Dynamics of microbial competition, commensalism, and cooperation and its implications for coculture and microbiome engineering

Nanoparticles in liposomes: a platform for increased antibiotic selectivity in multidrug resistant bacteria in respiratory tract infections

Antibiotic resistance is a cause of serious illness and death, originating often from insufficient permeability into gram-negative bacteria. Nanoparticles (NP) can increase antibiotic delivery in bacterial cells, however, may as well increase internalization in mammalian cells and toxicity. In this work, NP in liposome (NP-Lip) formulations were used to enhance the selectivity of the antibiotics (3C and tobramycin) and quorum sensing inhibitor (HIPS-1635) towards Pseudomonas aeruginosa by fusing with bacterial outer membranes and reducing uptake in mammalian cells due to their larger size. Poly (lactic-co-glycolic) acid NPs were prepared using emulsion solvent evaporation and incorporated in larger liposomes. Cytotoxicity and uptake studies were conducted on two lung cell lines, Calu-3 and H460. NP-Lip showed lower toxicity and uptake in both cell lines. Then formulations were investigated for suitability for oral inhalation. The deposition of NP and NP-Lip in the lungs was assessed by next generation impactor and corresponded to 75% and 45% deposition in the terminal bronchi and the alveoli respectively. Colloidal stability and mucus-interaction studies were conducted. NP-Lip showed higher diffusion through mucus compared to NPs with the use of nanoparticle tracking analyzer. Moreover, the permeation of delivery systems across a liquid-liquid interface epithelial barrier model of Calu-3 cells indicated that NP-Lip could cause less systemic toxicity upon in-vivo like administration by aerosol deposition. Monoculture and Pseudomonas aeruginosa biofilm with Calu-3 cells co-culture experiments were conducted, NP-Lip achieved highest toxicity towards bacterial biofilms and least toxicity % of the Calu-3 cells. Therefore, the NP- liposomal platform offers a promising approach for enhancing antibiotic selectivity and treating pulmonary infections.

Nano- and microplastics drive the dynamic equilibrium of amoeba-associated bacteria and antibiotic resistance genes

As emerging pollutants, microplastics have become pervasive on a global scale, inflicting significant harm upon ecosystems. However, the impact of these microplastics on the symbiotic relationship between protists and bacteria remains poorly understood. In this study, we investigated the mechanisms through which nano- and microplastics of varying sizes and concentrations influence the amoeba-bacterial symbiotic system. The findings reveal that nano- and microplastics exert deleterious effects on the adaptability of the amoeba host, with the magnitude of these effects contingent upon particle size and concentration. Furthermore, nano- and microplastics disrupt the initial equilibrium in the symbiotic relationship between amoeba and bacteria, with nano-plastics demonstrating a reduced ability to colonize symbiotic bacteria within the amoeba host when compared to their microplastic counterparts. Moreover, nano- and microplastics enhance the relative abundance of antibiotic resistance genes and heavy metal resistance genes in the bacteria residing within the amoeba host, which undoubtedly increases the potential transmission risk of both human pathogens and resistance genes within the environment. In sum, the results presented herein provide a novel perspective and theoretical foundation for the study of interactions between microplastics and microbial symbiotic systems, along with the establishment of risk assessment systems for ecological environments and human health.

Microbiome distribution modeling using gradient descent strategies for mock, in vitro and clinical community distributions

The human gut is home to a complex array of microorganisms interacting with the host and each other, forming a community known as the microbiome. This community has been linked to human health and disease, but understanding the underlying interactions is still challenging for researchers. Standard studies typically use high-throughput sequencing to analyze microbiome distribution in patient samples. Recent advancements in meta-omic data analysis have enabled computational modeling strategies to integrate this information into an in silico model. However, there is a need for improved parameter fitting and data integration features in microbial community modeling. This study proposes a novel alternative strategy utilizing state-of-the-art dynamic flux balance analysis (dFBA) to provide a simple protocol enabling accurate replication of abundance data composition through dynamic parameter estimation and integration of metagenomic data. We used a recurrent optimization algorithm to replicate community distributions from three different sources: mock, in vitro, and clinical microbiome. Our results show an accuracy of 98% and 96% when using in vitro and clinical bacterial abundance distributions, respectively. The proposed modeling scheme allowed us to observe the evolution of metabolites. It could provide a deeper understanding of metabolic interactions while taking advantage of the high contextualization features of GEM schemes to fit the study case. The proposed modeling scheme could improve the approach in cases where external factors determine specific bacterial distributions, such as drug intake.

Metaproteomic and gene expression analysis of interspecies interactions in a PAH-degrading synthetic microbial consortium constructed with the key microbes of a natural consortium

Polycyclic Aromatic Hydrocarbons (PAHs) impose adverse effects on the environment and human life. The use of synthetic microbial consortia is promising in bioremediation of contaminated sites with these pollutants. However, the design of consortia taking advantage of natural interactions has been poorly explored. In this study, a dual synthetic bacterial consortium (DSC_AB) was constructed with two key members (Sphingobium sp. AM and Burkholderia sp. Bk), of a natural PAH degrading consortium. DSC_AB showed significantly enhanced degradation of PAHs and toxic intermediary metabolites relative to the axenic cultures, indicating the existence of synergistic relationships. Metaproteomic and gene-expression analyses were applied to obtain a view of bacterial performance during phenanthrene removal. Overexpression of the Bk genes, naph, biph, tol and sal and the AM gene, ahdB, in DSC_AB relative to axenic cultures, demonstrated that both strains are actively participating in degradation, which gave evidence of cross-feeding. Several proteins related to stress response were under-expressed in DSC_AB relative to axenic cultures, indicating that the division of labour reduces cellular stress, increasing the efficiency of degradation. This is the one of the first works revealing bacterial relationships during PAH removal in a synthetic consortium applying an omics approach. Our findings could be used to develop criteria for evaluating the potential effectiveness of synthetic bacterial consortia in bioremediation.

Engineering living materials by synthetic biology

Natural biological materials are programmed by genetic information and able to self-organize, respond to environmental stimulus, and couple with inorganic matter. Inspired by the natural system and to mimic their complex and delicate fabrication process and functions, the field of engineered living materials emerges at the interface of synthetic biology and materials science. Here, we review the recent efforts and discuss the challenges and future opportunities.

Microbiome engineering for bioremediation of emerging pollutants

Axenic microbial applications in the open environment are unrealistic and may not be always practically viable. Therefore, it is important to use mixed microbial cultures and their interactions with the microbiome in the targeted ecosystem to perform robust functions towards their sustainability in harsh environmental conditions. Emerging pollutants like phthalates and hydrocarbons that are toxic to several aquatic and terrestrial life forms in the water bodies and lands are an alarming situation. The present review explores the possibility of devising an inclusive eco-friendly strategy like microbiome engineering which proves to be a unique and crucial technology involving the power of microbial communication through quorum sensing. This review discusses the interspecies and intra-species communications between different microbial groups with their respective environments. Moreover, this review also envisages the efforts for designing the next level of microbiome-host engineering concept (MHEC). The focus of the review also extended toward using omics and metabolic network analysis-based tools for effective microbiome engineering. These approaches might be quite helpful in the future to understand such microbial interactions but it will be challenging to implement in the real environment to get the desired functions. Finally, the review also discusses multiple approaches for the bioremediation of toxic chemicals from the soil environment.

A Two-Compartment Fermentation System to Quantify Strain-Specific Interactions in Microbial Co-Cultures

To fulfil the growing interest in investigating microbial interactions in co-cultures, a novel two-compartment bioreactor system was developed, characterised, and implemented. The system allowed for the exchange of amino acids and peptides via a polyethersulfone membrane that retained biomass. Further system characterisation revealed a Bodenstein number of 18, which hints at backmixing. Together with other physical settings, the existence of unwanted inner-compartment substrate gradients could be ruled out. Furthermore, the study of Damkoehler numbers indicated that a proper metabolite supply between compartments was enabled. Implementing the two-compartment system (2cs) for growing Streptococcus thermophilus and Lactobacillus delbrueckii subs. bulgaricus, which are microorganisms commonly used in yogurt starter cultures, revealed only a small variance between the one-compartment and two-compartment approaches. The 2cs enabled the quantification of the strain-specific production and consumption rates of amino acids in an interacting S. thermophilus-L. bulgaricus co-culture. Therefore, comparisons between mono- and co-culture performance could be achieved. Both species produce and release amino acids. Only alanine was produced de novo from glucose through potential transaminase activity by L. bulgaricus and consumed by S. thermophilus. Arginine availability in peptides was limited to S. thermophilus' growth, indicating active biosynthesis and dependency on the proteolytic activity of L. bulgaricus. The application of the 2cs not only opens the door for the quantification of exchange fluxes between microbes but also enables continuous production modes, for example, for targeted evolution studies.

Engineering microbial consortia with rationally designed cellular interactions

Synthetic microbial consortia represent a frontier of synthetic biology that promises versatile engineering of cellular functions. They are primarily developed through the design and construction of cellular interactions that coordinate individual dynamics and generate collective behaviors. Here we review recent advances in the engineering of synthetic communities through cellular-interaction programming. We first examine fundamental building blocks for intercellular communication and unidirectional positive and negative interactions. We then recap the assembly of the building blocks for creating bidirectional interactions in two-species ecosystems, which is followed by the discussion of engineering toward complex communities with increasing species numbers, under spatial contexts, and via model-guided design. We conclude by summarizing major challenges and future opportunities of engineered microbial ecosystems.

Time-lagged interspecies interactions prevail during biofilm development in moving bed biofilm reactor

Clarifying the essential succession dynamics of interspecies interactions during biofilm development is crucial for the regulation and application of biofilm-based processes. In this study, regular and time-series phylogenetic molecular ecological networks (pMENs) were constructed to investigate ordinary and time-lagged interspecies interactions during biofilm development in a moving bed biofilm reactor (MBBR). Positive interactions dominated both regular (89.78%) and time-series (77.04%) ecological networks, suggesting that extensive cooperative behaviors facilitated biofilm development. The pronounced directional interactions (72.52%) in the time-series network further indicated that time-lagged interspecies interactions prevailed in the biofilm development process. Specifically, the proportion of directional negative interactions was higher than that of positive interactions, implying that interspecific competition preferred to be time-lagged. The time-series network revealed that module hubs exhibited extensive time-lagged positive interactions with their neighbors, and most of them exhibited altruistic behaviors. Keystone species possessing more positive interactions were positively correlated with biofilm biomass, NO₃ ^- -N concentrations, and the removal efficiencies of NH₄ ⁺ -N and COD. However, keystone species and peripherals that were negatively targeted by their neighbors showed positive correlations with the concentrations of NO₂ ^- -N, polysaccharides, and proteins in the soluble microbial products. The data highlight that the time-series network can provide directional microbial interactions along with the biofilm development process, which would help to predict the tendency of community shifts and propose efficient strategies for the regulation of biofilm-based processes. This article is protected by copyright. All rights reserved.

Quantitative and analytical tools to analyze the spatiotemporal population dynamics of microbial consortia

Microorganisms occupy almost every niche on earth. They play critical roles in maintaining ecological balance, atmospheric C/N cycle, and human health. Microbes live in consortia with metabolite exchange or signal communication. Quantitative and analytical tools are becoming increasingly important to study microbial consortia dynamics. We argue that a combined reductionist and holistic approach will be important to understanding the assembly rules and spatiotemporal population dynamics of the microbial community (MICOM). Reductionism allows us to reconstruct complex MICOM from isolated or simple synthetic consortia. Holism allows us to understand microbes as a community with cooperation and competition. Here we review the recent development of quantitative and analytical tools to uncover the underlying principles in microbial communities that govern their spatiotemporal change and interaction dynamics. Mathematical models and analytical tools will continue to provide essential knowledge and expand our capability to manipulate and control microbial consortia.

Development of a Monte Carlo simulation model to predict pasteurized fluid milk spoilage due to post-pasteurization contamination with gram-negative bacteria

Psychrotolerant gram-negative bacteria introduced as post-pasteurization contamination (PPC) are a major cause of spoilage and reduced shelf life of high-temperature, short-time pasteurized fluid milk. To provide improved tools to (1) predict pasteurized fluid milk shelf life as influenced by PPC and (2) assess the effectiveness of different potential interventions that could reduce spoilage due to PPC, we developed a Monte Carlo simulation model that predicts fluid milk spoilage due to psychrotolerant gram-negative bacteria introduced as PPC. As a first step, 17 gram-negative bacterial isolates frequently associated with fluid milk spoilage were selected and used to generate growth data in skim milk broth at 6°C. The resulting growth parameters, frequency of isolation for the 17 different isolates, and initial concentration of bacteria in milk with PPC, were used to develop a Monte Carlo model to predict bacterial number at different days of shelf life based on storage temperature of milk. This model was then validated with data from d 7 and 10 of shelf life, collected from commercial operations. The validated model predicted that the parameters (1) maximum growth rate and (2) storage temperature had the greatest influence on the percentage of containers exceeding 20,000 cfu/mL standard plate count on d 7 and 10 (i.e., spoiling due to PPC), which indicates that accurate data on maximum growth rate and storage temperature are important for accurate predictions. In addition to allowing for prediction of fluid milk shelf life, the model allows for simulation of "what-if" scenarios, which allowed us to predict the effectiveness of different interventions to reduce overall fluid milk spoilage due to PPC through a set of proof-of-concept scenario (e.g., frequency of PPC in containers reduced from 100% to 10%; limiting distribution temperature to a maximum of 6°C). Combined with other models, such as previous models on fluid milk spoilage due to psychrotolerant spore-forming bacteria, the data and tools developed here will allow for rational, digitally enabled, fluid milk shelf life prediction and quality enhancement.

Engineering anaerobic digestion via optimizing microbial community: effects of bactericidal agents, quorum sensing inhibitors, and inorganic materials

Anaerobic digestion of sewage sludge (SS) is one of the effective ways to reduce the waste generated from human life activities. To date, there are many reports to improve or repress methane production during the anaerobic digestion of SS. In the anaerobic digestion process, many microorganisms work positively or negatively, and as a result of their microbe-to-microbe interaction and regulation, methane production increases or decreases. In other words, understanding the complex control mechanism among the microorganisms and identifying the strains that are key to increase or decrease methane production are important for promoting the advanced production of bioenergy and beneficial compounds. In this mini-review, the literature on methane production in anaerobic digestion has been summarized based on the results of antibiotic addition, quorum sensing control, and inorganic substance addition. By optimizing the activity of microbial groups in SS, methane or acetate can be highly produced. KEY POINTS: • Bactericidal agents such as an antibiotic alter microbial community for enhanced CH₄ production. • Bacterial interaction via quorum sensing is one of the key points for biofilm and methane production. • Anaerobic digestion can be altered in the presence of several inorganic materials.

Co-culturing microbial consortia: approaches for applications in biomanufacturing and bioprocessing

The application of microbial co-cultures is now recognized in the fields of biotechnology, ecology, and medicine. Understanding the biological interactions that govern the association of microorganisms would shape the way in which artificial/synthetic co-cultures or consortia are developed. The ability to accurately predict and control cell-to-cell interactions fully would be a significant enabler in synthetic biology. Co-culturing method development holds the key to strategically engineer environments in which the co-cultured microorganism can be monitored. Various approaches have been employed which aim to emulate the natural environment and gain access to the untapped natural resources emerging from cross-talk between partners. Amongst these methods are the use of a communal liquid medium for growth, use of a solid-liquid interface, membrane separation, spatial separation, and use of microfluidics systems. Maximizing the information content of interactions monitored is one of the major challenges that needs to be addressed by these designs. This review critically evaluates the significance and drawbacks of the co-culturing approaches used to this day in biotechnological applications, relevant to biomanufacturing. It is recommended that experimental results for a co-cultured species should be validated with different co-culture approaches due to variations in interactions that could exist as a result of the culturing method selected.

Control of synthetic microbial consortia in time, space, and composition

While synthetic microbial systems are becoming increasingly complicated, single-strain systems cannot match the complexity of their multicellular counterparts. Such complexity, however, is much more difficult to control. Recent advances have increased our ability to control temporal, spatial, and community compositional organization, including modular adhesive systems, strain growth relationships, and asymmetric cell division. While these systems generally work independently, combining them into unified systems has proven difficult. Once such unification is proven successful we will unlock a new frontier of synthetic biology and open the door to the creation of synthetic biological systems with true multicellularity.

Dynamics of microbial competition, commensalism, and cooperation and its implications for coculture and microbiome engineering

Microbial consortium is a complex adaptive system with higher‐order dynamic characteristics that are not present by individual members. To accurately predict the social interactions, we formulate a set of unstructured kinetic models to quantitatively capture the dynamic interactions of multiple microbial species. By introducing an interaction coefficient, we analytically derived the steady‐state solutions for the interacting species and the substrate‐depleting profile in the chemostat. We analyzed the stability of the possible coexisting states defined by competition, parasitism, amensalism, commensalism, and cooperation. Our model predicts that only parasitism, commensalism, and cooperation could lead to stable coexisting states. We also determined the optimal social interaction criteria of microbial coculture when sequential metabolic reactions are compartmentalized into two distinct species. Coupled with Luedeking–Piret and Michaelis–Menten equations, accumulation of metabolic intermediates in one species and formation of end‐product in another species could be derived and assessed. We discovered that parasitism consortia disfavor the bioconversion of intermediate to final product; and commensalism consortia could efficiently convert metabolic intermediates to final product and maintain metabolic homeostasis with a broad range of operational conditions (i.e., dilution rates); whereas cooperative consortia leads to highly nonlinear pattern of precursor accumulation and end‐product formation. The underlying dynamics and emergent properties of microbial consortia may provide critical knowledge for us to understand ecological coexisting states, engineer efficient bioconversion process, deliver effective gut therapeutics as well as elucidate probiotic‐pathogen or tumor‐host interactions in general.