Feature sequence-based genome mining uncovers the hidden diversity of bacterial siderophore pathways.

Microbial secondary metabolites are a rich source for pharmaceutical discoveries and play crucial ecological functions. While tools exist to identify secondary metabolite clusters in genomes, precise sequence-to-function mapping remains challenging because neither function nor substrate specificity of biosynthesis enzymes can accurately be predicted. Here, we developed a knowledge-guided bioinformatic pipeline to solve these issues. We analyzed 1928 genomes of Pseudomonas bacteria and focused on iron-scavenging pyoverdines as model metabolites. Our pipeline predicted 188 chemically different pyoverdines with nearly 100% structural accuracy and the presence of 94 distinct receptor groups required for the uptake of iron-loaded pyoverdines. Our pipeline unveils an enormous yet overlooked diversity of siderophores (151 new structures) and receptors (91 new groups). Our approach, combining feature sequence with phylogenetic approaches, is extendable to other metabolites and microbial genera, and thus emerges as powerful tool to reconstruct bacterial secondary metabolism pathways based on sequence data.

Interactions between Pseudomonas aeruginosa and six opportunistic pathogens cover a broad spectrum from mutualism to antagonism.

Bacterial infections often involve more than one pathogen. While it is well established that polymicrobial infections can impact disease outcomes, we know little about how pathogens interact and affect each other's behaviour and fitness. Here, we used a microscopy approach to explore interactions between Pseudomonas aeruginosa and six human opportunistic pathogens that often co-occur in polymicrobial infections: Acinetobacter baumannii, Burkholderia cenocepacia, Escherichia coli, Enterococcus faecium, Klebsiella pneumoniae, and Staphylococcus aureus. When following growing microcolonies on agarose pads over time, we observed a broad spectrum of species-specific ecological interactions, ranging from mutualism to antagonism. For example, P. aeruginosa engaged in a mutually beneficial interaction with E. faecium but suffered from antagonism by E. coli. While we found little evidence for active directional growth towards or away from cohabitants, we observed that some pathogens increased growth in double layers in response to competition and that physical forces due to fast colony expansion had a major impact on fitness. Overall, our work provides an atlas of pathogen interactions, highlighting the diversity of potential species dynamics that may occur in polymicrobial infections. We discuss possible mechanisms driving pathogen interactions and offer predictions of how the different ecological interactions could affect virulence.

RNA-Seq reveals that Pseudomonas aeruginosa mounts growth medium-dependent competitive responses when sensing diffusible cues from Burkholderia cenocepacia.

Most habitats host diverse bacterial communities, offering opportunities for inter-species interactions. While competition might often dominate such interactions, little is known about whether bacteria can sense competitors and mount adequate responses. The competition sensing hypothesis proposes that bacteria can use cues such as nutrient stress and cell damage to prepare for battle. Here, we tested this hypothesis by measuring transcriptome changes in Pseudomonas aeruginosa exposed to the supernatant of its competitor Burkholderia cenocepacia. We found that P. aeruginosa exhibited significant growth-medium-dependent transcriptome changes in response to competition. In an iron-rich medium, P. aeruginosa upregulated genes encoding the type-VI secretion system and the siderophore pyoverdine, whereas genes encoding phenazine toxins and hydrogen cyanide were upregulated under iron-limited conditions. Moreover, general stress response and quorum sensing regulators were upregulated upon supernatant exposure. Altogether, our results reveal nuanced competitive responses of P. aeruginosa when confronted with B. cenocepacia supernatant, integrating both environmental and social cues.

A new protocol for multispecies bacterial infections in zebrafish and their monitoring through automated image analysis.

The zebrafish Danio rerio has become a popular model host to explore disease pathology caused by infectious agents. A main advantage is its transparency at an early age, which enables live imaging of infection dynamics. While multispecies infections are common in patients, the zebrafish model is rarely used to study them, although the model would be ideal for investigating pathogen-pathogen and pathogen-host interactions. This may be due to the absence of an established multispecies infection protocol for a defined organ and the lack of suitable image analysis pipelines for automated image processing. To address these issues, we developed a protocol for establishing and tracking single and multispecies bacterial infections in the inner ear structure (otic vesicle) of the zebrafish by imaging. Subsequently, we generated an image analysis pipeline that involved deep learning for the automated segmentation of the otic vesicle, and scripts for quantifying pathogen frequencies through fluorescence intensity measures. We used Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae, three of the difficult-to-treat ESKAPE pathogens, to show that our infection protocol and image analysis pipeline work both for single pathogens and pairwise pathogen combinations. Thus, our protocols provide a comprehensive toolbox for studying single and multispecies infections in real-time in zebrafish.

Predicting bacterial interaction outcomes from monoculture growth and supernatant assays.

How to derive principles of community dynamics and stability is a central question in microbial ecology. Bottom-up experiments, in which a small number of bacterial species are mixed, have become popular to address it. However, experimental setups are typically limited because co-culture experiments are labor-intensive and species are difficult to distinguish. Here, we use a four-species bacterial community to show that information from monoculture growth and inhibitory effects induced by secreted compounds can be combined to predict the competitive rank order in the community. Specifically, integrative monoculture growth parameters allow building a preliminary competitive rank order, which is then adjusted using inhibitory effects from supernatant assays. While our procedure worked for two different media, we observed differences in species rank orders between media. We then parameterized computer simulations with our empirical data to show that higher order species interactions largely follow the dynamics predicted from pairwise interactions with one important exception. The impact of inhibitory compounds was reduced in higher order communities because their negative effects were spread across multiple target species. Altogether, we formulated three simple rules of how monoculture growth and supernatant assay data can be combined to establish a competitive species rank order in an experimental four-species community.

Space and genealogy determine inter-individual differences in siderophore gene expression in bacterial colonies.

Heterogeneity in gene expression is common among clonal cells in bacteria, although the sources and functions of variation often remain unknown. Here, we track cellular heterogeneity in the bacterium Pseudomonas aeruginosa during colony growth by focusing on siderophore gene expression (pyoverdine versus pyochelin) important for iron nutrition. We find that the spatial position of cells within colonies and non-genetic yet heritable differences between cell lineages are significant sources of cellular heterogeneity, while cell pole age and lifespan have no effect. Regarding functions, our results indicate that cells adjust their siderophore investment strategies along a gradient from the colony center to its edge. Moreover, cell lineages with below-average siderophore investment benefit from lineages with above-average siderophore investment, presumably due to siderophore sharing. Our study highlights that single-cell experiments with dual gene expression reporters can identify sources of gene expression variation of interlinked traits and offer explanations for adaptive benefits in bacteria.

Microbiome convergence enables siderophore-secreting-rhizobacteria to improve iron nutrition and yield of peanut intercropped with maize.

Intercropping has the potential to improve plant nutrition as well as crop yield. However, the exact mechanism promoting improved nutrient acquisition and the role the rhizosphere microbiome may play in this process remains poorly understood. Here, we use a peanut/maize intercropping system to investigate the role of root-associated microbiota in iron nutrition in these crops, combining microbiome profiling, strain and substance isolation and functional validation. We find that intercropping increases iron nutrition in peanut but not in maize plants and that the microbiota composition changes and converges between the two plants tested in intercropping experiments. We identify a Pseudomonas secreted siderophore, pyoverdine, that improves iron nutrition in glasshouse and field experiments. Our results suggest that the presence of siderophore-secreting Pseudomonas in peanut and maize intercropped plays an important role in iron nutrition. These findings could be used to envision future intercropping practices aiming to improve plant nutrition.

Pyoverdine Analysis - From High-resolution MS/MS Fragmentation to Ion Mobility Measurements.

Microorganisms produce iron chelators called siderophores that are a rich source for drug discovery or plant protective agents. Pyoverdines are a class of siderophores from fluorescent Pseudomonas members and consist of different peptide chains specific to each bacterial species. The structural elucidation and characterization of pyoverdines require comprehensive analytical methods as bacterial extracts are complex mixtures. Here, we present a high-throughput UHPLC-MS/MS pipeline and the application of ion mobility spectrometry to facilitate research in the field of medicine and agriculture.

Rapid and strain-specific resistance evolution of Staphylococcus aureus against inhibitory molecules secreted by Pseudomonas aeruginosa.

IMPORTANCE: Polymicrobial infections are common. In chronic infections, the different pathogens may repeatedly interact, which could spur evolutionary dynamics with pathogens adapting to one another. Here, we explore the potential of Staphylococcus aureus to adapt to its competitor Pseudomonas aeruginosa. These two pathogens frequently co-occur, and P. aeruginosa is seen as the dominant species being able to displace S. aureus. We studied three different S. aureus strains and found that all became quickly resistant to inhibitory compounds secreted by P. aeruginosa. Our experimental evolution revealed strains-specific adaptations with three main factors contributing to resistance evolution: (i) overproduction of staphyloxanthin, a molecule protecting from oxidative stress; (ii) the formation of small colony variants also protecting from oxidative stress; and (iii) alterations of membrane transporters possibly reducing toxin uptake. Our results show that species interactions can change over time potentially favoring species co-existence, which in turn could affect disease progression and treatment options.

Negative interactions and virulence differences drive the dynamics in multispecies bacterial infections.

Bacterial infections are often polymicrobial, leading to intricate pathogen-pathogen and pathogen-host interactions. There is increasing interest in studying the molecular basis of pathogen interactions and how such mechanisms impact host morbidity. However, much less is known about the ecological dynamics between pathogens and how they affect virulence and host survival. Here we address these open issues by co-infecting larvae of the insect model host Galleria mellonella with one, two, three or four bacterial species, all of which are opportunistic human pathogens. We found that host mortality was always determined by the most virulent species regardless of the number of species and pathogen combinations injected. In certain combinations, the more virulent pathogen simply outgrew the less virulent pathogen. In other combinations, we found evidence for negative interactions between pathogens inside the host, whereby the more virulent pathogen typically won a competition. Taken together, our findings reveal positive associations between a pathogen's growth inside the host, its competitiveness towards other pathogens and its virulence. Beyond being generalizable across species combinations, our findings predict that treatments against polymicrobial infections should first target the most virulent species to reduce host morbidity, a prediction we validated experimentally.

Evolutionary explanations for heterogeneous behavior in clonal bacterial populations.

Cellular heterogeneity in clonal bacterial populations is widespread. Division of labor and bet hedging are common adaptive explanations for the function of such heterogeneity. We suggest group-level phenotypes via shareable molecules and variation in cellular vigor as two alternative evolutionary explanations for bacterial cellular heterogeneity.

Chryseochelins-structural characterization of novel citrate-based siderophores produced by plant protecting Chryseobacterium spp.

Bacteria secrete siderophores whose function is to acquire iron. In recent years, the siderophores of several Chryseobacterium species were shown to promote the health and growth of various plants such as tomato or rice. However, the chemical nature of Chryseobacterium siderophores remained unexplored despite great interest. In this work, we present the purification and structure elucidation by nuclear magnetic resonance (NMR) spectroscopy and tandem mass spectrometry (MS/MS) of chryseochelin A, a novel citrate-based siderophore secreted by three Chryseobacterium strains involved in plant protection. It contains the unusual building blocks 3-hydroxycadaverine and fumaric acid. Furthermore, the unstable structural isomer chryseochelin B and its stable derivative containing fatty acid chains, named chryseochelin C, were identified by mass spectrometric methods. The latter two incorporate an unusual ester connectivity to the citrate moiety showing similarities to achromobactin from the plant pathogen Dickeya dadantii. Finally, we show that chryseochelin A acts in a concentration-dependent manner against the plant-pathogenic Ralstonia solanacearum strain by reducing its access to iron. Thus, our study provides valuable knowledge about the siderophores of Chryseobacterium strains, which have great potential in various applications.

Microbiome-Based Stain Analyses in Crime Scenes.

Recent advances in next-generation sequencing technologies (NGS) coupled with machine learning have demonstrated the potential of microbiome-based analyses in applied areas such as clinical diagnostics and forensic sciences. Particularly in forensics, microbial markers in biological stains left at a crime scene can provide valuable information for the reconstruction of crime scene cases, as they contain information on bodily origin, the time since deposition, and donor(s) of the stain. Importantly, microbiome-based analyses provide a complementary or an alternative approach to current methods when these are limited or not feasible. Despite the promising results from recent research, microbiome-based stain analyses are not yet employed in routine casework. In this review, we highlight the two main gaps that need to be addressed before we can successfully integrate microbiome-based analyses in applied areas with a special focus on forensic casework: one is a comprehensive assessment of the method's strengths and limitations, and the other is the establishment of a standard operating procedure. For the latter, we provide a roadmap highlighting key decision steps and offering laboratory and bioinformatic workflow recommendations, while also delineating those aspects that require further testing. Our goal is to ultimately facilitate the streamlining of microbiome-based analyses within the existing forensic framework to provide alternate lines of evidence, thereby improving the quality of investigations.

Iron acquisition strategies in pseudomonads: mechanisms, ecology, and evolution.

Iron is important for bacterial growth and survival, as it is a common co-factor in essential enzymes. Although iron is very abundant in the earth crust, its bioavailability is low in most habitats because ferric iron is largely insoluble under aerobic conditions and at neutral pH. Consequently, bacteria have evolved a plethora of mechanisms to solubilize and acquire iron from environmental and host stocks. In this review, I focus on Pseudomonas spp. and first present the main iron uptake mechanisms of this taxa, which involve the direct uptake of ferrous iron via importers, the production of iron-chelating siderophores, the exploitation of siderophores produced by other microbial species, and the use of iron-chelating compounds produced by plants and animals. In the second part of this review, I elaborate on how these mechanisms affect interactions between bacteria in microbial communities, and between bacteria and their hosts. This is important because Pseudomonas spp. live in diverse communities and certain iron-uptake strategies might have evolved not only to acquire this essential nutrient, but also to gain relative advantages over competitors in the race for iron. Thus, an integrative understanding of the mechanisms of iron acquisition and the eco-evolutionary dynamics they drive at the community level might prove most useful to understand why Pseudomonas spp., in particular, and many other bacterial species, in general, have evolved such diverse iron uptake repertoires.

Rapid identification of pyoverdines of fluorescent Pseudomonas spp. by UHPLC-IM-MS.

Siderophores are iron-chelating molecules produced by bacteria and other microbes. They are involved with virulence in infections and play key roles in bacterial community assembly and as plant protectants due to their pathogen control properties. Although assays exist to screen whether newly isolated bacteria can produce siderophores, the chemical structures of many of these bio-active molecules remain unidentified due to the lack of rapid analytical procedures. An important group of siderophores are pyoverdines. They consist of a structurally diverse group of chromopeptides, whose amino acid sequence is characteristic for the fluorescent Pseudomonas species that secrets them. Although over 60 pyoverdine structures have been described so far, their characterization is cumbersome and several methods (isoelectrofocusing, iron uptake measurement, mass determination) are typically combined as ambiguous results are often achieved by a single method. Those additional experiments consume valuable time and resources and prevent high-throughput analysis. In this work, we present a new pyoverdine characterisation option by recording their collision cross sections (CCS) using trapped ion mobility spectrometry. This can be done simultaneously in combination with UHPLC and high-resolution MS resulting in a rapid identification of pyoverdines. The high specificity of CCS values is presented for 17 pyoverdines secreted by different Pseudomonas strains. The pyoverdine mass determination by full scan MS was supported by fragments obtained from broadband collision induced dissociation (bbCID). As iron contaminations in laboratories are not uncommon, CCS values of ferripyoverdines were also evaluated. Thereby, unusual and highly characteristic ion mobility patterns were obtained that are suitable as an alternative identification marker.

Collective decision-making in Pseudomonas aeruginosa involves transient segregation of quorum-sensing activities across cells.

A hallmark of bacterial sociality is that groups can coordinate cooperative actions through a cell-to-cell communication process called quorum sensing (QS). QS regulates key bacterial phenotypes such as virulence in infections and digestion of extracellular compounds in the environment. Although QS responses are typically studied as group-level phenotypes, it is unclear whether individuals coordinate their actions at the single-cell level or whether group phenotypes simply reflect the sum of their noisy members. Here, we studied the behavior of Pseudomonas aeruginosa individuals by tracking their temporal commitments to the two intertwined Las and Rhl-QS systems, from low to high population density. Using chromosomally integrated fluorescent gene reporters, we found that QS gene expression (signal, receptor, and cooperative exoproduct) was noisy with heterogeneity peaking during the build-up phase of QS. Moreover, we observed the formation of discrete subgroups of cells that transiently segregate into two gene expression states: low Las-receptor expressers that instantly activate exoproduct production and high Las-receptor expressers with delayed exoproduct production. Later, gene expression activities converged with all cells fully committing to QS. We developed general mathematical models to show that gene expression segregation can mechanistically be spurred by molecular resource limitations during the initiation phase of regulatory cascades such as QS. Moreover, our models indicate that gene expression segregation across cells can operate as a built-in brake enabling a temporary bet-hedging strategy in unpredictable environments. Altogether, our work reveals that studying the behavior of bacterial individuals is key to understanding emergent collective actions at the group level.

Evolution of Quorum Sensing in Pseudomonas aeruginosa Can Occur via Loss of Function and Regulon Modulation.

Pseudomonas aeruginosa populations evolving in cystic fibrosis lungs, animal hosts, natural environments and in vitro undergo extensive genetic adaption and diversification. A common mutational target is the quorum sensing (QS) system, a three-unit regulatory system that controls the expression of virulence factors and secreted public goods. Three evolutionary scenarios have been advocated to explain selection for QS mutants: (i) disuse of the regulon, (ii) cheating through the exploitation of public goods, or (ii) modulation of the QS regulon. Here, we examine these scenarios by studying a set of 61 QS mutants from an experimental evolution study. We observed nonsynonymous mutations in all three QS systems: Las, Rhl, and Pseudomonas Quinolone Signal (PQS). The majority of the Las mutants had large deletions of the Las regulon, resulting in loss of QS function and the inability to produce QS-regulated traits, thus supporting the first or second scenarios. Conversely, phenotypic and gene expression analyses of Rhl mutants support network modulation (third scenario), as these mutants overexpressed the Las and Rhl receptors and showed an altered QS-regulated trait production profile. PQS mutants also showed patterns of regulon modulation leading to strain diversification and phenotypic tradeoffs, where the upregulation of certain QS traits is associated with the downregulation of others. Overall, our results indicate that mutations in the different QS systems lead to diverging effects on the QS trait profile in P. aeruginosa populations. These mutations might not only affect the plasticity and diversity of evolved populations but could also impact bacterial fitness and virulence in infections. IMPORTANCE Pseudomonas aeruginosa uses quorum sensing (QS), a three-unit multilayered network, to coordinate expression of traits required for growth and virulence in the context of infections. Despite its importance for bacterial fitness, the QS regulon appears to be a common mutational target during long-term adaptation of P. aeruginosa in the host, natural environments, and experimental evolutions. This raises questions of why such an important regulatory system is under selection and how mutations change the profile of QS-regulated traits. Here, we examine a set of 61 experimentally evolved QS mutants to address these questions. We found that mutations involving the master regulator, LasR, resulted in an almost complete breakdown of QS, while mutations in RhlR and PqsR resulted in modulations of the regulon, where both the regulon structure and the QS-regulated trait profile changed. Our work reveals that natural selection drives diversification in QS activity patterns in evolving populations.

Coordination of siderophore gene expression among clonal cells of the bacterium Pseudomonas aeruginosa.

There has been great progress in understanding how bacterial groups coordinate social actions, such as biofilm formation and public-goods secretion. Less clear is whether the seemingly coordinated group-level responses actually mirror what individual cells do. Here, we use a microscopy approach to simultaneously quantify the investment of individual cells of the bacterium Pseudomonas aeruginosa into two public goods, the siderophores pyochelin and pyoverdine. Using gene expression as a proxy for investment, we initially observe no coordination but high heterogeneity and bimodality in siderophore investment across cells. With increasing cell density, gene expression becomes more homogenized across cells, accompanied by a moderate shift from pyochelin to pyoverdine expression. We find positive associations in the expression of pyochelin and pyoverdine genes across cells, with cell-to-cell variation correlating with cellular metabolic states. Our work suggests that siderophore-mediated signalling aligns behaviour of individuals over time and spurs a coordinated three-phase siderophore investment cycle.

Enforced specialization fosters mutual cheating and not division of labour in the bacterium Pseudomonas aeruginosa.

A common way for bacteria to cooperate is via the secretion of beneficial public goods (proteases, siderophores, biosurfactants) that can be shared amongst individuals in a group. Bacteria often simultaneously deploy multiple public goods with complementary functions. This raises the question whether natural selection could favour division of labour where subpopulations or species specialize in the production of a single public good, whilst sharing the complementary goods at the group level. Here we use an experimental system, where we mix engineered specialists of the bacterium Pseudomonas aeruginosa that can each only produce one of the two siderophores, pyochelin or pyoverdine and explore the conditions under which specialization can lead to division of labour. When growing pyochelin and pyoverdine specialists at different mixing ratios under different levels of iron limitation, we found that specialists could only successfully complement each other in environments with moderate iron limitation and grow as good as the generalist wildtype but not better. Under more stringent iron limitation, the dynamics in specialist communities was characterized by mutual cheating and with higher proportions of pyochelin producers greatly compromising group productivity. Nonetheless, specialist communities remained stable through negative frequency-dependent selection. Our work shows that specialization in a bacterial community can be spurred by cheating and does not necessarily result in beneficial division of labour. We propose that natural selection might favour fine-tuned regulatory mechanisms in generalists over division of labour because the former enables generalists to remain flexible and adequately adjust public good investments in fluctuating environments.

A comprehensive method to elucidate pyoverdines produced by fluorescent Pseudomonas spp. by UHPLC-HR-MS/MS.

Microbial secondary metabolites represent a rich source for drug discovery, plant protective agents, and biotechnologically relevant compounds. Among them are siderophores, iron-chelating molecules, that show a great influence on bacterial community assembly and the potential to control pathogen invasions. One of such a siderophore is pyoverdine that is produced by fluorescent Pseudomonas members and consists of different peptide chains specific to each bacterial species. The identification and structural elucidation of such suites of siderophores remain widely underexplored as general high-throughput analytical protocols are missing. Therefore, a dedicated method was established allowing a rapid localization and structural elucidation of pyoverdines. Liquid bacterial culture samples were purified by an easy small-scale solid-phase extraction (SPE). Ultra-high-performance liquid chromatography high-resolution tandem mass spectrometry (UHPLC-HR-MS/MS) separated highly polar pyoverdines and their derivatives. All ion fragmentation (AIF) generated mass spectra containing the characteristic fragments of the biological precursor of pyoverdine, ferribactin. This led to the revelation of the mass of secreted pyoverdines. Targeted MS/MS experiments at multiple collision energies accomplished the full structure elucidation of the pyoverdine peptide chain. A mass calculator and a fragmentation predictor facilitated greatly the interpretation of MS/MS spectra by providing accurate masses for a straightforward comparison of measured and theoretical values. The method was successfully validated using four well-known pyoverdines with various peptide chains. Finally, the applicability was proven by the analysis of 13 unknown pyoverdines secreted by sampled bacterial cultures. Among these, 4 novel pyoverdine peptide chains were discovered and are herein reported for the first time.