Bacterial lifestyle switch in response to algal metabolites

Unicellular algae, termed phytoplankton, greatly impact the marine environment by serving as the basis of marine food webs and by playing central roles in biogeochemical cycling of elements. The interactions between phytoplankton and heterotrophic bacteria affect the fitness of both partners. It is becoming increasingly recognized that metabolic exchange determines the nature of such interactions, but the underlying molecular mechanisms remain underexplored. Here, we investigated the molecular and metabolic basis for the bacterial lifestyle switch, from coexistence to pathogenicity, in Sulfitobacter D7 during its interaction with Emiliania huxleyi, a cosmopolitan bloom-forming phytoplankter. To unravel the bacterial lifestyle switch, we profiled bacterial transcriptomes in response to infochemicals derived from algae in exponential and stationary growth, which induced the Sulfitobacter D7 coexistence and pathogenicity lifestyles, respectively. We found that algal dimethylsulfoniopropionate (DMSP) was a pivotal signaling molecule that mediated the transition between the lifestyles. However, the coexisting and pathogenic lifestyles were evident only in the presence of additional algal metabolites. In the pathogenic mode, Sulfitobacter D7 upregulated flagellar motility and many transport systems, presumably to maximize assimilation of E. huxleyi-derived metabolites released by algal cells upon cell death. Specifically, we discovered that algae-produced benzoate promoted the growth of Sulfitobacter D7, and negated the DMSP-inducing lifestyle switch to pathogenicity, demonstrating that benzoate is important for maintaining the coexistence of algae and bacteria. We propose that bacteria can sense the physiological status of the algal host through changes in the metabolic composition, which will determine the bacterial lifestyle during the interactions.

Cross-feeding shapes both competition and cooperation in microbial ecosystems

Recent work suggests that cross-feeding -- the secretion and consumption of metabolic biproducts by microbes -- is essential for understanding microbial ecology. Yet how cross-feeding and competition combine to give rise to ecosystem-level properties remains poorly understood. To address this question, we analytically analyze the Microbial Consumer Resource Model (MiCRM), a prominent ecological model commonly used to study microbial communities. Our mean-field solution exploits the fact that unlike replicas, the cavity method does not require the existence of a Lyapunov function. We use our solution to derive new species-packing bounds for diverse ecosystems in the presence of cross-feeding, as well as simple expressions for species richness and the abundance of secreted resources as a function of cross-feeding (metabolic leakage) and competition. Our results show how a complex interplay between competition for resources and cooperation resulting from metabolic exchange combine to shape the properties of microbial ecosystems.

Cell Growth Model with Stochastic Gene Expression Helps Understand the Growth Advantage of Metabolic Exchange and Auxotrophy

Cooperative behaviors are highly prevalent in the wild, but their evolution is not understood. Metabolic flux models can demonstrate the viability of metabolic exchange as cooperative interactions, but steady-state growth models cannot explain why cooperators grow faster.

Facilitating Imaging Mass Spectrometry of Microbial Specialized Metabolites with METASPACE

Metabolite annotation from imaging mass spectrometry (imaging MS) data is a difficult undertaking that is extremely resource intensive. Here, we adapted METASPACE, cloud software for imaging MS metabolite annotation and data interpretation, to quickly annotate microbial specialized metabolites from high-resolution and high-mass accuracy imaging MS data. Compared with manual ion image and MS1 annotation, METASPACE is faster and, with the appropriate database, more accurate. We applied it to data from microbial colonies grown on agar containing 10 diverse bacterial species and showed that METASPACE was able to annotate 53 ions corresponding to 32 different microbial metabolites. This demonstrates METASPACE to be a useful tool to annotate the chemistry and metabolic exchange factors found in microbial interactions, thereby elucidating the functions of these molecules.

An evolutionary algorithm for designing microbial communities via environmental modification

Despite a growing understanding of how environmental composition affects microbial communities, it remains difficult to apply this knowledge to the rational design of synthetic multispecies consortia. This is because natural microbial communities can harbour thousands of different organisms and environmental substrates, making up a vast combinatorial space that precludes exhaustive experimental testing and computational prediction. Here, we present a method based on the combination of machine learning and metabolic modelling that selects optimal environmental compositions to produce target community phenotypes. In this framework, dynamic flux balance analysis is used to model the growth of a community in candidate environments. A genetic algorithm is then used to evaluate the behaviour of the community relative to a target phenotype, and subsequently adjust the environment to allow the organisms to approach this target. We apply this iterative process to thousands of in silico communities of varying sizes, showing how it can rapidly identify environments that yield desired taxonomic compositions and patterns of metabolic exchange. Moreover, this combination of approaches produces testable predictions for the assembly of experimental microbial communities with specific properties and can facilitate rational environmental design processes for complex microbiomes.

Metabolic Exchange and Energetic Coupling between Nutritionally Stressed Bacterial Species: Role of Quorum-Sensing Molecules

ABSTRACT Formation of multispecies communities allows nearly every niche on earth to be colonized, and the exchange of molecular information among neighboring bacteria in such communities is key for bacterial success. To clarify the principles controlling interspecies interactions, we previously developed a coculture model with two anaerobic bacteria, Clostridium acetobutylicum (Gram positive) and Desulfovibrio vulgaris Hildenborough (Gram negative, sulfate reducing). Under conditions of nutritional stress for D. vulgaris, the existence of tight cell-cell interactions between the two bacteria induced emergent properties. Here, we show that the direct exchange of carbon metabolites produced by C. acetobutylicum allows D vulgaris to duplicate its DNA and to be energetically viable even without its substrates. We identify the molecular basis of the physical interactions and how autoinducer-2 (AI-2) molecules control the interactions and metabolite exchanges between C. acetobutylicum and D. vulgaris (or Escherichia coli and D. vulgaris). With nutrients, D. vulgaris produces a small molecule that inhibits in vitro the AI-2 activity and could act as an antagonist in vivo. Sensing of AI-2 by D. vulgaris could induce formation of an intercellular structure that allows directly or indirectly metabolic exchange and energetic coupling between the two bacteria. IMPORTANCE Bacteria have usually been studied in single culture in rich media or under specific starvation conditions. However, in nature they coexist with other microorganisms and build an advanced society. The molecular bases of the interactions controlling this society are poorly understood. Use of a synthetic consortium and reducing complexity allow us to shed light on the bacterial communication at the molecular level. This study presents evidence that quorum-sensing molecule AI-2 allows physical and metabolic interactions in the synthetic consortium and provides new insights into the link between metabolism and bacterial communication.

Microbiota metabolic exchange is critical for colorectal cancer redox homeostasis and growth

Intestinal microbiota play a fundamental role in human health and disease. Microbial dysbiosis is a hallmark of colorectal cancer (CRC) as tumor stage-specific shifts potentiate tumor growth, influence the inflammatory microenvironment, and alter response to therapy. Recent work has demonstrated a critical role for microbial metabolite exchange in host response. However, the role of most microbial metabolites in colon cancer growth is unclear. To better understand how metabolic exchange between the microbiota and tumor epithelium alter CRC growth, a screen of the most abundant bacterially derived metabolites was assessed. Several metabolites were found to alter CRC growth, but reuterin most significantly suppressed CRC cell proliferation. Reuterin is a bifunctional metabolite containing both hydroxy and aldehyde functional groups. Reuterin is primarily synthesized from glycerol by Lactobacillus reuteri, a commensal bacterium found throughout the gastrointestinal tract. We found that reuterin suppresses growth via alterations to the redox balance of CRC cells. Mechanistically, reuterin potentiates reactive oxygen species (ROS) which leads to irreversible cysteine oxidation and enhanced cell death. Supplementation of either antioxidants or hydrogen sulfide fully rescued growth, suggesting that reuterin is suppressing CRC growth through protein oxidation. These studies demonstrate the potential of reuterin to act as a potent chemotherapeutic for treating colorectal cancers.