Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network

Revisiting the evolution of bow-tie architecture in signaling networks

Bow-tie architecture is a layered network structure that has a narrow middle layer with multiple inputs and outputs. Such structures are widely seen in the molecular networks in cells, suggesting that a universal evolutionary mechanism underlies the emergence of bow-tie architecture. The previous theoretical studies have implemented evolutionary simulations of the feedforward network to satisfy a given input-output goal and proposed that the bow-tie architecture emerges when the ideal input-output relation is given as a rank-deficient matrix with mutations in network link intensities in a multiplicative manner. Here, we report that the bow-tie network inevitably appears when the link intensities representing molecular interactions are small at the initial condition of the evolutionary simulation, regardless of the rank of the goal matrix. Our dynamical system analysis clarifies the mechanisms underlying the emergence of the bow-tie structure. Further, we demonstrate that the increase in the input-output matrix reduces the width of the middle layer, resulting in the emergence of bow-tie architecture, even when evolution starts from large link intensities. Our data suggest that bow-tie architecture emerges as a side effect of evolution rather than as a result of evolutionary adaptation.

Local control: a hub-based model for the c-di-GMP network

The genome of Pseudomonas fluorescens encodes >50 proteins predicted to play a role in bis-(3'-5')-cyclic dimeric guanosine monophosphate (c-di-GMP)-mediated biofilm formation. We built a network representation of protein-protein interactions and extracted key information via multidimensional scaling (i.e., principal component analysis) of node centrality measures, which measure features of proteins in a network. Proteins of different domain types (diguanylate cyclase, dual domain, phosphodiesterase, PilZ) exhibit unique network behavior and can be accurately classified by their network centrality values (i.e., roles in the network). The predictive power of protein-protein interactions in biofilm formation indicates the possibility of localized pools of c-di-GMP. A regression model showed a statistically significant impact of protein-protein interactions on the extent of biofilm formation in various environments. These results highlight the importance of a localized c-di-GMP signaling, extend our understanding of signaling by this second messenger beyond the current "Bow-tie Model," support a newly proposed "Hub Model," and suggest future avenues of investigation.

Pleiotropic hubs drive bacterial surface competition through parallel changes in colony composition and expansion

Bacteria commonly adhere to surfaces where they compete for both space and resources. Despite the importance of surface growth, it remains largely elusive how bacteria evolve on surfaces. We previously performed an evolution experiment where we evolved distinct Bacilli populations under a selective regime that favored colony spreading. In just a few weeks, colonies of Bacillus subtilis showed strongly advanced expansion rates, increasing their radius 2.5-fold relative to that of the ancestor. Here, we investigate what drives their rapid evolution by performing a uniquely detailed analysis of the evolutionary changes in colony development. We find mutations in diverse global regulators, RicT, RNAse Y, and LexA, with strikingly similar pleiotropic effects: They lower the rate of sporulation and simultaneously facilitate colony expansion by either reducing extracellular polysaccharide production or by promoting filamentous growth. Combining both high-throughput flow cytometry and gene expression profiling, we show that regulatory mutations lead to highly reproducible and parallel changes in global gene expression, affecting approximately 45% of all genes. This parallelism results from the coordinated manner by which regulators change activity both during colony development-in the transition from vegetative growth to dormancy-and over evolutionary time. This coordinated activity can however also break down, leading to evolutionary divergence. Altogether, we show how global regulators function as major pleiotropic hubs that drive rapid surface adaptation by mediating parallel changes in both colony composition and expansion, thereby massively reshaping gene expression.

Genome-Based Analysis of Virulence Factors and Biofilm Formation in Novel P. aeruginosa Strains Isolated from Household Appliances

In household washing machines, opportunistic pathogens such as Pseudomonas aeruginosa are present, which represent the household as a possible reservoir for clinical pathogens. Here, four novel P. aeruginosa strains, isolated from different sites of household appliances, were investigated regarding their biofilm formation. Only two isolates showed strong surface-adhered biofilm formation. In consequence of these phenotypic differences, we performed whole genome sequencing using Oxford Nanopore Technology together with Illumina MiSeq. Whole genome data were screened for the prevalence of 285 virulence- and biofilm-associated genes as well as for prophages. Linking biofilm phenotypes and parallelly appearing gene compositions, we assume a relevancy of the las quorum sensing system and the phage-encoded bacteriophage control infection gene bci, which was found on integrated phi297 DNA in all biofilm-forming isolates. Additionally, only the isolates revealing strong biofilm formation harbored the ϕCTX-like prophage Dobby, implicating a role of this prophage on biofilm formation. Investigations on clinically relevant pathogens within household appliances emphasize their adaptability to harsh environments, with high concentrations of detergents, providing greater insights into pathogenicity and underlying mechanisms. This in turn opens the possibility to map and characterize potentially relevant strains even before they appear as pathogens in society.

Evolution and regulation of microbial secondary metabolism

Microbes have disproportionate impacts on the macroscopic world. This is in part due to their ability to grow to large populations that collectively secrete massive amounts of secondary metabolites and alter their environment. Yet, the conditions favoring secondary metabolism despite the potential costs for primary metabolism remain unclear. Here we investigated the biosurfactants that the bacterium Pseudomonas aeruginosa makes and secretes to decrease the surface tension of surrounding liquid. Using a combination of genomics, metabolomics, transcriptomics, and mathematical modeling we show that the ability to make surfactants from glycerol varies inconsistently across the phylogenetic tree; instead, lineages that lost this ability are also worse at reducing the oxidative stress of primary metabolism on glycerol. Experiments with different carbon sources support a link with oxidative stress that explains the inconsistent distribution across the P. aeruginosa phylogeny and suggests a general principle: P. aeruginosa lineages produce surfactants if they can reduce the oxidative stress produced by primary metabolism and have excess resources, beyond their primary needs, to afford secondary metabolism. These results add a new layer to the regulation of a secondary metabolite unessential for primary metabolism but important to change physical properties of the environments surrounding bacterial populations.

Identification of Cyclic-di-GMP-Modulating Protein Residues by Bidirectionally Evolving a Social Behavior in Pseudomonas fluorescens

Modulation of the intracellular cyclic di-GMP (c-di-GMP) pool is central to the formation of structured bacterial communities. Genome annotations predict the presence of dozens of conserved c-di-GMP catalytic enzymes in many bacterial species, but the functionality and regulatory control of the vast majority remain underexplored. Here, we begin to fill this gap by utilizing an experimental evolution system in Pseudomonas fluorescens Pf0-1, which repeatedly produces a unique social behavior through bidirectional transitions between two distinct phenotypes converging on c-di-GMP modulation. Parallel evolution of 33 lineages captured 147 unique mutations among 191 evolved isolates in genes that are empirically demonstrated, bioinformatically predicted, or previously unknown to impact the intracellular pool of c-di-GMP. Quantitative chemistry confirmed that each mutation causing the phenotypic shift either amplifies or reduces c-di-GMP production. We identify missense or in-frame deletion mutations in numerous diguanylate cyclase genes that largely fall outside the conserved catalytic domain. We also describe a novel relationship between a regulatory component of branched-chain amino acid biosynthesis and c-di-GMP production, and predict functions of several other unexpected proteins that clearly impact c-di-GMP production. Sequential mutations that continuously disrupt or recover c-di-GMP production across discrete functional elements suggest a complex and underappreciated interconnectivity within the c-di-GMP regulome of P. fluorescens. IMPORTANCE Microbial communities comprise densely packed cells where competition for space and resources is fierce. Aging colonies of Pseudomonas fluorescens are known to repeatedly produce mutants with two distinct phenotypes that physically work together to spread away from the overcrowded population. We demonstrate that the mutants with one phenotype produce high levels of cyclic di-GMP (c-di-GMP) and those with the second phenotype produce low levels. C-di-GMP is an intracellular signaling molecule which regulates many bacterial traits that cause tremendous clinical and environmental problems. Here, we analyze 147 experimentally selected mutations, which manifest either of the two phenotypes, to identify key residues in diverse proteins that force or shut down c-di-GMP production. Our data indicate that the intracellular pool of c-di-GMP is modulated through the catalytic activities of many independent c-di-GMP enzymes, which appear to be in tune with several proteins with no known links to c-di-GMP modulation.

Mathematical models to study the biology of pathogens and the infectious diseases they cause

Mathematical models have many applications in infectious diseases: epidemiologists use them to forecast outbreaks and design containment strategies; systems biologists use them to study complex processes sustaining pathogens, from the metabolic networks empowering microbial cells to ecological networks in the microbiome that protects its host. Here, we (1) review important models relevant to infectious diseases, (2) draw parallels among models ranging widely in scale. We end by discussing a minimal set of information for a model to promote its use by others and to enable predictions that help us better fight pathogens and the diseases they cause.

Evolutionary Divergence of the Wsp Signal Transduction Systems in Beta- and Gammaproteobacteria

Bacteria rapidly adapt to their environment by integrating external stimuli through diverse signal transduction systems. Pseudomonas aeruginosa, for example, senses surface contact through the Wsp signal transduction system to trigger the production of cyclic di-GMP. Diverse mutations in wsp genes that manifest enhanced biofilm formation are frequently reported in clinical isolates of P. aeruginosa and in biofilm studies of Pseudomonas spp. and Burkholderia cenocepacia. In contrast to the convergent phenotypes associated with comparable wsp mutations, we demonstrate that the Wsp system in B. cenocepacia does not impact intracellular cyclic di-GMP levels, unlike that in Pseudomonas spp. Our current mechanistic understanding of the Wsp system is based entirely on the study of four Pseudomonas spp., and its phylogenetic distribution remains unknown. Here, we present a broad phylogenetic analysis to show that the Wsp system originated in the betaproteobacteria and then horizontally transferred to Pseudomonas spp., the sole member of the gammaproteobacteria. Alignment of 794 independent Wsp systems with reported mutations from the literature identified key amino acid residues that fall within and outside annotated functional domains. Specific residues that are highly conserved but uniquely modified in B. cenocepacia likely define mechanistic differences among Wsp systems. We also find the greatest sequence variation in the extracellular sensory domain of WspA, indicating potential adaptations to diverse external stimuli beyond surface contact sensing. This study emphasizes the need to better understand the breadth of functional diversity of the Wsp system as a major regulator of bacterial adaptation beyond B. cenocepacia and select Pseudomonas spp. IMPORTANCE The Wsp signal transduction system serves as an important model system for studying how bacteria adapt to living in densely structured communities known as biofilms. Biofilms frequently cause chronic infections and environmental fouling, and they are very difficult to eradicate. In Pseudomonas aeruginosa, the Wsp system senses contact with a surface, which in turn activates specific genes that promote biofilm formation. We demonstrate that the Wsp system in Burkholderia cenocepacia regulates biofilm formation uniquely from that in Pseudomonas species. Furthermore, a broad phylogenetic analysis reveals the presence of the Wsp system in diverse bacterial species, and sequence analyses of 794 independent systems suggest that the core signaling components function similarly but with key differences that may alter what or how they sense. This study shows that Wsp systems are highly conserved and more broadly distributed than previously thought, and their unique differences likely reflect adaptations to distinct environments.

Estimation of pathogenic potential of an environmental Pseudomonas aeruginosa isolate using comparative genomics

The isolation and sequencing of new strains of Pseudomonas aeruginosa created an extensive dataset of closed genomes. Many of the publicly available genomes are only used in their original publication while additional in silico information, based on comparison to previously published genomes, is not being explored. In this study, we defined and investigated the genome of the environmental isolate P. aeruginosa KRP1 and compared it to more than 100 publicly available closed P. aeruginosa genomes. By using different genomic island prediction programs, we could identify a total of 17 genomic islands and 8 genomic islets, marking the majority of the accessory genome that covers ~ 12% of the total genome. Based on intra-strain comparisons, we are able to predict the pathogenic potential of this environmental isolate. It shares a substantial amount of genomic information with the highly virulent PSE9 and LESB58 strains. For both of these, the increased virulence has been directly linked to their accessory genome before. Hence, the integrated use of previously published data can help to minimize expensive and time consuming wetlab work to determine the pathogenetic potential.

Computation in bacterial communities

Bacteria across many scales are involved in a dynamic process of information exchange to coordinate activity and community structure within large and diverse populations. The molecular components bacteria use to communicate have been discovered and characterized, and recent efforts have begun to understand the potential for bacterial signal exchange to gather information from the environment and coordinate collective behaviors. Such computations made by bacteria to coordinate the action of a population of cells in response to information gathered by a multitude of inputs is a form of collective intelligence. These computations must be robust to fluctuations in both biological, chemical, and physical parameters as well as to operate with energetic efficiency. Given these constraints, what are the limits of computation by bacterial populations and what strategies have evolved to ensure bacterial communities efficiently work together? Here the current understanding of information exchange and collective decision making that occur in microbial populations will be reviewed. Looking toward the future, we consider how a deeper understanding of bacterial computation will inform future direction in microbiology, biotechnology, and biophysics.

One gene, multiple ecological strategies: A biofilm regulator is a capacitor for sustainable diversity

Many organisms, including bacteria, live in fluctuating environments that require attachment and dispersal. These lifestyle decisions require processing of multiple external signals by several genetic pathways, but how they are integrated is largely unknown. We conducted multiple evolution experiments totaling >20,000 generations with Burkholderia cenocepacia populations grown in a model of the biofilm life cycle and identified parallel mutations in one gene, rpfR, that is a conserved central regulator. Because RpfR has multiple sensor and catalytic domains, different mutations can produce different ecological strategies that can coexist and even increase net growth. This study demonstrates that a single gene may coordinate complex life histories in biofilm-dwelling bacteria and that selection in defined environments can reshape niche breadth by single mutations.

Many bacteria cycle between sessile and motile forms in which they must sense and respond to internal and external signals to coordinate appropriate physiology. Maintaining fitness requires genetic networks that have been honed in variable environments to integrate these signals. The identity of the major regulators and how their control mechanisms evolved remain largely unknown in most organisms. During four different evolution experiments with the opportunist betaproteobacterium Burkholderia cenocepacia in a biofilm model, mutations were most frequently selected in the conserved gene rpfR. RpfR uniquely integrates two major signaling systems—quorum sensing and the motile–sessile switch mediated by cyclic-di-GMP—by two domains that sense, respond to, and control the synthesis of the autoinducer cis-2-dodecenoic acid (BDSF). The BDSF response in turn regulates the activity of diguanylate cyclase and phosphodiesterase domains acting on cyclic-di-GMP. Parallel adaptive substitutions evolved in each of these domains to produce unique life history strategies by regulating cyclic-di-GMP levels, global transcriptional responses, biofilm production, and polysaccharide composition. These phenotypes translated into distinct ecology and biofilm structures that enabled mutants to coexist and produce more biomass than expected from their constituents grown alone. This study shows that when bacterial populations are selected in environments challenging the limits of their plasticity, the evolved mutations not only alter genes at the nexus of signaling networks but also reveal the scope of their regulatory functions.

Application of artificial intelligence to the in silico assessment of antimicrobial resistance and risks to human and animal health presented by priority enteric bacterial pathogens

Each year, approximately one in eight Canadians are affected by foodborne illness, either through outbreaks or sporadic illness, with animals being the major reservoir for the pathogens. Whole genome sequence analyses are now routinely implemented by public and animal health laboratories to define epidemiological disease clusters and to identify potential sources of infection. Similarly, a number of bioinformatics tools can be used to identify virulence and antimicrobial resistance (AMR) determinants in the genomes of pathogenic strains. Many important clinical and phenotypic characteristics of these pathogens can now be predicted using machine learning algorithms applied to whole genome sequence data. In this overview, we compare the ability of support vector machines, gradient-boosted decision trees and artificial neural networks to predict the levels of AMR within Salmonella enterica and extended-spectrum β-lactamase (ESBL) producing Escherichia coli. We show that minimum inhibitory concentrations (MIC) for each of 13 antimicrobials for S. enterica strains can be accurately determined, and that ESBL-producing E. coli strains can be accurately classified as susceptible, intermediate or resistant for each of seven antimicrobials. In addition to AMR and bacterial populations of greatest risk to human health, artificial intelligence algorithms hold promise as tools to predict other clinically and epidemiologically important phenotypes of enteric pathogens.

Analysis of two Mexican Pectobacterium brasiliense strains reveals an inverted relationship between c-di-GMP levels with exopolysaccharide production and swarming motility

Pectobacterium is a diverse genus of phytopathogenic species from soil and water that cause infection either to restricted or multiple plant hosts. Phylogenetic analysis and metabolic fingerprinting of large numbers of genomes have expanded classification of Pectobacterium members. Pectobacterium brasiliense sp. nov has been elevated to the species level having detached from P. carotovorum. Here we present two P. brasiliense strains BF20 and BF45 isolated in Mexico from Opuntia and tobacco, respectively, which cluster into two different groups in whole genome comparisons with other Pectobacterium. We found that BF20 and BF45 strains are phenotypically different as BF45 showed more severe and rapid symptoms in comparison to BF20 in the host models celery and broccoli. Both strains produced similar levels of the main autoinducers, but BF45 shows an additional low abundant autoinducer compared to strain BF20. The two strains had different levels of c-di-GMP, which regulates the transition from motile to sessile lifestyle. In contrast to BF45, BF20 had the highest levels of c-di-GMP, was more motile (swarming), non-flocculant and less proficient in biofilm formation and exopolysaccharide production. Genomic comparisons revealed that differences in c-di-GMP accumulation and perhaps the associated phenotypes might be due to unique c-di-GMP metabolic genes in these two strains. Our results improve our understanding of the associations between phenotype and genotype and how this has shaped the physiology of Pectobacterium strains.

Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection

Pseudomonas aeruginosa, a main cause of human infection, can gain resistance to the antibiotic aztreonam through a mutation in NalD, a transcriptional repressor of cellular efflux. Here we combine computational analysis of clinical isolates, transcriptomics, metabolic modeling and experimental validation to find a strong association between NalD mutations and resistance to aztreonam-as well as resistance to other antibiotics-across P. aeruginosa isolated from different patients. A detailed analysis of one patient's timeline shows how this mutation can emerge in vivo and drive rapid evolution of resistance while the patient received cancer treatment, a bone marrow transplantation, and antibiotics up to the point of causing the patient's death. Transcriptomics analysis confirmed the primary mechanism of NalD action-a loss-of-function mutation that caused constitutive overexpression of the MexAB-OprM efflux system-which lead to aztreonam resistance but, surprisingly, had no fitness cost in the absence of the antibiotic. We constrained a genome-scale metabolic model using the transcriptomics data to investigate changes beyond the primary mechanism of resistance, including adaptations in major metabolic pathways and membrane transport concurrent with aztreonam resistance, which may explain the lack of a fitness cost. We propose that metabolic adaptations may allow resistance mutations to endure in the absence of antibiotics and could be targeted by future therapies against antibiotic resistant pathogens.

The Ultimate Guide to Bacterial Swarming: An Experimental Model to Study the Evolution of Cooperative Behavior

Cooperation has fascinated biologists since Darwin. How did cooperative behaviors evolve despite the fitness cost to the cooperator? Bacteria have cooperative behaviors that make excellent models to take on this age-old problem from both proximate (molecular) and ultimate (evolutionary) angles. We delve into Pseudomonas aeruginosa swarming, a phenomenon where billions of bacteria move cooperatively across distances of centimeters in a matter of a few hours. Experiments with swarming have unveiled a strategy called metabolic prudence that stabilizes cooperation, have showed the importance of spatial structure, and have revealed a regulatory network that integrates environmental stimuli and direct cooperative behavior, similar to a machine learning algorithm. The study of swarming elucidates more than proximate mechanisms: It exposes ultimate mechanisms valid to all scales, from cells in cancerous tumors to animals in large communities.

Evolution at the Edge of Expanding Populations

Predicting the evolution of expanding populations is critical to controlling biological threats such as invasive species and cancer metastasis. Expansion is primarily driven by reproduction and dispersal, but nature abounds with examples of evolution where organisms pay a reproductive cost to disperse faster. When does selection favor this "survival of the fastest"? We searched for a simple rule, motivated by evolution experiments where swarming bacteria evolved into a hyperswarmer mutant that disperses ∼100% faster but pays a growth cost of ∼10% to make many copies of its flagellum. We analyzed a two-species model based on the Fisher equation to explain this observation: the population expansion rate (v) results from an interplay of growth (r) and dispersal (D) and is independent of the carrying capacity: v = 2 ( rD ) 1 / 2 . A mutant can take over the edge only if its expansion rate (v2) exceeds the expansion rate of the established species (v1); this simple condition ( v 2 > v 1 ) determines the maximum cost in slower growth that a faster mutant can pay and still be able to take over. Numerical simulations and time-course experiments where we tracked evolution by imaging bacteria suggest that our findings are general: less favorable conditions delay but do not entirely prevent the success of the fastest. Thus, the expansion rate defines a traveling wave fitness, which could be combined with trade-offs to predict evolution of expanding populations.

Causes and Biophysical Consequences of Cellulose Production by Pseudomonas fluorescens SBW25 at the Air-Liquid Interface

This work reveals a hitherto unrecognized behavior that manifests at the air-liquid interface that depends on production of cellulose and hints at undiscovered dimensions to bacterial life at surfaces. Additionally, the study links activation of known diguanylate cyclase-encoding pathways to cellulose expression and to signals encountered at the meniscus. Further significance stems from recognition of the consequences of fluid instabilities arising from surface production of cellulose for transport of water-soluble products over large distances.

Cellulose-overproducing wrinkly spreader mutants of Pseudomonas fluorescens SBW25 have been the focus of much investigation, but conditions promoting the production of cellulose in ancestral strain SBW25 and its effects and consequences have escaped in-depth investigation through lack of an in vitro phenotype. Here, using a custom-built device, we reveal that in static broth microcosms, ancestral SBW25 encounters environmental signals at the air-liquid interface that activate, via three diguanylate cyclase-encoding pathways (Wsp, Aws, and Mws), production of cellulose. Secretion of the polymer at the meniscus leads to modification of the environment and growth of numerous microcolonies that extend from the surface. Accumulation of cellulose and associated microbial growth leads to Rayleigh-Taylor instability resulting in bioconvection and rapid transport of water-soluble products over tens of millimeters. Drawing upon data, we built a mathematical model that recapitulates experimental results and captures the interactions between biological, chemical and physical processes.

IMPORTANCE This work reveals a hitherto unrecognized behavior that manifests at the air-liquid interface that depends on production of cellulose and hints at undiscovered dimensions to bacterial life at surfaces. Additionally, the study links activation of known diguanylate cyclase-encoding pathways to cellulose expression and to signals encountered at the meniscus. Further significance stems from recognition of the consequences of fluid instabilities arising from surface production of cellulose for transport of water-soluble products over large distances.

AmrZ Regulates Swarming Motility Through Cyclic di-GMP-Dependent Motility Inhibition and Controlling Pel Polysaccharide Production in Pseudomonas aeruginosa PA14

Swarming is a surface-associated motile behavior that plays an important role in the rapid spread, colonization, and subsequent establishment of bacterial communities. In Pseudomonas aeruginosa, swarming is dependent upon a functional flagella and aided by the production of biosurfactants. AmrZ, a conserved transcription factor across pseudomonads, has been shown to be a global regulator of multiple genes important for virulence and ecological fitness. In this study, we expand this concept of global control to swarming motility by showing that deletion of amrZ results in a severe defect in swarming, while multicopy expression of this gene stimulates swarming of P. aeruginosa. Mechanistic studies showed that the swarming defect of an amrZ mutant does not involve changes of biosurfactant production but is associated with flagellar malfunction. The ∆amrZ mutant exhibits increased levels of the second messenger cyclic di-GMP (c-di-GMP) compared to the wild-type strain, under swarming conditions. We found that the diguanylate cyclase GcbA was the main contributor to the increased accumulation of c-di-GMP observed in the ∆amrZ mutant and was a strong inhibitor of flagellar-dependent motility. Our results revealed that the GcbA-dependent inhibition of motility required the presence of two c-di-GMP receptors containing a PilZ domain: FlgZ and PA14_56180. Furthermore, the ∆amrZ mutant exhibits enhanced production of Pel polysaccharide. Epistasis analysis revealed that GcbA and the Pel polysaccharide act independently to limit swarming in ΔamrZ. Our results support a role for AmrZ in controlling swarming motility, yet another social behavior besides biofilm formation that is crucial for the ability of P. aeruginosa to colonize a variety of surfaces. The central role of AmrZ in controlling these behaviors makes it a good target for the development of treatments directed to combat P. aeruginosa infections.

Microbial life cycles link global modularity in regulation to mosaic evolution

Microbes are exposed to changing environments, to which they can respond by adopting various lifestyles such as swimming, colony formation or dormancy. These lifestyles are often studied in isolation, thereby giving a fragmented view of the life cycle as a whole. Here, we study lifestyles in the context of this whole. We first use machine learning to reconstruct the expression changes underlying life cycle progression in the bacterium Bacillus subtilis, based on hundreds of previously acquired expression profiles. This yields a timeline that reveals the modular organization of the life cycle. By analysing over 380 Bacillales genomes, we then show that life cycle modularity gives rise to mosaic evolution in which life stages such as motility and sporulation are conserved and lost as discrete units. We postulate that this mosaic conservation pattern results from habitat changes that make these life stages obsolete or detrimental. Indeed, when evolving eight distinct Bacillales strains and species under laboratory conditions that favour colony growth, we observe rapid and parallel losses of the sporulation life stage across species, induced by mutations that affect the same global regulator. We conclude that a life cycle perspective is pivotal to understanding the causes and consequences of modularity in both regulation and evolution.

The State of the Union Is Strong: a Review of ASM's 6th Conference on Cell-Cell Communication in Bacteria

The 6th American Society for Microbiology Conference on Cell-Cell Communication in Bacteria convened from 16 to 19 October 2017 in Athens, GA. In this minireview, we highlight some of the research presented at that meeting that addresses central questions emerging in the field, including the following questions. How are cell-cell communication circuits designed to generate responses? Where are bacteria communicating? Finally, why are bacteria engaging in such behaviors?

A Multimodal Strategy Used by a Large c-di-GMP Network

The Pseudomonas fluorescens genome encodes more than 50 proteins predicted to be involved in c-di-GMP signaling. Here, we demonstrated that, tested across 188 nutrients, these enzymes and effectors appeared capable of impacting biofilm formation. Transcriptional analysis of network members across ∼50 nutrient conditions indicates that altered gene expression can explain a subset of but not all biofilm formation responses to the nutrients. Additional organization of the network is likely achieved through physical interaction, as determined via probing ∼2,000 interactions by bacterial two-hybrid assays. Our analysis revealed a multimodal regulatory strategy using combinations of ligand-mediated signals, protein-protein interaction, and/or transcriptional regulation to fine-tune c-di-GMP-mediated responses. These results create a profile of a large c-di-GMP network that is used to make important cellular decisions, opening the door to future model building and the ability to engineer this complex circuitry in other bacteria.IMPORTANCE Cyclic diguanylate (c-di-GMP) is a key signaling molecule regulating bacterial biofilm formation, and many microbes have up to dozens of proteins that make, break, or bind this dinucleotide. A major open issue in the field is how signaling specificity is conferred in the unpartitioned space of a bacterial cell. Here, we took a systems approach, using mutational analysis, transcriptional studies, and bacterial two-hybrid analysis to interrogate this network. We found that a majority of enzymes are capable of impacting biofilm formation in a context-dependent manner, and we revealed examples of two or more modes of regulation (i.e., transcriptional control with protein-protein interaction) being utilized to generate an observable impact on biofilm formation.

Multiple Environmental Factors Influence the Importance of the Phosphodiesterase DipA upon Pseudomonas aeruginosa Swarming

Pseudomonas aeruginosa exhibits flagellum-mediated swimming in liquid and swarming on hydrated surfaces under diverse nutrient conditions. Prior studies have implicated a phosphodiesterase, DipA, in regulating these flagellum-mediated motilities, but collectively, the necessity for DipA was unclear. In this study, we find that the medium composition conditionally constrains the influence of DipA on flagellar motility. We show that DipA exhibits more influence on minimal medium supplemented with glutamate or glucose, where flagellar motility was negated for the dipA mutant. Conversely, a dipA-deficient mutant exhibits flagellar motility when growing with LB Lennox broth and minimal medium supplemented with Casamino Acids. Swarming under these rich medium conditions occurs under elevated levels of c-di-GMP. We also demonstrate that the influence of DipA upon swimming often differs from that upon swarming, and we conclude that a direct comparison of the motility phenotypes is generally valid only when characterizing motility assay results from the same medium composition. Our results are consistent with the explanation that DipA is one of several phosphodiesterases responding to the nutrient environment sensed by P. aeruginosa On minimal medium with glutamate or glucose, DipA is dominant; however, on rich medium, the necessity of DipA is fully negated.IMPORTANCE Motile and ubiquitous bacteria such as Pseudomonas aeruginosa can quickly colonize surfaces and form biofilms in numerous environments such as water distribution systems, soil, and the human lung. To effectively disrupt bacterial colonization, it is imperative to understand how bacteria regulate motility in these different growth environments. Here, we show that the phosphodiesterase DipA is not required for flagellar motility under all nutrient conditions. Thus, the maintenance of intracellular c-di-GMP levels to promote flagellar motility or biofilm development must be conditionally regulated by differing phosphodiesterases in variation with select nutrient cues.