Metabolism-Based Click-Mediated Platform for Specific Imaging and Quantification of Cell Surface Sialic Acids

Abstract

Although we believe that the cell surface sialic acids (Sias) are playing an important role in cell-cell interactions and related tumor metastasis processes, acquisition of their quantitative information has yet been a challenge to date. Here, we reported the construction of a new analytical platform for Sias-specific imaging and quantification. We used N-azidoacetyl-mannosamine tetraacylated as a metabolic sugar substrate to bioassemble azido-Sias on the surface of cells via the metabolic pathway of Sias de novo synthesis. These azido-Sias allow us to perform a duplex Sias-specific analysis with various fluorescent and elemental reporters such as DIBO-Alexa Fluor 647, DBCO-DOTA-Eu, and DBCO-PEG-BODIPY, which can be easily labeled and/or tagged through an effective copper-free bioorthogonal click reaction. Compared to the previous reported strategies, we quantified the cell surface Sias with the LODs (3σ) down to 8.9 fmol and 0.24 pmol using Eu- andB-species unspecific isotope dilution ICPMS, in addition to their red- and green-CLSM profiling. Such a platform enables us to evaluate Sias regulation under the administration of paclitaxel, finding that 1 μM paclitaxel induced a significant Sias decrease of 67% on the surface of hepatic tumor cell SMMC-7721, while had no obvious adverse effect to that of para-carcinomatous liver cell LO2. Besides Sias, we believe that this metabolism-based click-mediated platform will provide opportunities to study other monosaccharides and their corresponding biological roles when more corresponding chemically modified sugar substrates and specific bioorthogonal reactions are developed.

Laser Cleavable Probes-Based Cell Surface Engineering for in Situ Sialoglycoconjugates Profiling by Laser Desorption/Ionization Mass Spectrometry

“…We obtained a linear range (Figure b, Table S1) of Tphsene from 1 μM (100 fmol) to 1 mM (100 pmol) with correlation of 0.9973 ( y = 1.01258 x + 0.01086, the average RSD is 7.9%, n = 5). The limit of detection is 5 fmol under 20% laser energy, which is lower than the reported results of the ICPMS tag Figure S3 shows the signal of Tphsene with signal-to-noise (S/N) of 3 based on three repeated tests.…”

“…During the LDI MS test, only 1 μL of the cell solution was needed to spot on the target plate, which is counted to contain only 500 ± 15 cells. In the quantification of inductively coupled plasma mass spectrometry (ICPMS) based method, 1 mL of cell solution was injected into the MS spectrometer, which contained up to 165 000 cells . So it suggested that we have achieved sensitive and selective metabolic incorporation and labeling of the cell-surface sialoglycoconjugates.…”

“…However, the quantification of cell surface sialoglycoconjugates is still a challenge. As a sensitive, accurate, fast, and robust method, mass spectrometry (MS) has emerged for detecting glycoconjugates, especially glycoproteins. − Matrix-assisted LDI MS has high sensitivity, tolerance of mixtures, and high-throughput measurement capability, thus it has been the prevalent tool for analysis and relative quantification of glycoproteins/glycopeptides. ,, However, there are problems during analysis of sialoglycoproteins by matrix assisted LDI MS: (i) Sias give negative charge which will decrease their ionization efficiency, leading to low sensitivity; (ii) the labile nature of Sias makes them readily lost before the ions reach the detector (i.e., in- and post-source decay); (iii) existence of carboxyl groups often cause multiple alkali metal adducts, thus complicating mass spectral interpretation; (iv) the structural heterogeneity and low ionization efficiency of sialoglycoproteins lead to the relatively low sensitivity. To solve these problems, it is suggested: (i) analyzing in negative ion mode, but the loss of Sias is not suppressed; (ii) by modification of Sias such as derivatization of carboxyl groups, but the loss of Sias and multiple alkali metal adduction still exist; − (iii) effective separation, enrichment, and derivatization prior to MS analysis are required − but is complicated and easy sample-loss.…”

Viruslike Element-Tagged Nanoparticle Inductively Coupled Plasma Mass Spectrometry Signal Multiplier: Membrane Biomarker Mediated Cell Counting

“…Sensitivity and selectivity are the most important premises to accomplish an accurate quantitative bioanalysis. With the advantages of at least pg mL –1 level limit of detection and 0.5 atomic mass unit resolution as well as free of sample matrix, hard ionization inductively coupled plasma mass spectrometry (ICPMS) has evolved into a promising bioanalytical tool since the beginning of this century, − thanks to the continuous developments of chemoselective and biospecific element-tagging strategies. − Compared with the most popular soft ionization ESI/MALDI-based mass spectrometry, multiple proteins and nucleic acids could be quantified with only one isotopic element standard using ICPMS via selective labeling of element-complex tags. − Cells could also be counted when their specific membrane molecules were labeled with the element-complex tags, resulting in the membrane molecule quantity times signal amplification relative to one cell itself. − Biomolecule analysis and cell counting sensitivity could be further improved when element-loaded engineered nanoparticles and polymers were used. − They did well for relative signal amplification, however, and were particularly prone to some uncertainty for an absolute, quantitative bioanalysis because the number of elemental atoms and/or ions in the nanoparticles and polymers was somewhat difficult to control within a tolerant range. , For example, the most widely used Au nanoparticles prepared with conventional methods using citrate reduction of HAuCl 4 spanned 10% variation from small to large particles; and the lanthanide-containing polymer particles about 100 nm diameter coped with the size distribution range of 0.03 to 0.209 polydispersity index, the number of the lanthanide ions chelated by the individual particles was not easy to accurately control. These uncertainties are actually more serious when rare tumor cells need to be counted at the early stage of cancers.…”

Synthetic Host–Guest Assembly in Cells and Tissues: Fast, Stable, and Selective Bioorthogonal Imaging via Molecular Recognition

“…Developing strategies to selectively assemble bioorthogonal molecular components within the complexities of cells and tissues is of great interest in biology. , It continues to drive advancements in various domains of fundamental and medical research, including protein modification, − sensitive assay development, therapeutic targeting, and cell surface engineering . Additionally, such bioorthogonal strategies have become the key components in applications that require molecular tagging or labeling, such as imaging. − To date, a variety of covalent approaches were developed for this purpose. Notable examples include the Staudinger ligation reaction, Cu­(I) catalyzed or strain promoted azide–alkyne cycloaddition reaction (“click” chemistry), , and inverse electron demand 1,2,4,5-tetrazine (Tz) ligation. − …”