Model-based definition of population heterogeneity and its effects on metabolism in sporulating Bacillus subtilis

Options and Limitations in Clinical Investigation of Bacterial Biofilms

Bacteria can form single- and multispecies biofilms exhibiting diverse features based upon the microbial composition of their community and microenvironment. The study of bacterial biofilm development has received great interest in the past 20 years and is motivated by the elegant complexity characteristic of these multicellular communities and their role in infectious diseases. Biofilms can thrive on virtually any surface and can be beneficial or detrimental based upon the community's interplay and the surface. Advances in the understanding of structural and functional variations and the roles that biofilms play in disease and host-pathogen interactions have been addressed through comprehensive literature searches. In this review article, a synopsis of the methodological landscape of biofilm analysis is provided, including an evaluation of the current trends in methodological research. We deem this worthwhile because a keyword-oriented bibliographical search reveals that less than 5% of the biofilm literature is devoted to methodology. In this report, we (i) summarize current methodologies for biofilm characterization, monitoring, and quantification; (ii) discuss advances in the discovery of effective imaging and sensing tools and modalities; (iii) provide an overview of tailored animal models that assess features of biofilm infections; and (iv) make recommendations defining the most appropriate methodological tools for clinical settings.

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.

Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the ‘Warburg effect’. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

Different Polar Metabolites and Protein Profiles between High- and Low-Quality Japanese Ginjo Sake

Japanese ginjo sake is a premium refined sake characterized by a pleasant fruity apple-like flavor and a sophisticated taste. Because of technical difficulties inherent in brewing ginjo sake, off-flavors sometimes occur. However, the metabolites responsible for off-flavors as well as those present or absent in higher quality ginjo sake remain uncertain. Here, the relationship between 202 polar chemical compounds in sake identified using capillary electrophoresis coupled with time-of-flight mass spectrometry and its organoleptic properties, such as quality and off-flavor, was examined. First, we found that some off-flavored sakes contained higher total amounts of metabolites than other sake samples. The results also identified that levels of 2-oxoglutaric acid and fumaric acid, metabolites in the tricarboxylic acid cycle, were highly but oppositely correlated with ginjo sake quality. Similarly, pyridoxine and pyridoxamine, co-enzymes for amino transferase, were also highly but oppositely correlated with ginjo sake quality. Additionally, pyruvic acid levels were associated with good quality as well. Compounds involved in the methionine salvage cycle, oxidative glutathione derivatives, and amino acid catabolites were correlated with low quality. Among off-flavors, an inharmonious bitter taste appeared attributable to polyamines. Furthermore, protein analysis displayed that a diversity of protein components and yeast protein (triosephosphate isomerase, TPI) leakage was linked to the overall metabolite intensity in ginjo sake. This research provides insight into the relationship between sake components and organoleptic properties.

Integration of metabolism and virulence in Clostridium difficile

Synthesis of the major toxin proteins of the diarrheal pathogen, Clostridium difficile, is dependent on the activity of TcdR, an initiation (sigma) factor of RNA polymerase. The synthesis of TcdR and the activation of toxin gene expression are responsive to multiple components in the bacterium's nutritional environment, such as the presence of certain sugars, amino acids, and fatty acids. This review summarizes current knowledge about the mechanisms responsible for repression of toxin synthesis when glucose or branched-chain amino acids or proline are in excess and the pathways that lead to synthesis of butyrate, an activator of toxin synthesis. The regulatory proteins implicated in these mechanisms also play key roles in modulating bacterial metabolic pathways, suggesting that C. difficile pathogenesis is intimately connected to the bacterium's metabolic state.

Modeling microorganism transport and survival in the subsurface

An understanding of microbial transport and survival in the subsurface is needed for public health, environmental applications, and industrial processes. Much research has therefore been directed to quantify mechanisms influencing microbial fate, and the results demonstrate a complex coupling among many physical, chemical, and biological factors. Mathematical models can be used to help understand and predict the complexities of microbial transport and survival in the subsurface under given assumptions and conditions. This review highlights existing model formulations that can be used for this purpose. In particular, we discuss models based on the advection-dispersion equation, with terms for kinetic retention to solid-water and/or air-water interfaces; blocking and ripening; release that is dependent on the resident time, diffusion, and transients in solution chemistry, water velocity, and water saturation; and microbial decay (first-order and Weibull) and growth (logistic and Monod) that is dependent on temperature, nutrient concentration, and/or microbial concentration. We highlight a two-region model to account for microbe migration in the vicinity of a solid phase and use it to simulate the coupled transport and survival of species under a variety of environmentally relevant scenarios. This review identifies challenges and limitations of models to describe and predict microbial transport and survival. In particular, many model parameters have to be optimized to simulate a diversity of observed transport, retention, and survival behavior at the laboratory scale. Improved theory and models are needed to predict the fate of microorganisms in natural subsurface systems that are highly dynamic and heterogeneous.

Ultrasensitivity of the Bacillus subtilis sporulation decision

Starving Bacillus subtilis cells execute a gene expression program resulting in the formation of stress-resistant spores. Sporulation master regulator, Spo0A, is activated by a phosphorelay and controls the expression of a multitude of genes, including the forespore-specific sigma factor σ(F) and the mother cell-specific sigma factor σ(E). Identification of the system-level mechanism of the sporulation decision is hindered by a lack of direct control over Spo0A activity. This limitation can be overcome by using a synthetic system in which Spo0A activation is controlled by inducing expression of phosphorelay kinase KinA. This induction results in a switch-like increase in the number of sporulating cells at a threshold of KinA. Using a combination of mathematical modeling and single-cell microscopy, we investigate the origin and physiological significance of this ultrasensitive threshold. The results indicate that the phosphorelay is unable to achieve a sufficiently fast and ultrasensitive response via its positive feedback architecture, suggesting that the sporulation decision is made downstream. In contrast, activation of σ(F) in the forespore and of σ(E) in the mother cell compartments occurs via a cascade of coherent feed-forward loops, and thereby can produce fast and ultrasensitive responses as a result of KinA induction. Unlike σ(F) activation, σ(E) activation in the mother cell compartment only occurs above the KinA threshold, resulting in completion of sporulation. Thus, ultrasensitive σ(E) activation explains the KinA threshold for sporulation induction. We therefore infer that under uncertain conditions, cells initiate sporulation but postpone making the sporulation decision to average stochastic fluctuations and to achieve a robust population response.

Evolutionary computation for the design of a stochastic switch for synthetic genetic circuits

Biological systems are inherently stochastic, a fact which is often ignored when simulating genetic circuits. Synthetic biology aims to design genetic circuits de novo, and cannot therefore afford to ignore the effects of stochastic behavior. Since computational design tools will be essential for large-scale synthetic biology, it is important to develop an understanding of the role of stochasticity in molecular biology, and incorporate this understanding into computational tools for genetic circuit design. We report upon an investigation into the combination of evolutionary algorithms and stochastic simulation for genetic circuit design, to design regulatory systems based on the Bacillus subtilis sin operon.

Bistable responses in bacterial genetic networks: designs and dynamical consequences

A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles networks with bistable responses.

How mathematical modelling elucidates signalling in Bacillus subtilis

Appropriate stimulus perception, signal processing and transduction ensure optimal adaptation of bacteria to environmental challenges. In the Gram-positive model bacterium Bacillus subtilis signalling networks and molecular interactions therein are well-studied, making this species a suitable candidate for the application of mathematical modelling. Here, we review systems biology approaches, focusing on chemotaxis, sporulation, σ(B) -dependent general stress response and competence. Processes like chemotaxis and Z-ring assembly depend critically on the subcellular localization of proteins. Environmental response strategies, including sporulation and competence, are characterized by phenotypic heterogeneity in isogenic cultures. The examples of mathematical modelling also include investigations that have demonstrated how operon structure and signalling dynamics are intricately interwoven to establish optimal responses. Our review illustrates that these interdisciplinary approaches offer new insights into the response of B. subtilis to environmental challenges. These case studies reveal modelling as a tool to increase the understanding of complex systems, to help formulating hypotheses and to guide the design of more directed experiments that test predictions.

Broadly heterogeneous activation of the master regulator for sporulation in Bacillus subtilis

A model system for investigating how developmental regulatory networks determine cell fate is spore formation in Bacillus subtilis. The master regulator for sporulation is Spo0A, which is activated by phosphorylation via a phosphorelay that is subject to three positive feedback loops. The ultimate decision to sporulate is, however, stochastic in that only a portion of the population sporulates even under optimal conditions. It was previously assumed that activation of Spo0A and hence entry into sporulation is subject to a bistable switch mediated by one or more feedback loops. Here we reinvestigate the basis for bimodality in sporulation. We show that none of the feedback loops is rate limiting for the synthesis and phosphorylation of Spo0A. Instead, the loops ensure a just-in-time supply of relay components for rising levels of phosphorylated Spo0A, with phosphate flux through the relay being limiting for Spo0A activation and sporulation. In addition, genes under Spo0A control did not exhibit a bimodal pattern of expression as expected for a bistable switch. In contrast, we observed a highly heterogeneous pattern of Spo0A activation that increased in a nonlinear manner with time. We present a computational model for the nonlinear increase and propose that the phosphorelay is a noise generator and that only cells that attain a threshold level of phosphorylated Spo0A sporulate.