Genotypic variations and interspecific interactions modify gene expression and biofilm formation of Xanthomonas retroflexus

Multispecies biofilms are important models for studying the evolution of microbial interactions. Co-cultivation of Xanthomonas retroflexus (XR) and Paenibacillus amylolyticus (PA) systemically leads to the appearance of an XR wrinkled mutant (XRW), increasing biofilm production. The nature of this new interaction and the role of each partner remain unclear. We tested the involvement of secreted molecular cues in this interaction by exposing XR and XRW to PA or its supernatant and analysing the response using RNA-seq, colony-forming unit (CFU) estimates, biofilm quantification, and microscopy. Compared to wild type, the mutations in XRW altered its gene expression and increased its CFU number. These changes matched the reported effects for one of the mutated genes: a response regulator part of a two-component system involved in environmental sensing. When XRW was co-cultured with PA or its supernatant, the mutations effects on XRW gene expression were masked, except for genes involved in sedentary lifestyle, being consistent with the higher biofilm production. It appears that the higher biofilm production was the result of the interaction between the genetic context (mutations) and the biotic environment (PA signals). Regulatory genes involved in environmental sensing need to be considered to shed further light on microbial interactions.

Inferring microbial interactions with their environment from genomic and metagenomic data

Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because these interactions depend on the available environmental metabolites, we refer to the networks that we infer as metabolically contextualized, and so name our tool MetConSIN: Metabolically Contextualized Species Interaction Networks.

Anti-CRISPR Discovery: Using Magnets to Find Needles in Haystacks

CRISPR-Cas immune systems in bacteria and archaea protect against viral infection, which has spurred viruses to develop dedicated inhibitors of these systems called anti-CRISPRs (Acrs). Like most host-virus arms races, many diverse examples of these immune and counter-immune proteins are encoded by the genomes of bacteria, archaea, and their viruses. For the case of Acrs, it is almost certain that just a small minority of nature's true diversity has been described. In this review, I discuss the various approaches used to identify these Acrs and speculate on the future for Acr discovery. Because Acrs can determine infection outcomes in nature and regulate CRISPR-Cas activities in applied settings, they have a dual importance to both host-virus conflicts and emerging biotechnologies. Thus, revealing the largely hidden world of Acrs should provide important lessons in microbiology that have the potential to ripple far beyond the field.

Multi-kingdom microbiota analyses identify bacterial-fungal interactions and biomarkers of colorectal cancer across cohorts

Despite recent progress in our understanding of the association between the gut microbiome and colorectal cancer (CRC), multi-kingdom gut microbiome dysbiosis in CRC across cohorts is unexplored. We investigated four-kingdom microbiota alterations using CRC metagenomic datasets of 1,368 samples from 8 distinct geographical cohorts. Integrated analysis identified 20 archaeal, 27 bacterial, 20 fungal and 21 viral species for each single-kingdom diagnostic model. However, our data revealed superior diagnostic accuracy for models constructed with multi-kingdom markers, in particular the addition of fungal species. Specifically, 16 multi-kingdom markers including 11 bacterial, 4 fungal and 1 archaeal feature, achieved good performance in diagnosing patients with CRC (area under the receiver operating characteristic curve (AUROC) = 0.83) and maintained accuracy across 3 independent cohorts. Coabundance analysis of the ecological network revealed associations between bacterial and fungal species, such as Talaromyces islandicus and Clostridium saccharobutylicum. Using metagenome shotgun sequencing data, the predictive power of the microbial functional potential was explored and elevated D-amino acid metabolism and butanoate metabolism were observed in CRC. Interestingly, the diagnostic model based on functional EggNOG genes achieved high accuracy (AUROC = 0.86). Collectively, our findings uncovered CRC-associated microbiota common across cohorts and demonstrate the applicability of multi-kingdom and functional markers as CRC diagnostic tools and, potentially, as therapeutic targets for the treatment of CRC.

The evolution of mechanisms to produce phenotypic heterogeneity in microorganisms

In bacteria and other microorganisms, the cells within a population often show extreme phenotypic variation. Different species use different mechanisms to determine how distinct phenotypes are allocated between individuals, including coordinated, random, and genetic determination. However, it is not clear if this diversity in mechanisms is adaptive-arising because different mechanisms are favoured in different environments-or is merely the result of non-adaptive artifacts of evolution. We use theoretical models to analyse the relative advantages of the two dominant mechanisms to divide labour between reproductives and helpers in microorganisms. We show that coordinated specialisation is more likely to evolve over random specialisation in well-mixed groups when: (i) social groups are small; (ii) helping is more "essential"; and (iii) there is a low metabolic cost to coordination. We find analogous results when we allow for spatial structure with a more detailed model of cellular filaments. More generally, this work shows how diversity in the mechanisms to produce phenotypic heterogeneity could have arisen as adaptations to different environments.

Whole-Genome Sequencing of Corallococcus sp. Strain EGB Reveals the Genetic Determinants Linking Taxonomy and Predatory Behavior

Corallococcus sp. strain EGB is a Gram-negative myxobacteria isolated from saline soil, and has considerable potential for the biocontrol of phytopathogenic fungi. However, the detailed mechanisms related to development and predatory behavior are unclear. To obtain a comprehensive overview of genetic features, the genome of strain EGB was sequenced, annotated, and compared with 10 other Corallococcus species. The strain EGB genome was assembled as a single circular chromosome of 9.4 Mb with 7916 coding genes. Phylogenomics analysis showed that strain EGB was most closely related to Corallococcus interemptor AB047A, and it was inferred to be a novel species within the Corallococcus genus. Comparative genomic analysis revealed that the pan-genome of Corallococcus genus was large and open. Only a small proportion of genes were specific to strain EGB, and most of them were annotated as hypothetical proteins. Subsequent analyses showed that strain EGB produced abundant extracellular enzymes such as chitinases and β-(1,3)-glucanases, and proteases to degrade the cell-wall components of phytopathogenic fungi. In addition, 35 biosynthetic gene clusters potentially coding for antimicrobial compounds were identified in the strain EGB, and the majority of them were present in the dispensable pan-genome with unexplored metabolites. Other genes related to secretion and regulation were also explored for strain EGB. This study opens new perspectives in the greater understanding of the predatory behavior of strain EGB, and facilitates a potential application in the biocontrol of fungal plant diseases in the future.

A Deep Learning-Based Method for Identification of Bacteriophage-Host Interaction

Multi-drug resistance (MDR) has become one of the greatest threats to human health worldwide, and novel treatment methods of infections caused by MDR bacteria are urgently needed. Phage therapy is a promising alternative to solve this problem, to which the key is correctly matching target pathogenic bacteria with the corresponding therapeutic phage. Deep learning is powerful for mining complex patterns to generate accurate predictions. In this study, we develop PredPHI (Predicting Phage-Host Interactions), a deep learning-based tool capable of predicting the host of phages from sequence data. We collect >3000 phage-host pairs along with their protein sequences from PhagesDB and GenBank databases and extract a set of features. Then we select high-quality negative samples based on the K-Means clustering method and construct a balanced training set. Finally, we employ a deep convolutional neural network to build the predictive model. The results indicate that PredPHI can achieve a predictive performance of 81 percent in terms of the area under the receiver operating characteristic curve on the test set, and the clustering-based method is significantly more robust than that based on randomly selecting negative samples. These results highlight that PredPHI is a useful and accurate tool for identifying phage-host interactions from sequence data.

How does feedback from phage infections influence the evolution of phase variation in Campylobacter?

Campylobacter jejuni (C. jejuni) causes gastroenteritis following the consumption of contaminated poultry meat, resulting in a large health and economic burden worldwide. Phage therapy is a promising technique for eradicating C. jejuni from poultry flocks and chicken carcasses. However, C. jejuni can resist infections by some phages through stochastic, phase-variable ON/OFF switching of the phage receptors mediated by simple sequence repeats (SSR). While selection strength and exposure time influence the evolution of SSR-mediated phase variation (PV), phages offer a more complex evolutionary environment as phage replication depends on having a permissive host organism. Here, we build and explore several continuous culture bacteria-phage computational models, each analysing different phase-variable scenarios calibrated to the experimental SSR rates of C. jejuni loci and replication parameters for the F336 phage. We simulate the evolution of PV rates via the adaptive dynamics framework for varying levels of selective pressures that act on the phage-resistant state. Our results indicate that growth reducing counter-selection on a single PV locus results in the stable maintenance of the phage, while compensatory selection between bacterial states affects the evolutionary stable mutation rates (i.e. very high and very low mutation rates are evolutionarily disadvantageous), whereas, in the absence of either selective pressure the evolution of PV rates results in mutation rates below the basal values. Contrastingly, a biologically-relevant model with two phase-variable loci resulted in phage extinction and locking of the bacteria into a phage-resistant state suggesting that another counter-selective pressure is required, instance, the use of a distinct phage whose receptor is an F336-phage-resistant state. We conclude that a delicate balance between counter-selection and phage-attack can result in both the evolution of phase-variable phage receptors and persistence of PV-receptor-specific phage.

Globally rising rates of antibiotic resistance have renewed interest in phage therapy. Bacteriophages (phages) act on bacteria to select for resistance mechanisms such as loss of phage receptors by phase variation (PV). Phase-variable genes mediate rapid adaption by stochastic switching of gene expression. Campylobacter jejuni is a common commensal of birds but also causes serious gastrointestinal infections in humans. Optimisation of phage therapy against C. jejuni requires an in-depth understanding of how PV has evolved and mediates phage resistance. Here, we use a detailed continuous culture model for nutrient-limited bacteria-phage interactions, with PV rates calibrated to match the experimental observations for C.jejuni and phage F336. Evolution within a model accounting for two phase-variable loci closely matches the experimental results when growth reducing counter-selection is imposed on all phage-resistant states, but, not when restricted to the particular states associated with resistance to immune effectors. Our results emphasize that delicate balancing of selective pressures, imposed by single and multiple distinct phages, are necessary for effective use of phage therapy against C. jejuni.

In Vivo Competitions between Fibrobacter succinogenes, Ruminococcus flavefaciens, and Ruminoccus albus in a Gnotobiotic Sheep Model Revealed by Multi-Omic Analyses

Fibrobacter succinogenes, Ruminococcus albus, and Ruminococcus flavefaciens are the three predominant cellulolytic bacterial species found in the rumen. In vitro studies have shown that these species compete for adherence to, and growth upon, cellulosic biomass. Yet their molecular interactions in vivo have not heretofore been examined. Gnotobiotically raised lambs harboring a 17-h-old immature microbiota devoid of culturable cellulolytic bacteria and methanogens were inoculated first with F. succinogenes S85 and Methanobrevibacter sp. strain 87.7, and 5 months later, the lambs were inoculated with R. albus 8 and R. flavefaciens FD-1. Longitudinal samples were collected and profiled for population dynamics, gene expression, fibrolytic enzyme activity, in sacco fibrolysis, and metabolite profiling. Quantitative PCR, metagenome and metatranscriptome data show that F. succinogenes establishes at high levels initially but is gradually outcompeted following the introduction of the ruminococci. This shift resulted in an increase in carboxymethyl cellulase (CMCase) and xylanase activities but not in greater fibrolysis, suggesting that F. succinogenes and ruminococci deploy different but equally effective means to degrade plant cell walls. Expression profiles showed that F. succinogenes relied upon outer membrane vesicles and a diverse repertoire of CAZymes, while R. albus and R. flavefaciens preferred type IV pili and either CBM37-harboring or cellulosomal carbohydrate-active enzymes (CAZymes), respectively. The changes in cellulolytics also affected the rumen metabolome, including an increase in acetate and butyrate at the expense of propionate. In conclusion, this study provides the first demonstration of in vivo competition between the three predominant cellulolytic bacteria and provides insight on the influence of these ecological interactions on rumen fibrolytic function and metabolomic response.IMPORTANCE Ruminant animals, including cattle and sheep, depend on their rumen microbiota to digest plant biomass and convert it into absorbable energy. Considering that the extent of meat and milk production depends on the efficiency of the microbiota to deconstruct plant cell walls, the functionality of predominant rumen cellulolytic bacteria, Fibrobacter succinogenes, Ruminococcus albus, and Ruminococcus flavefaciens, has been extensively studied in vitro to obtain a better knowledge of how they operate to hydrolyze polysaccharides and ultimately find ways to enhance animal production. This study provides the first evidence of in vivo competitions between F. succinogenes and the two Ruminococcus species. It shows that a simple disequilibrium within the cellulolytic community has repercussions on the rumen metabolome and fermentation end products. This finding will have to be considered in the future when determining strategies aiming at directing rumen fermentations for animal production.

Genome Sequence of the Biocontrol Agent Coniothyrium minitans Conio (IMI 134523)

Coniothyrium minitans (synonym, Paraphaeosphaeria minitans) is a highly specific mycoparasite of the wide host range crop pathogen Sclerotinia sclerotiorum. The capability of C. minitans to destroy the sclerotia of S. sclerotiorum has been well recognized and it is available as a widely used biocontrol product Contans WG. We present the draft genome sequence of C. minitans Conio (IMI 134523), which has previously been used in extensive studies that formed part of a registration package of the commercial product. This work provides a distinctive resource for further research into the molecular basis of mycoparasitism to harness the biocontrol potential of C. minitans.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Roles of bacteriophages, plasmids and CRISPR immunity in microbial community dynamics revealed using time-series integrated meta-omics

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE-host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR-Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid-host and phage-host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant 'Candidatus Microthrix parvicella' population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.

Fungal-bacterial interaction selects for quorum sensing mutants with increased production of natural antifungal compounds

Soil microorganisms coexist and interact showing antagonistic or mutualistic behaviors. Here, we show that an environmental strain of Bacillus subtilis undergoes heritable phenotypic variation upon interaction with the soil fungal pathogen Setophoma terrestris (ST). Metabolomics analysis revealed differential profiles in B. subtilis before (pre-ST) and after (post-ST) interacting with the fungus, which paradoxically involved the absence of lipopeptides surfactin and plipastatin and yet acquisition of antifungal activity in post-ST variants. The profile of volatile compounds showed that 2-heptanone and 2-octanone were the most discriminating metabolites present at higher concentrations in post-ST during the interaction process. Both ketones showed strong antifungal activity, which was lost with the addition of exogenous surfactin. Whole-genome analyses indicate that mutations in ComQPXA quorum-sensing system, constituted the genetic bases of post-ST conversion, which rewired B. subtilis metabolism towards the depletion of surfactins and the production of antifungal compounds during its antagonistic interaction with S. terrestris.

Model-based and phylogenetically adjusted quantification of metabolic interaction between microbial species

Microbial community members exhibit various forms of interactions. Taking advantage of the increasing availability of microbiome data, many computational approaches have been developed to infer bacterial interactions from the co-occurrence of microbes across diverse microbial communities. Additionally, the introduction of genome-scale metabolic models have also enabled the inference of cooperative and competitive metabolic interactions between bacterial species. By nature, phylogenetically similar microbial species are more likely to share common functional profiles or biological pathways due to their genomic similarity. Without properly factoring out the phylogenetic relationship, any estimation of the competition and cooperation between species based on functional/pathway profiles may bias downstream applications. To address these challenges, we developed a novel approach for estimating the competition and complementarity indices for a pair of microbial species, adjusted by their phylogenetic distance. An automated pipeline, PhyloMint, was implemented to construct competition and complementarity indices from genome scale metabolic models derived from microbial genomes. Application of our pipeline to 2,815 human-gut associated bacteria showed high correlation between phylogenetic distance and metabolic competition/cooperation indices among bacteria. Using a discretization approach, we were able to detect pairs of bacterial species with cooperation scores significantly higher than the average pairs of bacterial species with similar phylogenetic distances. A network community analysis of high metabolic cooperation but low competition reveals distinct modules of bacterial interactions. Our results suggest that niche differentiation plays a dominant role in microbial interactions, while habitat filtering also plays a role among certain clades of bacterial species.

Bivariate genome-wide association study of the growth plasticity of Staphylococcus aureus in coculture with Escherichia coli

Phenotypic plasticity is the capacity to change the phenotype in response to different environments without alteration of the genotype. Despite sufficient evidence that microorganisms have a major role in the fitness and sickness of eukaryotes, there has been little research regarding microbial phenotypic plasticity. In this study, 45 strains of Staphylococcus aureus were grown for 12 days in both monoculture and in coculture with the same strain of Escherichia coli to create a competitive environment. Cell abundance was determined by quantitative PCR every 24 h, and growth curves of each S. aureus strain under the two sets of conditions were generated. Combined with whole-genome resequencing data, bivariate genome-wide association study (GWAS) was performed to analyze the growth plasticity of S. aureus in coculture. Finally, 20 significant single-nucleotide polymorphisms (eight annotated, seven unannotated, and five non-coding regions) were obtained, which may affect the competitive growth of S. aureus. This study advances genome-wide bacterial growth plasticity research and demonstrates the potential of bivariate GWAS for bacterial phenotypic plasticity research. KEY POINTS: • Growth plasticity of S. aureus was analyzed by bivariate GWAS. • Twenty significant SNPs may affect the growth plasticity of S. aureus.

Genome sequencing of Rigidoporus microporus provides insights on genes important for wood decay, latex tolerance and interspecific fungal interactions

Fungal plant pathogens remain a serious threat to the sustainable agriculture and forestry, despite the extensive efforts undertaken to control their spread. White root rot disease is threatening rubber tree (Hevea brasiliensis) plantations throughout South and Southeast Asia and Western Africa, causing tree mortality and severe yield losses. Here, we report the complete genome sequence of the basidiomycete fungus Rigidoporus microporus, a causative agent of the disease. Our phylogenetic analysis confirmed the position of R. microporus among the members of Hymenochaetales, an understudied group of basidiomycetes. Our analysis further identified pathogen's genes with a predicted role in the decay of plant cell wall polymers, in the utilization of latex components and in interspecific interactions between the pathogen and other fungi. We also detected putative horizontal gene transfer events in the genome of R. microporus. The reported first genome sequence of a tropical rubber tree pathogen R. microporus should contribute to the better understanding of how the fungus is able to facilitate wood decay and nutrient cycling as well as tolerate latex and utilize resinous extractives.

N-Acyl Homoserine Lactones and Lux Solos Regulate Social Behaviour and Virulence of Pseudomonas syringae pv. actinidiae

The phyllosphere is a complex environment where microbes communicate through signalling molecules in a system, generally known as quorum sensing (QS). One of the most common QS systems in Gram-negative proteobacteria is based on the production of N-acyl homoserine lactones (AHLs) by a LuxI synthase and their perception by a LuxR sensor. Pseudomonas syringae pv. actinidiae (Psa), the aetiological agent of the bacterial canker of kiwifruit, colonises plant phyllosphere before penetrating via wounds and natural openings. Since Psa genome encodes three LuxR solos without a cognate LuxI, this bacterium may perceive diffusible signals, but it cannot produce AHLs, displaying a non-canonical QS system. The elucidation of the mechanisms underlying the perception of environmental cues in the phyllosphere by this pathogen and their influence on the onset of pathogenesis are of crucial importance for a long-lasting and sustainable management of the bacterial canker of kiwifruit. Here, we report the ability of Psa to sense its own population density and the presence of surrounding bacteria. Moreover, we show that Psa can perceive AHLs, indicating that AHL-producing neighbouring bacteria may regulate Psa virulence in the host. Our results suggest that the ecological environment is important in determining Psa fitness and pathogenic potential. This opens new perspectives in the use of more advanced biochemical and microbiological tools for the control of bacterial canker of kiwifruit.

Interactome networks between the human respiratory syncytial virus (HRSV), the human metapneumovirus (ΗMPV), and their host: In silico investigation and comparative functional enrichment analysis

BACKGROUND AND OBJECTIVES

Human respiratory syncytial virus (HRSV) and human metapneumovirus (HMPV) are leading causes of upper and lower respiratory tract infections in non-immunocompetent subjects, yet the mechanisms by which they induce their pathogenicity differ significantly and remain elusive. In this study we aimed at identifying the gene interaction networks between the HRSV, HMPV respiratory pathogens and their host along with the different cell-signaling pathways associated with the above interactomes.

MATERIALS AND METHODS

The Viruses STRING database (http://viruses.string-db.org/) was used for the identification of the host-viruses interaction networks. The two lists of the predicted functional partners were entered in the FunRich tool (http://www.funrich.org) for the construction of the Venn diagram and the comparative Funcional Enrichment Analysis (FEA) with respect to biological pathways. The sets of the common and unique human genes identified in the two networks were also analyzed. The computational predictions regarding the shared human genes in the host-HRSV and the host-HMPV interactomes were further evaluated via the analysis of the GSE111732 dataset. miRNA transcriptomics data were mapped to gene targets using the miRNomics pipeline of the GeneTrail2 database (https://genetrail2.bioinf.uni-sb.de/).

RESULTS

Eleven out of twenty predicted human genes were common in the two interactomes (TLR4, SOCS3, SFXN1, AKT1, SFXN3, LY96, SFXN2, SOCS7, CISH, SOCS6, SOCS1). FEA of these common genes identified the kit receptor and the GH receptor signaling pathways as the most significantly enriched annotations. The remaining nine genes of the host-HRSV and the host-HMPV interaction networks were the IFIH1, DDX58, NCL, IRF3, STAT2, HSPA4, CD209, KLF6, CHKA and the MYD88, SOCS4, SOCS2, SOCS5 AKT2, AKT3, SFXN4, SFXN5 and TLR3 respectively. Distinct cell-signaling pathways were enriched per interactome. The comparative FEA highlighted the association of the host-HRSV functional partners with the negative regulation of RIG-I/MDA5 signaling. The analysis with respect to miRNAs mapping to gene targets of the GSE111732 dataset indicated that nine out of the eleven common host genes are either enriched or depleted in the sample sets (HRSV or HMPV infected) as compared with the reference set (non-infected), although with no significant scores.

CONCLUSIONS

We have identified both shared and unique host genes as members of the HRSV and HMPV interaction networks. The disparate human genes likely contribute to distinct responses in airway epithelial cells.

Molecular Piracy: Redirection of Bacteriophage Capsid Assembly by Mobile Genetic Elements

Horizontal transfer of mobile genetic elements (MGEs) is a key aspect of the evolution of bacterial pathogens. Transduction by bacteriophages is especially important in this process. Bacteriophages—which assemble a machinery for efficient encapsidation and transfer of genetic material—often transfer MGEs and other chromosomal DNA in a more-or-less nonspecific low-frequency process known as generalized transduction. However, some MGEs have evolved highly specific mechanisms to take advantage of bacteriophages for their own propagation and high-frequency transfer while strongly interfering with phage production—“molecular piracy”. These mechanisms include the ability to sense the presence of a phage entering lytic growth, specific recognition and packaging of MGE genomes into phage capsids, and the redirection of the phage assembly pathway to form capsids with a size more appropriate for the size of the MGE. This review focuses on the process of assembly redirection, which has evolved convergently in many different MGEs from across the bacterial universe. The diverse mechanisms that exist suggest that size redirection is an evolutionarily advantageous strategy for many MGEs.

Peer pressure from a Proteus mirabilis self-recognition system controls participation in cooperative swarm motility

Colonies of the opportunistic pathogen Proteus mirabilis can distinguish self from non-self: in swarming colonies of two different strains, one strain excludes the other from the expanding colony edge. Predominant models characterize bacterial kin discrimination as immediate antagonism towards non-kin cells, typically through delivery of toxin effector molecules from one cell into its neighbor. Upon effector delivery, receiving cells must either neutralize it by presenting a cognate anti-toxin as would a clonal sibling, or suffer cell death or irreversible growth inhibition as would a non-kin cell. Here we expand this paradigm to explain the non-lethal Ids self-recognition system, which stops access to a social behavior in P. mirabilis by selectively and transiently inducing non-self cells into a growth-arrested lifestyle incompatible with cooperative swarming. This state is characterized by reduced expression of genes associated with protein synthesis, virulence, and motility, and also causes non-self cells to tolerate previously lethal concentrations of antibiotics. We show that temporary activation of the stringent response is necessary for entry into this state, ultimately resulting in the iterative exclusion of non-self cells as a swarm colony migrates outwards. These data clarify the intricate connection between non-lethal recognition and the lifecycle of P. mirabilis swarm colonies.

A resident of animal intestines, Proteus mirabilis is a major cause of catheter-associated urinary tract infections and can cause recurrent, persistent infections. Swarming, which is a collective behavior that promotes centimeter-scale population migration, is implicated in colonization of bladders and kidneys. A regulatory factor of swarming is kin recognition, which involves the transfer of a self-identity protein from one cell into a physically adjacent neighboring cell. However, how kin recognition regulates swarming was previously unclear. We have now shown a mechanism linking kin recognition, swarm migration, and antibiotics tolerance: cells induce a transient antibiotics-tolerant, persister-like state in adjacent non-identical cells which in turn prevents non-identical cells from continuing to participate in collective swarming. These affected non-identical cells continue to exhibit large-scale gene expression suggesting an active shift into a different expression state. These data provide two key insights for the field. First, kin recognition can be a regulatory mechanism that acts with spatial and temporal precision. Second, induction into an antibiotics-tolerant state, instead of occurring stochastically, can be physically and spatially regulated by neighboring cells. These insights highlight the importance of further developing four-dimensional (time and X-, Y-, Z-axes) model systems for interrogating cell-cell signaling and control in microbial populations.

Understanding policing as a mechanism of cheater control in cooperating bacteria

Policing occurs in insect, animal and human societies, where it evolved as a mechanism maintaining cooperation. Recently, it has been suggested that policing might even be relevant in enforcing cooperation in much simpler organisms such as bacteria. Here, we used individual-based modelling to develop an evolutionary concept for policing in bacteria and identify the conditions under which it can be adaptive. We modelled interactions between cooperators, producing a beneficial public good, cheaters, exploiting the public good without contributing to it, and public good-producing policers that secrete a toxin to selectively target cheaters. We found that toxin-mediated policing is favoured when (a) toxins are potent and durable, (b) toxins are cheap to produce, (c) cell and public good diffusion is intermediate, and (d) toxins diffuse farther than the public good. Although our simulations identify the parameter space where toxin-mediated policing can evolve, we further found that policing decays when the genetic linkage between public good and toxin production breaks. This is because policing is itself a public good, offering protection to toxin-resistant mutants that still produce public goods, yet no longer invest in toxins. Our work thus highlights that not only specific environmental conditions are required for toxin-mediated policing to evolve, but also strong genetic linkage between the expression of public goods, toxins and toxin resistance is essential for this mechanism to remain evolutionarily stable in the long run.

Uncovering and resolving challenges of quantitative modeling in a simplified community of interacting cells

Quantitative modeling is useful for predicting behaviors of a system and for rationally constructing or modifying the system. The predictive power of a model relies on accurate quantification of model parameters. Here, we illustrate challenges in parameter quantification and offer means to overcome these challenges, using a case example in which we quantitatively predict the growth rate of a cooperative community. Specifically, the community consists of two Saccharomyces cerevisiae strains, each engineered to release a metabolite required and consumed by its partner. The initial model, employing parameters measured in batch monocultures with zero or excess metabolite, failed to quantitatively predict experimental results. To resolve the model-experiment discrepancy, we chemically identified the correct exchanged metabolites, but this did not improve model performance. We then remeasured strain phenotypes in chemostats mimicking the metabolite-limited community environments, while mitigating or incorporating effects of rapid evolution. Almost all phenotypes we measured, including death rate, metabolite release rate, and the amount of metabolite consumed per cell birth, varied significantly with the metabolite environment. Once we used parameters measured in a range of community-like chemostat environments, prediction quantitatively agreed with experimental results. In summary, using a simplified community, we uncovered and devised means to resolve modeling challenges that are likely general to living systems.

Isolation of multidrug-resistant Haemophilus influenzae harbouring multiple exogenous genes from a patient diagnosed with acute sinusitis

In paediatric patients, β-lactams and macrolides are widely used to treat acute otitis media and sinusitis, which are often caused by either Streptococcus pneumoniae or Haemophilus influenzae. However, resistant isolates have emerged and are becoming more prevalent. H. influenzae generally acquires antimicrobial resistance by mutation or by expression of β-lactamase. In this study, we isolated H. influenzae from a paediatric patient diagnosed with acute sinusitis. This strain harboured multiple exogenous resistance genes: bla_TEM-1, mef(A) and tet(M). DNA sequencing suggested that both mef(A) and tet(M) had been transferred from S. pneumoniae or another Streptococcus. This typical outpatient had not been exposed to excessive levels of antibiotics and had no underlying diseases, strongly suggesting that this type of resistant isolate could become more prevalent.

Pleiotropy, cooperation, and the social evolution of genetic architecture

Pleiotropy has been suggested as a novel mechanism for stabilising cooperation in bacteria and other microbes. The hypothesis is that linking cooperation with a trait that provides a personal (private) benefit can outweigh the cost of cooperation in situations when cooperation would not be favoured by mechanisms such as kin selection. We analysed the theoretical plausibility of this hypothesis, with analytical models and individual-based simulations. We found that (1) pleiotropy does not stabilise cooperation, unless the cooperative and private traits are linked via a genetic architecture that cannot evolve (mutational constraint); (2) if the genetic architecture is constrained in this way, then pleiotropy favours any type of trait and not especially cooperation; (3) if the genetic architecture can evolve, then pleiotropy does not favour cooperation; and (4) there are several alternative explanations for why traits may be linked, and causality can even be predicted in the opposite direction, with cooperation favouring pleiotropy. Our results suggest that pleiotropy could only explain cooperation under restrictive conditions and instead show how social evolution can shape the genetic architecture.

Changes in the genetic requirements for microbial interactions with increasing community complexity

Microbial community structure and function rely on complex interactions whose underlying molecular mechanisms are poorly understood. To investigate these interactions in a simple microbiome, we introduced E. coli into an experimental community based on a cheese rind and identified the differences in E. coli's genetic requirements for growth in interactive and non-interactive contexts using Random Barcode Transposon Sequencing (RB-TnSeq) and RNASeq. Genetic requirements varied among pairwise growth conditions and between pairwise and community conditions. Our analysis points to mechanisms by which growth conditions change as a result of increasing community complexity and suggests that growth within a community relies on a combination of pairwise and higher-order interactions. Our work provides a framework for using the model organism E. coli as a readout to investigate microbial interactions regardless of the genetic tractability of members of the studied ecosystem.

Plant⁻Microbe Interaction 2017-The Good, the Bad and the Diverse

Of the many ways that plants interact with microbes, three aspects are highlighted in this issue: interactions where the plant benefits from the microbes, interactions where the plant suffers, and interactions where the plant serves as habitat for microbial communities. In this editorial, the fourteen articles published in the Special Issue Plant–Microbe Interaction 2017 are summarized and discussed as part of the global picture of the current understanding of plant-microbe interactions.

Geosmithia-Ophiostoma: a New Fungus-Fungus Association

In Europe as in North America, elms are devastated by Dutch elm disease (DED), caused by the alien ascomycete Ophiostoma novo-ulmi. Pathogen dispersal and transmission are ensured by local species of bark beetles, which established a novel association with the fungus. Elm bark beetles also transport the Geosmithia fungi genus that is found in scolytids' galleries colonized by O. novo-ulmi. Widespread horizontal gene transfer between O. novo-ulmi and Geosmithia was recently observed. In order to define the relation between these two fungi in the DED pathosystem, O. novo-ulmi and Geosmithia species from elm, including a GFP-tagged strain, were grown in dual culture and mycelial interactions were observed by light and fluorescence microscopy. Growth and sporulation of O. novo-ulmi in the absence or presence of Geosmithia were compared. The impact of Geosmithia on DED severity was tested in vivo by co-inoculating Geosmithia and O. novo-ulmi in elms. A close and stable relation was observed between the two fungi, which may be classified as mycoparasitism by Geosmithia on O. novo-ulmi. These results prove the existence of a new component in the complex of organisms involved in DED, which might be capable of reducing the disease impact.

Proteus vulgaris and Proteus mirabilis Decrease Candida albicans Biofilm Formation by Suppressing Morphological Transition to Its Hyphal Form

PURPOSE

Candida albicans (C. albicans) and Proteus species are causative agents in a variety of opportunistic nosocomial infections, and their ability to form biofilms is known to be a virulence factor. In this study, the influence of co-cultivation with Proteus vulgaris (P. vulgaris) and Proteus mirabilis (P. mirabilis) on C. albicans biofilm formation and its underlying mechanisms were examined.

MATERIALS AND METHODS

XTT reduction assays were adopted to measure biofilm formation, and viable colony counts were performed to quantify yeast growth. Real-time reverse transcriptase polymerase chain reaction was used to evaluate the expression of yeast-specific genes (rhd1 and rbe1), filament formation inhibiting genes (tup1 and nrg1), and hyphae-related genes (als3, ece1, hwp1, and sap5).

RESULTS

Candida biofilm formation was markedly inhibited by treatment with either living or heat-killed P. vulgaris and P. mirabilis. Proteus-cultured supernatant also inhibited Candida biofilm formation. Likewise, treatment with live P. vulgaris or P. mirabilis or with Proteus-cultured supernatant decreased expression of hyphae-related C. albicans genes, while the expression of yeast-specific genes and the filament formation inhibiting genes of C. albicans were increased. Heat-killed P. vulgaris and P. mirabilis treatment, however, did not affect the expression of C. albicans morphology-related genes.

CONCLUSION

These results suggest that secretory products from P. vulgaris and P. mirabilis regulate the expression of genes related to morphologic changes in C. albicans such that transition from the yeast form to the hyphal form can be inhibited.

Two dynamic regimes in the human gut microbiome

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)—a multivariate method developed for econometrics—to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes.

Dynamics reveal crucial information about how a system functions. In this study, we develop an approach for disentangling two types of dynamics within the human gut microbiome. We find that autoregressive dynamics involve recovery from large deviations in community structure. These recovery processes appear to involve the blooming of facultative anaerobes and aerotolerant taxa, likely due to transient shifts in redox potential, followed by re-establishment of obligate anaerobes. Non-autoregressive dynamics carry a strong phylogenetic signal, wherein highly related taxa fluctuate coherently. These non-autoregressive dynamics appear to be driven by external, non-autoregressive variables like diet. We find that most of the community variance is driven by day-to-day fluctuations in the environment, with occasional autoregressive dynamics as the system recovers from larger shocks. Despite frequently observed disruptions to the gut ecosystem, there exists a returning force that continually pushes the gut microbiome back towards its steady-state configuration.

Genome composition and phylogeny of microbes predict their co-occurrence in the environment

The genomic information of microbes is a major determinant of their phenotypic properties, yet it is largely unknown to what extent ecological associations between different species can be explained by their genome composition. To bridge this gap, this study introduces two new genome-wide pairwise measures of microbe-microbe interaction. The first (genome content similarity index) quantifies similarity in genome composition between two microbes, while the second (microbe-microbe functional association index) summarizes the topology of a protein functional association network built for a given pair of microbes and quantifies the fraction of network edges crossing organismal boundaries. These new indices are then used to predict co-occurrence between reference genomes from two 16S-based ecological datasets, accounting for phylogenetic relatedness of the taxa. Phylogenetic relatedness was found to be a strong predictor of ecological associations between microbes which explains about 10% of variance in co-occurrence data, but genome composition was found to be a strong predictor as well, it explains up to 4% the variance in co-occurrence when all genomic-based indices are used in combination, even after accounting for evolutionary relationships between the species. On their own, the metrics proposed here explain a larger proportion of variance than previously reported more complex methods that rely on metabolic network comparisons. In summary, results of this study indicate that microbial genomes do indeed contain detectable signal of organismal ecology, and the methods described in the paper can be used to improve mechanistic understanding of microbe-microbe interactions.

It is still unknown to what extent ecological associations between microbes, as measured by co-occurrence of different taxa in 16S rRNA surveys, can be explained, or predicted, using composition and structure of microbial genomes alone. Here I introduce two new genome-wide, pairwise indices for quantifying the propensity of microbial species to interact with each other. The first measure quantifies similarity in genome composition between two microbes. The second measure summarizes the topology of a protein functional association network built for a given pair of microbes and quantifies the fraction of network edges crossing organismal boundaries. I then study the ability of two newly proposed and two previously reported indices to explain variation in microbial co-occurrence. All four measures are significantly correlated with co-occurrence of microbes even when accounting for evolutionary relationships between the species. One of the newly developed indices outperforms previously proposed ones and explains up to 3.5% of the variance in co-occurrence. In summary, the indices described here are able to detect ecological associations between species using only their genomic information; however, additional methods are needed to provide more reliable genomic tools for microbial ecology.

Comparative Genomics of cpn60-Defined Enterococcus hirae Ecotypes and Relationship of Gene Content Differences to Competitive Fitness

Natural microbial communities undergo selection-driven succession with changes in environmental conditions and available nutrients. In a previous study of the pig faecal Enterococcus community, we demonstrated that cpn60 universal target (UT) sequences could resolve phenotypically and genotypically distinct ecotypes of Enterococcus spp. that emerged over time in the faecal microbiome of growing pigs. In this study, we characterized genomic diversity in the identified Enterococcus hirae ecotypes in order to define further the nature and degree of genome content differences between taxa resolved by cpn60 UT sequences. Genome sequences for six representative isolates (two from each of three ecotypes) were compared. Differences in phosphotransferase systems and amino acid metabolism pathways for glutamine, proline and selenocysteine were observed. Differences in the lac family phosphotransferase system corresponded to lactose utilization phenotypes of the isolates. Competitive fitness of the E. hirae ecotypes was evaluated by in vitro growth competition assays in pig faecal extract medium. Isolates from E. hirae-1 and E. hirae-2 ecotypes were able to out-compete isolates from the E. hirae-3 ecotype, consistent with the relatively low abundance of E. hirae-3 relative to E. hirae-1 and E. hirae-2 previously observed in the pig faecal microbiome, and with observed differences between the ecotypes in gene content related to biosynthetic capacity. Results of this study provide a genomic basis for the definition of ecotypes within E. hirae and confirm the utility of the cpn60 UT sequence for high-resolution profiling of complex microbial communities.

Host-microbe interactions as a driver of acclimation to salinity gradients in brown algal cultures

Like most eukaryotes, brown algae live in association with bacterial communities that frequently have beneficial effects on their development. Ectocarpus is a genus of small filamentous brown algae, which comprises a strain that has recently colonized freshwater, a rare transition in this lineage. We generated an inventory of bacteria in Ectocarpus cultures and examined the effect they have on acclimation to an environmental change, that is, the transition from seawater to freshwater medium. Our results demonstrate that Ectocarpus depends on bacteria for this transition: cultures that have been deprived of their associated microbiome do not survive a transfer to freshwater, but restoring their microflora also restores the capacity to acclimate to this change. Furthermore, the transition between the two culture media strongly affects the bacterial community composition. Examining a range of other closely related algal strains, we observed that the presence of two bacterial operational taxonomic units correlated significantly with an increase in low salinity tolerance of the algal culture. Despite differences in the community composition, no indications were found for functional differences in the bacterial metagenomes predicted to be associated with algae in the salinities tested, suggesting functional redundancy in the associated bacterial community. Our study provides an example of how microbial communities may impact the acclimation and physiological response of algae to different environments, and thus possibly act as facilitators of speciation. It paves the way for functional examinations of the underlying host-microbe interactions, both in controlled laboratory and natural conditions.

Quasispecies dynamics in hepatitis C liver transplant recipients receiving grafts from hepatitis C virus infected donors

The allocation of liver grafts from hepatitis C virus (HCV)-positive donors in HCV-infected liver transplant (LT) recipients leads to infection with two different viral populations. In a previous study, we examined quasispecies dynamics during reinfection by clonal sequencing, which did not allow an accurate characterization of coexistence and competition events. To overcome this limitation, here we used deep-sequencing analysis of a fragment of the HCV NS5B gene in six HCV-infected LT recipients who received HCV-infected grafts. Successive expansions and contractions of quasispecies complexity were observed, evolving in all cases towards a more homogeneous population. The population that became dominant was the one displaying the highest mutant spectrum complexity. In four patients, coexistence of minority mutants, derived from the donor or the recipient, were detected. In conclusion, our study shows that, during reinfection with a different HCV strain in LT recipients, the viral population with the highest diversity always becomes dominant.

Intraspecies Interaction of Fusarium graminearum Contributes to Reduced Toxin Production and Virulence

Fusarium graminearum is a pathogenic fungus that causes Fusarium head blight in wheat and lowers the yield and quality of grains by contamination with the trichothecene mycotoxin deoxynivalenol. The fungi coexist and interact with several different fusaria as well as other plant pathogenic fungi and bacteria in the field. In Canada, F. graminearum exists as two main trichothecene chemotypes: 3-acetyldeoxynivalenol and 15-acetyldeoxynivalenol. To understand the potential interactions between two isolates of these chemotypes, we conducted coinoculation studies both in culture and in planta. The studies showed that intraspecies interaction reduces trichothecene yield in culture and disease symptoms in wheat. To elucidate the genes involved in the intraspecies interaction, expression profiling was performed on RNA samples isolated from coinoculated cultures, and potential genes were identified by using the genome sequences of the respective isolates.

The lifestyle switch protein Bd0108 of Bdellovibrio bacteriovorus is an intrinsically disordered protein

Bdellovibrio bacteriovorus is a δ-proteobacterium that preys upon Salmonella spp., E. coli, and other Gram-negative bacteria. Bdellovibrio can grow axenically (host-independent, HI, rare and mutation-driven) or subsist via a predatory lifecycle (host-dependent, HD, the usual case). Upon contact with prey, B. bacteriovorus enters the host periplasm from where it slowly drains the host cytosol of nutrients for its own replication. At the core of this mechanism is a retractile pilus, whose architecture is regulated by the protein Bd0108 and its interaction with the neighboring gene product Bd0109. Deletion of bd0108 results in negligible pilus formation, whereas an internal deletion (the one that instigates host-independence) causes mis-regulation of pilus length. These mutations, along with a suite of naturally occurring bd0108 mutant strains, act to control the entry to HI growth. To further study the molecular mechanism of predatory regulation, we focused on the apparent lifecycle switch protein Bd0108. Here we characterize the solution structure and dynamics of Bd0108 using nuclear magnetic resonance (NMR) spectroscopy complemented with additional biophysical methods. We then explore the interaction between Bd0108 and Bd0109 in detail utilizing isothermal titration calorimetry (ITC) and NMR spectroscopy. Together our results demonstrate that Bd0108 is an intrinsically disordered protein (IDP) and that the interaction with Bd0109 is of low affinity. Furthermore, we observe that Bd0108 retains an IDP nature while binding Bd0109. From our data we conclude that Bdellovibrio bacteriovorus utilizes an intrinsically disordered protein to regulate its pilus and control predation signaling.

First principles of Hamiltonian medicine

We introduce the field of Hamiltonian medicine, which centres on the roles of genetic relatedness in human health and disease. Hamiltonian medicine represents the application of basic social-evolution theory, for interactions involving kinship, to core issues in medicine such as pathogens, cancer, optimal growth and mental illness. It encompasses three domains, which involve conflict and cooperation between: (i) microbes or cancer cells, within humans, (ii) genes expressed in humans, (iii) human individuals. A set of six core principles, based on these domains and their interfaces, serves to conceptually organize the field, and contextualize illustrative examples. The primary usefulness of Hamiltonian medicine is that, like Darwinian medicine more generally, it provides novel insights into what data will be productive to collect, to address important clinical and public health problems. Our synthesis of this nascent field is intended predominantly for evolutionary and behavioural biologists who aspire to address questions directly relevant to human health and disease.

Phytopathogenic bacteria phenotype conversion as a result of their lysogenisation by coliphage P1

A set of lysogenic strains of phytopathogenic bacteria Erwinia "horticola" and Erwinia amylovora associated with woody plants was obtained using bacteriophage P1 Cmc1ts100. The phenotype conversion from Cm(S) to Cm(R) was shown to be connected with introducing of authentic prophage DNA of 94.8 kb as a single-copy plasmid into the cells. Prophage state is unstable: P1 plasmid is spontaneously lost with high frequency by the cells. In lysogenic cells the prophage genes of type III restriction-modification complex EcoP1I are actively expressed. The system formed by E. "horticola" 450 and 60 as well as their lysogenic derivatives and specific bacteriophages provides an opportunity to divide the latter into three groups according to the level of restriction in the course of their interaction with the enzyme EcoP1I. The difference in phage responses to the endonuclease presence in a lysogenized host presumably correlates with the number of enzyme recognition sequences and the adsorption sites availability. After the prophage plasmid DNA curing the characteristic value of phage sensitivity of cells is changed. The lysogenic strains obtained in this work allow for the exploration of EcoP1I restriction-modification gene complex interaction with polyvalent phages able to grow not only on E. coli, but also on such phytopathogens as E. "horticola" and E. amylovora.

Bacterial lipopolysaccharide binding enhances virion stability and promotes environmental fitness of an enteric virus

Enteric viruses, including poliovirus and reovirus, encounter a vast microbial community in the mammalian gastrointestinal tract, which has been shown to promote virus replication and pathogenesis. Investigating the underlying mechanisms, we find that poliovirus binds bacterial surface polysaccharides, which enhances virion stability and cell attachment by increasing binding to the viral receptor. Additionally, we identified a poliovirus mutant, VP1-T99K, with reduced lipopolysaccharide (LPS) binding. Although T99K and WT poliovirus cell attachment, replication, and pathogenesis in mice are equivalent, VP1-T99K poliovirus was unstable in feces following peroral inoculation of mice. Consequently, the ratio of mutant virus in feces is reduced following additional cycles of infection in mice. Thus, the mutant virus incurs a fitness cost when environmental stability is a factor. These data suggest that poliovirus binds bacterial surface polysaccharides, enhancing cell attachment and environmental stability, potentially promoting transmission to a new host.

feedback between population and evolutionary dynamics determines the fate of social microbial populations

A new study finds that the evolution of social genes may be coupled with population dynamics, and may dramatically affect ecological resilience, particularly in the face of rapidly deteriorating environments.

The evolutionary spread of cheater strategies can destabilize populations engaging in social cooperative behaviors, thus demonstrating that evolutionary changes can have profound implications for population dynamics. At the same time, the relative fitness of cooperative traits often depends upon population density, thus leading to the potential for bi-directional coupling between population density and the evolution of a cooperative trait. Despite the potential importance of these eco-evolutionary feedback loops in social species, they have not yet been demonstrated experimentally and their ecological implications are poorly understood. Here, we demonstrate the presence of a strong feedback loop between population dynamics and the evolutionary dynamics of a social microbial gene, SUC2, in laboratory yeast populations whose cooperative growth is mediated by the SUC2 gene. We directly visualize eco-evolutionary trajectories of hundreds of populations over 50–100 generations, allowing us to characterize the phase space describing the interplay of evolution and ecology in this system. Small populations collapse despite continual evolution towards increased cooperative allele frequencies; large populations with a sufficient number of cooperators “spiral” to a stable state of coexistence between cooperator and cheater strategies. The presence of cheaters does not significantly affect the equilibrium population density, but it does reduce the resilience of the population as well as its ability to adapt to a rapidly deteriorating environment. Our results demonstrate the potential ecological importance of coupling between evolutionary dynamics and the population dynamics of cooperatively growing organisms, particularly in microbes. Our study suggests that this interaction may need to be considered in order to explain intraspecific variability in cooperative behaviors, and also that this feedback between evolution and ecology can critically affect the demographic fate of those species that rely on cooperation for their survival.

The fact that rapid evolution within a species can cause dramatic ecological changes has only recently begun to be appreciated. In particular, it has often been assumed that population dynamics, controlled by ecological circumstances such as the presence of predators or disease, occur at such different timescales compared with evolutionary dynamics that they are effectively de-coupled. Recent studies, however, have found that evolution can occur over ecological timescales and thus may have important effects on ecological dynamics. Here, we demonstrate the presence of a tight coupling between population dynamics and the evolutionary dynamics of a “social” microbial gene, which allows a laboratory population of budding yeast to cooperatively break down sucrose and grow on the simpler sugars released from it. In such cooperative populations, evolution may favor non-cooperative, or “cheater” individuals that do not contribute to the public good (in this case, the products of sucrose break down), but still use that public good to grow at the expense of the individuals that do cooperate. Our study shows that a population of cooperators that is invaded by cheaters does not collapse as a result of cheater proliferation but can evolve to a viable equilibrium. However, the coexisting population is less resilient to perturbations.

Cooperation and the fate of microbial societies

Microorganisms have been cooperating with each other for billions of years: by sharing resources, communicating with each other, and joining together to form biofilms and other large structures. These cooperative behaviors benefit the colony as a whole; however, they may be costly to the individuals performing them. This raises the question of how such cooperation can arise from natural selection. Mathematical modeling is one important avenue for exploring this question. Evolutionary experiments are another, providing us with an opportunity to see evolutionary dynamics in action and allowing us to test predictions arising from mathematical models. A new study in this issue of PLOS Biology investigates the evolution of a cooperative resource-sharing behavior in yeast. Examining the competition between cooperating and "cheating" strains of yeast, the authors find that, depending on the initial mix of strains, this yeast society either evolves toward a stable coexistence or collapses for lack of cooperation. Using a simple mathematical model, they show how these dynamics arise from eco-evolutionary feedback, where changes in the frequencies of strains are coupled with changes in population size. This study and others illustrate the combined power of modeling and experiment to elucidate the origins of cooperation and other fundamental questions in evolutionary biology.

Comparative transcriptomics reveals different strategies of Trichoderma mycoparasitism

BACKGROUND

Trichoderma is a genus of mycotrophic filamentous fungi (teleomorph Hypocrea) which possess a bright variety of biotrophic and saprotrophic lifestyles. The ability to parasitize and/or kill other fungi (mycoparasitism) is used in plant protection against soil-borne fungal diseases (biological control, or biocontrol). To investigate mechanisms of mycoparasitism, we compared the transcriptional responses of cosmopolitan opportunistic species and powerful biocontrol agents Trichoderma atroviride and T. virens with tropical ecologically restricted species T. reesei during confrontations with a plant pathogenic fungus Rhizoctonia solani.

RESULTS

The three Trichoderma spp. exhibited a strikingly different transcriptomic response already before physical contact with alien hyphae. T. atroviride expressed an array of genes involved in production of secondary metabolites, GH16 ß-glucanases, various proteases and small secreted cysteine rich proteins. T. virens, on the other hand, expressed mainly the genes for biosynthesis of gliotoxin, respective precursors and also glutathione, which is necessary for gliotoxin biosynthesis. In contrast, T. reesei increased the expression of genes encoding cellulases and hemicellulases, and of the genes involved in solute transport. The majority of differentially regulated genes were orthologues present in all three species or both in T. atroviride and T. virens, indicating that the regulation of expression of these genes is different in the three Trichoderma spp. The genes expressed in all three fungi exhibited a nonrandom genomic distribution, indicating a possibility for their regulation via chromatin modification.

CONCLUSION

This genome-wide expression study demonstrates that the initial Trichoderma mycotrophy has differentiated into several alternative ecological strategies ranging from parasitism to predation and saprotrophy. It provides first insights into the mechanisms of interactions between Trichoderma and other fungi that may be exploited for further development of biofungicides.

Phenotypic plasticity stimulated by cooperation fosters pattern diversity of bacterial colonies

Colonies of flagellated bacteria on agar plates are known to take on diverse morphologies. A diffusion-reaction model is proposed for bacterial-colony pattern formation on a surface due to time scale separation between the slow mass migration of bacteria from the point of inoculation, and the fast, but localized, dynamics of bacterial phenotypic plasticity stimulated by public-goods cooperation and phenotypic switching. By considering two switchable phenotypes in the population, the model generates pattern diversity typifying those reported by experimental studies.

Streptococcus mutans out-competes Streptococcus gordonii in vivo

Streptococcus gordonii and Streptococcus mutans avidly colonize teeth. S. gordonii glucosyltransferase (GtfG) and amylase-binding proteins (AbpA/AbpB), and S. mutans glucosyltransferase (GtfB), affect their respective oral colonization abilities. We investigated their interrelationships and caries association in a rat model of human caries, examining the sequence of colonization and non- vs. high-sucrose diets, the latter being associated with aggressive decay in humans and rats. Virulence-characterized wild-types of both species and well-defined mutants of S. gordonii with interrupted abpA and gtfG genes were studied. While both S. gordonii and S. mutans were abundant colonizers of rat's teeth in the presence of either diet, if inoculated singly, S. mutans always out-competed S. gordonii on the teeth, independent of diet, strain of S. mutans, simultaneous or sequential inoculation, or presence/absence of mutations of S. gordonii's abpA and gtfG genes known to negatively or positively affect its colonization and to interact in vitro with S. mutans GtfB. S. mutans out-competed S. gordonii in in vivo plaque biofilm. Caries induction reflected S. mutans or S. gordonii colonization abundance: the former highly cariogenic, the latter not. S. gordonii does not appear to be a good candidate for replacement therapy. These results are consistent with human data.

Understanding microbial cooperation

The field of microbial cooperation has grown enormously over the last decade, leading to improved experimental techniques and a growing awareness of collective behavior in microbes. Unfortunately, many of our theoretical tools and concepts for understanding cooperation fail to take into account the peculiarities of the microbial world, namely strong selection strengths, unique population structure, and non-linear dynamics. Worse yet, common verbal arguments are often far removed from the math involved, leading to confusion and mistakes. Here, we review the general mathematical forms of Price's equation, Hamilton's rule, and multilevel selection as they are applied to microbes and provide some intuition on these otherwise abstract formulas. However, these sometimes overly general equations can lack specificity and predictive power, ultimately forcing us to advocate for more direct modeling techniques.

Cooperative adaptation to establishment of a synthetic bacterial mutualism

To understand how two organisms that have not previously been in contact can establish mutualism, it is first necessary to examine temporal changes in their phenotypes during the establishment of mutualism. Instead of tracing back the history of known, well-established, natural mutualisms, we experimentally simulated the development of mutualism using two genetically-engineered auxotrophic strains of Escherichia coli, which mimic two organisms that have never met before but later establish mutualism. In the development of this synthetic mutualism, one strain, approximately 10 hours after meeting the partner strain, started oversupplying a metabolite essential for the partner's growth, eventually leading to the successive growth of both strains. This cooperative phenotype adaptively appeared only after encountering the partner strain but before the growth of the strain itself. By transcriptome analysis, we found that the cooperative phenotype of the strain was not accompanied by the local activation of the biosynthesis and transport of the oversupplied metabolite but rather by the global activation of anabolic metabolism. This study demonstrates that an organism has the potential to adapt its phenotype after the first encounter with another organism to establish mutualism before its extinction. As diverse organisms inevitably encounter each other in nature, this potential would play an important role in the establishment of a nascent mutualism in nature.

Ralstonia solanacearum ΔPGI-1 strain KZR-5 is affected in growth, response to cold stress and invasion of tomato

The survival and persistence of Ralstonia solanacearum biovar 2 in temperate climates is still poorly understood. To assess whether genomic variants of the organism show adaptation to local conditions, we compared the behaviour of environmental strain KZR-5, which underwent a deletion of the 17.6 kb genomic island PGI-1, with that of environmental strain KZR-1 and potato-derived strains 1609 and 715. PGI-1 harbours two genes of potential ecological relevance, i.e. one encoding a hypothetical protein with a RelA/SpoT domain and one a putative cellobiohydrolase. We thus assessed bacterial fate under conditions of amino acid starvation, during growth, upon incubation at low temperature and invasion of tomato plants. In contrast to the other strains, environmental strain KZR-5 did not grow on media that induce amino acid starvation. In addition, its maximum growth rate at 28°C in rich medium was significantly reduced. On the other hand, long-term survival at 4°C was significantly enhanced as compared to that of strains 1609, 715 and KZR-1. Although strain KZR-5 showed growth rates (at 28°C) in two different media, which were similar to those of strains 1609 and 715, its ability to compete with these strains under these conditions was reduced. In singly inoculated tomato plants, no significant differences in invasiveness were observed among strains KZR-5, KZR-1, 1609 and 715. However, reduced competitiveness of strain KZR-5 was found in experiments on tomato plant colonisation and wilting when using 1:1 or 5:1 mixtures of strains. The potential role of PGI-1 in plant invasion, response to stress and growth in competition at high and moderate temperatures is discussed.

Co-swarming and local collapse: quorum sensing conveys resilience to bacterial communities by localizing cheater mutants in Pseudomonas aeruginosa

Background

Members of swarming bacterial consortia compete for nutrients but also use a co-operation mechanism called quorum sensing (QS) that relies on chemical signals as well as other secreted products (“public goods”) necessary for swarming. Deleting various genes of this machinery leads to cheater mutants impaired in various aspects of swarming cooperation.

Methodology/Principal Findings

Pairwise consortia made of Pseudomonas aeruginosa, its QS mutants as well as B. cepacia cells show that a interspecies consortium can “combine the skills” of its participants so that the strains can cross together barriers that they could not cross alone. In contrast, deleterious mutants are excluded from consortia either by competition or by local population collapse. According to modeling, both scenarios are the consequence of the QS signalling mechanism itself.

Conclusion/Significance

The results indirectly explain why it is an advantage for bacteria to maintain QS systems that can cross-talk among different species, and conversely, why certain QS mutants which can be abundant in isolated niches, cannot spread and hence remain localized.