Overexpression of thermostable meso-diaminopimelate dehydrogenase to redirect diaminopimelate pathway for increasing L-lysine production in Escherichia coli

Microbial production of sulfur-containing amino acids using metabolically engineered Escherichia coli

L-Cysteine and L-methionine, as the only two sulfur-containing amino acids among the canonical 20 amino acids, possess distinct characteristics and find wide-ranging industrial applications. The use of different organisms for fermentative production of L-cysteine and L-methionine is gaining increasing attention, with Escherichia coli being extensively studied as the preferred strain. This preference is due to its ability to grow rapidly in cost-effective media, its robustness for industrial processes, the well-characterized metabolism, and the availability of molecular tools for genetic engineering. This review focuses on the genetic and molecular mechanisms involved in the production of these sulfur-containing amino acids in E. coli. Additionally, we systematically summarize the metabolic engineering strategies employed to enhance their production, including the identification of new targets, modulation of metabolic fluxes, modification of transport systems, dynamic regulation strategies, and optimization of fermentation conditions. The strategies and design principles discussed in this review hold the potential to facilitate the development of strain and process engineering for direct fermentation of sulfur-containing amino acids.

A Computational Framework to Identify Metabolic Engineering Strategies for the Co-Production of Metabolites

Microbial production of chemicals is a more sustainable alternative to traditional chemical processes. However, the shift to bioprocess is usually accompanied by a drop in economic feasibility. Co-production of more than one chemical can improve the economy of bioprocesses, enhance carbon utilization and also ensure better exploitation of resources. While a number of tools exist for in silico metabolic engineering, there is a dearth of computational tools that can co-optimize the production of multiple metabolites. In this work, we propose co-FSEOF (co-production using Flux Scanning based on Enforced Objective Flux), an algorithm designed to identify intervention strategies to co-optimize the production of a set of metabolites. Co-FSEOF can be used to identify all pairs of products that can be co-optimized with ease using a single intervention. Beyond this, it can also identify higher-order intervention strategies for a given set of metabolites. We have employed this tool on the genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae, and identified intervention targets that can co-optimize the production of pairs of metabolites under both aerobic and anaerobic conditions. Anaerobic conditions were found to support the co-production of a higher number of metabolites when compared to aerobic conditions in both organisms. The proposed computational framework will enhance the ease of study of metabolite co-production and thereby aid the design of better bioprocesses.

Feedback regulation and coordination of the main metabolism for bacterial growth and metabolic engineering for amino acid fermentation

Living organisms such as bacteria are often exposed to continuous changes in the nutrient availability in nature. Therefore, bacteria must constantly monitor the environmental condition, and adjust the metabolism quickly adapting to the change in the growth condition. For this, bacteria must orchestrate (coordinate and integrate) the complex and dynamically changing information on the environmental condition. In particular, the central carbon metabolism (CCM), monomer synthesis, and macromolecular synthesis must be coordinately regulated for the efficient growth. It is a grand challenge in bioscience, biotechnology, and synthetic biology to understand how living organisms coordinate the metabolic regulation systems. Here, we consider the integrated sensing of carbon sources by the phosphotransferase system (PTS), and the feed-forward/feedback regulation systems incorporated in the CCM in relation to the pool sizes of flux-sensing metabolites and αketoacids. We also consider the metabolic regulation of amino acid biosynthesis (as well as purine and pyrimidine biosyntheses) paying attention to the feedback control systems consisting of (fast) enzyme level regulation with (slow) transcriptional regulation. The metabolic engineering for the efficient amino acid production by bacteria such as Escherichia coli and Corynebacterium glutamicum is also discussed (in relation to the regulation mechanisms). The amino acid synthesis is important for determining the rate of ribosome biosynthesis. Thus, the growth rate control (growth law) is further discussed on the relationship between (p)ppGpp level and the ribosomal protein synthesis.

Description of Anaerostipes faecalis sp. nov., a new segmented filamentous bacterium isolated from swine faeces

A novel, strictly anaerobic, gram-negative, segmented filamentous bacterium strain AGMB03513^T, was isolated from the faeces of a 5-month-old pig. Phylogenetic analysis based on the 16S rRNA gene indicated that the isolate was a member of the family Lachnospiraceae, and the closest strain was Anaerostipes butyraticus. Strain AGMB03513^T formed a lineage within the genus Anaerostipes and was closely related to A. butyraticus DSM 22094 ^T (= KCTC 15125 ^T, 95.8%), Anaerostipes hadrus DSM 3319 ^T (= KCTC 15606 ^T, 95.5%), Anaerostipes caccae DSM 14662 ^T (= KCTC 15019 ^T, 94.0%), and Anaerostipes rhamnosivorans DSM 26241 ^T (= KCTC 15316 ^T, 93.4%). Strain AGMB03513^T grew at temperatures between 30 and 45 °C, within a pH range of 7.0-9.0, and in medium containing up to 1.5% NaCl. Cells were found to utilise D-glucose, D-mannitol, D-lactose, D-saccharose, D-maltose, D-xylose, L-arabinose, D-mannose, and D-sorbitol, and acetate was identified as the major end product of metabolism. The major components of the cellular fatty acids were C_12:0, C_16:0, and C_18:0. In addition, the bacterium contained meso-diaminopimelic acid in the cell wall. According to the comparative analysis of the whole genome sequence, the DNA G + C content of strain AGMB03513 was 37.0 mol%. In addition, Average nucleotide identity (ANI), average amino acid identity (AAI), and digital DNA-DNA hybridisation (dDDH) values were obtained in comparisons of strain AGMB03513^T with reference strains of species in the genus Anaerostipes. ANI values were found to be between 71.0 and 75.7%, AAI values between 66.6 and 73.2%, and dDDH values between 19.5 and 21.4%. All the data were below the threshold range for species determination. Based on phenotypic, phylogenetic, biochemical, chemotaxonomic, and genomic characteristics, we considered it reasonable to assign a novel species status to strain AGMB03513^T, for which we propose the name Anaerostipes faecalis sp. nov. The type strain is AGMB03513^T (= KCTC 25020 ^T = NBRC 114896 ^T).

Metabolizable Near-Infrared-II Nanoprobes for Dynamic Imaging of Deep-Seated Tumor-Associated Macrophages in Pancreatic Cancer

Tumor-associated macrophages (TAMs) play a crucial part in cancer evolution. Dynamic imaging of TAMs is of great significance for treatment outcome evaluation and precision tumor therapy. Currently, most fluorescence nanoprobes tend to accumulate in the liver and are difficult to metabolize, which leads to strong background signals and inadequate imaging quality of TAMs nearby the liver such as pancreatic cancer. Herein, we aim to develop metabolizable dextran-indocyanine green (DN-ICG) nanoprobes in the second near-infrared window (NIR-II, 1 000-1 700 nm) for dynamic imaging of TAMs in pancreatic cancer. Compared to free ICG, the NIR-II fluorescence intensity of DN-ICG nanoprobes increased by 279% with significantly improved stability. We demonstrated that DN-ICG nanoprobes could specifically target TAMs through the interaction of dextran with specific ICAM-3-grabbing nonintegrin related 1 (SIGN-R1), which were highly expressed in TAMs. Subsequently, DN-ICG nanoprobes gradually metabolized in the liver yet remained in pancreatic tumor stroma in mouse models, achieving a high signal-to-background ratio (SBR = 7) in deep tissue (∼0.5 cm) NIR-II imaging of TAMs. Moreover, DN-ICG nanoprobes could detect dynamic changes of TAMs induced by low-dose radiotherapy and zoledronic acid. Therefore, the highly biocompatible and biodegradable DN-ICG nanoprobes harbor great potential for precision therapy in pancreatic cancer.

Identification and functional characterization of NAD(P)+ -dependent meso-diaminopimelate dehydrogenase from Numidum massiliense

meso‐Diaminopimelate dehydrogenase (meso‐DAPDH) catalyzes the reversible NADP⁺‐dependent oxidative deamination of meso‐2,6‐diaminopimelate (meso‐DAP) to produce l‐2‐amino‐6‐oxopimelate. Moreover, d‐amino acid dehydrogenase (d‐AADHs) derived from protein‐engineered meso‐DAPDH is useful for one‐step synthesis of d‐amino acids with high optical purity. Here, we report the identification and functional characterization of a novel NAD(P)⁺‐dependent meso‐DAPDH from Numidum massiliense (NmDAPDH). After the gene encoding the putative NmDAPDH was expressed in recombinant Escherichia coli cells, the enzyme was purified 4.0‐fold to homogeneity from the crude extract through five purification steps. Although the previously known meso‐DAPDHs use only NADP⁺ as a coenzyme, NmDAPDH was able to use both NADP⁺ and NAD⁺ as coenzymes. When NADP⁺ was used as a coenzyme, NmDAPDH exhibited an approximately 2 times higher k_cat/K_m value toward meso‐DAP than that of meso‐DAPDH from Symbiobacterium thermophilum (StDAPDH). NmDAPDH also catalyzed the reductive amination of corresponding 2‐oxo acids to produce acidic d‐amino acids such as d‐aspartate and d‐glutamate. The optimum pH and temperature for the oxidative deamination of meso‐DAP were about 10.5 and 75°C, respectively. Like StDAPDH, NmDAPDH exhibited high stability: it retained more than 75% of its activity after 30 min at 60°C (pH 7.2) or at pHs ranging from 5.5 to 13.0 (50°C). Alignment of the amino acid sequences of NmDAPDH and the known meso‐DAPDHs suggested NmDAPDH has a hexameric structure. Given its specificity for both NADP⁺ and NAD⁺, high stability, and a broad range of reductive amination activity toward 2‐oxo acids, NmDAPDH appears to offer advantages for engineering a more effective d‐AADH.