Chemical strategies to unravel bacterial–eukaryotic signaling

R. Gregor , S. David and M. M. Meijler *
Department of Chemistry and National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Be'er Sheva, 84105, Israel. E-mail:

Received 16th August 2017

First published on 20th December 2017

The common language of bacteria and higher life forms is a lexicon of small molecules that the research community is only beginning to decipher. While many new signaling molecules have been discovered in recent years, the identification of their targets is mostly lagging. This review will focus on the latest chemical-probe based research aimed at understanding how bacteria interact chemically with mammals and plants. In general, chemical biology strategies remain under-utilized in this complex field of research, with a few key exceptions, and we hope that this review encourages others to implement these techniques in their research. Specifically, we highlight the chemical biology techniques used in recent studies, especially activity-based protein profiling, that have been applied to unravel the chemical mechanisms of interkingdom interactions.

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R. Gregor

Rachel Gregor received her BSc degree in Chemistry with a minor in English literature at Ben-Gurion University of the Negev, Be'er Sheva, Israel, where she is currently continuing her PhD studies in the group of Prof. Michael M. Meijler. Her research focuses on quorum sensing and its role in guiding complex interactions between microbial communities and mammalian hosts, using advanced mass spectrometry (MS) methods, such as MS/MS networking and MS imaging.

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S. David

Shimrit David received her BSc degree in Chemistry at the Department of Chemistry at Ben-Gurion University of the Negev, Be'er Sheva, Israel, and her MSc degree in the same department, under the supervision of Prof. Michael M. Meijler. She is currently pursuing her PhD studies in the same group, focusing on quorum sensing and understanding bacterial–plant interactions by applying a wide range of chemical-biology methods.

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M. M. Meijler

Prof. Michael M. Meijler was born in Amsterdam, The Netherlands, in 1970. He studied Chemistry at the University of Amsterdam, after which he obtained his PhD from the Weizmann Institute of Science in Rehovot, Israel, in 2002. After postdoctoral studies at The Scripps Research Institute in La Jolla, California, he started his Chemical Biology group at Ben-Gurion University of the Negev in Be’er Sheva, Israel, in 2006, where he was promoted to full professor in 2015. The research in his group focuses on understanding how chemical communication regulates coexistence and competition between species.


Chemical biology can be defined as the application of approaches and techniques native to chemistry in the exploration of biological questions. Such interdisciplinary work requires a diverse skill set, including organic and analytical chemistry, as well as microbiology, immunology, plant biology, and more. This approach is uniquely suited to the study of interkingdom signaling, specifically communication between bacteria and higher life forms, such as mammals and plants. Many of these interactions rely on small molecules, and while the structures of the signals are often known and our knowledge of this lexicon is increasing rapidly, their mechanism of action and the identity of their receptors is mostly unknown. Synthetic alteration of these structures opens entirely new possibilities for research based on chemical probe analogues of biological signaling molecules.

This review focuses on the latest chemical-probe-based research aimed at understanding how bacteria interact with other life forms, specifically mammals and plants. First, we introduce the main chemical biology strategies that have been used thus far in interkingdom communication research (Section 1). Then, we summarize the major studies that have been performed in this area, in both bacterial–mammalian (Section 2) and bacterial–plant (Section 3) communication. Lastly, we conclude with suggesting some additional techniques which have yet to be utilized in this field (Section 4).

1. Key techniques

An important concept in the field of chemical biology is bioorthogonal chemistry, a term coined by Bertozzi and colleagues in 2003.1 In short, reactions that take place in a biological context must be specific, efficient, and inert to the myriad chemical groups in their surroundings.2 The most popular bioorthogonal reaction is the copper-catalyzed azide–alkyne 1,3-dipolar cycloaddition (CuAAC) reaction, reported in 2002 almost simultaneously by the groups of Sharpless and Meldal (Fig. 1A).3,4 This technique is often referred to as “click” chemistry, as it links together two components quickly and specifically. Utilizing CuAAC chemistry requires introducing two reaction partners, an alkyne and an azide, on the molecules which are to be covalently linked. Both of these functional groups are rare in biological systems and relatively inert to other reactive groups, making them ideal for this application.5 Although the copper catalyst is toxic in vivo, new chelating ligands, such as tris[(1-benzyl-1H-1,2,3-triazol-4-yl)methyl] amine (TBTA, Fig. 1A) and related compounds, have improved the rate of reaction as well as reduced toxicity.6,7 Another solution is the use of strain-promoted azide–alkyne cycloaddition, which eliminates the need for the copper catalyst and has been successfully utilized in vivo in cell culture and whole animals by the Bertozzi group and by others.8–10 In addition to the azide–alkyne cycloaddition, a wide variety of similar reactions exist, each with unique advantages and limitations.11–13
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Fig. 1 (A) The copper-catalyzed azide–alkyne 1,3-dipolar cycloaddition (CuAAC) reaction. (B) The two elements of chemical probe design. Left, a reactive group. Examples include the electrophilic groups, which can react with a nucleophile within the target (from top: α,β-unsaturated amide, isothiocyanate, epoxy). Alternately, the photoreactive groups are more general and bind indiscriminately upon UV irradiation (from top: aryl azide, diazirine, benzophenone). Right, the reporter tag. Useful reporters include fluorophores (e.g. fluorescein) or affinity tags (e.g. biotin). (C) Outline of the ABPP-CuAAC approach. First, the model organism or system is incubated with the clickable chemical probe, which has been modified to include two elements: a reactive group (oval) and an alkyne moiety. The probe undergoes interactions with the proteome, covalently labeling protein interacting partners via the reactive group. Then, a reporter tag (star) is introduced using CuAAC chemistry. Lastly, interacting proteins are characterized, often via in-gel fluorescence (top), or by enrichment of labeled proteins and subsequent identification by mass spectrometry (bottom).

An important application of CuAAC chemistry has been in activity-based protein profiling (ABPP), a field pioneered by the groups of Cravatt and Bogyo.14,15 This chemical proteomics strategy is used for the study of interactions between small molecules and proteins. A small molecule of interest must contain two components: a reactive group and a reporter tag (Fig. 1B). The reactive group enables the probe to bind covalently to its protein target, irreversibly linking the two together for further analysis. Seminal studies in the field of ABPP have characterized entire enzyme classes by designing chemical probes based on inherent qualities of the active site. For example, early ABPP studies on cysteine proteases incorporated these enzymes’ natural target motif in the probe design.14,15 Upon cleavage of this target motif, the probe covalently binds to the protease. An added advantage is that in this case, the probe will only detect catalytically-active species of the protein, therefore enabling the quantification and analysis of the total catalytic activity of a living system, a strategy sometimes termed “catalomics.”16 (For a similar probe design in the field of interkingdom signaling, see Section 3.1.)

Alternately, if no covalent reaction is inherent to the interaction of interest, a reactive group can be introduced onto the backbone of the small molecule. Such probes are sometimes termed affinity-based probes, as the interaction relies on the affinity of the small molecule to its target, and an additional step is needed to permanently link the two. Photoreactive groups, for example diazirine, benzophenone and aryl azide, are popular for this purpose, because they can be activated selectively (Fig. 1B). In such a workflow, the small molecule is first introduced to the biological system and incubated for a set time, to allow the probe to find its target/s. Then, the mixture is irradiated to induce covalent binding. This process can take place either in vivo in live cells or tissue, or in vitro in lysate. This strategy requires extensive optimization of the irradiation step in order to reduce background noise from unspecific binding of excess probe to non-target proteins upon irradiation. Additionally, the introduction of a photoreactive group may be challenging synthetically, as well as require careful probe design in order not to interfere with the probe's affinity to its target. However, this technique enables researchers to study a far wider range of non-covalent small molecule–protein interactions, such as many of those involved in interkingdom signaling.

Once the probe and target are covalently bound, the second component, the reporter tag, is utilized to further characterize the interaction (Fig. 1B). Some useful tags include fluorescent molecules such as fluorescein or rhodamine. These tags enable the visualization of the labeled proteome using in-gel fluorescence, often a useful first step in order to check the specificity and scope of the labeling, and further optimize the labeling procedure if needed. Additionally, fluorophores allow for the imaging of the probe–target complex within the cells or tissue using fluorescence microscopy, which can provide additional information about the biological mechanism of action.

However, for novel interactions in which the targets are unknown, it is essential to perform mass spectrometry (MS) in order to identify the proteins linked to the probe. To this end, biotin is often used as a reporter tag, as it allows for subsequent streptavidin-based affinity purification of labeled proteins. Once the sample has been enriched for the probe–protein complex, the proteins are digested using trypsin and the resulting peptides characterized by liquid chromatography tandem MS (LC-MS/MS). Peptide sequences can then be searched against a protein database for the organism of interest, and thus novel targets identified. Alternately, in-gel digestion can be used in a similar workflow, in which peptides are commonly analyzed by matrix-assisted laser desorption/ionization MS (MALDI-MS). Regardless, any protein target of interest should then undergo further biological validation, for example by western blotting, knockdown assays, or overexpression in vitro.

Initially, one of the limitations of ABPP was that the reporter tags were relatively bulky in comparison to the size of the small molecule, thus potentially interfering with binding affinity and specificity. The application of CuAAC chemistry has enabled the introduction of a small alkyne or azide handle on the molecule of interest, instead of a larger reporter tag (Fig. 1C). The interaction between the probe and its targets takes place with only this small handle present, and the covalent bond is formed. Then, the probe–protein complex can be linked to a reporter tag of choice, using CuAAC chemistry. This method has been used to find the protein targets of natural products, for example, among other applications.17

Of course, the introduction of any modifications whatsoever to a small molecule may interfere with its biological activity. Therefore, before designing a chemical probe, ideally some structure–activity relationship (SAR) studies should be performed. In fishing for unknown proteins, it is not possible to rely on crystal structures or any prior information in designing effective probes. Therefore, iterative changes can be implemented on the parent molecule to systematically evaluate the effects of various chemical features on the biological activity of the molecule. Regardless, the activity of the final ABPP probes must be tested as well, and it is often helpful to prepare several different analogues to find the most specific and active probe, as will be shown in the works highlighted here.

2. Bacterial–mammalian interactions

2.1 Pseudomonas aeruginosa, AHLs, and the immune system

Much work in this area has focused on Pseudomonas aeruginosa, an opportunistic human pathogen that is the cause of a significant proportion of nosocomial infections, often by antibiotic-resistant strains. This bacterium has a sophisticated cell–cell communication – or quorum sensing (QS) – system that it uses to assess its population density and regulate virulence and defense mechanisms, and respond to changes in its environment. This system is well-characterized and includes several small molecule signals, including N-3-oxo-dodecanoyl-L-homoserine-lactone (C12; 1, Fig. 2), a member of the N-acyl-homoserine lactone (AHL) class of QS-signals. In addition to its role as a central QS signal, C12 has been shown to directly affect mammalian cellular immune responses18,19via a TLR4-independent mechanism.20 We have previously reported that this effect occurs via modulation of the transcriptional activity of the NF-κB cascade in different types of immune-related cells.21 Other studies have shown the effect of C12 on calcium signaling22–24 and TRAIL-induced apoptosis.25
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Fig. 2 Different approaches to prepare affinity probes based on the bacterial signalling molecule C12 (1). 2 and 3 utilized a piperazine linker to attach the molecules to an affinity matrix. 4 and 5 introduced reporter tags (star): fluorescein (left) and biotin (right). 6 shows the incorporation of diazirine and alkyne moieties.

Chemical biology strategies have been applied by our group and others to unravel the molecular mechanisms of action of C12 and discover a specific mammalian receptor for this molecule. First, synthetic analogues of C12 with systematic modifications to the backbone prepared by Pritchard, Bycroft and co-workers led to a better understanding of the SAR between C12 and its unknown receptor.26 The molecule was divided into three functional components: the hydrophobic side-chain, the 3-oxo-acyl group, and the lactone ring, and each element modified for a total of 24 different analogues. Based on this work, it was concluded that the L-configuration at the chiral center, the non-polar nature of the side-chain, and the lactone ring were all critical for immune-suppression activity, strengthening the conclusion that there is a specific mammalian receptor protein for C12.

Following this study, the Pritchard group used an affinity matrix approach in order to search for such proteins (2 and 3, Fig. 2).27 C12 analogues were attached to an affinity matrix gel using a piperazine linker via the center (2) or end (3) of the side-chain, which was determined to be the optimal site for immobilization based on the SAR data. Lymphocyte cell lysates were then incubated with the matrix to bind proteins that interact with C12, and those proteins were subsequently enriched and identified using MS, western blot, and binding experiments using radiolabeled [3H]-C12. The heterodimer calprotectin was isolated using this method; however, a knockdown cell line of one of its protein components showed no change in the immune response to C12, suggesting that the binding is not necessarily biologically relevant in this context. Although this C12 affinity matrix approach has not been explored further in other interkingdom communication studies, it has since been successfully used in a proof-of-concept study to isolate native C12-binding proteins within P. aeruginosa lysates.28

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Fig. 3 Chemical probes based on P. aeruginosa QS signals PQS (7) and HHQ (8). An affinity matrix approach was used in which a linker was attached via the 5-position of the quinolone ring (arrow), and subsequently attached to the matrix via the amine (9 and 10).

Other ABPP probes based on C12 have been developed in order to identify mammalian receptors. Vikström and co-workers prepared analogues in which the C12 analogue was modified via the side chain (4, Fig. 2) and lactone ring (5, Fig. 2) with biotin or fluorescein, for use in ABPP and confocal microscopy, respectively.29 Using this methodology, they proposed an interaction between C12 and the IQ-motif-containing GTPase-activating protein, IQGAP1. However, the protein discovered has been implicated in epithelial cell migration, but is not directly involved in the immune response. Subsequently, our group developed an additional ABPP strategy, in which two of the smallest possible modifications are introduced into the C12 side-chain: a diazirine group and an alkyne group (6, Fig. 2).30,31 Upon UV irradiation, a covalent bond between the probe and neighboring residues in any tight-binding protein is formed. Then, under CuAAC conditions a biotin moiety or fluorescent tag is introduced to identify the C12 receptor. Similar strategies have been employed successfully by the groups of Cravatt and Sieber, among others, in the characterization of several classes of enzymes (see Sections 2.3 and 2.4).32,33 In initial studies, the modified probes retained their immune-modulatory activity, and current research focuses on the validation of a novel mammalian C12 receptor.30,31

2.2 Other bacterial signaling molecules

Some work has also been done on other bacterial signaling molecules, including the quinolone-based signals such as the Pseudomonas quinolone signal (PQS; 7, Fig. 3) and its precursor 2-heptyl-4(1H)-quinolone (HHQ; 8, Fig. 3). These signals have also been shown to have immune-modulatory effects in mammals.34,35 In recent studies by Welch and co-workers, PQS and HHQ affinity resins (9 and 10, Fig. 3) were prepared in order to isolate novel receptors, in a similar strategy to the affinity-matrix work on C12 mentioned above.36 The proteins were then eluted from the matrix and resolved by gel electrophoresis, and the resulting bands excised and identified using MALDI-MS. The quinolones were attached to the matrix via the 5-position of the quinolone ring, chosen based on a previous SAR study by the same group.37 The PQS affinity resin was shown to bind the cognate receptor PqsR and iron(III) in vitro, indicating that the immobilized PQS retained its biological activity.

The authors applied their system in order to search for binding partners of PQS within P. aeruginosa, and found two unreported proteins. The first, MgtA, is a P-type ATPase involved in magnesium(II) transport, a process previously linked to quinolone signaling in P. aeruginosa.38 The second is MexG, part of a resistance-nodulation-cell division (RND) efflux pump, which crosses the inner and outer cell membranes and allows for active transport of substrates. MexG is usually not present in such complexes, and its role remains unclear, although one previous study did find that transcription of this protein was severely downregulated in a PqsR mutant.39 In order to verify this result, MexG was purified and shown to bind PQS in vitro using fluorescence spectroscopy, exhibiting biphasic tight (Kd = 1 μM) and weaker (Kd = 5 μM) binding behavior. It was also found that the deletion of a conserved domain in this protein, DoxX, abolished this interaction altogether. The authors state that they intend in the future to use these PQS and HHQ affinity resins to tackle other biological questions, including the immunomodulatory interkingdom effects of these molecules. Additionally, some related work on a different interkingdom interaction was performed by O’Gara and co-workers, who tested a suite of 15 HHQ/PQS synthetic analogues on the fungal pathogen Candida albicans.40

2.3 Microbiome–host crosstalk via bile acids

Bile acids (BAs) are a class of cholesterol-based metabolites that play a critical role in diverse processes in the human body, including intestinal absorption of nutrients as well as signaling and inflammation.41 Primary BAs are synthesized in the liver and undergo chemical modifications by gut bacteria, including isomerization, deconjugation, and dehydroxylation, forming what are referred to as secondary BAs. BA levels are tightly regulated, and disruptions of this delicate balance have been correlated to microbial dysbiosis and host metabolic disorders.42 However, despite the wide range of activity of these molecules, most mechanistic studies have focused on only two known host receptors for these molecules, FXR and TGR5.43,44

Recently, Lei and co-workers presented an untargeted ABPP approach in order to profile additional mammalian receptors for BAs, specifically the primary BA cholic acid (11, Fig. 4).45 Three probes were prepared based on the cholic acid structure, each incorporating an alkyne and a diazirine moiety via an amide linkage (12–14, Fig. 4; additional probes using an ester linkage were found to be unstable). The probes were incubated in vivo with HeLa cells and analyzed in a standard ABPP workflow, with the addition of a quantitative proteomics technique termed stable isotope-labeled amino acids in cell culture (SILAC; Fig. 4).46,47 SILAC enables the simultaneous MS analysis of two samples, for example a treated sample and a control, by growing one in media containing isotopically-heavy amino acids, and the other in standard media. This allows for a direct, quantitative comparison between the samples, and can be used in ABPP experiments to distinguish between specific targets and background noise. In this case, the authors utilized SILAC in order to quantitatively compare the binding of their probes with and without the presence of the natural molecule, cholic acid, in a competition experiment, in order to ensure that their probes compete for the same target. Out of the three probes, 13 led to the highest number of specific interactions and was the only one to bind the known receptor FXR. The authors propose that the position of the diazirine on the BA backbone allows the probe to capture interactions close to binding pockets of interaction partners, without any bulky linker to interfere.

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Fig. 4 Left, cholic acid (11) and three affinity probe analogues incorporating diazirine and alkyne groups at different positions (12–14). Right, SILAC workflow. (I) Regular (light) and isotopically-labeled (heavy) HeLa cells are treated with two conditions: the ABPP probe alone, and a competition experiment with ABPP probe and native bile acid. The cells are then treated with UV light to induce binding of the photoreactive diazirine group (purple) to the target protein(s). (II) The cells undergo lysis and are mixed in a 1[thin space (1/6-em)]:[thin space (1/6-em)]1 ratio, to allow for simultaneous processing and analysis. (III) The labeled proteins are linked to biotin via a CuAAC reaction, and then (IV) the sample is enriched for labeled proteins using streptavidin affinity purification. (V) Lastly, the samples are trypsin-digested and analyzed by MS, allowing for identification of labeled proteins. The ratio between the heavy and light peptides is determined, allowing for a quantitative comparison between the two experimental conditions.

Out of the hundreds of proteins identified in this pull-down assay, the authors chose six to validate: three known BA receptors and three novel proteins which may have roles in disease. The proteins were overexpressed with a histidine-tag for western blot identification and treated with probe alone, or a mixture of probe and excess cholic acid in a competition experiment. All six were conclusively captured by the probe in a UV-dependent manner, and inclusion of excess cholic acid abolished the interaction, indicating that the probe competes for the same binding pocket as the native molecule. This study provides a wealth of new targets to better understand the ways in which BAs function in the body, and the methodology could be easily extended to secondary BAs and bacterial receptors to get a fuller picture of this complex regulatory system.

2.4 Mammalian hormones in interkingdom communication

Twenty-five years have passed since the pioneering work of Lyte and co-workers on the sensing of the mammalian stress hormone noradrenaline by E. coli, which was initially met with skepticism and resistance from the scientific community.48,49 Now, numerous studies exist in the field of microbial endocrinology, the study of bacterial reactions to mammalian hormones as indicators of host stress and potential cues to activate pathogenicity.50,51 Chemical biology techniques remain under-utilized in this field, with the exception of an ABPP study published this year by the group of Sieber on dynorphin, a human opioid peptide composed of 13 amino acids.33 Dynorphin has been previously shown to affect P. aeruginosa by inducing the production of the bacterial virulence factor pyocyanin as well as mild toxicity.52,53 Sieber and co-workers synthesized five unnatural amino acids: propargyl-glycine, diazirine-bearing proline and lysine, and two additional analogues containing benzophenone and aryl azide (Fig. 5). Then, six analogues of dynorphin were prepared, each containing propargyl-glycine for the attachment of the reporter tag, and one of the other four amino acids as a photoaffinity group (15, Fig. 5). All probes were tested, and the analogue containing diazirine-bearing proline showed the most specific binding. Using this probe and the ABPP workflow, a bacterial sensor kinase, ParS, was identified as a potential target. This hit was validated using transposon-mutants of parS and its regulator parR, which both showed increased sensitivity to dynorphin-induced toxicity and no pyocyanin response.
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Fig. 5 Scheme of analogues of the peptide dynorphin, each containing propargyl-glycine and a photo-affinity group (15). Four synthetic amino acids containing photo-affinity groups were utilized (from top left, clockwise): aryl azide, benzophenone, diazirine-bearing proline, and diazirine-bearing lysine.

3. Bacterial–plant interactions

3.1 Pseudomonas syringae targets host signaling pathways

Pseudomonas syringae pv. syringae (Psy) is a globally-widespread plant pathogen responsible for numerous diseases in crop plants, including brown spots on beans, citrus blast, and blossom blight in pear plants, among others.54Psy enters the plant via wounds, and causes extensive damage to plant tissue by producing ice-nucleation active proteins, leaving the plants vulnerable to frost damage. The group of van der Hoorn has developed to date 40 probes spanning 14 chemotypes that target a vast variety of plant proteins.55 A number of studies in recent years have focused on the role of the small, nonribosomal cyclic peptide syringolin A (SylA; 16, Fig. 6A) produced by Psy, known to inhibit the eukaryotic proteasome and recently linked by these authors to plant signaling pathways.56,57 SylA inhibits the eukaryotic proteasome via a Michael-type addition between the α,β-unsaturated amide in the compound and a threonine residue in the active site of the protein, leading to the formation of a covalent ether bond and therefore inhibition (Fig. 6B).58
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Fig. 6 (A) SylA (16) and a rhodamine-tagged analogue, RhSylA (17). The α,β-unsaturated amide is shown in red. (B) Mechanism of reaction between the α,β-unsaturated amide of SylA and the threonine residue, Thr1, in the active site of the eukaryotic proteasome. (C) RhSylA was used in a wound inoculation model in which it was placed directly into a cut in a leaf. The probe was incubated for two hours and the leaf removed for imaging with fluorescence microscopy (left), and it was found that RhSylA migrated throughout the vasculature of the leaf. Additionally, leaf tissue was extracted and the proteins analyzed by gel (right), showing that RhSylA covalently labeled the B1/2/5 subunits of the plant proteasome.

Van der Hoorn collaborated with the groups of Overkleeft and Kaiser to utilize a rhodamine-tagged SylA derivative (17, Fig. 6A) in order to study the mechanism of virulence of SylA in its plant host in vivo, using ABPP and imaging.56 This probe, designed by Overkleeft and Kaiser in a previous study, relies on the compound's native mechanism of action in order to form a covalent linkage for the purpose of ABPP, with the addition of a rhodamine tag for imaging.59 This work also included a SAR study based on a number of other SylA analogues, in which each of the two double bonds, including that of the α,β-unsaturated amide, were saturated, and the stereochemistry of the chiral center reversed. The authors utilized this system in a later study that linked SylA to the process of colonization of its plant host, by not only suppressing local immune responses, but also allowing the bacteria to spread by interfering with salicylic acid signalling.57 Salicylic acid has been recognized for hundreds of years as a natural medicine in humans, but in its natural role in the plant it functions as a stress hormone and is essential to the plant's response to pathogen invasion.60 In this study, van der Hoorn and co-workers showed that SylA diffuses from the site of initial infection to healthy areas and blocks salicylic acid signaling via proteasome inhibition, leaving surrounding tissue vulnerable to colonization by Psy.57 The authors used the rhodamine-tagged SylA probe both to directly image the spread of this molecule in a plant leaf, as well as to validate its target, the proteasome (Fig. 6C).

In another study, van der Hoorn and colleagues focused on the AvrPphB effector, a protease injected by Psy into plant cells which interferes with host immune signaling.61 A wide variety of similar bacterial proteases exist, but studying their active forms has proven difficult, as these proteins undergo folding, eukaryotic post-translational modifications, and prodomain removal in the host cell. For example, it has been shown that AvrPphB autocatalytically cleaves a prodomain in order to form the mature isoform, although it is unknown if this happens in the bacterium or host and what role the prodomain has in folding.62 The protease subsequently undergoes host fatty acid acylation in order to take advantage of a native pathway to target proteins to the host membrane.63,64 There, the protease cleaves various host kinases and thereby suppresses immune signaling and induces localized plant cell death via the hypersensitive response (HR). In order to elucidate the details of this process, the authors prepared a specific activity-based probe for AvrPphB, essentially a small, artificial substrate for this protease. The substrate was comprised of a tripeptide motif which the protease cleaves, a reactive acyloxymethylketone (AOMK) group, and a rhodamine reporter tag. Upon attack by the protease, the probe covalently binds due to the AOMK group, and is thus labeled and can be detected by fluorescence scanning. Using this strategy, the regulation of protease activity of different isoforms of the protein in different cellular locations was characterized. The authors concluded that the protease is active before cleavage of the prodomain, at least for this relatively small substrate, and that while the prodomain is essential for secretion of the protease, it is not necessary for folding or stabilization. Additionally, the prodomain must be removed in order to induce HR. These studies showcase the power of ABPP approaches in answering fundamental questions regarding plant–microbe interactions.

3.2 Bacterial AHLs in plants

Various plant species have been shown to sense and react to AHL signals of varying chain lengths, secreted by both beneficial and pathogenic bacteria.65–67 A recent study by Pomini and co-workers isolated microbial AHLs from Saccharum officinarum (sugarcane) extract, and detected the 8-carbon AHL (18, Fig. 7).68 Both enantiomers were synthesized and their effects on sugarcane culm growth were examined. While both were active in inducing root sprouting, the S-enantiomer was significantly more effective. Surprisingly, while the S-enantiomer stimulated growth of buds, the R-enantiomer caused the opposite effect. These findings strengthen the hypothesis that plant responses to these compounds are mediated by specific receptors or enzymes, and further studies are needed in order to characterize them.

Blackwell and co-workers have developed an extensive library of natural and synthetic AHLs, including some potent QS inhibitors,69,70 and used them to study QS in bacteria as well as in interkingdom studies on plant hosts. One such study investigated the effects of AHL degradation products on seedling growth of A. thaliania and M. truncatula, in light of well-characterized mechanisms of hydrolysis and enzymatic degradation of AHLs in the rhizosphere.71 The authors screened a focused library of 17 AHLs and degradation byproducts, with structural variations including chain length, absence of the 3-oxo group, and the stereochemistry of the chiral center. Surprisingly, most of the growth effects observed were attributed to the AHL amidolysis product, L-homoserine (19, Fig. 7). The analogues indeed showed varying activity, which the authors propose is due to varying affinities of these molecules to the putative degradation enzyme, a fatty acid amide hydrolases, which then releases the active L-homoserine. In a later study, the Blackwell lab examined the effect of AHLs on nodulation in the rhizobial bacterium Sinorhizobium meliloti and a model legume host, Medicago truncatula.72 An extensive library of 118 natural and synthetic AHLs, including aryl derivatives, was screened on a QS-reporter of S. meliloti, and then 12 lead compounds were tested for their effect on nodulation in the plant model. The authors found that some compounds generated distinct effects on the host and on the bacterium. Host detection of AHLs with chains of >12 carbons (20, Fig. 7) led to an increased number of nodules, and this effect may be due to a similar amidolysis mechanism as was described in the previous study. The most active bacterial agonists were the halogenated phenoxylacetyl homoserine lactones (21, Fig. 7), which affected the rate of nodule formation.

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Fig. 7 Molecules involved in plant–bacteria interactions. Studies on AHLs focused on the 8-carbon AHL (18); L-homoserine, an amidolysis product (19); longer-chain AHLs (20); and halogenated phenoxylacetyl homoserine lactones such as the brominated analogue shown here (21). Lastly, the natural product coronatine (22) is composed of two elements linked by an amide bond: (+)-coronafacic acid (bottom) and (+)-coronamic acid (top). An affinity probe based on its structure incorporates a diyne in place of the cyclopropane moiety (23).

3.3 Coronatine and plant immune signaling

The plant hormone 7-iso-jasmonoyl-L-isoleucine activates immunity against herbivores and tissue injury, through the COI1-JAZ signaling pathway.73 Coronatine (22, Fig. 7), a small phytotoxin produced by P. syringae, is generally considered an effective mimic of this hormone, and is a strong agonist of the COI1-JAZ co-receptor.73,74 However, another role for this small molecule has also been reported. Following bacterial infection, plant stomata generally close in order to prevent the invasion from spreading to the plant apoplast, in a defense mechanism regulated by another signaling cascade involving abscisic acid. Coronatine has been shown to reverse stomatal closure, and while there is some indication that this process is also regulated by the COI1-JAZ signaling pathway, the mechanism remained mostly unclear.75

A recent paper published by Ueda and colleagues combines SAR studies with an elegant alkyne tag in vivo RAMAN imaging (ATRI) approach in order to shed light on this phenomenon.76 Previously, these authors published the total synthesis of coronatine via condensation of its two components, (+)-coronafacic acid and (+)-coronamic acid via the amide bond, as well as the three unnatural stereoisomers.77 Here, these compounds were tested both for their ability to reverse stomatal closure in Arabidopsis thaliana and their activity as agonists of COI1-JAZ signaling. The coronatine analogue composed of naturally-occurring (+)-coronafacic acid and the enantiomeric (−)-coronamic acid could effectively reverse stomatal closure, yet was not an agonist of COI1-JAZ, indicating that an additional mechanism may be involved. The authors then prepared an analogue of this molecule to probe the stomatal re-opening process using ATRI. A previous attempt by these authors to image this molecule using fluorescence imaging by attaching a fluorescein tag to coronatine had failed, because the bulky probe was no longer biologically active.78

In the current study, a new probe was prepared in which the cyclopropane is replaced with a diyne moiety (23, Fig. 7). The diyne produces a distinct signature in RAMAN in an area which is clean of signals from other biomolecules. This enables the tracking of the diyne-containing probe in living plant cells and the determination of its sub-cellular localization using ATRI. The authors found that the diyne probe colocalized with the endoplasmic reticulum of plant cells, distinct from the nuclear COI1-JAZ receptor. This result strongly supports the existence of an additional, unknown receptor for coronatine, although more research is needed in order to fully characterize this mechanism.

While the number of studies that utilize chemical probes to study plant–bacterial interactions is still limited, the examples described here show their power and significant progress in their use, and recent advances in MS and chemical proteomics should provide a rich stage for future discoveries in this area.

4. Future directions and conclusions

In this review, we have described the use of ABPP, bioorthogonal chemistry, and SAR studies in the study of interkingdom signaling between bacteria and plants or mammals. The combination of photochemistry and click-chemistry methods have been especially useful in the challenging identification of proteins that bind signaling molecules without electrophilic moieties. While the described techniques have proven to be highly valuable in the mechanistic unravelling of interspecies communication, there are additional techniques being applied in the field of chemical biology that we predict can be successfully applied to such questions.

For example, the incorporation of unnatural amino acids via genetic code expansion, pioneered by the groups of Schultz and Tirrell, among others, have provided additional powerful tools to the discipline.79 Amino acids with handles appropriate for various bioorthogonal reactions, such as azides and alkynes, have already been incorporated into bacterial proteins by hijacking a native stop codon for the loading of the unnatural amino acid. This strategy has been implemented in mammalian cells as well.80,81 As this technique becomes more accessible, it will be possible to target the protein partner of interactions, rather than the small molecule.

Additionally, a recent, exciting paper by Bode and colleagues showed that different bacterial species can incorporate externally-provided azide-labeled fatty acids and amines into their primary and secondary metabolism, thus resulting in labeled complex metabolites.82 This type of in vivo labeling of small molecules was utilized by the authors for the enrichment of natural products, but could also potentially enable tracking and detection of signals in interkingdom interactions.

Another useful methodology is chemical genetics, in which small molecules are used to genetically manipulate an organism of interest in a specific and reversible manner.83 This has not been utilized to study interkingdom interactions per se, although one recent study by Blackwell and co-workers utilized AHL-based inhibitors to inhibit gene expression of QS-related virulence factors in wild-type bacteria in vivo in infection models of plant hosts.84 Additionally, the van der Hoorn group has implemented this technique extensively in the study of plants, but not yet in the context of plant–microbe communication.85

Lastly, diversity-oriented synthesis has become an increasingly powerful tool in recent years.86,87 While it is relatively common to create targeted libraries of molecules based on a similar scaffold, as has been described in the examples given in this review, diversity-oriented synthesis aims to reverse this paradigm. This technique is based on the design of high-throughput synthetic routes in order to generate libraries consisting of as wide a range of chemical structures as possible. This enables the discovery of entirely new targets and molecules for further investigation; however, the main challenge in this field remains the development of clean and efficient synthetic strategies.

There remains much room for a wider application of chemical biology techniques to the study of interkingdom communication, and for the development of new tools to answer specific open questions in the field. In addition to bacterial–mammalian and bacterial–plant communication, other interkingdom interactions have yet to be investigated at all using these tools, including the developing field of bacterial–algal communication.88 However, such initiatives will require high-risk, interdisciplinary collaborations, which must be fostered and encouraged by funding organizations and research institutions.89 We surmise that the field is at the cusp of many more breakthrough discoveries in the coming years, and it is likely that this review merely highlights the pioneering discoveries and techniques.

Conflicts of interest

There are no conflicts to declare.


R. G. is grateful to the Azrieli Foundation for the award of an Azrieli Fellowship. M. M. M. acknowledges support from the Israel Science Foundation (Personal Grant 1667/15).

Notes and references

  1. E. M. Sletten and C. R. Bertozzi, Acc. Chem. Res., 2011, 44, 666–676 CrossRef CAS PubMed.
  2. E. M. Sletten and C. R. Bertozzi, Angew. Chem., Int. Ed., 2009, 48, 6974–6998 CrossRef CAS PubMed.
  3. V. V. Rostovtsev, L. G. Green, V. V. Fokin and K. Barry Sharpless, Angew. Chem., Int. Ed., 2002, 41, 2596–2599 CrossRef CAS PubMed.
  4. C. W. Tornøe, C. Christensen and M. Meldal, J. Org. Chem., 2002, 67, 3057–3064 CrossRef.
  5. C. S. McKay and M. G. Finn, Chem. Biol., 2014, 21, 1075–1101 CrossRef CAS PubMed.
  6. C. Besanceney-Webler, H. Jiang, T. Zheng, L. Feng, D. Soriano del Amo, W. Wang, L. M. Klivansky, F. L. Marlow, Y. Liu and P. Wu, Angew. Chem., Int. Ed., 2011, 50, 8051–8056 CrossRef CAS PubMed.
  7. L. Li and Z. Zhang, Molecules, 2016, 21, 1393 CrossRef PubMed.
  8. N. J. Agard, J. A. Prescher and C. R. Bertozzi, J. Am. Chem. Soc., 2004, 126, 15046–15047 CrossRef CAS PubMed.
  9. J. M. Baskin, J. A. Prescher, S. T. Laughlin, N. J. Agard, P. V. Chang, I. A. Miller, A. Lo, J. A. Codelli and C. R. Bertozzi, Proc. Natl. Acad. Sci. U. S. A., 2007, 104, 16793–16797 CrossRef CAS PubMed.
  10. S. T. Laughlin, J. M. Baskin, S. L. Amacher and C. R. Bertozzi, Science, 2008, 320, 664–667 CrossRef CAS PubMed.
  11. D. M. Patterson, L. A. Nazarova and J. A. Prescher, ACS Chem. Biol., 2014, 9, 592–605 CrossRef CAS PubMed.
  12. H.-W. Shih, D. N. Kamber and J. A. Prescher, Curr. Opin. Chem. Biol., 2014, 21, 103–111 CrossRef CAS PubMed.
  13. J. C. Jewett and C. R. Bertozzi, Chem. Soc. Rev., 2010, 39, 1272–1279 RSC.
  14. A. E. Speers and B. F. Cravatt, Curr. Protoc. Chem. Biol., 2009, 1, 29–41 Search PubMed.
  15. D. Greenbaum, K. F. Medzihradszky, A. Burlingame and M. Bogyo, Chem. Biol., 2000, 7, 569–581 CrossRef CAS PubMed.
  16. W. P. Heal, T. H. T. Dang and E. W. Tate, Chem. Soc. Rev., 2011, 40, 246–257 RSC.
  17. M. H. Wright and S. A. Sieber, Nat. Prod. Rep., 2016, 33, 681–708 RSC.
  18. M. Teplitski, U. Mathesius and K. P. Rumbaugh, Chem. Rev., 2011, 111, 100–116 CrossRef CAS PubMed.
  19. D. I. Pritchard, Int. J. Med. Microbiol., 2006, 296, 111–116 CrossRef CAS PubMed.
  20. V. V. Kravchenko, G. F. Kaufmann, J. C. Mathison, D. A. Scott, A. Z. Katz, M. R. Wood, A. P. Brogan, M. Lehmann, J. M. Mee, K. Iwata, Q. Pan, C. Fearns, U. G. Knaus, M. M. Meijler, K. D. Janda and R. J. Ulevitch, J. Biol. Chem., 2006, 281, 28822–28830 CrossRef CAS PubMed.
  21. V. V. Kravchenko, G. F. Kaufmann, J. C. Mathison, D. A. Scott, A. Z. Katz, D. C. Grauer, M. Lehmann, M. M. Meijler, K. D. Janda and R. J. Ulevitch, Science, 2008, 321, 259–263 CrossRef CAS PubMed.
  22. M. L. Mayer, J. A. Sheridan, C. J. Blohmke, S. E. Turvey and R. E. W. Hancock, PLoS One, 2011, 6, e16246 CAS.
  23. E. K. Shiner, D. Terentyev, A. Bryan, S. Sennoune, R. Martinez-Zaguilan, G. Li, S. Gyorke, S. C. Williams and K. P. Rumbaugh, Cell. Microbiol., 2006, 8, 1601–1610 CrossRef CAS PubMed.
  24. C. Schwarzer, S. Wong, J. Shi, E. Matthes, B. Illek, J. P. Ianowski, R. J. Arant, E. Isacoff, H. Vais, J. K. Foskett, I. Maiellaro, A. M. Hofer and T. E. Machen, J. Biol. Chem., 2010, 285, 34850–34863 CrossRef CAS PubMed.
  25. V. Kravchenko, A. L. Garner, J. Mathison, A. Seit-Nebi, J. Yu, I. P. Gileva, R. Ulevitch and K. D. Janda, ACS Chem. Biol., 2013, 8, 1117–1120 CrossRef CAS PubMed.
  26. S. R. Chhabra, C. Harty, D. S. W. Hooi, M. Daykin, P. Williams, G. Telford, D. I. Pritchard and B. W. Bycroft, J. Med. Chem., 2003, 46, 97–104 CrossRef CAS PubMed.
  27. R. Seabra, A. Brown, D. S. W. Hooi, C. Kerkhoff, S. R. Chhabra, C. Harty, P. Williams and D. I. Pritchard, Calcium Bind. Proteins, 2008, 3, 31–37 Search PubMed.
  28. T. Praneenararat, T. M. J. Beary, A. S. Breitbach and H. E. Blackwell, Bioorg. Med. Chem. Lett., 2011, 21, 5054 CrossRef CAS PubMed.
  29. T. Karlsson, M. V. Turkina, O. Yakymenko, K.-E. Magnusson and E. Vikström, PLoS Pathog., 2012, 8, e1002953 Search PubMed.
  30. L. Dubinsky, L. M. Jarosz, N. Amara, P. Krief, V. V. Kravchenko, B. P. Krom and M. M. Meijler, Chem. Commun., 2009, 7378–7380 RSC.
  31. L. Dubinsky, A. Delago, N. Amara, P. Krief, J. Rayo, T. Zor, V. V. Kravchenko and M. M. Meijler, Chem. Commun., 2013, 49, 5826–5828 RSC.
  32. A. E. Speers, G. C. Adam and B. F. Cravatt, J. Am. Chem. Soc., 2003, 125, 4686–4687 CrossRef CAS PubMed.
  33. M. H. Wright, C. Fetzer and S. A. Sieber, J. Am. Chem. Soc., 2017, 139, 6152–6159 CrossRef CAS PubMed.
  34. D. S. W. Hooi, B. W. Bycroft, S. R. Chhabra, P. Williams and D. I. Pritchard, Infect. Immun., 2004, 72, 6463–6470 CrossRef CAS PubMed.
  35. M. E. Skindersoe, L. H. Zeuthen, S. Brix, L. N. Fink, J. Lazenby, C. Whittall, P. Williams, S. P. Diggle, H. Froekiaer, M. Cooley and M. Givskov, FEMS Immunol. Med. Microbiol., 2009, 55, 335–345 CrossRef CAS PubMed.
  36. J. T. Hodgkinson, J. Gross, Y. R. Baker, D. R. Spring and M. Welch, Chem. Sci., 2016, 7, 2553–2562 RSC.
  37. J. Hodgkinson, S. D. Bowden, W. R. J. D. Galloway, D. R. Spring and M. Welch, J. Bacteriol., 2010, 192, 3833–3837 CrossRef CAS PubMed.
  38. T. Guina, S. O. Purvine, E. C. Yi, J. Eng, D. R. Goodlett, R. Aebersold and S. I. Miller, Proc. Natl. Acad. Sci. U. S. A., 2003, 100, 2771–2776 CrossRef CAS PubMed.
  39. E. Déziel, S. Gopalan, A. P. Tampakaki, F. Lépine, K. E. Padfield, M. Saucier, G. Xiao and L. G. Rahme, Mol. Microbiol., 2005, 55, 998–1014 CrossRef PubMed.
  40. F. Jerry Reen, J. P. Phelan, L. Gallagher, D. F. Woods, R. M. Shanahan, R. Cano, E. Ó. Muimhneacháin, G. P. McGlacken and F. O’Gara, Antimicrob. Agents Chemother., 2016, 60, 5894–5905 CrossRef PubMed.
  41. J. Y. L. Chiang, J. Lipid Res., 2009, 50, 1955–1966 CrossRef CAS PubMed.
  42. A. Wahlström, S. I. Sayin, H.-U. Marschall and F. Bäckhed, Cell Metab., 2016, 24, 41–50 CrossRef PubMed.
  43. M. Makishima, Science, 1999, 284, 1362–1365 CrossRef CAS PubMed.
  44. Y. Kawamata, R. Fujii, M. Hosoya, M. Harada, H. Yoshida, M. Miwa, S. Fukusumi, Y. Habata, T. Itoh, Y. Shintani, S. Hinuma, Y. Fujisawa and M. Fujino, J. Biol. Chem., 2003, 278, 9435–9440 CrossRef CAS PubMed.
  45. S. Zhuang, Q. Li, L. Cai, C. Wang and X. Lei, ACS Cent. Sci., 2017, 3, 501–509 CrossRef CAS PubMed.
  46. S.-E. Ong, B. Blagoev, I. Kratchmarova, D. B. Kristensen, H. Steen, A. Pandey and M. Mann, Mol. Cell. Proteomics, 2002, 1, 376–386 CAS.
  47. S.-E. Ong and M. Mann, Nat. Protoc., 2006, 1, 2650–2660 CrossRef CAS PubMed.
  48. A. Mullard, Nature, 2009, 459, 159–161 CrossRef CAS PubMed.
  49. Microbial Endocrinology: Interkingdom Signaling in Infectious Disease and Health, ed. M. Lyte and P. P. E. Primrose, Springer, Berlin, 2015 Search PubMed.
  50. P. P. E. Freestone, S. M. Sandrini, R. D. Haigh and M. Lyte, Trends Microbiol., 2008, 16, 55–64 CrossRef CAS PubMed.
  51. M. H. Karavolos, K. Winzer, P. Williams and C. M. A. Khan, Mol. Microbiol., 2013, 87, 455–465 CrossRef CAS PubMed.
  52. O. Zaborina, F. Lepine, G. Xiao, V. Valuckaite, Y. Chen, T. Li, M. Ciancio, A. Zaborin, E. O. Petrof, E. Petroff, J. R. Turner, L. G. Rahme, E. Chang and J. C. Alverdy, PLoS Pathog., 2007, 3, e35 CrossRef PubMed.
  53. A. Zaborin, S. Gerdes, C. Holbrook, D. C. Liu, O. Y. Zaborina and J. C. Alverdy, PLoS One, 2012, 7, e34883 CAS.
  54. CABI Invasive Species Compendium,, accessed 19 July 2017.
  55. K. Morimoto and R. A. L. van der Hoorn, Plant Cell Physiol., 2016, 57, 446–461 CrossRef CAS PubMed.
  56. I. Kolodziejek, J. C. Misas-Villamil, F. Kaschani, J. Clerc, C. Gu, D. Krahn, S. Niessen, M. Verdoes, L. I. Willems, H. S. Overkleeft, M. Kaiser and R. A. L. van der Hoorn, Plant Physiol., 2011, 155, 477–489 CrossRef CAS PubMed.
  57. J. C. Misas-Villamil, I. Kolodziejek, E. Crabill, F. Kaschani, S. Niessen, T. Shindo, M. Kaiser, J. R. Alfano and R. A. L. van der Hoorn, PLoS Pathog., 2013, 9, e1003281 CAS.
  58. M. Groll, B. Schellenberg, A. S. Bachmann, C. R. Archer, R. Huber, T. K. Powell, S. Lindow, M. Kaiser and R. Dudler, Nature, 2008, 452, 755–758 CrossRef CAS PubMed.
  59. J. Clerc, B. I. Florea, M. Kraus, M. Groll, R. Huber, A. S. Bachmann, R. Dudler, C. Driessen, H. S. Overkleeft and M. Kaiser, ChemBioChem, 2009, 10, 2638–2643 CrossRef CAS PubMed.
  60. A. C. Vlot, D. A. Dempsey and D. F. Klessig, Annu. Rev. Phytopathol., 2009, 47, 177–206 CrossRef CAS PubMed.
  61. H. Lu, Z. Wang, M. Shabab, J. Oeljeklaus, S. H. Verhelst, F. Kaschani, M. Kaiser, M. Bogyo and R. A. L. van der Hoorn, Chem. Biol., 2013, 20, 168–176 CrossRef CAS PubMed.
  62. N. Puri, C. Jenner, M. Bennett, R. Stewart, J. Mansfield, N. Lyons and J. Taylor, Mol. Plant-Microbe Interact., 1997, 10, 247–256 CrossRef CAS PubMed.
  63. Z. Nimchuk, E. Marois, S. Kjemtrup, R. T. Leister, F. Katagiri and J. L. Dangl, Cell, 2000, 101, 353–363 CrossRef CAS PubMed.
  64. R. H. Dowen, J. L. Engel, F. Shao, J. R. Ecker and J. E. Dixon, J. Biol. Chem., 2009, 284, 15867–15879 CrossRef CAS PubMed.
  65. A. Hartmann, M. Rothballer, B. A. Hense and P. Schröder, Front. Plant Sci., 2014, 5, 131 Search PubMed.
  66. A. S. Sebastian and T. Schenk, Front. Plant Sci., 2015, 643 Search PubMed.
  67. A. Schikora, S. T. Schenk and A. Hartmann, Plant Mol. Biol., 2016, 90, 605–612 CrossRef CAS PubMed.
  68. V. G. A. Olher, N. P. Ferreira, A. G. Souza, L. U. R. Chiavelli, A. F. Teixeira, W. D. Santos, S. M. O. Santin, O. Ferrarese Filho, C. C. Silva and A. M. Pomini, J. Nat. Prod., 2016, 79, 1316–1321 CrossRef CAS PubMed.
  69. M. E. Mattmann, P. M. Shipway, N. J. Heth and H. E. Blackwell, ChemBioChem, 2011, 12, 942–949 CrossRef CAS PubMed.
  70. G. D. Geske, J. C. O’Neill, D. M. Miller, M. E. Mattmann and H. E. Blackwell, J. Am. Chem. Soc., 2007, 129, 13613–13625 CrossRef CAS PubMed.
  71. A. G. Palmer, A. C. Senechal, A. Mukherjee, J.-M. Ané and H. E. Blackwell, ACS Chem. Biol., 2014, 9, 1834–1845 CrossRef CAS PubMed.
  72. A. G. Palmer, A. Mukherjee, D. M. Stacy, S. Lazar, J.-M. Ané and H. E. Blackwell, ChemBioChem, 2016, 17, 2199–2205 CrossRef CAS PubMed.
  73. S. Fonseca, A. Chini, M. Hamberg, B. Adie, A. Porzel, R. Kramell, O. Miersch, C. Wasternack and R. Solano, Nat. Chem. Biol., 2009, 5, 344–350 CrossRef CAS PubMed.
  74. L. Katsir, A. L. Schilmiller, P. E. Staswick, S. Y. He and G. A. Howe, Proc. Natl. Acad. Sci. U. S. A., 2008, 105, 7100–7105 CrossRef CAS PubMed.
  75. X.-Y. Zheng, N. W. Spivey, W. Zeng, P.-P. Liu, Z. Q. Fu, D. F. Klessig, S. Y. He and X. Dong, Cell Host Microbe, 2012, 11, 587–596 CAS.
  76. M. Ueda, S. Egoshi, K. Dodo, Y. Ishimaru, H. Yamakoshi, T. Nakano, Y. Takaoka, S. Tsukiji and M. Sodeoka, ACS Cent. Sci., 2017, 3, 462–472 CrossRef CAS PubMed.
  77. M. Okada, S. Ito, A. Matsubara, I. Iwakura, S. Egoshi and M. Ueda, Org. Biomol. Chem., 2009, 7, 3065 CAS.
  78. S. Egoshi, Y. Takaoka, H. Saito, Y. Nukadzuka, K. Hayashi, Y. Ishimaru, H. Yamakoshi, K. Dodo, M. Sodeoka and M. Ueda, RSC Adv., 2016, 6, 19404–19412 RSC.
  79. K. Lang and J. W. Chin, Chem. Rev., 2014, 114, 4764–4806 CrossRef CAS PubMed.
  80. J. T. Ngo, E. M. Schuman and D. A. Tirrell, Proc. Natl. Acad. Sci. U. S. A., 2013, 110, 4992–4997 CrossRef CAS PubMed.
  81. H. Xiao, A. Chatterjee, S.-H. Choi, K. M. Bajjuri, S. C. Sinha and P. G. Schultz, Angew. Chem., Int. Ed., 2013, 52, 14080–14083 CrossRef CAS PubMed.
  82. A. J. Pérez, F. Wesche, H. Adihou and H. B. Bode, Chemistry, 2016, 22, 639–645 CrossRef PubMed.
  83. C. J. O’Connor, L. Laraia and D. R. Spring, Chem. Soc. Rev., 2011, 40, 4332 RSC.
  84. A. G. Palmer, E. Streng and H. E. Blackwell, ACS Chem. Biol., 2011, 6, 1348–1356 CrossRef CAS PubMed.
  85. R. Tóth and R. A. L. van der Hoorn, Trends Plant Sci., 2010, 15, 81–88 CrossRef PubMed.
  86. C. J. O’Connor, H. S. G. Beckmann and D. R. Spring, Chem. Soc. Rev., 2012, 41, 4444–4456 RSC.
  87. D. S. Tan, Nat. Chem. Biol., 2005, 1, 74–84 CrossRef CAS PubMed.
  88. J. Zhou, Y. Lyu, M. Richlen, D. M. Anderson and Z. Cai, CRC Crit. Rev. Plant Sci., 2016, 35, 81–105 CrossRef CAS PubMed.
  89. (a) C. Reyers, The Kavli Microbiome Ideas Challenge Funds Innovative, Cross-Cutting Research – Kavli Challenge,, accessed 13 August 2017; (b) An encouraging example of funding in this area is the Kavli Microbiome Ideas Challenge grant, which, for instance, was recently awarded to the team of Theberge, Berthier, and Keller, who propose to create “new analytical chemistry and engineering tools that pull out key molecules from a mix of molecular noise in order to selectively ‘listen’ to molecular signals produced by specific fungi, bacteria, or human cells.”.

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