Quod erat demonstrandum? The mystery of experimental validation of apparently erroneous computational analyses of protein sequences

BACKGROUND: Computational predictions are critical for directing the experimental study of protein functions. Therefore it is paradoxical when an apparently erroneous computational prediction seems to be supported by experiment. RESULTS: We analyzed six cases where application of novel or conventional computational methods for protein sequence and structure analysis led to non-trivial predictions that were subsequently supported by direct experiments. We show that, on all six occasions, the original prediction was unjustified, and in at least three cases, an alternative, well-supported computational prediction, incompatible with the original one, could be derived. The most unusual cases involved the identification of an archaeal cysteinyl-tRNA synthetase, a dihydropteroate synthase and a thymidylate synthase, for which experimental verifications of apparently erroneous computational predictions were reported. Using sequence-profile analysis, multiple alignment and secondary-structure prediction, we have identified the unique archaeal 'cysteinyl-tRNA synthetase' as a homolog of extracellular polygalactosaminidases, and the 'dihydropteroate synthase' as a member of the beta-lactamase-like superfamily of metal-dependent hydrolases. CONCLUSIONS: In each of the analyzed cases, the original computational predictions could be refuted and, in some instances, alternative strongly supported predictions were obtained. The nature of the experimental evidence that appears to support these predictions remains an open question. Some of these experiments might signify discovery of extremely unusual forms of the respective enzymes, whereas the results of others could be due to artifacts

Lipogenesis and redox balance in nitrogen-fixing pea bacteroids

Within legume root nodules, rhizobia differentiate into bacteroids that oxidise host-derived dicarboxylic acids, which is assumed to occur via the TCA-cycle to generate NAD(P)H for reduction of N2. Metabolic flux analysis of laboratory grown Rhizobium leguminosarum showed that the flux from 13C-succinate was consistent with respiration of an obligate aerobe growing on a TCA-cycle intermediate as the sole carbon source. However, the instability of fragile pea bacteroids prevented their steady state labelling under N2-fixing conditons. Therefore, comparitive metabolomic profiling was used to compare free-living R. leguminosarum with pea bacteroids. While the TCA-cycle was shown to be essential for maximal rates of N2-fixation, pyruvate (5.5-fold down), acetyl-CoA (50-fold down), free coenzyme A (33-fold) and citrate (4.5-fold down) were much lower in bacteroids. Instead of completely oxidising acetyl-CoA, pea bacteroids channel it into both lipid and the lipid-like polymer poly-β-hydroxybutyrate (PHB), the latter via a type II PHB synthase that is only active in bacteroids. Lipogenesis may be a fundamental requirement of the redox poise of electron donation to N2 in all legume nodules. Direct reduction by NAD(P)H of the likely electron donors for nitrogenase, such as ferredoxin, is inconsistent with their redox potentials. Instead, bacteroids must balance the production of NAD(P)H from oxidation of acetyl-CoA in the TCA-cycle with its storage in PHB and lipids

CHASE : an extracellular sensing domain common to transmembrane receptors from prokariotes, lower eukaryotes and plants

International audienc

Comment les bactéries perçoivent et répondent aux modifications de leur environnement ? Génomique comparative des systèmes à deux composantes bactériens : organisation, distribution et fonction

National audienc

Three unrelated chemoreceptors provide Pectobacterium atrosepticum with a broad-spectrum amino acid sensing capability

Amino acids are important nutrients and also serve as signals for diverse signal transduction pathways. Bacteria use chemoreceptors to recognize amino acid attractants and to navigate their gradients. In Escherichia coli two likely paralogous chemoreceptors Tsr and Tar detect 9 amino acids, whereas in Pseudomonas aeruginosa the paralogous chemoreceptors PctA, PctB and PctC detect 18 amino acids. Here, we show that the phytobacterium Pectobacterium atrosepticum uses the three non-homologous chemoreceptors PacA, PacB and PacC to detect 19 proteinogenic and several non-proteinogenic amino acids. PacB recognizes 18 proteinogenic amino acids as well as 8 non-proteinogenic amino acids. PacB has a ligand preference for the three branched chain amino acids L-leucine, L-valine and L-isoleucine. PacA detects L-proline next to several quaternary amines. The third chemoreceptor, PacC, is an ortholog of E. coli Tsr and the only one of the 36 P. atrosepticum chemoreceptors that is encoded in the cluster of chemosensory pathway genes. Surprisingly, in contrast to Tsr, which primarily senses serine, PacC recognizes aspartate as the major chemoeffector but not serine. Our results demonstrate that bacteria use various strategies to sense a wide range of amino acids and that it takes more than one chemoreceptor to achieve this goal.This work was supported by the Spanish Ministry for Science and Innovation/Agencia Estatal de Investigación 10.13039/501100011033 (grants PID2020-112612GB-I00 to TK and PID2019-103972GA-I00 to MAM), the Junta de Andalucía (grant P18-FR-1621 to TK) and the NIH (grant 1R35GM131760 to I.B.Z.)

Amine-recognizing domain in diverse receptors from bacteria and archaea evolved from the universal amino acid sensor

Bacteria possess various receptors that sense different signals and transmit information to enable an optimal adaptation to the environment. A major limitation in microbiology is the lack of information on the signal molecules that activate receptors. Signals recognized by sensor domains are poorly reflected in overall sequence identity, and therefore, the identification of signals from the amino acid sequence of the sensor alone presents a challenge. Biogenic amines are of great physiological importance for microorganisms and humans. They serve as substrates for aerobic and anaerobic growth and play a role of neurotransmitters and osmoprotectants. Here, we report the identification of a sequence motif that is specific for amine-sensing sensor domains that belong to the Cache superfamily of the most abundant extracellular sensors in prokaryotes. We identified approximately 13,000 sensor histidine kinases, chemoreceptors, receptors involved in second messenger homeostasis and Ser/Thr phosphatases from 8,000 bacterial and archaeal species that contain the amine-recognizing motif. The screening of compound libraries and microcalorimetric titrations of selected sensor domains confirmed their ability to specifically bind biogenic amines. Mutants in the amine-binding motif or domains that contain a single mismatch in the binding motif had either no or a largely reduced affinity for amines. We demonstrate that the amine-recognizing domain originated from the universal amino acid-sensing Cache domain, thus providing insight into receptor evolution. Our approach enables precise "wet"-lab experiments to define the function of regulatory systems and therefore holds a strong promise to enable the identification of signals stimulating numerous receptors.This work was supported by the Spanish Ministry for Science and Innovation/Agencia Estatal de Investigación 10.13039/501100011033 (grant PID2020- 112612GB- I00 to T.K.) and the Junta de Andalucía (grant P18- FR- 1621 to T.K.) and by the US National Institutes of Health (grant R35GM131760 to I.B.Z.). J.P.C.- V. was supported by the grant Unión Europea- NextGeneration EU RD 289/2021 UPM- Recualifica Margarita Salas

Bioinformatic prediction and experimental validation of signals recognised by sensor domains in bacterial receptors: the case of amino acid specific dcache_1AA domain

Resumen del poster presentado en: XIII Reunión del Grupo de Microbiología Molecular de La SEM. Granada, 7-9 septiembre (2022)This work was supported by grants PID2019-103972GA-I00 (to M.A.M.) and PID2020-112612GBI00 (to T.K.) from the Spanish Ministry for Science and Innovation/Agencia Estatal de Investigación 10.13039/501100011033 and grant P18-FR-1621(to T.K.) from the Junta de Andalucía

Emergence of an auxin sensing domain in plant-associated bacteria

Bacteria have evolved a sophisticated array of signal transduction systems that allow them to adapt their physiology and metabolism to changing environmental conditions. Typically, these systems recognize signals through dedicated ligand binding domains (LBDs) to ultimately trigger a diversity of physiological responses. Nonetheless, an increasing number of reports reveal that signal transduction receptors also bind antagonists to inhibit responses mediated by agonists. The mechanisms by which antagonists block the downstream signaling cascade remain largely unknown. To advance our knowledge in this field, we used the LysR-type transcriptional regulator AdmX as a model. AdmX activates the expression of an antibiotic biosynthetic cluster in the rhizobacterium Serratia plymuthica. AdmX specifically recognizes the auxin phytohormone indole-3-acetic acid (IAA) and its biosynthetic intermediate indole-3-pyruvic acid (IPA) as signals. However, only IAA, but not IPA, was shown to regulate antibiotic production in S. plymuthica. Here, we report the high-resolution structures of the LBD of AdmX in complex with IAA and IPA. We found that IAA and IPA compete for binding to AdmX. Although IAA and IPA binding does not alter the oligomeric state of AdmX, IPA binding causes a higher degree of compactness in the protein structure. Molecular dynamics simulations revealed significant differences in the binding modes of IAA and IPA by AdmX, and the inspection of the three-dimensional structures evidenced differential agonist- and antagonist-mediated structural changes. Key residues for auxin binding were identified and an auxin recognition motif defined. Phylogenetic clustering supports the recent evolutionary emergence of this motif specifically in plant-associated enterobacteria.This study was supported through grants from the CSIC to M.A.M. (PIE-202040I003), from the Spanish Ministry for Science and Innovation/Agencia Estatal de Investigación 10.13039/501100011033 (PID2019-103972GA-I00 to M.A.M., grant PID2020-112612GB-I00 to T.K. and PID2020-116261GB-I00 to J.A.G.), the Junta de Andalucía (grant P18-FR-1621 to T.K.), by NIH Grant 1R35GM131760 (to I.B.Z.), and by the Academic Leadership Program Priority 2030 proposed by Federal State Autonomous Educational Institution of Higher Education I. M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University) to Y.B.P. A.O. acknowledges support by the Ministry of Science and Innovation (MCIN), the State Research Agency (AEI/10.13039/501100011033), the European Regional Development Fund (RTI2018–094393-BC21-MCIU/AEI/FEDER, UE), and the Seneca Foundation CARM, 20786/PI/18. We are grateful to the European Synchrotron Radiation Facility (ESRF) for the provision of time and to the staff at beamlines ID23-1, ID23-2, and ID30A-3 and at the Xaloc beamline of the ALBA Spanish synchrotron radiation source (Barcelona) for assistance during data collection