13C-Fingerprinting and Metabolic Flux Analysis of Bacterial Metabolisms

Tuning a high performing multiplexed-CRISPRi Pseudomonas putida strain to further enhance indigoidine production

In this study, a 14-gene edited Pseudomonas putida KT2440 strain for heterologous indigoidine production was examined using three distinct omic datasets. Transcriptomic data indicated that CRISPR/dCpf1-interference (CRISPRi) mediated multiplex repression caused global gene expression changes, implying potential undesirable changes in metabolic flux. ¹³C-metabolic flux analysis (¹³C-MFA) revealed that the core P. putida flux network after CRISPRi repression was conserved, with moderate reduction of TCA cycle and pyruvate shunt activity along with glyoxylate shunt activation during glucose catabolism. Metabolomic results identified a change in intracellular TCA metabolites and extracellular metabolite secretion profiles (sugars and succinate overflow) in the engineered strains. These omic analyses guided further strain engineering, with a random mutagenesis screen first identifying an optimal ribosome binding site (RBS) for Cpf1 that enabled stronger product-substrate pairing (1.6-fold increase). Then, deletion strains were constructed with excision of the PHA operon (ΔphaAZC-IID) resulting in a 2.2-fold increase in indigoidine titer over the optimized Cpf1-RBS construct at the end of the growth phase (∼6 h). The maximum indigoidine titer (at 72 h) in the ΔphaAZC-IID strain had a 1.5-fold and 1.8-fold increase compared to the optimized Cpf1-RBS construct and the original strain, respectively. Overall, this study demonstrated that integration of omic data types is essential for understanding responses to complex metabolic engineering designs and directly quantified the effect of such modifications on central metabolism.

13C metabolic flux analysis: Classification and characterization from the perspective of mathematical modeling and application in physiological research of neural cell

¹³C metabolic flux analysis (¹³C-MFA) has emerged as a forceful tool for quantifying in vivo metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of ¹³C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of ¹³C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.

Quantifying Methane and Methanol Metabolism of "Methylotuvimicrobium buryatense" 5GB1C under Substrate Limitation

Methanotrophic metabolism has been under investigation for decades using biochemical and genetic approaches. Recently, a further step has been taken toward understanding methanotrophic metabolism in a quantitative manner by means of flux balance analysis (FBA), a mathematical approach that predicts fluxes constrained by mass balance and a few experimental measurements. However, no study has previously been undertaken to experimentally quantitate the complete methanotrophic central metabolism. The significance of this study is to fill such a gap by performing ¹³C INST-MFA on a fast-growing methanotroph. Our quantitative insights into the methanotrophic carbon and energy metabolism will pave the way for future FBA studies and set the stage for rational design of methanotrophic strains for industrial applications. Further, the experimental strategies can be applied to other methane or methanol utilizers, and the results will offer a unique and quantitative perspective of diverse methylotrophic metabolism.

Methanotrophic bacteria are a group of prokaryotes capable of using methane as their sole carbon and energy source. Although efforts have been made to simulate and elucidate their metabolism via computational approaches or ¹³C tracer analysis, major gaps still exist in our understanding of methanotrophic metabolism at the systems level. Particularly, direct measurements of system-wide fluxes are required to understand metabolic network function. Here, we quantified the central metabolic fluxes of a type I methanotroph, “Methylotuvimicrobium buryatense” 5GB1C, formerly Methylomicrobium buryatense 5GB1C, via ¹³C isotopically nonstationary metabolic flux analysis (INST-MFA). We performed labeling experiments on chemostat cultures by switching substrates from ¹²C to ¹³C input. Following the switch, we measured dynamic changes of labeling patterns and intracellular pool sizes of several intermediates, which were later used for data fitting and flux calculations. Through computational optimizations, we quantified methane and methanol metabolism at two growth rates (0.1 h⁻¹ and 0.05 h⁻¹). The resulting flux maps reveal a core consensus central metabolic flux phenotype across different growth conditions: a strong ribulose monophosphate cycle, a preference for the Embden-Meyerhof-Parnas pathway as the primary glycolytic pathway, and a tricarboxylic acid cycle showing small yet significant fluxes. This central metabolic consistency is further supported by a good linear correlation between fluxes at the two growth rates. Specific differences between methane and methanol growth observed previously are maintained under substrate limitation, albeit with smaller changes. The substrate oxidation and glycolysis pathways together contribute over 80% of total energy production, while other pathways play less important roles.

IMPORTANCE Methanotrophic metabolism has been under investigation for decades using biochemical and genetic approaches. Recently, a further step has been taken toward understanding methanotrophic metabolism in a quantitative manner by means of flux balance analysis (FBA), a mathematical approach that predicts fluxes constrained by mass balance and a few experimental measurements. However, no study has previously been undertaken to experimentally quantitate the complete methanotrophic central metabolism. The significance of this study is to fill such a gap by performing ¹³C INST-MFA on a fast-growing methanotroph. Our quantitative insights into the methanotrophic carbon and energy metabolism will pave the way for future FBA studies and set the stage for rational design of methanotrophic strains for industrial applications. Further, the experimental strategies can be applied to other methane or methanol utilizers, and the results will offer a unique and quantitative perspective of diverse methylotrophic metabolism.