Marine cyanobacterial biomass is an efficient feedstock for fungal bioprocesses.

BACKGROUND: Marine cyanobacteria offer many sustainability advantages, such as the ability to fix atmospheric CO2, very fast growth and no dependence on freshwater for culture. Cyanobacterial biomass is a rich source of sugars and proteins, two essential nutrients for culturing any heterotroph. However, no previous study has evaluated their application as a feedstock for fungal bioprocesses. RESULTS: In this work, we cultured the marine cyanobacterium Synechococcus sp. PCC 7002 in a 3-L externally illuminated bioreactor with working volume of 2 L with a biomass productivity of ~ 0.8 g L-1 day-1. Hydrolysis of the biomass with acids released proteins and hydrolyzed glycogen while hydrolysis of the biomass with base released only proteins but did not hydrolyze glycogen. Among the different acids tested, treatment with HNO3 led to the highest release of proteins and glucose. Cyanobacterial biomass hydrolysate (CBH) prepared in HNO3 was used as a medium to produce cellulase enzyme by the Penicillium funiculosum OAO3 strain while CBH prepared in HCl and treated with charcoal was used as a medium for citric acid by Aspergillus tubingensis. Approximately 50% higher titers of both products were obtained compared to traditional media. CONCLUSIONS: These results show that the hydrolysate of marine cyanobacteria is an effective source of nutrients/proteins for fungal bioprocesses.

Modeling N-Glycosylation: A Systems Biology Approach for Evaluating Changes in the Steady-State Organization of Golgi-Resident Proteins.

The organization of Golgi-resident proteins is crucial for sorting molecules within the secretory pathway and regulating posttranslational modifications. However, evaluating changes to Golgi organization can be challenging, often requiring extensive experimental investigations. Here, we propose a systems biology approach in which changes to Golgi-resident protein sorting and localization can be deduced using cellular N-glycan profiles as the only experimental input.The approach detailed here utilizes the influence of Golgi organization on N-glycan biosynthesis to investigate the mechanisms involved in establishing and maintaining Golgi organization. While N-glycosylation is carried out in a non-template-driven manner, the distribution of N-glycan biosynthetic enzymes within the Golgi ensures this process is not completely random. Therefore, changes to N-glycan profiles provide clues into how altered cell phenotypes affect the sorting and localization of Golgi-resident proteins. Here, we generate a stochastic simulation of N-glycan biosynthesis to produce a simulated glycan profile similar to that obtained experimentally and then combine this with Bayesian fitting to enable inference of changes in enzyme amounts and localizations. Alterations to Golgi organization are evaluated by calculating how the fitted enzyme parameters shift when moving from simulating the glycan profile of one cellular state (e.g., a wild type) to an altered cellular state (e.g., a mutant). Our approach illustrates how an iterative combination of mathematical systems biology and minimal experimental cell biology can be utilized to maximally integrate biological knowledge to gain insightful knowledge of the underlying mechanisms in a manner inaccessible to either alone.

The Effects of Antibiotic Combination Treatments on Pseudomonas aeruginosa Tolerance Evolution and Coexistence with Stenotrophomonas maltophilia.

The Pseudomonas aeruginosa bacterium is a common pathogen of cystic fibrosis (CF) patients due to its ability to evolve resistance to antibiotics during treatments. While P. aeruginosa resistance evolution is well-characterized in monocultures, it is less well-understood in polymicrobial CF infections. Here, we investigated how exposure to ciprofloxacin, colistin, or tobramycin antibiotics, administered at sub-minimum inhibitory concentration (MIC) doses, both alone and in combination, shaped the tolerance evolution of P. aeruginosa (PAO1 lab and clinical CF LESB58 strains) in the absence and presence of a commonly co-occurring species, Stenotrophomonas maltophilia. The increases in antibiotic tolerances were primarily driven by the presence of that antibiotic in the treatment. We observed a reciprocal cross-tolerance between ciprofloxacin and tobramycin, and, when combined, the selected antibiotics increased the MICs for all of the antibiotics. Though the presence of S. maltophilia did not affect the tolerance or the MIC evolution, it drove P. aeruginosa into extinction more frequently in the presence of tobramycin due to its relatively greater innate tobramycin tolerance. In contrast, P. aeruginosa dominated and drove S. maltophilia extinct in most other treatments. Together, our findings suggest that besides driving high-level antibiotic tolerance evolution, sub-MIC antibiotic exposure can alter competitive bacterial interactions, leading to target pathogen extinctions in multispecies communities. IMPORTANCE Cystic fibrosis (CF) is a genetic condition that results in thick mucus secretions in the lungs that are susceptible to chronic bacterial infections. The bacterial pathogen Pseudomonas aeruginosa is often associated with morbidity in CF and is difficult to treat due to its high resistance to antibiotics. The resistance evolution of Pseudomonas aeruginosa is poorly understood in polymicrobial infections that are typical of CF. To study this, we exposed P. aeruginosa to sublethal concentrations of ciprofloxacin, colistin, or tobramycin antibiotics in the absence and presence of a commonly co-occurring CF species, Stenotrophomonas maltophilia. We found that low-level antibiotic concentrations selected for high-level antibiotic resistance. While P. aeruginosa dominated in most antibiotic treatments, S. maltophilia drove it into extinction in the presence of tobramycin due to an innately higher tobramycin resistance. Our findings suggest that, besides driving high-level antibiotic tolerance evolution, sublethal antibiotic exposure can magnify competition in bacterial communities, which can lead to target pathogen extinctions in multispecies communities.

Integration of Aspergillus niger transcriptomic profile with metabolic model identifies potential targets to optimise citric acid production from lignocellulosic hydrolysate.

BACKGROUND: Citric acid is typically produced industrially by Aspergillus niger-mediated fermentation of a sucrose-based feedstock, such as molasses. The fungus Aspergillus niger has the potential to utilise lignocellulosic biomass, such as bagasse, for industrial-scale citric acid production, but realising this potential requires strain optimisation. Systems biology can accelerate strain engineering by systematic target identification, facilitated by methods for the integration of omics data into a high-quality metabolic model. In this work, we perform transcriptomic analysis to determine the temporal expression changes during fermentation of bagasse hydrolysate and develop an evolutionary algorithm to integrate the transcriptomic data with the available metabolic model to identify potential targets for strain engineering. RESULTS: The novel integrated procedure matures our understanding of suboptimal citric acid production and reveals potential targets for strain engineering, including targets consistent with the literature such as the up-regulation of citrate export and pyruvate carboxylase as well as novel targets such as the down-regulation of inorganic diphosphatase. CONCLUSIONS: In this study, we demonstrate the production of citric acid from lignocellulosic hydrolysate and show how transcriptomic data across multiple timepoints can be coupled with evolutionary and metabolic modelling to identify potential targets for further engineering to maximise productivity from a chosen feedstock. The in silico strategies employed in this study can be applied to other biotechnological goals, assisting efforts to harness the potential of microorganisms for bio-based production of valuable chemicals.

Inter-species interactions alter antibiotic efficacy in bacterial communities.

The efficacy of antibiotic treatments targeting polymicrobial communities is not well predicted by conventional in vitro susceptibility testing based on determining minimum inhibitory concentration (MIC) in monocultures. One reason for this is that inter-species interactions can alter the community members' susceptibility to antibiotics. Here we quantify, and identify mechanisms for, community-modulated changes of efficacy for clinically relevant antibiotics against the pathogen Pseudomonas aeruginosa in model cystic fibrosis (CF) lung communities derived from clinical samples. We demonstrate that multi-drug resistant Stenotrophomonas maltophilia can provide high levels of antibiotic protection to otherwise sensitive P. aeruginosa. Exposure protection to imipenem was provided by chromosomally encoded metallo-ß-lactamase that detoxified the environment; protection was dependent upon S. maltophilia cell density and was provided by S. maltophilia strains isolated from CF sputum, increasing the MIC of P. aeruginosa by up to 16-fold. In contrast, the presence of S. maltophilia provided no protection against meropenem, another routinely used carbapenem. Mathematical ordinary differential equation modelling shows that the level of exposure protection provided against different carbapenems can be explained by differences in antibiotic efficacy and inactivation rate. Together, these findings reveal that exploitation of pre-occurring antimicrobial resistance, and inter-specific competition, can have large impacts on pathogen antibiotic susceptibility, highlighting the importance of microbial ecology for designing successful antibiotic treatments for multispecies communities.

Computational Modeling of Glycan Processing in the Golgi for Investigating Changes in the Arrangements of Biosynthetic Enzymes.

Modeling glycan biosynthesis is becoming increasingly important due to the far-reaching implications that glycosylation can exhibit, from pathologies to biopharmaceutical manufacturing. Here we describe a stochastic simulation approach, to overcome the deterministic nature of previous models, that aims to simulate the action of glycan modifying enzymes to produce a glycan profile. This is then coupled with an approximate Bayesian computation methodology to systematically fit to empirical data in order to determine which set of parameters adequately describes the organization of enzymes within the Golgi. The model is described in detail along with a proof of concept and therapeutic applications.

Plasmid fitness costs are caused by specific genetic conflicts enabling resolution by compensatory mutation.

Plasmids play an important role in bacterial genome evolution by transferring genes between lineages. Fitness costs associated with plasmid carriage are expected to be a barrier to gene exchange, but the causes of plasmid fitness costs are poorly understood. Single compensatory mutations are often sufficient to completely ameliorate plasmid fitness costs, suggesting that such costs are caused by specific genetic conflicts rather than generic properties of plasmids, such as their size, metabolic burden, or gene expression level. By combining the results of experimental evolution with genetics and transcriptomics, we show here that fitness costs of 2 divergent large plasmids in Pseudomonas fluorescens are caused by inducing maladaptive expression of a chromosomal tailocin toxin operon. Mutations in single genes unrelated to the toxin operon, and located on either the chromosome or the plasmid, ameliorated the disruption associated with plasmid carriage. We identify one of these compensatory loci, the chromosomal gene PFLU4242, as the key mediator of the fitness costs of both plasmids, with the other compensatory loci either reducing expression of this gene or mitigating its deleterious effects by up-regulating a putative plasmid-borne ParAB operon. The chromosomal mobile genetic element Tn6291, which uses plasmids for transmission, remained up-regulated even in compensated strains, suggesting that mobile genetic elements communicate through pathways independent of general physiological disruption. Plasmid fitness costs caused by specific genetic conflicts are unlikely to act as a long-term barrier to horizontal gene transfer (HGT) due to their propensity for amelioration by single compensatory mutations, helping to explain why plasmids are so common in bacterial genomes.

Rapid compensatory evolution can rescue low fitness symbioses following partner switching.

Partner switching plays an important role in the evolution of symbiosis, enabling local adaptation and recovery from the breakdown of symbiosis. Because of intergenomic epistasis, partner-switched symbioses may possess novel combinations of phenotypes but may also exhibit low fitness due to their lack of recent coevolutionary history. Here, we examine the structure and mechanisms of intergenomic epistasis in the Paramecium-Chlorella symbiosis and test whether compensatory evolution can rescue initially low fitness partner-switched symbioses. Using partner-switch experiments coupled with metabolomics, we show evidence for intergenomic epistasis wherein low fitness is associated with elevated symbiont stress responses either in dark or high irradiance environments, potentially owing to mismatched light management traits between the host and symbiont genotypes. Experimental evolution under high light conditions revealed that an initially low fitness partner-switched non-native host-symbiont pairing rapidly adapted, gaining fitness equivalent to the native host-symbiont pairing in less than 50 host generations. Compensatory evolution took two alternative routes: either hosts evolved higher symbiont loads to mitigate for their new algal symbiont's poor performance, or the algal symbionts themselves evolved higher investment in photosynthesis and photoprotective traits to better mitigate light stress. These findings suggest that partner switching combined with rapid compensatory evolution can enable the recovery and local adaptation of symbioses in response to changing environments.

Simulating the evolutionary trajectories of metabolic pathways for insect symbionts in the genus Sodalis.

Insect-bacterial symbioses are ubiquitous, but there is still much to uncover about how these relationships establish, persist and evolve. The tsetse endosymbiont Sodalis glossinidius displays intriguing metabolic adaptations to its microenvironment, but the process by which this relationship evolved remains to be elucidated. The recent chance discovery of the free-living species of the genus Sodalis, Sodalis praecaptivus, provides a serendipitous starting point from which to investigate the evolution of this symbiosis. Here, we present a flux balance model for S. praecaptivus and empirically verify its predictions. Metabolic modelling is used in combination with a multi-objective evolutionary algorithm to explore the trajectories that S. glossinidius may have undertaken from this starting point after becoming internalized. The order in which key genes are lost is shown to influence the evolved populations, providing possible targets for future in vitro genetic manipulation. This method provides a detailed perspective on possible evolutionary trajectories for S. glossinidius in this fundamental process of evolutionary and ecological change.

In silico evolution of Aspergillus niger organic acid production suggests strategies for switching acid output.

BACKGROUND: The fungus Aspergillus niger is an important industrial organism for citric acid fermentation; one of the most efficient biotechnological processes. Previously we introduced a dynamic model that captures this process in the industrially relevant batch fermentation setting, providing a more accurate predictive platform to guide targeted engineering. In this article we exploit this dynamic modelling framework, coupled with a robust genetic algorithm for the in silico evolution of A. niger organic acid production, to provide solutions to complex evolutionary goals involving a multiplicity of targets and beyond the reach of simple Boolean gene deletions. We base this work on the latest metabolic models of the parent citric acid producing strain ATCC1015 dedicated to organic acid production with the required exhaustive genomic coverage needed to perform exploratory in silico evolution. RESULTS: With the use of our informed evolutionary framework, we demonstrate targeted changes that induce a complete switch of acid output from citric to numerous different commercially valuable target organic acids including succinic acid. We highlight the key changes in flux patterns that occur in each case, suggesting potentially valuable targets for engineering. We also show that optimum acid productivity is achieved through a balance of organic acid and biomass production, requiring finely tuned flux constraints that give a growth rate optimal for productivity. CONCLUSIONS: This study shows how a genome-scale metabolic model can be integrated with dynamic modelling and metaheuristic algorithms to provide solutions to complex metabolic engineering goals of industrial importance. This framework for in silico guided engineering, based on the dynamic batch growth relevant to industrial processes, offers considerable potential for future endeavours focused on the engineering of organisms to produce valuable products.

Comparison of Independent Evolutionary Origins Reveals Both Convergence and Divergence in the Metabolic Mechanisms of Symbiosis.

Through the merger of previously independent lineages, symbiosis promotes the acquisition of new traits and exploitation of inaccessible ecological niches [1, 2], driving evolutionary innovation and important ecosystem functions [3-6]. The transient nature of establishment makes study of symbiotic origins difficult, but experimental comparison of independent origins could reveal the degree of convergence in the underpinning mechanisms [7, 8]. We compared the metabolic mechanisms of two independent origins of Paramecium bursaria-Chlorella photosymbiosis [9-11] using a reciprocal metabolomic pulse-chase method. This showed convergent patterns of nutrient exchange and utilization for host-derived nitrogen in the Chlorella genotypes [12, 13] and symbiont-derived carbon in the P. bursaria genotypes [14, 15]. Consistent with a convergent primary nutrient exchange, partner-switched host-symbiont pairings were functional. Direct competition of hosts containing native or recombined symbionts against isogenic symbiont-free hosts showed that the fitness benefits of symbiosis for hosts increased with irradiance but varied by genotype. Global metabolism varied more between the Chlorella than the P. bursaria genotypes and suggested divergent mechanisms of light management. Specifically, the algal symbiont genotypes either produced photo-protective carotenoid pigments at high irradiance or more chlorophyll, resulting in corresponding differences in photosynthetic efficiency and non-photochemical quenching among host-symbiont pairings. These data suggest that the multiple origins of P. bursaria-Chlorella symbiosis use a convergent nutrient exchange, whereas other photosynthetic traits linked to functioning of photosymbiosis have diverged. Although convergence enables partner switching among diverse strains, phenotypic mismatches resulting from divergence of secondary symbiotic traits could mediate host-symbiont specificity in nature.

Spatial Organization of Expanding Bacterial Colonies Is Affected by Contact-Dependent Growth Inhibition.

Identifying how microbes are able to manipulate, survive, and thrive in complex multispecies communities has expanded our understanding of how microbial ecosystems impact human health and the environment. The ability of bacteria to negatively affect neighbors, through explicit toxin delivery systems, provides them with an opportunity to manipulate the composition of growing microbial communities. Contact-dependent inhibition (CDI) systems (a Type Vb secretion system) are a distinct subset of competition systems whose contribution to shaping the development of spatially structured bacterial communities are yet to be fully understood. Here, we compare the impact of different CDI systems, at both the single-cell and population level, to determine the key drivers of CDI-mediated competition within spatially structured bacterial populations. Through an iterative approach using both an Escherichia coli experimental system and computational modeling, we show that CDI systems have subtle and system-specific effects at the single-cell level, generating single-cell-wide boundaries between CDI-expressing inhibitor cells and their neighboring targets. Despite the subtle effects of CDI at a single-cell level, CDI systems greatly diminished the ability of susceptible targets to expand their range during colony growth. The inoculum density of the population, together with the CDI system-specific variables of the speed of inhibition after contact and biological cost of CDI, strongly affects CDI-mediated competition. In contrast, the magnitude of the toxin-induced growth retardation of target cells only weakly impacts the composition of the population. Our work reveals how distinct CDI systems can differentially affect the composition and spatial arrangement of bacterial populations.

The N-Glycosylation Processing Potential of the Mammalian Golgi Apparatus.

Heterogeneity is an inherent feature of the glycosylation process. Mammalian cells often produce a variety of glycan structures on separate molecules of the same protein, known as glycoforms. This heterogeneity is not random but is controlled by the organization of the glycosylation machinery in the Golgi cisternae. In this work, we use a computational model of the N-glycosylation process to probe how the organization of the glycosylation machinery into different cisternae drives N-glycan biosynthesis toward differing degrees of heterogeneity. Using this model, we demonstrate the N-glycosylation potential and limits of the mammalian Golgi apparatus, for example how the number of cisternae limits the goal of achieving near homogeneity for N-glycans. The production of specific glycoforms guided by this computational study could pave the way for "glycoform engineering," which will find uses in the functional investigation of glycans, the modulation of glycan-mediated physiological functions, and in biotechnology.

The role of exploitation in the establishment of mutualistic microbial symbioses.

Evolutionary theory suggests that the conditions required for the establishment of mutualistic symbioses through mutualism alone are highly restrictive, often requiring the evolution of complex stabilising mechanisms. Exploitation, whereby initially the host benefits at the expense of its symbiotic partner and mutual benefits evolve subsequently through trade-offs, offers an arguably simpler route to the establishment of mutualistic symbiosis. In this review, we discuss the theoretical and experimental evidence supporting a role for host exploitation in the establishment and evolution of mutualistic microbial symbioses, including data from both extant and experimentally evolved symbioses. We conclude that exploitation rather than mutualism may often explain the origin of mutualistic microbial symbioses.

Fine-scale behavioural adjustments of prey on a continuum of risk.

In the wild, prey species often live in the vicinity of predators, rendering the ability to assess risk on a moment-to-moment basis crucial to survival. Visual cues are important as they allow prey to assess predator species, size, proximity and behaviour. However, few studies have explicitly examined prey's ability to assess risk based on predator behaviour and orientation. Using mosquitofish, Gambusia holbrooki, and their predator, jade perch, Scortum barcoo, under controlled conditions, we provide some of the first fine-scale characterization of how prey adapt their behaviour according to their continuous assessment of risk based on both predator behaviour and angular distance to the predator's mouth. When these predators were inactive and posed less of an immediate threat, prey within the attack cone of the predator showed reductions in speed and acceleration characteristic of predator-inspection behaviour. However, when predators became active, prey swam faster with greater acceleration and were closer together within the attack cone of predators. Most importantly, this study provides evidence that prey do not adopt a uniform response to the presence of a predator. Instead, we demonstrate that prey are capable of rapidly and dynamically updating their assessment of risk and showing fine-scale adjustments to their behaviour.

Modeling Glycan Processing Reveals Golgi-Enzyme Homeostasis upon Trafficking Defects and Cellular Differentiation.

The decoration of proteins by carbohydrates is essential for eukaryotic life yet heterogeneous due to a lack of biosynthetic templates. This complex carbohydrate mixture-the glycan profile-is generated in the compartmentalized Golgi, in which level and localization of glycosylation enzymes are key determinants. Here, we develop and validate a computational model for glycan biosynthesis to probe how the biosynthetic machinery creates different glycan profiles. We combined stochastic modeling with Bayesian fitting that enables rigorous comparison to experimental data despite starting with uncertain initial parameters. This is an important development in the field of glycan modeling, which revealed biological insights about the glycosylation machinery in altered cellular states. We experimentally validated changes in N-linked glycan-modifying enzymes in cells with perturbed intra-Golgi-enzyme sorting and the predicted glycan-branching activity during osteogenesis. Our model can provide detailed information on altered biosynthetic paths, with potential for advancing treatments for glycosylation-related diseases and glyco-engineering of cells.

A Tale of Three Species: Adaptation of Sodalis glossinidius to Tsetse Biology, Wigglesworthia Metabolism, and Host Diet.

The tsetse fly is the insect vector for the Trypanosoma brucei parasite, the causative agent of human African trypanosomiasis. The colonization and spread of the trypanosome correlate positively with the presence of a secondary symbiotic bacterium, Sodalis glossinidius The metabolic requirements and interactions of the bacterium with its host are poorly understood, and herein we describe a metabolic model of S. glossinidius metabolism. The model enabled the design and experimental verification of a defined medium that supports S. glossinidius growth ex vivo This has been used subsequently to analyze in vitro aspects of S. glossinidius metabolism, revealing multiple unique adaptations of the symbiont to its environment. Continued dependence on a sugar, and the importance of the chitin monomer N-acetyl-d-glucosamine as a carbon and energy source, suggests adaptation to host-derived molecules. Adaptation to the amino acid-rich blood diet is revealed by a strong dependence on l-glutamate as a source of carbon and nitrogen and by the ability to rescue a predicted l-arginine auxotrophy. Finally, the selective loss of thiamine biosynthesis, a vitamin provided to the host by the primary symbiont Wigglesworthia glossinidia, reveals an intersymbiont dependence. The reductive evolution of S. glossinidius to exploit environmentally derived metabolites has resulted in multiple weaknesses in the metabolic network. These weaknesses may become targets for reagents that inhibit S. glossinidius growth and aid the reduction of trypanosomal transmission.IMPORTANCE Human African trypanosomiasis is caused by the Trypanosoma brucei parasite. The tsetse fly vector is of interest for its potential to prevent disease spread, as it is essential for T. brucei life cycle progression and transmission. The tsetse's mutualistic endosymbiont Sodalis glossinidius has a link to trypanosome establishment, providing a disease control target. Here, we describe a new, experimentally verified model of S. glossinidius metabolism. This model has enabled the development of a defined growth medium that was used successfully to test aspects of S. glossinidius metabolism. We present S. glossinidius as uniquely adapted to life in the tsetse, through its reliance on the blood diet and host-derived sugars. Additionally, S. glossinidius has adapted to the tsetse's obligate symbiont Wigglesworthia glossinidia by scavenging a vitamin it produces for the insect. This work highlights the use of metabolic modeling to design defined growth media for symbiotic bacteria and may provide novel inhibitory targets to block trypanosome transmission.

Temporal dynamics of bacteria-plasmid coevolution under antibiotic selection.

Horizontally acquired genes can be costly to express even if they encode useful traits, such as antibiotic resistance. We previously showed that when selected with tetracycline, Escherichia coli carrying the tetracycline-resistance plasmid RK2 evolved mutations on both replicons that together provided increased tetracycline resistance at reduced cost. Here we investigate the temporal dynamics of this intragenomic coevolution. Using genome sequencing we show that the order of adaptive mutations was highly repeatable across three independently evolving populations. Each population first gained a chromosomal mutation in ompF which shortened lag phase and increased tetracycline resistance. This was followed by mutations impairing the plasmid-encoded tetracycline efflux pump, and finally, additional resistance-associated chromosomal mutations. Thus, reducing the cost of the horizontally acquired tetracycline resistance was contingent on first evolving a degree of chromosomally encoded resistance. We conclude therefore that the trajectory of bacteria-plasmid coevolution was constrained to a single repeatable path.

Variation and asymmetry in host-symbiont dependence in a microbial symbiosis.

BACKGROUND: Symbiosis is a major source of evolutionary innovation and, by allowing species to exploit new ecological niches, underpins the functioning of ecosystems. The transition from free-living to obligate symbiosis requires the alignment of the partners' fitness interests and the evolution of mutual dependence. While symbiotic taxa are known to vary widely in the extent of host-symbiont dependence, rather less is known about variation within symbiotic associations. RESULTS: Using experiments with the microbial symbiosis between the protist Paramecium bursaria and the alga Chlorella, we show variation between pairings in host-symbiont dependence, encompassing facultative associations, mutual dependence and host dependence upon the symbiont. Facultative associations, that is where both the host and the symbiont were capable of free-living growth, displayed higher symbiotic growth rates and higher per host symbiont loads than those with greater degrees of dependence. CONCLUSIONS: These data show that the Paramecium-Chlorella interaction exists at the boundary between facultative and obligate symbiosis, and further suggest that the host is more likely to evolve dependence than the algal symbiont.

An accurate description of Aspergillus niger organic acid batch fermentation through dynamic metabolic modelling.

BACKGROUND: Aspergillus niger fermentation has provided the chief source of industrial citric acid for over 50 years. Traditional strain development of this organism was achieved through random mutagenesis, but advances in genomics have enabled the development of genome-scale metabolic modelling that can be used to make predictive improvements in fermentation performance. The parent citric acid-producing strain of A. niger, ATCC 1015, has been described previously by a genome-scale metabolic model that encapsulates its response to ambient pH. Here, we report the development of a novel double optimisation modelling approach that generates time-dependent citric acid fermentation using dynamic flux balance analysis. RESULTS: The output from this model shows a good match with empirical fermentation data. Our studies suggest that citric acid production commences upon a switch to phosphate-limited growth and this is validated by fitting to empirical data, which confirms the diauxic growth behaviour and the role of phosphate storage as polyphosphate. CONCLUSIONS: The calibrated time-course model reflects observed metabolic events and generates reliable in silico data for industrially relevant fermentative time series, and for the behaviour of engineered strains suggesting that our approach can be used as a powerful tool for predictive metabolic engineering.