compared (solid- vs open-symbols) in 11Then magnetism is considered due to possible magnetic moment of TiB and 0.662 μB (without Hubbard U) respectively. It is reasonable that the total magnetic moment is between 0 μB and 1 μB because there is only one doped electron in the PTO part. The details of local magnetic moments with and without Hubbard U are summarized in U will not change the results qualitatively, although it enhances the local magnetic moments as expected.The magnetic moment of each ion, calculated using the Wigner-Seitz sphere as specified by VASP, is shown in As mentioned above, the doped electron can be trapped around the head-to-head domain wall in PTO layers, thus the largest local magnetic moments in both the PE and FE initial conditions always appear at the domain walls, despite the different domain wall positions. Although the charge dipole and magnetism are mutually exclusive, the local magnetism can survive at the head-to-head domain walls as an edge state effect of ferroelectrics, since the local FE displacement vanishes at such domain walls. This domain wall carried  magnetic moment is switchable electrically, rending a magnetoelectric functionality. Namely, if the domain wall is switched between the PE and FE-type ones or between the positive and negative FE-type ones by external electric fields, the peak of magnetic moments will move among the left, middle, and right of PTO layers.It should be noted that although the total magnetic moment is a constant before and after such a switch, the movement of magnetism carried by the FE domain can still be considered as a type of microscopic magnetoelectric coupling. In a famous review on multiferroics by Khomskiin-n type interfaces. Thus, here we only focus on those SLs with the n-n type interfaces: m = 1.5, 2.5, and 3.5.It is well known that FE domain structures seriously depend on the size of samples. In the SL geometry, the thickness effect of PTO layers deserves a systematic check. According to the above calculations, the induced magnetism is always associated with the FE domain wall in the SL with the m = 4.5 case, as listed in In all these thinner SLs, the initial PE and FE conditions give the same relaxed structure, with the head-to-head domain at the center layer, as shown in n-n type SLs are displayed in m. It is obvious that the total magnetic moments are significantly enhanced with the decreasing thickness of those SLs when the pure GGA method is used, which is reasonable since the average valences of Ti ions in thinner PTO cases are closer to the magnetic-active Ti3+. While using the GGA + U method, the total magnetic moment is close to the saturated value (1.0 μB due to the non-stoichiometry), and thus is almost independent of the thickness. These results agree with the scenario of FE domain wall carried magnetism. However, in these SLs, the domain walls and their affiliated magnetism are not electrical switchable.The total magnetic moments of the m cases, a thicker case is also tested. According to our above results, the LAO layers play three roles. First, the LaO terminations dope one extra electron to the PTO layers in the n-n type SLs. Second, the polar terminations build an inner electric field. Third, the highly-insulating LAO barrier confirms the extra carrier within the PTO layers. However, the cation Al3+ itself is neither ferroelectric-active nor magnetic-active, and thus the thickness of LAO layers, if not too thin, will not qualitatively affect the ferroelectricity and magnetism in the PTO layers. Thus, to save the computational CPU time, here we calculate (LAO)3.5/(PTO)6.5, in which the thickness of LAO does not equal to that of PTO, which will not alter the physical conclusion. The relaxed crystal structures  easily, while the valences of other elements are almost constants. Thus, the extra electron from the U results. Since the HSE calculation is extremely CPU-time consuming, only the shortest periodic SL (m = 1.5) and parent materials are tested, while others are beyond our computational capabilities. According to the band gaps shown in U one. The magnetic moments are 0.472 μB/Ti, also in consistent with the results of GGA + U.Second, the hybrid functional calculations with Heyd-Scuseria-Ernzerhof (HSE) exchange correlation27283/BaTiO3/SrRuO3 capacitors could form closure domains. To verify the robust of the head-to-head structure, more calculations with expanded in-plane unit-cell  have been done. Such expanded cells have been tested for both the m = 2.5 and m = 4.5 (√2 × √2 only) SLs. Starting from the proper 180° domains , identical to the above PE one in the 1 × 1 in-plane unit cell. All these results suggest that the head-to-head domain is robust since the internal field induced by the polar interface is so strong that make the charge compensation dominant rather than the compensation of breaking up the system into lateral domains.Third, generally, the head-to-head FE domain is not usual since it is energetically costly. However, previous literature reported this type of domain in PTO30313334P and magnetic moment M. From the symmetry consideration, the first-order coupling between P and M, namely P•M, is forbidden, because P violates the space-inversion symmetry but M violates the time-reversal symmetry, and the system energy should not change under the individual operation of time reversal or space inversion. The second order coupling P2M2 is allowed to manifest the magnetoelectric coupling, which can be achieved via the proximity strain effect between magnetostrictive materials and ferroelectrics with ferroelastic behavior.The FE domain wall carried magnetism revealed above is not only potentially useful in applications, but also stands for an interesting type of magnetoelectric coupling. The energy of a system can be expressed as a function of FE polarization 3 or at the Néel-type ferromagnetic domain wall. In these spiral magnets, the magnetoelectric coupling term in the energy is in the form of P• [M(∇ · M)-(M · ∇)M]P2M2. Thus this type of coupling can be essentially stronger than the conventional one, especially in terms of magnetic control of polarization. In addition, the electromagnon, namely a spin wave excited by an alternating electric field, is another type of magnetoelectric coupling, which can be expressed as a term like Pd/dt · (∇ · M) (or its variations) in the energyThe great progress of multiferroics in the past decade has revealed more types of magnetoelectric couplings. A typical example is the improper FE polarizations induced by noncollinear magnetic orders, e.g. in TbMnOP (e.g. ∇•P), can be used to couple with any terms of even order of M, e.g. M2(dPz/dz) (or its variations) in the SL geometry where z is the position vector along the stacking direction, which can also satisfy the symmetry requirements of energy. The relationship between local dPiz/dz andMi2 in all the above studied SLs (with pure GGA) is summarized in Mi2 has a coupling with dPiz/dz: a large Mi2 always accompanies a large dPiz/dz. This type of coupling, also with a lower order than the conventional P2M2, gives an intrinsically strong magnetoelectric coupling, especially in terms of electrical control of magnetism.The electromagnetic coupling revealed in the current work belongs to an additional one. In analogous to the above expression, the derivative of dPz/dz, which means a net charge at position z, classifies this type of local magnetoelectric coupling to be the carrier driven one. This concept was proposed by Rondinelli, Stengel, and Spaldin1039404142dPz/dz) at the FE-manganite interfaces controls the interfacial magnetism.In fact, the term P and M belongs to two different materials, coupled only via the interface. In the present SLs, both the local Pi and Mi reside in the single component PTO. Then the coupling between Mi2 and dPiz/dz can be locally on-site and thus more direct and stronger. The key differences of magnetoelectric coupling between these SLs and other systems are listed in Despite the similarity of our current work to these previous studies, there are still some conceptual differences. In all these previous FE-manganite HSs, the order parameters m/(LAO)m SLs. In the SLs with double n-type interfaces, the head-to-head FE domains are observed, whose structures are determined by the thickness of PTO layers and the initial FE or PE states. Such FE domains are understood as a result of the competition between the polar discontinuity and spontaneous FE polarization. The most interesting finding is that ferromagnetically aligned magnetic moments emerge at these FE domain walls. Such FE domain wall carried magnetism evades the principle of mutual exclusion between ferroelectricity and magnetism, since the local FE displacement at the head-to-head FE domain wall vanishes. In contrast, the m = 4 SL with asymmetric n- and p-type interfaces, owns a single domain  polarized by the interfaces, which is magnetism free. Our calculation predicts that m = 4.5 is a critical and optimal thickness for switchable FE domains and thus magnetoelectric function.In summery, we have investigated the crystal structures and electronic structures of (PTO)m/(PTO)m SLs, a density functional theory (DFT) calculation is performed based on the Perdew-Burke-Ernzerhoff (PBE) exchange-correlation form of generalized gradient approximation (GGA) implemented in the Vienna ab-initio simulation package (VASP)44To explore the crystal and electronic structures of the (LAO)d- and f-orbitals. Here, the band gaps of FE PTO and LAO are about 2.0 eV and 3.84 eV in our pure GGA calculation, respectively. Thus, following previous literature46U method in Liechtenstein approachUd = 5 eV, Jd = 0.64 eV on Ti’s d-orbital is also adopted to compare with the pure GGA ones. Then the band gap of PTO increases to 2.3 eV, which is closer to the previous onesf bands lie higher than the GGA prediction, Uf = 11 eV, Jf = 0.68 eV is imposed on La’s f-orbital to avoid mixing with the conduction band46505152U method which may result in  “pathological” band alignment in heterostructure2425−6 eV/u.c., and the crystal structures are relaxed until the Hellman-Feynman forces on ions are all below 0.01 eV/Å. The Monkhorst-Pack k-point mesh is 10 × 10 × 1 for the m = 4 and longer periodic SLs, and is increased for other shorter periodic SLs correspondingly.It is well known that DFT calculations often underestimate band gaps in insulating systems with localized c and the inner atoms’ positions are fully relaxed. Both the PE state and FE state of PTO are considered in these relaxations. Since the in-plane lattice constant of LAO substrate is smaller than that of PTO  are supplied in the To verify the rationality of the GGA and GGA + How to cite this article: Zhou, P. X. et al. Ferroelectricity driven magnetism at domain walls in LaAlO3/PbTiO3 superlattices. Sci. Rep.5, 13052; doi: 10.1038/srep13052 (2015).


Annotation transfer for function and structure within the sequence homology concept essentially requires protein sequence similarity for the secondary structural blocks forming the fold of a protein. A simplistic similarity approach in the case of non-globular segments  is not justified and a pertinent source for mistaken homologies. The latter is either due to positional sequence conservation as a result of a very simple, physically induced pattern or integral sequence properties that are critical for function. Furthermore, against the backdrop that the number of well-studied proteins continues to grow at a slow rate, it necessitates for a search methodology to dive deeper into the sequence similarity space to connect the unknown sequences to the well-studied ones, albeit more distant, for biological function postulations.http://dissecthmmer.bii.a-star.edu.sg.Based on our previous work of dissecting the hidden markov model (HMMER) based similarity score into fold-critical and the non-globular contributions to improve homology inference, we propose a framework-dissectHMMER, that identifies more fold-related domain hits from standard HMMER searches. Subsequent statistical stratification of the fold-related hits into cohorts of functionally-related domains allows for the function postulation of the query sequence. Briefly, the technical problems as to how to recognize non-globular parts in the domain model, resolve contradictory HMMER2/HMMER3 results and evaluate fold-related domain hits for homology, are addressed in this work. The framework is benchmarked against a set of SCOP-to-Pfam domain models. Despite being a sequence-to-profile method, dissectHMMER performs favorably against a profile-to-profile based method-HHsuite/HHsearch. Examples of function annotation using dissectHMMER, including the function discovery of an uncharacterized membrane protein Q9K8K1_BACHD (WP_010899149.1) as a lactose/H+ symporter, are presented. Finally, dissectHMMER webserver is made publicly available at The proposed framework-dissectHMMER, is faithful to the original inception of the sequence homology concept while improving upon the existing HMMER search tool through the rescue of statistically evaluated false-negative yet fold-related domain hits to the query sequence. Overall, this translates into an opportunity for any novel protein sequence to be functionally characterized.This article was reviewed by Masanori Arita, Shamil Sunyaev and L. Aravind.The online version of this article (doi:10.1186/s13062-015-0068-3) contains supplementary material, which is available to authorized users. The sequence homology concept –3 is colDespite the simplicity and elegance of the sequence homology concept, homology itself is not readily computable. Its closest surrogate is the sequence similarity measure. This measure comes along with the caveat of possibly high sequence similarity does not necessarily imply homology. Worse, as we delve deeper into sequence search space, high sequence divergence among the distant homologs will inevitably corrupt the homology signal. Hence, the only recourse to maintain on the correct search path is to piggyback on the similarity between the structural pieces of the alignment to ensure reasonable fold similarity and, hence, the implied biological function.Regrettably, current implementation of sequence search algorithms do not consciously differentiate between the 3D-structural  sequence segments and the non-globular  segments. As such, statistically significant yet spurious alignments (attributed by the remnant segments) can pass off as homologous sequences once they escape the designated statistical threshold. In mitigation though, mainstream sequence search algorithms like BLAST , 10 and And given that the number of well-studied proteins continues to grow at a slow rate , the traAs fold similarity detection is the cornerstone of homology searches and the fold is defined as the spatial arrangement of secondary structural elements , the excThe idea of dissecting the similarity score of the sequence-to-domain alignment into its fold-critical  and remnant  sums with subsequent statistical re-evaluation of their E-values was introduced in our recent work . In partWith the necessary proof of concept established in our previous work , the curIn the course of implementing dissectHMMER, several issues were resolved. Firstly, the annotation of fold-critical residues in domain models is an integral part of the score dissection idea. Previously, for domain models without PDB/DSSP information, the quality-score  was usedSecondly, the fold-critical E-value and the ratio  of a sequence-to-domain alignment are two critical surrogate measures of the fold-critical score in the score dissection idea. Briefly, a confident sequence-to-domain hit is founded on a low fold-critical E-value and a low ratio. However, the ranges of fold-critical E-values and the ratios exhibited by the HMMER variants (i.e. HMMER2 and HMMER3) can differ. Fundamentally, the difference stems from the utilized alignment modes in HMMER2  and HMMER3 . This is further underpinned by the difference between glocal gapped alignment statistics in HMMER2 and ungapped alignment statistics in HMMER3.Beyond the different statistical consideration, HMMER3 can only operate in local mode where significant hits are concluded from fragmented sequence-to-domain alignments. Unlike HMMER2, the latter is insufficient for inferring protein domain function since a domain denotes a unit of function. As such, HMMER2 glocal mode remains relevant for domain annotation work and its results can be complemented by HMMER3’s improved sensitivity and specificity that increases search space.In practice, the difference in the derived E-values by the HMMER variants can nevertheless be problematic for overlapping HMMER2 and HMMER3 sequence-to-domain alignments. At times, contradiction cases can occur, where one HMMER variants declares the hit as true and the other declares it as false.In the current work, the differences are properly quantified by dissectHMMER where the hits are associated to some expected false-positive rates. These false-positives rates which were sampled from the vicinity of negative domain hits to a set of SCOP-to-Pfam sequences, are employed to correct the fold-critical E-values and ratios accordingly. By doing so, the overlapping  sequence-to-domain results can then be merged in a justified manner after the corrections.Thirdly, an error-adjusted domain-coverage measure is introduced in dissectHMMER. Since the objective of dissectHMMER is to detect domains with similar fold, this measure accounts for the statistical significance of the domain hits, as well as the coverage of the domain. When benchmarked against a set of SCOP superfamily profiles (i.e. distant homologs with the same protein fold), dissectHMMER was found to perform favourably against its former self, HMMER and a profile-to-profile method-HHsuite/HHsearch.Finally, through several case studies of elucidating more fold-related domain hits through a deeper search depth and subsequently stratifying the quantified hits into functionally-related domain cohorts, dissectHMMER has demonstrated its ability to minimally propose a generalized function when combined with biological evidence. The latter is crucial for many novel sequences whose current search space cannot be linked to any well-characterized protein sequences. In addition, the stratification of the quantified domain hits  helps to guide the amount or level of function transfer from the most significant domain hit to the sequence, depending on the magnitude of the total FPR. As such, the dissectHMMER framework attempts to balance between over-and under-prediction of biological function while presenting an opportunity for the currently novel protein sequences to be functionally characterized as exemplified by the novel sequence Q9K8K1_BACHD (WP_010899149.1) in our case study.The HMMER score dissection framework, herewith, dissectHMMER is implemented in Perl and resides at dissecthmmer.bii.a-star.edu.sg. As depicted in Fig. In the sequence-to-domain alignment generation stage, both HMMER2  and HMMER3  were used concurrently to generate the alignment results when presented with a query sequence. In the current setup, the glocal mode for HMMER2 is enforced so that a full alignment with respect to the domain model can be made with the query sequence to maximize the belief of the domain’s overall fold similarity when the hit is subsequently evaluated to be true. In contrast, HMMER3 by itself cannot always guarantee the full alignment with respect to the domain model. As such, this can lead to fragmented sequence-to-domain alignments that suggest only partial domain fold similarity. In hindsight, the overall fold similarity to a domain is a necessary condition for inferring its biological function since the ideal notion of protein domain necessarily encompasses an unit of function by definition.overlapratio of 0.9  are calculated for each pair of overlapping HMMER2/HMMER3 sequence-to-domain alignment  domains can minimally postulate the generalized biological function of the query sequence. This is further fuelled by the fact that experimental protein studies occur under different conditions and cell-specific context. Hence, the task of cataloguing the complete biological function of any protein is a time-extended effort . In contAs an integral part of dissectHMMER, the annotation of the Pfam domains which denotes the positions of the fold-critical and remnant residues in the models, allows for the computations of fold-critical and remnant sums of a sequence-to-domain alignment. For Pfam domains with representative structure, the identification of their fold-critical residues can be resolved using the PDB/DSSP information. For those without representative structures, the identification becomes a prediction task. Previously, the quality-score (that measures sequence conservation ) has beeIn this work, the task of predicting the fold-critical residues in domain models through a weighted combination of several sequence property predictors was investigated. These predictors are quality-score (that predicts sequence conservation ), PSIPreTo evaluate the performance in terms of sensitivity (i.e. true-positive rate) and specificity  for each of the predictors, they were benchmarked against a reference set of 6599 Pfam domains with PDB/DSSP information  between the true-positive rate (TPR) and false-positive rate (FPR) at each threshold level. Based on the data from Additional file see Eqs. –2 which Figure Generally speaking, the weighted-scoring scheme performed the best amongst all the predictors, especially for false-positive rate (i.e. 1-specificity) of less than 0.235  also allow for a multi-dimensional coverage of fold-critical residues.As a result of resolving fold-critical residues in Pfam domains in the preceding section, two sets of annotated Pfam domain were derived. A set of 6599 domain models with representative PDB/DSSP entries where locations of the fold-critical or remnant residues with respect to each domain model can be straightforwardly resolved, and another set of the full 14,831 Pfam domains where the fold-critical and remnant residues are predicted using a weighted set of calibrated sequence predictors , while To properly resolve these issues, we calibrate HMMER2 and HMMER3 E-values against a set of sequence-structure-Pfam domain assignments. While the SCOP superfamilies were derived from alignments of similar structures, Pfam domains were created from alignments of homologous sequences. Essentially, the SCOP-to-Pfam mappings create a set of distant homologous Pfam domains for each SCOP superfamily where its sequences share good fold similarity. Through the sampling of the fold-critical E-value range of the negative domain hits in the vicinity of the SCOP-to-Pfam sequences, it allows dissectHMMER to examine the extent to which the fold-critical score can be used to infer fold similarity  from sequence similarity .Therefore, a set of 1330 mapped SCOP superfamilies (version 1.75) to Pfam domains (release 27) was created where each SCOP superfamily (with an average of 16.5 sequences) can be mapped to an average of 4.8 Pfam domains . The negative domain hits were then dissected into the fold-critical and remnant scores and then evaluated for their corresponding fold-critical and remnant E-values. Altogether, 136,642 HMMER2 and 41,506 HMMER3 fold-critical E-values of the negative domain hits were generated over the 22,001 SCOP sequences. Consequently, using Eq. –3. The latter falls within the recommended E-value of << 1 by the manual . ConverTaken together, the original recommended E-value cutoff of 0.1 is probably too generous for the fold-critical E-value cutoff since the false-positive rates are both over 0.50 for the HMMER variants. Conversely, if one opts to control for a common false-positive rate between the HMMER variants, then the fold-critical E-value cutoff of both HMMER algorithms need to be set at different levels, with the case of HMMER3’s being more stringent.In hindsight, it must be emphasized that this is not a comprehensive comparative study between HMMER2 and HMMER3 given the differences in the alignment modes . Moreover, it is unreasonable to assume a one-to-one correspondence relationship between HMMER2 and HMMER3 for the case of negative domain hits. Rather, we only wish to highlight that the HMMER3 local alignments do have a general tendency towards more significant E-values than HMMER2 glocal alignments at the same false-positive rate see Fig. . UnfortuAs discussed earlier, the respective false-positive rates associated to any overlapping HMMER2 and HMMER3 sequence-to-domain alignments can vary greatly at the same E-value cutoff. Although in mitigation, one may preset independent HMMER2-specific and HMMER3-specific fold-critical E-value cutoffs to limit hits beyond a common false-positive rate, this will inevitably cause some of the paired or overlapping HMMER2 and HMMER3 alignments to be orphaned. As a consequence, this may create a bias towards one of the HMMER alignments; for better or worse. Also, besides achieving statistical significance, the sequence-to-domain hit should also reflect some level of fold similarity of the domain model. This issue is particularly relevant to the HMMER3 hits since HMMER3 returns fragmented alignments, thus satisfying only partial domain fold similarity. In the case of HMMER2 hits, domain coverage is always one, since the glocal mode can be enforced.With the preceding background considerations, an error-adjusted domain coverage measure is proposed as shown by Eq. To backtrack, dissectHMMER creates a pair of fold-critical and remnant score for each sequence-to-domain alignment that is subsequently evaluated for its fold-critical E-value and its remnant E-values. As such, two surrogate measures of the fold-critical score can be derived : (i) fold-critical E-value and (ii) ratio of fold-critical E-value over remnant E-value.ratio and coveragefold ‐ critical E ‐ value . A confident sequence-to-domain hit is characterized by low fold-critical E-value and low ratio. In any case, both fold-critical E-value and ratio can be associated to some level of false-positive rate as part of the error-adjusted domain coverage formula. Therefore, two versions of the error-adjusted domain coverage for the paired HMMER2/HMMER3 alignments can be evaluated for, as represented by coverage see Eq. .For the purpose of evaluating the error-adjusted domain coverage measure of dissectHMMER, it was pit against the well-regarded profile-to-profile HMM method–HHsuite/HHsearch. The two algorithms were evaluated across 1330 SCOP superfamilies where a multiple sequence alignment of each SCOP superfamily profile was generated using the clustalw program and presented to the respective algorithms as inputs. To reiterate, each SCOP superfamily fold can be shared by several Pfam domain models. Meanwhile, since dissectHMMER is fundamentally a sequence-to-profile method, some additional steps were added to allow dissectHMMER to derive a domain-wise score measure (see Eq. 6) comparable to that of HHsearch for this evaluation.The HMMER score dissection framework: dissectHMMER webserver”) to generate a list of sequence-to-domain hits and their associated error-adjusted domain coverage score measures . Then, the collection of all sequence-to-domain hits for this SCOP profile were sorted into groups of individual domain models. As such, the averages of error-adjusted domain coverage scores per domain model can be computed (see Eq. 6) in “kratio or domainscorekfold − critical E ‐ value for the kth domain model) for the dissectHMMER algorithm.As usual, each sequence of the SCOP profile was first processed by the dissectHMMER workflow (see section “ftp://toolkit.genzentrum.lmu.de/pub/HH-suite/), the SCOP profile was directly used to sea rch against the HHsearch-specific Pfam release 27 database (PfamA_27.0.hhm downloaded from ftp://toolkit.genzentrum.lmu.de/pub/HH-suite/databases/hhsearch_dbs/). In addition, the search model was set to the “local alignment” mode to maximize for search sensitivity. For each SCOP superfamily profile, the HHSearch algorithm presented a list of domain-to-domain hits that were sorted based on their probabilities, E-values  and P-values. For this comparison, the probability score of each domain-to-domain from HHsearch is taken as its best measure against that of dissectHMMER’s.Meanwhile, for the HHsuite/HHsearch algorithm  while only 1199 SCOP superfamilies for the HHsearch algorithm. In hindsight, some SCOP profiles contain information entropy that was too low for the HHsearch to create its native HMM representation. In any case, to ensure that comparison is fair, only the common 1199 superfamilies (with 5966 mappable Pfam domains) between the two algorithms were further analyzed. This made up 80,592 domainscorefprmeasureHMMER2)coverageHMMER2 and fprmeasureHMMER3 in Eq. As a baseline prior to applying score dissection, the HMMER3 algorithm was also evaluated at three E-value cutoffs of 0.1, 1 and 10. For each of the cutoffs, only the sequence-to-domain alignment hits below the designated E-value thresholds  were kept and the domain-wise score measure is simply the domain coverage. This implies that the terms  of below 0.15, HMMER3 which belongs to the sequence-to-profile method, performed worse than the profile-to-profile method HHsearch as expected. And although HMMER3 picked up higher sensitivities than HHsearch when false-positive rates went over 0.15, large false-positive rate thresholds are seldom considered since they admit a large number of false hits.Most importantly, when the score dissection framework is integrated into the HMMER algorithm, the end results are a set of dissectHMMER’s ROC plots that hover above that of both HMMER3 and HHsearch by a considerably margin see Fig. . At a faratio and coveragefold ‐ critical E ‐ value in dissectHMMER that critically corrects the fold-critical sums of the sequence-to-domain hits with estimated false-positive rates.Taken together, dissectHMMER is more capable at detecting Pfam domains that share a superfamily fold; thus, better bridging sequence similarity search space and structural similarity search space. This better performance is underpinned by the error-adjusted domain coverage score measures coverageIn hindsight, the score dissection concept can benefit the supposedly less sensitive sequence-to-profile search method by outperforming the more superior profile-to-profile search method (e.g. HHsearch) as exemplified by dissectHMMER. It would hardly be surprising if the “dissected” version of HHsearch would improve upon itself and over dissectHMMER as well, though it is beyond the scope of this work. Overall, the improvement brought about by score dissection asserts the necessity of segregating between the fold-critical and remnant residues that is deeply rooted in the core of the homology inference problem. And beyond mere numerical improvements, dissectHMMER’s implementation is the most faithful to the sequence homology concept as compared to other current search algorithms since only the structural residues  will be considered for inferring homology.http://pfam.xfam.org/) and their domain architectures are depicted in Fig. In this section, the improved postulation of biological function for protein sequences by dissectHMMER, beyond that of the typical Pfam/HMMER analysis, was demonstrated through the analysis of three UniProt sequences: HEM1_METKA NP_613487.1), TIP12_MAIZE (NP_001105029.1) and Q9K8K1_BACHD . These sequences were first analyzed by the Pfam webserver  by dissectHMMER , was used to perform structural alignments  againstBased on the listed biological functions in Table With the exception of the IlvN domain (PF07991.7), the top 9 domain hits Shikimate_DH (PF01488.15), F420_oxidored (PF03807.12), THF_DHG_CYH_C (PF02882.14), NAD_binding_2 (PF03446.10), 2-Hacid_dh_C(PF02826.14), adh_short (PF00106.20), KR (PF08659.5), NAD_binding_7 (PF13241.1) and NAD_binding_10 (PF13460.1) are NADP+ driven anabolic processes with a total FPR range of between 0.0 and 0.06 and a structural-derived %Id range of between 9.0 and 14. Essentially, this cohort of NADP+ driven biosynthesis processes corroborates well with the notion that the HEM1_HETKA possesses a NADP+ domain to drive its tetrapyrrole biosynthesis. In the case of the IlvN domain, the structural alignment covers about 120 positions between the NADP+ binding domains of 1GPJ|A and 1YVE|A . On thiIn the second example, the analysis of 6-TM (transmembrane) TIP12_MAIZE (sequence length of 252 AA) by dissectHMMER reveals 11 relevant domain hits altogether  to some anions, chloride (Cl−) and nitrite (NO2−) respectively. The fourth domain ECF-ribofla_trS (PF07155.7) scores a total FPR of 0.61 with a structurally-derived %Id of 6.4, and is a 5-TM channel protein that transports riboflavin molecules  across the membrane. Despite the differences in the substrate specificity, the cohort of domain hits i.e., MIP, Voltage_CLC, Form_Nir_tranp and ECF-ribofla_trS generally describes a channel protein that transports its solute across the lipid membrane. This cohort ranges a total FPR of between 0.00 and 0.61 and a structurally-derived %Id of between 6.4 and 100. Although the Pfam server was also able to conclude that TIP12_MAIZE is an aquaporin  domain hit. In turn, the MIP domain has a representative PDB structure 1YMG|A that describes a bovine aquaporin . Then, t0.15 domasee Fig. , the cohIn contrast, the last domain hit BCCT (PF02028.12) describes a 12-TM antiporter (concurrent exchange of carnitine and butyrobetaine) that is mechanistically different from a channel protein. This BCCT hit scores an unimpressive total FPR of 1.01. It is further ousted as a positive domain hit by its structural alignment results against 1YMG|A and scores a bad RMSD of 9.73 and a low structurally-derived %Id of 3.8. Meanwhile, it would have been difficult to identify the other less significant channel domains  via their original HMMER2 E-values since these values can span between a much less significant range of between 3.54e–3 and 3.89e–1 as compared to the very significant E-values of MIP at 1.46e–127. At the same time, the outlier antiporter domain (BCCT) with an E-value of 7.24e–2, complicates the analysis by sitting in the middle of the range. Meanwhile, using HMMER3, only two domains, MIP and Voltage_CLC were detected at E-values of 8.5e–73 and 6.52e–05, respectively.In the last example, the dissectHMMER analysis of the uncharacterized 11-TM Q9K8K1_BACHD (sequence length of 388 AA) found 16 fold-related domain hits for further consideration  and COX1  domains. This group spans between a total FPR of between 0.18 and 0.76 with an unimpressive structurally-derived %Id of between 1.7 and 6.7 (bad RMSD range of between 4.99 and 7.4). Furthermore, the Na_H_Exchanger domain is an antiporter that is structurally different from the sugar symporters. And for the last group of peptide/amino-acid transporter, which is made up of the OPT and BCCT domain, it spans a total FPR of between 0.98 and 1.01 with a low %Id of 3.1. Taken together, Q9K8K1_BACHD is neither a proton transporter nor a peptide/amino-acid transporter given the low sequence identity and structural similarity. Rather, the uncharacterized Q9K8K1_BACHD sequence is a 11-TM sugar transporter and particularly, a lactose/H+ symporter.Based on the original HMMER2 results, the distinction among the sugar transporters , the proton transporters  and the peptide/amino-acid transporters  would have been difficult due to the highly overlapping ranges. And based on the HMMER3 results with the detection of only the DUF819 and MFS_1 domains, conclusions would have been difficult. In this example, the steep jump in E-values between DUF819 and MFS_1  would likely exclude the MFS_1 domain as a plausible hit, whereas dissectHMMER  rescues it .In hindsight, the vast range of the NADP-binding domains , channel proteins  and sugar transporters  in the preceding case studies indicates a high level of sequence divergence within the various homologous groups. This, in turn, downplayed the statistical significance of some of these hits due to the penalty imposed by the non-globular segments, when evaluated over the full alignments.Instead, by re-evaluating the fold-critical segments of the alignments through score dissection, dissectHMMER exhibits a deeper search depth and maintains a correct search path to elucidate more fold-related and relevant domain hits. And when these properly quantified and functionally-characterized hits are stratified into relevant cohorts, dissectHMMER is minimally able to postulate the generalized function of the query sequence. In the case of HEM1_METKA, its generalized biological function hints at cellular metabolism and specifically at an anabolic reaction as supported by the top hits of NADP+ binding domains . Meanwhile, for TIP12_MAIZE, it can be generalized as a channel pore that conducts some solute and particularly water/glycerol as supported by the MIP domain hit . And for the case of the novel sequence Q9K8K1_BACHD, it can be generalized as a sugar transporter and is strongly postulated to be a lactose/H+ symporter as supported by the MFS_1 domain .-,NO2-) for TIP12_MAIZE; from lactose to glucose for Q9K8K1_BACHD) occurs around the total FPR range of between 0.18 and 0.29. Anecdotally speaking, for cases where the total FPR of the most significant domain hit is below this range, the specific function may be inferred from this significant hit. However, if this most significant hit straddles around this range and beyond, the postulation of function should be limited to the level of the generalized biological function. As such, dissectHMMER attempts to balance between over and under-prediction of the biological function while transferring sufficient information to uncharacterized sequences that are currently not linked to any domain hits.At the same time, the stratification of the quantified domain hits  helps to guide the amount or level of function transfer from the most significant domain hit to the sequence. To emphasize, the change in substrate specificity between the actual and next best domain hits  and, hence, the implied biological function. However, high sequence similarity (being the only surrogate measure to homology) does not necessarily imply homology. To add further complexity, current implementation of sequence search algorithms do not consciously differentiate between the 3D-structural sequence segments and the non-globular segments of the alignments. And hence, spurious yet statistically significant alignments can be propagated as homology pieces. The situation is made worse when one attempts to transfer function annotation between two distant sequences in the deeper sequence similarity search space since this implies higher sequence divergence that inevitably corrupts the homology signal.The proposed framework, dissectHMMER, is built upon our previous work  in an atftp://ftp.ebi.ac.uk/pub/databases/Pfam/mappings/, Nov 2013), there is a total of 6863 Pfam to PDB associations. Using the initial mapping, hmmsearch (HMMER2) was performed for each of the 6863 Pfam (release 27) models against 249,830 PDB sequences extracted from the file “ss.txt” . In addition, the database size was corrected to n = 540,261 (UniProt as of April 2013) so that the E-values become more conservative. At E-value ≤1, there were 6599 Pfam-PDB mappings. In each Pfam-PDB mapping, the fold-critical residues  and the remnant residues  can be easily defined using the associated DSSP information from the “ss.txt” file. The PDB-Pfam derived residue information serves as a reference to evaluate the performance of selected sequence tools for predicting the fold-critical residues  and remnant residues (gaps ‘-’ or ‘?’) for the set of 6599 Pfam domains. These PDB/DSSP-derived Pfam domain annotations is given in Additional file Firstly, a list of Pfam-PDB mappings needs to be derived as a reference set. Based on the mapping file “pdb_pfam_mapping.txt” from the Pfam ftp site  domain model will be converted into a score vector where each alignment position exhibits a score (i.e. a score-residue pair) that ranges between the values from 0 to 1 for each of the following predictors: the quality-score  , false-positive (FP), false-negative (FN) and true-negative (TN) based on the PDB-derived residues as reference. Consequently, the false-positive rate (FPR) and true-positive rate (TPR) can be computed. The detailed results were tabulated in Additional file Based on the Table, quality-score , PSIPredTo combine the 4 predictor outputs into a single prediction outcome for each score-residue pair, a weighted-scoring scheme equation is given as follows:wqualityscore = 0.61, wPSIPred = 0.50, wSEG = 0.41 and wGlobPlot = 0.39 respectively.where predictor = {qualityscore, PSIPred, SEG, GlobPlot} and αmin = min{scoreweighted,k : k = 1.. K}, αmax = max{scoreweighted,k : k = 1.. K} and k is the alignment position of the domain model with length K.Then for each domain model, the score range is normalized to between 0 and 1 so that it is comparable to that of the predictors. This is achieved as follows:Likewise, the performance of the weighted score was evaluated and the results were tabulated in Additional file Finally, using the weighted-scoring scheme  and its corresponding sequence file “astral-scopdom-seqres-gd-all-1.75.fasta”  from the SCOP website, one can construct a list of 1330 SCOP superfamilies (i.e. cl.cf.sf) with at least 2 sequences per superfamily after removing repeated sequences and substrings.Up till SCOP release 1.75, protein sequences are subdivided into a hierarchical order of class (cl), fold (cf), superfamily (sf), family (fa) and domain(dm). Furthermore, between SCOP and PDB sequences, there is a 1:1 relationship that can be established since SCOP is a subset of the PDB database and herein, the SCOP-PDB entry. Based on the SCOP-PDB entry to SCOP classification file “dir.cla.scop.txt_1.75.txt”  using the common PDB|chain identifier so that the associated Pfam domains per SCOP superfamily could be associated. The list of SCOP superfamily to Pfam domains is provided as Additional file Then, for each of the 1330 SCOP superfamilies, the corresponding SCOP-PDB entries per superfamily were resolved against the mapping file “pdb_pfam_mapping.txt” from the Pfam ftp site  and HMMER3  algorithms were used, a query sequence can simultaneously generate both HMMER2-specific and HMMER3-specific, yet overlapping sequence-to-domain alignments. The alignments will be subjected to score reconstruction (based on Eqs. 1–2 from ) where iTo quantify the false-positive rates associated to these fold-critical scores, two surrogate measures are derived : (i) the fold-critical E-value and (ii) the ratio of fold-critical E-value over remnant E-value. These measures were derived for both HMMER2 and HMMER3 over the 1330 SCOP superfamilies with mapped Pfam domains (see preceding section).Potentially, each SCOP-PDB sequence within a superfamily can make a hit to any of the superfamily’s mapped Pfam domains. To create a hit list, each sequence in a SCOP superfamily is searched via hmmpfam (for HMMER2) or hmmscan (for HMMER3) against the full Pfam domain library  at an E-value cutoff of 20. These domain hits were then checked against the superfamily’s mapped list of Pfam domains  for the negative sets respectively. The total numbers in the ratio sets are slightly smaller than the fold-critical sets since ratios with remnant E-values of zero were excluded (i.e. ratios would have been infinity).th interval containing the cutoff value, x as follows:i is the height of interval i, x is the observed ratio or fold-critical E-value to be used as the cutoff. Essentially, P(measure ≤ x) denotes the chances of seeing a value smaller than the observed value (i.e. x) under the null hypothesis that assumes all sample observations arise by chance.Figures −2.25), the corresponding FPR for HMMER2 is found to be about 0.1 . Similarly, based on Fig. −3.45), the FPR is found to be approximately 0.1 (see dotted line) for HMMER2. Meanwhile, the fold-critical E-value is set at 1.0e–6 (10−6) for the same FPR for HMMER3 based on Fig. As an example, given the ratio between fold-critical versus remnant E-values of 0.056 , false-negative (FN), false-positive (FP) and true-negative (TN), the cutoff values have to be determined for the (i) original E-value  and the (ii) fold-critical E-value.−3 . For the fold-critical E-value, the HMMER2 and HMMER3 values are 10–3.45 and 10−6 respectively. These values has an associated false-positive rate of 0.1. As a result, the criteria for the hit classification are summarized in Table For the original E-value, the reference is taken from the recommended HMMER2 E-value for trusted hits  at 0.1  is the start and end positions of sequence segment i,  is the start and end positions of sequence segment j.where  of length L can be created using the clustalw program as follows :ij is the amino acid alphabet or a gap, i is the index of the sequence and j is the alignment position.where SFor each sequence, dissectHMMER will be applied to generate the sequence-to-domain alignment hits and the associated error-adjusted domain coverage mesasures . Nevertheless, the obtained results are quite notable as in Fig. In the background section, it is better to explain the difference between HMMER2 and HMMER3 because their difference is crucial in the analysis. Explanation of the glocal mode and the limitation of HMMER3 because of its statistical model greatly helps readers to understand the merits of using both tools other than speed.We thank the reviewer for his kind comments on our work. We have added some explanation in the background section to better explain the rationale of using both HMMER2 and HMMER3.Authors’ response: The performance comparison with HHsearch needs more care: although tools were compared on 1199 SCOP families, a part of them could only create marginal HMM representation due to the family size. I would like to know the performance by using large families only, because the number of families for comparison needs not be as much as 1000. If there is a performance difference depending on fold superfamilies, that would also provide important insights for readers.We thank the reviewer for his critical consideration. In fact, the issue is slightly more involved. Out of the 131 SCOP superfamilies that were unable to generate HHsearch profiles, 125 of them indeed contain 6 or less sequences. At the same time, 6 other SCOP superfamilies have between 11 and 1318 sequences. While insufficient sequences can degenerate the quality of a HMM profile, the multiple sequence alignment of a large superfamily can also be challenging at the same time. In hindsight, the quality of the multiple sequence alignment is also an important factor that contributes to the entropy of a HMM profile, especially for profile-to-profile based methods like HHsearch.Authors’ response: To illustrate the point, the top 5 % (65 out of 1199) of SCOP superfamilies with large alignments (i.e. the number of sequences >60) were excluded while the attempt to exclude superfamilies with low number of sequences does not further improve the HHsearch plot (data not shown). Overall, the performance comparison for 1134 SCOP superfamilies is depicted in Fig.13.Compared to Fig.6, all individual plots  were generally shifted towards better sensitivity (i.e. TPR) with the plot of HHsearch being dramatically improved and almost comparable to the dissectHMMER[Ratio] plot. Despite so, at a FPR of ≤0.05, dissectHMMER remains more sensitive than HHsearch, given the latter’s best performance in this comparison. As such, the results again reinforced that score dissection can improve fold similarity detection in existing methods, namely, HMMER3, and comparable to a profile-to-profile search method like HHsearch.Minor points:Page 3 first paragraph: The word “inductive proof” is too strong a word. Since this is not a mathematics paper I would suggest a softer language than a proof.Page 12 2nd paragraph: “for better or worst” --> worse?Page 13 2nd paragraph: “profile-to-profile HMMER method” --> “profile-to-profile HMM method”Page 19 2nd last paragraph: “dissecthmmer” --> “dissectHMMER”The minor points have all been addressed in the revised manuscript.Authors’ response: This manuscript offers a framework to evaluate remote homology by focusing on positions critical to protein folds. It combines HMMER search with methods for predicting disordered regions. The method has been successfully validated and implemented as an online tool. This development is of interest and the tool is potentially useful. As a minor comment, the paper can be written in a more economical and focused way. A shorter title may also be better.We thank the reviewer for his kind comments and we have shortened the title. Though the manuscript’s main aim is to provide an improved search tool to evaluate homology, the rationale behind dissectHMMER also needs to be sufficiently justified in the manuscript. As such, the existing text is considered polished and tightened.Authors’ response: The paper develops a concept worked out by the authors that the “dissection” of positions into fold critical versus non-globular contributions improves judgement of homology and thereby function prediction. In conceptual terms this proposal might be viewed in two potentially opposing ways: On one hand, the separation of the fold-critical and non-globular parts in the domain model is expected to reduce “false signal” of homology that tends to arise from non-globular regions. This is favorably reflected in the benchmarking experiments presented here by the authors. Indeed, the directed use of the fold-critical parts of the model seem to enhance recognition of correct structural relationship. On the other hand it should be kept in mind that natural selection does not entirely respect the fold-critical-non-globular dichotomy with potentially functionally critical constellations of residues being lodged in regions deemed non-globular. These can provide specific functional information that goes over and beyond the basic fold-recognition, and in some cases tend to be strongly conserved. Hence, the removal of such can potentially hamper function inference. The authors might hence want to clearly specify how this might affect their approach.The reviewer has highlighted an important issue. We agree that the well-conserved non-globular segments might contain useful functional annotations like the cases of many diverse PTM sites/motifs. However, fold similarity  implies an overall emphasize over the full-length domain scoring whereas functional sites/motifs are small and localized signals that covers only part of the larger domain model. As such, the latter remains complementary for further clarifying sequence-to-domain hits that have similar fold-critical scores. But alone, it is likely to attract sequence-to-domain hits of unrelated biological functions, which is the bane of the problem in functional annotation.Authors’ response: In practice, dissectHMMER considers short non-globular aligned segments of ≤10 alignment positions as part of the fold-critical segments. These segments are generally well-conserved in the multiple sequence alignment (See methods: Annotation of Pfam domain models…) yet they are in minority. Mostly, the non-globular alignment segments in domain models have many gaps (due to varying inter-linkers lengths) and the supposedly conserved pieces are also not well-aligned. The latter is largely responsible for the spurious sequence-to-domain hits and the situation is made worse when used with the local-mode only HMMER3. To properly capture the non-globular functional sites/motifs in each domain model, the sites/motifs need to be detected via specific PTM predictors and then to construct some well-conserved alignment out of them. Finally, only part of the overall gapped alignment that captures the well-conserved pieces should be considered as part of the fold-critical segments. However, this is beyond the scope of the current work.The second aspect of this work pertains to functional inference from fold recognition. Here the key process followed by the authors is the stratification of hits in clusters of related domains. The biological evidence can be of two types:1) a biochemical function which can have differing levels of precision, like “methylase” or “methylase catalyzing methylation of particular substrate”, etc. and2) general biological function like “epigenetic modification”. It is not clear how these are distinguished in during the creation of cohorts during analysis of the hits. The former tends to be much more informative in terms of function prediction:Historically, most domain libraries (e.g. SMART and Pfam) started with the collection of models that describe enzymatic/biochemical function and hence characterized by folds (as evident in the early versions of domain libraries). In contrast, biological function like “epigenetic modification” describes the more localized functional annotations of the models. dissectHMMER works towards detecting sequence-to-domain hits that shares good fold similarity to infer function of the first type. Adding the extra description of localized functional annotations of the second type (as our future work) will help to further segregate the results into more defined sub-cohorts.Authors’ response: Minor:-The results in the abstract are presented in the past tense: it might be stylistically better to use the present tense to distinguish current work from previously published work.-Several figures were invisible in the PDF version for review making some of the statements hard to visualize-Regretfully - > “Regrettably” would make better sense-DUF819 is called PF05684.7 but in Pfam it is just PF05684.The preceding minor points have all been addressed in the revised manuscript.Authors’ response: -DUF819 belongs in “Clan” with several other transported which could be used for functional inference though by itself it is a DUF.Although DUF819 belongs to the CPA superfamily (clan: CL0064) and is suggestive of transporter function, its specific function is more difficult to clarify this way.Authors’ response: