Biosynthesis of Peptide Signals in Gram-Positive Bacteria

Thoendel, Matthew; Horswill, Alexander R.

doi:10.1016/s0065-2164(10)71004-2

Cited by 84 publications

(69 citation statements)

References 72 publications

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“…Without such an approach, it is not possible to draw definitive conclusions about the nature of the native pheromone. However, the findings that the peptide identified in our study corresponded to the seven C-terminal amino acids of ComS previously shown to induce high levels of S. mutans transformation in its synthetic form (26) and that active pheromones in Gram-positive bacteria usually represent truncated C-terminal derivatives modified before import (37) indicate that XIP is an active form of the pheromone. To date, no identified systems for the processing of ComR/ ComS pheromones have been reported.…”

Section: Discussionmentioning

confidence: 47%

Extracellular Identification of a Processed Type II ComR/ComS Pheromone of Streptococcus mutans

et al. 2012

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The competence-stimulating peptide (CSP) and the sigX-inducing peptide (XIP) are known to induce Streptococcus mutans competence for genetic transformation. For both pheromones, direct identification of the native peptides has not been accomplished. The fact that extracellular XIP activity was recently observed in a chemically defined medium devoid of peptides, as mentioned in an accompanying paper (K. Desai, L. Mashburn-Warren, M. J. Federle, and D. A. Morrison, J. Bacteriol. 194:3774 -3780, 2012), provided ideal conditions for native XIP identification. To search for the XIP identity, culture supernatants were filtered to select for peptides of less than 3 kDa, followed by C 18 extraction. One peptide, not detected in the supernatant of a comS deletion mutant, was identified by tandem mass spectrometry (MS/MS) fragmentation as identical to the ComS C-terminal sequence GLDWWSL. ComS processing did not require Eep, a peptidase involved in processing or import of bacterial small hydrophobic peptides, since eep deletion had no inhibitory effect on XIP production or on synthetic XIP response. We investigated whether extracellular CSP was also produced. A reporter assay for CSP activity detection, as well as MS analysis of supernatants, revealed that CSP was not present at detectable levels. In addition, a mutant with deletion of the CSP-encoding gene comC produced endogenous XIP levels similar to those of a nondeletion mutant. The results indicate that XIP pheromone production is a natural phenomenon that may occur in the absence of natural CSP pheromone activity and that the heptapeptide GLDWWSL is an extracellular processed form of ComS, possibly the active XIP pheromone. This is the first report of direct identification of a ComR/ComS pheromone.

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Section: Discussionmentioning

confidence: 47%

Extracellular Identification of a Processed Type II ComR/ComS Pheromone of Streptococcus mutans

et al. 2012

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“…For exam-ple, several oligopeptide AIs are posttranslationally modified (14), and AI transfer through the cytoplasmic membrane can be passive (by diffusion) or active (15). Two properties relevant for ecological function have been described for most, but not all, AI systems: (i) autoregulation, i.e., AIs positively regulate their own activity via expression of their synthase, and (ii) cooperativity of the AI effect (Hill coefficient of Ͼ1), e.g., via multimerization of receptor-AI complexes.…”

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confidence: 99%

Core Principles of Bacterial Autoinducer Systems

Hense

Schuster

2015

Microbiol Mol Biol Rev

164

156

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SUMMARY Autoinduction (AI), the response to self-produced chemical signals, is widespread in the bacterial world. This process controls vastly different target functions, such as luminescence, nutrient acquisition, and biofilm formation, in different ways and integrates additional environmental and physiological cues. This diversity raises questions about unifying principles that underlie all AI systems. Here, we suggest that such core principles exist. We argue that the general purpose of AI systems is the homeostatic control of costly cooperative behaviors, including, but not limited to, secreted public goods. First, costly behaviors require preassessment of their efficiency by cheaper AI signals, which we encapsulate in a hybrid “push-pull” model. The “push” factors cell density, diffusion, and spatial clustering determine when a behavior becomes effective. The relative importance of each factor depends on each species' individual ecological context and life history. In turn, “pull” factors, often stress cues that reduce the activation threshold, determine the cellular demand for the target behavior. Second, control is homeostatic because AI systems, either themselves or through accessory mechanisms, not only initiate but also maintain the efficiency of target behaviors. Third, AI-controlled behaviors, even seemingly noncooperative ones, are generally cooperative in nature, when interpreted in the appropriate ecological context. The escape of individual cells from biofilms, for example, may be viewed as an altruistic behavior that increases the fitness of the resident population by reducing starvation stress. The framework proposed here helps appropriately categorize AI-controlled behaviors and allows for a deeper understanding of their ecological and evolutionary functions.

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“…Among the best studied signaling molecules produced by bacteria are the so-called autoinducers, either acylated homoserine lactones or peptides in Gram-negative and Gram-positive bacteria, respectively (2). In addition, specific signaling nucleotides have been discovered in all bacteria in which they have been searched (3).…”

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confidence: 99%

“…Although the autoinducers serve mainly for purposes of cell-cell communication (quorum sensing), the signaling nucleotides are used for intracellular signaling. In addition to cyclic AMP and (p)ppGpp that are involved in carbon catabolite repression and the stringent response, respectively, many bacteria also synthesize cyclic dinucleotides such as cyclic di-AMP (c-di-AMP) 2 and cyclic di-GMP (c-di-GMP). These nucleotides are often involved in the control of motility and biofilm formation i.e.…”

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confidence: 99%