Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies

2021 ◽  
Vol 118 (49) ◽  
pp. e2109633118
Author(s):  
Berkley M. Ellis ◽  
Piyoosh K. Babele ◽  
Jody C. May ◽  
Carl H. Johnson ◽  
Brian F. Pfleger ◽  
...  

Reading and writing DNA were once the rate-limiting step in synthetic biology workflows. This has been replaced by the search for the optimal target sequences to produce systems with desired properties. Directed evolution and screening mutant libraries are proven technologies for isolating strains with enhanced performance whenever specialized assays are available for rapidly detecting a phenotype of interest. Armed with technologies such as CRISPR-Cas9, these experiments are capable of generating libraries of up to 1010 genetic variants. At a rate of 102 samples per day, standard analytical methods for assessing metabolic phenotypes represent a major bottleneck to modern synthetic biology workflows. To address this issue, we have developed a desorption electrospray ionization–imaging mass spectrometry screening assay that directly samples microorganisms. This technology increases the throughput of metabolic measurements by reducing sample preparation and analyzing organisms in a multiplexed fashion. To further accelerate synthetic biology workflows, we utilized untargeted acquisitions and unsupervised analytics to assess multiple targets for future engineering strategies within a single acquisition. We demonstrate the utility of the developed method using Escherichia coli strains engineered to overproduce free fatty acids. We determined discrete metabolic phenotypes associated with each strain, which include the primary fatty acid product, secondary products, and additional metabolites outside the engineered product pathway. Furthermore, we measured changes in amino acid levels and membrane lipid composition, which affect cell viability. In sum, we present an analytical method to accelerate synthetic biology workflows through rapid, untargeted, and multiplexed metabolomic analyses.

2021 ◽  
Author(s):  
Berkley M Ellis ◽  
Piyoosh Babele ◽  
Jody C May ◽  
Brian F Pfleger ◽  
Jamey D Young ◽  
...  

Progress in the fields of genomic and biologic sciences has yielded microbial bioprocesses for the advanced production of chemicals. While biomanufacturing has the potential to address global demands for renewable fuels and chemicals, engineering microbial cell factories that can compete with synthetic chemical processes remains a challenge. Optimizing strains for enhanced chemical production is no longer limited by reading and writing DNA, rather it is impeded by the lack of high-throughput platforms for characterizing the metabolic phenotypes resulting from specific gene editing events. To address this issue, we have developed a desorption electrospray ionization- imaging mass spectrometry (DESI-IMS) screening assay that is conducive to both multiplexed sampling and untargeted analyses. This technology bridges the gap between genomic and metabolomic timescales by simultaneously characterizing the chemical output of various engineered Escherichia coli strains rapidly and directly under ambient conditions. The developed method was used to phenotype four E. coli strains on the basis of measured metabolomes, which were validated via PCR genotyping. Untargeted DESI-IMS phenotyping suggests multiple strategies for future engineering which include: (i) relative amounts of specific biosynthetic products, (ii) identification of secondary products, and (iii) the metabolome of engineered organisms. In sum, we present a workflow to accelerate strain engineering by providing rapid, untargeted, and multiplexed analyses of microbial metabolic phenotypes.


2010 ◽  
Vol 122 (34) ◽  
pp. 6089-6092 ◽  
Author(s):  
Livia S. Eberlin ◽  
Allison L. Dill ◽  
Alexandra J. Golby ◽  
Keith L. Ligon ◽  
Justin M. Wiseman ◽  
...  

2013 ◽  
Vol 85 (3) ◽  
pp. 1276-1279 ◽  
Author(s):  
Rachel V. Bennett ◽  
H. James Cleaves ◽  
Jeffrey M. Davis ◽  
Denis A. Sokolov ◽  
Thomas M. Orlando ◽  
...  

2013 ◽  
Vol 85 (21) ◽  
pp. 10385-10391 ◽  
Author(s):  
Jeramie Watrous ◽  
Patrick Roach ◽  
Brandi Heath ◽  
Theodore Alexandrov ◽  
Julia Laskin ◽  
...  

Planta Medica ◽  
2018 ◽  
Vol 84 (09/10) ◽  
pp. 584-593 ◽  
Author(s):  
Delphine Parrot ◽  
Stefano Papazian ◽  
Daniel Foil ◽  
Deniz Tasdemir

AbstractImaging mass spectrometry (IMS) has recently established itself in the field of “spatial metabolomics.” Merging the sensitivity and fast screening of high-throughput mass spectrometry with spatial and temporal chemical information, IMS visualizes the production, location, and distribution of metabolites in intact biological models. Since metabolite profiling and morphological features are combined in single images, IMS offers an unmatched chemical detail on complex biological and microbiological systems. Thus, IMS-type “spatial metabolomics” emerges as a powerful and complementary approach to genomics, transcriptomics, and classical metabolomics studies. In this review, we summarize the current state-of-the-art IMS methods with a strong focus on desorption electrospray ionization (DESI)-IMS. DESI-IMS utilizes the original principle of electrospray ionization, but in this case solvent droplets are rastered and desorbed directly on the sample surface. The rapid and minimally destructive DESI-IMS chemical screening is achieved at ambient conditions and enables the accurate view of molecules in tissues at the µm-scale resolution. DESI-IMS analysis does not require complex sample preparation and allows repeated measurements on samples from different biological sources, including microorganisms, plants, and animals. Thanks to its easy workflow and versatility, DESI-IMS has successfully been applied to many different research fields, such as clinical analysis, cancer research, environmental sciences, microbiology, chemical ecology, and drug discovery. Herein we discuss the present applications of DESI-IMS in natural product research.


2010 ◽  
Vol 49 (34) ◽  
pp. 5953-5956 ◽  
Author(s):  
Livia S. Eberlin ◽  
Allison L. Dill ◽  
Alexandra J. Golby ◽  
Keith L. Ligon ◽  
Justin M. Wiseman ◽  
...  

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