A universal fixation method based on quaternary ammonium salts (RNAlater) for omics-technologies: Saccharomyces cerevisiae as a case study.

Genomics, transcriptomics, proteomics and fluxomics are powerful omics-technologies that play a major role in today's research. For each of these techniques good sample quality is crucial. Major factors contributing to the quality of a sample is the actual sampling procedure itself and the way the sample is stored directly after sampling. It has already been described that RNAlater can be used to store tissues and cells in a way that the RNA quality and quantity are preserved. In this paper, we demonstrate that quaternary ammonium salts (RNAlater) are also suitable to preserve and store samples from Saccharomyces cerevisiae for later use with the four major omics-technologies. Moreover, it is shown that RNAlater also preserves the cell morphology and the potential to recover growth, permitting microscopic analysis and yeast cell culturing at a later stage.

Metabolic flexibility of D-ribose producer strain of Bacillus pumilus under environmental perturbations.

The metabolic reaction rate vector is a bridge that links gene and protein expression alterations to the phenotypic endpoint. We present a simple approach for the estimation of flux distribution at key branch points in the metabolic network by using substrate uptake, metabolite secretion rate, and biomass growth rate for transketolase (tkt) deficient Bacillus pumilus ATCC 21951. We find that the glucose-6-phosphate (G6P) and pseudo catabolic/anabolic branch points are flexible in the D: -ribose-producing tkt deficient strain of B. pumilus. The normalized flux through the pentose phosphate pathway (PPP) varied from 1.5 to 86 % under different growth conditions, thereby enabling substantial extracellular accumulation of D: -ribose under certain conditions. Interestingly, the flux through PPP was affected by the extracellular phosphate concentration and dissolved oxygen concentration. This metabolic flexibility may have been the underlying reason for this strain being selected from thousands of others in a screening for D: -ribose producers conducted in the 1970s.

Role of extracellular protease in nitrogen substrate management during antibiotic fermentation: a process model and experimental validation.

Kinetics of extracellular protease (ECP) production has typically been studied for processes that involve protease as a product. We argue that ECP is equally important in fermentations where protease is not a product of interest. Industrial fermentations typically use complex nitrogen substrates, which are proteolytically hydrolyzed to amino acids (AA) by ECP before assimilation. However, high AA concentrations may lead to nitrogen catabolite repression (NCR) of the products such as antibiotics. Thus, ECP plays a crucial role in managing the nitrogen substrate supply thereby affecting the antibiotic productivity. Here, we have studied the induction of ECP and its effect on the antibiotic productivity for a rifamycin B overproducer strain Amycolatopsis meditterranei S699. This organism produces ECP at the level of 14 U mL(-1) in complex media, which is sufficient for hydrolysis of proteins in the media but low compared to other ECP overproducers. We find ECP secretion to be repressed by ammonia, AA, and under conditions that support high growth rate. We propose a structured kinetic model which accounts for the kinetics of ECP secretion, amino acid availability, growth, and antibiotic production. In addition to the quantity, the timing of ECP induction was critical in achieving higher rifamycin productivity. We artificially created conditions that led to delayed protease secretion, which in turn led to premature termination of batch and lower productivity. The predictive value of the model can be useful in better management of the available nitrogen supply, minimization of NCR, and in the monitoring of fermentation batches.

Reducing the variability of antibiotic production in Streptomyces by cultivation in 24-square deepwell plates.

Highly reproducible production values of the aminocoumarin antibiotic novobiocin were achieved by cultivation of a heterologous Streptomyces producer strain in commercially available square deepwell plates consisting of 24 wells of 3 ml culture volume each. Between parallel cultivation batches in the deepwell plates, novobiocin accumulation showed standard deviations of 4-9%, compared to 39% in baffled Erlenmeyer flasks. Mycelia used as inoculum could be frozen in the presence of 20% peptone and stored at -70 degrees C, allowing repeated cultivations from the same batch of inoculum over extended periods of time. Originally, novobiocin titers in the deepwell plate (5-12 mg l(-1)) were lower than in Erlenmeyer flasks (24 mg l(-1)). Optimization of the inoculation procedure as well as addition of a siloxylated ethylene oxide/propylene oxide copolymer, acting as oxygen carrier, to the production medium increased novobiocin production to 54 mg l(-1). The additional overexpression of the pathway-specific positive regulator gene novG increased novobiocin production to 163 mg l(-1). Harvesting the precultures in a defined section of growth phase greatly reduced variability between different batches of inoculum. The use of deepwell plates may considerably reduce the workload and cost of investigations of antibiotic biosynthesis in streptomycetes and other microorganisms due to the high reproducibility and the low requirement for shaker space and culture medium.

Overexpression of a novel endogenous NADH kinase in Aspergillus nidulans enhances growth.

The complete genome sequence of the filamentous fungi Aspergillus nidulans has paved the way for fundamental research on this industrially important species. To the best of our knowledge, this is the first time a gene encoding for ATP-dependent NADH kinase (ATP:NADH 2'-phosphotransferase, EC 2.7.1.86) has been identified. The enzyme has a predicted molecular weight of 49 kDa. We characterised the role of this NADH kinase by genomic integration of the putative gene AN8837.2 under a strong constitutive promoter. The physiological effects of overexpressed NADH kinase in combination with different aeration rates were studied in well-controlled glucose batch fermentations. Metabolite profiling and metabolic network analysis with [1-(13)C] glucose were used for characterisation of the strains, and the results demonstrated that NADH kinase activity has paramount influence on growth physiology. Biomass yield on glucose and the maximum specific growth rate increased from 0.47 g/g and 0.22 h(-1) (wild type) to 0.54 g/g and 0.26 h(-1) (NADH kinase overexpressed), respectively. The results suggest that overexpression of NADH kinase improves the growth efficiency of the cell by increasing the access to NADPH. Our findings indicate that A. nidulans is not optimised for growth in nutrient-rich conditions typically found in laboratory and industrial fermentors. This conclusion may impact the design of new strains capable of generating reducing power in the form of NADPH, which is crucial for efficient production of many industrially important metabolites and enzymes.

Detection of phase shifts in batch fermentation via statistical analysis of the online measurements: a case study with rifamycin B fermentation.

Industrial production of antibiotics, biopharmaceuticals and enzymes is typically carried out via a batch or fed-batch fermentation process. These processes go through various phases based on sequential substrate uptake, growth and product formation, which require monitoring due to the potential batch-to-batch variability. The phase shifts can be identified directly by measuring the concentrations of substrates and products or by morphological examinations under microscope. However, such measurements are cumbersome to obtain. We present a method to identify phase transitions in batch fermentation using readily available online measurements. Our approach is based on Dynamic Principal Component Analysis (DPCA), a multivariate statistical approach that can model the dynamics of non-stationary processes. Phase-transitions in fermentation produce distinct patterns in the DPCA scores, which can be identified as singular points. We illustrate the application of the method to detect transitions such as the onset of exponential growth phase, substrate exhaustion and substrate switching for rifamycin B fermentation batches. Further, we analyze the loading vectors of DPCA model to illustrate the mechanism by which the statistical model accounts for process dynamics. The approach can be readily applied to other industrially important processes and may have implications in online monitoring of fermentation batches in a production facility.

Sporulating bacteria prefers predation to cannibalism in mixed cultures.

Predatory behavior, a property associated with ecosystems, is not commonly observed in microorganisms. However, cannibalistic tendencies have been observed in microorganisms under stress. For example, pure culture of Bacillus subtilis exhibits cannibalism under nutrient limitation. It has been proposed that a fraction of cells in the population produce Spo0A, a regulatory protein that is responsible for delaying sporulation. Cells containing spo0A would produce a killing factor by activating skf operon and an associated pump to export the factor. Cells that do not contain spo0A in the population are lysed. However in addition to the competition among the cells of B. subtilis, these cells also compete with other organisms for the limited nutrients. In this work, we report the cannibalistic behavior of B. subtilis in presence of Escherichia coli under severe nutritional limitation. We demonstrate that B. subtilis lyses cells of E. coli using an antibacterial factor under the regulation of Spo0A. Our experiments also suggest that B. subtilis prefers predation of E. coli to cannibalism in mixed cultures. B. subtilis also demonstrated predation in mixed cultures with other soil microorganisms, such as, Xanthomonas campestris, Pseudomonas aeruginosa and Acinetobactor lwoffi. This may offer B. subtilis a niche to survive in an environment with limited nutrients and under competition from other microorganisms.

Hierarchical amino acid utilization and its influence on fermentation dynamics: rifamycin B fermentation using Amycolatopsis mediterranei S699, a case study.

BACKGROUND: Industrial fermentation typically uses complex nitrogen substrates which consist of mixture of amino acids. The uptake of amino acids is known to be mediated by several amino acid transporters with certain preferences. However, models to predict this preferential uptake are not available. We present the stoichiometry for the utilization of amino acids as a sole carbon and nitrogen substrate or along with glucose as an additional carbon source. In the former case, the excess nitrogen provided by the amino acids is excreted by the organism in the form of ammonia. We have developed a cybernetic model to predict the sequence and kinetics of uptake of amino acids. The model is based on the assumption that the growth on a specific substrate is dependent on key enzyme(s) responsible for the uptake and assimilation of the substrates. These enzymes may be regulated by mechanisms of nitrogen catabolite repression. The model hypothesizes that the organism is an optimal strategist and invests resources for the uptake of a substrate that are proportional to the returns. RESULTS: Stoichiometric coefficients and kinetic parameters of the model were estimated experimentally for Amycolatopsis mediterranei S699, a rifamycin B overproducer. The model was then used to predict the uptake kinetics in a medium containing cas amino acids. In contrast to the other amino acids, the uptake of proline was not affected by the carbon or nitrogen catabolite repression in this strain. The model accurately predicted simultaneous uptake of amino acids at low cas concentrations and sequential uptake at high cas concentrations. The simulated profile of the key enzymes implies the presence of specific transporters for small groups of amino acids. CONCLUSION: The work demonstrates utility of the cybernetic model in predicting the sequence and kinetics of amino acid uptake in a case study involving Amycolatopsis mediterranei, an industrially important organism. This work also throws some light on amino acid transporters and their regulation in A. mediterranei. Further, cybernetic model based experimental strategy unravels formation and utilization of ammonia as well as its inhibitory role during amino acid uptake. Our results have implications for model based optimization and monitoring of other industrial fermentation processes involving complex nitrogen substrate.

Phase shifts in the stoichiometry of rifamycin B fermentation and correlation with the trends in the parameters measured online.

Antibiotic fermentation processes are raw material cost intensive and the profitability is greatly dependent on the product yield per unit substrate consumed. In order to reduce costs, industrial processes use organic nitrogen substrates (ONS) such as corn steep liquor and yeast extract. Thus, although the stoichiometric analysis is the first logical step in process development, it is often difficult to achieve due to the ill-defined nature of the medium. Here, we present a black-box stoichiometric model for rifamycin B production via Amycolatopsis mediterranei S699 fermentation in complex multi-substrate medium. The stoichiometric coefficients have been experimentally evaluated for nine different media compositions. The ONS was quantified in terms of the amino acid content that it provides. Note that the black box stoichiometric model is an overall result of the metabolic reactions that occur during growth. Hence, the observed stoichiometric coefficients are liable to change during the batch cycle. To capture the shifts in stoichiometry, we carried out the stoichiometric analysis over short intervals of 8-16 h in a batch cycle of 100-200 h. An error analysis shows that there are no systematic errors in the measurements and that there are no unaccounted products in the process. The growth stoichiometry shows a shift from one substrate combination to another during the batch cycle. The shifts were observed to correlate well with the shifts in the trends of pH and exit carbon dioxide profiles. To exemplify, the ammonia uptake and nitrate uptake phases were marked by a decreasing pH trend and an increasing pH trend, respectively. Further, we find the product yield per unit carbon substrate to be greatly dependent on the nature of the nitrogen substrate. The analysis presented here can be readily applied to other fermentation systems that employ multi-substrate complex media.

A cybernetic model to predict the effect of freely available nitrogen substrate on rifamycin B production in complex media.

It is well-known that secondary metabolite production is repressed by excess nitrogen substrate available in the fermentation media. Although the nitrogen catabolite repression has been known, quantitative process models have not been reported to represent this phenomenon in complex medium. In this paper, we present a cybernetic model for rifamycin B production via Amycolatopsis mediterranei S699 in complex medium, which is typically used in industry. Nitrogen substrate is assumed to be present in two forms in the medium; available nitrogen (S(ANS)) such as free amino acids and unavailable nitrogen (S(UNS)) such as peptides and proteins. The model assumes that an inducible enzyme catalyzes the conversion of S(UNS) to S(ANS). Although S(ANS) is required for growth and product formation, high concentrations were found to inhibit rifamycin production. To experimentally validate the model, five different organic nitrogen sources were used that differ in the ratio of S(ANS)/S (UNS). The model successfully predicts higher rifamycin B productivity for nitrogen sources that contain lower initial S(ANS). The higher productivity is attributed to the sustained availability of S(ANS) at low concentration via conversion of S(UNS) to S(ANS), thereby minimizing the effects of nitrogen catabolite repression on rifamycin production. The model can have applications in model-based optimization of substrate feeding recipe and in monitoring and control of fed batch processes.

Structured kinetic model to represent the utilization of multiple substrates in complex media during rifamycin B fermentation.

Industrial fermentations typically use media that are balanced with multiple substitutable substrates including complex carbon and nitrogen source. Yet, much of the modeling effort to date has mainly focused on defined media. Here, we present a structured model that accounts for growth and product formation kinetics of rifamycin B fermentation in a multi-substrate complex medium. The phenomenological model considers the organism to be an optimal strategist with an in-built mechanism that regulates the sequential and simultaneous uptake of the substrate combinations. This regulatory process is modeled by assuming that the uptake of a substrate depends on the level of a key enzyme or a set of enzymes, which may be inducible. Further, the fraction of flux through a given metabolic branch is estimated using a simple multi-variable constrained optimization. The model has the typical form of Monod equation with terms incorporating multiple limiting substrates and substrate inhibition. Several batch runs were set up with varying initial substrate concentrations to estimate the kinetic parameters for the rifamycin overproducer strain Amycolatopsis mediterranei S699. Glucose and ammonium sulfate (AMS) demonstrated significant substrate inhibition toward growth as well as product formation. The model correctly predicts the experimentally observed regulated simultaneous uptake of the substitutable substrate combinations under different fermentation conditions. The modeling results may have applications in the optimization and control of rifamycin B fermentation while the modeling strategy presented here would be applicable to other industrially important fermentations.

Optimization of rifamycin B fermentation in shake flasks via a machine-learning-based approach.

Rifamycin B is an important polyketide antibiotic used in the treatment of tuberculosis and leprosy. We present results on medium optimization for Rifamycin B production via a barbital insensitive mutant strain of Amycolatopsis mediterranei S699. Machine-learning approaches such as Genetic algorithm (GA), Neighborhood analysis (NA) and Decision Tree technique (DT) were explored for optimizing the medium composition. Genetic algorithm was applied as a global search algorithm while NA was used for a guided local search and to develop medium predictors. The fermentation medium for Rifamycin B consisted of nine components. A large number of distinct medium compositions are possible by variation of concentration of each component. This presents a large combinatorial search space. Optimization was achieved within five generations via GA as well as NA. These five generations consisted of 178 shake-flask experiments, which is a small fraction of the search space. We detected multiple optima in the form of 11 distinct medium combinations. These medium combinations provided over 600% improvement in Rifamycin B productivity. Genetic algorithm performed better in optimizing fermentation medium as compared to NA. The Decision Tree technique revealed the media-media interactions qualitatively in the form of sets of rules for medium composition that give high as well as low productivity.

An optimized method for Aspergillus niger spore production on natural carrier substrates.

Aspergillus niger spores have wide ranging applications in the fermentation industry as well as in wastewater treatment. We present an optimized method for production of A. niger spores on natural substrates such as rice, split pea, and millet. The specific productivity (number of spores per gram of dry substrate) was 31-fold greater and volumetric productivity was 750-fold greater compared to agar slopes. The important process variables were incubation temperature, moisture content, and inoculum quantity. We find that the optimal condition for total spore count is different from the viable spore count for millet. The optimum lies in a narrow region defined by the process parameters. Of the three substrates tested split pea gave the highest specific spore productivity of 3.1 x 10(10) spores per gram of dry substrate. This is the first report of systematic study on the effect of process parameters on spore viability. The method of A. niger spore production on natural substrate appears advantageous as compared to the currently practiced method in terms of scale-up, cost, and ease of operation.