Microbial production of polyhydroxybutyrate with tailor-made properties: an integrated modelling approach and experimental validation

The microbial production of polyhydroxybutyrate (PHB) is a complex process in which the final quantity and quality of the PHB depend on a large number of process operating variables. Consequently, the design and optimal dynamic operation of a microbial process for the efficient production of PHB with tailor-made molecular properties is an extremely interesting problem. The present study investigates how key process operating variables (i.e., nutritional and aeration conditions) affect the biomass production rate and the PHB accumulation in the cells and its associated molecular weight distribution. A combined metabolic/polymerization/macroscopic modelling approach, relating the process performance and product quality with the process variables, was developed and validated using an extensive series of experiments and measurements. The model predicts the dynamic evolution of the biomass growth, the polymer accumulation, the consumption of carbon and nitrogen sources and the average molecular weights of the PHB in a bioreactor, under batch and fed-batch operating conditions. The proposed integrated model was used for the model-based optimization of the production of PHB with tailor-made molecular properties in Azohydromonas lata bacteria. The process optimization led to a high intracellular PHB accumulation (up to 95% g of PHB per g of DCW) and the production of different grades (i.e., different molecular weight distributions) of PHB.     

A combined computational and microarray-based approach identifies novel microRNAs encoded by human gamma-herpesviruses

We have developed an approach to identify microRNAs (miRNAs) that is based on bioinformatics and array-based technologies, without the use of cDNA cloning. The approach, designed for use on genomes of small size (<2 Mb), was tested on cells infected by either of two lymphotropic herpesviruses, KSHV and EBV. The viral genomes were scanned computationally for pre-miRNAs using an algorithm (VMir) we have developed. Candidate hairpins suggested by this analysis were then synthesized as oligonucleotides on microarrays, and the arrays were hybridized with small RNAs from infected cells. Candidate miRNAs that scored positive on the arrays were then subjected to confirmatory Northern blot analysis. Using this approach, 10 of the known KSHV pre-miRNAs were identified, as well as a novel pre-miRNA that had earlier escaped detection. This method also led to the identification of seven new EBV-encoded pre-miRNAs; by using additional computational approaches, we identified a total of 18 new EBV pre-miRNAs that produce 22 mature miRNA molecules, thereby more than quadrupling the total number of hitherto known EBV miRNAs. The advantages and limitations of the approach are discussed.     

Analysis of Chinese hamster ovary cell metabolism through a combined computational and experimental approach

Optimization of cell culture processes can benefit from the systematic analysis of experimental data and their organization in mathematical models, which can be used to decipher the effect of individual process variables on multiple outputs of interest. Towards this goal, a kinetic model of cytosolic glucose metabolism coupled with a population-level model of Chinese hamster ovary cells was used to analyse metabolic behavior under batch and fed-batch cell culture conditions. The model was parameterized using experimental data for cell growth dynamics, extracellular and intracellular metabolite profiles. The results highlight significant differences between the two culture conditions in terms of metabolic efficiency and motivate the exploration of lactate as a secondary carbon source. Finally, the application of global sensitivity analysis to the model parameters highlights the need for additional experimental information on cell cycle distribution to complement metabolomic analyses with a view to parameterize kinetic models.     

RNomics: an experimental approach that identifies 201 candidates for novel, small, non-messenger RNAs in mouse

In mouse brain cDNA libraries generated from small RNA molecules we have identified a total of 201 different expressed RNA sequences potentially encoding novel small non-messenger RNA species (snmRNAs). Based on sequence and structural motifs, 113 of these RNAs can be assigned to the C/D box or H/ACA box subclass of small nucleolar RNAs (snoRNAs), known as guide RNAs for rRNA. While 30 RNAs represent mouse homologues of previously identified human C/D or H/ACA snoRNAs, 83 correspond to entirely novel snoRNAS: Among these, for the first time, we identified four C/D box snoRNAs and four H/ACA box snoRNAs predicted to direct modifications within U2, U4 or U6 small nuclear RNAs (snRNAs). Furthermore, 25 snoRNAs from either class lacked antisense elements for rRNAs or snRNAS: Therefore, additional snoRNA targets have to be considered. Surprisingly, six C/D box snoRNAs and one H/ACA box snoRNA were expressed exclusively in brain. Of the 88 RNAs not belonging to either snoRNA subclass, at least 26 are probably derived from truncated heterogeneous nuclear RNAs (hnRNAs) or mRNAS: Short interspersed repetitive elements (SINEs) are located on five RNA sequences and may represent rare examples of transcribed SINES: The remaining RNA species could not as yet be assigned either to any snmRNA class or to a part of a larger hnRNA/mRNA. It is likely that at least some of the latter will represent novel, unclassified snmRNAS:     

Combined experimental and computational strategies define an expansive regulon for GcvB small RNA

The bacterial small RNA GcvB has been known as a translational repressor of mRNAs encoding amino acid transporters and has been postulated to limit uptake of unnecessary amino acids under nutrient-rich conditions. In this issue of Molecular Microbiology, Sharma et al. (2011) provide evidence for a much broader role for GcvB as a global regulator of amino acid metabolism. Using a unique combination of experimental and biocomputational approaches, the authors triple the size of the GcvB regulon, making it the largest sRNA regulon defined to date.     

Dynamic generation and qualitative analysis of metabolic pathways by a joint database/graph theoretical approach.

The dynamic generation and qualitative analysis of metabolic networks relying on continuously growing qualified metabolic data by a joint database/graph theoretical approach is described. The procedure is applied to analyze the connectivity of a metabolic network after enzyme removal and to subsequently perform shortest path analyses. The focus lies on the analysis of the connectivity of the metabolic network depending on model assumptions. Here we analyze the influence of the number of strongly connected components on the assignment of reversibility or irreversibility of the biochemical reactions.     

A multimethod computational simulation approach for investigating mitochondrial dynamics and dysfunction in degenerative aging

Research in biogerontology has largely focused on the complex relationship between mitochondrial dysfunction and biological aging. In particular, the mitochondrial free radical theory of aging (MFRTA) has been well accepted. However, this theory has been challenged by recent studies showing minimal increases in reactive oxygen species (ROS) as not entirely deleterious in nature, and even beneficial under the appropriate cellular circumstances. To assess these significant and nonintuitive observations in the context of a functional system, we have taken an in silico approach to expand the focus of the MFRTA by including other key mitochondrial stress response pathways, as they have been observed in the nematode Caenorhabditis elegans. These include the mitochondrial unfolded protein response (UPR^mt), mitochondrial biogenesis and autophagy dynamics, the relevant DAF‐16 and SKN‐1 axes, and NAD⁺‐dependent deacetylase activities. To integrate these pathways, we have developed a multilevel hybrid‐modeling paradigm, containing agent‐based elements among stochastic system‐dynamics environments of logically derived ordinary differential equations, to simulate aging mitochondrial phenotypes within a population of energetically demanding cells. The simulation experiments resulted in accurate predictions of physiological parameters over time that accompany normal aging, such as the declines in both NAD⁺ and ATP and an increase in ROS. Additionally, the in silico system was virtually perturbed using a variety of pharmacological (e.g., rapamycin, pterostilbene, paraquat) and genetic (e.g., skn‐1, daf‐16, sod‐2) schemes to quantitate the temporal alterations of specific mechanistic targets, supporting insights into molecular determinants of aging as well as cytoprotective agents that may improve neurological or muscular healthspan.     

Synergistic computational and experimental proteomics approaches for more accurate detection of active serine hydrolases in yeast

An analysis of the structurally and catalytically diverse serine hydrolase protein family in the Saccharomyces cerevisiae proteome was undertaken using two independent but complementary, large-scale approaches. The first approach is based on computational analysis of serine hydrolase active site structures; the second utilizes the chemical reactivity of the serine hydrolase active site in complex mixtures. These proteomics approaches share the ability to fractionate the complex proteome into functional subsets. Each method identified a significant number of sequences, but 15 proteins were identified by both methods. Eight of these were unannotated in the Saccharomyces Genome Database at the time of this study and are thus novel serine hydrolase identifications. Three of the previously uncharacterized proteins are members of a eukaryotic serine hydrolase family, designated as Fsh (family of serine hydrolase), identified here for the first time. OVCA2, a potential human tumor suppressor, and DYR-SCHPO, a dihydrofolate reductase from Schizosaccharomyces pombe, are members of this family. Comparing the combined results to results of other proteomic methods showed that only four of the 15 proteins were identified in a recent large-scale, "shotgun" proteomic analysis and eight were identified using a related, but similar, approach (neither identifies function). Only 10 of the 15 were annotated using alternate motif-based computational tools. The results demonstrate the precision derived from combining complementary, function-based approaches to extract biological information from complex proteomes. The chemical proteomics technology indicates that a functional protein is being expressed in the cell, while the computational proteomics technology adds details about the specific type of function and residue that is likely being labeled. The combination of synergistic methods facilitates analysis, enriches true positive results, and increases confidence in novel identifications. This work also highlights the risks inherent in annotation transfer and the use of scoring functions for determination of correct annotations.     

Metabolic compartmentalization in yeast mitochondria: Burden and solution for squalene overproduction

Harnessing mitochondria is considered as a promising method for biosynthesis of terpenes due to the adequate supply of acetyl-CoA and redox equivalents in mitochondria. However, mitochondrial engineering often causes serious metabolic burden indicated by poor cell growth. Here, we systematically analyzed the metabolic burden caused by the compartmentalization of the MVA pathway in yeast mitochondria for squalene synthesis. The phosphorylated intermediates of the MVA pathway, especially mevalonate-5-P and mevalonate-5-PP, conferred serious toxicity within mitochondria, which significantly compromised its possible advantages for squalene synthesis and was difficult to be significantly improved by routine pathway optimization. These phosphorylated intermediates were converted into ATP analogues, which strongly inhibited ATP-related cell function, such as mitochondrial oxidative respiration. Fortunately, the introduction of a partial MVA pathway from acetyl-CoA to mevalonate in mitochondria as well as the augmentation of the synthesis of mevalonate in cytosol could significantly promote the growth of yeasts. Accordingly, a combinatorial strategy of cytoplasmic and mitochondrial engineering was proposed to alleviate the metabolic burden caused by the compartmentalized MVA pathway in mitochondria and improve cell growth. The strategy also displayed the superimposed effect of cytoplasmic engineering and mitochondrial engineering on squalene production. Through a two-stage fermentation process, the squalene titer reached 21.1 g/L with a specific squalene titer of 437.1 mg/g dcw, which was the highest at present. This provides new insight into the production of squalene and other terpenes in yeasts based on the advantages of mitochondrial engineering.     

A novel micro-to-macro approach for cardiac tissue mechanics

For studying cardiac mechanics, hyperelastic anisotropic computational models have been developed which require the tissue anisotropic and hyperelastic parameters. These parameters are obtained by tissue samples mechanically testing. The validity of such parameters are limited to the specific tissue sample only. They are not adaptable for pathological tissues commonly associated with tissue microstructure alterations. To investigate cardiac tissue mechanics, a novel approach is proposed to model hyperelasticity and anisotropy. This approach is adaptable to various tissue microstructural constituent’s distributions in normal and pathological tissues. In this approach, the tissue is idealized as composite material consisting of cardiomyocytes distributed in extracellular matrix (ECM). The major myocardial tissue constituents are mitochondria and myofibrils while the main ECM’s constituents are collagen fibers and fibroblasts. Accordingly, finite element simulations of uniaxial and equibiaxial tests of normal and infarcted tissue samples with known amounts of these constituents were conducted, leading to corresponding tissue stress–strain data that were fitted to anisotropic/hyperelastic models. The models were validated where they showed good agreement characterized by maximum average stress-strain errors of 16.17 and 10.01% for normal and infarcted cardiac tissue, respectively. This demonstrate the effectiveness of the proposed models in accurate characterization of healthy and pathological cardiac tissues.     

Clustering hybrid regression: a novel computational approach to study and model biohydrogen production through dark fermentation

Clustering hybrid regression (CHR) approach was developed and evaluated using data from H(2)-producing glucose-based, suspended-cell bioreactor operated for 5 months. The aim was to describe the relationship between metabolic end products and H(2)-production rate. Self-organizing maps (SOM) were used to better visualize the dataset and to detect main metabolic patterns in bioprocess data. SOM detected three distinct metabolic patterns with butyrate, acetate and ethanol as dominant metabolites, respectively. Butyrate dominated metabolism was related to high H(2) production, while acetate and ethanol dominated metabolisms resulted in low H(2) production. CHR models performed well [mean square error (MSE) 0.55 and 0.56] in modeling the H(2)-production rate. The results validate the suitability of the CHR approach in describing the bioprocess behavior and in the modeling of H(2) production rate. The developed model can help in discovering key metabolic interactions and suitable process parameters from complex datasets, and increase the understanding of the bioprocesses occurring in engineered and natural environments.     

A novel bioinformatics approach identifies candidate genes for the synthesis and feruloylation of arabinoxylan

Arabinoxylans (AXs) are major components of graminaceous plant cell walls, including those in the grain and straw of economically important cereals. Despite some recent advances in identifying the genes encoding biosynthetic enzymes for a number of other plant cell wall polysaccharides, the genes encoding enzymes of the final stages of AX synthesis have not been identified. We have therefore adopted a novel bioinformatics approach based on estimation of differential expression of orthologous genes between taxonomic divisions of species. Over 3 million public domain cereal and dicot expressed sequence tags were mapped onto the complete sets of rice (Oryza sativa) and Arabidopsis (Arabidopsis thaliana) genes, respectively. It was assumed that genes in cereals involved in AX biosynthesis would be expressed at high levels and that their orthologs in dicotyledonous plants would be expressed at much lower levels. Considering all rice genes encoding putative glycosyl transferases (GTs) predicted to be integral membrane proteins, genes in the GT43, GT47, and GT61 families emerged as much the strongest candidates. When the search was widened to all other rice or Arabidopsis genes predicted to encode integral membrane proteins, cereal genes in Pfam family PF02458 emerged as candidates for the feruloylation of AX. Our analysis, known activities, and recent findings elsewhere are most consistent with genes in the GT43 families encoding beta-1,4-xylan synthases, genes in the GT47 family encoding xylan alpha-1,2- or alpha-1,3-arabinosyl transferases, and genes in the GT61 family encoding feruloyl-AX beta-1,2-xylosyl transferases.     

A novel proteomic approach identifies new interaction partners for proliferating cell nuclear antigen

During DNA replication and repair, many proteins bind to and dissociate in a highly specific and ordered manner from proliferating cell nuclear antigen (PCNA). We describe a combined approach of in silico searches at the genome level and combinatorial peptide synthesis to investigate the binding properties of hundreds of short PCNA-interacting peptides (PIP-peptides) to archaeal and eukaryal PCNAs. Biological relevance of our combined approach was demonstrated by identification an inactive complex of Pyrococcus abyssi ribonuclease HII with PCNA. Furthermore we show that PIP-peptides interact with PCNA largely in a sequence independent manner. Our experimental approach also identified many so far unidentified PCNA interacting peptides in a number of human proteins.     

Manipulation of GES and ERG20 for geraniol overproduction in Saccharomyces cerevisiae

Manipulation of monoterpene synthases to maximize flux towards targeted products from GPP (geranyl diphosphate) is the main challenge for heterologous monoterpene overproduction, in addition to cell toxicity from compounds themselves. In our study, by manipulation of the key enzymes geraniol synthase (GES) and farnesyl diphosphate synthase (Erg20), geraniol (a valuable acyclic monoterpene alcohol) overproduction was achieved in Saccharomyces cerevisiae with truncated 3-hydroxy-3-methylglutaryl-coenzyme reductase (tHMGR) and isopentenyl diphosphate isomerase (IDI1) overexpressed. The expressions of all above engineered genes were under the control of Gal promoter for alleviating product toxicity. Geraniol production varied from trace amount to 43.19 mg/L (CrGES, GES from Catharanthus roseus) by screening of nine GESs from diverse species. Further through protein structure analysis and site-directed mutation in CrGES, it was firstly demonstrated that among the high-conserved amino acid residues located in active pocket, Y436 and D501 with strong affinity to diphosphate function group, were critical for the dephosphorylation (the core step for geraniol formation). Moreover, the truncation position of the transit peptide from the N-terminus of CrGES was found to influence protein expression and activity significantly, obtaining a titer of 191.61 mg/L geraniol in strain with CrGES truncated at S43 (t3CrGES). Furthermore, directed by surface electrostatics distribution of t3CrGES and Erg20^WW (Erg20^F96W-N127W), co-expression of the reverse fusion of Erg20^ww/t3CrGES and another copy of Erg20^WW promoted the geraniol titer to 523.96 mg/L at shakes flask level, due to enhancing GPP accessibility led by protein interaction of t3CrGES-Erg20^WW and the free Erg20^WW. Eventually, a highest reported titer of 1.68 g/L geraniol in eukaryote cells was achieved in 2.0 L fed-batch fermentation under carbon restriction strategy. Our research opens large opportunities for other microbial production of monoterpenes. It also sets a good reference for desired compounds overproduction in microorganisms in terms of manipulation of key enzymes by protein engineering and metabolic engineering.     

A chemical and computational approach to comprehensive glycation characterization on antibodies

Non-enzymatic glycation is a challenging post-translational modification to characterize due to the structural heterogeneity it generates in proteins. Glycation has become increasingly recognized as an important product quality attribute to monitor, particularly for the biotechnology sector, which produces recombinant proteins under conditions that are amenable to protein glycation. The elucidation of sites of glycation can be problematic using conventional collision-induced dissociation (CID)-based mass spectrometry because of the predominance of neutral loss ions. A method to characterize glycation using an IgG1 monoclonal antibody (mAb) as a model is reported here. The sugars present on this mAb were derivatized using sodium borohydride chemistry to stabilize the linkage and identified using CID-based MS² mass spectrometry and spectral search engines. Quantification of specific glycation sites was then done using a targeted MS¹ based approach, which allowed the identification of a glycation hot spot in the heavy chain complementarity-determining region 3 of the mAb. This targeted approach provided a path forward to developing a structural understanding of the propensity of sites to become glycated on mAbs. Through structural analysis we propose a model in which the number and 3-dimensional distances of carboxylic acid amino acyl residues create a favorable environment for glycation to occur.     

A novel canonical dual computational approach for prion AGAAAAGA amyloid fibril molecular modeling

Many experimental studies have shown that the prion AGAAAAGA palindrome hydrophobic region (113-120) has amyloid fibril forming properties and plays an important role in prion diseases. However, due to the unstable, noncrystalline and insoluble nature of the amyloid fibril, to date structural information on AGAAAAGA region (113-120) has been very limited. This region falls just within the N-terminal unstructured region PrP (1-123) of prion proteins. Traditional X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy experimental methods cannot be used to get its structural information. Under this background, this paper introduces a novel approach of the canonical dual theory to address the 3D atomic-resolution structure of prion AGAAAAGA amyloid fibrils. The novel and powerful canonical dual computational approach introduced in this paper is for the molecular modeling of prion AGAAAAGA amyloid fibrils, and that the optimal atomic-resolution structures of prion AGAAAAGA amyloid fibils presented in this paper are useful for the drive to find treatments for prion diseases in the field of medicinal chemistry. Overall, this paper presents an important method and provides useful information for treatments of prion diseases.     

Novel approach to engineer strains for simultaneous sugar utilization

Use of lignocellulosic biomass as a second generation feedstock in the biofuels industry is a pressing challenge. Among other difficulties in using lignocellulosic biomass, one major challenge is the optimal utilization of both 6-carbon (glucose) and 5-carbon (xylose) sugars by industrial microorganisms. Most industrial microorganisms preferentially utilize glucose over xylose owing to the regulatory phenomenon of carbon catabolite repression (CCR). Microorganisms that can co-utilize glucose and xylose are of considerable interest to the biofuels industry due to their ability to simplify the fermentation processes. However, elimination of CCR in microorganisms is challenging due to the multiple coordinating mechanisms involved. We report a novel algorithm, SIMUP, which finds metabolic engineering strategies to force co-utilization of two sugars, without targeting the regulatory pathways of CCR. Mutants of Escherichia coli based on SIMUP algorithm showed predicted growth phenotypes and co-utilized glucose and xylose; however, consumed the sugars slower than the wild-type. Some solutions identified by the algorithm were based on stoichiometric imbalance and were not obvious from the metabolic network topology. Furthermore, sequencing studies on the genes involved in CCR showed that the mechanism for co-utilization of the sugars could be different from previously known mechanisms.     

Development of a novel continuous culture device for experimental evolution of bacterial populations

The availability of a robust and reliable continuous culture apparatus that eliminates wall growth problems would lead to many applications in the microbial field, including allowing genetically engineered strains to recover high fitness, improving biodegradation strains, and predicting likely antibiotic resistance mechanisms. We describe the design and implementation of a novel automated continuous culture machine that can be used both in time-dependent mode (similar to a chemostat) and turbidostat modes, in which wall growth is circumvented through the use of a long, variably divisible tube of growth medium. This tube can be restricted with clamps to create a mobile growth chamber region in which static portions of the tube and the associated medium are replaced together at equal rates. To functionally test the device as a tool for re-adaptation of engineered strains, we evolved a strain carrying a highly deleterious deletion of Elongation Factor P, a gene involved in translation. In 200 generations over 2 weeks of dilution cycles, the evolved strain improved in generation time by a factor of three, with no contaminations and easy manipulation.