In-depth profiling of lysine-producing Corynebacterium glutamicum by combined analysis of the transcriptome, metabolome, and fluxome

Recent advances in the Design-Build-Test-Learn (DBTL) cycle for systems metabolic engineering of Corynebacterium glutamicum

Existing microbial engineering strategies-encompassing metabolic engineering, systems biology, and systems metabolic engineering-have significantly enhanced the potential of microbial cell factories as sustainable alternatives to the petrochemical industry by optimizing metabolic pathways. Recently, systems metabolic engineering, which integrates tools from synthetic biology, enzyme engineering, omics technology, and evolutionary engineering, has been successfully developed. By leveraging modern engineering strategies within the Design-Build-Test-Learn (DBTL) cycle framework, these advancements have revolutionized the biosynthesis of valuable compounds. This review highlights recent progress in the metabolic engineering of Corynebacterium glutamicum, a versatile microbial platform, achieved through various approaches from traditional metabolic engineering to advanced systems metabolic engineering, all within the DBTL cycle. A particular focus is placed C5 platform chemicals derived from L-lysine, one of the key amino acid production pathways of C. glutamicum. The development of DBTL cycle-based metabolic engineering strategies for this process is discussed.

Rapid exometabolome footprinting combined with multivariate statistics: A powerful tool for bioprocess optimization

Corynebacterium glutamicum is used as an industrial platform organism for amino acid production. Previously, the organism was utilized to produce l-histidine with research focusing on metabolic engineering approaches to increase titer and yield. Only a few studies have been published that provide information on bioprocess development, with media optimization and fed-batch cultivation procedure being particularly promising areas. In this work, we show how experimental setups such as miniature cultivation technology, dynamic and time-optimized LC-MS/MS metabolic footprinting tools, and automated workflows for the detection of local and global metabolic patterns can significantly accelerate bioprocess development. Potential media bottlenecks in form of phosphate and magnesium availability were identified by sensitivity analysis in parallelized microscale cultivation assisted by lab automation. A rapid dilute-and-shoot flow-injection-analysis tandem mass spectrometry approach was used to cope with the resulting cultivation throughput and allowed to quantify amino acids with 1 min per sample. We were able to increase the l-histidine titer of a C. glutamicum random mutagenesis mutant by a factor of 5.8 through process optimization while also identifying both known and previously unknown targets for additional strain improvements. The presented methodology can be seen as a supplement to traditional approaches in the field of bioprocess development.

Mitochondrial enzyme FAHD1 reduces ROS in osteosarcoma

This study investigated the impact of overexpressing the mitochondrial enzyme Fumarylacetoacetate hydrolase domain-containing protein 1 (FAHD1) in human osteosarcoma epithelial cells (U2OS) in vitro. While the downregulation or knockdown of FAHD1 has been extensively researched in various cell types, this study aimed to pioneer the exploration of how increased catalytic activity of human FAHD1 isoform 1 (hFAHD1.1) affects human cell metabolism. Our hypothesis posited that elevation in FAHD1 activity would lead to depletion of mitochondrial oxaloacetate levels. This depletion could potentially result in a decrease in the flux of the tricarboxylic acid (TCA) cycle, thereby accompanied by reduced ROS production. In addition to hFAHD1.1 overexpression, stable U2OS cell lines were established overexpressing a catalytically enhanced variant (T192S) and a loss-of-function variant (K123A) of hFAHD1. It is noteworthy that homologs of the T192S variant are present in animals exhibiting increased resistance to oxidative stress and cancer. Our findings demonstrate that heightened activity of the mitochondrial enzyme FAHD1 decreases cellular ROS levels in U2OS cells. However, these results also prompt a series of intriguing questions regarding the potential role of FAHD1 in mitochondrial metabolism and cellular development.

Structure-Guided Protein Engineering of Glyceraldehyde-3-phosphate Dehydrogenase from Corynebacterium glutamicum for Dual NAD/NADP Cofactor Specificity

Since the discovery of l-glutamate-producing Corynebacterium glutamicum, it has evolved to be an industrial workhorse. For biobased chemical production, suppling sufficient amounts of the NADPH cofactor is crucial. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), a glycolytic enzyme that converts glyceraldehyde-3-phosphate (G3P) to 1,3-bisphosphoglycerate and produces NADH, is a major prospective solution for the cofactor imbalance issue. In this study, we determined the crystal structure of GAPDH from C. glutamicum ATCC13032 (CgGAPDH). Based on the structural information, we generated six CgGAPDH variants, CgGAPDHL36S, CgGAPDHL36S/T37K, CgGAPDHL36S/T37K/P192S, CgGAPDHL36S/T37K/F100V/P192S, CgGAPDHL36S/T37K/F100L/P192S, and CgGAPDHL36S/T37K/F100I/P192S, that can produce both NADH and NAPDH. The final CgGAPDHL36S/T37K/F100V/P192S variant showed a 212-fold increase in enzyme activity for NADP as well as 200% and 30% increased activity for the G3P substrate under NAD and NADP cofactor conditions, respectively. In addition, crystal structures of CgGAPDH variants in complex with NAD(P) permit the elucidation of differences between wild-type CgGAPDH and variants in relation to cofactor stabilization.

Influence of metabolic guilds on a temporal scale in an experimental fermented food derived microbial community

The influence of community diversity, which can be measured at the level of metabolic guilds, on community function is a central question in ecology. Particularly, the long-term temporal dynamic between a community's function and its diversity remains unclear. We investigated the influence of metabolic guild diversity on associated community function by propagating natural microbial communities from a traditionally fermented milk beverage diluted to various levels. Specifically, we assessed the influence of less abundant microbial types, such as yeast, on community functionality and bacterial community compositions over repeated propagation cycles amounting to ∼100 generations. The starting richness of metabolic guilds had a repeatable effect on bacterial community compositions, metabolic profiles, and acidity. The influence of a single metabolic guild, yeast in our study, played a dramatic role on function, but interestingly not on long-term species sorting trajectories of the remaining bacterial community. Our results together suggest an unexpected niche division between yeast and bacterial communities and evidence ecological selection on the microbial communities in our system.

Transcriptomics and metabolomics analysis of L-phenylalanine overproduction in Escherichia coli

BACKGROUND

Highly efficient production of L-phenylalanine (L-Phe) in E. coli has been achieved by multiple rounds of random mutagenesis and modification of key genes of the shikimate (SHIK) and L-Phe branch pathways. In this study, we performed transcriptomic (16, 24 and 48 h) and metabolomic analyses (8, 16, 24, 32,40, and 48 h) based on time sequences in an engineered E. coli strain producing L-Phe, aiming to reveal the overall changes of metabolic activities during the fermentation process.

RESULTS

The largest biomass increase rate and the highest production rate were seen at 16 h and 24 h of fermentation, respectively reaching 5.9 h^-1 and 2.76 g/L/h, while the maximal L-Phe titer of 60 g/L was accumulated after 48 h of fermentation. The DEGs and metabolites involved in the EMP, PP, TCA, SHIIK and L-Phe-branch pathways showed significant differences at different stages of fermentation. Specifically, the significant upregulation of genes encoding rate-limiting enzymes (aroD and yidB) and key genes (aroF, pheA and aspC) pushed more carbon flux toward the L-Phe synthesis. The RIA changes of a number of important metabolites (DAHP, DHS, DHQ, Glu and PPN) enabled the adequate supply of precursors for high-yield L-Phe production. In addition, other genes related to Glc transport and phosphate metabolism increased the absorption of Glc and contributed to rerouting the carbon flux into the L-Phe-branch.

CONCLUSIONS

Transcriptomic and metabolomic analyses of an L-Phe overproducing strain of E. coli confirmed that precursor supply was not a major limiting factor in this strain, whereas the rational distribution of metabolic fluxes was achieved by redistributing the carbon flux (for example, the expression intensity of the genes tyrB, aspC, aroL and aroF/G/H or the activity of these enzymes is increased to some extent), which is the optimal strategy for enhancing L-Phe production.

Systems metabolic engineering upgrades Corynebacterium glutamicum for selective high-level production of the chiral drug precursor and cell-protective extremolyte L-pipecolic acid

The nonproteinogenic cyclic metabolite l-pipecolic acid is a chiral precursor for the synthesis of various commercial drugs and functions as a cell-protective extremolyte and mediator of defense in plants, enabling high-value applications in the pharmaceutical, medical, cosmetic, and agrochemical markets. To date, the production of the compound is unfavorably fossil-based. Here, we upgraded the strain Corynebacterium glutamicum for l-pipecolic acid production using systems metabolic engineering. Heterologous expression of the l-lysine 6-dehydrogenase pathway, apparently the best route to be used in the microbe, yielded a family of strains that enabled successful de novo synthesis from glucose but approached a limit of performance at a yield of 0.18 mol mol^-1. Detailed analysis of the producers at the transcriptome, proteome, and metabolome levels revealed that the requirements of the introduced route were largely incompatible with the cellular environment, which could not be overcome after several further rounds of metabolic engineering. Based on the gained knowledge, we based the strain design on l-l-lysine 6-aminotransferase instead, which enabled a substantially higher in vivo flux toward l-pipecolic acid. The tailormade producer C. glutamicum PIA-7 formed l-pipecolic acid up to a yield of 562 mmol mol^-1, representing 75% of the theoretical maximum. Ultimately, the advanced mutant PIA-10B achieved a titer of 93 g L^-1 in a fed-batch process on glucose, outperforming all previous efforts to synthesize this valuable molecule de novo and even approaching the level of biotransformation from l-lysine. Notably, the use of C. glutamicum allows the safe production of GRAS-designated l-pipecolic acid, providing extra benefit toward addressing the high-value pharmaceutical, medical, and cosmetic markets. In summary, our development sets a milestone toward the commercialization of biobased l-pipecolic acid.

Assessing the growth kinetics and stoichiometry of Escherichia coli at the single-cell level

Microfluidic cultivation and single-cell analysis are inherent parts of modern microbial biotechnology and microbiology. However, implementing biochemical engineering principles based on the kinetics and stoichiometry of growth in microscopic spaces remained unattained. We here present a novel integrated framework that utilizes distinct microfluidic cultivation technologies and single-cell analytics to make the fundamental math of process-oriented biochemical engineering applicable at the single-cell level. A combination of non-invasive optical cell mass determination with sub-pg sensitivity, microfluidic perfusion cultivations for establishing physiological steady-states, and picoliter batch reactors, enabled the quantification of all physiological parameters relevant to approximate a material balance in microfluidic reaction environments. We determined state variables (biomass concentration based on single-cell dry weight and mass density), biomass synthesis rates, and substrate affinities of cells grown in microfluidic environments. Based on this data, we mathematically derived the specific kinetics of substrate uptake and growth stoichiometry in glucose-grown Escherichia coli with single-cell resolution. This framework may initiate microscale material balancing beyond the averaged values obtained from populations as a basis for integrating heterogeneous kinetic and stoichiometric single-cell data into generalized bioprocess models and descriptions.

Systems metabolic engineering of Corynebacterium glutamicum eliminates all by-products for selective and high-yield production of the platform chemical 5-aminovalerate

5-aminovalerate (AVA) is a platform chemical of substantial commercial value to derive nylon-5 and five-carbon derivatives like δ-valerolactam, 1,5-pentanediol, glutarate, and 5-hydroxyvalerate. De-novo bio-production synthesis of AVA using metabolically engineered cell factories is regarded as exemplary route to provide this chemical in a sustainable way. So far, this route is limited by low titers, rates and yields and suffers from high levels of by-products. To overcome these limitations, we developed a novel family of AVA producing C. glutamicum cell factories. Stepwise optimization included (i) improved AVA biosynthesis by expression balancing of the heterologous davAB genes from P. putida, (ii) reduced formation of the by-product glutarate by disruption of the catabolic y-aminobutyrate pathway (iii), increased AVA export, and (iv) reduced AVA re-import via native and heterologous transporters to account for the accumulation of intracellular AVA up to 300 mM. Strain C. glutamicum AVA-5A, obtained after several optimization rounds, produced 48.3 g L^-1 AVA in a fed-batch process and achieved a high yield of 0.21 g g^-1. Surprisingly in later stages, the mutant suddenly accumulated glutarate to an extent equivalent to 30% of the amount of AVA formed, tenfold more than in the early process, displaying a severe drawback toward industrial production. Further exploration led to the discovery that ArgD, naturally aminating N-acetyl-l-ornithine during l-arginine biosynthesis, exhibits deaminating side activity on AVA toward glutarate formation. This promiscuity became relevant because of the high intracellular AVA level and the fact that ArgD became unoccupied with the gradually stronger switch-off of anabolism during production. Glutarate formation was favorably abolished in the advanced strains AVA-6A, AVA-6B, and AVA-7, all lacking argD. In a fed-batch process, C. glutamicum AVA-7 produced 46.5 g L^-1 AVA at a yield of 0.34 g g^-1 and a maximum productivity of 1.52 g L^-1 h^-1, outperforming all previously reported efforts and stetting a milestone toward industrial manufacturing of AVA. Notably, the novel cell factories are fully genome-based, offering high genetic stability and requiring no selection markers.

Microbial Remediation: A Promising Tool for Reclamation of Contaminated Sites with Special Emphasis on Heavy Metal and Pesticide Pollution: A Review

Heavy metal and pesticide pollution have become an inevitable part of the modern industrialized environment that find their way into all ecosystems. Because of their persistent nature, recalcitrance, high toxicity and biological enrichment, metal and pesticide pollution has threatened the stability of the environment as well as the health of living beings. Due to the environmental persistence of heavy metals and pesticides, they get accumulated in the environs and consequently lead to food chain contamination. Therefore, remediation of heavy metals and pesticide contaminations needs to be addressed as a high priority. Various physico-chemical approaches have been employed for this purpose, but they have significant drawbacks such as high expenses, high labor, alteration in soil properties, disruption of native soil microflora and generation of toxic by-products. Researchers worldwide are focusing on bioremediation strategies to overcome this multifaceted problem, i.e., the removal, immobilization and detoxification of pesticides and heavy metals, in the most efficient and cost-effective ways. For a period of millions of evolutionary years, microorganisms have become resistant to intoxicants and have developed the capability to remediate heavy metal ions and pesticides, and as a result, they have helped in the restoration of the natural state of degraded environs with long term environmental benefits. Keeping in view the environmental and health concerns imposed by heavy metals and pesticides in our society, we aimed to present a generalized picture of the bioremediation capacity of microorganisms. We explore the use of bacteria, fungi, algae and genetically engineered microbes for the remediation of both metals and pesticides. This review summarizes the major detoxification pathways and bioremediation technologies; in addition to that, a brief account is given of molecular approaches such as systemic biology, gene editing and omics that have enhanced the bioremediation process and widened its microbiological techniques toward the remediation of heavy metals and pesticides.

Transcriptional Regulation of the Creatine Utilization Genes of Corynebacterium glutamicum ATCC 14067 by AmtR, a Central Nitrogen Regulator

In the genus Corynebacterium, AmtR is a key component of the nitrogen regulatory system, and it belongs to the TetR family of transcription regulators. There has been much research on AmtR structure, functions, and regulons in the type strain C. glutamicum ATCC 13032, but little research in other C. glutamicum strains. In this study, chromatin immunoprecipitation and massively parallel DNA sequencing (ChIP-seq) was performed to identify the AmtR regulon in C. glutamicum ATCC 14067. Ten peaks were obtained in the C. glutamicum ATCC 14067 genome including two new peaks related to three operons (RS_01910-RS_01915, RS_15995, and RS_16000). The interactions between AmtR and the promoter regions of the three operons were confirmed by electrophoretic mobility shift assays (EMSAs). The RS_01910, RS_01915, RS_15995, and RS_16000 are not present in the type strain C. glutamicum ATCC 13032. Sequence analysis indicates that RS_01910, RS_01915, RS_15995, and RS_16000, are related to the degradation of creatine and creatinine; RS_01910 may encode a protein related to creatine transport. The genes RS_01910, RS_01915, RS_15995, and RS_16000 were given the names crnA, creT, cshA, and hyuB, respectively. Real-time quantitative PCR (RT-qPCR) analysis and sfGFP (superfolder green fluorescent protein) analysis reveal that AmtR directly and negatively regulates the transcription and expression of crnA, creT, cshA, and hyuB. A growth test shows that C. glutamicum ATCC 14067 can use creatine or creatinine as a sole nitrogen source. In comparison, a creT deletion mutant strain is able to grow on creatinine but loses the ability to grow on creatine. This study provides the first genome-wide captures of the dynamics of in vivo AmtR binding events and the regulatory network they define. These elements provide more options for synthetic biology by extending the scope of the AmtR regulon.

Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis

Mastitis, inflammation of the mammary gland, is the most prevalent disease in dairy cattle that has a potential impact on profitability and animal welfare. Specifically designed multi-omics studies can be used to prioritize candidate genes and identify biomarkers and the molecular mechanisms underlying mastitis in dairy cattle. Hence, the present study aimed to explore the genetic basis of bovine mastitis by integrating microarray and RNA-Seq data containing healthy and mastitic samples in comparative transcriptome analysis with the results of published genome-wide association studies (GWAS) using a literature mining approach. The integration of different information sources resulted in the identification of 33 common and relevant genes associated with bovine mastitis. Among these, seven genes—CXCR1, HCK, IL1RN, MMP9, S100A9, GRO1, and SOCS3—were identified as the hub genes (highly connected genes) for mastitis susceptibility and resistance, and were subjected to protein-protein interaction (PPI) network and gene regulatory network construction. Gene ontology annotation and enrichment analysis revealed 23, 7, and 4 GO terms related to mastitis in the biological process, molecular function, and cellular component categories, respectively. Moreover, the main metabolic-signalling pathways responsible for the regulation of immune or inflammatory responses were significantly enriched in cytokine–cytokine-receptor interaction, the IL-17 signaling pathway, viral protein interaction with cytokines and cytokine receptors, and the chemokine signaling pathway. Consequently, the identification of these genes, pathways, and their respective functions could contribute to a better understanding of the genetics and mechanisms regulating mastitis and can be considered a starting point for future studies on bovine mastitis.

Transcriptome analysis of L-leucine-producing Corynebacterium glutamicum under the addition of trimethylglycine

It has been widely reported that the addition of trimethylglycine (betaine) decreases osmotic pressure inhibition for cell growth, leading to increased production of amino acids. However, the underlying mechanism is unclear. To determine the global metabolic differences that occur under the addition of trimethylglycine, transcriptome analysis was performed. Transcriptome analysis of Corynebacterium glutamicum JL1211 revealed that 272 genes exhibited significant changes under trimethylglycine addition. We performed Gene Ontology (GO) and KEGG enrichment pathway analyses on these differentially expressed genes (DEGs). Significantly upregulated genes were mainly involved in the regulation of ABC transporters, especially phosphate transporters and sulfur metabolism. The three phosphate transporter genes pstC, pstA and pstB were upregulated by 13.06-fold, 29.80-fold and 30.49-fold, respectively. Notably, the transcriptional levels of the cysD, cysN, cysH and sir genes were upregulated by 81.5-fold, 57.3-fold, 77.6-fold and 125.4-fold, respectively, consistent with assimilatory sulfate reduction under the addition of trimethylglycine. The upregulation of ilvBN and leuD genes might result in increased L-leucine formation. The data indicated changes in the transcriptome of C. glutamicum with trimethylglycine treatment, thus providing a mechanism supporting the application of trimethylglycine in the production of L-leucine and other amino acids by C. glutamicum strains.

Comparison of bacteria disintegration methods and their influence on data analysis in metabolomics

Metabolomic experiments usually contain many different steps, each of which can strongly influence the obtained results. In this work, metabolic analyses of six bacterial strains were performed in light of three different bacterial cell disintegration methods. Three strains were gram-negative (Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumoniae), and three were gram-positive (Corynebacterium glutamicum, Bacillus cereus, and Enterococcus faecalis). For extraction, the methanol–water extraction method (1:1) was chosen. To compare the efficiency of different cell disintegration methods, sonication, sand mill, and tissue lyser were used. For bacterial extract metabolite analysis, ¹H NMR together with univariate and multivariate analyses were applied. The obtained results showed that metabolite concentrations are strongly dependent on the cell lysing methodology used and are different for various bacterial strains. The results clearly show that one of the disruption methods gives the highest concentration for most identified compounds (e. g. sand mill for E. faecalis and tissue lyser for B. cereus). This study indicated that the comparison of samples prepared by different procedures can lead to false or imprecise results, leaving an imprint of the disintegration method. Furthermore, the presented results showed that NMR might be a useful bacterial strain identification and differentiation method. In addition to disintegration method comparison, the metabolic profiles of each elaborated strain were analyzed, and each exhibited its metabolic profile. Some metabolites were identified by the ¹H NMR method in only one strain. The results of multivariate data analyses (PCA) show that regardless of the disintegration method used, the strain group can be identified. Presented results can be significant for all types of microbial studies containing the metabolomic targeted and non-targeted analysis.

Advances in metabolic engineering of Corynebacterium glutamicum to produce high-value active ingredients for food, feed, human health, and well-being

The soil microbe Corynebacterium glutamicum is a leading workhorse in industrial biotechnology and has become famous for its power to synthetise amino acids and a range of bulk chemicals at high titre and yield. The product portfolio of the microbe is continuously expanding. Moreover, metabolically engineered strains of C. glutamicum produce more than 30 high value active ingredients, including signature molecules of raspberry, savoury, and orange flavours, sun blockers, anti-ageing sugars, and polymers for regenerative medicine. Herein, we highlight recent advances in engineering of the microbe into novel cell factories that overproduce these precious molecules from pioneering proofs-of-concept up to industrial productivity.

Multi-omics tools for studying microbial biofilms: current perspectives and future directions

The advent of omics technologies has greatly improved our understanding of microbial biology, particularly in the last two decades. The field of microbial biofilms is, however, relatively new, consolidated in the 1980s. The morphogenic switching by microbes from planktonic to biofilm phenotype confers numerous survival advantages such as resistance to desiccation, antibiotics, biocides, ultraviolet radiation, and host immune responses, thereby complicating treatment strategies for pathogenic microorganisms. Hence, understanding the mechanisms governing the biofilm phenotype can result in efficient treatment strategies directed specifically against molecular markers mediating this process. The application of omics technologies for studying microbial biofilms is relatively less explored and holds great promise in furthering our understanding of biofilm biology. In this review, we provide an overview of the application of omics tools such as transcriptomics, proteomics, and metabolomics as well as multi-omics approaches for studying microbial biofilms in the current literature. We also highlight how the use of omics tools directed at various stages of the biological information flow, from genes to metabolites, can be integrated via multi-omics platforms to provide a holistic view of biofilm biology. Following this, we propose a future artificial intelligence-based multi-omics platform that can predict the pathways associated with different biofilm phenotypes.

LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism

BACKGROUND

The systems-scale analysis of cellular metabolites, "metabolomics," provides data ideal for applications in metabolic engineering. However, many of the computational tools for strain design are built around Flux Balance Analysis (FBA), which makes assumptions that preclude direct integration of metabolomics data into the underlying models. Finding a way to retain the advantages of FBA's linear structure while relaxing some of its assumptions could allow us to account for metabolite levels and metabolite-dependent regulation in strain design tools built from FBA, improving the accuracy of predictions made by these tools. We designed, implemented, and characterized a modeling strategy based on Dynamic FBA (DFBA), called Linear Kinetics-Dynamic Flux Balance Analysis (LK-DFBA), to satisfy these specifications. Our strategy adds constraints describing the dynamics and regulation of metabolism that are strictly linear. We evaluated LK-DFBA against alternative modeling frameworks using simulated noisy data from a small in silico model and a larger model of central carbon metabolism in E. coli, and compared each framework's ability to recapitulate the original system.

RESULTS

In the smaller model, we found that we could use regression from a dynamic flux estimation (DFE) with an optional non-linear parameter optimization to reproduce metabolite concentration dynamic trends more effectively than an ordinary differential equation model with generalized mass action rate laws when tested under realistic data sampling frequency and noise levels. We observed detrimental effects across all tested modeling approaches when metabolite time course data were missing, but found these effects to be smaller for LK-DFBA in most cases. With the E. coli model, we produced qualitatively reasonable results with similar properties to the smaller model and explored two different parameterization structures that yield trade-offs in computation time and accuracy.

CONCLUSIONS

LK-DFBA allows for calculation of metabolite concentrations and considers metabolite-dependent regulation while still retaining many computational advantages of FBA. This provides the proof-of-principle for a new metabolic modeling framework with the potential to create genome-scale dynamic models and the potential to be applied in strain engineering tools that currently use FBA.

Deciphering the Adaptation of Corynebacterium glutamicum in Transition from Aerobiosis via Microaerobiosis to Anaerobiosis

Zero-growth processes are a promising strategy for the production of reduced molecules and depict a steady transition from aerobic to anaerobic conditions. To investigate the adaptation of Corynebacterium glutamicum to altering oxygen availabilities, we conceived a triple-phase fermentation process that describes a gradual reduction of dissolved oxygen with a shift from aerobiosis via microaerobiosis to anaerobiosis. The distinct process phases were clearly bordered by the bacteria’s physiologic response such as reduced growth rate, biomass substrate yield and altered yield of fermentation products. During the process, sequential samples were drawn at six points and analyzed via RNA-sequencing, for metabolite concentrations and for enzyme activities. We found transcriptional alterations of almost 50% (1421 genes) of the entire protein coding genes and observed an upregulation of fermentative pathways, a rearrangement of respiration, and mitigation of the basic cellular mechanisms such as transcription, translation and replication as a transient response related to the installed oxygen dependent process phases. To investigate the regulatory regime, 18 transcriptionally altered (putative) transcriptional regulators were deleted, but none of the deletion strains showed noticeable growth kinetics under an oxygen restricted environment. However, the described transcriptional adaptation of C. glutamicum resolved to varying oxygen availabilities provides a useful basis for future process and strain engineering.

Comprehensive optimization of the metabolomic methodology for metabolite profiling of Corynebacterium glutamicum

Metabolomics has been a potential tool for strain improvement through analyzing metabolite changes in the context of different conditions. However, the availability of a universal metabolite profiling analysis is still a big challenge. In this study, we presented an optimized liquid chromatography-tandem mass spectrometry-based metabolomics methodology for Corynebacterium glutamicum, an important industrial workhorse. It was found that quenching the cellular metabolism with 5-fold volume of - 20 °C 40% methanol was highly recommended due to its lower cell damage rate and higher intracellular metabolite recovery rate. For extracting intracellular metabolites, ethanol/water (3:1, v/v) at 100 °C combined with acidic acetonitrile/water (1:1, v/v, with 0.1% formic acid) at - 20 °C achieved the unbiased metabolite profiling of C. glutamicum. The established methodology was then applied to investigate the intracellular metabolite differences between C. glutamicum ATCC 13032 and an mscCG-deleted mutant under biotin limitation condition. It was observed that in the presence of the functional L-glutamate exporter MscCG, biotin limitation led to accumulation of intracellular 2-oxoglutarate but not L-glutamate. Deletion of mscCG severely inhibited L-glutamate excretion and resulted in a dramatical increase of intracellular L-glutamate, which in turn affected the metabolite profile. The optimized metabolomics methodology holds promise for promoting studies on metabolic mechanism of C. glutamicum.

Importance of the cultivation history for the response of Escherichia coli to oscillations in scale-down experiments

Large-scale bioreactors are inhomogeneous systems, in which the fluid phase expresses concentration gradients. They depend on the mass transfer and fluid dynamics in the reactor, the feeding strategy, the cell-specific substrate uptake parameters, and the cell density. As high cell densities are only obtained at low specific growth rates, it is necessary to investigate the cellular responses to oscillations in particular under such conditions, an issue which is mostly neglected. Instead, the feed oscillations are often started directly after the batch phase, when the specific growth rate is close to the maximum. We show here that the cultivation mode before oscillations are started has a tremendous effect on the metabolic responses. In difference to cells, which were pre-grown under batch conditions at a high growth rate, Escherichia coli cells that were pre-grown under glucose limitation at a low growth rate accumulate short-chain fatty acids (acetate, lactate, succinate) and glycolysis-related amino acids to a higher extent in a two-compartment scale-down bioreactor. Thus, cells which enter oscillations from a lower specific growth rate seem to react more sensitive to oscillations than cells that are subjected to oscillations directly after a batch phase. These results are interesting in designing reliable scale-down systems, which better reflect large-scale bioprocesses.

Rapid acquisition and model-based analysis of cell-free transcription-translation reactions from nonmodel bacteria

Native cell-free transcription-translation systems offer a rapid route to characterize the regulatory elements (promoters, transcription factors) for gene expression from nonmodel microbial hosts, which can be difficult to assess through traditional in vivo approaches. One such host, Bacillus megaterium, is a giant Gram-positive bacterium with potential biotechnology applications, although many of its regulatory elements remain uncharacterized. Here, we have developed a rapid automated platform for measuring and modeling in vitro cell-free reactions and have applied this to B. megaterium to quantify a range of ribosome binding site variants and previously uncharacterized endogenous constitutive and inducible promoters. To provide quantitative models for cell-free systems, we have also applied a Bayesian approach to infer ordinary differential equation model parameters by simultaneously using time-course data from multiple experimental conditions. Using this modeling framework, we were able to infer previously unknown transcription factor binding affinities and quantify the sharing of cell-free transcription-translation resources (energy, ribosomes, RNA polymerases, nucleotides, and amino acids) using a promoter competition experiment. This allows insights into resource limiting-factors in batch cell-free synthesis mode. Our combined automated and modeling platform allows for the rapid acquisition and model-based analysis of cell-free transcription-translation data from uncharacterized microbial cell hosts, as well as resource competition within cell-free systems, which potentially can be applied to a range of cell-free synthetic biology and biotechnology applications.

The fumarylacetoacetate hydrolase (FAH) superfamily of enzymes: multifunctional enzymes from microbes to mitochondria

Prokaryotic and eukaryotic fumarylacetoacetate hydrolase (FAH) superfamily members, sharing conserved regions that form the so-called FAH-domain, catalyze a remarkable variety of reactions. These enzymes are essential in the metabolic pathways to degrade aromatic compounds in prokaryotes and eukaryotes. It appears that prokaryotic FAH superfamily members evolved mainly to allow microbes to generate energy and useful metabolites from complex carbon sources. We review recent findings, indicating that both prokaryotic and eukaryotic members of the FAH superfamily also display oxaloacetate decarboxylase (ODx) activity. The identification of human FAH domain-containing protein 1 as mitochondrial ODx regulating mitochondrial function supports the new concept that, during evolution, eukaryotic FAH superfamily members have acquired important regulatory functions beyond catabolism of complex carbon sources. Molecular studies on the evolution and function of FAH superfamily members are expected to provide new mechanistic insights in their physiological roles.

The Genome-Scale Integrated Networks in Microorganisms

The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types) of the molecular networks, for example, genome-scale metabolic network (GMN), transcriptional regulatory network (TRN), and signal transduction network (STN). It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling) of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

Systems metabolic engineering strategies for the production of amino acids

Systems metabolic engineering is a multidisciplinary area that integrates systems biology, synthetic biology and evolutionary engineering. It is an efficient approach for strain improvement and process optimization, and has been successfully applied in the microbial production of various chemicals including amino acids. In this review, systems metabolic engineering strategies including pathway-focused approaches, systems biology-based approaches, evolutionary approaches and their applications in two major amino acid producing microorganisms: Corynebacterium glutamicum and Escherichia coli, are summarized.

Mini review: Recombinant production of tailored bio-pharmaceuticals in different Bacillus strains and future perspectives

Bio-pharmaceuticals like antibodies, hormones and growth factors represent about one-fifth of commercial pharmaceuticals. Host candidates of growing interest for recombinant production of these proteins are strains of the genus Bacillus, long being established for biotechnological production of homologous and heterologous proteins. Bacillus strains benefit from development of efficient expression systems in the last decades and emerge as major industrial workhorses for recombinant proteins due to easy cultivation, non-pathogenicity and their ability to secrete recombinant proteins directly into extracellular medium allowing cost-effective downstream processing. Their broad product portfolio of pharmaceutically relevant recombinant proteins described in research include antibody fragments, growth factors, interferons and interleukins, insulin, penicillin G acylase, streptavidin and different kinases produced in various cultivation systems like microtiter plates, shake flasks and bioreactor systems in batch, fed-batch and continuous mode. To further improve production and secretion performance of Bacillus, bottlenecks and limiting factors concerning proteases, chaperones, secretion machinery or feedback mechanisms can be identified on different cell levels from genomics and transcriptomics via proteomics to metabolomics and fluxomics. For systematical identification of recurring patterns characteristic of given regulatory systems and key genetic targets, systems biology and omics-technology provide suitable and promising approaches, pushing Bacillus further towards industrial application for recombinant pharmaceutical protein production.

Culturomics: A New Kid on the Block of OMICS to Enable Personalized Medicine

This innovation analysis highlights the underestimated and versatile potential of the new field of culturomics and examines its relation to other OMICS system sciences such as infectiomics, metabolomics, phenomics, and pharmacomicrobiomics. The advent of molecular biology, followed by the emergence of various disciplines of the genomics, and most importantly metagenomics, brought about the sharp decline of conventional microbiology methods. Emergence of culturomics has a natural synergy with therapeutic and clinical genomic approaches so as to realize personalized medicine. Notably, the concept of culturomics expands on that of phenomics and allows a reintroduction of the culture-based phenotypic characterization into the 21st century research repertoire, bolstered by robust technology for automated and massive execution, but its potential is largely unappreciated at present; the few available references show unenthusiastic pursuit and in narrow applications. This has not to be so: depending on the specific brand of culturomics, the scope of applications may extend to medicine, agriculture, environmental sciences, pharmacomicrobiomics, and biotechnology innovation. Moreover, culturomics may produce Big Data. This calls for a new generation of data scientists and innovative ways of harnessing and valorizing Big Data beyond classical genomics. Much more detailed and objective classification and identification of microbiota may soon be at hand through culturomics, thus enabling precision diagnosis toward truly personalized medicine. Culturomics may both widen the scope of microbiology and improve its contributions to diagnostics and personalized medicine, characterizing microbes and determining their associations with health and disease dynamics.

Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production

Metabolic engineering of industrial microorganisms to produce chemicals, fuels, and drugs has attracted increasing interest as it provides an environment-friendly and renewable route that does not depend on depleting petroleum sources. However, the microbial metabolism is so complex that metabolic engineering efforts often have difficulty in achieving a satisfactory yield, titer, or productivity of the target chemical. To overcome this challenge, ¹³C Metabolic Flux Analysis (¹³C-MFA) has been developed to investigate rigorously the cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, ¹³C-MFA has been widely used in academic labs and the biotechnology industry to pinpoint the key issues related to microbial-based chemical production and to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this chapter we introduce the basics of ¹³C-MFA and illustrate how ¹³C-MFA has been applied to synergize with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production.

Actinobacteria: Current research and perspectives for bioremediation of pesticides and heavy metals

Actinobacteria exhibit cosmopolitan distribution since their members are widely distributed in aquatic and terrestrial ecosystems. In the environment they play relevant ecological roles including recycling of substances, degradation of complex polymers, and production of bioactive molecules. Biotechnological potential of actinobacteria in the environment was demonstrated by their ability to remove organic and inorganic pollutants. This ability is the reason why actinobacteria have received special attention as candidates for bioremediation, which has gained importance because of the widespread release of contaminants into the environment. Among organic contaminants, pesticides are widely used for pest control, although the negative impact of these chemicals in the environmental balance is increasingly becoming apparent. Similarly, the extensive application of heavy metals in industrial processes lead to highly contaminated areas worldwide. Several studies focused in the use of actinobacteria for cleaning up the environment were performed in the last 15 years. Strategies such as bioaugmentation, biostimulation, cell immobilization, production of biosurfactants, design of defined mixed cultures and the use of plant-microbe systems were developed to enhance the capabilities of actinobacteria in bioremediation. In this review, we compiled and discussed works focused in the study of different bioremediation strategies using actinobacteria and how they contributed to the improvement of the already existing strategies. In addition, we discuss the importance of omic studies to elucidate mechanisms and regulations that bacteria use to cope with pollutant toxicity, since they are still little known in actinobacteria. A brief account of sources and harmful effects of pesticides and heavy metals is also given.

Analysis of intracellular metabolites of Corynebacterium glutamicum at high cell density with automated sampling and filtration and assessment of engineered enzymes for effective l-lysine production

Engineering of enzymes and pathways is generally required for the development of efficient strains for bioproduction processes. To this end, quantitative and reliable data of intracellular metabolites are highly desired, but often not available, especially for conditions more close to industrial applications, i.e. at high cell density and product concentration. Here, we investigated the intracellular metabolite profiles of an engineered l-lysine-producing Corynebacterium glutamicum strain and the corresponding wild-type strain to assess the impacts of deregulation of product inhibition of the key enzymes aspartate kinase and phosphoenolpyruvate carboxylase and to identify potentials for their further improvement. A bioreactor system with automated fast-sampling, filtration and on-filter quenching of the metabolism was used for a more reliable determination of intracellular metabolites in batch cultures with optical cell density (OD₆₆₀) up to 40. The l-lysine-producing strain showed substantially different metabolite profiles in the amino acid metabolism, including increased intracellular pool sizes in the l-lysine-, l-homoserine- and l-threonine pathways and decreased intracellular pool sizes for all other determined amino acids. By comparing data of in vitro inhibition of the engineered enzymes and determined intracellular concentrations of the inhibitors it was found that the inferred in vivo activities of these enzymes are still significantly below their in vitro maximums. This work demonstrates the usefulness of metabolic analysis for assessing the impact of engineered enzymes and identifying targets for further strain development.

Quantification of Microbial Phenotypes

Metabolite profiling technologies have improved to generate close to quantitative metabolomics data, which can be employed to quantitatively describe the metabolic phenotype of an organism. Here, we review the current technologies available for quantitative metabolomics, present their advantages and drawbacks, and the current challenges to generate fully quantitative metabolomics data. Metabolomics data can be integrated into metabolic networks using thermodynamic principles to constrain the directionality of reactions. Here we explain how to estimate Gibbs energy under physiological conditions, including examples of the estimations, and the different methods for thermodynamics-based network analysis. The fundamentals of the methods and how to perform the analyses are described. Finally, an example applying quantitative metabolomics to a yeast model by 13C fluxomics and thermodynamics-based network analysis is presented. The example shows that (1) these two methods are complementary to each other; and (2) there is a need to take into account Gibbs energy errors. Better estimations of metabolic phenotypes will be obtained when further constraints are included in the analysis.

Identifying model error in metabolic flux analysis - a generalized least squares approach

BACKGROUND

The estimation of intracellular flux through traditional metabolic flux analysis (MFA) using an overdetermined system of equations is a well established practice in metabolic engineering. Despite the continued evolution of the methodology since its introduction, there has been little focus on validation and identification of poor model fit outside of identifying "gross measurement error". The growing complexity of metabolic models, which are increasingly generated from genome-level data, has necessitated robust validation that can directly assess model fit.

RESULTS

In this work, MFA calculation is framed as a generalized least squares (GLS) problem, highlighting the applicability of the common t-test for model validation. To differentiate between measurement and model error, we simulate ideal flux profiles directly from the model, perturb them with estimated measurement error, and compare their validation to real data. Application of this strategy to an established Chinese Hamster Ovary (CHO) cell model shows how fluxes validated by traditional means may be largely non-significant due to a lack of model fit. With further simulation, we explore how t-test significance relates to calculation error and show that fluxes found to be non-significant have 2-4 fold larger error (if measurement uncertainty is in the 5-10 % range).

CONCLUSIONS

The proposed validation method goes beyond traditional detection of "gross measurement error" to identify lack of fit between model and data. Although the focus of this work is on t-test validation and traditional MFA, the presented framework is readily applicable to other regression analysis methods and MFA formulations.

Systems metabolic engineering of Corynebacterium glutamicum for the production of the carbon-5 platform chemicals 5-aminovalerate and glutarate

Background

The steadily growing world population and our ever luxurious life style, along with the simultaneously decreasing fossil resources has confronted modern society with the issue and need of finding renewable routes to accommodate for our demands. Shifting the production pipeline from raw oil to biomass requires efficient processes for numerous platform chemicals being produced with high yield, high titer and high productivity.

Results

In the present work, we established a de novo bio-based production process for the two carbon-5 platform chemicals 5-aminovalerate and glutarate on basis of the lysine-hyperproducing strain Corynebacterium glutamicum LYS-12. Upon heterologous implementation of the Pseudomonas putida genes davA, encoding 5-aminovaleramidase and davB, encoding lysine monooxygenase, 5-aminovalerate production was established. Related to the presence of endogenous genes coding for 5-aminovalerate transaminase (gabT) and glutarate semialdehyde dehydrogenase, 5-aminovalerate was partially converted to glutarate. Moreover, residual l-lysine was secreted as by-product. The issue of by-product formation was then addressed by deletion of the lysE gene, encoding the l-lysine exporter. Additionally, a putative gabT gene was deleted to enhance 5-aminovalerate production. To fully exploit the performance of the optimized strain, fed-batch fermentation was carried out producing 28 g L⁻¹ 5-aminovalerate with a maximal space–time yield of 0.9 g L⁻¹ h⁻¹.

Conclusions

The present study describes the construction of a recombinant microbial cell factory for the production of carbon-5 platform chemicals. Beyond a basic proof-of-concept, we were able to specifically increase the production flux of 5-aminovalerate thereby generating a strain with excellent production performance. Additional improvement can be expected by removal of remaining by-product formation and bottlenecks, associated to the terminal pathway, to generate a strain being applicable as centerpiece for a bio-based production of 5-aminovalerate.

Integrated analysis of gene expression and metabolic fluxes in PHA-producing Pseudomonas putida grown on glycerol

Background

Given its high surplus and low cost, glycerol has emerged as interesting carbon substrate for the synthesis of value-added chemicals. The soil bacterium Pseudomonas putida KT2440 can use glycerol to synthesize medium-chain-length poly(3-hydroxyalkanoates) (mcl-PHA), a class of biopolymers of industrial interest. Here, glycerol metabolism in P. putida KT2440 was studied on the level of gene expression (transcriptome) and metabolic fluxes (fluxome), using precisely adjusted chemostat cultures, growth kinetics and stoichiometry, to gain a systematic understanding of the underlying metabolic and regulatory network.

Results

Glycerol-grown P. putida KT2440 has a maintenance energy requirement [0.039 (mmol_glycerol (g_CDW h)⁻¹)] that is about sixteen times lower than that of other bacteria, such as Escherichia coli, which provides a great advantage to use this substrate commercially. The shift from carbon (glycerol) to nitrogen (ammonium) limitation drives the modulation of specific genes involved in glycerol metabolism, transport electron chain, sensors to assess the energy level of the cell, and PHA synthesis, as well as changes in flux distribution to increase the precursor availability for PHA synthesis (Entner–Doudoroff pathway and pyruvate metabolism) and to reduce respiration (glyoxylate shunt). Under PHA-producing conditions (N-limitation), a higher PHA yield was achieved at low dilution rate (29.7 wt% of CDW) as compared to a high rate (12.8 wt% of CDW). By-product formation (succinate, malate) was specifically modulated under these regimes. On top of experimental data, elementary flux mode analysis revealed the metabolic potential of P. putida KT2440 to synthesize PHA and identified metabolic engineering targets towards improved production performance on glycerol.

Conclusion

This study revealed the complex interplay of gene expression levels and metabolic fluxes under PHA- and non-PHA producing conditions using the attractive raw material glycerol as carbon substrate. This knowledge will form the basis for the development of future metabolically engineered hyper-PHA-producing strains derived from the versatile bacterium P. putida KT2440.

13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, ¹³C Metabolic Flux Analysis (¹³C-MFA) has been continuously developed and widely applied to rigorously investigate cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, many ¹³C-MFA studies have been performed in academic labs and biotechnology industries to pinpoint key issues related to microbe-based chemical production. Insightful information about the metabolic rewiring has been provided to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this review, we will introduce the basics of ¹³C-MFA and illustrate how ¹³C-MFA has been applied via integration with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production for various host microorganisms