Coupling MALDI-TOF mass spectrometry protein and specialized metabolite analyses to rapidly discriminate bacterial function

LC-MS/MS-based metabolic profiling of Escherichia coli under heterologous gene expression stress

Escherichia coli is frequently exploited for genetic manipulations and heterologous gene expression studies. We have evaluated the metabolic profile of E. coli strain BL21 (DE3) RIL CodonPlus after genetic modifications and subjecting to the production of recombinant protein. Three genetically variable E. coli cell types were studied, normal cells (susceptible to antibiotics) cultured in simple LB medium, cells harboring ampicillin-resistant plasmid pET21a (+), grown under antibiotic stress, and cells having recombinant plasmid pET21a (+) ligated with bacterial lactate dehydrogenase gene grown under ampicillin and standard isopropyl thiogalactoside (IPTG)-induced gene expression conditions. A total of 592 metabolites were identified through liquid chromatography-mass spectrometry/mass spectrometry analysis, feature and peak detection using XCMS and CAMERA followed by precursor identification by METLIN-based procedures. Overall, 107 metabolites were found differentially regulated among genetically modified cells. Quantitative analysis has shown a significant modulation in DHNA-CoA, p-aminobenzoic acid, and citrulline levels, indicating an alteration in vitamin K, folic acid biosynthesis, and urea cycle of E. coli cells during heterologous gene expression. Modulations in energy metabolites including NADH, AMP, ADP, ATP, carbohydrate, terpenoids, fatty acid metabolites, diadenosine tetraphosphate (Ap4A), and l-carnitine advocate major metabolic rearrangements. Our study provides a broader insight into the metabolic adaptations of bacterial cells during gene manipulation experiments that can be prolonged to improve the yield of heterologous gene products and concomitant production of valuable biomolecules.

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

In order to visualize the relationship between bacterial phylogeny and specialized metabolite production of bacterial colonies growing on nutrient agar, we developed IDBac-a low-cost and high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) bioinformatics pipeline. IDBac software is designed for non-experts, is freely available, and capable of analyzing a few to thousands of bacterial colonies. Here, we present procedures for the preparation of bacterial colonies for MALDI-TOF MS analysis, MS instrument operation, and data processing and visualization in IDBac. In particular, we instruct users how to cluster bacteria into dendrograms based on protein MS fingerprints and interactively create Metabolite Association Networks (MANs) from specialized metabolite data.

Rapid dereplication of microbial isolates using matrix-assisted laser desorption ionization time-of-flight mass spectrometry: A mini-review

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MALDI-TOF MS is applicable as high-resolution and high-throughput tool.

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The classification and characterization of cultivable microorganisms is targeted.

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Advantageous are its simple sample preparation and short measurement time.

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It accelerates the dereplication of isolates from large-scale screening campaigns.

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Applications for studying microbial diversity and future trends are discussed.

Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) has become one of the most popular methods for the rapid, cost-effective and accurate classification and characterization of cultivable microorganisms. Due to its simple sample preparation and short measurement time, MALDI-TOF MS is an excellent choice for the high-throughput study of microbial isolates from rhizospheres or plants grown under diverse environmental conditions. While clinical isolates have a higher identification rate than environmental isolates due to the focus of commercial mass spectral libraries on the former, no identification is necessary in the dereplication step of large environmental studies. The grouping of large sets of isolates according to their intact protein profiles can be performed without knowledge of their taxonomy. Thus, this method is easily applicable to environmental samples containing microorganisms from yet undescribed phylogenetic origins. The main strategies applied to achieve effective dereplication are, first, expanding existing mass spectral libraries and, second, using an additional statistical analysis step to group measured mass spectra and identify unique isolates. In this review, these aspects are addressed. It closes with a prospective view on how MALDI-TOF MS-based microbial characterisation can accelerate the exploitation of plant-associated microbiota.

Whole Cell MALDI Fingerprinting Is a Robust Tool for Differential Profiling of Two-Component Mammalian Cell Mixtures

MALDI fingerprinting was first described two decades ago as a technique to identify microbial cell lines. Microbial fingerprinting has since evolved into an automated platform for microorganism identification and classification, which is now routinely used in clinical and environmental sectors. The extension of fingerprinting to mammalian cells has yet to progress partly due to compartmentalization of eukaryotic cells and overall higher cellular complexity. A number of publications on mammalian whole cell fingerprinting suggest that the method could be useful for classification of different cell types, cell states, and monitoring cell differentiation. We report the optimization of MALDI fingerprinting workflow parameters for mammalian cells and its application for differential profiling of mammalian cell lines and two-component cell line mixtures. Murine fallopian tube cells and high-grade ovarian carcinoma cell lines and their mixtures are used as model mammalian cell lines. Two-component cell mixtures serve to determine the method's feasibility for complex biological samples as the ability to detect cancer cells in a mixed cell population. The level of detection of cancer cells in the two-component mixture by principle component analysis (PCA) starts to deteriorate at 5% but with application of a different statistical approach, Wilcoxon rank sum test, the level of detection was determined to be 1%. The ability to differentiate heterogeneous cell mixtures will help further extend whole cell MALDI fingerprinting to complex biological systems. Graphical Abstract.

Assessing the Efficiency of Cultivation Techniques To Recover Natural Product Biosynthetic Gene Populations from Sediment

Despite decades of cultivating microorganisms for use in drug discovery, few attempts have been made to measure the extent to which common cultivation techniques have accessed existing chemical space. Metagenomic studies have shown that cultivable bacteria represent a fraction of those that exist in the environment, and that uncultivated populations in sediment have genes that encode for a high diversity of novel natural product (NP) biosynthetic enzymes. Quantifying these genes in both sediment and cultivatable bacterial populations allows us to assess how much diversity is present on nutrient agar and is critical to guiding the trajectory of future NP discovery platforms. Herein, we employed next-generation amplicon sequencing to assess the NP biosynthetic gene populations present in two Lake Huron sediment samples, and compared these with populations from their corresponding cultivatable bacteria. We highlight three findings from our study: (1) after cultivation, we recovered between 7.7% and 23% of three common types of NP biosynthetic genes from the original sediment population; (2) between 76.3% and 91.5% of measured NP biosynthetic genes from nutrient agar have yet to be characterized in known biosynthetic gene cluster databases, indicating that readily cultivatable bacteria harbor the potential to produce new NPs; and (3) even though the predominant taxa present on nutrient media represented some of the major producers of bacterial NPs, the sediment harbored a significantly greater pool of NP biosynthetic genes that could be mined for structural novelty, and these likely belong to taxa that typically have not been represented in microbial drug discovery libraries.