利用微滴生物传感和选择系统增强乳酸乳球菌氨基酸的产生和分泌

IF 3.7 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Metabolic Engineering Communications Pub Date : 2020-12-01 DOI:10.1016/j.mec.2020.e00133
Jhonatan A. Hernandez-Valdes , Myrthe aan de Stegge , Jos Hermans , Johan Teunis , Rinke J. van Tatenhove-Pel , Bas Teusink , Herwig Bachmann , Oscar P. Kuipers
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引用次数: 17

摘要

氨基酸是制药和食品工业领域有吸引力的代谢物。一方面,大规模生产微生物细胞工厂的建设旨在满足氨基酸作为大宗生化原料的需求。另一方面,氨基酸促进了发酵食品风味的形成。关于后者,乳制品(如奶酪)中的风味形成与乳酸菌(LAB)的存在有关。乳酸乳球菌是最重要的乳酸菌之一,被用作发酵食品的发酵剂。某些乳酸菌的蛋白水解活性产生多肽和氨基酸,这些多肽和氨基酸是风味化合物或风味前体。然而,分离具有增强氨基酸生产和分泌活性的细菌细胞仍然是一个挑战。在这项工作中,我们开发了一种基于生长的传感器菌株,用于检测必需氨基酸异亮氨酸、亮氨酸、缬氨酸、组氨酸和蛋氨酸。氨基酸是一些细菌可以分泌的代谢物。因此,通过将生物传感器菌株与可能产生氨基酸的菌株共培养,我们的生物传感器使我们能够鉴定自然分泌氨基酸的野生型乳酸乳杆菌菌株。随后,我们将该生物传感器与基于液滴的筛选方法相结合,分离出3株氨基酸分泌量比野生型增加5-10倍的突变乳酸乳杆菌IPLA838菌株。基因组重测序揭示了编码参与肽摄取和肽降解的蛋白质的基因突变。我们认为,由于这些基因突变,氨基酸水平调节的不平衡可能会驱动这些氨基酸的积累和分泌。这种生物传感系统解决了分泌分子过量产生的选择问题,这需要将产物与液滴中的产生细胞偶联。
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Enhancement of amino acid production and secretion by Lactococcus lactis using a droplet-based biosensing and selection system

Amino acids are attractive metabolites for the pharmaceutical and food industry field. On one hand, the construction of microbial cell factories for large-scale production aims to satisfy the demand for amino acids as bulk biochemical. On the other hand, amino acids enhance flavor formation in fermented foods. Concerning the latter, flavor formation in dairy products, such as cheese is associated with the presence of lactic acid bacteria (LAB). In particular, Lactococcus lactis, one of the most important LAB, is used as a starter culture in fermented foods. The proteolytic activity of some L. lactis strains results in peptides and amino acids, which are flavor compounds or flavor precursors. However, it is still a challenge to isolate bacterial cells with enhanced amino acid production and secretion activity. In this work, we developed a growth-based sensor strain to detect the essential amino acids isoleucine, leucine, valine, histidine and methionine. Amino acids are metabolites that can be secreted by some bacteria. Therefore, our biosensor allowed us to identify wild-type L. lactis strains that naturally secrete amino acids, by using co-cultures of the biosensor strain with potential amino acid producing strains. Subsequently, we used this biosensor in combination with a droplet-based screening approach, and isolated three mutated L. lactis IPLA838 strains with 5–10 fold increased amino acid-secretion compared to the wild type. Genome re-sequencing revealed mutations in genes encoding proteins that participate in peptide uptake and peptide degradation. We argue that an unbalance in the regulation of amino acid levels as a result of these gene mutations may drive the accumulation and secretion of these amino acids. This biosensing system tackles the problem of selection for overproduction of secreted molecules, which requires the coupling of the product to the producing cell in the droplets.

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来源期刊
Metabolic Engineering Communications
Metabolic Engineering Communications Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
13.30
自引率
1.90%
发文量
22
审稿时长
18 weeks
期刊介绍: Metabolic Engineering Communications, a companion title to Metabolic Engineering (MBE), is devoted to publishing original research in the areas of metabolic engineering, synthetic biology, computational biology and systems biology for problems related to metabolism and the engineering of metabolism for the production of fuels, chemicals, and pharmaceuticals. The journal will carry articles on the design, construction, and analysis of biological systems ranging from pathway components to biological complexes and genomes (including genomic, analytical and bioinformatics methods) in suitable host cells to allow them to produce novel compounds of industrial and medical interest. Demonstrations of regulatory designs and synthetic circuits that alter the performance of biochemical pathways and cellular processes will also be presented. Metabolic Engineering Communications complements MBE by publishing articles that are either shorter than those published in the full journal, or which describe key elements of larger metabolic engineering efforts.
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