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B L Taylor

Publications and source records attributed to B L Taylor.

At least 19 recordsLinked to original sources
PubMed2000

PAS domain residues involved in signal transduction by the Aer redox sensor of Escherichia coli.

PAS domains sense oxygen, redox potential and light, and are implicated in behaviour, circadian rhythmicity, development and metabolic regulation. Although PAS domains are widespread in archaea, bacteria and eukaryota, the mechanism of signal transduction has been elucidated only for the bacterial photo sensor PYP and oxygen sensor FixL. We investigated the signalling mechanism in the PAS domain of Aer, the redox potential sensor and aerotaxis transducer in Escherichia coli. Forty-two residues in Aer were substituted using cysteine-replacement mutagenesis. Eight mutations resulted in a null phenotype for aerotaxis, the behavioural response to oxygen. Four of them also led to the loss of the non-covalently bound FAD cofactor. Three mutant Aer proteins, N34C, F66C and N85C, transmitted a constant signal-on bias. One mutation, Y111C, inverted signalling by the transducer so that positive stimuli produced negative signals and vice versa. Residues critical for signalling were mapped onto a three-dimensional model of the Aer PAS domain, and an FAD-binding site and 'active site' for signal transduction are proposed.

Amino Acid Sequence↗
PubMed1999

First policy then science: why a management unit based solely on genetic criteria cannot work.

In contrast to the goals of the symposium from which this series of papers originated, we argue that attempts to apply unambiguously defined and general management unit criteria based solely on genetic parameters can easily lead to incorrect management decisions. We maintain that conservation genetics is best served by altering the perspective of data analysis so that decision making is optimally facilitated. To do so requires accounting for policy objectives early in the design and execution of the science. This contrasts with typical hypothesis testing approaches to analysing genetic data for determining population structure, which often aspire to objectivity by considering management objectives only after the analysis is complete. The null hypothesis is generally taken as panmixia with a strong predilection towards avoiding false acceptance of the alternative hypothesis (the existence of population structure). We show by example how defining management units using genetic data and standard scientific analyses that do not consider either the specific management objectives or the anthropogenic risks facing the populations being studied can easily result in a management failure by losing local populations. We then use the same example to show how an 'applied' approach driven by specific objectives and knowledge of abundance and mortality results in appropriate analyses and better decisions. Because management objectives stem from public policy, which differs among countries and among species groups, criteria for defining management units must be specific, not general. Therefore, we conclude that the most productive way to define management units is on a case-by-case basis. We also suggest that creating analytical tools designed specifically to address decision making in a management context, rather than re-tooling academic tools designed for other purposes, will increase and improve the use of genetics in conservation.

Animals↗
PubMed1999

Loss of cytochrome c oxidase activity and acquisition of resistance to quinone analogs in a laccase-positive variant of Azospirillum lipoferum.

Laccase, a p-diphenol oxidase typical of plants and fungi, has been found recently in a proteobacterium, Azospirillum lipoferum. Laccase activity was detected in both a natural isolate and an in vitro-obtained phase variant that originated from the laccase-negative wild type. In this study, the electron transport systems of the laccase-positive variant and its parental laccase-negative forms were compared. During exponential (but not stationary) growth under fully aerobic (but not under microaerobic) conditions, the laccase-positive variant lost a respiratory branch that is terminated in a cytochrome c oxidase of the aa(3) type; this was most likely due to a defect in the biosynthesis of a heme component essential for the oxidase. The laccase-positive variant was significantly less sensitive to the inhibitory action of quinone analogs and fully resistant to inhibitors of the bc(1) complex, apparently due to the rearrangements of its respiratory system. We propose that the loss of the cytochrome c oxidase-containing branch in the variant is an adaptive strategy to the presence of intracellular oxidized quinones, the products of laccase activity.

Azospirillum↗
PubMed1999

PAS domains: internal sensors of oxygen, redox potential, and light.

PAS domains are newly recognized signaling domains that are widely distributed in proteins from members of the Archaea and Bacteria and from fungi, plants, insects, and vertebrates. They function as input modules in proteins that sense oxygen, redox potential, light, and some other stimuli. Specificity in sensing arises, in part, from different cofactors that may be associated with the PAS fold. Transduction of redox signals may be a common mechanistic theme in many different PAS domains. PAS proteins are always located intracellularly but may monitor the external as well as the internal environment. One way in which prokaryotic PAS proteins sense the environment is by detecting changes in the electron transport system. This serves as an early warning system for any reduction in cellular energy levels. Human PAS proteins include hypoxia-inducible factors and voltage-sensitive ion channels; other PAS proteins are integral components of circadian clocks. Although PAS domains were only recently identified, the signaling functions with which they are associated have long been recognized as fundamental properties of living cells.

Amino Acid Sequence↗
PubMed1999

Aerotaxis and other energy-sensing behavior in bacteria.

Energy taxis is widespread in motile bacteria and in some species is the only known behavioral response. The bacteria monitor their cellular energy levels and respond to a decrease in energy by swimming to a microenvironment that reenergizes the cells. This is in contrast to classical Escherichia coli chemotaxis in which sensing of stimuli is independent of cellular metabolism. Energy taxis encompasses aerotaxis (taxis to oxygen), phototaxis, redox taxis, taxis to alternative electron acceptors, and chemotaxis to a carbon source. All of these responses share a common signal transduction pathway. An environmental stimulus, such as oxygen concentration or light intensity, modulates the flow of reducing equivalents through the electron transport system. A transducer senses the change in electron transport, or possibly a related parameter such as proton motive force, and initiates a signal that alters the direction of swimming. The Aer and Tsr proteins in E. coli are newly recognized transducers for energy taxis. Aer is homologous to E. coli chemoreceptors but unique in having a PAS domain and a flavin-adenine dinucleotide cofactor that is postulated to interact with a component of the electron transport system. PAS domains are energy-sensing modules that are found in proteins from archaea to humans. Tsr, the serine chemoreceptor, is an independent transducer for energy taxis, but its sensory mechanism is unknown. Energy taxis has a significant ecological role in vertical stratification of microorganisms in microbial mats and water columns. It plays a central role in the behavior of magnetotactic bacteria and also appears to be important in plant-microbe interactions.

Bacterial Physiological Phenomena↗
PubMed1998

Rewiring a receptor: negative output from positive input.

A point mutation or covalent modification in bacterial chemotaxis receptors causes bacteria to be repelled by attractants, and attracted to repellents. The variety of conditions causing inverse responses suggest that the signal transduction mechanism in receptors can be readily rewired to elicit inverse responses. A model is presented in which the orientation of a critical residue with respect to an active site determines whether the receptor produces normal or inverted signals. The model is consistent with observed responses and can be generalized to include receptors in other signal transduction systems.

Bacterial Proteins↗
PubMed1998

In search of higher energy: metabolism-dependent behaviour in bacteria.

Bacteria use different strategies to navigate to niches where environmental factors are favourable for growth. Chemotaxis is a behavioural response mediated by specific receptors that sense the concentration of chemicals in the environment. Recently, a new type of sensor has been described in Escherichia coli that responds to changes in cellular energy (redox) levels. This sensor, Aer, guides the bacteria to environments that support maximal energy levels in the cells. A variety of stimuli, such as oxygen, alternative electron acceptors, light, redox carriers that interact with the electron transport system and metabolized carbon sources, effect changes in the cellular energy (redox) levels. These changes are detected by Aer and by the serine chemotaxis receptor Tsr and are transduced into signals that elicit appropriate behavioural responses. Diverse environmental signals from Aer and chemotaxis receptors converge and integrate at the level of the CheA histidine kinase. Energy sensing is widespread in bacteria, and it is now evident that a variety of signal transduction strategies are used for the metabolism-dependent behaviours. The occurrence of putative energy-sensing domains in proteins from cells ranging from Archaea to humans indicates the importance of this function for all living systems.

Bacterial Physiological Phenomena↗
PubMed1997

The Aer protein and the serine chemoreceptor Tsr independently sense intracellular energy levels and transduce oxygen, redox, and energy signals for Escherichia coli behavior.

We identified a protein, Aer, as a signal transducer that senses intracellular energy levels rather than the external environment and that transduces signals for aerotaxis (taxis to oxygen) and other energy-dependent behavioral responses in Escherichia coli. Domains in Aer are similar to the signaling domain in chemotaxis receptors and the putative oxygen-sensing domain of some transcriptional activators. A putative FAD-binding site in the N-terminal domain of Aer shares a consensus sequence with the NifL, Bat, and Wc-1 signal-transducing proteins that regulate gene expression in response to redox changes, oxygen, and blue light, respectively. A double mutant deficient in aer and tsr, which codes for the serine chemoreceptor, was negative for aerotaxis, redox taxis, and glycerol taxis, each of which requires the proton motive force and/or electron transport system for signaling. We propose that Aer and Tsr sense the proton motive force or cellular redox state and thereby integrate diverse signals that guide E. coli to environments where maximal energy is available for growth.

Amino Acid Sequence↗
PubMed1997

Magneto-aerotaxis in marine coccoid bacteria.

Magnetotactic cocci swim persistently along local magnetic field lines in a preferred direction that corresponds to downward migration along geomagnetic field lines. Recently, high cell concentrations of magnetotactic cocci have been found in the water columns of chemically stratified, marine and brackish habitats, and not always in the sediments, as would be expected for persistent, downward-migrating bacteria. Here we report that cells of a pure culture of a marine magnetotactic coccus, designated strain MC-1, formed microaerophilic bands in capillary tubes and used aerotaxis to migrate to a preferred oxygen concentration in an oxygen gradient. Cells were able to swim in either direction along the local magnetic field and used magnetotaxis in conjunction with aerotaxis, i.e., magnetically assisted aerotaxis, or magneto-aerotaxis, to more efficiently migrate to and maintain position at their preferred oxygen concentration. Cells of strain MC-1 had a novel, aerotactic sensory mechanism that appeared to function as a two-way switch, rather than the temporal sensory mechanism used by other bacteria, including Magnetospirillum megnetotacticum, in aerotaxis. The cells also exhibited a response to short-wavelength light (< or = 500 nm), which caused them to swim persistently parallel to the magnetic field during illumination.

Cell Movement↗
PubMed1997

How do bacteria avoid high oxygen concentrations?

Bacteria, such as Escherichia coli and Azospirillum brasilense, avoid microenvironments with elevated oxygen concentrations, not by sensing reactive oxygen derivatives, but by sensing a metabolic down-shift that results from elevated oxygen levels. A novel protein, Aer, and the chemotaxis serine receptor, Tsr, have recently been identified as transducers for aerotaxis which monitor internal energy levels in the bacteria.

Bacterial Physiological Phenomena↗
PubMed1997

Prediction of outcome from intensive care: a prospective cohort study comparing Acute Physiology and Chronic Health Evaluation II and III prognostic systems in a United Kingdom intensive care unit.

OBJECTIVE: To evaluate the ability of two prognostic systems to predict hospital mortality in adult intensive care patients. DESIGN: Prospective cohort study. SETTING: A mixed medical and surgical intensive care unit (ICU) in the United Kingdom. PATIENTS: A total of 1,144 patients consecutively admitted to the study. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Acute Physiology and Chronic Health Evaluation (APACHE) II and III prognostic systems were applied to assess probabilities of hospital mortality, which were compared with the actual outcome. The overall goodness-of-fit of both models was assessed. Hospital death rates were higher than those predicted by each system. Risk estimates showed a strong positive correlation between both systems (nonsurvivors r2 = 0.756, p < .0001; survivors r2 = 0.787, p < .0001). Calibration of APACHE II (chi 2 = 98.6, Lemeshow-Hosmer) was superior to that of APACHE III (chi 2 = 129.8, Lemeshow-Hosmer). The total correct classification rate of APACHE III was greater for all decision criteria applied; the best overall total correct classification rate was 80.6% for APACHE III and 77.9% for APACHE II (both for a decision criterion of 40%). The areas under the receiver operating characteristic curves were 0.806 and 0.847 for APACHE II and III, respectively, confirming the better discrimination of APACHE III. When patients were classified by diagnostic categories, risk predictions did not fit uniformly across the spectrum of disease groups. For both models, mortality ratios were highest for trauma patients and lowest for the group with respiratory disease. APACHE II predictions for patients with gastrointestinal disease were significantly better. Risk estimates for surgical admissions were superior with APACHE II (MR = 1.27) compared with APACHE III (MR = 1.56), but were similar for medical patients (1.22 vs. 1.28 for APACHE II and III, respectively). Bias induced by factors reflecting the clinical practice in an individual ICU (e.g., admission criteria, treatment before admission) may have considerable impact on risk estimates. The identification of such factors appears to be a prerequisite for the meaningful interpretation of observed and predicted death rates on the individual ICU level. CONCLUSIONS: Both predictive models demonstrated a similar degree of overall goodness-of-fit. APACHE II showed better calibration, but discrimination was better with APACHE III. Hospital mortality was higher than predicted by both models, but was underestimated to a greater degree by APACHE III. Risk estimates by both models showed considerable variation across the disease spectrum of ICU patients. Risk predictions for surgical patients and patients with gastrointestinal disease were better with APACHE II. Factors reflecting the clinical practice of an individual ICU are not accounted for by APACHE II and III. Overall, the performance of APACHE III was not superior to that of its predecessor for a cohort of United Kingdom ICU patients; for certain diagnostic categories, APACHE III performed worse than APACHE II despite an improved system of disease classification.

APACHE↗
PubMed1997

Glycerol elicits energy taxis of Escherichia coli and Salmonella typhimurium.

Escherichia coli and Salmonella typhimurium show positive chemotaxis to glycerol, a chemical previously reported to be a repellent for E. coli. The threshold of the attractant response in both species was 10(-6) M glycerol. Glycerol chemotaxis was energy dependent and coincident with an increase in membrane potential. Metabolism of glycerol was required for chemotaxis, and when lactate was present to maintain energy production in the absence of glycerol, the increases in membrane potential and chemotactic response upon addition of glycerol were abolished. Methylation of a chemotaxis receptor was not required for positive glycerol chemotaxis in E. coli or S. typhimurium but is involved in the negative chemotaxis of E. coli to high concentrations of glycerol. We propose that positive chemotaxis to glycerol in E. coli and S. typhimurium is an example of energy taxis mediated via a signal transduction pathway that responds to changes in the cellular energy level.

Bacterial Proteins↗
PubMed1997

Oxygen-dependent growth of the obligate anaerobe Desulfovibrio vulgaris Hildenborough.

Desulfovibrio vulgaris Hildenborough, a sulfate-reducing bacterium classified as an obligate anaerobe, swam to a preferred oxygen concentration of 0.02 to 0.04% (0.24 to 0.48 microM), a level which also supported growth. Oxygen concentrations of 0.08% and higher arrested growth. We propose that in zones of transition from an oxic to an anoxic environment, D. vulgaris protects anoxic microenvironments from intrusion of oxygen.

Aerobiosis↗
PubMed1996

Behavioral responses of Escherichia coli to changes in redox potential.

Escherichia coli bacteria sensed the redox state in their surroundings and they swam to a niche that had a preferred reduction potential. In a spatial redox gradient of benzoquinone/benzoquinol, E. coli cells migrated to form a sharply defined band. Bacteria swimming out of either face of the band tumbled and returned to the preferred conditions at the site of the band. This behavioral response was named redox taxis. Redox molecules, such as substituted quinones, that elicited redox taxis, interact with the bacterial electron transport system, thereby altering electron transport and the proton motive force. The magnitude of the behavioral response was dependent on the reduction potential of the chemoeffector. The Tsr, Tar, Trg, Tap, and CheR proteins, which have a role in chemotaxis, were not essential for redox taxis. A cheB mutant had inverted responses in redox taxis, as previously demonstrated in aerotaxis. A model is proposed in which a redox effector molecule perturbs the electron transport system, and an unknown sensor in the membrane detects changes in the proton motive force or the redox status of the electron transport system, and transduces this information into a signal that regulates phosphorylation of the CheA protein. A similar mechanism has been proposed for aerotaxis. Redox taxis may play an important role in the distribution of bacterial species in natural environments.

Bacterial Proteins↗