Multi-Replicated Enrichment Communities as a Model System in Microbial Ecology

Complete genome sequences of 30 bacterial species from a synthetic community

We present complete genome sequences from 30 bacterial species that can be used to construct defined synthetic communities that stably form in the laboratory under controlled conditions.

The optimization of microbial functions through rational environmental manipulations

Microorganisms play a central role in biotechnology and it is key that we develop strategies to engineer and optimize their functionality. To this end, most efforts have focused on introducing genetic manipulations in microorganisms which are then grown either in monoculture or in mixed-species consortia. An alternative strategy to optimize microbial processes is to rationally engineer the environment in which microbes grow. The microbial environment is multidimensional, including factors such as temperature, pH, salinity, nutrient composition, etc. These environmental factors all influence the growth and phenotypes of microorganisms and they generally "interact" with one another, combining their effects in complex, non-additive ways. In this piece, we overview the origins and consequences of these "interactions" between environmental factors and discuss how they have been built into statistical, bottom-up predictive models of microbial function to identify optimal environmental conditions for monocultures and microbial consortia. We also overview alternative "top-down" approaches, such as genetic algorithms, to finding optimal combinations of environmental factors. By providing a brief summary of the state of this field, we hope to stimulate further work on the rational manipulation and optimization of the microbial environment.

Serial cultures in invert emulsion and monophase systems for microbial community shaping and propagation

BACKGROUND

Microbial communities harbor important biotechnological potential in diverse domains, however, the engineering and propagation of such communities still face both knowledge and know-how gaps. More specifically, culturing tools are needed to propagate and shape microbial communities, to obtain desired properties, and to exploit them. Previous work suggested that micro-confinement and segregation of microorganisms using invert (water-in-oil, w/o) emulsion broth can shape communities during propagation, by alleviating biotic interactions and inducing physiological changes in cultured bacteria. The present work aimed at evaluating invert emulsion and simple broth monophasic cultures for the propagation and shaping of bacterial communities derived from raw milk in a serial propagation design.

RESULTS

The monophasic setup resulted in stable community structures during serial propagation, whereas the invert emulsion system resulted in only transiently stable structures. In addition, different communities with different taxonomic compositions could be obtained from a single inoculum. Furthermore, the implementation of invert emulsion systems has allowed for the enrichment of less abundant microorganisms and consequently facilitated their isolation on culture agar plates.

CONCLUSIONS

The monophasic system enables communities to be propagated in a stable manner, whereas the invert emulsion system allowed for the isolation of less abundant microorganisms and the generation of diverse taxonomic compositions from a single inoculum.

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.

Leveraging phylogenetic signal to unravel microbiome function and assembly rules

Clarifying the general rules behind microbial community assembly will foster the development of microbiome-based technological solutions. Here, we study microbial community assembly through a computational analysis of phylogenetic core groups (PCGs): discrete portions of the bacterial phylogeny with high prevalence in the ecosystem under study. We first show that the existence of PCGs was a predominant feature of the varied set of microbial ecosystems studied. Then, we re-analyzed an in vitro experimental dataset using a PCG-based approach, drawing only from its community composition data and from publicly available genomic databases. Using mainly genome scale metabolic models and population dynamics modeling, we obtained ecological insights on metabolic niche structure and population dynamics comparable to those gained after canonical experimentation. Thus, leveraging phylogenetic signal to help unravel microbiome function and assembly rules offers a potential avenue to gain further insight on Earth's microbial ecosystems.

Synthesizing microbial biodiversity

The diversity of microbial ecosystems is linked to crucial ecological processes and functions. Despite its significance, the ecological mechanisms responsible for the initiation and maintenance of microbiome diversity are still not fully understood. The primary challenge lies in the difficulty of isolating, monitoring, and manipulating the complex and interrelated ecological processes that modulate the diversity of microbial communities in their natural habitats. Synthetic ecology experiments provide a suitable alternative for investigating the mechanisms behind microbial biodiversity in controlled laboratory settings, as the environment can be systematically and modularly manipulated by adding and removing components. This enables the testing of hypotheses and the advancement of predictive theories. In this review, we present an overview of recent progress toward achieving this goal.

Artificial selection of communities drives the emergence of structured interactions

Species-rich communities, such as the microbiota or microbial ecosystems, provide key functions for human health and climatic resilience. Increasing effort is being dedicated to design experimental protocols for selecting community-level functions of interest. These experiments typically involve selection acting on populations of communities, each of which is composed of multiple species. If numerical simulations started to explore the evolutionary dynamics of this complex, multi-scale system, a comprehensive theoretical understanding of the process of artificial selection of communities is still lacking. Here, we propose a general model for the evolutionary dynamics of communities composed of a large number of interacting species, described by disordered generalised Lotka-Volterra equations. Our analytical and numerical results reveal that selection for scalar community functions leads to the emergence, along an evolutionary trajectory, of a low-dimensional structure in an initially featureless interaction matrix. Such structure reflects the combination of the properties of the ancestral community and of the selective pressure. Our analysis determines how the speed of adaptation scales with the system parameters and the abundance distribution of the evolved communities. Artificial selection for larger total abundance is thus shown to drive increased levels of mutualism and interaction diversity. Inference of the interaction matrix is proposed as a method to assess the emergence of structured interactions from experimentally accessible measures.

Emergent coexistence in multispecies microbial communities

Understanding the mechanisms that maintain microbial biodiversity is a critical aspiration in ecology. Past work on microbial coexistence has largely focused on species pairs, but it is unclear whether pairwise coexistence in isolation is required for coexistence in a multispecies community. To address this question, we conducted hundreds of pairwise competition experiments among the stably coexisting members of 12 different enrichment communities in vitro. To determine the outcomes of these experiments, we developed an automated image analysis pipeline to quantify species abundances. We found that competitive exclusion was the most common outcome, and it was strongly hierarchical and transitive. Because many species that coexist within a stable multispecies community fail to coexist in pairwise co-culture under identical conditions, we concluded that multispecies coexistence is an emergent phenomenon. This work highlights the importance of community context for understanding the origins of coexistence in complex ecosystems.

Non-gene-editing microbiome engineering of spontaneous food fermentation microbiota-Limitation control, design control, and integration

Non-gene-editing microbiome engineering (NgeME) is the rational design and control of natural microbial consortia to perform desired functions. Traditional NgeME approaches use selected environmental variables to force natural microbial consortia to perform the desired functions. Spontaneous food fermentation, the oldest kind of traditional NgeME, transforms foods into various fermented products using natural microbial networks. In traditional NgeME, spontaneous food fermentation microbiotas (SFFMs) are typically formed and controlled manually by the establishment of limiting factors in small batches with little mechanization. However, limitation control generally leads to trade-offs between efficiency and the quality of fermentation. Modern NgeME approaches based on synthetic microbial ecology have been developed using designed microbial communities to explore assembly mechanisms and target functional enhancement of SFFMs. This has greatly improved our understanding of microbiota control, but such approaches still have shortcomings compared to traditional NgeME. Here, we comprehensively describe research on mechanisms and control strategies for SFFMs based on traditional and modern NgeME. We discuss the ecological and engineering principles of the two approaches to enhance the understanding of how best to control SFFM. We also review recent applied and theoretical research on modern NgeME and propose an integrated in vitro synthetic microbiota model to bridge gaps between limitation control and design control for SFFM.

The community-function landscape of microbial consortia

Quantitatively linking the composition and function of microbial communities is a major aspiration of microbial ecology. Microbial community functions emerge from a complex web of molecular interactions between cells, which give rise to population-level interactions among strains and species. Incorporating this complexity into predictive models is highly challenging. Inspired by a similar problem in genetics of predicting quantitative phenotypes from genotypes, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.

Guided by the principles of microbiome engineering: Accomplishments and perspectives for environmental use

Although the accomplishments of microbiome engineering highlight its significance for the targeted manipulation of microbial communities, knowledge and technical gaps still limit the applications of microbiome engineering in biotechnology, especially for environmental use. Addressing the environmental challenges of refractory pollutants and fluctuating environmental conditions requires an adequate understanding of the theoretical achievements and practical applications of microbiome engineering. Here, we review recent cutting-edge studies on microbiome engineering strategies and their classical applications in bioremediation. Moreover, a framework is summarized for combining both top-down and bottom-up approaches in microbiome engineering toward improved applications. A strategy to engineer microbiomes for environmental use, which avoids the build-up of toxic intermediates that pose a risk to human health, is suggested. We anticipate that the highlighted framework and strategy will be beneficial for engineering microbiomes to address difficult environmental challenges such as degrading multiple refractory pollutants and sustain the performance of engineered microbiomes in situ with indigenous microorganisms under fluctuating conditions.

Microbial ecology of biofiltration used for producing safe drinking water

Abstract

Biofiltration is a water purification technology playing a pivotal role in producing safe drinking water. This technology attracts many interests worldwide due to its advantages, such as no addition of chemicals, a low energy input, and a high removal efficiency of organic compounds, undesirable taste and odours, and pathogens. The current review describes the microbial ecology of three biofiltration processes that are routinely used in drinking water treatment plants, i.e. (i) rapid sand filtration (RSF), (ii) granular activated carbon filtration (GACF), and (iii) slow sand filtration (SSF). We summarised and compared the characteristics, removal performance, and corresponding (newly revealed) mechanisms of the three biofiltration processes. Specifically, the microbial ecology of the different biofilter processes and the role of microbial communities in removing nutrients, organic compounds, and pathogens were reviewed. Finally, we highlight the limitations and challenges in the study of biofiltration in drinking water production, and propose future perspectives for obtaining a comprehensive understanding of the microbial ecology of biofiltration, which is needed to promote and optimise its further application.

Key points

• Biofilters are composed of complex microbiomes, primarily shaped by water quality.

• Conventional biofilters contribute to address safety challenges in drinking water.

• Studies may underestimate the active/functional role of microbiomes in biofilters.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-022-12013-x.

Microbiome breeding: conceptual and practical issues

Microbiome breeding is a new artificial selection technique that seeks to change the genetic composition of microbiomes in order to benefit plant or animal hosts. Recent experimental and theoretical analyses have shown that microbiome breeding is possible whenever microbiome-encoded genetic factors affect host traits (e.g., health) and microbiomes are transmissible between hosts with sufficient fidelity, such as during natural microbiome transmission between individuals of social animals, or during experimental microbiome transplanting between plants. To address misunderstandings that stymie microbiome-breeding programs, we (i) clarify and visualize the corresponding elements of microbiome selection and standard selection; (ii) elucidate the eco-evolutionary processes underlying microbiome selection within a quantitative genetic framework to summarize practical guidelines that optimize microbiome breeding; and (iii) characterize the kinds of host species most amenable to microbiome breeding.

Treponema denticola Induces Alzheimer-Like Tau Hyperphosphorylation by Activating Hippocampal Neuroinflammation in Mice

Alzheimer's disease (AD) is the most common type of dementia. Tau hyperphosphorylation and amyloid β (Aβ) deposition are the key pathological hallmarks of AD. Recent studies have shown that periodontitis is a significant risk factor for AD. The periodontal pathogen Porphyromonas gingivalis and its virulence factors have been shown to initiate and promote the hallmark pathologies and behavioral symptoms of AD. A possible link between Treponema denticola, another main periodontal pathogen, and AD has been reported. However, the role of T. denticola in AD pathogenesis is still unclear, and whether T. denticola and P. gingivalis exert a synergistic effect to promote AD development needs to be further studied. In this study, we investigated whether oral infection with T. denticola caused tau hyperphosphorylation in the hippocampi of mice and explored the underlying mechanisms. Orally administered T. denticola induced alveolar bone resorption, colonized brain tissues, and increased the activity of the phosphokinase GSK3β by activating neuroinflammation in the hippocampus, thus promoting the hyperphosphorylation of the tau protein at Ser396, Thr181, and Thr231 in mice. An in vitro study with BV2 and N2a cell models of T. denticola invasion also verified the role of this pathogen in tau phosphorylation. T. denticola and P. gingivalis were not found to exert a synergistic effect on tau phosphorylation. In summary, these findings provide new insight into the important role of T. denticola in AD pathogenesis, providing biological connections between periodontal diseases and AD.

Functional attractors in microbial community assembly

For microbiome biology to become a more predictive science, we must identify which descriptive features of microbial communities are reproducible and predictable, which are not, and why. We address this question by experimentally studying parallelism and convergence in microbial community assembly in replicate glucose-limited habitats. Here, we show that the previously observed family-level convergence in these habitats reflects a reproducible metabolic organization, where the ratio of the dominant metabolic groups can be explained from a simple resource-partitioning model. In turn, taxonomic divergence among replicate communities arises from multistability in population dynamics. Multistability can also lead to alternative functional states in closed ecosystems but not in metacommunities. Our findings empirically illustrate how the evolutionary conservation of quantitative metabolic traits, multistability, and the inherent stochasticity of population dynamics, may all conspire to generate the patterns of reproducibility and variability at different levels of organization that are commonplace in microbial community assembly.

Artificial Selection on Microbiomes To Breed Microbiomes That Confer Salt Tolerance to Plants

We develop a method to artificially select for rhizosphere microbiomes that confer salt tolerance to the model grass Brachypodium distachyon grown under sodium salt stress or aluminum salt stress. In a controlled greenhouse environment, we differentially propagated rhizosphere microbiomes between plants of a nonevolving, highly inbred plant population; therefore, only microbiomes evolved in our experiment, but the plants did not evolve in parallel. To maximize microbiome perpetuation when transplanting microbiomes between plants and, thus, maximize response to microbiome selection, we improved earlier methods by (i) controlling microbiome assembly when inoculating seeds at the beginning of each selection cycle; (ii) fractionating microbiomes before transfer between plants to harvest, perpetuate, and select on only bacterial and viral microbiome components; (iii) ramping of salt stress gradually from minor to extreme salt stress with each selection cycle to minimize the chance of overstressing plants; (iv) using two nonselection control treatments (e.g., nonselection microbial enrichment and null inoculation) that permit comparison to the improving fitness benefits that selected microbiomes impart on plants. Unlike previous methods, our selection protocol generated microbiomes that enhance plant fitness after only 1 to 3 rounds of microbiome selection. After nine rounds of microbiome selection, the effect of microbiomes selected to confer tolerance to aluminum salt stress was nonspecific (these artificially selected microbiomes equally ameliorate sodium and aluminum salt stresses), but the effect of microbiomes selected to confer tolerance to sodium salt stress was specific (these artificially selected microbiomes do not confer tolerance to aluminum salt stress). Plants with artificially selected microbiomes had 55 to 205% greater seed production than plants with unselected control microbiomes. IMPORTANCE We developed an experimental protocol that improves earlier methods of artificial selection on microbiomes and then tested the efficacy of our protocol to breed root-associated bacterial microbiomes that confer salt tolerance to a plant. Salt stress limits growth and seed production of crop plants, and artificially selected microbiomes conferring salt tolerance may ultimately help improve agricultural productivity. Unlike previous experiments of microbiome selection, our selection protocol generated microbiomes that enhance plant productivity after only 1 to 3 rounds of artificial selection on root-associated microbiomes, increasing seed production under extreme salt stress by 55 to 205% after nine rounds of microbiome selection. Although we artificially selected microbiomes under controlled greenhouse conditions that differ from outdoor conditions, increasing seed production by 55 to 205% under extreme salt stress is a remarkable enhancement of plant productivity compared to traditional plant breeding. We describe a series of additional experimental protocols that will advance insights into key parameters that determine efficacy and response to microbiome selection.

Oral Osteomicrobiology: The Role of Oral Microbiota in Alveolar Bone Homeostasis

Osteomicrobiology is a new research field in which the aim is to explore the role of microbiota in bone homeostasis. The alveolar bone is that part of the maxilla and mandible that supports the teeth. It is now evident that naturally occurring alveolar bone loss is considerably stunted in germ-free mice compared with specific-pathogen-free mice. Recently, the roles of oral microbiota in modulating host defense systems and alveolar bone homeostasis have attracted increasing attention. Moreover, the mechanistic understanding of oral microbiota in mediating alveolar bone remodeling processes is undergoing rapid progress due to the advancement in technology. In this review, to provide insight into the role of oral microbiota in alveolar bone homeostasis, we introduced the term “oral osteomicrobiology.” We discussed regulation of alveolar bone development and bone loss by oral microbiota under physiological and pathological conditions. We also focused on the signaling pathways involved in oral osteomicrobiology and discussed the bridging role of osteoimmunity and influencing factors in this process. Finally, the critical techniques for osteomicrobiological investigations were introduced.

Microbial effects on plant phenology and fitness

Plant development and the timing of developmental events (phenology) are tightly coupled with plant fitness. A variety of internal and external factors determine the timing and fitness consequences of these life-history transitions. Microbes interact with plants throughout their life history and impact host phenology. This review summarizes current mechanistic and theoretical knowledge surrounding microbe-driven changes in plant phenology. Overall, there are examples of microbes impacting every phenological transition. While most studies have focused on flowering time, microbial effects remain important for host survival and fitness across all phenological phases. Microbe-mediated changes in nutrient acquisition and phytohormone signaling can release plants from stressful conditions and alter plant stress responses inducing shifts in developmental events. The frequency and direction of phenological effects appear to be partly determined by the lifestyle and the underlying nature of a plant-microbe interaction (i.e., mutualistic or pathogenic), in addition to the taxonomic group of the microbe (fungi vs. bacteria). Finally, we highlight biases, gaps in knowledge, and future directions. This biotic source of plasticity for plant adaptation will serve an important role in sustaining plant biodiversity and managing agriculture under the pressures of climate change.