Bioconvergence: Progenitor of the Nanotechnology Age

March 8, 2001 by Charles Ostman, Senior Fellow, Institute for Global Futures
Original link:  http://www.kurzweilai.net/bioconvergence-progenitor-of-the-nanotechnology-age

Advances in genetic engineering, advanced computational processes, nanobiology, and biological metaphors in computing are leading to a “bioconvergence” that will reshape the economies of the world and perhaps even the very definition of life itself.

Updates in molecular genetics, biomolecular and physiological modeling software, advanced genome cloning and synthesis technologies, and developments in synthetic tissue and organs, bioinformatics and related computing, IT resources, and an ever more diverse range of interrelated technologies are forging the progenitors of an ultimate example of convergence as a process, as a business and economic model, and as a socioeconomic paradigm of a transglobal, unparalleled, and absolutely irreversible transformative nature.

At stake, the biological engineering and bio-economy future of the entire planet.
As defined in Webster’s New Universal Unabridged Dictionary, convergence is “1) the act, fact, or condition of converging, 2) in biology, the formation of similarities in unrelated organisms living in the same environment.”

Convergence, a word which has become ubiquitous throughout the telecommunications, electronic media, internet, and IT (Information Technology) industries, is perhaps one of the most frequently used, but perhaps, misdirected terms of the modern era.

Near-term Major Outcome “Marker Points”

Global economic indices of valuation, by which the major sovereign nation states and trading cartel entities–which have been correlated with primary commodity assets such as energy, telecommunications, IT (information technology) resources and infrastructure–are in a stage of transition, toward the next global standard of valuation.

Ultimately, entirely new classes of synthetically contrived organisms, which would not evolve under “natural” circumstances, can be conjured up as protein-sequence codes, mapped onto a chip, and cloned out on demand.

Enter the era of artificially enhanced evolution, synthetic organisms, genetically derived and targeted pharmacopia, cellular cybernetics, intracellular “corrective chemistry” systems, and bioengineering on demand, as a commodity resource.

Seminal Marker Points–An Evolutionary Eventstream

Now, at the edge of the next millennium, quasi-viral components do indeed exist, in the form of modified viral hybrid “entities” designed to precisely target cell types based on their external protein signature. This is an extraordinary technology, not the least of the applications being the potential ability to genetically target cells, such as cancer cells, in order to arrest their growth. Another application is to deliver proteomic compounds to cellular components within the nucleus of a living cell (such as ribosomes or mitochondria) as a method for treating, or rather, “correcting” the pathogenic affects of disease and biological exposure events or to kill the cell.

This technology exists today, as a patented process developed by Onyx pharmaceutical (Richmond, CA), and has been engaged in a development program with Lawrence Livermore Lab.

Onyx is not alone in such pursuits, however. Just over a year ago, at the Molecular Nanotechnology – Biological Applications and Novel Approaches (San Diego) conference, I met with Dr. Stephen Lee, the director of the nanobiological molecular systems group from Monsanto, who was chairing the conference. The Monsanto approach, to specifically target cell types via their external protein signature, is to utilize spherical “assemblies” of a type of pseudo-protein like molecular material, referred to as dendrimers, to facilitate this process.

Unlike the quasi-viral component approach, in which these “molecular devices” are self replicating, the Monsanto-developed dendrimer molecular devices are static, inert. Both approaches have their advantages and shortcomings, but the core concept is the same: target a specific cell type, and only that cell type, enter the cell via enzymic action, enter the cell nucleus, and instigate some form of molecular chemistry activity.

The Emergent Nanotechnology Age–Fundamental Considerations

Previous, recent “ages” of technology and economic development, with substantial and irreversible social and cultural influences, such as the “Computing Age” (subsequently evolving into the “Information Age,” driven by the combination of the internet, and ubiquitously distributed computing capacity), are only the minimal progenitors of what is about to emerge, “the Nanotechnology Age,” the first stage progenitor of which is the phenomenon of bioconvergence.

What is about to transpire is the rapid evolution into an era where health care, the very definition of “medicine,” or for that matter, even life itself as it is currently understood to be, is in a state of transition. This phenomenon is directly in parallel with extraordinary changes in agricultural processes, bio-resource management, and ultimately, the de facto equivalent of bioengineering entire ecosystems.

The stakes are enormous. The actual scale of economic implications rivals any “industrial revolution” of previous eras and the outcome is likely to affect virtually every sovereign nation state, geographical region, and their associated population bases, whether or not they are direct participants in this transitional process.

The closest analogy, in terms of geopolitical and economic systems influence, might be appropriately compared to the conceptual model of “petrodollars,” as in the global petroleum resource base functioning as an implied currency reference.

It may become the case, at some point in the not too distant future, that “biotech-dollars,” as a metaphorical reference of valuation, will begin to drive the major economies of the world, and influence geopolitical and social policy imperatives.

Randy Scott, founder of Incyte Inc., proclaimed at the recent “Seizing Opportunities in Emerging BioChips Technologies” conference (March 19 – 20, 1998, San Francisco) that “protein is software.” This was no idle statement, though the significance of what was implied may have only been apparent to the select audience in attendance at that time.

Barely a year later, by every standard of measure that may be effectively used to analyze such phenomena, an inescapable truth is indeed emerging: an extraordinary revolution is at hand, driven by the urge of necessity, and spectacular economic opportunity potential.

The “history of the future” is already unfolding and the primary elements of this evolutionary eventstream that are poised to reshape the economies of the world, and perhaps even the very definition of life itself, are currently at hand.

Five Primary Vectors of Bioconvergence

1) Human Genome Mapping: Genopharmacopia, Recombinant Proteomics

2) Nanobiology as an Applied Technology

3) Bioengineering of Crops, Livestock, and Ecological Systems

4) Cross Convergence of Microscale Fabrication Technologies, and Biological Materials, Advanced Computing Processes (IT, bioinfomatics, AI, Alife), and telecommunications infrastructure

5) Emergent Economic Ecology of Process-Based Intellectual Property Resource Development and Deployment: Virtual Commodity Asset Valuation

Particularly in the arenas of immunoassay, DNA diagnostics and genetic sequencing applications, the ability to automate high throughput laboratory procedures, which previously were extremely time consuming, labor intensive, and less accurate, has immediate, extraordinarily lucrative implications in a host of pharmaceutical and biomedical applications.

Healthcare is shifting toward an arena of applied “human genetic mapping,” providing preventive medical strategies, patient-specific therapies, the genetic targeting of disease and pathologies.

Agriculture is shifting ever more toward an arena of bioengineered plants, animals, and entire multi-functional “contained ecologies.” These key phenomena are already taking place, and the world’s major economic systems practitioners, industry analysts, and political policy makers are beginning to orient themselves to the emergent “biotechnology epicenter” driven global economy.

The Emergent Convergence Syndrome

My primary focus has been (and continues to be) on providing access to realms of technology development and emergent economic phenomena, which are evolving into an “operational ecology” from which are being spawned a series of societal and cultural transformations, incomparable in scale, complexity, and velocity, to any previous eras of known human history.

Knowledge itself is even being compressed into shorter useful lifetime cycle windows. Knowledge velocity, complexity, and scale are surpassing human decision rendering capacity, particularly under duress in ever diminishing timescales. We are entering into a realm where mission-critical decision rendering exceeds human decision-rendering capacity in this operational ecology.

Virtual Commodity Assets

There is currently an emergent “virtual commodity asset” based economic ecology, in which the primary indices of valuation are transitioning toward the brokering of processes, and the inception of ubiquitous computing and telecommunication infrastructures, as an emergent “operational ecology,” populated with artificial life, genetic and evolutionary algorithms, hierarchical autonomous agent “colonies” and societal systems.

Biological and non-biological nanotechnology, and its myriad variant applications already in advanced stages of development in many cases, are the material artifacts of this operational ecology.

Nanotechnology is not a singular niche technology or arena of potential commercial interest. It is a concept, a transformative threshold that the human species is about to encounter on a truly evolutionary scale. Incremental marker points of human development have been recorded throughout the span of recorded history, as reference coordinates by which the scale, complexity, and velocity of such evolutionary development can be measured.

Compression is now occurring, however, in both temporal and functional domains. The incremental partitioning of major transitional thresholds which may have at one point been measured in terms of millennia, then centuries, and more recently, in decades, is now compressing down time spans of a few years, and perhaps in the near term, increments of months and weeks.

Proportional with an acceleration of temporal compression is an acceleration of functional complexity, or what I refer to here as the “convergence syndrome.” As a process, events, technologies, belief systems, cultural and societal paradigms, even the very definitions of life itself, are becoming ever more interconnected and interdependent on a global scale. In this newly emerging domain, nothing is isolated or autonomous.

As vector coordinates on an enormous existence matrix, in which all forms of life “here” (as it is currently interpreted to be), and in parallel domains, any perturbations within this matrix cause a wave front to be propagated throughout this matrix, eventually affecting all of the other nodes embedded within.

All activities and process dynamics have effects and counter effects, just as can be witnessed in the most fundamental rules of physics in the observable universe, but these now being translated upon the populations of the planet, and indeed, the planet itself.

The interstitial graticule spacing of this existence matrix, or what might be referred to here as mesh granularity, is compressing as well, in direct proportion with the temporal compression and functional complexity factors. Indeed, this proportional increase in mesh granularity of the existence matrix can be visualized as an topological index of trend status and plotted as such, as an artifact of this process.

The acceleration vectors indicated by this composite of interacting dynamic factors in this existence matrix may be in a state of flux as to the precise rate of increase inherent in these indicators, but the trend topologies to be recognized in this matrix, and their associated rates of acceleration, do tend to suggest a culmination into a vertical vector, a singularity “convergence point” threshold boundary.

At this point, the critical mass of existence as it is currently understood will be extruded through a series of evolutionary “test” increments, each one of which representing an increase of amplitude in functional complexity, and a compression in temporal partitioning, greater than the increment preceding it.

The outcome of this rapid succession of test increments, threshold boundaries to be encountered and negotiated, will determine whether we continue to the next great increment of evolutionary process, as an experiment on this particular world at this particular moment in time, or simply go into failure mode, perhaps to re-evolve to some new life form entity countless millennia from now.

In terms of galactic, and indeed universal scale, this is not unusual at all, or even particularly significant. We are but a speck of life, very much like a bit of plankton adrift in the sea of the universe. Other worlds and their respective life forms and ecosystems have evolved to levels of incremental development far beyond what can be currently witnessed here, and many others have no doubt lapsed into complete failure mode in far more relatively primitive stages of development.

What is significant, however, is that from the perspective of being here on this world, at this moment, is that never before in the known history of this world and its current inhabitants have the threshold of transition by which the very future of this current world are about to be determined and measured within the reach of its current inhabitants.

Current processes by which the current life support capacity of the biosphere may be suppressed into eventual system level failure mode:

1) Predatory manufacturing and industrial processes

2) Acceleration in consumption of non-renewable resources

3) Irreversible alterations to ecosystems, soil, oceans, atmosphere

4) Increased dispensation of hazardous materials, pathogens, mutagens

5) Situational dysfunction of societies, socio-economic systems and substrates

6) Hard asset-based commodity systems decaying into irrecoverable debt vorticesResources and processes currently existing, or in various stages of development: 1) “Manufactured” synthetic life forms, pseudomorphs, quasi-organic entities. 2) Materialization of “virtual assets” via applied nanotechnology. 3) Cybernetic and genetic modification of the human body. 4) Synthetic sentience as a strategic resource. 5) Infinitely scalable computational resource

7) Mind/machine interface

8) Human/internet symbiosis
9) Dissolution of the geographically defined autonomous nation state

10) Virtual asset based commodity systems

11) Knowledge conveyance as an interactive experiential process

Computers are becoming functionality matrices, business entities cluster together and temporarily form into “strategic alliances,” physical systems are interconnected into ubiquitous function engines, product lifetime cycles are compressed into a continuum of “upgrade entities.”

This is only the beginning edge of an event horizon beyond which exists a realm populated with virtual asset-based commodity systems, work and life itself flourish in the virtual terraform, and manufacturing of physical goods is morphed into an engineered-materials singularity spawned from nanotechnology.

Seminal Marker Points of the Nanotechnology Evolutionary Evenstream

• Virtual synthetic organisms flourishing within synthetic environments, which in turn reside within the dynamic fabric of a self-modifying, self-organizing dendritic connectivity macrostructure on a planetary scale, referred to at this time as “The internet.”
• Molecular self-assembling subcomponents organizing as self-modifying organelle entities, which in turn become the functional pseudo-cellular components of self reassembling xenomorphic synthetic macro-organisms, become ubiquitous, and flourish on the physical terraform.
• Self organizing molecular substructures which are the core components for synthetic brain entities, which in turn become the physical components for enabling synthetic sentience rendering as a process, enmeshed into a functionality matrix of contiguous consciousness
• Molecular assembly as a programmable process yields the components for molecular computing components, which in turn are assembled into ultra-computing processor engines which are ubiquitously embedded into the global connectivity grid.
• Synthetic brain engines which themselves are nano-manufactured synthetic organism components are inter-connectable to the ubiquitous computing grid, which in turn develops synthetic sentience as a global scale macro entity.
• Tangible, hard asset-based commodity driven economic systems are supplanted by a virtual asset based economic ecology, in which valuation is measured not by ownership of things, but access to processes, of which synthetic sentience, and the intelligence stream for on-demand nano-assembly are the primary components.
• Virtual work space, which resides on the virtual terraform of the globally contiguous Internet connectivity grid, which is in turn an organic macrosystem enmeshed into a global scale human/Internet symbiosis.
• Virtual workspace evolves into virtual existence space as the dividing line between work and non-work merges into an artificially contrived existence continuum, the singular reward of participation which is access to the invocation of rapture as the ultimate “consumer” commodity.
• The reality matrix of life for the human inhabitants within the symbiotic connectivity grid tissue substrate is driven by a mind-machine interface link in which the perception of the real and the virtual become ubiquitously interchangable.

Operational Process Dynamics of the Nanotechnology Development Matrix

The fabric of this matrix, which is being woven into a contiguous mesh of synergistic co-dependency, is evolving into a realm in which independent, autonomous technologies, business entities, and socio-economic systems are being compressed into a functionality matrix singularity–a convergence.

Furthermore, the convergence itself consists of a fractal geometry of sub-convergencies of development processes, business entities, physical systems, computing, media content creation, knowledge conveyance, manufacturing, products and services.

Computers are becoming bi-directional process transaction nodes embedded into a ubiquitous fabric, business entities cluster together and temporarily form into “strategic alliances,” epicenters of value are defined into newly formed sovereign knowledge, physical systems are interconnected into functionality matrices, product lifetime cycles are compressed into a continuum of near real-time “upgrade entities.”

This is only the beginning edge of an event horizon beyond which exists a realm populated with virtual asset-based commodity systems, work and life itself flourish as a de facto symbiosis within the operational ecology of the virtual terraform, and manufacturing of physical goods is morphed into a JIT (just in time) engineered materials singularity spawned from applied nanotechnology.

The culmination of nanotechnology, nanobiology, biological metaphors in computing (including GP and EC), the evolution of the human-Internet symbiosis, and eventual involuntary co-evolution with distributed artificial intelligences and collective “physiological organelle” component systems, leading to the spawning of synthetic sentience as an operational requirement for our collective evolution . . . this is an emergent, transformative phenomenon which has already become manifest.

Adapted from NanoIndustries newsletter, July 2000

Related Links

Evolution into the Next Millennium

Nanobiology – Where nanotechnology and biology come together. Welcome to the new frontier of nanobiology

Charles Ostman Web site

Amyloid

From Wikipedia, the free encyclopedia

Micrograph showing amyloid deposits (pink) in small bowel. H&E stain.

Amyloids are aggregates of proteins that become folded into a shape that allows many copies of that protein to stick together forming fibrils. In the human body, amyloids have been linked to the development of various diseases. Pathogenic amyloids form when previously healthy proteins lose their normal physiological functions and form fibrous deposits in plaques around cells which can disrupt the healthy function of tissues and organs.

Such amyloids have been associated with (but not necessarily as the cause of) more than 50^[1] human diseases, known as amyloidosis, and may play a role in some neurodegenerative disorders.^[2] Some amyloid proteins are infectious; these are called prions in which the infectious form can act as a template to convert other non-infectious proteins into infectious form.^[3] Amyloids may also have normal biological functions; for example, in the formation of fimbriae in some genera of bacteria, transmission of epigenetic traits in fungi, as well as pigment deposition and hormone release in humans.^[4]

Amyloids have been known to arise from many different proteins and polypeptides.^[5] These polypeptide chains generally form β-sheet structures that aggregate into long fibers; however, identical polypeptides can fold into multiple distinct amyloid conformations. The diversity of the conformations may have led to different forms of the prion diseases.^[4]

Definition

The name amyloid comes from the early mistaken identification by Rudolf Virchow of the substance as starch (amylum in Latin, from Greek ἄμυλον amylon), based on crude iodine-staining techniques. For a period, the scientific community debated whether or not amyloid deposits are fatty deposits or carbohydrate deposits until it was finally found (in 1859) that they are, in fact, deposits of albumoid proteinaceous material.^[6]

Micrograph showing amyloid deposition in small bowel. Congo red stain.

• The classical, histopathological definition of amyloid is an extracellular, proteinaceous deposit exhibiting beta sheet structure. Common to most cross-beta-type structures, in general, they are identified by apple-green birefringence when stained with congo red and seen under polarized light. These deposits often recruit various sugars and other components such as Serum Amyloid P component, resulting in complex, and sometimes inhomogeneous structures.^[7] Recently this definition has come into question as some classic, amyloid species have been observed in distinctly intracellular locations.^[8]
• A more recent, biophysical definition is broader, including any polypeptide that polymerizes to form a cross-beta structure, in vivo or in vitro. Some of these, although demonstrably cross-beta sheet, do not show some classic histopathological characteristics such as the Congo-red birefringence. Microbiologists and biophysicists have largely adopted this definition,^[9][10] leading to some conflict in the biological community over an issue of language.

The remainder of this article will use the biophysical context.

Diseases featuring amyloids

Disease	Protein featured	Official abbreviation
Alzheimer's disease	Beta amyloid from Amyloid precursor protein[11][12][13][14]	Aβ, APP
Diabetes mellitus type 2	IAPP (Amylin)[15][16]	AIAPP
Parkinson's disease	Alpha-synuclein[12]	none
Transmissible spongiform encephalopathy (e.g. bovine spongiform encephalopathy)	PrPSc[17]	APrP
Fatal familial insomnia	PrPSc	APrP
Huntington's disease	Huntingtin[18][19]	none
Medullary carcinoma of the thyroid	Calcitonin[20]	ACal
Cardiac arrhythmias, isolated atrial amyloidosis	Atrial natriuretic factor	AANF
Atherosclerosis	Apolipoprotein AI	AApoA1
Rheumatoid arthritis	Serum amyloid A	AA
Aortic medial amyloid	Medin	AMed
Prolactinomas	Prolactin	APro
Familial amyloid polyneuropathy	Transthyretin	ATTR
Hereditary non-neuropathic systemic amyloidosis	Lysozyme	ALys
Dialysis related amyloidosis	Beta-2 microglobulin	Aβ2M
Finnish amyloidosis	Gelsolin	AGel
Lattice corneal dystrophy	Keratoepithelin	AKer
Cerebral amyloid angiopathy	Beta amyloid[21]	Aβ
Cerebral amyloid angiopathy (Icelandic type)	Cystatin	ACys
Systemic AL amyloidosis	Immunoglobulin light chain AL[20]	AL
Sporadic Inclusion body myositis	S-IBM	none

The International Society of Amyloidosis classifies amyloid fibrils based upon associated proteins.^[22]

Non-disease and functional amyloids

• Native amyloids in organisms^[23]
  • Curli fibrils produced by E. coli, Salmonella, and a few other members of the Enterobacteriales (Csg). The genetic elements (operons) encoding the curli system are phylogenetic widespread and can be found in at least four bacterial phyla.^[24] This suggest that many more bacteria may express curli fibrils.
  • Gas vesicles, the buoyancy organelles of aquatic archaea and eubacteria^[25]
  • Functional amyloids in Pseudomonas (Fap)^[26][27]
  • Chaplins from Streptomyces coelicolor
  • Podospora anserina prion het-s
  • Malarial coat protein
  • Spider silk (some but not all spiders)
  • Mammalian melanosomes (PMEL)
  • Tissue-type plasminogen activator (tPA), a hemodynamic factor
  • ApCPEB protein and its homologues with a glutamine-rich domain
  • Peptide/protein hormones stored as amyloids within endocrine secretory granules^[28]
  • Proteins and peptides engineered to make amyloid that display specific properties, such as ligands that target cell surface receptors^[29]
  • Several yeast prions are based on an infectious amyloid, e.g. [PSI+] (Sup35p); [URE3] (Ure2p); [PIN+] (Rnq1p); [SWI1+] (Swi1p) and [OCT8+] (Cyc8p)
  • Functional amyloids are abundant in most environmental biofilms according to staining with amyloid specific dyes and antibodies^[30]
  • Fungal cell adhesion proteins aggregate on the surface of the fungi to form cell surface amyloid regions with greatly increased binding strength ^[31][32]
  • The tubular sheaths encasing Methanosaeta thermophila filaments are the first functional amyloids to be reported from archeal domain of life ^[33]

Amyloid deposits occur in the pancreas of patients with diabetes mellitus, although it is not known if this is functionally important. The major component of pancreatic amyloid is a 37-amino acid residue peptide known as islet amyloid polypeptide or amylin. This is stored with insulin in secretory granules in B cells and is co secreted with insulin" (Rang and Dale's Pharmacology, 2015).

ATTR amyloid deposits from transthyretin occur not only in Transthyretin-related hereditary amyloidosis, but also in advanced cases of aging in many tissues, in many mammalian species. They are a common result in supercentenarian autopsies. A proposal is that they may mediate some tissue pathologies seen in advanced aging, and pose a limit to human life span.^[34]

Amyloid biophysics

Structure

Amyloids are formed of long unbranched fibers that are characterized by a cross-beta sheet quaternary structure in which antiparallel chains of β-stranded peptides are arranged in an orientation perpendicular to the axis of the fiber. Each individual fiber may be 5–15 nanometres in width and a few micrometres in length.^[4] While amyloid is usually identified using fluorescent dyes, stain polarimetry, circular dichroism, or FTIR (all indirect measurements), the "gold-standard" test to see whether a structure contains cross-β fibres is by placing a sample in an X-ray diffraction beam. The term "cross-β" was based on the observation of two sets of diffraction lines, one longitudinal and one transverse, that form a characteristic "cross" pattern.^[35] There are two characteristic scattering diffraction signals produced at 4.7 and 10 Ångstroms (0.47 nm and 1.0 nm), corresponding to the interstrand and stacking distances in beta sheets.^[36] The "stacks" of beta sheet are short and traverse the breadth of the amyloid fibril; the length of the amyloid fibril is built by aligned strands. The cross-beta pattern is considered a diagnostic hallmark of amyloid structure.^[4]

For a long time our knowledge of the atomic-level structure of amyloid fibrils was limited by the fact that they are unsuitable for the most traditional methods for studying protein structures. Recent years have seen progress in experimental methods that now enable direct data on the internal structure of different types of amyloid fibrils. Two prominent methods include the use of solid-state NMR spectroscopy and (cryo) electron microscopy. Combined, these methods have provided 3D atomic structures of amyloid fibrils formed by amyloid β peptides, α-synuclein, tau, and the FUS protein, associated with various neurodegenerative diseases.^[37][38]

X-ray diffraction studies of microcrystals revealed atomistic details of core region of amyloid.^[39][40] The crystallographic structures show that short stretches from amyloid-prone regions of amyloidogenic proteins run perpendicular to the filament axis, consistent with the "cross-β" feature of amyloid structure. They also reveal a number of characteristics of amyloid structures – neighboring β-sheets are tightly packed together via an interface devoid of water (therefore referred to as dry interface), with the opposing β-strands slightly offset from each other such that their side-chains interdigitate. This compact dehydrated interface created was termed a steric-zipper interface.^[4] There are eight theoretical classes of steric-zipper interfaces, dictated by the directionality of the β-sheets (parallel and anti-parallel) and symmetry between adjacent β-sheets.

A variety of tertiary structures have been observed in amyloid. The β-sheets may form a β-sandwich, or a β-solenoid which may be either β-helix or β-roll. Identical polypeptides can fold into multiple distinct amyloid conformations.^[4]

Formation

Amyloid is formed through the polymerization of hundreds to thousands of monomeric peptides into long fibers. In general, amyloid polymerization (aggregation or non-covalent polymerization) is sequence-sensitive, that is, causing mutations in the sequence can prevent self-assembly, especially if the mutation is a beta-sheet breaker, such as proline or non-coded alpha-aminoisobutyric acid.^[41] For example, humans produce amylin, an amyloidogenic peptide associated with type II diabetes, but in rats and mice prolines are substituted in critical locations and amyloidogenesis does not occur. Studies comparing synthetic to recombinant Amyloid beta 1-42 in assays measuring rate of fibrillation, fibril homogeneity, and cellular toxicity showed that recombinant Amyloid beta 1-42 has a faster fibrillation rate and greater toxicity than synthetic Amyloid beta 1-42 peptide.^[42] This observation combined with the irreproducibility of certain Amyloid beta 1-42 experimental studies has been suggested to be responsible for the lack of progress in Alzheimer's research.^[43] Consequently, there have been renewed efforts to manufacture Amyloid beta 1-42 and other amyloid peptides at unprecedented (>99%) purity.^[44]

There are multiple classes of amyloid-forming polypeptide sequences. Glutamine-rich polypeptides are important in the amyloidogenesis of Yeast and mammalian prions, as well as Trinucleotide repeat disorders including Huntington's disease. When glutamine-rich polypeptides are in a β-sheet conformation, glutamines can brace the structure by forming inter-strand hydrogen bonding between its amide carbonyls and nitrogens of both the backbone and side chains. The onset age for Huntington's disease shows an inverse correlation with the length of the polyglutamine sequence, with analogous findings in a C. elegans model system with engineered polyglutamine peptides.^[45]

Other polypeptides and proteins such as amylin and the Alzheimer's beta protein do not have a simple consensus sequence and are thought to operate by hydrophobic association.^{[citation needed]} Among the hydrophobic residues, aromatic amino-acids are found to have the highest amyloidogenic propensity.

For these peptides, cross-polymerization (fibrils of one polypeptide sequence causing other fibrils of another sequence to form) is observed in vitro and possibly in vivo.^{[citation needed]} This phenomenon is important, since it would explain interspecies prion propagation and differential rates of prion propagation, as well as a statistical link between Alzheimer's and type 2 diabetes.^[48] In general, the more similar the peptide sequence the more efficient cross-polymerization is, though entirely dissimilar sequences can cross-polymerize and highly similar sequences can even be "blockers" that prevent polymerization.^{[citation needed]} Polypeptides will not cross-polymerize their mirror-image counterparts, indicating that the phenomenon involves specific binding and recognition events.

The fast aggregation process, rapid conformational changes as well as solvent effects provide challenges in measuring monomeric and oligomeric amyloid peptide structures in solution. Theoretical and computational studies complement experiments and provide insights that are otherwise difficult to obtain using conventional experimental tools. Several groups have successfully studied the disordered structures of amyloid and reported random coil structures with specific structuring of monomeric and oligomeric amyloid as well as how genetics and oxidative stress impact the flexible structures of amyloid in solution.^[49]

Oligomeric intermediates of insulin during fibrillation (more toxic than other intermediates: native, protofibril, and fibril) decreased the surface tension of solution which indicated to detergent-like properties of oligomers and significant role of hydrophobic forces in cytotoxicity of oligomers.^[50]

Amyloid pathology

The reasons for amyloid association disease are unclear. In some cases, the deposits physically disrupt tissue architecture, suggesting disruption of function by some bulk process. An emerging consensus implicates prefibrillar intermediates rather than mature amyloid fibers in causing cell death.^[13][51]

Calcium dysregulation has been observed in cells exposed to amyloid oligomers. These small aggregates can form ion channels planar lipid bilayer membranes. Channel formation has been hypothesized to account for calcium dysregulation and mitochondrial dysfunction by allowing indiscriminate leakage of ions across cell membranes.^[52]

Studies have shown that amyloid deposition is associated with mitochondrial dysfunction and a resulting generation of reactive oxygen species (ROS), which can initiate a signalling pathway leading to apoptosis.^[53]

There are reports that indicate amyloid polymers (such as those of huntingtin, associated with Huntington's disease) can induce the polymerization of essential amyloidogenic proteins, which should be deleterious to cells. Also, interaction partners of these essential proteins can also be sequestered.^[54]

Histological staining

In the clinical setting, amyloid diseases are typically identified by a change in the fluorescence intensity of planar aromatic dyes such as thioflavin T, congo red or NIAD-4.^[55] In general, this is attributed to the environmental change, as these dyes intercalate between beta-strands to confine their structure.^[56] Congo Red positivity remains the gold standard for diagnosis of amyloidosis. In general, binding of Congo Red to amyloid plaques produces a typical apple-green birefringence when viewed under cross-polarized light. Recently, significant enhancement of fluorescence quantum yield of NIAD-4 was exploited to super-resolution fluorescence imaging of amyloid fibrils^[57] and oligomers.^[58] To avoid nonspecific staining, other histology stains, such as the hematoxylin and eosin stain, are used to quench the dyes' activity in other places such as the nucleus, where the dye might bind. Modern antibody technology and immunohistochemistry has made specific staining easier, but often this can cause trouble because epitopes can be concealed in the amyloid fold; in general, an amyloid protein structure is a different conformation from the one that the antibody recognizes.

Evolution of ageing

From Wikipedia, the free encyclopedia

Old man at a nursing home in Norway.

Enquiry into the evolution of ageing aims to explain why survival, reproductive success, and functioning of almost all living organisms decline at old age. Leading hypotheses suggest that a combination of limited resources, and an increasing risk of death by environmental causes determine an "optimal" level of self-maintenance, i.e. the repair of molecular and cellular level damage that accumulates over time. Allocation of limited resources into such damage repair is traded-off with investment into reproduction, which determines the individual's Darwinian fitness. In consequence, traits that improve an individual's performance in early life are favored by selection, even if the same traits have negative effects late in life, when the individual has already passed on their genes to the next generation.

History

August Weismann was responsible for interpreting and formalizing the mechanisms of Darwinian evolution in a modern theoretical framework. In 1889, he theorized that ageing was part of life's program because the old need to remove themselves from the theatre to make room for the next generation, sustaining the turnover that is necessary for evolution.^[3] This theory again has much intuitive appeal, but it suffers from having a teleological or goal-driven explanation. In other words, a purpose for ageing has been identified, but not a mechanism by which that purpose could be achieved. Ageing may have this advantage for the long-term health of the community; but that doesn't explain how individuals would acquire the genes that make them get old and die, or why individuals that had ageing genes would be more successful than other individuals lacking such genes. (In fact, there is every reason to think that the opposite is true: ageing decreases individual fitness.) Weismann later abandoned his theory.

Theories suggesting that deterioration and death due to ageing are a purposeful result of an organism's evolved design (such as Weismann's "programmed death" theory) are referred to as theories of programmed ageing or adaptive ageing. The idea that the ageing characteristic was selected (an adaptation) because of its deleterious effect was largely discounted for much of the 20th century, but a theoretical model suggests that altruistic ageing could evolve if there is little migration among populations.^[4]

Mutation accumulation

The first modern theory of mammal ageing was formulated by Peter Medawar in 1952. It formed from discussions in the previous decade with J. B. S. Haldane and the selection shadow concept. Their idea was that ageing was a matter of neglect. Nature is a highly competitive place, and almost all animals in nature die before they attain old age. Therefore, there is not much reason why the body should remain fit for the long haul – not much selection pressure for traits that would maintain viability past the time when most animals would be dead anyway, killed by predators, disease, or accident.^[5]

Medawar's theory is referred to as Mutation Accumulation. The mechanism of action involves random, detrimental germline mutations of a kind that happen to show their effect only late in life. Unlike most detrimental mutations, these would not be efficiently weeded out by natural selection. On the grand scale, senescence would just be the summation of deleterious genes that only present in older individuals.^[6] Hence they would 'accumulate' and, perhaps, cause all the decline and damage that we associate with ageing.^[7][8]

Modern genetics science has disclosed a possible problem with the mutation accumulation concept in that it is now known that genes are typically expressed in specific tissues at specific times (see regulation of gene expression). Expression is controlled by some genetic "program" that activates different genes at different times in the normal growth, development, and day-to-day life of the organism. Defects in genes cause problems (genetic diseases) when they are not properly expressed when required. A problem late in life suggests that the genetic program called for expression of a gene only in late life and the mutational defect prevented proper expression. This implies existence of a program that called for different gene expression at that point in life. Why, given Medawar's concept, would there exist genes only needed in late life or a program that called for different expression only in late life? The maintenance mechanism theory (discussed below) avoids this problem.

Medawar's concept suggested that the evolution process was affected by the age at which an organism was capable of reproducing. Characteristics that adversely affected an organism prior to that age would severely limit the organism's ability to propagate its characteristics and thus would be highly "selected against" by natural selection. Characteristics that caused the same adverse effects that only appeared well after that age would have relatively little effect on the organism's ability to propagate and therefore might be allowed by natural selection. This concept fits well with the observed multiplicity of mammal life spans (and differing ages of sexual maturity) and is important to all of the subsequent theories of ageing discussed below.

Antagonistic pleiotropy

Medawar's theory was further developed by George C. Williams in 1957, who noted that senescence may be causing many deaths,^{[citation needed]} even if animals are not 'dying of old age.' In the earliest stages of senescence, an animal may lose a bit of its speed, and then predators will seize it first, while younger animals flee successfully. Or its immune system may decline, and it becomes the first to die of a new infection. Nature is such a competitive place, said Williams, (turning Medawar's argument back at him), that even a little bit of senescence can be fatal; hence natural selection does indeed care; ageing isn't cost-free.

Williams's objection has turned out to be valid: Modern studies of demography in natural environments demonstrate that senescence does indeed make a substantial contribution to the death rate in nature. These observations cast doubt on Medawar's theory. Another problem with Medawar's theory became apparent in the late 1990s, when genomic analysis became widely available. It turns out that the genes that cause ageing are not random mutations; rather, these genes form tight-knit families that have been around as long as eukaryotic life. Baker's yeast, worms, fruit flies, and mice all share some of the same ageing genes.^[9]

Williams (1957) proposed his own theory, called antagonistic pleiotropy. Pleiotropy means one gene that has two or more effects on the phenotype. In antagonistic pleiotropy, one of these effects is beneficial and another is detrimental. In essence, this refers to genes that offer benefits early in life, but exact a cost later on. If evolution is a race to have the most offspring the fastest, then enhanced early fertility could be selected even if it came with a price tag that included decline and death later on.^[1] Because ageing was a side effect of necessary functions, Williams considered any alteration of the ageing process to be "impossible."

Antagonistic pleiotropy is a prevailing theory today, but this is largely by default, and not because the theory has been well verified. In fact, experimental biologists have looked for the genes that cause ageing, and since about 1990 the technology has been available to find them efficiently. Of the many ageing genes that have been reported, some seem to enhance fertility early in life, or to carry other benefits. But there are other ageing genes for which no such corresponding benefit has been identified. This is not what Williams predicted. This may be thought of as partial validation of the theory, but logically it cuts to the core premise: that genetic trade-offs are the root cause of ageing.

Another difficulty with antagonistic pleiotropy and other theories that suppose that ageing is an adverse side effect of some beneficial function is that the linkage between adverse and beneficial effects would need to be rigid in the sense that the evolution process would not be able to evolve a way to accomplish the benefit without incurring the adverse effect even over a very long time span. Such a rigid relationship has not been experimentally demonstrated and, in general, evolution is able to independently and individually adjust myriad organism characteristics.

In breeding experiments, Michael R. Rose selected fruit flies for long lifespan. Based on antagonistic pleiotropy, Rose expected that this would surely reduce their fertility. His team found that they were able to breed flies that lived more than twice as long as the flies they started with, but to their surprise, the long-lived, inbred flies actually laid more eggs than the short-lived flies. This was another setback for pleiotropy theory, though Rose maintains it may be an experimental artefact.^[10]

Disposable soma theory

A third mainstream theory of ageing, the ''Disposable soma theory, proposed in 1977 by Thomas Kirkwood, presumes that the body must budget the amount of energy available to it. The body uses food energy for metabolism, for reproduction, and for repair and maintenance. With a finite supply of food, the body must compromise, and do none of these things quite as well as it would like. It is the compromise in allocating energy to the repair function that causes the body gradually to deteriorate with age.^[11] A caveat to the disposable soma theory suggests that time, rather than energy, is a limiting resource that may be critical to an organism. The concept is that each organism must reproduce in an optimal period in order to ensure the greatest chance of success for the offspring. This optimal period is dictated by the ecological niche of the organism but in essence, it limits the time that any given organism can devote to growth and development prior to bearing offspring. Thus, developmental rate and gestational rate are subject to evolutionary pressure. The need to accelerate gestation limits the time allocated to damage repair at the cellular level, resulting in an accumulation of damage and a decreased lifespan relative to organisms with longer gestation. This concept stems from a comparative analysis of genomic stability in mammalian cells.^[12]

There are arguments against the disposable soma theory. The theory clearly predicts that a shortage of food should make the compromise more severe all around; but in many experiments, ongoing since 1930, it has been demonstrated that animals live longer when fed substantially less than controls. This is the caloric restriction (CR) effect,^[13][14][15] and it cannot be easily reconciled with the Disposable Soma theory. Though by decreasing energy expenditure the damage generated (by free radicals, for instance) is expected to be reduced and the total energy budget might indeed be reduced, but the investment in repair function might still be relatively the same. But dietary restriction has not been shown to increase lifetime reproductive success (fitness), because when food availability is lower, reproductive output is also lower. So CR does thus not completely dismiss disposable soma theory.

With respect to such limitations Kriete^[16] proposed consideration of systems-level properties like robustness to characterize ageing as a robustness tradeoff. According to this concept living systems evolve into a state of highly optimized tolerance promoting traits beneficial for survival and fitness at the cost of fragilities driving the ageing phenotype. The view is compatible with aspects of the antagonistic pleiotropy and the disposable soma theory, but offers additional mechanisms rooted in complex systems theory.

Other problems with the classical ageing theories

A raised criticism for all three mainstream theories based on classical evolutionary process concepts is the potential existence of 'deliberate' metabolic mechanisms that work to promote death.

One is apoptosis, or programmed cell death. Apoptosis is responsible for killing infected cells, cancerous cells, and cells that are simply in the wrong place during development. There are clear benefits to apoptosis, so the existence of apoptosis isn't a problem for evolutionary theory. The problem is that apoptosis seems to ramp up late in life and kill healthy cells, causing weakness and degeneration^{[citation needed]}. And, paradoxically, apoptosis has been observed as a kind of 'altruistic suicide' in colonies of yeast under stress.^[17] This seems to be a direct hint that senescence arose because it conferred a direct evolutionary advantage, rather than some kind of side effect of genes that have other evolutionary advantages (pleiotropy).

A second 'deliberate' mechanism is called replicative senescence or cellular senescence. Metaphorically, a cell may be said to 'count' (with its telomeres) the number of times that it has divided, and after a set number of replications, it languishes and dies. It has been proposed that this mechanism evolved to suppress cancer.^[18][19] Many invertebrates experience replicative senescence, though they never die of cancer.^{[citation needed]} Even one-celled organisms count replications, and will die if they don't replenish their telomeres with conjugation (sex).^[20]

More strictly, cells cannot 'count' the number of times they have divided^{[citation needed]}. Telomeres are not a counting mechanism^{[citation needed]}, though they may be used to indicate the number of times a particular chromosome has been replicated. Cellular processes for genetic material replication occur in both directions along DNA, 5' to 3' and on the other strand, 3' to 5'. As the 3' or 5' end is impossible for DNA polymerase to grab at the 1 base pair mark, a handful of basepairs (10-15) are cut off each replication. Over time, this cutting short of the DNA results in no telomeres, and the cell is unable to replicate that chromosome without cutting into genes.

The dilemma is that classical evolutionary theory says that what is maintained in a lineage is that which ensures the viability of an organism and its offspring. Ageing can only cut off an individual's capacity to reproduce. So, according to classical theory, ageing could only evolve as a side effect, or epiphenomenon of selection. The disposable soma theory and antagonistic pleiotropy theory are examples in which a compensating individual benefit, compatible with classical evolution theory (See neo-Darwinism) is proposed. Nevertheless, there is accumulated evidence that ageing looks like an adaptation in its own right, selected for its own sake.^[21][22]

Semelparous organisms and others that die suddenly following reproduction (e.g. salmon, octopus, marsupial mouse (brown antechinus), etc.) also represent instances of organisms who incorporate a lifespan-limiting feature. Sudden death is more obviously an instance of programmed death or a purposeful adaptation than gradual ageing. Biological elements clearly associated with evolved mechanisms such as hormone signalling have been identified in the death mechanisms of organisms such as the octopus.^[23]

Impact of new evolution concepts on ageing theories

At the time most of the non-programmed ageing theories were developed, there was very little scientific disagreement with classical theories (i.e. Neo-Darwinism) regarding the process of evolution. However, in addition to suicidal behaviour of semelparous species (not handled by the classical ageing theories) other apparently individually adverse organism characteristics such as altruism and sexual reproduction were observed. In response to these other conflicts, adjustments to classical theory were proposed:

• Various group selection theories (beginning in 1962) propose that benefit to a group could offset the individually adverse nature of a characteristic such as altruism. The same principle could be applied to characteristics that limited life span and theories proposing group benefits for limited lifespans appeared.
• Evolvability theories (beginning in 1995) suggest that a characteristic that increased an organism's ability to evolve could also offset an individual disadvantage and thus be evolved and retained. Multiple evolvability benefits of a limited lifespan were subsequently proposed in addition to those originally proposed by Weismann.

Ageing theories based on group selection

Group selection is often criticized to be too slow to happen in real biology. However, Jiang-Nan Yang^[4] recently showed with an individual-based model that the evolution of altruistic ageing occurs under fairly general conditions by kin/group selection. Group selection can be based on population viscosity (limited offspring dispersal, first proposed by Hamilton (1964) for kin selection) that is widely present in natural populations. This population structure builds a continuum between individual selection, kin selection, kin group selection and group selection without a clear boundary for each level. Although early theoretical models by D.S. Wilson et al. (1992)^[24] and Taylor (1992)^[25] showed that pure population viscosity cannot lead to cooperation/altruism because of the exact cancelling out of the benefit of kin cooperation and the cost of kin competition, this exact cancelling out also suggests that any additional benefit of local cooperation would be sufficient for the evolution of cooperation.^[4] Mitteldorf and D.S. Wilson (2000) later showed that if the population is allowed to fluctuate, then local populations can temporarily store the benefit of local cooperation and promote the evolution of altruism.^[26] By assuming individual differences in adaptations, Yang (2013) further showed that the benefit of local altruism can be stored in the form of offspring quality and thus promote the evolution of altruistic ageing even if the population does not fluctuate, this is because local competition among the young will result in an increased average local inherited fitness of survived progenies after the elimination of the less adapted by natural selection, since the young do not have strong age-associated abilities and have to depend more on inherited abilities to compete.^[4] In Yang (2013)'s model, altruistic ageing is stabilized by higher-level selection instead of just kin selection.^[4]

Mitteldorf^[27] proposed a group benefit of a limited lifespan involving regulation of population dynamics. Populations in nature are subject to boom and bust cycles. Often overpopulation can be punished by famine or by epidemic. Either one could wipe out an entire population. Senescence is a means by which a species can 'take control' of its own death rate, and level out the boom-bust cycles. This story may be more plausible than the Weismann hypothesis as a mechanistic explanation, because it addresses the question of how group selection can be rapid enough to compete with individual selection.

Libertini^[28] also suggests benefits for adaptive ageing.

Inversely, within a Negative Senescence Theory R.D. Lee (similarly J.W. Vaupel) considered positive group effects performing a selection force directed to survival beyond the age of fertility.^[29] Often also postreproductive individuals make intergenerational transfers: bottlenose dolphins and pilot whales guard their grandchildren; there is cooperative breeding in some mammals, many insects and about 200 species of birds; sex differences in the survival of anthropoid primates tend to correlate with the care to offspring; or an Efe infant is often attended by more than 10 people. Lee developed a formal theory integrating selection due to transfers (at all ages) with selection due to fertility.^[30]

Ageing theories based on evolvability

Goldsmith^[31] proposed that in addition to increasing the generation rate, and thereby evolution rate, a limited lifespan improves the evolution process by limiting the ability of older individuals to dominate the gene pool. Further, the evolution of characteristics such as intelligence and immunity may specially require a limited lifespan because otherwise acquired characteristics such as experience or exposure to pathogens would tend to override the selection of the beneficial inheritable characteristic. An older and more experienced, but less intelligent animal would have a fitness advantage over a younger, more intelligent animal except for the effects of ageing.

Skulachev^[32] has suggested that programmed ageing assists the evolution process by providing a gradually increasing challenge or obstacle to survival and reproduction, and therefore enhancing the selection of beneficial characteristics. In this sense, ageing would act in a manner similar to that of mating rituals that take the form of contests or trials that must be overcome in order to mate (another individually adverse observation). This suggests an advantage of gradual ageing over sudden death as a means of lifespan regulation.

Weissmann's 1889 ageing theory was essentially an evolvability theory. Ageing or otherwise purposely limited lifespan helps evolution by freeing resources for younger, and therefore, presumably better-adapted individuals.

Yang (2013)'s model^[4] is also based on mechanisms of evolvability. Ageing accelerates the accumulation of novel adaptive genes in local populations. However, Yang changed the terminology of "evolvability" into "genetic creativity" throughout his paper to facilitate the understanding of how ageing can have a shorter-term benefit than the word "evolvability" would imply.

Lenart and Vašku (2016) ^[33] have also invoked evolvability as the main mechanism driving evolution of aging. However, they proposed that even though the actual rate of aging can be an adaptation the aging itself is inevitable. In other words, evolution can change speed of aging but some aging no matter how slow will always occur.

Mechanism

If organisms purposely limit their lifespans via ageing or semelparous behaviour, the associated evolved mechanisms could be very complex, just as mechanisms that provide for mentation, vision, digestion, or other biological function are typically very complex. Such a mechanism could involve hormones, signalling, sensing of external conditions, and other complex functions typical of evolved mechanisms. Such complex mechanisms could explain all of the observations of ageing and semelparous behaviours as described below.

It is typical for a given biological function to be controlled by a single mechanism that is capable of sensing the germane conditions and then executing the necessary function^{[citation needed]}. The mechanism signals all the systems and tissues that need to respond to that function by means of organism-wide signals (hormones). If ageing is indeed a biological function, we would expect all or most manifestations of ageing to be similarly controlled by a common mechanism. Various observations (listed below) indeed suggest the existence of a common control mechanism.

It is also typical for biological functions to be modulated by or synchronized to external events or conditions. The circadian rhythm and synchronization of mating behaviour to planetary cues are examples. In the case of ageing seen as a biological function, the caloric restriction effect may well be an example of the ageing function being modulated in order to optimize organism lifespan in response to external conditions. Temporary extension of lifespan under famine conditions would aid in group survival because extending lifespan, combined with less-frequent reproduction, would reduce the resources required to maintain a given population.

Theories to the effect that ageing results by default (mutation accumulation) or is an adverse side effect of some other function are logically much more limited and suffer when compared to empirical evidence of complex mechanisms. The choice of ageing theory therefore is logically essentially determined by one's position regarding evolutionary processes, and some theorists reject programmed ageing based entirely on evolutionary process considerations.^[34]

Maintenance theories

It is generally accepted that deteriorative processes (wear, other molecular damage) exist and that living organisms have mechanisms to counter deterioration. Wounds heal; dead cells are replaced; claws regrow.

A non-programmed theory of mammal ageing^[35] that fits with classical evolution theory and Medawar's concept is that different mammal species possess different capabilities for maintenance and repair. Longer-lived species possess many mechanisms for offsetting damage due to causes such as oxidation, telomere shortening, and other deteriorative processes that are each more effective than those of shorter-lived species. Shorter-lived species, having earlier ages of sexual maturity, had less need for longevity and thus did not evolve or retain the more-effective repair mechanisms. Damage therefore accumulates more rapidly, resulting in earlier manifestations and shorter lifespan. Since there are a wide variety of ageing manifestations that appear to have very different causes, it is likely that there are many different maintenance and repair functions.

A corresponding programmed maintenance theory based on evolvability^[36] suggests that the repair mechanisms are in turn controlled by a common control mechanism capable of sensing conditions, such as caloric restriction, and also capable of producing the specific lifespan needed by the particular species. In this view, the differences between short- and long-lived species are in the control mechanisms, as opposed to each individual maintenance mechanism.

DNA damage theory

The DNA damage theory of aging is a prominent explanation for aging at the molecular level. This theory postulates that DNA damage is ubiquitous in the biological world and is the primary cause of aging.^[37] Consistent with this theory, genetic elements that regulate repair of DNA damage in somatic cells were proposed to have pleiotropic effects that are beneficial during early development but allow deleterious consequences later in life.^[37][38][39] As an example, studies of mammalian brain and muscle have shown that DNA repair capability is relatively high during early development when cells are dividing mitotically, but declines substantially as cells enter the post-mitotic state. The reduction in DNA repair capability presumably reflects an evolutionary adaptation for diverting resources from cell duplication and repair to more essential neuronal and muscular functions.^[37] The effect of reducing expression of DNA repair capability is to allow increased accumulation of DNA damage. This then impairs gene transcription and causes the progressive loss of cellular and tissue functions that define aging.

Evidence

• Complex programmed death mechanisms exist in semelparous species (e.g. octopus), including hormone signalling, nervous system involvement, etc. If a limited lifespan is generally useful as predicted by the programmed ageing theories, it would be unusual for an octopus to possess a more complex mechanism for accomplishing that function than a mammal.
• "Ageing genes" with no other apparent function. However to date no evidence that such genes exist has been found.
• Caloric restriction effect: reduction of available resources increases lifespan. This behavior has a plausible group benefit in enhancing the survival of a group under famine conditions and also suggests common control.
• Progeria and Werner syndrome are both single-gene genetic diseases that cause acceleration of many or most symptoms of ageing. The fact that a single gene malfunction can cause similar effects on many different manifestations of ageing suggests a common mechanism. However, both genes affected influence DNA stability and so can be explained by stochastic theories of ageing that attribute ageing to accumulation of DNA damage.
• Although mammal lifespans vary over an approximately 100:1 range, manifestations of ageing (cancer, arthritis, weakness, sensory deficit, etc.) are similar in different species. This suggests that the deterioration mechanisms and corresponding maintenance mechanisms operate over a short period (less than the lifespan of a short-lived mammal). All the mammals therefore need all the maintenance mechanisms. This suggests that the difference between mammals is in a control mechanism or repair efficiency.
• Lifespan varies greatly among otherwise very similar species (e.g. different varieties of salmon 3:1, different fish 600:1) suggesting that relatively few genes control lifespan and that relatively minor changes to genotype could cause major differences in lifespan. This could be consistent with a common control mechanism for lifespan but note that this does not in itself provide evidence for programmed aging but is equally consistent with traditional theories.

Problems with programmed ageing theories

Contrary to the theory of programmed death by ageing, individuals from a single species usually live much longer in a protected (laboratory, domestic, civilized) environment than in their wild (natural) environment, reaching ages that would be otherwise practically impossible. Also, in majority of species, there doesn't exist any critical age after which death rates change dramatically, as intended by the programmed death by ageing^{[citation needed]}, but the age-dependence of death rates is very smooth and monotonic. However, as mentioned above, V.P. Skulachev^[43] explained that a process of gradual ageing has the advantage of facilitating selection for useful traits by allowing old individuals with a useful trait to live longer. It is also easy to imagine that animals with gradual ageing will live longer in a protected environment.

The death rates at extreme old ages start to slow down, which is the opposite of what would be expected if death by ageing was programmed. From an individual-selection point of view, having genes that would not result in a programmed death by ageing would displace genes that cause programmed death by ageing, as individuals would produce more offspring in their longer lifespan and they could increase the survival of their offspring by providing longer parental support.^[44]

Biogerontology considerations

Theories of ageing affect efforts to understand and find treatments for age-related conditions (see biogerontology):

• Those who believe in the idea that ageing is an unavoidable side effect of some necessary function (antagonistic pleiotropy or disposable soma theories) logically tend to believe that attempts to delay ageing would result in unacceptable side effects to the necessary functions. Altering ageing is therefore "impossible",^[1] and study of ageing mechanisms is of only academic interest.
• Those believing in default theories of multiple maintenance mechanisms tend to believe that ways might be found to enhance the operation of some of those mechanisms. Perhaps they can be assisted by anti-oxidants or other agents.
• Those who believe in programmed ageing suppose that ways might be found to interfere with the operation of the part of the ageing mechanism that appears to be common to multiple symptoms, essentially "slowing down the clock" and delaying multiple manifestations. Such effect might be obtained by fooling a sense function. One such effort is an attempt to find a "mimetic" that would "mime" the anti-ageing effect of calorie restriction without having to actually radically restrict diet.