6-Hydroxynicotinic acid (6-HNA) serves as a valuable pharmaceutical intermediate and chemical precursor. Its significance extends to the production of nitrogen-containing heterocyclic compounds crucial in chemical pesticides. Specifically, it plays a vital role in synthesizing pyridylmethyl amine insecticides like imidacloprid, known for its high efficiency, broad application range, and low toxicity [1–3]. In the field of medicine development, utilizing 6-HNA as the reaction substrate enables the creation of 5,6-dichloronicotinic acid, which facilitates lipase breakdown. The lipid-lowering capabilities of 6-HNA make it valuable in the formulation of weight loss medications [4]. Additionally, in molecular microbiology, 6-HNA can function as a regulator by binding to transcriptional regulators associated with nicotinic acid metabolism, thereby exerting control over the breakdown of nicotinic acid [5]. In the realm of electrochemistry advancement, 6-HNA can be utilized to create modified electrodes, significantly influencing electrical conductivity [6]. Extensive research underscores the critical biochemical significance of 6-HNA. Biosynthesis stands as the primary method for producing 6-HNA, involving the processing of nicotinic acid with nicotinic acid dehydrogenase. The investigation of nicotinate dehydrogenase relies on the separation and purification of this enzyme from strains involved in nicotinic acid metabolism. The endeavor to strain screening for nicotinic acid dehydrogenase commenced in the 1950s, and the recent outcomes of strain selections are documented in Table 1. However, the process of strain screening that produce nicotinic acid dehydrogenase remains laborious, constraining its widespread industrial applicability. Therefore, it is imperative to establish a sifting process that is quicker, more accurate, and more practical, with the aim of enhancing effectiveness of the filter.
Most reported biosynthesis methods for 6-hydroxynicotinic acid involve the catalysis of nicotinic acid by nicotinic acid dehydrogenase produced by Pseudomonas strains [7]. The production of 6-HNA is directly influenced by the activity of nicotinic dehydrogenase [8]. In previous studies, selection of strains producing nicotinic acid dehydrogenase were typically first fermented and cultured in a 96-well plate. The culture solution obtained was then dropped onto filter paper, after drying the filter paper, observe its development under ultraviolet irradiation. Subsequently, the selected developing strains were fermented in a 24 well plate to determine enzyme activity [9]. Although this approach allows for screening thousands of wild strains daily, it is affected by low screening accuracy, intricate sample processing, and expensive labor. Therefore, there is a need for a quick, easy, and effective approach to strain selections.
6-HNA is an aromatic hydrocarbon derivative containing multiple chromophores, capable of absorbing light radiation. Therefore, utilizing a spectrophotometer to quantify the ability of bacterial strains to produce products has become a promising method for screening bacterial strains. In recent years, optical detection technology has found widespread use in the identification and characterization of microorganisms [10]. Optical sensors inducing colony light diffraction have been applied for the development, identification, and characterization of bacteria. These studys present a novel approach to summarizing the properties of bacterial colonies swiftly, precisely, and quantitatively. The commonality of these studies is that the colonies obtain reflectance spectra from their optical sensing devices by selecting light sources for absorption [11]. Strain parameters can be deduced from variations in light intensity, which are transformable into digital data. However, the pivotal question in employing changes in colony light intensity for strain selections is how to accurately quantify the intricate relationship between radiation levels of bacterial strains and their biological activity. Therefore, establishing a relatively accurate quantitative model is fundamental to this new method.
Several strain selections platforms have been developed for various modeling needs [12–15]. However, fluorescence spectrometers have not been utilized for selection of strains. With the capability to investigate the photoluminescence, chemiluminescence, and bioluminescence of various materials, the fluorescence spectrometer can swiftly and accurately measure the fluorescence of bacterial colonies. It is noteworthy that no research has combined the fluorescence spectrometer and fluorescence intensity of bacterial colonies for strain screening.
In this study, bacteria producing nicotinic acid dehydrogenase were utilized as an example to investigate the fluorescence spectrometer based on the spectral principle in the strain screening process. Nicotinic dehydrogenase, identified as an oxidoreductase, specifically catalyzes the 6-hydroxylation of the pyridine ring of nicotinic acid, resulting in the production of 6-hydroxynicotinic acid [16]. The objective was to establish an efficient selection of strains platform by integrating the detection of colony fluorescence intensity and strain biological activity using a fluorescence spectrometer, a strain with high enzyme activity that has not been reported was screened by this method. In addition, research has been conducted on the catalytic process conditions for utilizing novel bacterial strains to produce 6-HNA.Consequently, this methodology provides valuable insights into the development of strain screening and improvement.
Table 1
Reported nicotinic dehydrogenase-producing strains
Source | Time | Optimum temperature (℃) | Optimum pH | Enzyme activity(U/mL) | Reference |
Pseudomonas fluorescens KB1 | 1959 | 25 | 7.2 | -- | [17] |
Pseudomonas fluorescens TN5 | 1994 | 28 | 7.0 | -- | [18] |
Comamonas testosteroni JA1 | 2005 | 30 | 7.0 | 0.42 | [19] |
Pseudomonas putida NA-1 | 2006 | 30 | 7.0 | 0.58 | [20] |
Pseudomonas putida BK-1 | 2007 | 30 | 7.0 | 0.57 | [21] |
Pseudomonas putida KT2440 | 2009 | 30 | 7.0 | 0.34 | [22] |
Pseudomonas putida H9 | 2017 | 25 | 7.0 | 0.37 | [23] |
Pseudomonas putida S14 | 2021 | 30 | 7.0 | 1.11 | [7] |