Exometabolome analysis reveals hypoxia at the up-scaling of a Saccharomyces cerevisiae high-cell density fed-batch biopharmaceutical process

Optimization of limonin invertase production by scaling up Aspergillus tubingensis UA13 fermentation to a 5-l scale

The enzymatic approach is a highly effective and the major scientific method to eliminating bitter components in citrus-derived products nowadays. Microbial production of limonin invertase stands out due to its pivotal role in the removal of the bitter substance, limonin. The optimization of fermentation parameters and the study of scale-up fermentation are imperative for product commercialization. In this study, we focused on optimizing stirring speed, fermentation temperature, and initial pH to enhance the growth and limonin invertase production by the Aspergillus tabin strain UA13 in a 5-l stirred-tank bioreactor. Our results revealed the following optimal parameters are: a stirring speed of 300 rpm, a fermentation temperature of 35°C and a pH 5.0. Under these optimized conditions, the limonin invertase activity reached its peak at 63.38 U ml-1, representing a 1.67-fold increase compared to the unoptimized conditions (38.10 U ml-1), while also reducing the fermentation duration by 12 h. Furthermore, our research demonstrated that limonin invertase effectively hydrolyze limonin in grapefruit juice, reducing its content from 13.28 to 2.14 μg ml-1, as determined by HPLC, resulting in a 6.21-fold reduction of the bitter substance.

Precision fermentation with mass spectrometry-based spent media analysis

Optimization and monitoring of bioprocesses requires the measurement of several process parameters and quality attributes. Mass spectrometry (MS)-based techniques such as those coupled to gas chromatography (GCMS) and liquid Chromatography (LCMS) enable the simultaneous measurement of hundreds of metabolites with high sensitivity. When applied to spent media, such metabolome analysis can help determine the sequence of substrate uptake and metabolite secretion, consequently facilitating better design of initial media and feeding strategy. Furthermore, the analysis of metabolite diversity and abundance from spent media will aid the determination of metabolic phases of the culture and the identification of metabolites as surrogate markers for product titer and quality. This review covers the recent advances in metabolomics analysis applied to the development and monitoring of bioprocesses. In this regard, we recommend a stepwise workflow and guidelines that a bioprocesses engineer can adopt to develop and optimize a fermentation process using spent media analysis. Finally, we show examples of how the use of MS can revolutionize the design and monitoring of bioprocesses.

SubTap, a Versatile 3D Printed Platform for Eavesdropping on Extracellular Interactions

Communication within the microbiome occurs through an immense diversity of small molecules. Capturing these microbial interactions is a significant challenge due to the complexity of the exometabolome and its sensitivity to environmental stimuli. Traditional methods for acquiring exometabolomic data from interacting microorganisms are limited by their low throughput or lack of sampling depth. To address this challenge, we introduce subtapping (short for substrate tapping), a technique for tapping into extracellular metabolites that are being transferred through the growth substrate during coculture. High-throughput subtapping is made possible by a new coculturing platform, named SubTap, that we engineered to resemble a 96-well plate. The three-dimensional (3D) printed SubTap platform captures the exometabolome in an agar compartment that connects physically separated growth chambers, which permits cell growth without competition for space. We show how SubTap facilitates replicable and quick detection of exometabolites via direct infusion mass spectrometry analysis. Using bacterial isolates from the soil, we apply SubTap to characterize the effects of growth medium, growth duration, and mixed versus unmixed coculturing on the exometabolome. Finally, we demonstrate SubTap's versatility by interrogating microbial interactions in multicultures with up to four strains. IMPORTANCE Improvements in experimental techniques and instrumentation have led to the discovery that the microbiome plays an essential role in human and environmental health. Nevertheless, there remain major impediments to conducting large-scale interrogations of the microbiome in a high-throughput manner, particularly in the field of exometabolomics. Existing methods to coculture microorganisms and interrogate their interactions are labor-intensive and low throughput. This inspired us to develop a solution for coculturing that was (i) open source, (ii) inexpensive, (iii) scalable, (iv) customizable, and (v) compatible with existing mass spectrometry instrumentation. Here, we present SubTap-a 3D printed coculturing platform that permits tapping directly into the growth substrate between physically separated, but interconnected, growth compartments. SubTap allows multiculture (with up to four distinct growth compartments) in spatially mixed or unmixed configurations and enables repeatable results with mass spectrometry, as shown by our validation with known compounds and cultures of one to four organisms.

Exometabolome profiling reveals activation of the carnitine buffering pathway in fed-batch cultures of CHO cells co-fed with glucose and lactic acid

Adjustments to CHO cell physiology were recently observed during implementation of a Raman spectroscopy-based glucose and lactate control strategy. To further understand how these cells, under monoclonal antibody (mAb) production conditions, utilized the extra lactic acid fed, we performed a comprehensive semi-quantitative and time-dependent analysis of the exometabolome. This study focused on the CHO cell's metabolic shift from the fifth day of culture. We compared relative levels of extracellular metabolites in the absence or presence of a 2 g/L lactic acid setpoint while glucose was kept at 4 g/L. Our hypothesis is that extra lactic acid would supply more pyruvate, favoring oxidative phosphorylation. We subsequentially uncovered several carnitine derivatives as biomarkers of the simultaneous activation of TCA anaplerotic pathways as well as a carbon-buffering pathway. CHO cells exhibited a balance between intermediates from (i) amino acid catabolism, (ii) fatty acid β-oxidation, and (iii) pyruvate from glycolysis and lactic acid; and the secretion of their intermediate carnitine derivatives. In addition, 3-hydroxy-methyl-glutaric acid (HMG) and mevalonate syntheses were found as biomarkers of alternative acyl group removal. Together, under a limited capacity to assimilate the surplus of acyl-CoA groups as well as an ability to maintain the acyl-CoA: free CoA ratio for proper and continuous functioning of the TCA cycle, CHO cells activate the carnitine-buffering system, HMG, and mevalonate pathways.

Optimization of process parameters for naringinase production by Aspergillus tubingensis UA13 and pilot scale-up study

To improve the naringinase production of Aspergillus tubingensis UA13, shorten the fermentation period, and verify its industrial application value, naringinase production conditions were optimized, and 5 L scale-up study in stirred tank bioreactor was carried out. Parameters, including carbon, nitrogen sources and inducer, optimal seed age, inoculum amount, temperature and pH, were adjusted and optimized in shaking flask. Keeping pH at the optimal value 6 in bioreactor, dissolved oxygen was monitored during the fermentation and the optimal stirring rate was investigated. In 5 L scale-up study, the highest naringinase activity was 72.62 U/mL, which was 1.75 times higher than that (41.52 U/mL) in shaking flask and the fermentation period was shortened by 24 h.

Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation

Background

Despite the latest advancements in metabolic engineering for genome editing and characterization of host performance, the successful development of robust cell factories used for industrial bioprocesses and accurate prediction of the behavior of microbial systems, especially when shifting from laboratory-scale to industrial conditions, remains challenging. To increase the probability of success of a scale-up process, data obtained from thoroughly performed studies mirroring cellular responses to typical large-scale stimuli may be used to derive crucial information to better understand potential implications of large-scale cultivation on strain performance. This study assesses the feasibility to employ a barcoded yeast deletion library to assess genome-wide strain fitness across a simulated industrial fermentation regime and aims to understand the genetic basis of changes in strain physiology during industrial fermentation, and the corresponding roles these genes play in strain performance.

Results

We find that mutant population diversity is maintained through multiple seed trains, enabling large scale fermentation selective pressures to act upon the community. We identify specific deletion mutants that were enriched in all processes tested in this study, independent of the cultivation conditions, which include MCK1, RIM11, MRK1, and YGK3 that all encode homologues of mammalian glycogen synthase kinase 3 (GSK-3). Ecological analysis of beta diversity between all samples revealed significant population divergence over time and showed feed specific consequences of population structure. Further, we show that significant changes in the population diversity during fed-batch cultivations reflect the presence of significant stresses. Our observations indicate that, for this yeast deletion collection, the selection of the feeding scheme which affects the accumulation of the fermentative by-product ethanol impacts the diversity of the mutant pool to a higher degree as compared to the pH of the culture broth. The mutants that were lost during the time of most extreme population selection suggest that specific biological processes may be required to cope with these specific stresses.

Conclusions

Our results demonstrate the feasibility of Bar-seq to assess fermentation associated stresses in yeast populations under industrial conditions and to understand critical stages of a scale-up process where variability emerges, and selection pressure gets imposed. Overall our work highlights a promising avenue to identify genetic loci and biological stress responses required for fitness under industrial conditions.

Engineering Robust Production Microbes for Large-Scale Cultivation

Systems biology and synthetic biology are increasingly used to examine and modulate complex biological systems. As such, many issues arising during scaling-up microbial production processes can be addressed using these approaches. We review differences between laboratory-scale cultures and larger-scale processes to provide a perspective on those strain characteristics that are especially important during scaling. Systems biology has been used to examine a range of microbial systems for their response in bioreactors to fluctuations in nutrients, dissolved gases, and other stresses. Synthetic biology has been used both to assess and modulate strain response, and to engineer strains to improve production. We discuss these approaches and tools in the context of their use in engineering robust microbes for applications in large-scale production.

Saccharomyces cerevisiae morphological changes and cytokinesis arrest elicited by hypoxia during scale-up for production of therapeutic recombinant proteins

Background

Scaling up of bioprocesses represents a crucial step in the industrial production of biologicals. However, our knowledge about the impact of scale-up on the organism’s physiology and function is still incomplete. Our previous studies have suggested the existence of morphological changes during the scale-up of a yeast (Saccharomyces cerevisiae) fermentation process as inferred from the volume fraction occupied by yeast cells and exometabolomics analyses. In the current study, we noticed cell morphology changes during scale-up of a yeast fermentation process from bench (10 L) to industrial scale (10,000 L). We hypothesized that hypoxia observed during scale-up partially impaired the availability of N-acetyl-glucosamine, a precursor of chitin synthesis, a key polysaccharide component of yeast mother-daughter neck formation.

Results

Using a combination of flow cytometry with two high throughput cell imaging technologies, Vi-CELL and Flow Imaging, we found changes in the distribution of cell size and morphology as a function of process duration at the industrial scale of the production process. At the end of run, concomitantly with lowest levels of dissolved oxygen (DO), we detected an increase in cell subpopulations exhibiting low aspect ratio corresponding to morphologies exhibited by large-single-budded and multi-budded cells, reflecting incomplete cytokinesis at the M phase of the yeast mitotic cycle. Metabolomics from the intracellular milieu pointed to an impaired supply of precursors for chitin biosynthesis likely affecting the septum formation between mother and daughter and cytokinesis. Inducing hypoxia at the 10 L bench scale by varying DO levels, confirmed the existence and impact of hypoxic conditions on yeast cell size and morphology observed at the industrial scale.

Conclusions

We conclude that the observed increments in wet cell weight at the industrial scale correspond to morphological changes characterized by the large diameter and low aspect ratio exhibited by cell subpopulations comprising large single-budded and multi-budded cells. These changes are consistent with impairment of cytokinesis triggered by hypoxia as indicated by experiments mimicking this condition at DO 5% and 10 L scale. Mechanistically, hypoxia impairs N-acetyl-glucosamine availability, a key precursor of chitin synthesis.

Production efficiency of the bacterial non-ribosomal peptide indigoidine relies on the respiratory metabolic state in S. cerevisiae

BACKGROUND

Beyond pathway engineering, the metabolic state of the production host is critical in maintaining the efficiency of cellular production. The biotechnologically important yeast Saccharomyces cerevisiae adjusts its energy metabolism based on the availability of oxygen and carbon sources. This transition between respiratory and non-respiratory metabolic state is accompanied by substantial modifications of central carbon metabolism, which impact the efficiency of metabolic pathways and the corresponding final product titers. Non-ribosomal peptide synthetases (NRPS) are an important class of biocatalysts that provide access to a wide array of secondary metabolites. Indigoidine, a blue pigment, is a representative NRP that is valuable by itself as a renewably produced pigment.

RESULTS

Saccharomyces cerevisiae was engineered to express a bacterial NRPS that converts glutamine to indigoidine. We characterize carbon source use and production dynamics, and demonstrate that indigoidine is solely produced during respiratory cell growth. Production of indigoidine is abolished during non-respiratory growth even under aerobic conditions. By promoting respiratory conditions via controlled feeding, we scaled the production to a 2 L bioreactor scale, reaching a maximum titer of 980 mg/L.

CONCLUSIONS

This study represents the first use of the Streptomyces lavendulae NRPS (BpsA) in a fungal host and its scale-up. The final product indigoidine is linked to the activity of the TCA cycle and serves as a reporter for the respiratory state of S. cerevisiae. Our approach can be broadly applied to investigate diversion of flux from central carbon metabolism for NRPS and other heterologous pathway engineering, or to follow a population switch between respiratory and non-respiratory modes.

Transcriptional profile of the human skin pathogenic fungus Mucor irregularis in response to low oxygen

Mucormycosis is one of the most invasive mycosis and has caused global concern in public health. Cutaneous mucormycosis caused by Mucor irregularis (formerly Rhizomucor variabilis) is an emerging disease in China. To survive in the human body, M. irregularis must overcome the hypoxic (low oxygen) host microenvironment. However, the exact molecular mechanism of its pathogenicity and adaptation to low oxygen stress environment is relatively unexplored. In this study, we used Illumina HiSeq technology (RNA-Seq) to determine and compare the transcriptome profile of M. irregularis CBS103.93 under normal growth condition and hypoxic stress. Our analyses demonstrated a series of genes involved in TCA, glyoxylate cycle, pentose phosphate pathway, and GABA shunt were down-regulated under hypoxic condition, while certain genes in the lipid/fatty acid metabolism and endocytosis were up-regulated, indicating that lipid metabolism was more active under hypoxia. Comparing the data with other important human pathogenic fungi such as Aspergillus spp., we found that the gene expression pattern and metabolism in responses to hypoxia in M. irregularis were unique and different. We proposed that these metabolic changes can represent a species-specific hypoxic adaptation in M. irregularis, and we hypothesized that M. irregularis could use the intra-lipid pool and lipid secreted in the infection region, as an extracellular nutrient source to support its hypoxic growth. Characterizing the significant differential gene expression in this species could be beneficial to uncover their role in hypoxia adaptation and fungalpathogenesis and further facilitate the development of novel targets in disease diagnosis and treatment against mucormycosis.

A GRX1 Promoter Variant Confers Constitutive Noisy Bimodal Expression That Increases Oxidative Stress Resistance in Yeast

Higher noise in the expression of stress-related genes was previously shown to confer better resistance in selective conditions. Thus, evolving the promoter of such genes toward higher transcriptional noise appears to be an attractive strategy to engineer microbial strains with enhanced stress resistance. Here we generated hundreds of promoter variants of the GRX1 gene involved in oxidative stress resistance in Saccharomyces cerevisiae and created a yeast library by replacing the native GRX1 promoter by these variants at the native locus. An outlier clone with very strong increase in noise (6-times) at the same mean expression level as the native strain was identified whereas the other noisiest clones were only 3-times increased. This variant provides constitutive bimodal expression and consists in 3 repeated but differently mutated copies of the GRX1 promoter. In spite of the multi-factorial oxidative stress-response in yeast, replacement of the native promoter by this variant is sufficient alone to confer strongly enhanced resistance to H₂O₂ and cumene hydroperoxide. New replacement of this variant by the native promoter in the resistant strain suppresses the resistance. This work shows that increasing noise of target genes in a relevant strategy to engineer microbial strains toward better stress resistance. Multiple promoter replacement could synergize the effect observed here with the sole GRX1 promoter replacement. Finally this work suggests that combining several mutated copies of the target promoter could allow enhancing transcriptional-mediated noise at higher levels than mutating a single copy by providing constitutive bimodal and highly heterogeneous expression distribution.

Metabolite secretion in microorganisms: the theory of metabolic overflow put to the test

INTRODUCTION

Microbial cells secrete many metabolites during growth, including important intermediates of the central carbon metabolism. This has not been taken into account by researchers when modeling microbial metabolism for metabolic engineering and systems biology studies.

MATERIALS AND METHODS

The uptake of metabolites by microorganisms is well studied, but our knowledge of how and why they secrete different intracellular compounds is poor. The secretion of metabolites by microbial cells has traditionally been regarded as a consequence of intracellular metabolic overflow.

CONCLUSIONS

Here, we provide evidence based on time-series metabolomics data that microbial cells eliminate some metabolites in response to environmental cues, independent of metabolic overflow. Moreover, we review the different mechanisms of metabolite secretion and explore how this knowledge can benefit metabolic modeling and engineering.

Bioprocess scale-up/down as integrative enabling technology: from fluid mechanics to systems biology and beyond

Efficient optimization of microbial processes is a critical issue for achieving a number of sustainable development goals, considering the impact of microbial biotechnology in agrofood, environment, biopharmaceutical and chemical industries. Many of these applications require scale-up after proof of concept. However, the behaviour of microbial systems remains unpredictable (at least partially) when shifting from laboratory-scale to industrial conditions. The need for robust microbial systems is thus highly needed in this context, as well as a better understanding of the interactions between fluid mechanics and cell physiology. For that purpose, a full scale-up/down computational framework is already available. This framework links computational fluid dynamics (CFD), metabolic flux analysis and agent-based modelling (ABM) for a better understanding of the cell lifelines in a heterogeneous environment. Ultimately, this framework can be used for the design of scale-down simulators and/or metabolically engineered cells able to cope with environmental fluctuations typically found in large-scale bioreactors. However, this framework still needs some refinements, such as a better integration of gas-liquid flows in CFD, and taking into account intrinsic biological noise in ABM.

Wastewater recycling technology for fermentation in polyunsaturated fatty acid production

To reduce fermentation-associated wastewater discharge and the cost of wastewater treatment, which further reduces the total cost of DHA and ARA production, this study first analyzed the composition of wastewater from Aurantiochytrium (DHA) and Mortierella alpina (ARA) fermentation, after which wastewater recycling technology for these fermentation processes was developed. No negative effects of DHA and ARA production were observed when the two fermentation wastewater methods were cross-recycled. DHA and ARA yields were significantly inhibited when the wastewater from the fermentation process was directly reused. In 5-L fed-batch fermentation experiments, using this cross-recycle technology, the DHA and ARA yields were 30.4 and 5.13gL^-1, respectively, with no significant changes (P>0.05) compared to the control group, and the water consumption was reduced by half compared to the traditional process. Therefore, this technology has great potential in industrial fermentation for polyunsaturated fatty acid production.

Hypoxia-elicited impairment of cell wall integrity, glycosylation precursor synthesis, and growth in scaled-up high-cell density fed-batch cultures of Saccharomyces cerevisiae

Background

In this study we examine the integrity of the cell wall during scale up of a yeast fermentation process from laboratory scale (10 L) to industrial scale (10,000 L). In a previous study we observed a clear difference in the volume fraction occupied by yeast cells as revealed by wet cell weight (WCW) measurements between these scales. That study also included metabolite analysis which suggested hypoxia during scale up. Here we hypothesize that hypoxia weakens the yeast cell wall during the scale up, leading to changes in cell permeability, and/or cell mechanical resistance, which in turn may lead to the observed difference in WCW. We tested the cell wall integrity by probing the cell wall sensitivity to Zymolyase. Also exometabolomics data showed changes in supply of precursors for the glycosylation pathway.

Results

The results show a more sensitive cell wall later in the production process at industrial scale, while the sensitivity at early time points was similar at both scales. We also report exometabolomics data, in particular a link with the protein glycosylation pathway. Significantly lower levels of Man6P and progressively higher GDP-mannose indicated partially impaired incorporation of this sugar nucleotide during co- or post-translational protein glycosylation pathways at the 10,000 L compared to the 10 L scale. This impairment in glycosylation would be expected to affect cell wall integrity. Although cell viability from samples obtained at both scales were similar, cells harvested from 10 L bioreactors were able to re-initiate growth faster in fresh shake flask media than those harvested from the industrial scale.

Conclusions

The results obtained help explain the WCW differences observed at both scales by hypoxia-triggered weakening of the yeast cell wall during the scale up.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-016-0542-3) contains supplementary material, which is available to authorized users.

MetaboTools: A Comprehensive Toolbox for Analysis of Genome-Scale Metabolic Models

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorials explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. This computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.

Exometabolomics Assisted Design and Validation of Synthetic Obligate Mutualism

Synthetic microbial ecology has the potential to enhance the productivity and resiliency of biotechnology processes compared to approaches using single isolates. Engineering microbial consortia is challenging; however, one approach that has attracted significant attention is the creation of synthetic obligate mutualism using auxotrophic mutants that depend on each other for exchange or cross-feeding of metabolites. Here, we describe the integration of mutant library fitness profiling with mass spectrometry based exometabolomics as a method for constructing synthetic mutualism based on cross-feeding. Two industrially important species lacking known ecological interactions, Zymomonas mobilis and Escherichia coli, were selected as the test species. Amino acid exometabolites identified in the spent medium of Z. mobilis were used to select three corresponding E. coli auxotrophs (proA, pheA and IlvA), as potential E. coli counterparts for the coculture. A pooled mutant fitness assay with a Z. mobilis transposon mutant library was used to identify mutants with improved growth in the presence of E. coli. An auxotroph mutant in a gene (ZMO0748) with sequence similarity to cysteine synthase A (cysK), was selected as the Z. mobilis counterpart for the coculture. Exometabolomic analysis of spent E. coli medium identified glutathione related metabolites as potentially available for rescue of the Z. mobilis cysteine synthase mutant. Three sets of cocultures between the Z. mobilis auxotroph and each of the three E. coli auxotrophs were monitored by optical density for growth and analyzed by flow cytometry to confirm high cell counts for each species. Taken together, our methods provide a technological framework for creating synthetic mutualisms combining existing screening based methods and exometabolomics for both the selection of obligate mutualism partners and elucidation of metabolites involved in auxotroph rescue.

Characterization of a Saccharomyces cerevisiae fermentation process for production of a therapeutic recombinant protein using a multivariate Bayesian approach

The principle of quality by design (QbD) has been widely applied to biopharmaceutical manufacturing processes. Process characterization is an essential step to implement the QbD concept to establish the design space and to define the proven acceptable ranges (PAR) for critical process parameters (CPPs). In this study, we present characterization of a Saccharomyces cerevisiae fermentation process using risk assessment analysis, statistical design of experiments (DoE), and the multivariate Bayesian predictive approach. The critical quality attributes (CQAs) and CPPs were identified with a risk assessment. The statistical model for each attribute was established using the results from the DoE study with consideration given to interactions between CPPs. Both the conventional overlapping contour plot and the multivariate Bayesian predictive approaches were used to establish the region of process operating conditions where all attributes met their specifications simultaneously. The quantitative Bayesian predictive approach was chosen to define the PARs for the CPPs, which apply to the manufacturing control strategy. Experience from the 10,000 L manufacturing scale process validation, including 64 continued process verification batches, indicates that the CPPs remain under a state of control and within the established PARs. The end product quality attributes were within their drug substance specifications. The probability generated with the Bayesian approach was also used as a tool to assess CPP deviations. This approach can be extended to develop other production process characterization and quantify a reliable operating region. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:799-812, 2016.

A novel process-based model of microbial growth: self-inhibition in Saccharomyces cerevisiae aerobic fed-batch cultures

BACKGROUND

Microbial population dynamics in bioreactors depend on both nutrients availability and changes in the growth environment. Research is still ongoing on the optimization of bioreactor yields focusing on the increase of the maximum achievable cell density.

RESULTS

A new process-based model is proposed to describe the aerobic growth of Saccharomyces cerevisiae cultured on glucose as carbon and energy source. The model considers the main metabolic routes of glucose assimilation (fermentation to ethanol and respiration) and the occurrence of inhibition due to the accumulation of both ethanol and other self-produced toxic compounds in the medium. Model simulations reproduced data from classic and new experiments of yeast growth in batch and fed-batch cultures. Model and experimental results showed that the growth decline observed in prolonged fed-batch cultures had to be ascribed to self-produced inhibitory compounds other than ethanol.

CONCLUSIONS

The presented results clarify the dynamics of microbial growth under different feeding conditions and highlight the relevance of the negative feedback by self-produced inhibitory compounds on the maximum cell densities achieved in a bioreactor.

Optimization of a multi-stage, multi-subunit malaria vaccine candidate for the production in Pichia pastoris by the identification and removal of protease cleavage sites

We demonstrated the successful optimization of a recombinant multi-subunit malaria vaccine candidate protein for production in the methylotrophic yeast Pichia pastoris by the identification and subsequent removal of two protease cleavage sites. After observing protein degradation in the culture supernatant of a fed-batch fermentation, the predominant proteolytic fragment of the secreted recombinant protein was analyzed by mass spectrometry. The MS data indicated the cleavage of an amino acid sequence matching the yeast KEX2-protease consensus motif EKRE. The cleavage in this region was completely abolished by the deletion of the EKRE motif in a modified variant. This modified variant was produced, purified, and used for immunization of rabbits, inducing high antigen specific antibody titers (2 × 10(6) ). Total IgG from rabbit immune sera recognized different stages of Plasmodium falciparum parasites in immunofluorescence assays, indicating native folding of the vaccine candidate. However, the modified variant was still degraded, albeit into different fragments. Further analysis by mass spectrometry and N-terminal sequencing revealed a second cleavage site downstream of the motif PEVK. We therefore removed a 17-amino-acid stretch including the PEVK motif, resulting in the subsequent production of the full-length recombinant vaccine candidate protein without significant degradation, with a yield of 53 mg per liter culture volume. We clearly demonstrate that the proteolytic degradation of recombinant proteins by endogenous P. pastoris proteases can be prevented by the identification and removal of such cleavage sites. This strategy is particularly relevant for the production of recombinant subunit vaccines, where product yield and stability play a more important role than for the production of a stringently-defined native sequence which is necessary for most therapeutic molecules.