The idiosyncrasy of spatial structure in bacterial competition

Population Density Affects the Outcome of Competition in Co-cultures of Gardnerella Species Isolated from the Human Vaginal Microbiome

Negative frequency-dependent selection is one possible mechanism for maintenance of rare species in communities, but the selective advantage of rare species may be checked at lower overall population densities where resources are abundant. Gardnerella spp. belonging to cpn60 subgroup D, are detected at low levels in vaginal microbiomes and are nutritional generalists relative to other more abundant Gardnerella spp., making them good candidates for negative frequency-dependent selection. The vaginal microbiome is a dynamic environment, and the resulting changes in density of the microbiota may explain why subgroup D never gains dominance. To test this, we co-cultured subgroup D isolates with isolates from the more common and abundant subgroup C. Deep amplicon sequencing of rpoB was used to determine proportional abundance of each isolate at 0 h and 72 h in 152 co-cultures and to calculate change in proportion. D isolates had a positive change in proportional abundance in most co-cultures regardless of initial proportion. Initial density affected the change in proportion of subgroup D isolates either positively or negatively depending on the particular isolates combined, suggesting that growth rate, population density and other intrinsic features of the isolates influenced the outcome. Our results demonstrate that population density is an important factor influencing the outcome of competition between Gardnerella spp. isolated from the human vaginal microbiome.

Bacterial Behavior in Confined Spaces

In confined spaces, bacteria exhibit unexpected cellular behaviors that are related to the biogeochemical cycle and human health. Types of confined spaces include lipid vesicles, polymer vesicles, emulsion droplets, microfluidic chips, and various laboratory-made chambers. This mini-review summarizes the behaviors of living bacteria in these confined spaces, including (a) growth and proliferation, (b) cell communication, and (c) motion. Future trends and challenges are also discussed in this paper.

Radial Expansion Facilitates the Maintenance of Double Antibiotic Resistances

Most microbes live in spatially confined subpopulations. Under spatial structure conditions, the efficacy of natural selection is often reduced (relative to homogeneous conditions) due to the increased importance of genetic drift and local competition. Additionally, under spatial structure conditions, the fittest genotype may not always be the one with better access to the heterogeneous distribution of nutrients. The effect of radial expansion may be particularly relevant for the elimination of antibiotic resistance mutations, as their dynamics within bacterial populations are strongly dependent on their growth rate. Here, we use Escherichia coli to systematically compare the allele frequency of streptomycin, rifampin, and fluoroquinolone single and double resistance mutants after 24 h of coexistence with a susceptible strain under radial expansion (local competition) and homogeneous (global competition) conditions. We show that there is a significant effect of structure on the maintenance of double resistances which is not observed for single resistances. Radial expansion also facilitates the persistence of double resistances when competing against their single counterparts. Importantly, we found that spatial structure reduces the rate of compensation of the double mutant RpsL^K43T RpoB^H526Y and that a strongly compensatory mutation in homogeneous conditions becomes deleterious under spatial structure conditions. Overall, our results unravel the importance of spatial structure for facilitating the maintenance and accumulation of multiple resistances over time and for determining the identity of compensatory mutations.

Investigating the dynamics of microbial consortia in spatially structured environments

The spatial organization of microbial communities arises from a complex interplay of biotic and abiotic interactions, and is a major determinant of ecosystem functions. Here we design a microfluidic platform to investigate how the spatial arrangement of microbes impacts gene expression and growth. We elucidate key biochemical parameters that dictate the mapping between spatial positioning and gene expression patterns. We show that distance can establish a low-pass filter to periodic inputs and can enhance the fidelity of information processing. Positive and negative feedback can play disparate roles in the synchronization and robustness of a genetic oscillator distributed between two strains to spatial separation. Quantification of growth and metabolite release in an amino-acid auxotroph community demonstrates that the interaction network and stability of the community are highly sensitive to temporal perturbations and spatial arrangements. In sum, our microfluidic platform can quantify spatiotemporal parameters influencing diffusion-mediated interactions in microbial consortia.

Three-Way Interactions in an Artificial Community of Bacterial Strains Directly Isolated From the Environment and Their Effect on the System Population Dynamics

This work is motivated by previous studies that have analyzed the population ecology of a collection of culturable thermoresistant bacteria, isolated from the Churince lagoon in Cuatro Cienegas, Mexico. In particular, it is aimed at testing a hypothesis from a modeling study, which states that antagonistic and sensitive bacteria co-exist thanks to resistant bacteria that protect sensitive ones by forming physical barriers. We selected three different bacterial strains from the referred collection: one antagonistic, one sensitive, and one resistant, and studied the population dynamics of mixed colonies. Our results show that, although the proposed protective mechanism does not work in this case, the resistant strain confers some kind of protection to sensitive bacteria. Further modeling and experimental results suggest that the presence of resistant bacteria indirectly improves the probability that patches of sensitive bacteria grow in a mixed colony. More precisely, our results suggest that by making antagonistic bacteria produce and secrete an antagonistic substance (with the concomitant metabolic cost and growth rate reduction), resistant bacteria increase the likelihood that sensitive bacteria locally outcompete antagonistic ones.

Do Organic Substrates Drive Microbial Community Interactions in Arctic Snow?

The effect of nutrients on microbial interactions, including competition and collaboration, has mainly been studied in laboratories, but their potential application to complex ecosystems is unknown. Here, we examined the effect of changes in organic acids among other parameters on snow microbial communities in situ over 2 months. We compared snow bacterial communities from a low organic acid content period to that from a higher organic acid period. We hypothesized that an increase in organic acids would shift the dominant microbial interaction from collaboration to competition. To evaluate microbial interactions, we built taxonomic co-variance networks from OTUs obtained from 16S rRNA gene sequencing. In addition, we tracked marker genes of microbial cooperation (plasmid backbone genes) and competition (antibiotic resistance genes) across both sampling periods in metagenomes and metatranscriptomes. Our results showed a decrease in the average connectivity of the network during late spring compared to the early spring that we interpreted as a decrease of cooperation. This observation was strengthened by the significantly more abundant plasmid backbone genes in the metagenomes from the early spring. The modularity of the network from the late spring was also found to be higher than the one from the early spring, which is another possible indicator of increased competition. Antibiotic resistance genes were significantly more abundant in the late spring metagenomes. In addition, antibiotic resistance genes were also positively correlated to the organic acid concentration of the snow across both seasons. Snow organic acid content might be responsible for this change in bacterial interactions in the Arctic snow community.

Solid phase microextraction as a powerful alternative for screening of secondary metabolites in actinomycetes

Actinobacteria are one of the most promising producers of medically and industrially relevant secondary metabolites. However, screening of such compounds in actinobacteria growth demands simple, fast, and efficient extraction procedures that enable detection and precise quantification of biologically active compounds. In this regard, solid phase microextraction (SPME) emerges as an ideal extraction technique for screening of secondary metabolites in bacteria culture due to its non-exhaustive, minimally invasive, and non-destructive nature: its integrated sample preparation workflow; balanced coverage feature; metabolism quenching capabilities; and superior cleanup, as well as its versatility in configuration, which enables automation and high throughput applications. The current work provides a comparison of micro-scale and direct immersion SPME (DI-SPME) for screening of secondary metabolites, describes the optimization of the developed DI-SPME method, and introduces the developed technique for mapping of target secondary metabolites as well as its direct coupling to mass spectrometry for such applications. The optimized DI-SPME method provided higher amounts of extracted ions and intensity signals, yielding superior extraction and desorption efficiency as compared with micro-scale extraction. Studied compounds presented stability on the coating for 24 h at room temperature. The DI-SPME mapping approach revealed that lysolipin I and the lienomycin analog are distributed along the center and edges of the colony, respectively. Direct coupling of SPME to MS provided a similar ions profile as SPME-LC-MS while enabling a significant decrease in analysis time, demonstrating its suitability for such applications. DI-SPME is herein presented as an alternative to micro-scale extraction for screening of secondary metabolites in actinobacteria solid medium, as well as a feasible alternative to DESI-IMS for mapping of biologic radial distribution of secondary metabolites and cell life cycle studies. Lastly, the direct coupling of DI-SPME to MS is presented as a fast, powerful technique for high throughput analysis of secondary metabolites in this medium.

Bacteria-in-paper, a versatile platform to study bacterial ecology

Habitat spatial structure has a profound influence on bacterial life, yet there currently are no low-cost equipment-free laboratory techniques to reproduce the intricate structure of natural bacterial habitats. Here, we demonstrate the use of paper scaffolds to create landscapes spatially structured at the scales relevant to bacterial ecology. In paper scaffolds, planktonic bacteria migrate through liquid-filled pores, while the paper's cellulose fibres serve as anchor points for sessile colonies (biofilms). Using this novel approach, we explore bacterial colonisation dynamics in different landscape topographies and characterise the community composition of Escherichia coli strains undergoing centimetre-scale range expansions in habitats structured at the micrometre scale. The bacteria-in-paper platform enables quantitative assessment of bacterial community dynamics in complex environments using everyday materials.

Ecology determines how low antibiotic concentration impacts community composition and horizontal transfer of resistance genes

Low concentrations of antibiotics have numerous effects on bacteria. However, it is unknown whether ecological factors such as trophic interactions and spatial structuring influence the effects of low concentrations of antibiotics on multispecies microbial communities. Here, we address this question by investigating the effects of low antibiotic concentration on community composition and horizontal transfer of an antibiotic resistance plasmid in a 62-strain bacterial community in response to manipulation of the spatial environment and presence of predation. The strong effects of antibiotic treatment on community composition depend on the presence of predation and spatial structuring that have strong community effects on their own. Overall, we find plasmid transfer to diverse recipient taxa. Plasmid transfer is likely to occur to abundant strains, occurs to a higher number of strains in the presence of antibiotic, and also occurs to low-abundance strains in the presence of spatial structures. These results fill knowledge gaps concerning the effects of low antibiotic concentrations in complex ecological settings.

Synthetic microbial ecology and the dynamic interplay between microbial genotypes

Assemblages of microbial genotypes growing together can display surprisingly complex and unexpected dynamics and result in community-level functions and behaviors that are not readily expected from analyzing each genotype in isolation. This complexity has, at least in part, inspired a discipline of synthetic microbial ecology. Synthetic microbial ecology focuses on designing, building and analyzing the dynamic behavior of ‘ecological circuits’ (i.e. a set of interacting microbial genotypes) and understanding how community-level properties emerge as a consequence of those interactions. In this review, we discuss typical objectives of synthetic microbial ecology and the main advantages and rationales of using synthetic microbial assemblages. We then summarize recent findings of current synthetic microbial ecology investigations. In particular, we focus on the causes and consequences of the interplay between different microbial genotypes and illustrate how simple interactions can create complex dynamics and promote unexpected community-level properties. We finally propose that distinguishing between active and passive interactions and accounting for the pervasiveness of competition can improve existing frameworks for designing and predicting the dynamics of microbial assemblages.

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

The advent of easy-to-use open source microcontrollers, off-the-shelf electronics and customizable manufacturing technologies has facilitated the development of inexpensive scientific devices and laboratory equipment. In this study, we describe an imaging system that integrates low-cost and open-source hardware, software and genetic resources. The multi-fluorescence imaging system consists of readily available 470 nm LEDs, a Raspberry Pi camera and a set of filters made with low cost acrylics. This device allows imaging in scales ranging from single colonies to entire plates. We developed a set of genetic components (e.g. promoters, coding sequences, terminators) and vectors following the standard framework of Golden Gate, which allowed the fabrication of genetic constructs in a combinatorial, low cost and robust manner. In order to provide simultaneous imaging of multiple wavelength signals, we screened a series of long stokes shift fluorescent proteins that could be combined with cyan/green fluorescent proteins. We found CyOFP1, mBeRFP and sfGFP to be the most compatible set for 3-channel fluorescent imaging. We developed open source Python code to operate the hardware to run time-lapse experiments with automated control of illumination and camera and a Python module to analyze data and extract meaningful biological information. To demonstrate the potential application of this integral system, we tested its performance on a diverse range of imaging assays often used in disciplines such as microbial ecology, microbiology and synthetic biology. We also assessed its potential use in a high school environment to teach biology, hardware design, optics, and programming. Together, these results demonstrate the successful integration of open source hardware, software, genetic resources and customizable manufacturing to obtain a powerful, low cost and robust system for education, scientific research and bioengineering. All the resources developed here are available under open source licenses.

Artificial Symmetry-Breaking for Morphogenetic Engineering Bacterial Colonies

Morphogenetic engineering is an emerging field that explores the design and implementation of self-organized patterns, morphologies, and architectures in systems composed of multiple agents such as cells and swarm robots. Synthetic biology, on the other hand, aims to develop tools and formalisms that increase reproducibility, tractability, and efficiency in the engineering of biological systems. We seek to apply synthetic biology approaches to the engineering of morphologies in multicellular systems. Here, we describe the engineering of two mechanisms, symmetry-breaking and domain-specific cell regulation, as elementary functions for the prototyping of morphogenetic instructions in bacterial colonies. The former represents an artificial patterning mechanism based on plasmid segregation while the latter plays the role of artificial cell differentiation by spatial colocalization of ubiquitous and segregated components. This separation of patterning from actuation facilitates the design-build-test-improve engineering cycle. We created computational modules for CellModeller representing these basic functions and used it to guide the design process and explore the design space in silico. We applied these tools to encode spatially structured functions such as metabolic complementation, RNAPT7 gene expression, and CRISPRi/Cas9 regulation. Finally, as a proof of concept, we used CRISPRi/Cas technology to regulate cell growth by controlling methionine synthesis. These mechanisms start from single cells enabling the study of morphogenetic principles and the engineering of novel population scale structures from the bottom up.

Metabolic modeling of a chronic wound biofilm consortium predicts spatial partitioning of bacterial species

Background

Chronic wounds are often colonized by consortia comprised of different bacterial species growing as biofilms on a complex mixture of wound exudate. Bacteria growing in biofilms exhibit phenotypes distinct from planktonic growth, often rendering the application of antibacterial compounds ineffective. Computational modeling represents a complementary tool to experimentation for generating fundamental knowledge and developing more effective treatment strategies for chronic wound biofilm consortia.

Results

We developed spatiotemporal models to investigate the multispecies metabolism of a biofilm consortium comprised of two common chronic wound isolates: the aerobe Pseudomonas aeruginosa and the facultative anaerobe Staphylococcus aureus. By combining genome-scale metabolic reconstructions with partial differential equations for metabolite diffusion, the models were able to provide both temporal and spatial predictions with genome-scale resolution. The models were used to analyze the metabolic differences between single species and two species biofilms and to demonstrate the tendency of the two bacteria to spatially partition in the multispecies biofilm as observed experimentally. Nutrient gradients imposed by supplying glucose at the bottom and oxygen at the top of the biofilm induced spatial partitioning of the two species, with S. aureus most concentrated in the anaerobic region and P. aeruginosa present only in the aerobic region. The two species system was predicted to support a maximum biofilm thickness much greater than P. aeruginosa alone but slightly less than S. aureus alone, suggesting an antagonistic metabolic effect of P. aeruginosa on S. aureus. When each species was allowed to enhance its growth through consumption of secreted metabolic byproducts assuming identical uptake kinetics, the competitiveness of P. aeruginosa was further reduced due primarily to the more efficient lactate metabolism of S. aureus. Lysis of S. aureus by a small molecule inhibitor secreted from P. aeruginosa and/or P. aeruginosa aerotaxis were predicted to substantially increase P. aeruginosa competitiveness in the aerobic region, consistent with in vitro experimental studies.

Conclusions

Our biofilm modeling approach allows the prediction of individual species metabolism and interspecies interactions in both time and space with genome-scale resolution. This study yielded new insights into the multispecies metabolism of a chronic wound biofilm, in particular metabolic factors that may lead to spatial partitioning of the two bacterial species. We believe that P. aeruginosa lysis of S. aureus combined with nutrient competition is a particularly relevant scenario for which model predictions could be tested experimentally.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0334-8) contains supplementary material, which is available to authorized users.

Bacterial Communities: Interactions to Scale

In the environment, bacteria live in complex multispecies communities. These communities span in scale from small, multicellular aggregates to billions or trillions of cells within the gastrointestinal tract of animals. The dynamics of bacterial communities are determined by pairwise interactions that occur between different species in the community. Though interactions occur between a few cells at a time, the outcomes of these interchanges have ramifications that ripple through many orders of magnitude, and ultimately affect the macroscopic world including the health of host organisms. In this review we cover how bacterial competition influences the structures of bacterial communities. We also emphasize methods and insights garnered from culture-dependent pairwise interaction studies, metagenomic analyses, and modeling experiments. Finally, we argue that the integration of multiple approaches will be instrumental to future understanding of the underlying dynamics of bacterial communities.

The fitness change and the diversity maintenance in the growing mixed colony of two Serratia rubidaea clones

We extend the palette of possible colonies models of two different clones of Serratia rubidaea. Our model fits the real morphology of the colonies. We also present that the colony growth leads to a change in the ratio of the fitness which propose to be caused by the production of some signal. This signal influences the behavior of the clones and leads to the prolonged diversity maintenance. The explanation of the diversity maintenance of the mixed concurrent population in one niche is the current studied problem in the ecology and evolution.

Genome-scale modelling of microbial metabolism with temporal and spatial resolution

Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated.