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.     

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.     

Issues impacting genetic network reverse engineering algorithm validation using small networks

Genetic network reverse engineering has been an area of intensive research within the systems biology community during the last decade. With many techniques currently available, the task of validating them and choosing the best one for a certain problem is a complex issue. Current practice has been to validate an approach on in-silico synthetic data sets, and, wherever possible, on real data sets with known ground-truth. In this study, we highlight a major issue that the validation of reverse engineering algorithms on small benchmark networks very often results in networks which are not statistically better than a randomly picked network. Another important issue highlighted is that with short time series, a small variation in the pre-processing procedure might yield large differences in the inferred networks. To demonstrate these issues, we have selected as our case study the IRMA in-vivo synthetic yeast network recently published in Cell. Using Fisher's exact test, we show that many results reported in the literature on reverse-engineering this network are not significantly better than random. The discussion is further extended to some other networks commonly used for validation purposes in the literature. The results presented in this study emphasize that studies carried out using small genetic networks are likely to be trivial, making it imperative that larger real networks be used for validating and benchmarking purposes. If smaller networks are considered, then the results should be interpreted carefully to avoid over confidence. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.     

Megacell phenotype and its relation to metabolic alterations in transketolase deficient strain of Bacillus pumilus

Fermentation with transketolase (tkt) deficient strain of Bacillus is the only reported industrially viable process for production of D ‐ribose, a commercially important pentose sugar. In addition to direct effects of tkt deficiency, the mutation in non‐oxidative part of pentose phosphate pathway (PPP) is known to display several unexpected physiological characteristics such as decreased ability to utilize D ‐glucose, altered carbon catabolite repression, lack of motility, etc. Here we demonstrate the morphological plasticity of tkt deficient strain of Bacillus pumilus ATCC 21951 and its possible relation with D ‐ribose productivity, a measure of carbon flux through PPP. The bacilli divide normally in nutrient rich media such as Luria–Bertani (LB) broth while showing cell elongation of up to 20‐fold without a visible septum accompanied by moderate to high extracellular D ‐ribose accumulation in glucose‐rich media. The cells stained with DAPI (4′‐6‐diamidino‐2‐phenylindole) and anti FtsZ antibody showed nucleoid separation and Z‐ring formation in LB broth but not in glucose‐rich media. FtsZ protein is known to localize at the future division site forming a ring, called Z‐ring, at an early stage in cytokinesis. The strain experiences inhibition or delay in Z‐ring formation resulting in cell elongation, possibly due to its altered cell membrane composition resulting from tkt deficiency. We hypothesize that the lack of PPP intermediates may have two effects on the strain: (i) altered the cell membrane leading to delay in Z‐ring formation and cell elongation; and (ii) induction of genes of the oxidative part of PPP resulting in D ‐ribose accumulation. Nutrient rich media such as LB broth may alleviate these metabolite deficiencies thereby restoring normal cell division and inhibiting excessive D ‐ribose accumulation. The D ‐ribose productivity and cell elongation may therefore be co‐morbid. The results have implications in designing optimal media and monitoring strategy based on morphological analysis. Biotechnol. Bioeng. 2009;102: 1387–1397. © 2008 Wiley Periodicals, Inc.     

Effect in rats of simultaneous prenatal exposure to ochratoxin A and aflatoxin B1. II. Histopathological features of teratological anomalies induced in fetuses

The histopathological features of various abnormalities induced by different doses of ochratoxin A (OA), aflatoxin B1 (AFB1), and their combination in rat fetuses were studied. The pregnant Wistar rats were orally treated during 6-15 gestation days with different doses of OA (0.125, 0.25, 0.50, 0.75 mg/kg), AFB1 (0.125, 0.25, 0.50, 1.00 mg/kg), and their combination (0.125+0.125, 0.25+0.50, 0.50+0.25 mg/kg). The fetal sections passing through liver, kidney, brain, heart, and eyes were selected from the fetuses given visceral examination representing each litter. The selected sections were processed for paraffin embedding, stained with H and E, and examined by light microscopy. The histological examination of the fetal organs revealed that OA, AFB1, and their combination treatments caused variable changes in internal organs. In the case of OA, the incidence of pathological lesions liver, kidney, brain, and eye lesions was high, whereas in AFB1 treatment, liver, brain, kidney, and heart were affected. The incidence of heart lesions, especially valvular defects, increased in the combination groups. Bile duct proliferation/new bile duct formation, defective ossification of cranial bones, exposure of the brain to the exterior, hypoplasia of cerebellum, and retinal defects observed in OA treatment and spinal cord defects in addition to liver, kidney, and brain changes observed in AFB1 were less severe in the combination groups. The present study indicates that the occurrence of brain, kidney, and liver lesions in combination treatment was less than in either individual treatment suggesting antagonism of OA-induced teratogenic effects by AFB1. The indication of subtle lesions due to an interference with normal development and arrest of differentiation in various internal organs observed in the present study suggests that microscopic examination of the tissues can provide additional useful information to a developmental toxicity study.     

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

The production of compound K and aglycon protopanaxadiol (APPD) from ginsenoside Rd and ginseng root extract was performed using a recombinant β-glycosidase from Pyrococcus furiosus. The activity for Rd was optimal at pH 5.5 and 95°C with a half-life of 68 h at 95°C. β-Glycosidase converted Rb₁, Rb₂, Rc, and Rd to APPD via compound K. With increases in the enzyme activity, the productivities of compound K and APPD increased. The substrate concentration was optimal at 4.0 mM Rd or 10% (w/v) ginseng root extract; 4 mM of Rd was converted to 3.3 mM compound K with a yield of 82.5% (mol/mol) and a productivity of 2,010 mg l⁻¹ h⁻¹ at 1 h and was hydrolyzed completely to APPD with 364 mg l⁻¹ h⁻¹ after 5 h. Rb₁, Rb₂, Rc, and Rd at 3.9 mM in 10% ginseng root extract were converted to 3.1 mM compound K with 79.5% and 1,610 mg l⁻¹ h⁻¹ at 1.2 h and were hydrolyzed completely to APPD with 300 mg l⁻¹ h⁻¹ after 6 h. The concentrations and productivities of compound K and APPD in the present study are the highest ever reported.     

Multi-objective optimization of glycopeptide antibiotic production in batch and fed batch processes

Fermentation optimization involves potentially conflicting multiple objectives such as product concentration and production media cost. Simultaneous optimization of these objectives would result in a multiobjective optimization problem, which is characterized by a set of multiple solutions, knows as pareto optimal solutions. These solutions gives flexibility in evaluating the trade-offs and selecting the most suitable operating policy. Here, ε-constraint approach was used to generate the pareto solutions for two objectives: product concentration and product per unit cost of media, for batch and fed batch operations using process model for Amycolatopsis balhimycina, a glycopeptide antibiotic producer. This resulted in a set of several pareto optimal solutions with the two objectives ranging from (0.75 g l⁻¹, 3.97 g $^-1) to (0.44 g l⁻¹, 5.19 g $^-1) for batch and from (1.5 g l⁻¹, 5.46 g $^-1) to (1.1 g l⁻¹, 6.34 g $^-1) for fed batch operations. One pareto solution each for batch and for fed batch mode was experimentally validated.     

Characterization and sequence prediction of structural variations in α-helix

Background

Centralised resources such as GenBank and UniProt are perfect examples of the major international efforts that have been made to integrate and share biological information. However, additional data that adds value to these resources needs a simple and rapid route to public access. The Distributed Annotation System (DAS) provides an adequate environment to integrate genomic and proteomic information from multiple sources, making this information accessible to the community. DAS offers a way to distribute and access information but it does not provide domain experts with the mechanisms to participate in the curation process of the available biological entities and their annotations.

Results

We designed and developed a Collaborative Annotation System for proteins called DAS Writeback. DAS writeback is a protocol extension of DAS to provide the functionalities of adding, editing and deleting annotations. We implemented this new specification as extensions of both a DAS server and a DAS client. The architecture was designed with the involvement of the DAS community and it was improved after performing usability experiments emulating a real annotation task.

Conclusions

We demonstrate that DAS Writeback is effective, usable and will provide the appropriate environment for the creation and evolution of community protein annotation.     

SHARP: genome-scale identification of gene–protein–reaction associations in cyanobacteria

Genome scale metabolic model provides an overview of an organism’s metabolic capability. These genome-specific metabolic reconstructions are based on identification of gene to protein to reaction (GPR) associations and, in turn, on homology with annotated genes from other organisms. Cyanobacteria are photosynthetic prokaryotes which have diverged appreciably from their nonphotosynthetic counterparts. They also show significant evolutionary divergence from plants, which are well studied for their photosynthetic apparatus. We argue that context-specific sequence and domain similarity can add to the repertoire of the GPR associations and significantly expand our view of the metabolic capability of cyanobacteria. We took an approach that combines the results of context-specific sequence-to-sequence similarity search with those of sequence-to-profile searches. We employ PSI-BLAST for the former, and CDD, Pfam, and COG for the latter. An optimization algorithm was devised to arrive at a weighting scheme to combine the different evidences with KEGG-annotated GPRs as training data. We present the algorithm in the form of software “Systematic, Homology-based Automated Re-annotation for Prokaryotes (SHARP).” We predicted 3,781 new GPR associations for the 10 prokaryotes considered of which eight are cyanobacteria species. These new GPR associations fall in several metabolic pathways and were used to annotate 7,718 gaps in the metabolic network. These new annotations led to discovery of several pathways that may be active and thereby providing new directions for metabolic engineering of these species for production of useful products. Metabolic model developed on such a reconstructed network is likely to give better phenotypic predictions.     

Metabolic flux analysis of Cyanothece sp. ATCC 51142 under mixotrophic conditions

Cyanobacteria are a group of photosynthetic prokaryotes capable of utilizing solar energy to fix atmospheric carbon dioxide to biomass. Despite several “proof of principle” studies, low product yield is an impediment in commercialization of cyanobacteria-derived biofuels. Estimation of intracellular reaction rates by ¹³C metabolic flux analysis (¹³C-MFA) would be a step toward enhancing biofuel yield via metabolic engineering. We report ¹³C-MFA for Cyanothece sp. ATCC 51142, a unicellular nitrogen-fixing cyanobacterium, known for enhanced hydrogen yield under mixotrophic conditions. Rates of reactions in the central carbon metabolism under nitrogen-fixing and -non-fixing conditions were estimated by monitoring the competitive incorporation of ¹²C and ¹³C from unlabeled CO₂ and uniformly labeled glycerol, respectively, into terminal metabolites such as amino acids. The observed labeling patterns suggest mixotrophic growth under both the conditions, with a larger fraction of unlabeled carbon in nitrate-sufficient cultures asserting a greater contribution of carbon fixation by photosynthesis and an anaplerotic pathway. Indeed, flux analysis complements the higher growth observed under nitrate-sufficient conditions. On the other hand, the flux through the oxidative pentose phosphate pathway and tricarboxylic acid cycle was greater in nitrate-deficient conditions, possibly to supply the precursors and reducing equivalents needed for nitrogen fixation. In addition, an enhanced flux through fructose-6-phosphate phosphoketolase possibly suggests the organism’s preferred mode under nitrogen-fixing conditions. The ¹³C-MFA results complement the reported predictions by flux balance analysis and provide quantitative insight into the organism’s distinct metabolic features under nitrogen-fixing and -non-fixing conditions.