Trace impurities in sodium phosphate influences the physiological activity of Escherichia coli in M9 minimal medium.

In the field of applied microbiology, reproducibility and experimental variability are important factors that influence both basic research as well as process development for industrial applications. Experimental reproducibility and accuracy depend not only on culture conditions such as temperature and aeration but also on raw materials and procedures used for media preparation. The M9 minimal medium is one of the most common synthetic media for culturing Escherichia coli and other bacteria. This synthetic medium can be used to observe and evaluate the physiological activity of microbes under minimal nutritional requirements and determine the limiting factor for the desired phenotype. Although one of the advantages using the M9 medium is that its composition can be modulated, it is difficult to control presence of trace components and impurities from the reagents for preparing this medium. Herein, we showed that trace ingredients present in the reagents used for M9 media preparation affect the bacterial physiological activities (e.g., cell growth, substrate consumption, and byproduct formation). Additionally, we systematically identified the trace ingredient that influenced phenotypic differences. Our results showed that the selection of reagents and accuracy during reagent preparation is important for experimental reproducibility in the field of bio-engineering and systems biology focused on the systematic and continuous development of biomolecular systems (e.g., biorefinery, metabolic engineering, and synthetic biology).

Modulation of host glutamine anabolism enhances the sensitivity of small cell lung cancer to chemotherapy.

Small cell lung cancer (SCLC) is one of the deadliest human cancers, with a 5-year survival rate of ∼7%. Here, we performed a targeted proteomics analysis of human SCLC samples and thereby identified hypoxanthine phosphoribosyltransferase 1 (HPRT1) in the salvage purine synthesis pathway as a factor that contributes to SCLC malignancy by promoting cell survival in a glutamine-starved environment. Inhibition of HPRT1 by 6-mercaptopurine (6-MP) in combination with methotrexate (MTX), which blocks the de novo purine synthesis pathway, attenuated the growth of SCLC in mouse xenograft models. Moreover, modulation of host glutamine anabolism with the glutamine synthetase inhibitor methionine sulfoximine (MSO) in combination with 6-MP and MTX treatment resulted in marked tumor suppression and prolongation of host survival. Our results thus suggest that modulation of host glutamine anabolism combined with simultaneous inhibition of the de novo and salvage purine synthesis pathways may be of therapeutic benefit for SCLC.

In-Needle Pre-Column Derivatization for Amino Acid Quantification (iPDAQ) Using HPLC.

Pre-column fluorescent derivatization has been used for the fast quantification of amino acids using high-performance liquid chromatography (HPLC) systems. However, it generally requires an offline in-vial derivatization process with multiple derivatization reagents. The offline derivatization requires the same number of reaction vials as the number of sample vials for use as a reaction chamber for the derivatization reaction in an autosampler. Therefore, the number of samples analyzed per batch using the pre-column derivatization method is halved. To benefit from the pre-column derivatization method, we transformed the derivatization process from an offline chamber process to an online in-needle process (in-needle Pre-column Derivatization for Amino acids Quantification; iPDAQ). Fluorescent derivatization in the injection needle obviated the need for vacant vials as reaction chambers. Consequently, the throughput per batch improved up to two times, and the consumption of derivatization reagents was reduced to less than one-tenth of that in the conventional vial method. We demonstrated to separate and quantify the amino acids in various biological samples. Herein, we presented a novel HPLC-based amino acid quantification method that enables the continuous analysis of a large number of samples. The iPDAQ facilitates accurate amino acid quantification due to the automation of derivatization and achieves improvement in the throughput and reduction of analysis labor.