Metabolomics/Introduction to Metabolomics/Relationship to Traditional Metabolism

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Introduction edit

Relationship of Metabolomics to Traditional Metabolism

The traditional methodology of analytical biochemistry as it relates to metabolism is slowly and carefully being replaced by the newer and far more effective methods of the new field Metabolomics. This is being done simply because the old methods of classic metabolism can't yield the type of data needed for the aims of systems biology and metabolic engineering by concentrating on single pathways and only minor interactions between them. In comparison, Metabolomics is far more effective for a wide variety of systems biology concerns, like nutrigenomics and toxicology. Previously all attempts had been concentrated on proteomics and genomics because keeping track of the entire metabolome was an extraordinarily difficult task. But as more cheap and effective methods of doing this were developed Metabolomics steadily became more effective than even proteomics and genomics. The differences are strong enough to necessitate a rethinking of the experimental processes and procedures and the integrations of data sharing and acquisition. Even the nomenclature and terminology is undergoing an overhaul showing just how much of a radical change in focus and method Metabolomics is. This doesn't mean that the reductionism method is useless by any means. Parts of the biochemical processes and the metabolic systems of organisms can be better understood through reductionism Classical analytical biochemistry for metabolism is not being replaced. It just has a brand new systems orientated partner in the new and exciting biological and biochemistry fields of study and application that are opening up even now.

Phenylalanine Metabolism edit

Phenylalanine biosynthesis

Metabolomics relationship to traditional metabolism is not strictly for the biochemistry or proteomics to analyze. Certainly many other biological specialists can look at a metabolic pathway and relate to their specialized field. Whether there is an increase or decrease of intermediates concentration or a blockade or degrade of a metabolites, it will certainly have an effect over all of the biology of that system. Consider the metabolism of phenylalanine. Our body cannot synthesize phenylalanine and must obtain it through our diet. Phenylalanine called L-phenylalanine that is found in all proteins (beef, chicken, fish, pork, yogurt, eggs...). The other forms of phenylalanine are D-phenylalanine and D/L-phenylalanine, a blend of 50/50 portion of L and D-phenylalanine. D-phenylalanine is not found in food but can be synthesized in the lab.

Phenylalanine is an important amino acid because the body converts phenylalanine into tyrosine which is metabolize into acetoacetic acid, a ketone body, and fumeric acid, an organic acid that is an intermediate in the citric acid cycle. Phenylalanine is an essential amino acid because it helps synthesize the right intermediates as part of the body energy synthesis mechanism.If we consider the metabolism of phenylalanine, every single intermediate is important in this pathway. If we consider the metabolism of phenylalanine, every single intermediate is important in this pathway.

What would a geneticist say?

If there is a mutation in a gene that cause an enzyme to become dysfunctional in the pathway will result in the accumulation of an intermediate in the blood, which inevitably causes a genetic disease. When this occurs, the accumulation of an intermediate can either burst the cell or cause the body to find a way to break down the excess which both can invoke serious diseases and organ damage. For example, phenylalanine hydroxylase is the enzyme that converts of phenylalanine into tyrosine. If a mutation occurred that made phenylalanine hydroxylase to be dysfunctional, meaning it does not allow phenylalanine to be convert into tyrosine, there will be an accumulation of phenylalanine in the blood. The body has to find a way to get rid of the excess phenylalanine so phenylalanine is converted into phenylketone, a toxic intermediate that causes the disease phenylketonuria (PKU, 12q22-q24 mutation). The symptoms of a person with PKU are a mousy odor in the urine, irreversible psychomotor retardation and autism. Consider the enzyme homogenistic acid oxidase that converts homogenistic acid into maleylacetoacetic acid in the phenylalanine metabolism. If there is a mutation that limited the function of this enzyme, the result is the accumulation of homogenistic acid in the blood. This give rise a genetic disease known as alkaptonuria (AKU, 3q21-q23 mutation). Sir Archibald Edward Garrod discovered this inborn genetic disease and proposed that if there is a mutation in a gene it will alter an enzyme in the pathway. This disease cause a urine to turn black because of the oxidation of homogenistic acid in the urine when expose to air. In addition, ochronosis (black pigments) in the joints, bones and schlera will appear due to deposition of homogenistic acid. In every case of genetic disease resulted from the phenylalanine metabolism, if accumulation of an intermediate that caused by a mutation in the pathway.

Article: Phenylalanine metabolism in uremic and normal man

Article: PKU mutation G46S is associated with increased aggregation and degradation of the phenylalanine hydroxylase enzyme.

Article: Alkaptonuria, ochronosis, and ochronotic arthropathy

Website Sources edit

Web Site #1: Classic Metabolomics edit

General Overview

The focus of this resource is specifically the description of Metabolism as a concept and partially the description of the classical methodology of investigating its function and predicting its actions normally and when perturbed. It describes the classic methods of investigating and quantifying metabolism as following a reductionist approach by focusing on single metabolic pathways or on minor interactions between several pathways. see picture) The methods used here often were the tracking of radioactive tracers through a pathway or the tracking of metabolic levels of certain key metabolites and biomarkers. Slightly newer pre Metabolomics methods included using genomic and proteomic data to apply holistic mathematical and statistic analysis to the metabolic systems overall. (see picture) These methods were still less effective than Metabolomics would presumably be.

New Terms

An approach to understanding the function and nature of a complex entity or process by reducing it to the interactions of its parts and subprocesses. Considered the main way to understand chemistry up until recently, new approaches within metabolomics and other systems biology fields have shown that reductionism is not effective for the needs of the biological sciences and applications of said sciences. wiki/Reductionism
Metabolic Network
The complete set of metabolic and physical processes that determine the physiological and biochemical properties of a cell. The entire metabolic network is closely related to the Metabolome. wiki/Metabolic_network
Radioactive Tracer
A radioactive molecule used to track the flow of molecules and atoms within a set of reactions. Can also be used to track biofluids.
Metabolic Pathway
A naming convention in biochemistry, the word pathway describes a collection of related chemical reactions that all happen in sequence moving from an arbitrary beginning point and afterwards to an arbitrary ending point. The pathway model is used to reduce the complexity of biochemical systems for easier analysis and teaching. Metabolic pathways are specifically biochemical pathways of the metabolome. (gleaned from context of the resource)
Molecular Dynamics
a form of computer simulation that attempts to model the motions and interactions of atoms and molecules under the known laws of physics. In the context of this resource it was one of the methods of classical biochemistry, using the reduced aspects of chemistry to try to model the whole. wiki/Molecular_dynamics

Course Relevance

This particular resource relates directly to the class since we continue to learn about biochemistry using the reductionist approach today. Biochemical pathways are a standard part of the learning of metabolic biochemistry and nearly everything we’ve done up to this date has been involved in learning and being tested on our knowledge of various important pathways in the metabolic networks of animal and plant cells.

Web Site #2: The Metabolomics Standards Initiative (MSI) edit The Metabolomics Standards Initiative

General Overview

The focus of this resource is to provide important information and establish standards for the Metabolomics field during its infancy and beyond. It has coordinated several workgroups together to detail the aims and standards of Metabolomics as a field and benefit other researchers working on similar projects.
Biological metadata workgroups are responsible for detailing the metadata of the experiments for Metabolomics and setting up the standards for running a Metabolomics experiment as detailed by the Metabolomics Society Metabolomics Society Webpage. The chemical analysis workgroup's job is to “identify, develop and disseminate best chemical analysis practices in all aspects of Metabolomics” CAWG. It's not their job to determine how experiments should be run but to establish a set of minimal standards to follow. The Data Processing workgroup concentrates on establishing standards for algorithms and data reporting DPWG and the Ontology workgroup will concentrate on making the language of Metabolomics coherent and understandable as well as relevant to the sciences OWG. The exchange format Workgroup concentrates on the exchange of information and the format of analysis. EFGW.
All of these workgroups represent the ongoing efforts to establish Metabolomics as a field in its own right. It shows that the old terminology and methodology of classic analytical biochemistry is simply not viable for the new Metabolomics field. The fact that a new set of terms, descriptions and ontology is needed shows just how far this field has gone from the traditional field.

New Terms

Ontology (information science)
The representation of a set of concepts within a domain and the relationships between those concepts. wiki/Ontology_(information_science). In the context of this resource the domain is metabolic networks and the metabolome as well as the science of Metabolomics and the concepts contained within.
Data Processing
The conversion of raw data (usually through algorithms or analysis) into knowledge about a topic or concept. In the context of this resource, Data processing refers to the processing of data regarding metabolites and metabolic networks to yield knowledge about the function of biological systems and the effects of perturbations of them.
Metabolomics Society
A group of scientists and researchers dedicated to aiding the growth and development of the field of metabolomics as well as facilitating the cooperation between Metabolomics and other related fields.
Controlled Vocabularies (CV's)
Collection of terms and descriptions of concepts that are forced to follow specific rules or conventions to allow for maximum usefulness in the discourse about a field of study.
Disparate resources
Diverse or markedly different resources. This state in resources can often be a cause of problems for data communication since the differences in the resources make translation difficult.

Course Relevance

The description of the Biological Contexts and the Chemical analysis relates heavily to our class work as it describes the new base standards for metabolic investigation and deals with many of the biochemical pathways and aspects we have learned about.

Web Resource 3: The New Field of Metabolomics edit Wikipedia Article on Metabolomics

General Overview

The focus of this particular resource is a general overview of Metabolomics and the Metabolome. It describes the Metabolome and Metabolites as well as the study of them (Metabolomics itself) and then proceeds into giving a history of the new field. The webpage describes the analytical technologies used acquire data from the Metabolome and used to apply that data. It also went over many of the main applications that this field of study could be applied to.

New Terms

Systems Biology
The new realm of biological study that concentrates on the systematic analysis of complex interactions in biological systems. This represents a move away from reductionism in biology towards the perspective of integration. Some scientists state that systems biology is not new but instead a return to the original workings of biology which put full stock on learning the overall system during its earlier times. wiki/Systems_biology
The products and intermediate materials of metabolic processes. wiki/Metabolite#Metabolites
Secondary Metabolite
Any organic compound that is not directly involved in the normal development, growth and/or reproduction of an organism. wiki/Secondary_metabolite
Hypercycles (chemical)
A self reproducing macromolecular system in which the RNAs and enzymes cooperate (see picture) The macromolecules also cooperate to provide primitive translation abilities which allows information to be translated into enzymes.
“The quantitative measurement of the dynamic multiparametric metabolic response of loving systems to pathophysiological stimul or genetic modification” wiki/Metabolite#Metabonomics
The study of the relation between nutrition and genomics with the application of boosting and monitoring human health. wiki/Nutrigenomics

Course Relevance

Describes in some detail the workings of the metabolic systems of organisms and what is needed to understand them fully. Our class has dealt in the differences between Metabolomics and traditional metabolism as well as introductions to Metabolomics itself. This resource gives a very general but informative view of the material that we learned on our own for the first project on Metabolomics and expands off of it slightly. It also describes the Metabolome, which we have learned about piece by piece through pathways using the reductionist approach of classical biochemistry.

Article Resources edit

Article 1: New Methods of “-Omics” edit Metabolic Engineering in the -omics Era: Elucidating and Modulating Regulatory Networks

General Overview

The focus of this article is to describe the impact of the expansion of traditional sciences into “–omics” a shorthand reference for a systems biology approach that expands from a single function or pathway (something like genetics or metabolism) into an integrated system model (like genomics and metabolomics). It goes over specifically the advances made in each field and how those advances serve to benefit metabolic engineering overall. The article first describes the nature of the situation giving background on what we know about regulation and the hierarchy of the regulation of metabolic processes (see picture) and then goes deeper into the contributions of proteomics, systems biology, genomics and finally metabolomics (see picture). They wrap up the article discussing how this will benefit metabolic engineering more than previous techniques.

New Terms

Metabolic engineering
The optimization of the regulatory and genetic processes in a cell in order to produce certain substances more efficiently and faster. The entire context of this article orientates around making this sort of thing easier and more effective. wiki/Metabolic_engineering
The digestion of proteins by cellular enzymes or by other cellular means for a wide variety of purposes. This article cites it as one of the methods of phenotype regulation on the translation level of the hierarchy. wiki/Proteolysis
Holistic Approach
An approach that avoids the idea that the parts could yield an idea of what the whole would do and instead attempts to understand the function of the whole system. (gleaned from context in the article)
Hierarchical Metabolic Regulation
A set of theories that state that metabolic regulation operates in a hierarchy, that the genetic level is the first level, the protein translation level is the next level and the enzymatic regulation level is after that. It also states that complex interactions between level 2 and 3 often occur and blend the two together. (gleaned from context in the article)
Double growth. A description of the growth phases of a bacterial colony that is metabolizing a mixture of metabolites, usually sugars. wiki/Diauxie

Connection To Class

This article connects to Biochemistry
Metabolism mostly through its description of the Metabolomics portion and its focus on metabolic engineering. All of those things depend heavily on Metabolism and Metabolic knowledge. The article itself however is suggesting a move to the more systems orientated approach in Metabolomics (among other -omics) because the older methods of concentrating on single pathways and small scale integration simply does not give the knowledge necessary to achieve the aims that metabolic engineers wish to achieve. This relates to our Metabolomics projects and their contrast to the techniques and information we’ve learned that follows the more traditional approach of reduction of the systems to stand alone pathways with small levels of integration.

Article 2: Metabolomics and its new place in systems biology edit The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

General Overview

This article focuses entirely on Metabolomics and whether it will be a scientific contender in the near future. It initially describes the history of Metabolomics and how it fits into the entire scheme of biological investigation and prediction for systems biology (see picture) as well as the past difficulties in working in this relatively new field. Because the numbers of metabolites that need to be kept track of at once are so high, the sciences have put more energy into proteomics and genomics previously. However the new techniques being used are high thorough put and cheap to use. Due to this Metabolomics has easily surpassed past Metabolism investigation methods and is beginning to surpass proteomics and genomics as well.
The article describes several major success stories for Metabolomics including comparisons of silent phenotypes in yeast, a high throughput diagnosis of coronary artery disease, and monitoring gene therapy in Duchenne Muscular Dystrophy among several others. These things in particular are in contrast to previous investigations of simple metabolism mostly due to their higher level of application. Metabolomics is simply capable of a far greater effect on the application of biochemistry than the original reductionist approaches of metabolism
The article also discusses the sheer volume of data that needs to be cataloged and measured before full effectiveness was reached and how cross correlations between Metabolomics and other “-omics” technologies can have major mutual benefits. For instance, Metabolomics is an effective rapid phenotyping tool for mutant tracking in genomics and can speed up the data acquisition in many genomics investigations as well as giving a more accurate view (see picture).
The article also discusses in slightly less detail the need for powerful databases and accounts for the fact that the technology and methods already exist to create and populate these data storage and manipulation tools. The article proceeded to point out the need for new and more powerful analysis technology due to the sheer amount of data that one needs to acquire. New Software is especially needed to manipulate and analyze the data as it comes in. The article concludes by stating the great potential Metabolomics has both in working with other “-omics” and in revolutionizing metabolic profiling but states that the Metabolomics needs to carefully consider a lot of different factors to get its foot in the door, especially in terms of metadata.

New Terms

literally “data about data”. wiki/Metadata In the context of this article, Metabolomics metadata is the important side information about the metabolites, the profiles they interact within and their effects on the overall system. For Metabolomics the metadata could reach very high levels since the amount of variation and interconnected effects of changes within a metabolic profile can be astronomical.
Duchenne Muscular Dystrophy
Also referred to as DMD it is a form of muscular dystrophy caused by a mutation in the X chromosome related to the protein dystrophin. It causes decreasing muscle mass and progressive loss of muscle function in male children. wiki/Duchenne_muscular_dystrophy
Rapid Phenotyping
Phenotyping is generally a multiple tier process, requiring multiple tests, imaging and pathology to determine a phenotype of a specimen. Rapid phenotyping, using Metabolomics to generate a metabolic profile, is a high-speed method of generating the same resultant information that would normally take a battery of tiered tests and modeling. (gleaned from context in the article)
Co-resonant metabolites
In NMR spectroscopy nuclear magnetic resonance is used to detect certain chemicals. A co-resonant metabolite is specifically a metabolite whom has a resonance similar enough to other metabolites that detection and cataloging is difficult or even impossible using NMR. (gleaned from context of the article)
Toxicological insult
A metabolic event in which chemicals or metabolites themselves reach too high or too low of a level or interact with the metabolic system in some way that causes a toxicological effect on the system or part of the system. (context gleaned from article)

Course Relevance

This article deals very heavily in the chemical pathways that we’ve seen in class. During the discussion of how many metabolites needed to be measured the article discussed the structure and formation of various fatty acids and what effect that could have on the data needs of Metabolomics. It also discussed several side paths connected to pathways we’ve discussed in the success stories like tracking oxidative phosphorylation and sugar metabolism in yeast to find silent phenotypes.
It also discusses a lot of the new advances in Metabolomics, which directly relates to the previous project and how the new field of Metabolomics is growing.

Article 3: New drawing methods to represent changes in metabolic profiling edit

Metabolic network visualization eliminating node redundance and preserving metabolic pathways

General Overview

The focus of this article is describing the issues surrounding the previous metabolic profiling approaches that centered themselves on reductionism pathway analysis. It points out the shortcomings of attempts to draw genome scale metabolic networks using the typical pathway methods.
The article is a useful view into the methodology of traditional metabolism. For instance, it describes in the background how many biochemists would study one particular pathway, like glycolysis without taking into account other seemingly unrelated pathways that could interact with it. This article cited the usefulness of having large-scale representations of the metabolic profile and how it allowed a scientist to track perturbations of the metabolic system in multiple locations therefore boosting the efficiency and accuracy of metabolic investigation.
The article also discusses the issues with overlapping nodes and proposes a system in which concentration and focus of the metabolic profile and drawing may be chosen by the individual using it, to eliminate overlapping nodes but avoiding the loss of necessary data and context. They propose a software system using several algorithms to draw the metabolic maps in a more effective way. Several of these test maps are shown (see picture).
The article suggests using mixed bipartite graphs to model the data (see picture) and multi scale clustering in the drawing algorithm in order to help group together the drawing in a way that can be tracked visually and easily but not result in data loss. (see picture). The drawing method also draws metanodes to further enhance visualization with a recursive algorithm that draws the subgraphs from the most nested to the least nested. (see picture)
The article tested the software and methods and compared the drawing to other methodology tracking whether the drawing method was more or less accurate and whether it was easier or more difficult to read.

New Terms

Data Clustering is the partitioning of a data set into subsets of clusters, so that the data in each cluster share a common trait. Proximity to each cluster is often used as a measure of relatedness. wiki/Data_clustering In the context of the article, clustering was used to determine which overlapping node would go where to prevent node repetition in each of the pathways represented.
Mixed Graph
A graph is a basic object of graph theory. It is a set of objects referred to as points, nodes or vertices (nodes for this article), which are linked by lines or edges (edges for this article) wiki/Mixed_graph. A mixed graph specifically is a graph in which some edges may be directed and some may be undirected, meaning that a node can be related to another node in a one-way relation or both can be related to one another. This was based on the context of metabolic reactions sometimes being reversible and other times not being reversible.
Bipartite graph
A graph in which the vertices can be divided into two disjoint sets such that every edge connects a vertex between the two sets (no edge between two vertices of the same set.) They tend to be useful for matching problems. wiki/Bipartite_graph. Within the scope of this paper, bipartite graphs were chosen because the nodes were not linked (this is because of no link between reactions themselves and no link between substrates themselves, which were the nodes in that example.)
Node (graph)
Also referred to as a vertex, it is a fundamental unit for the formation of a graph. They are the objects in a graph, the edges imply relation between the nodes themselves. If two nodes are unrelated then there is no edge between them wiki/Vertex_graph_theory
Metabolic perturbation
Any event that causes a metabolic system to change from its normal functionality (gleaned from context in the article)
Recursion (recursive algorithm)
A method of defining functions in which the function being defined is applied within its own definition. More generally it is a concept used to describe a process of repeating objects in a self-similar way. A good analogy is two parallel mirrors and the infinite nested images they show of each other. Recursive algorithms are simple but effective because of the concept of recursion and always require some form of base case (an end condition) that stops the recursion from going infinite. In the context of this article a recursive algorithm was used to boost the efficiency of the drawing technique. wiki/Recursion

Course Relevance

This article is so far the most divergent from our class studies because of its strong emphasis of statistical analysis, algorithms and drawing methodology. However it does have some strong connections to our class work primarily because its description of past methods resembles our own methodology for learning biochemistry in relation to metabolism.
The old methods of concentrating on single pathways or mild interaction between several pathways is the methodology with which we learn about the metabolic biochemistry. The reductionist approach has benefits for learning as it makes things smaller and easier to absorb for students who are still working their way up into an understanding of the concepts.
It also relates because most of our learning results from drawn diagrams that follow biochemical conventions for showing reactions and path integration. So it directly impacts the methods with which we learn biochemistry not just the material we have learned so far.

Articles and Web Pages for Review and Inclusion edit