Jia Zhang, Xi Liu, Zhihang Chen, X. Edward Zhou, Mingying Li, Zengyan Sun, Tao Xu, Taoran Zheng, Xiaomeng Wang, Xinnan Cui, Jiajun Du, Gongchao Jing, Yanmei Zhang, Mingqin Xu, Bo Ma, Fuli Li, Huiying Luo, Bin Yao, Guo-Qiang Chen, Jian Xu
Rapid yet high-information-content monitoring of cellular metabolism during fermentation is highly desirable for process optimization. While single-cell Raman spectroscopy can rapidly distinguish intracellular biopolymer classes, finer-resolution discrimination of monomeric units remains challenging. In this study, we demonstrated that the ramanome can classify polyhydroxyalkanoate (PHA)-producing Halomonas bluephagenesis cells that synthesize either polyhydroxybutyrate or poly(3-hydroxybutyrate-co-4-hydroxybutyrate) with 99.75% accuracy and simultaneously quantify total intracellular PHA and its constituent monomeric units (3-hydroxybutyrate and 4-hydroxybutyrate) at the single-cell level (median absolute deviation <3.8%). Such information enabled timely, data-driven selection of the optimal harvest time and revealed precursor competition between nucleic acid and PHA biosynthesis. Moreover, when monitoring PHA production in an industrial-scale 5000 l-fermenter, our method achieved a 12-min turnaround time, representing a more than100-fold acceleration over gas chromatography. Furthermore, tests on protein production by Saccharomyces cerevisiae and on lipid synthesis in Rhodococcus opacus supported its versatility. Thus, ramanomics is a valuable approach for process control and strain evaluation in biomanufacturing.