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One example is the grass Anthoxanthum odoratum , which can undergo parapatric speciation in response to localised metal pollution from mines. Selection against interbreeding with the metal-sensitive parental population produced a gradual change in the flowering time of the metal-resistant plants, which eventually produced complete reproductive isolation.

Selection against hybrids between the two populations may cause reinforcement , which is the evolution of traits that promote mating within a species, as well as character displacement , which is when two species become more distinct in appearance. Finally, in sympatric speciation species diverge without geographic isolation or changes in habitat. This form is rare since even a small amount of gene flow may remove genetic differences between parts of a population. One type of sympatric speciation involves crossbreeding of two related species to produce a new hybrid species.

This is not common in animals as animal hybrids are usually sterile. This is because during meiosis the homologous chromosomes from each parent are from different species and cannot successfully pair. However, it is more common in plants because plants often double their number of chromosomes, to form polyploids. Speciation events are important in the theory of punctuated equilibrium , which accounts for the pattern in the fossil record of short "bursts" of evolution interspersed with relatively long periods of stasis, where species remain relatively unchanged.

As a result, the periods of stasis in the fossil record correspond to the parental population and the organisms undergoing speciation and rapid evolution are found in small populations or geographically restricted habitats and therefore rarely being preserved as fossils. Extinction is the disappearance of an entire species. Extinction is not an unusual event, as species regularly appear through speciation and disappear through extinction.

The role of extinction in evolution is not very well understood and may depend on which type of extinction is considered. The Earth is about 4. Microbial mat fossils have been found in 3. More than 99 percent of all species, amounting to over five billion species, [] that ever lived on Earth are estimated to be extinct.

Highly energetic chemistry is thought to have produced a self-replicating molecule around 4 billion years ago, and half a billion years later the last common ancestor of all life existed. All organisms on Earth are descended from a common ancestor or ancestral gene pool. Second, the diversity of life is not a set of completely unique organisms, but organisms that share morphological similarities. Third, vestigial traits with no clear purpose resemble functional ancestral traits and finally, that organisms can be classified using these similarities into a hierarchy of nested groups—similar to a family tree.

Past species have also left records of their evolutionary history. Fossils, along with the comparative anatomy of present-day organisms, constitute the morphological, or anatomical, record. However, this approach is most successful for organisms that had hard body parts, such as shells, bones or teeth. Further, as prokaryotes such as bacteria and archaea share a limited set of common morphologies, their fossils do not provide information on their ancestry.

More recently, evidence for common descent has come from the study of biochemical similarities between organisms. For example, all living cells use the same basic set of nucleotides and amino acids. Prokaryotes inhabited the Earth from approximately 3—4 billion years ago. The next major change in cell structure came when bacteria were engulfed by eukaryotic cells, in a cooperative association called endosymbiosis. The history of life was that of the unicellular eukaryotes, prokaryotes and archaea until about million years ago when multicellular organisms began to appear in the oceans in the Ediacaran period.

Soon after the emergence of these first multicellular organisms, a remarkable amount of biological diversity appeared over approximately 10 million years, in an event called the Cambrian explosion. Here, the majority of types of modern animals appeared in the fossil record, as well as unique lineages that subsequently became extinct. About million years ago, plants and fungi colonised the land and were soon followed by arthropods and other animals.

Concepts and models used in evolutionary biology, such as natural selection, have many applications. Artificial selection is the intentional selection of traits in a population of organisms. This has been used for thousands of years in the domestication of plants and animals.

Proteins with valuable properties have evolved by repeated rounds of mutation and selection for example modified enzymes and new antibodies in a process called directed evolution. Understanding the changes that have occurred during an organism's evolution can reveal the genes needed to construct parts of the body, genes which may be involved in human genetic disorders. Breeding together different populations of this blind fish produced some offspring with functional eyes, since different mutations had occurred in the isolated populations that had evolved in different caves.

Evolutionary theory has many applications in medicine. Many human diseases are not static phenomena, but capable of evolution. Viruses, bacteria, fungi and cancers evolve to be resistant to host immune defences , as well as pharmaceutical drugs. It is possible that we are facing the end of the effective life of most of available antibiotics [] and predicting the evolution and evolvability [] of our pathogens and devising strategies to slow or circumvent it is requiring deeper knowledge of the complex forces driving evolution at the molecular level.

In computer science , simulations of evolution using evolutionary algorithms and artificial life started in the s and were extended with simulation of artificial selection. He used evolution strategies to solve complex engineering problems. In the 19th century, particularly after the publication of On the Origin of Species in , the idea that life had evolved was an active source of academic debate centred on the philosophical, social and religious implications of evolution.

Today, the modern evolutionary synthesis is accepted by a vast majority of scientists. While various religions and denominations have reconciled their beliefs with evolution through concepts such as theistic evolution , there are creationists who believe that evolution is contradicted by the creation myths found in their religions and who raise various objections to evolution. The teaching of evolution in American secondary school biology classes was uncommon in most of the first half of the 20th century.

The Scopes Trial decision of caused the subject to become very rare in American secondary biology textbooks for a generation, but it was gradually re-introduced later and became legally protected with the Epperson v. Arkansas decision. Since then, the competing religious belief of creationism was legally disallowed in secondary school curricula in various decisions in the s and s, but it returned in pseudoscientific form as intelligent design ID , to be excluded once again in the Kitzmiller v.

Dover Area School District case. From Wikipedia, the free encyclopedia. This article is about evolution in biology. For related articles, see Outline of evolution. For other uses, see Evolution disambiguation. Change in the heritable characteristics of biological populations over successive generations. For a more accessible and less technical introduction to this topic, see Introduction to evolution.

Darwin's finches by John Gould. Key topics. Introduction to evolution Evidence of evolution Common descent Evidence of common descent. Processes and outcomes. Natural history. History of evolutionary theory. Fields and applications. Applications of evolution Biosocial criminology Ecological genetics Evolutionary aesthetics Evolutionary anthropology Evolutionary computation Evolutionary ecology Evolutionary economics Evolutionary epistemology Evolutionary ethics Evolutionary game theory Evolutionary linguistics Evolutionary medicine Evolutionary neuroscience Evolutionary physiology Evolutionary psychology Experimental evolution Phylogenetics Paleontology Selective breeding Speciation experiments Sociobiology Systematics Universal Darwinism.

Social implications. Evolution as fact and theory Social effects Creation—evolution controversy Objections to evolution Level of support. Main article: History of evolutionary thought.


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Further information: History of speciation. Main article: Modern synthesis 20th century. Further information: Introduction to genetics , Genetics , Heredity , and Reaction norm. White peppered moth. Black morph in peppered moth evolution. Main article: Genetic variation. Further information: Genetic diversity and Population genetics. Main article: Mutation. Further information: Sexual reproduction , Genetic recombination , and Evolution of sexual reproduction.

Further information: Gene flow. Main article: Natural selection. Further information: Sexual selection. Further information: Genetic drift and Effective population size. Further information: Genetic hitchhiking , Hill—Robertson effect , and Selective sweep. Further information: Gene flow , Hybrid biology , and Horizontal gene transfer. Play media. Further information: Adaptation. Further information: Coevolution. Further information: Co-operation evolution. Main article: Speciation. Further information: Assortative mating and Panmixia. Further information: Extinction. Life timeline. This box: view talk edit.

Single-celled life. Multicellular life. Earliest water. Earliest life. Earliest oxygen. Atmospheric oxygen. Oxygen crisis. Sexual reproduction. Earliest plants. Ediacara biota. Cambrian explosion. Earliest apes. See also: Human timeline , and Nature timeline. Main article: Evolutionary history of life. See also: Timeline of evolutionary history of life. Further information: Common descent and Evidence of common descent.

Main articles: Evolutionary history of life and Timeline of evolutionary history of life. Main articles: Applications of evolution , Selective breeding , and Evolutionary computation. Further information: Social effects of evolutionary theory , Oxford evolution debate , Creation—evolution controversy , Objections to evolution , and Evolution in fiction. Argument from poor design Biocultural evolution Biological classification Evidence of common descent Evolution in Variable Environment Evolutionary anthropology Evolutionary ecology Evolutionary epistemology Evolutionary neuroscience Evolution of biological complexity Evolution of plants Project Steve Timeline of the evolutionary history of life Universal Darwinism.

Archived from the original on Evolution Fourth ed. Sunderland, Massachusetts: Sinauer Associates, Inc. May Evolutionary processes are generally thought of as processes by which these changes occur. Four such processes are widely recognized: natural selection in the broad sense, to include sexual selection , genetic drift, mutation, and migration Fisher ; Haldane The latter two generate variation; the first two sort it.

Fundamentals of Biochemistry: Life at the molecular level Fifth ed. Hoboken, New Jersey: Wiley. On the Origin of Species 2nd ed. London: John Murray. November Annual Review of Ecology and Systematics. Archived PDF from the original on Ford February Scientific American. Bibcode : SciAm. Archived from the original PDF on Retrieved Biology Direct. William ; Kudryavtsev, Anatoliy B.

October 5, Precambrian Research. Bibcode : PreR.. January Nature Geoscience. Bibcode : NatGe Associated Press. Archived from the original on June 29, The Daily Telegraph. London: Telegraph Media Group. November 16, Bibcode : AsBio.. Leeds International Classical Studies. The Quarterly Review of Biology. December The British Journal for the History of Science.

Evolution Online exhibit. October 4, September—October The Textbook Letter. August Behavioral and Brain Sciences. Darwin Correspondence Project. Cambridge, UK: University of Cambridge. Letter , November 22, June Journal of Biosciences. Bibcode : PNAS.. March—April The American Naturalist. Journal of the Proceedings of the Linnean Society of London. July 17, Archived from the original on January 19, September Journal of Applied Genetics. American Journal of Medical Genetics.

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April 25, Bibcode : Natur. It has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material. The American Biology Teacher. Bibcode : NW May 11, Nature Reviews Genetics. Trends in Genetics. April Molecular Medicine Today. Evolutionary Ecology Submitted manuscript.

Annals of the New York Academy of Sciences. International Microbiology. Butlin, Roger K. Some of the values in table 1 on p. The errors do not affect the conclusions drawn in the paper. The corrected table is reproduced below. Journal of Molecular Evolution. Bibcode : JMolE.. April 17, Journal of Molecular Biology. Ryan ; Hebert, Paul D. Genome Research. PLOS Biology.

October Cell Research. July Annual Review of Biochemistry. Annual Review of Genetics. September 5, Current Biology. Bibcode : CBio Charles J. Evolutionary Theory. Bibcode : PNAS Molecular Ecology. Thane; et al. Current Opinion in Microbiology. October 29, May 30, Science Submitted manuscript. Bibcode : Sci Journal of Virology.

September 9, February Allen August March 14, Perspectives in Biology and Medicine. July 31, July 7, Proceedings of the Royal Society B. Evolutionary Ecology Research. December 23, October 12, Spencer; et al. February 11, Barsh, Gregory S. PLOS Genetics. Richard October 29, Journal of Heredity.

January—February March 6, William, Jr. The Japanese Journal of Human Genetics. Long live the neutral theory". Journal of Evolutionary Biology. Molecular Biology and Evolution. Nei, Masatoshi May Molecular Biology and Evolution Erratum. American Journal of Human Genetics. November 29, May 15, July 20, July 22, TalkOrigins Archive. February 22, June 9, Microbiology and Molecular Biology Reviews. Origins of Life and Evolution of Biospheres. Craig; Brockhurst, Michael A. Allen February Microbiology and Immunology. He also showed that RNA, the nucleic acid that many scientists believe served as the precursor to DNA-based life, is a particularly cheap building material.

This principle would apply to inanimate matter as well. Scientists have already observed self-replication in nonliving systems. According to new research led by Philip Marcus of the University of California, Berkeley, and reported in Physical Review Letters in August, vortices in turbulent fluids spontaneously replicate themselves by drawing energy from shear in the surrounding fluid.

And in a paper appearing online this week in Proceedings of the National Academy of Sciences, Michael Brenner, a professor of applied mathematics and physics at Harvard, and his collaborators present theoretical models and simulations of microstructures that self-replicate. These clusters of specially coated microspheres dissipate energy by roping nearby spheres into forming identical clusters.

Besides self-replication, greater structural organization is another means by which strongly driven systems ramp up their ability to dissipate energy. A plant, for example, is much better at capturing and routing solar energy through itself than an unstructured heap of carbon atoms. Thus, England argues that under certain conditions, matter will spontaneously self-organize.

This tendency could account for the internal order of living things and of many inanimate structures as well. Condensation, wind and viscous drag are the relevant processes in these particular cases. He is currently running computer simulations to test his theory that systems of particles adapt their structures to become better at dissipating energy. The next step will be to run experiments on living systems. Having an overarching principle of life and evolution would give researchers a broader perspective on the emergence of structure and function in living things, many of the researchers said.

These characteristics include a heritable change to gene expression called methylation, increases in complexity in the absence of natural selection , and certain molecular changes Louis has recently studied. Emily Singer contributed reporting. Reprinted with permission from Quanta Magazine , an editorially independent division of SimonsFoundation.

You have free article s left. These studies raised concerns in the media that larger, more complex organisms, such as the smallpox virus which is approximately , base pairs long , might be within reach. DNA synthesis technology is currently limited by the cost and time involved to create long DNA constructs of high fidelity as well as by its high error rate. Several recent studies have demonstrated important steps toward making gene synthesis readily affordable and accessible to researchers with small budgets, by decreasing its cost and improving its error rate.

Almost simultaneously, another research group described a novel approach for reducing errors by more than fold compared to conventional gene synthesis techniques, yielding DNA with one error per 10, base pairs. Developments in DNA synthetic capacity have generated strong interest in the fabrication of increasingly larger constructs, including genetic circuitry, 12 the engineering of entire biochemical pathways, 13 and, as mentioned above, the construction of small genomes.

DNA synthesis technology could be used as an alternative method for producing high-value compounds. DNA synthesis technology could allow for the efficient, rapid synthesis of viral and other pathogen genomes—either for vaccine or therapeutic research and development, or for malevolent purposes or with unintentional consequences. The proposal focuses on instrument and reagent licensing e.

Classical genetic breeding has proven itself over and over again throughout human history as a powerful means to improve plant and animal stocks to meet changing societal needs. The late 20th century discovery of restriction endonucleases, enzymes that cut DNA molecules at sites comprising specific short nucleotide sequences, and the subsequent emergence of recombinant DNA technology provided scientists with high-precision tools to insert or remove single genes into the genomes of a variety of viruses and organisms, leading, for example, to the introduction of production-enhancing traits into crop plants.

The process is repeated for several generations.

With DNA shuffling, sequence diversity is generated by fragmenting and then recombining related versions of the same sequence or gene from multiple sources e. Basically, it allows for the simultaneous mating of many different species. The result is a collection of DNA mosaics. The reassortment that occurs during the shuffling process yields a higher diversity of functional progeny sequences than can be produced by a sequential single-gene approach. But chances are it never would have evolved. Evidence from at least one study shows that the best parent is not necessarily the one closest in sequence to the best chimeric offspring and thus would probably not represent the best starting point for single-gene evolution i.

The technology has developed quickly, such that scientists are not just shuffling single genes, they are shuffling entire genomes. In , biologists used whole-genome shuffling for the rapid improvement of tylosin production from the bacterium Streptomyces fradiae ; after only two rounds of shuffling, a bacterial strain was generated that could produce tylosin an antibiotic at a rate comparable to strains that had gone through 20 generations of sequential selection.

Despite continual improvements in the throughput of current screening procedures, the use of conditions that impose strong selective pressures for emergence of molecules with the desired properties is far more efficient in finding the most potent molecule in the pool. Ultimately, this rapid molecular method of directed evolution will allow biologists to generate novel proteins, viruses, bacteria, and other organisms with desired properties in a fraction of the time required with classical breeding and in a more cost-effective manner.

For example, virologists are using DNA shuffling to optimize viruses for gene therapy and vaccine applications. Bioprospecting is the search for previously unrecognized, naturally occurring, biological diversity that may serve as a source of material for use in medicine, agriculture, and industry. These materials include genetic blueprints DNA and RNA sequences , proteins and complex biological compounds, and intact organisms themselves. Humans have been exploiting naturally-derived products for thousands of years.

Even as high-throughput technologies like combinatorial chemistry, described above, have practically revolutionized drug discovery, modern therapeutics is still largely dependent on compounds derived from natural products. Excluding biologics products made from living organisms , 60 percent of drugs approved by the Food and Drug Administration and pre-new drug application candidates between and were of natural origin. And aspirin—arguably one of the best known and most universally used medicines—is derived from salicin, a glycoside found in many species in the plant genera Salix and Populus.

Bioprospecting is not limited to plants, nor is drug discovery its only application. Most recently, with the use of molecular detection methods, scientists have uncovered a staggering number of previously unrecognized and uncharacterized microbial life forms. Natural products discovered through bioprospecting microbial endophytes—microorganisms that reside in the tissues of living plants—include antibiotics, antiviral compounds, anticancer agents, antioxidants, antidiabetic agents, immunosuppressive compounds, and insectides.

With respect to the last, bioinsecticides are a small but growing component of the insecticide market. Bioprospected compounds exhibiting potent insecticidal properties include nodulisporic compounds for use against blowfly larvae isolated from a Nodulisporium spp. Prospecting directly for DNA and RNA sequences that encode novel proteins with useful activities has become a potentially important scientific and business enterprise.

This approach entails searches based on random expression of thousands or millions of sequences, followed by screening or selection for products with desired activities. This kind of approach can synergize with the DNA shuffling technology described above. For example, Diversa Corporation San Diego, CA utilizes bioprospecting of microbial genomes to develop small molecules and enzymes for the pharmaceutical, agricultural, chemical, and industrial markets. The samples are collected from environments ranging from thermal vents to contaminated industrial sites to supercooled sea ice.

Bioprospecting has also been applied to the discovery of microbial agents in efforts to better understand the diversity of microbes in the environment that might serve as human pathogens if provided the opportunity. It has been argued that by deliberately scrutinizing the kinds of vectors and reservoirs that exist in a local environment for previously unrecognized microbes, novel agents might be identified long before they are discovered to be human, animal or plant pathogens, thus providing early warning of potential disease-causing agents.

One might consider both molecular and traditional cultivation-based approaches for examining hosts, such as fruit bats and small rodents, which are already known to serve as reservoirs for important human microbial pathogens Hendra and Nipah viruses, Borrelia spp. As described above, the potential benefits associated with the discovery of novel products and microbial genetic diversity are innumerable. Whereas DNA synthesis enables the acquisition of genetic sequence diversity, these techniques allow for the generation of libraries of chemical compounds having a diversity of shapes, sizes, and charge characteristics—all of which may be of interest for their varied abilities to interact with and bind to biologically active proteins or macromolecular complexes, thereby altering the biological properties of these proteins and complexes.

Combinatorial chemistry techniques can be used to create a wide range of chemotypes or molecular motifs, ranging from large polycyclic compounds of a peptidic nature to smaller, presumably more druglike, compounds. Initially, it was believed that when used in combination with high-throughput screening technologies, combinatorial techniques would dramatically. While this has not yet proven to be the case, most pharmaceutical companies are still heavily invested in combinatorial chemistry and are exploring the development and implementation of novel methods to create additional libraries of compounds.

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A recent trend noted in the pharmaceutical industry is the move from the development of large, unfocused, general screening libraries to smaller, less diverse libraries for screening against a particular target or family of related targets. The origins of this new branch of chemistry can be traced back to the early s, when methods were developed for the solid-phase synthesis of peptides.

The final polypeptide is released by chemically breaking its bond with the solid support and washing it free. This reduced the scale of the process and greatly facilitated the parallel synthesis of large numbers of peptides. A further modification of the technique enhanced the ability to create a diversity of peptide sequences by incorporating a combinatorial approach. However, by mixing the resin from different tea bags after each individual stepwise addition of an amino acid residue, combinatorial peptide libraries involving a great diversity of amino acid sequences could be readily generated, in which each resin bead bears an individual peptide with a unique amino acid sequence.

After the compounds are synthesized and a library is constructed, a selection or screening strategy is needed to identify unique compounds of interest to the biological sciences. The most obvious method involves affinity isolation of the peptide of interest on an immobilized target molecule, followed by release of the peptide and analysis utilizing combinations of gas-phase chromatography, high-performance liquid chromatography HPLC , mass spectrometry, and nuclear magnetic resonance NMR.

It is also possible to determine the structure of compounds still. While direct determination of structure, as described in the previous paragraph, works well for small libraries, these techniques are generally not applicable to large, mixture-based libraries. One of the earliest tagging approaches employed the use of oligonucleotides. Numerous additional tagging techniques and agents have since been developed. Solution-phase parallel synthesis is becoming the combinatorial chemistry technique of choice in the pharmaceutical industry, driven primarily by advances in laboratory automation, instrumentation, and informatics.

Compounds can be synthesized either as single discrete compounds per reaction vessel or as mixtures of compounds in a single reaction vessel, so many of the same principles described above for solid-phase resinbound principles are applicable here as well. The earliest reports of solution phase combinatorial chemistry techniques involved the use of a common multicomponent reaction, termed the Ugi reaction, in which an isocyanide, an aldehyde, an amine, and a carboxylic acid are combined in a single-reaction vessel to create a single major product.

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Using this synthetic approach coupled with advanced data analysis techniques, scientists were able to identify compounds with the desired biological effect after synthesizing only a compound subset of the , possible products. This represents a fold increase in discovery efficiency over conventional approaches.

The current trend in parallel solution-phase chemistry is leaning toward the development of smaller arrays 12 to 96 compounds of simple to moderately complex chemical compositions. As the robotics and laboratory instrumentation required for parallel synthesis become more af-. Such efforts are ideally carried out with knowledge of the structure of the target molecule, usually gained by application of either x-ray crystallography or NMR techniques.

Structure-activity relationships are determined as lead compounds, identified initially through the screening of large libraries of compounds, are modified at specific sites, and the impact of the chemical modification on the desired biological properties of the compound is determined. The purity and identity of combinatorially-produced compounds have been a source of recent great discussion and technological advance since, in order for any meaningful data to be produced from a biological assay, the purity of the compound of interest must be as high as possible.

Combinatorial chemistry techniques are not only useful for drug discovery and development, they are being used in the search for better superconductors, better phosphors for use in video monitors phosphors are substances that emit light , better materials for use in computer magnetic and other storage devices, and better biosensors for the detection of medically-important molecules and environmental toxins.

Using combinatorial and high-throughput methods, the pharmaceutical industry synthesizes and screens several million new potential ligands annually. Although most companies have little use for the tens of thousands of these compounds identified each year as toxic, some might have potential as biochemical weapons Chapter 1. The NIH Roadmap discovery effort is particularly worrisome in this regard, because of plans to optimize lead compounds shown to be capable of targeting specific cellular proteins. The goal is not to develop therapeutic agents but rather to provide a series of reagents, facilitating.

While the technologies applied in combinatorial chemistry are not exceedingly complex, a wide variety of laboratory automation and instrumentation is needed to stage an effective combinatorial chemistry campaign. High-throughput screening HTS refers to the process of examining large numbers of diverse biomolecular or chemical compounds in a rapid and efficient manner for properties of interest.

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Such technologies are essential to achieving any benefit from the construction of large and diverse libraries of compounds, as they are used to select a particular compound having the desired properties. These properties might include biochemical or enzymatic activities desired of a potential therapeutic agent or toxicity in such an agent that under usual circumstances one would wish to avoid. Advances in miniaturized screening technologies, bioinformatics, robotics, and a variety of other technologies have all contributed to the improved biological assay efficiency that characterizes HTS.

In contrast to this paradigm, in which a large library of compounds i. These are routinely used in both basic and applied research to facilitate the large-scale screening and monitoring of gene expression levels, gene function, and genetic variation in biological samples, and to identify novel drug targets.

The process of screening large numbers of compounds against potential disease targets is characterized by a collection of technologies that strive to increase biological assay efficiency through the application of miniaturized screening formats and advanced liquid handling, signal detection, robotics, informatics, and a variety of other technologies.

Over the past several years, the industry has witnessed an evolution in screening capabilities, resulting in the ability of a user to screen more than , compounds per day for potential biological activity. Evaluating upward of 1 million compounds for biological or various other properties in a screening campaign is now commonplace in the pharmaceutical industry. Effective HTS relies on robust assays that can detect and then translate biological or other activities into a format that can be readily interpreted.

A wide variety of assays are currently in use, including:. NMR assays, which involve identifying small molecule ligands for macromolecular receptor targets;. DNA microarrays high density arrangements of double-stranded DNA clones cDNA or oligonucleotides that serve as identical or complementary probes, respectively, for specific genes, transcripts, or genome sequences ; and.

Other types of microarrays, including high-density arrangements of antibodies, nucleic acid or peptide aptamers, antigens protein or lipid , MHC 53 -peptide antigen complexes, and intact cells. Future advances in HTS—such as the development of one-step assays and increased miniaturization—will continue to increase the throughput and reduce the cost of HTS assays and may eventually allow the simultaneous monitoring of multiple endpoints e. An analysis of the current HTS technology landscape reveals the following as potential opportunities and future directions:. In short, HTS assays and technologies will permeate new sectors in the life sciences, affecting the productivity and speed of advances and discoveries in these varied sectors.

The cost effectiveness of HTS assays and technologies will improve, such that tasks previously believed to be impractical will become quite tractable. Coupled with methods to generate enhanced sequence and structural diversity beyond that seen in nature, these assays and technologies will permit the identification and selection of novel molecules with important biological functions, with ramifications for all of the life sciences.

There are other technologies, besides those described in the previous category of technologies, that seek to generate new kinds of genetic or molecular diversity. The methods described above, wherein a large library of diverse chemical compounds are screened using HTS methods to identify a smaller number of potential lead compounds with desired activities, are gradually being enhanced by less empirical approaches that are based on a greater understanding of biological systems i.

Such structural knowledge has grown rapidly over the past decade due to advances in x-ray crystallography, NMR technologies, and associated computational techniques that now allow for rapid determination of the structure of even large proteins or nucleic acid molecules at atomic-level resolution. A quick survey of the Protein Data Bank PDB , 54 the global resource for all publicly available biological macromolecular structures, reveals that the number of structures deposited on an annual basis witnessed nearly a fold increase between 3, and 28, ; see Figure With such structural knowledge of targets in hand, chemists can rationally pursue the design of novel chemical compounds that either bind to selected sites on the surface of these target molecules or mimic the structure of the target molecule and thereby compete for the binding to a receptor molecule.

Large macromolecular complexes in the protein data bank: A status report. Structure 13 3 , with permission from Elsevier. An excellent example of technological convergence exists with the field of in silico , or virtual, screening. This methodology capitalizes on the advances described above with respect to the determination of structures for target molecules as well as advances in computer hardware and specialized chemical informatics algorithms, so-called docking and scoring programs.

Many thousands of virtual compounds can be rapidly and effectively assessed for potential target molecule complementarity, 55 as a prerequisite for biological activity, prior to any actual chemistry being carried out or biological assays being performed.

The product of this computational effort is thus a rationally designed molecule that, once synthesized, can potentially serve as a lead compound in the drug discovery process. Although rational drug design has received a great deal of attention from the pharmaceutical industry and is recognized as having great potential for the future, most efforts today by the drug discovery industry reflect a combination of structure-aided rational design of compounds and the HTS screening of libraries of diverse compounds.

Thus, the use of structure, when known for a given molecular target, may come into play once a lead compound has been identified through an HTS process and efforts are made to optimize this lead and improve the biological activity or pharmacological properties of the compound. The field today is such that absence of knowledge of the structure of a targeted molecule is viewed as a critical impediment to the development of a new drug. In contrast to the rational design of small-molecule therapeutics, the rational design of therapeutic nucleic-acid-based compounds is much easier in that such compounds are synthesized to be complementary to the targeted nucleic acid sequence.

While nucleic acid therapeutics based on antisense oligonucleotides or ribozymes, enzymatically-active RNAs that cleave specific RNA target sequences, have been pursued for over a decade, their promise has not yet been realized due to difficulties in delivering stable compounds to desired sites. Significant advances are now occurring, however, in providing desired pharmacological properties to siRNA-based compounds and morpholino antisense oligonucleotides.

As the structure of greater numbers of potential target molecules are identified in the future and as both in silico screening and chemical synthesis methods continue to advance, it seems clear that a greater reliance. Greater application of rational, structure-based design approaches is likely to speed the discovery process significantly. While there are dual-use implications for such technologies, as there are for almost any advancing life sciences technology, the infrastructure required to pursue such structure-based design of novel biologically active compounds is likely to limit its use to the legitimate pharmaceutical industry for a number of years.

It should be noted, however, that like the nucleotide sequence databases that are open to the public, rapidly growing numbers of protein structures are being placed in the public domain.

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This trend is likely to continue and even accelerate, and as the computer hardware and software requirements for viewing and interpreting such structures becomes increasingly simple, these approaches will become increasingly accessible to scientists outside the pharmaceutical industry. The fledgling 5-year-old-field of synthetic biology—which is attracting engineers and biologists in equal measure—means different things to different researchers.

Engineers view it primarily as a way to fabricate useful microbes to do what no current technology can do i. Biologists see it as a powerful new way to learn about underlying principles of cellular function. Unlike systems biologists see description later in this chapter , who adopt a big-picture approach to biology by analyzing troves of data on the simultaneous activity of thousands of genes and proteins, synthetic biologists reduce the very same systems to their simplest components.

They create models of genetic circuits, build the circuits, see if they work, and adjust them if they do not, learning underlying principles of biology in the process. Because the molecular nature of many cellular reactions is only partially understood, most synthetic genetic circuits require considerable further empirical refinement after the initial computational work. Some scientists use DNA shuffling to streamline the empirical process. After inserting mutated DNA circuits into cells and selecting for those cells and the circuits therein that performed the best, researchers can evolve an effective product in just a couple of generations.

One of the goals of the field is to transform bacteria into tiny programmable computers. Like electronic computers, the live bacterial circuits would use both analog and digital logic circuits to perform simple computations. For example, researchers are working to develop modular units, such as sensors and actuators, input and output devices, genetic circuits to control cells, and a microbial chassis in which to assemble these pieces. Rather, the beauty of synthetic biology lies in what living cells can do.

If the markers are present, the nanoparticle sends out a therapeutic short nucleic acid that can affect the level of gene expression. Synthetic biology technology has many potential applications, including designing bacteria that can detect chemical or biological agent signatures, engineering bacteria that can clean up environmental pollutants, and engineering organisms or compounds that can diagnose disease or fix faulty genes. Although initial efforts are focused on microbial cells, some synthetic biologists imagine a day when they will be able to pro-.

Many of the same issues are raised by the genetic engineering of viruses. As described above, the development of recombinant DNA technology and the ability to manipulate DNA sequences in bacterial species such as E. Placing the DNA inserted under appropriate transcriptional controls, and the protein encoded by it under appropriate translational control, allows that gene to direct the expression of almost any kind of protein: a fluorescent marker as in the GloFish described in Chapter 1 , an enzyme that might function as a reporter, an antibiotic resistance marker, or even a toxin.

Using very similar techniques, genes of interest subject to size constraints can be introduced into the genomes of many different types of DNA viruses, ranging from adenoviruses to herpesviruses. Such capabilities raise obvious and compelling dual-use concerns. The introduction of heterologous gene sequences into the genomes of RNA viruses, or other types of modifications to the RNA genomes of these viruses, presents a special set of technical difficulties due to the fact that the genetic material is RNA, which is less stable than DNA and not as amenable to the genetic splicing techniques that have made recombinant DNA technology as versatile.

However, this has been accomplished for a growing number of different types of RNA viruses. Moreover, given the small size of these RNA genomes, it has proven possible to synthesize completely de novo all the genetic material needed to recover fully infectious virus particles with near wild-type infectivity, virulence and replication potential. RNA viruses come in several types, depending on the number of strands of RNA in each molecule of their genome i.

It has been known for many years that genomic RNA isolated from positive-strand RNA viruses, such as poliovirus, is intrinsically infectious. When transfected i. To manipulate the viral RNA genome, scientists in the age of molecular biology have developed efficient enzymatic methods for creating complementary DNA cDNA copies of the viral genomic RNA using reverse transcriptase enzymes encoded by retroviruses. This can include the deletion of protein coding sequences, the creation of deletion or point mutations, or even the introduction of completely novel protein-coding sequences.

The modified cDNA can then be placed downstream of an appropriate promoter sequence for a DNA-dependent RNA polymerase and a novel, molecularly engineered viral RNA genome efficiently transcribed in an in vitro transcription reaction. The transcribed RNA can then be transfected back into a permissive cell and, if the introduced mutations are compatible with continued viability of the virus, will give rise to novel infectious viruses. First carried out in with poliovirus, 64 infectious cDNA clones have now been constructed for members of many positive-stranded RNA virus families, including brome mosaic virus, 65 yellow fever virus, 66 Sindbis virus, 67 citrus tristeza virus, 68 and equine arteritis virus.

On the other hand, fully infectious poliovirus, a member of the family Picornaviridae , has been recovered in a cell-free reaction carried out in vitro in an optimized cell extract system. In the past, coronaviruses, which have the largest genomes of all positive-strand RNA viruses around 30 kilobases long , were difficult to reverse engineer because of the sheer size and instability of their full-length cDNA clones in bacterial vectors.

Similarly, the reverse genetic engineering of negative-strand RNA viruses 73 has proven much more difficult, given the fact that the RNA genomes of these viruses do not function directly as messenger RNAs and thus do not give rise to infectious virus progeny following their introduction into permissive cells. These RNAs require the expression of certain viral proteins, in order to make positive-strand copies of the negative-stranded RNA genome and to initiate the replicative cycle. The technology to accomplish this was first developed for influenza A virus in the late s to early s.

Like the earlier efforts with positive-strand RNA viruses, these efforts not only have dramatically improved our understanding of how these viruses replicate, but have also created the means for genetically manipulating viral genomes in order to generate new viruses for use as live, attenuated vaccines or vectors. Initially, reverse engineering of the influenza virus required the use of helper viruses, which provided proteins and RNA segments that the reconstituted in vitro RNPs i.

Later, alternative methods for introducing influenza RNPs into cells were developed, including entirely plasmid-driven rescue that did not require the involvement of a helper virus. By at least one laboratory had generated a pathogenic H5N1 virus using reverse engineering. Most recently, as mentioned in Chapter 1 , reverse engineering has been used to produce infectious influenza A viruses containing the viral. Scientists demonstrated that the HA of the virus confers enhanced pathogenicity in mice to recent human viruses that are otherwise nonpathogenic in their murine host. HA is a major surface protein that stimulates the production of neutralizing antibodies in the host, and changes in the genome segment that encodes it may render the virus resistant to preexisting neutralizing antibodies, thus increasing the potential for epidemics or pandemics of disease.

Moreover, the reverse engineered viruses expressing viral HA elicited hallmark symptoms of the illness produced during the original pandemic. With the complete genetic sequencing of the H1N1 influenza A virus, referred to in Chapter 1 , some have questioned whether these studies should have been published 90 in the open literature given concerns that terrorists could, in theory, use the information to reconstruct the flu virus.

Reverse engineering of the causative agent of SARS illustrates the many potential beneficial applications of the technology. In addition to opening up new opportunities for exploring the complexity of the SARS-coronavirus genome, the availability of a full-length cDNA provides a genetic template for manipulating the genome in ways that will allow for rapid and rational development and testing of candidate vaccines and therapeutics.

The influenza A reverse genetic engineering system serves as an excellent example of the potential for this technology to be used with the intent to do harm. As summarized in a article on the potential use of influenza virus as an agent for bioterrorism, with respect to advances that allowed for helper virus free production of a pathogenic H5N1 virus, virologist Robert M.

Krug University of Texas, Austin has written:. There is every reason to believe that the same recombinant DNA techniques can be used to render this H5N1 virus transmissible from humans to humans. Furthermore, it should be possible to introduce mutations into such a recombinant virus so that it is resistant to currently available influenza virus antivirals M2 inhibitors: amantadine and rimantadine; and NA inhibitors: zanamivir and oseltamivir , and so that it possesses an HA antigenic site that is unlike those in recently circulating human viruses.

In fact, several viruses with different HA antigenic sites could be generated. The human population would lack immunological protection against such viruses, existing antiviral drugs would not afford any protection, and these viruses could be spread simply by release of an aerosol spray in several crowded areas. A more holistic understanding of complex biological systems e. Critical components can then serve as targets for therapeutic and preventive intervention or manipulation; they can also serve as targets for malevolent manipulation and as the basis for novel kinds of biological attack.

Examples of the tools that could be used to manipulate complex biological systems include gene silencing, novel binding reagents e. In many ways this category of technologies opens up entirely novel aspects of the future biodefense and biothreat agent landscapes and changes the fundamental paradigm for future discussions on this topic. The phenomenon is now known as RNA interference, and is recognized to be a common antiviral defense mechanism in plants and a common phenomenon in many other organisms, including mammals.

This field is exploding with new discoveries almost daily concerning the role of miRNAs in regulating gene expression during development and after. The interaction of endogenous miRNAs with cellular mRNAs encoding specific proteins leads to suppression of protein expression, either by impairing the stability of the mRNA or by suppressing its translation into protein. The fact that small, largely double-stranded RNAs of this type, about 21 nucleotides in length, could play such an apparently broad and fundamental role in development and in the control of cellular homeostasis was not at all appreciated just a few years ago and highlights the sudden, unpredictable paradigm shifts and sharp turns in the way scientists think that are possible in the advance of the life sciences Figure The basic molecular mechanism of RNAi is as follows.

They are capable of similarly silencing gene expression but can also direct post-transcriptional silencing by blocking translation of a targeted host mRNA. RNAi is highly specific and remarkably potent only a few dsRNA molecules per cell are required for effective interference , and the interfering activity can occur in cells and tissues far removed from the site of introduction. The technology is expected to prove particularly valuable in cases where the targeted RNA encodes genes and protein products inaccessible to conventional drugs i.

However, clinical delivery poses a significant challenge, as does the likelihood of undesirable silencing of nontargeted genes. In , a German research team announced the successful lentivirus vector. Substantial progress is being made toward this aim, however, using liposome and lipid nanoparticle formulations of chemically modified, and hence stabilized, siRNAs. Scientists at Sirna, a small biotech company working for well over a decade on nucleic-acid-based therapies, have recently described a 1,fold reduction in the amount of hepatitis B virus present in the blood of mice replicating this virus in the liver, following a series of three separate intravenous inoculations of a lipid nanoparticle formulated, chemically modified, siRNA.

In November , researchers from Alnylam Pharmaceuticals used chemically modified siRNAs to silence genes encoding Apolipoprotein B ApoB in mice, resulting in decreased plasma levels of ApoB protein and reduced total cholesterol. Importantly, the delivery did not inadvertently impact nontargeted genes. Still, there are questions about the specificity of the siRNA, given that the investigators did not evaluate all proteins and given that they collected measurements over a relatively short period of time.

Observations that RNAi works in vivo in mammals has not only created opportunities for the development of new therapeutic tools but also spawned a new generation of genetic research in mammals. One could temporarily switch off a tumor suppressor gene suspected of providing genome protection e. It is reasonable to expect significant additional advances in the formulation of siRNAs for use as pharmacological agents, particularly with contributions from the field of nanotechnology.

As with so many of the technologies outlined in this chapter, just as RNAi promises new therapeutic options for cancer and other diseases, it could also be used to manipulate gene expression with the intent to do harm. Aptamers are short, single-stranded nucleic acid or peptidic ligands that fold into well-defined three-dimensional shapes, allowing them to inhibit or modulate their protein targets with high affinity and specificity. Since their discovery in the early s, aptamers have been used in target validation, detection reagents, and functional proteomic tools.

One of the first aptamers tested in an animal model was an antithrombin agent that blocks the proteolytic activity of thrombin, a protein involved in thrombosis blood clot formation in a blood vessel. Cambridge, MA and Nuvelo, Inc. New York, NY is testing Macugen, an aptamer that targets VEGF vascular endothelial growth factor as a treatment for age-related macular degeneration and diabetic macular edema.

The head has an affinity for a specific target molecule; the tail, which contains a region for PCR. Their sensitivity, dynamic range, and, in the case of tadpoles, precise quantification make these high-affinity binding molecules potentially very useful tools for disease diagnosis and environmental detection, including pathogen and other biological agent detection in the event of a naturally occurring or deliberate biological attack.

Despite their promise as therapeutic agents, aptamers are very expensive to synthesize and are still a largely unknown entity with respect to administration, formulation, adverse effects, etc. So although several compounds have entered clinical trial, their future as biopharmaceuticals is unclear.

Life scientists have exploited computing for many years in some form or another. But what is different today—and will be increasingly so in the future—is that the knowledge of computing and mathematical theory needed to address many of the most challenging biological problems can no longer be easily acquired but requires instead a fusion of the disciplines of biology, computation, and informatics.

A National Research Council NRC report entitled Catalyzing Inquiry at the Interface of Computing and Biology December has pointed out that the kinds and levels of expertise needed to address the most challenging problems of contemporary biology stretch the current state of knowledge of the field. The report identifies four distinct but interrelated roles of computing for biology:. Computational tools are artifacts—usually implemented as software but sometimes hardware—that enable biologists to solve very specific and precisely defined problems.

Such biologically oriented tools acquire, store, manage, query, and analyze biological data in a myriad of forms and in enormous volume for its complexity. These tools allow bi-. Computational models are abstractions of biological phenomena implemented as artifacts that can be used to test insight, to make quantitative predictions, and to help interpret experimental data. These models enable biological scientists to understand many types of biological data in context, and even at very large volumes, and to make model-based predictions that can then be tested empirically.

Such models allow biological scientists to tackle harder problems that could not readily be posed without visualization, rich databases, and new methods for making quantitative predictions. Biological modeling itself has become possible because data are available in unprecedented richness and because computing itself has matured enough to support the analysis of such complexity. A computational perspective or metaphor on biology applies the intellectual constructs of computer science and information technology as ways of coming to grips with the complexity of biological phenomena that can be regarded as performing information processing in different ways.

This perspective is a source for information and computing abstractions that can be used to interpret and understand biological mechanisms and function. Because both computing and biology are concerned with function, information and computing abstractions can provide well-understood constructs that can be used to characterize the biological function of interest. Further, they may well provide an alternative and more appropriate language and set of abstractions for representing biological interactions, describing biological phenomena, or conceptualizing some characteristics of biological systems.

Cyberinfrastructure and data acquisition are enabling support technologies for 21st century biology. Cyberinfrastructure—high-end general-purpose computing centers that provide supercomputing capabilities to the community at large; well-curated data repositories that store and make available to all researchers large volumes and many types of biological data; digital libraries that contain the intellectual legacy of biological researchers and provide mechanisms for sharing, annotating, reviewing, and disseminating knowledge in a collaborative context; and high-speed networks that connect geographically distributed computing resources—will become an enabling mechanism for large-scale, data-intensive biological research that is distributed over multiple laboratories and investigators around the world.

New data acquisition technologies such as genomic sequencers will enable researchers to obtain larger amounts of data of different types and at different scales, and advances in informa-. A new level of sophistication in computing and informatics is required for interpretation of much of the data generated today in the life sciences. These data are highly heterogenous in content and format, multimodal in collection, multidimensional, multidisciplinary in creation and analysis, multiscale in organization, and international in collaborations, sharing, and relevance. These data may well be of very high dimension, since data points that might be associated with the behavior of an individual unit must be collected for thousands or tens of thousands of comparable units.

The size and complexity of the data sets being generated require novel methods of analysis, which are being provided by computational biologists. For example, scientists at the U. The application of this technology means that large-scale problems—such as the analysis of an organism—can be solved in minutes rather than weeks. The NRC report notes that these data are windows into structures of immense complexity.

Biological entities and systems consisting of multiple entities are sufficiently complex that it may well be impossible for any human being to keep all of the essential elements in his or her head at once. Thus, advances in computational biology will be driven by the need to understand how complex biological systems operate and are controlled and will contribute fundamentally to the development of a systems view in biology.

In some ways, computing and information will have a relationship to the language of 21st century biology that is similar to the. Computing itself can provide biologists with an alternative and possibly more appropriate language and sets of intellectual abstractions for creating models and data representations of higher-order interactions, describing biological phenomena, and conceptualizing some characteristics of biological systems. Systems biology—also known as integrative biology—uses high-throughput, genome-wide tools e.

It is, in a sense, classical physiology taken to a new level of complexity and detail. A systems biologist seeks to quantify all of the molecular elements that make up a biological system and then integrate that information into graphical network models that can serve as predictive hypotheses. A growing number of researchers in the life sciences community are recognizing the usefulness of systems biology tools for analyzing complex regulatory networks both inside the cell, and the regulatory networks that integrate and control the functions of distinctly different cell types in multicellular organisms like humans and for making sense of the vast genomic and proteomic data sets that are so rapidly accumulating.

Systems biology is being seen as a valuable addition to the drug discovery toolbox. This field is rapidly evolving, with the computational tools still in an immature state and inadequate for handling the reams of data derived from microarray assays and their functional correlates.

Unconventional means of recording experimental results and conveying them rapidly to others in the field using an Internet-based approach are being pursued in an effort to manage the scale of data collection and analysis required for this effort. They are coming to realize that many novel molecular mechanisms are involved in controlling these signaling pathways, not only phosphorylation and kinase activation as classically recognized in signal transduction but also specific protein conformational changes, the translocation of proteins to different cellular compartments, proteolytic cleavage of signaling partners and latent transcription factors, and the binding and release of modulatory proteins from key signaling intermediates.

A similar multiplicity of mechanisms exists within the extracellular regulatory networks, that must ultimately take their cues from intracellular events.