Targeted analysis of lipids showed that sphingolipids were significantly upregulated in Ag treatments, indicating disturbance in the vacuolar and plasma membrane of A. thaliana plants . In 4-week old cucumber plants, exposed to 10 and 100 mg/l nAg, three times daily for consecutive 7- days via foliar spray, the responses were similar to ionic Ag exposure . Both AgNPs and Agþ ion exposures altered the accumulation of 76 metabolites involved in activation of carbohydrate metabolism , antioxidant system and defense response . Ag treatments also resulted in decreased accumulation of Gln and Asn, responsible for N fixation, and over-accumulation of salicylic acid, which is a major signaling molecule that activates plant defense and systemic acquired resistance. Exposure to 100 mg/l nAg enhanced the accumulation of linolenic and linoleic acids, the most abundant unsaturated fatty acids in the membrane .They also accumulated polyamines , GABA and its metabolites , which play a predominant role in stress response, nitrogen storage, signal transduction, growth and development. In maize leaves, TCA cycle intermediates, citric acid and a-ketoglutaric acid were increased whereas, succinic acid was decreased, affecting the carbon metabolism. The NPs altered several biological pathways in the leaves including amino acid metabolism , methane metabolism, pantothenate and CoA biosynthesis, carbon metabolism and pyridine metabolism. In addition, nFe3O4 and nTiO2 specifically altered isoquinoline alkaloid biosynthesis and glyoxylate and dicarboxylate metabolism. In roots, all the ENMs affected inositol phosphate metabolism and TCA cycle, however, nFe3O4 and nTiO2 affected ascorbate/aldarate, methane, glycerolipid, glyoxylate, dicarboxylate metabolisms. nTiO2 exposure to 7-day old rice seedlings in hydroponic media for 14-days resulted in elevated levels of metabolites in TCA cycle and pentose phosphate pathway , whereas decreased levels of metabolites involved in the carbohydrate synthesis metabolism including starch and sucrose metabolism, and glyoxylate and dicarboxylate metabolism . Direct exposure to nTiO2 suspension also increased the biosynthesis of fatty acids, amino acids and secondary metabolites in the rice seedlings. In a recent study, Gong et al. reported that a 6- day exposure to 10 and 500 mg/l nY2O3 disturbed carbohydrate metabolism, TCA cycle and amino acid metabolism in maize seeds . An increased accumulation of sugars , nft growing system free amino acids , GABA, and organic acids was attributed to cellular response to nY2O3 stress.
Three weeks-old Phaseolus vulgaris plants were chronically exposed to 250 and 1000 mg/l nCeO2 in the form of suspension every 48 h for 2 weeks via foliar spray or soil application, resulting in a total exposure load of 50 and 200 mg nCeO2 . Foliar application was shown to exhibit stronger negative effects; membrane lipids, lignans , and metabolites involved in pteridin and lignin synthesis were enriched, demonstrating immediate response on structural integrity, whereas most carotenoids, glucosinolates, terpenoids, andphenolic compounds were down-accumulated. In contrast, soil application resulted in overaccumulation of carotenoid and phenolic compounds, whereas polyols and pteridin-related compounds were down-accumulated. A three generational chronic exposure to nCeO2 exhibited higher degree of alterations in the metabolite accumulation in wheat grains compared to two-generational exposure . The altered metabolites were primarily involved in fructose-mannose metabolism, pentose-phosphate, phosphoribosyl pyrophosphate pathways; however, the degree of alteration in the grain metabolites was influenced by soil N availability. Vecerova et al. separated the polar and non-polar fractions of the leaf extracts obtained from barley plants exposed to an aerosol spray of CdO NPs for 21 days . LC-MS was used to determine sugars, phenolics, amino acids and Krebs cycle acids, while fatty acids were analyzed using GC-MS. An increase in the total amino acid content in roots and leaves, indicated protective mechanisms in response to stress. Decrease in levels of sugars in the roots, and phenolic acids in leaves were reported. In a recent study, we performed targeted metabolomics in soybeans exposed to CdS-quantum dots for 14 days in vermiculite soil media, which showed that major metabolic pathways in soybeans including glutathione metabolism, TCA cycle, glycolysis, fatty acid oxidation and biosynthesis were perturbed .In 7-day old A. thaliana plants grown on artificial media spiked with 125 and 1000 mg/l carbon nanodots for 7 days, growth was significantly inhibited compared to control and activated-carbon treatments. The metabolite profiling suggested increased accumulation of carbohydrates in A. thaliana roots and shoots, which indicates impact on the carbohydrate metabolism and cell wall stress . In the Cdot exposed A. thaliana tissues, overaccumulation of various alkaloids, lignan, carotenoids, flavonoids, amino acids, organic acids , and fatty acids were noted, indicating activation of defense response.
A three week chronic exposure of C60 fullerols via foliar spray twice a day for two days to cucumber plants showed degradation of plasma membrane metabolites like linolenic and palmitic acid, whereas increased accumulation of antioxidant metabolites such as 3-hydroxyflavone, 4-vinylphenol dimer, 1,4 benzenetriol, methyl transcinnamate, quinic acid, and dehydroascorbic acid .Plant rhizosphere is rich in metabolites that exude from roots and assist plants to cope with abiotic or biotic stress by building tolerance, defense and resilience . Zhao et al. reported that nCu exposure triggered an increase in the release of amino acid from C. sativus plants to sequester Cu ions at ENM-root interface and decreased citric acid content to control Cu dissolution from nCu, in order to lower Cu bio-availability and subsequent implications . Enhanced levels of ascorbic acid and phenolic compounds in the root exudate confirms increased stress in the plants exposed to nCu . In another study, ENM -treated soil collected after 28 days plant growth showed decreased levels of water-soluble Cu and increased levels of levoglucosan, linolenic acid, 4-hydroxycinnamic acid, allo-inositol, b-mannosylglycerate, gluconic acid, methyl phosphate, and methyl b-D galactopyranoside compared to untreated soil, indicating exudation of compounds involved in defense response . However, since the soil is a concomitant mixture of metabolites from the plant, residual organic matter and the soil microbiome, conclusions on root exudate characterization based on soil metabolomics could be confusing. Thus, sampling is crucial to extract maximum information from root exudate metabolomic studies, which may otherwise lead to inconclusive information. Appropriate control samples must be introduced while comparing ENM effects on root exudates between different plant species or varieties, as secondary metabolite composition vary significantly.Plant genome encodes for 36,795 proteins and the average size of a plant protein is 436 amino acid residues, which is 27% smaller than the average animal protein . Proteins are the key players in plant signaling and stress response as they are directly utilized in processes involved in cellular homeostasis. Characterizing the plant proteome offers functional analysis of the translated regions of the genome; hence, proteomics complements transcriptomic and metabolomic for a comprehensive understanding of underlying cellular mechanism in plants.Proteomic analysis serves as an important tool in crop improvement, protection and phytotoxicity studies as it has the potential to identify the key regulatory proteins, posttranslation modifications and protein-protein interactions in plants in response to an external stimulus.
Probing the ENM-plant interaction at the protein level is necessary to elucidate the cellular processes and identify the candidate proteins involved in ENM response. Using time-resolved experimental designs and by delving at sub-cellular or organelle levels, it is also feasible to identify ENM-responsive proteins involved in specific biological pathways at different growth stages of a plant . A rather unexplored area is the characterization of protein coronas formed around ENMs while interacting with plant tissues under different growth conditions, which also influence the toxicity and mobility of ENMs in plants.Two-dimensional gel electrophoresis separates protein mixtures based on charge in the first dimension and by mass in the second dimension on 2D-gels, which in combination with MS have been used for decades for plant proteome profiling. However, it has its limitations owing to poor sensitivity, low reproducibility, and low throughput. Especially for plant whole lysates that contain an array of secondary metabolites like pigments and phenolics, these compounds can introduce streaking in a gel . With rapid development in MS techniques, quantitative proteomics have evolved from gelbased to gel-free approaches. Like metabolomics,vertical hydroponic nft system proteomics can also be categorized into untargeted and targeted method. Due to the exploratory nature of untargeted proteomics, it is the preferred approach to screen for candidate protein markers to elucidate plant responses to ENM exposure. This approach can facilitate high-throughput analysis of protein abundance across different ENM exposures, tissue types, stages of growth, physiological conditions and stress conditions . In a gel-based approach, proteins are separated by 2DE and the spots showing comparable differences are excised from the gel. The proteins in the gel fractions are digested into peptides, which are then characterized by LC-MS. A typical gel- and label-free quantitative proteomic analysis used for discovery studies employ a bottom-up approach, where the proteins in a sample are cleaved into peptides, which are then separated, identified and quantified using LC-MS/MS . The steps and key challenges in proteomic analysis in ENM-plant interaction study are summarized below.Proteomic analysis demands robust sampling methods aligned with the scope of the study. Combining different organs into one sample must be avoided as the tissue-specific protein information is lost, resulting in confounding interpretation of results. In addition, proteomics result is also prone to variation in response to age, time of harvest, and growth conditions. Hence, control experiments and biological replicates should always be carried out simultaneously and harvested at the same time of the day. Plant tissues must be immediately frozen upon harvest, followed by homogenization into fine powder which can be stored at _x0005_ 80 C. The proteins in the sample are then subjected to precipitation, resuspension in buffer, followed by digestion using protease trypsin, which are then analyzed using LC-MS. The major challenges in sample preparation for proteomics arise from recalcitrant tissues, hydrophobic membrane proteins, presence of lignin, proteases, and metabolites like phenolic compounds, lipids, organic acids, carbohydrates, terpenes, and pigments, and presence of high abundance proteins that may mask variation in low abundance proteins during analysis .Electrospray ionization and Matrix-Assisted Laser Desorption Ionization are the most common platforms used to ionize peptides and proteins. The precise molecular mass of the resulting ions is then analyzed using mass analyzers, such as ion trap, quadrupole, Orbitrap, time-of-flight , and Fourier transform ion cyclotron resonance , which are often used in tandem to achieve higher degrees of ion separation .
In untargeted proteomics using LC-MS/MS, data dependent acquisition is performed, where the highest abundance peptide ions from full MS scans are selected for MS/MS. However, this may generate datasets skewed toward the identification of relatively high abundance proteins, thereby masking and excluding the low abundance proteins from quantification . Several labeling techniques such as isobaric Tags for Relative and Absolute Quantitation and Stable Isotope Labeling by Amino acids in Cell culture are also available which can help to reduce errors introduced during measurement conditions. However, untargeted proteomic analysis requires extensive data processing and is currently challenged by incomplete and limited nature of plant genomic and proteomic databases. In recent times, the use of labelfree shotgun proteomic techniques have become increasingly popular, as they do not restrict the number of proteins identified compared to gel based methods . However, gel-free methods have several drawbacks, such as masking of low abundant peptides and unavailability of protein database for all species.Untargeted proteomics require extensive post acquisition data processing after extracting features using LC-MS. There are several open-access and commercial software tools that can be used for feature extraction, such as MaxQuant, Proteome Discover, OpenMS, etc. The extracted features are subjected to filtering, peak detection, normalization, spectral identification, retention time/peak alignment, statistical analysis, peptide identification, quantitation, protein inference, and data visualization. All the raw and processed proteomics data should be deposited into public data repositories. Targeted proteomics, on the other hand, is hypothesis-driven and provides unparallel specificity and sensitivity for the targeted proteins of biological interest. In targeted proteomics, the mass spectrometer is programed to analyze a pre-selected group of proteins, using SRM, whereby assays are developed on a QqQ to detect fragment-ion signals arising from unique peptides representing each targeted protein.Comparative assessment of plant proteomes in response to ENMs can effectively screen candidate proteins and associated pathways, and potentially elucidate the cross talk between different processes that control the metabolite regulation in the cells. Several studies have employed untargeted proteomics to identify key plant proteins involved in ENMs-associated cellular signaling or stress response.