Visualization of mRNA Expression in Pseudomonas aeruginosa Aggregates Reveals Spatial Patterns of Fermentative and Denitrifying Metabolism

Mechanisms of microbial co-aggregation in mixed anaerobic cultures

Co-aggregation of anaerobic microorganisms into suspended microbial biofilms (aggregates) serves ecological and biotechnological functions. Tightly packed aggregates of metabolically interdependent bacteria and archaea play key roles in cycling of carbon and nitrogen. Additionally, in biotechnological applications, such as wastewater treatment, microbial aggregates provide a complete metabolic network to convert complex organic material. Currently, experimental data explaining the mechanisms behind microbial co-aggregation in anoxic environments is scarce and scattered across the literature. To what extent does this process resemble co-aggregation in aerobic environments? Does the limited availability of terminal electron acceptors drive mutualistic microbial relationships, contrary to the commensal relationships observed in oxygen-rich environments? And do co-aggregating bacteria and archaea, which depend on each other to harvest the bare minimum Gibbs energy from energy-poor substrates, use similar cellular mechanisms as those used by pathogenic bacteria that form biofilms? Here, we provide an overview of the current understanding of why and how mixed anaerobic microbial communities co-aggregate and discuss potential future scientific advancements that could improve the study of anaerobic suspended aggregates. KEY POINTS: • Metabolic dependency promotes aggregation of anaerobic bacteria and archaea • Flagella, pili, and adhesins play a role in the formation of anaerobic aggregates • Cyclic di-GMP/AMP signaling may trigger the polysaccharides production in anaerobes.

Spatial transcriptome-guided multi-scale framework connects P. aeruginosa metabolic states to oxidative stress biofilm microenvironment

With the generation of spatially resolved transcriptomics of microbial biofilms, computational tools can be used to integrate this data to elucidate the multi-scale mechanisms controlling heterogeneous biofilm metabolism. This work presents a Multi-scale model of Metabolism In Cellular Systems (MiMICS) which is a computational framework that couples a genome-scale metabolic network reconstruction (GENRE) with Hybrid Automata Library (HAL), an existing agent-based model and reaction-diffusion model platform. A key feature of MiMICS is the ability to incorporate multiple -omics-guided metabolic models, which can represent unique metabolic states that yield different metabolic parameter values passed to the extracellular models. We used MiMICS to simulate Pseudomonas aeruginosa regulation of denitrification and oxidative stress metabolism in hypoxic and nitric oxide (NO) biofilm microenvironments. Integration of P. aeruginosa PA14 biofilm spatial transcriptomic data into a P. aeruginosa PA14 GENRE generated four PA14 metabolic model states that were input into MiMICS. Characteristic of aerobic, denitrification, and oxidative stress metabolism, the four metabolic model states predicted different oxygen, nitrate, and NO exchange fluxes that were passed as inputs to update the agent's local metabolite concentrations in the extracellular reaction-diffusion model. Individual bacterial agents chose a PA14 metabolic model state based on a combination of stochastic rules, and agents sensing local oxygen and NO. Transcriptome-guided MiMICS predictions suggested microscale denitrification and oxidative stress metabolic heterogeneity emerged due to local variability in the NO biofilm microenvironment. MiMICS accurately predicted the biofilm's spatial relationships between denitrification, oxidative stress, and central carbon metabolism. As simulated cells responded to extracellular NO, MiMICS revealed dynamics of cell populations heterogeneously upregulating reactions in the denitrification pathway, which may function to maintain NO levels within non-toxic ranges. We demonstrated that MiMICS is a valuable computational tool to incorporate multiple -omics-guided metabolic models to mechanistically map heterogeneous microbial metabolic states to the biofilm microenvironment.

Targeting Anaerobic Respiration in Pseudomonas aeruginosa with Chlorate Improves Healing of Chronic Wounds

Objective: Pseudomonas aeruginosa is an opportunistic pathogen that can establish chronic infections and form biofilm in wounds. Because the wound environment is largely devoid of oxygen, P. aeruginosa may rely on anaerobic metabolism, such as nitrate respiration, to survive in wounds. While nitrate reductase (Nar) typically reduces nitrate to nitrite, it can also reduce chlorate to chlorite, which is a toxic oxidizing agent. Therefore, chlorate can act as a prodrug to specifically eradicate hypoxic/anoxic, nitrate-respiring P. aeruginosa populations, which are often tolerant to conventional antibiotic treatments. Approach: Using a diabetic mouse model for chronic wounds, we tested the role that anaerobic nitrate respiration plays in supporting chronic P. aeruginosa infections. Results: P. aeruginosa forms biofilm deep within the wound where the environment is anoxic. Daily treatment of P. aeruginosa-infected wounds with chlorate supported wound healing. Chlorate treatment was as effective as a treatment with ciprofloxacin (a conventional antibiotic that targets both oxic and hypoxic/anoxic P. aeruginosa populations). Chlorate-treated wounds showed markers of good-quality wound healing, including well-formed granulation tissue, reepithelialization and microvessel development. Loss- and gain-of-function experiments showed that P. aeruginosa requires nitrate respiration to establish a chronic wound infection and form biofilms. Innovation: We show that the small molecule chlorate, kills the opportunistic pathogen, P. aeruginosa, by targeting a form of anaerobic metabolism called nitrate respiration. Conclusion: Chlorate holds promise as a treatment to combat diverse bacterial infections where oxygen is limiting and/or where pathogens grow as biofilms because many other pathogens possess Nar and survive using anaerobic metabolism.

How to study biofilms: technological advancements in clinical biofilm research

Biofilm formation is an important survival strategy commonly used by bacteria and fungi, which are embedded in a protective extracellular matrix of organic polymers. They are ubiquitous in nature, including humans and other animals, and they can be surface- and non-surface-associated, making them capable of growing in and on many different parts of the body. Biofilms are also complex, forming polymicrobial communities that are difficult to eradicate due to their unique growth dynamics, and clinical infections associated with biofilms are a huge burden in the healthcare setting, as they are often difficult to diagnose and to treat. Our understanding of biofilm formation and development is a fast-paced and important research focus. This review aims to describe the advancements in clinical biofilm research, including both in vitro and in vivo biofilm models, imaging techniques and techniques to analyse the biological functions of the biofilm.

What's in a name? Characteristics of clinical biofilms

In vitro biofilms are communities of microbes with unique features compared to individual cells. Biofilms are commonly characterized by physical traits like size, adhesion, and a matrix made of extracellular substances. They display distinct phenotypic features, such as metabolic activity and antibiotic tolerance. However, the relative importance of these traits depends on the environment and bacterial species. Various mechanisms enable biofilm-associated bacteria to withstand antibiotics, including physical barriers, physiological adaptations, and changes in gene expression. Gene expression profiles in biofilms differ from individual cells but, there is little consensus among studies and so far, a 'biofilm signature transcriptome' has not been recognized. Additionally, the spatial and temporal variability within biofilms varies greatly depending on the system or environment. Despite all these variable conditions, which produce very diverse structures, they are all noted as biofilms. We discuss that clinical biofilms may differ from those grown in laboratories and found in the environment and discuss whether the characteristics that are commonly used to define and characterize biofilms have been shown in infectious biofilms. We emphasize that there is a need for a comprehensive understanding of the specific traits that are used to define bacteria in infections as clinical biofilms.

Biofilm antimicrobial susceptibility through an experimental evolutionary lens

Experimental evolution experiments in which bacterial populations are repeatedly exposed to an antimicrobial treatment, and examination of the genotype and phenotype of the resulting evolved bacteria, can help shed light on mechanisms behind reduced susceptibility. In this review we present an overview of why it is important to include biofilms in experimental evolution, which approaches are available to study experimental evolution in biofilms and what experimental evolution has taught us about tolerance and resistance in biofilms. Finally, we present an emerging consensus view on biofilm antimicrobial susceptibility supported by data obtained during experimental evolution studies.