Development and application of a transcriptional sensor for detection of heterologous acrylic acid production in E. coli

Abstract

Background Acrylic acid (AA) is a widely used commodity chemical derived from non-renewable fossil fuel sources. Alternative microbial-based production methodologies are being developed with the aim of providing “green” acrylic acid. These initiatives will benefit from component sensing tools that facilitate rapid and easy detection of in vivo AA production. Results We developed a novel transcriptional sensor facilitating in vivo detection of acrylic acid (AA). RNAseq analysis of Escherichia coli exposed to sub-lethal doses of acrylic acid identified a selectively responsive promoter (P yhcN ) that was cloned upstream of the eGFP gene. In the presence of AA, eGFP expression in E. coli cells harbouring the sensing construct was readily observable by fluorescence read-out. Low concentrations of AA (500 μM) could be detected whilst the closely related lactic and 3-hydroxy propionic acids failed to activate the sensor. We further used the developed AA-biosensor for in vivo FACS-based screening and identification of amidase mutants with improved catalytic properties for deamination of acrylamide to acrylic acid. Conclusions The transcriptional AA sensor developed in this study will benefit strain, enzyme and pathway engineering initiatives targeting the efficient formation of bio-acrylic acid. Electronic supplementary material The online version of this article (10.1186/s12934-019-1185-y) contains supplementary material, which is available to authorized users.

Transcription Factor Engineering for High-Throughput Strain Evolution and Organic Acid Bioproduction: A Review

“…So far, TFs in prokaryotes can be grouped into a dozen families identified on the basis of sequence analysis, with the LacI, AraC, LysR, CRP, TetR, and OmpR families being characterized best (Browning and Busby, 2004). New TFs continue to be identified by experimental methods such as transcriptome analysis (Raghavan et al, 2019), onehybrid assays (Reece-Hoyes and Walhout, 2012), electrophoretic mobility shift assay (EMSA, Hellman and Fried, 2007), DNA affinity purification-mass spectrometry (AP-MS, Tacheny et al, 2013), and protein microarrays (Hu et al, 2009).…”

“…TFs can be used to detect small molecules, ion accumulation, and changes in physiological parameters. A wide variety of TF-based biosensors have been constructed and characterized that recognize different small molecules, including but not limited to glutarate (Thompson et al, 2019), 3-hydroxypropionic acid (Rogers and Church, 2016;Seok et al, 2018;Nguyen et al, 2019), itaconic acid (Hanko et al, 2018), flavonoids (Siedler et al, 2014a;Trabelsi et al, 2018), anhydrotetracycline (Lutz and Bujard, 1997), arabinose (Lee and Keasling, 2006), lactam (Zhang et al, 2016), mevalonate (Tang and Cirino, 2011), L-methionine (Mustafi et al, 2012), amino acids (Binder et al, 2012;Mustafi et al, 2012;Leavitt et al, 2016), acrylic acid (Raghavan et al, 2019), isoprene (Kim et al, 2018), shikimate , and aromatic compounds (Willardson et al, 1998;Kim et al, 2005;Jha et al, 2016). Some typical biosensors with sensing kinetics are listed in Table 1.…”

“…Large-scale production using microorganisms requires the development of HTS tools for strain engineering and techniques for analyzing strain performance and the efficiency of biological processes. Many TF-based biosensors for measuring the intracellular concentrations of organic acids are currently available (Sint Fiet et al, 2006;Uchiyama and Miyazaki, 2010;Dietrich et al, 2013;Tang et al, 2013;Raman et al, 2014;Chen et al, 2015;Zhou et al, 2015;Leavitt et al, 2017;Hanko et al, 2018;Nguyen et al, 2019;Raghavan et al, 2019;Thompson et al, 2019) that provide a HTS method when combined with FACS. Alternatively, TFs can activate or repress the expression of target genes, which can be used to rewire microbial metabolic pathways, thus leading to an increase in the production of organic acids ( Figure 2G).…”

“…As mentioned above, AA biosynthesis via enzymatic dehydration of 3-HP has been demonstrated in engineered E. coli (Chu et al, 2015;Liu and Liu, 2016). However, the yields are low, which led Raghavan et al (2019) to apply HTS to identify strains the exhibited greater activity of key enzymes in the AA synthesis pathway. By identifying E. coli genes that were selectively upregulated in the presence of AA, this group found that the gene yhcN encodes a protein that can respond specifically to AA at low concentrations when it was coupled to an eGFP reporter (Raghavan et al, 2019).…”

“…However, the yields are low, which led Raghavan et al (2019) to apply HTS to identify strains the exhibited greater activity of key enzymes in the AA synthesis pathway. By identifying E. coli genes that were selectively upregulated in the presence of AA, this group found that the gene yhcN encodes a protein that can respond specifically to AA at low concentrations when it was coupled to an eGFP reporter (Raghavan et al, 2019). This biosensor was used to find an amidase variant that converted acrylamide to AA with 1.6fold improvement in catalytic efficiency, which is important to enhance AA production.…”