Proteomics and metabolomics pdf

Evotec scientists have pioneered chemical proteomics applications to support target deconvolution of bioactive compounds emerging from phenotypic screens. Cellular target identification is the crucial step to enable further drug optimisation and development. Evotec has established a chemical proteomics platform which employs high-end quantitative mass spectrometry for compound selectivity analysis in the context of native proteomes and sub-proteomes.

Selectivity data about cellular on- and off-target liabilities is particularly useful for informed decisions at various stages of drug development, for example in the lead optimisation phase or in the pre-clinical candidate selection process. Evotec has strong expertise in the analysis of MHC class I peptidomes of cells, animal tissues, and patient derived samples.

The workflow enables the discrimination of biological samples based on presented peptides, the generation of target hypotheses, and the discovery of neo-antigens presented by tumours and infected cells. Evotec has established expertise and state-of-the-art methodologies in targeted metabolomics for the functional analysis of metabolic networks with applications in health, biotechnology and microbiology.

Our targeted metabolomics approach focuses on the analysis of specific group of metabolites related to certain metabolic pathways or a class of compounds including lipids phospholipids, lysophospholipids, sphingolipids, and neutral lipids , endocannabinoids, eicosanoids, corticosteroids, neurosteroids, oxysterols, nucleotides free fatty acids, and nicotinamide metabolome.

Proteomics and metabolomics. Figure 2 1. Metabolites present in the human body range from 2, to 3, and sometimes as high as 20, This number is very low when compared with 29, for genes and , for protein. In addition to metabolite profiling characteristic to metabolomics, it describes the wide spectrum of metabolites changing under certain conditions, such as disease intervention and functional gene changes.

Types of metabolites Metabolites may be divided into two types, primary and secondary metabolites. Primary metabolites is very important to the growth of the cell. They are produced during primary metabolic process such as respiration and photosynthesis. They are found in most organisms include sugars, amino acids, proteins, nucleic acids and polysaccharides. Secondary metabolites are compounds which produced biochemically from primary metabolites. They are not very important to cell growth as primary metabolites.

Secondary metabolites include alkaloids, phenolics, steroids, essential oils, lignins, resins and tannins. The History of Metabolomics History of metabolomics, starts with the pioneering work of Horning who is in the early s applied gas chromatography for the metabolites profiling in urine.

The Importance Metabolomics Metabolomics was first applied to study of toxicology and pharmacology, in born metabolic errors, and nutrition. In addition, metabolomics has been utilized in the investigation of metabolic pathways, biomarker identifications and molecular interactions and regulations. Metabolomics has been successfully used for the identification of new metabolic pathways and the quantification of metabolic fluxes. Human diseases One of the most greatest challenges in medicine is the use of metabolomics in predicting the appearance of tumor cells.

Agriculture The Agrochemical Division of the American chemical society sponsored as symposium at the 'ACS' national meeting was addressed methods for rapid detection, identification, and quantification of small molecules and metabolites within a sample and the potential relevance of such results.

The purpose of the symposium was to assemble key international research scientists to provide an appreciation of the technical challenges associated with metabolomics, its current application in agriculture in terms of plant biochemistry, food, environmental safety and its potential to be used as a tool to improve nutrition, diet and health,23 have been created. Drug resistance and development Metabolomics can lead to an improved understanding of drug candidate action and selection of target molecules as well as target population.

With a current estimate that bringing a new drug to the market costs approximately million USD and takes 14 years,24 the development of novel methods for more accurate, quicker and more cost effective drug testing and development is highly desirable. Detailed maps of cellular metabolic pathways for many species including humans. Bioenergy Due to rising demand for energy, compared with the effects of increasing CO2, the world turned to use biomass and biofuels as a source of energy.

Some attempts to make the production of lignocellulosic biofuels possible include the development of strategies to harness structural sugars from plant cell walls by prospecting novel microbial enzymes and biomass printed plant breeding. Sample preparation Figure 6 : a Harvest plant.

Grind the materials under liquid nitrogen. Compared to GC, HPLC has lower chromatography resolution, but it has the advantages that a much wider range of analytes can potentially be measured. Detection methods Mass spectrometry and NMR are the most commonly techniques that used in detection of the metabolites, although NMR is highly selective, non-destructive, has relative stability of chemical shifts and ease of quantification,31 its low sensitivity makes it the most technique that used in metabolite detection.

Over the past decade, mass spectrometry has undergone tremendous technological improvements allowing for its application to proteins, peptides, carbohydrates, DNA, drugs, and many other biologically relevant molecules. This chapter provides an overview of mass spectrometry, focusing on ionization sources and their significance in the development of mass spectrometry in biomolecular analysis This progress has led to the advent of entirely new instruments.

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Only tasks requiring hands-on effort in the laboratory will be performed there. Data delivery will continue to be made using the on-line Express Data Repository. Plants avoid being eaten in two ways, both involving a dominant role of SMs: repelling ovipositing herbivores along with attracting enemies and causing herbivore mortality. Insects may overcome this by secreting effectors in salivary proteins or capitalizing SMs Lu et al.

Although the strategies used by plants to defend against each kind of insect may vary Harun-Or-Rashid et al. Proteomics and metabolomics studies on rice response to BPH infection have revealed the occurrence of dynamic changes.

Lipid transport and metabolism, SM biosynthesis, amino acid transport and metabolism, and phytohormone signaling are commonly induced by BPH in both susceptible and resistant cultivars Wei et al. Notably, studies that have utilized resistant and susceptible cultivars to observe changes on protein and metabolite levels have identified markers and features associated with resistance to BPH infection.

This has also been demonstrated in time-course studies during each stage of BPH infection. Lower levels of amino acids in nymphs at the early, but not the late, stage of infection were reported in resistant cultivars compared with susceptible cultivars, indicating the rapid adaptation of BPH Liu et al.

A lipidomics study reported that the resistance conveyed by Bph6 gene involves wax biosynthesis for example fatty acid methyl esters Zhang et al. Recently, Kang et al. In that study, amino acids, organic acids, and fatty acids were also found to be stable in resistant cultivars. Phytohormones play an important role in the interaction between rice and hopper.

The function of SA in this interaction appears ambiguous, as it has been reported to be upregulated in both susceptible Peng et al. Studies on the response of rice to other insects have also revealed specific responses.

The response of a resistant rice line cultivar Qingliu to rice leafroller Cnaphalocrocis medinalis involved the activation of the Calvin cycle and the light reaction of photosynthesis, followed by the biosynthesis of amino acids and other metabolites Cheah et al.

Furthermore, resistance was determined by flavonoid biosynthesis at a specific rate and time. Rice also defends against the rice stem borer Chilo suppressalis using a similar mechanism. An integrated transcriptomics and metabolomics study suggested increased photosynthesis via the accumulation of monosaccharides and not of oligosaccharides, galactinol, and various amino acids Liu et al. Conversely, the resistance of rice to rice gall midge was found to involve differences in fatty acids before and after infection, whereas glutamine and oxotetracosanoic acids were associated with susceptibility Agarrwal et al.

Nematodes are universally present in nature and include species that are parasitic to plants, including rice Sato et al. Studies investigating rice-parasitic nematode interactions have generally involved mutants and transcriptome analyses, with a notable lack of proteomics and metabolomics studies.

In , a group of researchers used HPLC to evaluate differences in the phenolic profiles of five resistant and two susceptible deep-water rice upon Ditylenchus angustus infection.

They reported changes in SMs, such as chlorogenic acids and phytoalexin sakuranetin, which were mainly identified in the resistant rice Gill et al. A previous proteomics study on the rice and root-knot-nematode Meloidogyne graminicola interaction revealed new proteins as well as changes in existing proteins Xiang et al. Importantly, proteins involved in stress, metabolic pathways, and SM biosynthesis were found to accumulate at the early stage of infection, and this continued to the later stage of infection.

Lesion mimic mutants have been used to study resistance for over two decades. Therefore, proteomics studies on lesion mimic mutants of rice have widened our understanding of the fundamentals of hypersensitive response HR -like symptom.

A 2DE study on the lesion-mimic mutant Cell death and resistance 2 cdr2 and Rice spotted leaf 5 spl5 reported the accumulation of defense-related proteins, including probenazole-induced PBZ1 protein Tsunezuka et al. PBZ1 protein is also highly inducible in the Squamosa promoter-binding-like protein 1 spl1 mutant Kim et al.

Regarding central metabolism, photosynthesis is inhibited whereas respiration is enhanced via the down and upregulation of the associated proteins, respectively. Interestingly, the overproduction of ROS in lesion mimic mutants induces ROS-scavenging enzymes, such as L-ascorbate peroxidase 7, but suppresses superoxide dismutase in cdr2 mutant, confirming that the tight regulation of ROS is correlated with the formation time and density of lesions.

In addition, pathogen-infected mimic responses, such as enhanced lipid metabolism, were found to suppress carbon and nitrogen metabolism and the accumulation of SA and SMs in oscul3a mutants Gao et al. Proteomics and metabolomics have been studied to understand PTI, also known as basal resistance.

Loss-of-function of Pi21 , a quantitative resistance gene encoding a proline-rich protein that includes a putative heavy metal-binding domain and putative protein-protein interaction motifs, results in non-race specific and durable blast resistance Fukuoka et al. Protein profiling of a Pi21 -knockout mutant in the absence of pathogen infection revealed the accumulation of photosynthates, carbohydrate metabolites, and small molecule metabolites, compared with the WT plants Nawaz et al.

Proteomics has also been studied to understand ETI in Pizt -expressing plants in response to avirulent and virulent isolates, which suggested that various specific responses are induced by Pizt Tian et al. Accordingly, fluctuations in 56 proteins were common between Pizt and WT plants after infection and included PR proteins, proteins related to hormonal regulation and defense and stress response, receptor-like kinases, and cytochrome P Interestingly, the incompatible interaction differed significantly from the compatible interaction in only a few proteins, including alcohol dehydrogenase I, receptor-like protein kinase, endochitinase, similar-to-rubisco large subunit, NADP-dependent malic enzyme, and two hypothetical proteins.

This finding raises the question of whether variation in only those compounds could lead to different ETI outcomes. Studies investigating the response to biotic stresses have commonly reported changes in photosynthesis, possibly due to the abundant related proteins and metabolites.

Photosynthesis is upregulated or downregulated in susceptible or resistant phenotypes in response to different pathogens. In response to insects, two theories have been proposed to explain this phenomenon. The first notes that the intrinsic activation of photosynthesis provides organic compounds for the synthesis of defense-related metabolites as a result of pathogen manipulation for food resources Cheah et al. An opposing theory states that plants suppress photosynthesis to conserve energy and reduce food supply to pathogens.

Photosynthesis is enhanced by Xoo Sana et al. Therefore, photosynthetic activity varies depending on the feeding style of the pathogen, which is consistent with the response in other species for review Chen et al.

In addition, the appearance of cell death lesions during the necrotrophic infection stage is likely to underly the significantly lower level of photosynthesis-related enzymes and metabolites.

ROS exert a positive effect on defense to various pathogens by acting as signaling molecules or inhibiting pathogens by inducing local cell death. However, enhanced accumulation of ROS might result in cell death, thus facilitating the virus Xu et al. Therefore, the balance of ROS production and scavenging must be tightly regulated. The global profiling studies reviewed herein support the correlation between ROS and photorespiration and photosynthesis.

Although ROS accumulation has been reported in response to most biotic stresses, the timing and intensity of ROS vary significantly depending on the pathogen and cultivar, which present different levels of susceptibility. Phytohormones are also a key response exploited by rice and pathogens. In order to induce a defense response, rice plants upregulate SA signaling when exposed to M.

Conversely, ABA and cytokinins are activated during viral infection or during the early stage of M. SA activates ROS faster in resistant cultivars and alleviates the decrease in plant photosynthesis Li et al.

These findings suggest that phytohormone regulation, as part of plant defense mechanisms, via different target pathways is complicated, and that cooperation occurs between the pathways. Signaling components and SMs are highly diversified molecules, dependent on the type of biotic stress. For example, different interactions between rice and PGPR result in different metabolic changes Chamam et al. This is explained by the diverse types and functions of these molecules, especially SMs Erb and Kliebenstein SMs are less well-conserved, multifunctional metabolites, which guarantee the response to various biotic factors, but resist manipulation and save costs associated with biosynthesis.

Therefore, differences in SMs are associated with the resistance of different cultivars to pathogens at different stages of infection. Moreover, each cultivar has a set of differentially expressed proteins Prathi et al. Studying proteins and metabolites is more difficult than studying transcriptomics for several reasons: 1 the complexity of proteins and metabolites with different properties makes them difficult to identify using the same method.

In addition, proteins undergo various post-translational modifications, resulting in the generation of different isoforms for review, see Wu et al. Due to the cost of producing SMs, rice plants are required to maintain a high level of regulation, processing, and storage, to ensure that some SMs are produced at trace amounts for review, see Erb and Kliebenstein To detect those SMs, an appropriate experimental design, pipelines, and standard methods are critical for review, see Alexander and Cilia ; Chen et al.

For example, 15 out of 21 general differentially expressed proteins were unknown in the study of Zhang Zhang et al.

Thirty-three identified metabolites were undefined in the study of Madhavan Madhavan et al. Rice plants possess specific metabolites for review, see Okazaki and Saito , which cannot be identified based on the libraries of other species. However, with recently developed methods, we have made progress and expanded our knowledge in this area, exemplified by the identification of new biomarkers Agarrwal et al.

Global studies of proteins and metabolites are usually combined with transcription profiling Table 1 and Table 2. In general, the fluctuation of major molecules is well corelated with gene expression Sana et al.

Peroxidase expression is not associated with the activity between Nipponbare and O. In the study of Zhang, the expression patterns of four out of eight genes were in contrast to the expression pattens of the proteins Zhang et al. A low correlation between mRNA and protein levels has also been observed in half of all genes examined in secreted proteins from rice suspensions Dong et al.

This may be due to post-transcriptional regulation, for example by RNA binding proteins Xu et al. Furthermore, the challenges of methods used in proteomics have limited the identification of all possible isoforms, consequently influencing correlation studies.

Time-series studies have complemented our understanding on the conflict between pathogens and rice at each stage of infection in susceptible and resistant cultivars. Accordingly, the outcome of this conflict is determined by the up or downregulation of certain molecules as well as the intensity of these molecules. For example, defense-related metabolites, cyanoamino acids, and lipid metabolism were increased in both susceptible and resistant cultivars but were more stable in rice resistant to BPH Kang et al.

Resistant rice infected with M. These studies confirmed a potential metabolic target but emphasized the limitations associated with studying and utilizing metabolites, especially phytohormones, whose balance is critical for plant growth and development Peleg and Blumwald One necessary approach for more effective outcome from rice-pathogen interaction studies would be integration of omics approaches, such as combining transcriptomics with proteomics or metabolomics Prathi et al.

Moreover, combining separate studies on specific stressor may serve as excellent approach, even though this may bring out some inconsistency.

Resultant proteins and metabolites in response to a common biotic stressor may belong to similar pathways, which will eventually increase the efficacy of outcome to get more detailed insight into the intricate cellular activities during rice responses to that stressor.

For instance, two separate proteomics and metabolomics studies on rice response to leafroller insect Cnaphalocrocis medinalis suggest that the JA biosynthesis pathway related proteins and metabolites are critical for resistance Cheah et al. The limited identification of molecules in proteomics and metabolomics studies as compared to transcriptomics studies has implied the simpler outcome at the final products than the gene regulation.

In this context, metabolomics studies on resistance genes have recalled a long-standing question: whether different genes associated with resistance result in different outcomes via different metabolic pathways. If this is the case, SMs represent a tool that is guaranteed to perform well.

However, the greatest obstacle is the cost of SM biosynthesis. In most studies, the number of upregulated SMs is greater than the number of downregulated SMs, affirming the tight regulation of SMs due to their cost.

Therefore, more studies on resistance genes and how to deploy SMs in plant resistance are needed. The application of metabolomics to improve plant performance to stresses has been previously suggested Hong et al. An example was proposed by Kushalappa and Gunnaiah , who suggested 10 heuristic steps to streamline metabolomics-proteomics studies to identify resistance genes.

The main difference in the metabolic profiles of resistant and susceptible cultivars provided us with scaffolds to produce stable resistant rice, which is sometimes confined by a resistance gene approach. Thus, we collected the potent metabolites responsible for resistance to different stressors, as illustrated in Fig.

These metabolites are specifically induced or reduced in resistant rice cultivars Table 2. Due to the multiple functions of primary metabolites in rice, we limited our analysis to SMs or primary metabolites that function in resistance via a non-primary pathway. These SMs provide targets for further investigation and use. Potent metabolites linked to stress resistance in rice.

Those metabolites were specifically increased red arrow or decreased green arrow in resistant plants as compared to susceptible plants in indicated studies Table 2 , marked by a.