
Automation in Proteomics and Genomics: An Engineering Case-Based Approach
Author(s): Gil Alterovitz (Author), Roseann M. Benson (Author), Marco Ramoni (Author)
- Publisher: Wiley
- Publication Date: April 20, 2009
- Edition: 1st
- Language: English
- Print length: 340 pages
- ISBN-10: 0470727233
- ISBN-13: 9780470727232
Book Description
Automation in Proteomics & Genomics: An Engineering Case-Based Approach describes the automation technology currently in the areas of analysis, design, and integration, as well as providing basic biology concepts behind proteomics and genomics. The book also discusses the current technological limitations that can be viewed as an emerging market rather than a research bottleneck. Topics covered include:
- molecular biology fundamentals: from ‘blueprint’ (DNA) to ‘task list’ (RNA) to ‘molecular machine’ (protein); proteomics methods and technologies; modelling protein networks and interactions
- analysis via automation: DNA sequencing; microarrays and other parallelization technologies; protein characterization and identification; protein interaction and gene regulatory networks
- design via automation: DNA synthesis; RNA by design; building protein libraries; synthetic networks
- integration: multiple modalities; computational and experimental methods; trends in automation for genomics and proteomics
- new enabling technologies and future applications
Automation in Proteomics & Genomics: An Engineering Case-Based Approach is an essential guide to the current capabilities and challenges of high-throughput analysis of genes and proteins for bioinformaticians, engineers, chemists, and biologists interested in developing a cross-discipline problem-solving based approach to systems biology.
Editorial Reviews
From the Inside Flap
Automation in Proteomics & Genomics: An Engineering Case-Based Approach describes the automation technology currently in the areas of analysis, design, and integration, as well as providing basic biology concepts behind proteomics and genomics. The book also discusses the current technological limitations that can be viewed as an emerging market rather than a research bottleneck.
Topics Covered include:
- molecular biology fundamentals: from ‘blueprint’ (DNA) to ‘task list’ (RNA) to molecular machine’ (protein); proteomics methods and technologies; modelling protein networks and interactions
- analysis via automation: DNA sequencing; microarrays and other parallelization technologies; protein characterization and identification; protein interaction and gene regulatory networks
- design via automation: DNA synthesis; RNA by design, building protein libraries; synthetic networks
- integration: multiple modalities; computational and experimental methods; trends in automation for genomics and proteomics
- new enabling technologies and future applications
Automation in Proteomics & Genomics: An Engineering case-Based Approach is an essential guide to the current capabilities and challenges of high-throughput analysis of genes and proteins for bioinformaticians, engineers, chemists, and biologists interested in developing a cross-discipline problem-solving based approach to systems biology.
From the Back Cover
Automation in Proteomics & Genomics: An Engineering Case-Based Approach describes the automation technology currently in the areas of analysis, design, and integration, as well as providing basic biology concepts behind proteomics and genomics. The book also discusses the current technological limitations that can be viewed as an emerging market rather than a research bottleneck.
Topics Covered include:
- molecular biology fundamentals: from ‘blueprint’ (DNA) to ‘task list’ (RNA) to molecular machine’ (protein); proteomics methods and technologies; modelling protein networks and interactions
- analysis via automation: DNA sequencing; microarrays and other parallelization technologies; protein characterization and identification; protein interaction and gene regulatory networks
- design via automation: DNA synthesis; RNA by design, building protein libraries; synthetic networks
- integration: multiple modalities; computational and experimental methods; trends in automation for genomics and proteomics
- new enabling technologies and future applications
Automation in Proteomics & Genomics: An Engineering case-Based Approach is an essential guide to the current capabilities and challenges of high-throughput analysis of genes and proteins for bioinformaticians, engineers, chemists, and biologists interested in developing a cross-discipline problem-solving based approach to systems biology.
About the Author
Dr. Alterovitz received his PhD in Electrical and biomedical Engineering at MIT through the Harvard/MIT Division of Health Sciences and Technology. He is a biomedical informatics fellow with the Harvard/MIT Division of Health Sciences and Technology (HST), Children’s Hospital Informatics Program, and the Harvard Medical School-Partners Center for Genetics and Genomics. He is currently heading a new class that he initiated at Harvard University, bio.95hfa: ‘Proteomics and Cellular Network Engineering’. He has served on the Harvard/MIT Division of Health Sciences and technology MD Curriculum and the Harvard/MIT Division of Health Sciences and Technology PhD Admission committees. He was a US Fulbright to Canada (University of Toronto) in 1998-1999. Dr Alterovitz has an S.M. Degree from the Massachusetts Institute of Technology (MIT) in Electrical Engineering and Computer Science, where he was a NDSEG Fellow. His B.S. is in Electrical and Computer Engineering from Carnegie Mellon University.
Dr Alterovitz has worked at Motorola (where he won the Motorola Intellectual Property Award), at IBM, and as a consultant for several national clients. As an invited contributor, he wrote the ‘Proteomics’ section for the Wiley Encyclopedia of Biomedical Engineering. Dr Alterovitz has appeared or has been cited for achievements in several national media outlets, including three separate editions of USA Today and National Public Radio. He was also featured in the Boston Globe. In 2001, he was selected as one of approximately 20 international delegates to the Canada 25 forum (to discuss healthcare/technology) covered by CBC radio, a national V special and Canada’s Maclean’s.
RoSeann Benson
For eleven years, Ms Benson was a chemical engineer, and participated in all phases of automation implementation projects in a variety of industries: nuclear, semiconductor, aluminum, specialty chemical and environmental. Her engineering experience ran the project gamut, from inception to completion, and included framing the technical problems correctly; designing bench tests to establish system specifications; setting and calculating design parameters; selecting,purchasing and installing equipment; and utilizing general equipment to meet particular applications. As part of thee engineering projects, Ms Benson acquired extensive experience with documentation. One paper, ‘Shock Deionization of the K and L Basins’, presented the research and outcome of a successful project where indefinite scientific principle were defined more accurately within a particular context. She won an American Institute of Chemical Engineers’ (AIChE) National ‘Outstanding Paper’ award for the paper that she wrote and presented at an AIChE meeting. Ms Benson’s formal credentials include a Clarkson University Chemical Engineering bachelor’s Certificate in Administration and Management.
Ms Benson writes nonfiction outside of the engineering field, and is a contributor to three Cadogan Guides. Her first book, 101 Puppy-Buying Tips has recently been published by LifeTips.com. In addition, she serves on the City of Beverly’s Library Board of Trustees.
Marco F. Ramoni
Marco F. Ramoni is Assistant Professor of Pediatrics and Medicine at Harvard Medical School and Assistant Professor of Health Sciences and Technology at the Harvard University and the Massachusetts Institute of Technology Division of Health Sciences and Technology. He is also Associate Director of Bioinformatics at the Harvard Partners center for Genetics and Genomics and the Director of the National Library of Medicine Training Fellowship in Biomedical Informatics ‘Biomedical Informatics’ at the Harvard-MIT Division of Health Sciences and technology, core faculty of the course Genomic Medicine at Harvard Medical School and a member of the curriculum committee of the Cellular and Molecular Medicine track of the Medical Physics and Medical Engineering graduate program at Harvard Medical School and a member of the curriculum committee of the cellular and Molecular Medicine track of the Medical Physics and Medical Engineering graduate program at Harvard-MIT Division of Health Sciences and Technology. He is cofounder of Bayesware LLC, a software company developing machine-learning programs based on Bayesian methods. He received a PhD in Biomedical Engineering and a BA in Philosophy (Epistemology) from the University of Pavia (Italy), completed his postdoctoral training at McGill University, Montreal (Canada). He has held academic and visiting positions at the University of Massachusetts, the University of London (United Kingdom), the Knowledge Media Institute (United Kingdom) and the University of Geneva (Switzerland). He is author of over 90 publications in genetics, biomedical informatics, statistics and artificial intelligence.
Excerpt. © Reprinted by permission. All rights reserved.
Automation in Proteomics and Genomics
An Engineering Case-Based Approach
John Wiley & Sons
Copyright © 2009 John Wiley & Sons, Ltd
All right reserved.
ISBN: 978-0-470-72723-2
Chapter One
The Central Dogma: From DNA to RNA, and to Protein
Takashi Ohtsuki and Masahiko Sisido Department of Bioscience and Biotechnology, Okayama University, Japan
Within a single cell – the minimum unit of every living organism – many millions of different types of molecule are working to maintain the cell, to promote its replication, or even to cause its suicide. The bioprocesses conducted within the cell are chemical reactions that proceed under the control of a highly organized network of molecular interactions between relevant biomolecules.
Among these biomolecules, three types of biopolymer are crucial, namely nucleic acids, proteins and polysaccharides. Nucleic acids preserve, replicate and transform the genetic information that serves to design a number of different proteins and low-molecular-weight biomolecules. Proteins function at almost all stages of the bioprocesses, from the birth to the death of a cell. Polysaccharides play important roles in communicating molecular network information and in storing chemical energy. Biopolymer concentrations are regulated to optimum levels for each stage of the bioprocess, but decompose when their roles are complete. This chapter will focus on the molecules and bioprocesses that are related to protein biosynthesis, where DNA is the source of genetic information and the amino acids are the raw materials.
1.1 Chemistry of DNA
Deoxyribonucleic acid (DNA) is a biopolymer that is located inside the nucleus of mammalian cells or in the cytosol of bacterial cells. DNA stores the genetic information that will be converted into the amino acid sequences of protein molecules in the cell.
DNA, as shown in Figure 1.1, is a polyester made through condensations between a deoxyribose as the diol unit and a phosphoric acid as the bivalent acid unit. The negatively charged phosphates make the DNA molecule water-soluble. Due to the asymmetric arrangement of the 5′-OH and 3′-OH groups on the deoxyribose unit, DNA is a directional biopolymer. The chain end with the 5′-OH or 5′-O-phosphate unit is called the 5′-end, while the end with the 3′-OH or 3′-O-phosphate unit is called the 3′-end.
DNAs are characterized by the sequences of base groups that are linked to the deoxyribose units. There are four types of base group: adenine (A), thymine (T), guanine (G) and cytosine (C). Different DNAs carry different sequences of nucleobases that are read from the 5′ end to the 3′ end.
Nucleobases form hydrogen bonds between A and T and between G and C exclusively, as shown in Figure 1.2. With few exceptions, the A-T/G-C pairing is a basic rule common to all organisms. As a result of this exclusive pairing, a DNA strand that has a 5′ A-T-G-C-A-T-G-C-3 sequence, for instance, forms a stable hybrid only with a DNA strand of a 5′-G-C-A-T-G-C-A-T-3′ sequence. Note that the two DNA strands hybridize in an antiparallel manner, as shown in Figure 1.3. The two DNA strands that carry fully matched sequences are called a complementary pair. Watson and Crick discovered that the complementary DNA strands form a double-helical structure, as shown in Figure 1.4.
As the base sequences are kept safely inside the cylinder of negatively charged, double-helical chains, the genetic information has been stored securely for many generations in the form of the sequences of nucleobases. The double-helical structure, however, is not absolutely stable, and unfolds at high temperatures or by the action of an enzyme called a helicase.
1.2 Replication of DNA
In order for genetic information to be transferred to the next generation, DNA must first be copied to replicate itself. DNA replication is conducted with an aid of an enzyme called DNA polymerase. The basic chemistry of the replication proceeding inside the enzyme is illustrated in Figure 1.5.
First, the double-helical chain is unfolded and one of the DNA chains is copied to create its complementary chain. The monomer units involved in this polymerization are activated nucleotide units, dATP, dTTP, dGTP and dCTP. The triphosphate unit of the dNTP units is very susceptible to the attack of the 3′-OH group, and forms a diphosphate linkage. Guided by the enzyme, a correct monomer binds to the template DNA chain and reacts with the 3′-OH group of the growing chain. In this way, the new chain grows from the 5′ end to the 3 end.
1.3 Transcription from DNA to RNA
Although the stable and inflexible DNA double-helical structure is suitable for the storage of genetic information, its large size necessitates that a smaller, more flexible biopolymer, is used to translate the stored genetic code into proteins. To that end, the base sequences are copied into another type of biopolymer nucleic acid, specifically ribonucleic acid (RNA).
RNA is structurally different from DNA in two ways (see the left part of Figure 1.6). The first difference is that an OH group is attached to the 2’C atom of deoxyribose unit; the 2′-OH derivative is called a ribose unit. The second difference is that a methyl group is removed from the thymine unit to make a uracil unit, U. The introduction of a 2′-OH group causes a small conformational change on the ribose unit such that the RNA chain will favor single-stranded conformations. The single-stranded RNAs, however, often assume an intramolecularly hydrogen-bonded structure, such as a stem-loop structure (see Figure 1.6, right).
Similar to DNA replication, one of the double-stranded DNA chains is copied to a single RNA chain of the complementary nucleobase sequence, except for the alteration of T to U, as shown schematically in Figure 1.7. This procedure is known the transcription process, and is conducted with an enzyme called RNA polymerase. The chemistry of transcription is similar to the replication process, and the monomers are ATP, UTP, GTP and CTP.
1.4 Translation of the Nucleobase Sequence of mRNA to the Amino Acid Sequence of Protein
The information stored in the form of a nucleobase sequence along an RNA chain is translated to an amino acid sequence of a protein, as shown schematically in Figure 1.8. RNAs that serve the translation process are called messenger RNAs (mRNAs). In the translation process, three consecutive nucleobases on a mRNA are taken together and converted to a specific amino acid. The set of three nucleobases is called a codon. As four possibilities (A, U, G and C) exist for each nucleobase, there are [4.sup.3] = 64 different codons.
Adapter molecules bridge the codons and the amino acids. A class of small RNAs, called transfer RNAs (tRNAs), serve as those adapters. The base sequence of a yeast tRNA that bridges between a codon UUC and an amino acid, phenylalanine, is shown in Figure 1.9.
tRNAs commonly have stem-loop structures with three loops and four stems. Among the loops, the anticodon loop contains three consecutive nucleobases that bond specifically to its complementary codon; thus, a tRNA of a specific anticodon binds to a specific codon on an mRNA. If a particular amino acid is linked to a specific tRNA of specific anticodon, the amino acid will be called up by the codon. In this way, the sequence of nucleobases is translated to the sequence of amino acids.
1.5 The Codon Table
A list that correlates between the base sequences of codons and the amino acids is called a codon table (see Figure 1.10). The codon table is common to almost all organisms on the earth, except for several violations found in mitochondria. The codon table is, therefore, the second basic rule of living organisms.
Because 64 codons correspond to 20 amino acids, there is redundancy in the use of codons. For example, phenylalanine is coded by both UUU and UUC, while leucine is coded by six codons. It must be noted that UUA, UAG and UGA do not correspond to any amino acid, and so are called stop codons. Thus, if they appear on an mRNA, the protein synthesis will cease. Compared with the stop signal, the mechanism of the start of protein synthesis is a little complicated, and is different in bacteria and eukaryotic cells. In prokaryotic bacteria, mRNA has a special region, called the Shine-Dalgano (SD) sequence, and the first AUG codon after the SD sequence works as the start codon. In eukaryotic cells, the first AUG codon from the 5′ terminal of an mRNA is the start codon. In any case, the N-terminal amino acid of a newly synthesized protein will be methionine.
1.6 The Twenty Amino Acids
The types of amino acid that constitute proteins, again, are common to all organisms; the chemical structures of the 20 amino acids are listed in Figure 1.11.
Amino acids are classified into five types, depending on chemical and physical properties of their side groups. The first group (Gly, Ala, Val, Leu, Ile, Met and Pro) has hydrophobic side groups, while the second group (Ser, Cys, Thr, Asn and Gln) has nonionic polar side groups. The third group (Asp and Glu) has anionic side groups, and the fourth (Arg and Lys) has cationic groups. The fifth group (His, Phe, Tyr and Trp) has aromatic groups. Protein conformations depend on the combination of the different groups along a polypeptide chain, such as water-soluble globular proteins, membrane-penetrating hydrophobic proteins, and so on.
1.7 Aminoacylation of tRNA
The process of linking a specific amino acid to a specific tRNA is called the aminoacylation of tRNA, and is governed by a single enzyme, aminoacyl tRNA synthetase (ARS) for each amino acid. For example, phenylalanine (Phe) is charged onto a tRNA that has an anticodon UUU or UUC, with an enzyme PheRS. Aminoacylation consists of two stages, as illustrated in Figure 1.12 (top). First, a particular amino acid is bound to its specific ARS and is activated with adenosine triphosphate (ATP) to form an adenylated amino acid. In the second stage, a particular tRNA is bound to its specific ARS that holds the adenylated amino acid. The latter then reacts with the 3′-terminal OH group of the tRNA to form an ester linkage between the amino acid and the tRNA.
ARS is a ‘super’ enzyme that recognizes three different substrates: ATP, a specific amino acid, and a specific tRNA. In the first stage of aminoacylation, the formation of an adenylated amino acid activates an amino acid. The mixed anhydride of carboxylic acid and phosphoric acid of the adenylated amino acid is very susceptible to water. Inside the enzyme, however, the mixed anhydride is kept safe, until a correct tRNA is bound in proximity so as to induce the aminoacylation. The accuracy of the ARS/amino acid/tRNA selection is very high, and the probability of an erroneous aminoacylation is less than [10.sup.-4].
(Continues…)
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