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Primary sclerosing cholangitis (PSC) is characterized by progressive biliary inflammation and fibrosis. Although gut commensals are associated with PSC, their causative roles and therapeutic strategies remain elusive. Here we detect abundant Klebsiella pneumoniae (Kp) and Enterococcus gallinarum in fecal samples from 45 PSC patients, regardless of intestinal complications. Carriers of both pathogens exhibit high disease activity and poor clinical outcomes. Colonization of PSC-derived Kp in specific pathogen-free (SPF) hepatobiliary injury-prone mice enhances hepatic Th17 cell responses and exacerbates liver injury through bacterial translocation to mesenteric lymph nodes. We developed a lytic phage cocktail that targets PSC-derived Kp with a sustained suppressive effect in vitro. Oral administration of the phage cocktail lowers Kp levels in Kp-colonized germ-free mice and SPF mice, without off-target dysbiosis. Furthermore, we demonstrate that oral and intravenous phage administration successfully suppresses Kp levels and attenuates liver inflammation and disease severity in hepatobiliary injury-prone SPF mice. These results collectively suggest that using a lytic phage cocktail shows promise for targeting Kp in PSC., (© 2023. The Author(s).)

Human gut commensals are increasingly suggested to impact non-communicable diseases, such as inflammatory bowel diseases (IBD), yet their targeted suppression remains a daunting unmet challenge. In four geographically distinct IBD cohorts (n = 537), we identify a clade of Klebsiella pneumoniae (Kp) strains, featuring a unique antibiotics resistance and mobilome signature, to be strongly associated with disease exacerbation and severity. Transfer of clinical IBD-associated Kp strains into colitis-prone, germ-free, and colonized mice enhances intestinal inflammation. Stepwise generation of a lytic five-phage combination, targeting sensitive and resistant IBD-associated Kp clade members through distinct mechanisms, enables effective Kp suppression in colitis-prone mice, driving an attenuated inflammation and disease severity. Proof-of-concept assessment of Kp-targeting phages in an artificial human gut and in healthy volunteers demonstrates gastric acid-dependent phage resilience, safety, and viability in the lower gut. Collectively, we demonstrate the feasibility of orally administered combination phage therapy in avoiding resistance, while effectively inhibiting non-communicable disease-contributing pathobionts., Competing Interests: Declaration of interests H. Sokol received consultancy or lecture fees from Carenity, Abbvie, Astellas, Danone, Ferring, Mayoly Spindler, MSD, Novartis, Roche, Tillots, Enterome, Maat, BiomX, Biose, and Takeda and is a co-founder of Exeliom Bioscience. N.M. received consultancy or lecture fees from BiomX, Pfizer, Takeda, Janssen, Ferring, Nestle, and BMS and grant support from Takeda, Janssen, Abbott, Pfizer, Abbvie, Neopharm, Corundum Innovation Ltd, Mycolivia, and Nestle. S.K.-R., E.W., Y.M, Y.S., I.W., E.K., N.B.-I., D.I., H.B.-D., J.N., N.K., E.K., T.C., E.F.-G., L.Z., A.C., U.R., I.G.-S., M.G., V.L., N.Z., S.P., and M.S. are paid BiomX employees. R.S. is a scientific cofounder of Ecophage and BiomX. E.E. is a scientific cofounder of DayTwo and BiomX and an advisor to Hello Inside and Aposense. E.E. serves as a scientific advisory board member in Cell. A patent proposal has been submitted by the Weizmann Institute of Science and BiomX., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Summary: Next-Generation Sequencing is widely used as a tool for identifying and quantifying microorganisms pooled together in either natural or designed samples. However, a prominent obstacle is achieving correct quantification when the pooled microbes are genetically related. In such cases, the outcome mostly depends on the method used for assigning reads to the individual targets. To address this challenge, we have developed Exodus-a reference-based Python algorithm for quantification of genomes, including those that are highly similar, when they are sequenced together in a single mix. To test Exodus' performance, we generated both empirical and in silico next-generation sequencing data of mixed genomes. When applying Exodus to these data, we observed median error rates varying between 0% and 0.21% as a function of the complexity of the mix. Importantly, no false negatives were recorded, demonstrating that Exodus' likelihood of missing an existing genome is very low, even if the genome's relative abundance is low and similar genomes are present in the same mix. Taken together, these data position Exodus as a reliable tool for identifying and quantifying genomes in mixed samples. Exodus is open source and free to use at: https://github.com/ilyavs/exodus., Availability and Implementation: Exodus is implemented in Python within a Snakemake framework. It is available on GitHub alongside a docker containing the required dependencies: https://github.com/ilyavs/exodus. The data underlying this article will be shared on reasonable request to the corresponding author., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press.)

In fish, both follicle-stimulating hormone (FSH) and luteinizing hormone (LH) play important roles in reproduction. Here we explored the structure and differential specificity of tilapia (t) gonadotropins (GTHs) to delineate their physiological relevance and the nature of their regulation. We generated structural models of tGTHs and GTH receptors (R) that enabled us to better understand the hormone-receptor interacting region. In tilapia, FSH release is under the control of the hypothalamic decapeptide GnRH, an effect that was abolished by specific bioneutralizing antisera [anti-recombinant (r) tFSHβ]. These antisera also reduced the basal secretion and delayed GnRH-stimulated production of 11-ketotestosterone (11KT), and dramatically reduced LH levels. Immunoneutralization of tLH using anti-rtLHβ significantly reduced its GnRH-stimulated levels. Basal 11KT and FSH levels were also reduced. Taken together, these results suggest a feedback mechanism between FSH and LH release in tilapia., (Copyright © 2014 Elsevier Inc. All rights reserved.)

G-protein-coupled receptors (GPCRs) are a large superfamily of membrane receptors that are involved in a wide range of signaling pathways. To fulfill their tasks, GPCRs interact with a variety of partners, including small molecules, lipids and proteins. They are accompanied by different proteins during all phases of their life cycle. Therefore, GPCR interactions with their partners are of great interest in basic cell-signaling research and in drug discovery.Due to the rapid development of computers and internet communication, knowledge and data can be easily shared within the worldwide research community via freely available databases and servers. These provide an abundance of biological, chemical and pharmacological information.This chapter describes the available web resources for investigating GPCR interactions. We review about 40 freely available databases and servers, and provide a few sentences about the essence and the data they supply. For simplification, the databases and servers were grouped under the following topics: general GPCR-ligand interactions; particular families of GPCRs and their ligands; GPCR oligomerization; GPCR interactions with intracellular partners; and structural information on GPCRs. In conclusion, a multitude of useful tools are currently available. Summary tables are provided to ease navigation between the numerous and partially overlapping resources. Suggestions for future enhancements of the online tools include the addition of links from general to specialized databases and enabling usage of user-supplied template for GPCR structural modeling.

The gonadotropins follicle-stimulating hormone (FSH) and luteinizing hormone (LH) and their receptors play critical roles in vertebrate reproduction. In order to study intra- and interspecies ligand promiscuity of gonadotropins, COS-7 cells were transiently transfected with one of the gonadotropin receptor genes, FSHR or LHR, and tested for activation by gonadotropins from representative fish orders: Aquilliformes (eel; e), Salmoniformes (trout; tr), and Perciformes (tilapia; ta), and of mammalian origin: porcine (p), bovine (b) and human (h). The study reveals complex relations between the gonadotropin hormones and their receptors. Each gonadotropin activated its own cognate receptor. However, taLHR was also activated by hCG and eLHR was activated by hFSH, hCG, and trFSH. For FSHR, the only cross-reactivity detected was for hFSHR, which was activated by pFSH and bFSH. These findings are of great interest and applicability in the context of activation of various GTHRs by their ligands and by ligands from other vertebrates. Analysis of the three-dimensional models of the structures highlights the importance of residues outside of the currently established hormone-receptor interface region. In addition, the interface residues in taFSHR and the effect of exon duplication, which causes an insert in the LRR domain, are suggested to affect the interaction and binding of taFSH., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

Experimental evidence suggests that most members of class A G-protein coupled receptors (GPCRs) can form homomers and heteromers in addition to functioning as single monomers. In particular, serotonin (5-HT) receptors were shown to homodimerize and heterodimerize with other GPCRs, although the details and the physiological role of the oligomerization has not yet been fully elucidated. Here we used computational modeling of the 5-HT(1A) receptor monomer and dimer to predict residues important for dimerization. Based on these results, we carried out rationally designed site-directed mutagenesis. The ability of the mutants to dimerize was evaluated using different FRET-based approaches. The reduced levels of acceptor photobleaching-Förster resonance energy transfer (FRET) and the lower number of monomers participating in oligomers, as assessed by lux-FRET, confirmed the decreased ability of the mutants to dimerize and the involvement of the predicted contacts (Trp175(4.64), Tyr198(5.41), Arg151(4.40), and Arg152(4.41)) at the interface. This information was reintroduced as constraints for computational protein-protein docking to obtain a high-quality dimer model. Analysis of the refined model as well as molecular dynamics simulations of wild-type (WT) and mutant dimers revealed compensating interactions in dimers composed of WT and W175A mutant. This provides an explanation for the requirement of mutations of Trp175(4.64) in both homomers for disrupting dimerization. Our iterative computational-experimental study demonstrates that transmembrane domains TM4/TM5 can form an interaction interface in 5-HT(1A) receptor dimers and indicates that specific amino acid interactions maintain this interface. The mutants and the optimized model of the dimer structure may be used in functional studies of serotonin dimers.

The critical assessment of protein interactions (CAPRI) experiment provides a unique opportunity for unbiased assessment of docking procedures. The recent CAPRI targets T29-T42 entailed docking of bound, unbound, and modeled structures, presenting a wide range of prediction difficulty. We submitted accurate predictions for targets T40, T41, and T42, a good prediction for T32 and acceptable predictions for T29 and T34. The accuracy of our docking results generally matched the prediction difficulty; hence, docking of modeled proteins produced less accurate results. However, there were interesting exceptions: an accurate prediction was submitted for the dimer of modeled tetratricopeptide repeat (T42) and only an acceptable prediction for the bound/unbound case T29. The ensembles of docking models produced in the scans included an acceptable or better prediction for every target. We show here that our recently developed postscan reevaluation procedure, which tests propensity and solvation measures of the whole interface and the interface core, successfully distinguished these predictions from false docking models. For enzyme-inhibitor targets, we show that the distance of the interface from the enzyme's centroid ranked high native like docking models. Also, for one case we demonstrate that docking of an ensemble of conformers produced by normal modes analysis can improve the accuracy of the prediction., (© 2010 Wiley-Liss, Inc.)

Computational protein-protein docking scans commonly produce correct and nearly correct interaction models, but sometimes these models are ranked low. We present here postscan processing procedures that dramatically enhance the distinction between nearly correct and false predictions. The procedures employ propensity descriptors calculated for the interface core, an interface-core clusters count, solvation energy, and a geometric-electrostatic-hydrophobic complementarity score. The various descriptors rank high different selections of false models (shuffling effect), and therefore, are used as Boolean yes/no classifiers in soft intersection filters, which eliminate large proportions of false models. Furthermore, the standardized descriptors are used in new scoring functions that highlight nearly correct models (NCMs). All the tests are performed on unbound docking models produced with MolFit without use of external data. We find that the discrimination between nearly correct and false models by the various descriptors is class dependent; hence, our postscan processing is class specific. The filters reduce the number of putative models from 10,726, 12,517, and 11,054 to 758, 157, and 1218 for enzyme-inhibitor, antibody-antigen, and nonclassified systems. When combined with the new scoring functions, they improve the average rank of the highest ranking NCMs from 673 to 122. Application to 23 CAPRI targets demonstrates the effectiveness of the postscan procedures in cases where external information is used in the production of the putative models. Our new per-molecule residue propensity descriptors show that interacting interfaces are enriched with high propensity residues except for antigenic sites, which resemble more the noninteracting regions of protein surfaces.

Motivation: The limited success rate of protein-protein docking procedures is generally attributed to structure differences between the bound and unbound states of the molecules. Herein we analyze a large dataset of protein-protein docking results and identify additional parameters that affect the performance of docking procedures., Results: We find that the distinction between nearly correct models (NCMs) and decoys depends on the size of the interface to be predicted thus setting a limit to the prediction ability of docking procedures, particularly those in which the geometric complementarity descriptor is dominant. The geometric complementarity score in grid-based docking carries a large statistical error which further reduces the distinction between NCMs and decoys. We propose a method for correcting the statistical error and show that the distinction is improved when the docking models are ranked by statistically equivalent scores., Availability: MolFit can be downloaded from our website http://www.weizmann.ac.il/Chemical_Research_Support/molfit., Supplementary Information: Supplementary data are available at Bioinformatics online.

Cleavage fragments of de novo synthesized vimentin were recently reported to interact with phosphorylated Erk1 and Erk2 MAP kinases (pErk) in injured sciatic nerve, thus linking pErk to a signaling complex retrogradely transported on importins and dynein. Here we clarify the structural basis for this interaction, which explains how pErk is protected from dephosphorylation while bound to vimentin. Pull-down and ELISA experiments revealed robust calcium-dependent binding of pErk to the second coiled-coil domain of vimentin, with observed affinities of binding increasing from 180 nM at 0.1 microM calcium to 15 nM at 10 microM calcium. In contrast there was little or no binding of non-phosphorylated Erk to vimentin under these conditions. Geometric and electrostatic complementarity docking generated a number of solutions wherein vimentin binding to pErk occludes the lip containing the phosphorylated residues in the kinase. Binding competition experiments with Erk peptides confirmed a solution in which vimentin covers the phosphorylation lip in pErk, interacting with residues above and below the lip. The same peptides inhibited pErk binding to the dynein complex in sciatic nerve axoplasm, and interfered with protection from phosphatases by vimentin. Thus, a soluble intermediate filament fragment interacts with a signaling kinase and protects it from dephosphorylation by calcium-dependent steric hindrance.

Substrate recognition and specificity are essential for the reliability and fidelity of protein kinase function. GSK-3 has a unique substrate specificity that requires prior phosphorylation of its substrates. However, how the enzyme selects its phosphorylated substrates is unknown. Here, we combined in silico modeling with mutagenesis and biological studies to identify GSK-3-substrate interaction sites located within its binding cleft. Protein-protein docking of GSK-3beta and the phosphorylated cAMP responsive element binding protein (pCREB) (using the available experimentally determined structures), identified Phe67, Gln89, and Asn95 of GSK-3beta as putative binding sites interacting with the CREB phosphorylation motif. Mutations of these residues to alanine impaired GSK-3beta phosphorylation of several substrates, without abrogating its autocatalytic activity. Subsequently, expression of the GSK-3beta mutants in cells resulted in decreased phosphorylation of substrates CREB, IRS-1, and beta-catenin, and prevented their suppression of glycogen synthase activity as compared with cells expressing the wild-type GSK-3beta. Our studies provide important additional understanding of how GSK-3beta recognizes its substrates: In addition to prior phosphorylation typically required in GSK-3 substrates, substrate recognition involves interactions with GSK-3beta residues: Phe67, Gln89, and Asn95, which confer a common basis for substrate binding and selectivity, yet allow for substrate diversity.