Microbial Cell Factories

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. Published: 02 November 2006 Microbial Cell Factories 2006, 5:32 doi:10.1186/1475-2859-5-32 Received: 10 October 2006 Accepted: 02 November 2006 This article is available from: http://www.microbialcellfactories.com/content/5/1/32 © 2006 Bapat et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Microbial Cell Factories 2006, 5:32 http://www.microbialcellfactories.com/content/5/1/32 Page 2 of 14 (page number not for citation purposes) Background Majority of the industrial fermentations employ a batch or a fed batch process with complex media that offers multiple substitutable substrates [1]. The batch process goes through several distinct phases of fermentation during the batch cycle. Even small changes in the substrate concentration during the crucial phase of the batch may significantly affect the product yield and quality[2,3]. One of the major nutrient source in a complex medium is the pool of amino acids, peptides and proteins derived from the organic nitrogen substrates such as soybean flour, yeast extract, corn steep liquor, etc. Thus, it is of interest to understand the pattern of uptake of the amino acids during industrially important fermentation processes. The regulation of uptake of nitrogen substrates has been studied extensively in prokaryotes [4-11] and lower eukaryotes such as Saccharomyces cerevisiae [12-16] and the filamentous fungus Aspergillus nidulans [17-20]. These organisms regulate the amino acid uptake through a multiplicity of amino acid transporters (permeases). Different amino acid transporters differ in their substrate specificities, uptake capacities and the mode of regulation [21]. All fungal and several of the bacterial amino acid transporters show significant sequence similarities, suggesting a unique transporter family conserved across the prokaryotic-eukaryotic boundary [17]. Most of the transporters are specific for one or a few related L-amino acids. In addition, several organisms such as Saccharomyces cerevisiae, Aspergillus nidulans, Penicillum chrysogenum and Neurospora crassa possess a broad specificity, large capacity, general amino acid permease (GAP) mediating the uptake of most Land D-amino acids, non proteinogenic amino acids such as citrulline, ornithine and a number of amino acid analogs [21-24]. Most microorganisms thus possess multiple transport systems with partially overlapping specificities. Although regulation of amino acid transporters in yeast and fungi operates mainly at the level of transcription, post transcriptional, translational and posttranslational regulation has been reported [12,13,16,25,26]. The transcriptional regulation includes nitrogen catabolite repression, carbon catabolite repression and regulation in response to amino acid availability[21]. Many specific permeases in Saccharomyces cerevisiae have been reported to be expressed constitutively [27]. However, this is not a general rule for microbial eukaryotes. For example, proline permease encoded by the prn B gene in Aspergillus nidulans is highly inducible [21]. Proline can act as both a carbon source and nitrogen source. Thus, the efficiency of prn B expression is highly dependent on the presence of other carbon and nitrogen substrates in the medium, possibly regulated via nitrogen catabolite and carbon catabolite repression. Likewise, the L-serine permease in Saccharomyces cerevisiae and Eschirichia coli is inducible as L-serine being its only substrate and inducer [10,21]. Its activity is highly regulated by nitrogen sources, with low activity in the presence of ammonia and substantially increased activity in nitrogen starved cells. Most of the industrial fermentations involving actinomycetes employ a mixture of inorganic and organic nitrogen substrates. For the commercially important actinomycete fermentations, the sequence of uptake of amino acids and the underlying mechanism of regulation has not been reported. It is of interest to predict the sequence of uptake of an amino acid and its implication on product formation under various nitrogen substrate combinations. We have chosen to study the amino acid uptake in a rifamycin B over-producer strain of Amycolatopsis mediterranei S699. Rifamycin B is an important antitubercular antibiotic [28] while Amycolatopsis mediterranei S699 is an Actinomycete, a species that is a source of a majority of marketed antibiotics [29]. We note that this strain is not an amino acid auxotroph and can grow on ammonia as a sole nitrogen substrate [30,31]. The cybernetic model presented here assumes that the uptake of each amino acid is aided by a key enzyme, which is subject to induction by substrate and nitrogen catabolite repression. Physiologically this enzyme could be an amino acid transporter or permease. Through a model-driven experimental analysis we address the following key questions: (i) what is the stoichiometry and sequence of amino acid uptake in a batch fermentation of Amycolatopsis mediterranei? (ii) is the sequence of uptake dependent on the amino acid abundance in the medium? (iii) what is the likely multiplicity of the transporters in Amycolatopsis mediterranei? (iv) how the presence of different nitrogen substrates affect product formation? Results Amino acids can be assimilated as sole source of carbon and nitrogen during the microbial growth. To verify this with our model strain Amycolatopsis mediterranei S699, we set up preliminary growth experiments with amino acids mixture with or without glucose as a carbon source. First, we studied the pattern of uptake of amino acids in batch fermentations with (i) a defined medium containing 3.25 mM of each of the 20 amino acids being the sole source of carbon and nitrogen and (ii) medium with amino acids as in (i) along with 80 g.l-1 glucose. The concentration of amino acids was chosen so as to keep the initial total nitrogen below 1.5 g.l-1, as well as to provide glucose and the mixture of amino acids in approximate stoichiometric proportion as carbon and nitrogen substrates respectively. The results of these two experiments were used to obtain the stoichiometric and kinetic parameters. Subsequently, the model was verified on semi synthetic medium containing 80 g.l-1 glucose supplemented with different concentration of cas amino acids. Microbial Cell Factories 2006, 5:32 http://www.microbialcellfactories.com/content/5/1/32 Page 3 of 14 (page number not for citation purposes) Model fit for defined medium The results of the experiments with amino acids as the sole source of carbon and nitrogen are presented in figure 1(A– F). We found that although growth occurred in the absence of glucose; rifamycin B was not detected throughout the fermentation batch. In first 20 hrs, lysine, glutamic acid, aspartic acid, glycine and threonine were utilized. This was followed by the utilization of isoluecine, leucine, alanine, valine, phenyl alanine, methionine and proline. The concentration of ammonia in the fermentation broth continued to increase during the course of uptake of amino acids (data not shown). Interestingly, sudden arrest in the utilization of amino acids was observed around 60 hrs. This may possibly be due to the inhibition of growth by the accumulated ammonia (data not shown), a similar observation was reported by Xie and Wang [32] for animal cell cultivation on amino acids. In industrial fermentation, stoichiometric coefficients are the crucial parameters for the process optimization [33]. From the profiles of glucose, amino acids, CO2, biomass and ammonia obtained during shake flask and reactor experiments, we estimated the stoichiometric coefficients of equation 1 and 2. The yield coefficients for amino acids, ammonia and glucose are given in Table 1. The biomass yield coefficient was low when organism utilizes amino acids as a sole source of carbon and nitrogen, whereas it was high where glucose was primary carbon source. The biomass yields on amino acids and ammonia were similar. Interestingly, biomass yield on glucose was Amino acids uptake profile in medium containing equimolar mixture of amino acids Figure 1 Amino acids uptake profile in medium containing equimolar mixture of amino acids. Amycolatopsis mediterranei S699 was cultivated in a media containing mixture of amino acids at a concentration of 3.25 mM each. Besides this, fermentation medium contained, 11 gl-1 CaCO3, 1 gl-1 KH2PO4, 1 gl-1 MgSO4, 0.01 gl-1 FeSO4, 0.05 gl-1 ZnSO4 and 0.003 gl-1 COCl2. For more information, please refer materials and method section. Microbial Cell Factories 2006, 5:32 http://www.microbialcellfactories.com/content/5/1/32 Page 4 of 14 (page number not for citation purposes) significantly influenced by the nitrogen source used. The estimated stoichiometric coefficients are in agreement with the previous reports on E.coli and S.cerevisiae [34-36]. The kinetic parameters of the model were estimated by fitting the model equations to amino acid, glucose, biomass as well as product formation profiles. The R2 values, a measure of the goodness of fit of the model, were in the range of 0.90 to 0.95 for amino acid profiles. The specific growth rates measured for the individual amino acids (μ1) were in the range of 1 × 10-4 to 0.39 h-1 (Table 2). The amino acids which support a higher specific growth rate were utilized first. For example, the μmax values for lysine, glutamic acid, aspartic acid, glycine and threonine were much greater than those for isoleucine, leucine, phenylalanine and methionine. The μmax for valine was among the lowest indicating strong substrate inhibition; a similar observation was reported by Schimidt and coworkers for a nitrifying bacterium Nitrosomonas europaea [37]. The amino acids uptake profile was then studied in the presence of glucose as a primary carbon substrate (Figure 2). The organism can utilize (i) amino acid as the sole substrate of carbon thereby leading to ammonia accumulation (equ 1), (ii) amino acid along with glucose (equ 2) and (iii) glucose along with ammonia that may be formed as a product of reaction 1 (equ 3). We found that the organism takes up amino acids as the sole substrate for the first 20 hours. Model predictions for the amino acids uptake profile shows a reasonably good fit with the experimental data. Specifically, histidine, aspartic acid, lysine, glutamic acid and threonine were taken up first as observed in the case where amino acids were the sole source of carbon and nitrogen. Ammonia accumulation was detected during this period at a maximum concentration of 0.010 moles of ammonia.l-1(data not shown). Subsequently, growth reactions proceed via reaction 2 and 3 with simultaneous uptake of amino acids, ammonia and glucose. During this period, ammonia, serine, isoleucine, phenylalanine, methionine, leucine, proline, valine, glycine and alanine were taken up simultaneously and exhausted by 60 hours leading to nitrogen limitation in the batch. Rifamycin B production was concomitant with the utilization of glucose (data not shown). Finally, 0.035 moles.l-1 rifamycin B was formed, while 0.28 moles.l-1 glucose remain unutilized in this batch. Model validation on semi synthetic media The model predictions were experimentally validated on glucose minimal medium supplemented with 5 g.l-1 cas amino acids (Figure 3) and 15 g.l-1 cas amino acids (Figure 4). Note that the relative proportions of the different amino acids in cas are significantly different from that in the synthetic medium described above. The model was able to accurately predict the uptake pattern of amino acids in both the cases. Similar to the synthetic medium, the first 20 hours of the batch were marked by the uptake of amino acids as the sole substrate followed by the simultaneous uptake of amino acids, ammonia and glucose. For 5 g.l-1 cas amino acids, model accurately predicted the uptake profile for almost all amino acids except methionine. As observed from the Figure 3B, model tends to over-estimate the utilization of methionine after 40 hrs. On the other hand, for 15 g.l-1 cas amino acids, the model predicted values deviated from the experimentally observed uptake of phenylalanine, alanine (after 60 hrs), and methionine (after 20 hrs) (Figures 4E and 4F). It may be noted that the cas amino acids contain a relatively higher amount of proline than that used in the defined medium. For 5 g.l-1 cas amino acids, although the amino acids got exhausted in the same sequence as in the defined medium, the utilization of all the amino acids started simultaneously within the first 10 hrs of the batch cycle. Interestingly for 15 g.l-1 cas amino acids (Figure 4) the uptake of amino acids followed a pattern similar to those in the synthetic medium and 5 g.l-1 cas amino acids, albeit with longer lag periods for the utilization of some of the Table 1: Stoichiometric coefficients for batch fermentation of rifamycin B using Amycolatopsis maditerranei S699 Stoichiometric coefficientsa (moles of substrate. C-mole of biomass-1) Amino acids Glucose and amino acids Glucose and ammonia Y1,1,k = 0.51 Y2,1,k = 0.13 Y3,2 = 0.35 Y1,3 = 1.30 Y2,2 = 0.24 Y3,6 = 0.16 Y1,6 = 0.85 Y2,3 = 1.10 a Amycolatopsis mediterranei S699 was cultivated in two media compositions. (i) Containing mixture of amino acids at a concentraton of 3.25 mM each and (ii) medium (i) supplemented wih glucose (80 g.l-1). Both the media were supplemented with 11 gl-1 CaCO3, 1 gl-1 KH2PO4, 1 gl-1 MgSO4, 0.01 gl-1 FeSO4, 0.05 gl-1 ZnSO4 and 0.003 gl-1 COCl2. Samples were taken at regular intervals to estimate concentrations of amino acids, rifamycin B, biomass, residual ammonia and glucose. Online data such as vent CO2 and dissolved oxygen was obtained from exit gas analyzer. The offline and online data was further used to estimate stoichiometric coefficients on respective substrate assimilation modes. Y i,j are stoichiometric coefficients where i is reaction number (refer equations in materials and methods) and j is the substrate for example : Amino acid (1) where k represents 20 different amino acids, glucose (2), CO2 (3), O2 (4), H2O (5), Ammonia (6). M i c r o b i a l C e l l F a c t o r i e s 2 0 0 6 , 5 : 3 2 h t t p : / / w w w . m i c r o b i a l c e l l f a c t o r i e s . c o m / c o n t e n t / 5 / 1 / 3 2