In Vivo Chemical Analysis of Plant Sap from the Xylem and Single Parenchymal Cells by Capillary Microsampling Electrospray Ionization Mass Spectrometry

Nutrient supplementation-induced metabolic profile changes and early appearance of free N-glycans in nutrient deficient tomato plants revealed by mass spectrometry

Inorganic fertilizers are routinely used in large scale crop production for the supplementation of nitrogen, phosphorus, and potassium in nutrient poor soil. To explore metabolic changes in tomato plants grown on humic sand under different nutritional conditions, matrix-assisted laser desorption ionization (MALDI) mass spectrometry was utilized for the analysis of xylem sap. Variations in the abundances of metabolites and oligosaccharides, including free N-glycans (FNGs), were determined. Statistical analysis of the sample-related peaks revealed significant differences in the abundance ratios of multiple metabolites, including oligosaccharides, between the control plants, grown with no fertilizers, and plants raised under "ideal" and "nitrogen deficient" nutritional conditions, i.e., under the three treatment types. Among the 36 spectral features tentatively identified as oligosaccharides, the potential molecular structures for 18 species were predicted based on their accurate masses and isotope distribution patterns. To find the spectral features that account for most of the differences between the spectra corresponding to the three different treatments, multivariate statistical analysis was carried out by orthogonal partial least squares-discriminant analysis (OPLS-DA). They included both FNGs and non-FNG compounds that can be considered as early indicators of nutrient deficiency. Our results reveal that the potential nutrient deficiency indicators can be expanded to other metabolites beyond FNGs. The m/z values for 20 spectral features with the highest variable influence on projection (VIP) scores were ranked in the order of their influence on the statistical model.

Capillary self-aspirating electrospray ionization (CSESI) for convenient and versatile mass spectrometry analysis

Electrospray ionization (ESI) is one of the most widely used ionization techniques, and its simplification can benefit many interested users. In this study, sample introduction by capillary action was studied and used to develop a simple ESI source called capillary self-aspirating electrospray ionization (CSESI). A conventional CSESI source requires only a common capillary of appropriate diameter in addition to the support of high voltage (HV). No pumps and sample loading is needed because the solution can spontaneously climb across the capillary by capillary action. With the proper modification of the glass capillary, the operation of CSESI can be further simplified and efficient. Specifically, cold plasma processing of the capillary creates a more hydrophilic surface that can facilitate sample introduction. Moreover, sputtering a thin platinum layer on the capillary tip makes the application of HV more convenient, and it also eliminates the influence of air bubbles in the capillary to ensure a sustained and stable electrospray. Overall, CSESI exhibits multiple desirable features such as simple structure, self-aspiration ability, low sample consumption, and inherent physical filtration capability. Apart from the routine ESI-MS analysis, it has also been applied in real-time monitoring of the oxidative dimerization of 8-methyl-1,2,3,4-tetrahydroquinoline, as well as direct analysis of muddy soil solutions without pretreatment.

Single cell metabolism: current and future trends

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

Extraction of cucumber phloem sap based on the capillary-air pressure principle

Changes in the substances in phloem sap can effectively reflect the nutritional status of cucumber plants during their growth. Because of the limitations of the time-consuming and complex operations of existing phloem sap extraction methods, the authors proposed a new extraction method based on the capillary-air pressure principle and designed a new sap sampling device. To examine the feasibility of the new sampling device, sap sampled from the same plant with the new method and the common EDTA method was analyzed by gas-phase mass spectrometry. The data showed that the number of substances in the sap sampled using capillary-air pressure was higher than that observed using the EDTA method. The concentration of substances sampled using capillary-air pressure was much higher than that observed using EDTA.

Single-Cell Metabolomics with Rapid Determination of Chemical Formulas from Isotopic Fine Structures

Metabolomic measurements can provide functional readouts of cellular states and phenotypes. Here, we present a protocol for single-cell metabolomics that permits direct untargeted detection of a broad number of metabolites under ambient conditions, without the need for sample processing, and with high confidence in the discovery and identification of the molecular formulas for detected metabolites. This protocol describes combining fiber-based laser ablation electrospray ionization (f-LAESI) with a 21 Tesla Fourier transform ion cyclotron resonance mass spectrometer (21T-FTICR-MS) to obtain high confidence molecular formula information about detected metabolites. The f-LAESI source utilizes mid-infrared laser ablation through a sharp optical fiber tip, affording direct ambient analysis of cells without the need for sample processing. Using the 21T-FTICR-MS as a mass analyzer enabled measurement of the isotopic fine structure (IFS) for numerous metabolites simultaneously from single cells, and the IFSs were in turn computationally processed to rapidly determine the corresponding elemental compositions. This metabolomics technique complements other single cell omics measurement methods, helping to resolve complex molecular interactions that take place within cells unattainable from single cell transcriptomic and proteomics methods.

Mass Spectrometry Imaging of Biological Tissues by Laser Desorption Ionization from Silicon Nanopost Arrays

Mass spectrometry imaging (MSI) plays an expanding role in the label-free spatial mapping of hundreds of molecules simultaneously. Currently, matrix-assisted laser desorption ionization (MALDI) is among the most widely adopted MSI techniques. However, matrix application can impact the fidelity of spatial distributions, and matrix selection and related spectral interferences in the low mass range can lead to biased molecular coverage. Nanophotonic ionization from silicon nanopost arrays (NAPA) is an emerging matrix-free MSI platform with enhanced sensitivity for several molecular classes, for example, neutral lipids and biooligomers. Here, we describe a protocol with minimal sample preparation for NAPA-MSI of metabolites, lipids, and biooligomers from biological tissues.

Hydrogen/Deuterium Exchange Aiding Metabolite Identification in Single-Cell Nanospray High-Resolution Mass Spectrometry Analysis

The identification of metabolites in single-cell or small-volume tissue samples using single-cell mass spectrometry (MS) is challenging. In this study, hydrogen/deuterium (H/D) exchange was combined with microsampling nanospray high-resolution mass spectrometry (HRMS) to improve the efficiency and confidence level of metabolite identification in a single cell using commercial software. A nanospray ion source showed an improved reaction depth of 8% for H/D exchange compared with an electrospray ion source. In total, 273 metabolites were identified in Allium cepa L. single cells by searching commercial databases. Generally, more than one candidate is given for a precursor ion by MS or tandem MS (MS²) databases such as ChemSpider, MetDNA, MassBank, and mzCloud. With the help of the H/D exchange technique, the number of candidates decreased and reduction of the search space by a factor of 8 was achieved. In addition, two enzymolysis products of isoalliin, the transient intermediate and its isomer, were tracked at the single-cell level using the proposed method.

Discriminating Leukemia Cellular Heterogeneity and Screening Metabolite Biomarker Candidates using Label-Free Mass Cytometry

Discriminating various leukocyte subsets with specific functions is critical due to their important roles in the development of many diseases. Here, we proposed a general strategy to unravel leukocytes heterogeneity and screen differentiated metabolites as biomarker candidates for leukocyte subtypes using the label-free mass cytometry (CyESI-MS) combined with a homemade data processing workflow. Taking leukemia cells as an example, metabolic fingerprints of single leukemia cells were obtained from 472 HL-60, 416 THP-1, 313 U937, 356 Jurkat, and 366 Ramos cells, with throughput up to 40 cells/min. Five leukemia subtypes were clearly distinguished by unsupervised learning t-SNE analysis of the single-cell metabolic fingerprints. Cell discrimination in the mixed leukemia cell samples was also realized by supervised learning of the single-cell metabolic fingerprints with high recovery and good repetition (98.31 ± 0.24%, -102.35 ± 4.82%). Statistical analysis and metabolite assignment were carried out to screen characteristic metabolites for discrimination and 36 metabolites with significant differences were annotated. Then, differentiated metabolites for pairwise discrimination of five leukemia subtypes were further selected as biomarker candidates. Furthermore, discriminating cultured leukemia cells from human normal leukocytes, separated from fresh human peripheral blood, was performed based on single-cell metabolic fingerprints as well as the proposed biomarker candidates, unveiling the potential of this strategy in clinical research. This work makes efforts to realize high-throughput single-leukocyte metabolic analysis and metabolite-based discrimination of leukocytes. It is expected to be a powerful means for the clinical molecular diagnosis of hematological diseases.

A needle-type micro-sampling device for collecting nanoliter sap sample from plants

In plant research, measuring the physiological parameters of plants is vital for understanding the behavior and response of plants to changes in the external environment. Plant sap analysis provides an approach for elucidating the physiological condition of plants. However, to facilitate accurate sap analysis, a sampling device capable of collecting sap samples from plants is required. In this paper, a minimally invasive, needle-type micro-sampling device capable of collecting nanoliter (~ 91 nL) quantities of sap from plants is described. The developed micro-sampling system showed great reproducibility (3%) in experiments designed to assess sampling performance. As a proof of concept, sap samples were collected continuously from target plants with the micro-sampling system, and the dynamic changes in potassium ions, plant hormones and sugar levels inside plants were analyzed. The results demonstrated the feasibility of the micro-sampling device and its potential for developing a measurement system for plant research in the future.

Single cell metabolomics using mass spectrometry: Techniques and data analysis

Mass spectrometry (MS) based techniques are gaining popularity for metabolomics research due to their high sensitivity, wide detection range, and capability of molecular identification. Utilizing such powerful technique to explore the cellular metabolism at the single cell level not only appreciates the subtle cell-to-cell difference (i.e., cell heterogeneity), but also gains biological merits corresponding to individual cells or small cell subpopulations. In this review article, we first briefly summarize recent advances in single cell MS experimental techniques, and then emphasize on the single cell metabolomics data analysis approaches. Through implementation of statistical analysis and more advanced data analysis methods, single cell metabolomics is expected to find more potential applications in the translational and clinical fields in the future.