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Lower motor neurons (LMNs) are motor neurons located in either the anterior grey column, anterior nerve roots (spinal lower motor neurons) or the cranial nerve nuclei of the brainstem and cranial nerves with motor function (cranial nerve lower motor neurons). Many voluntary movements rely on spinal lower motor neurons, which innervate skeletal muscle fibers and act as a link between upper motor neurons and muscles. Cranial nerve lower motor neurons also control some voluntary movements of the eyes, face and tongue, and contribute to chewing, swallowing and vocalization. Damage to lower motor neurons often leads to hypotonia, hyporeflexia, flaccid paralysis as well as muscle atrophy and fasciculations.
== Classification ==
Lower motor neurons are classified based on the type of muscle fiber they innervate:
Alpha motor neurons (α-MNs) innervate extrafusal muscle fibers, the most numerous type of muscle fiber and the one involved in muscle contraction.
Beta motor neurons (β-MNs) innervate intrafusal fibers of muscle spindles with collaterals to extrafusal fibers (type of slow twitch fibers).
Gamma motor neurons (γ-MNs) innervate intrafusal muscle fibers, which together with sensory afferents compose muscle spindles. These are part of the system for sensing body position (proprioception).
== Physiology ==
Glutamate released from the upper motor neurons triggers depolarization in the lower motor neurons in the anterior grey column, which in turn causes an action potential to propagate the length of the axon to the neuromuscular junction where acetylcholine is released to carry the signal across the synaptic cleft to the postsynaptic receptors of the muscle cell membrane, signaling the muscle to contract.
== Clinical significance ==
Damage to lower motor neurons, lower motor neuron lesions (LMNL) cause muscle wasting (atrophy), decreased strength and decreased reflexes in affected areas. These findings are in contrast to findings in upper motor neuron lesions. LMNL is indicated by abnormal EMG potentials, fasciculations, paralysis, weakening of muscles, and neurogenic atrophy of skeletal muscle. Bell's palsy, bulbar palsy, poliomyelitis and amyotrophic lateral sclerosis (ALS) are all pathologies associated with lower motor neuron dysfunction.
== See also ==
Upper motor neuron
Upper motor neuron lesion
Motor system
== References == | Wikipedia/Lower_motor_neuron |
Medium spiny neurons (MSNs), also known as spiny projection neurons (SPNs), are a special type of inhibitory GABAergic neuron representing approximately 90% of neurons within the human striatum, a basal ganglia structure. Medium spiny neurons have two primary phenotypes (characteristic types): D1-type MSNs of the direct pathway and D2-type MSNs of the indirect pathway. Most striatal MSNs contain only D1-type or D2-type dopamine receptors, but a subpopulation of MSNs exhibit both phenotypes.
Direct pathway MSNs excite their ultimate basal ganglia output structure (such as the thalamus) and promote associated behaviors; these neurons express D1-type dopamine receptors, adenosine A1 receptors, dynorphin peptides, and substance P peptides. Indirect pathway MSNs inhibit their output structure and in turn inhibit associated behaviors; these neurons express D2-type dopamine receptors, adenosine A2A receptors (A2A), DRD2–A2A heterotetramers, and enkephalin. Both types express glutamate receptors (NMDAR and AMPAR), cholinergic receptors (M1 and M4) and CB1 receptors are expressed on the somatodendritic area of both MSN types. A subpopulation of MSNs contain both D1-type and D2-type receptors, with approximately 40% of striatal MSNs expressing both DRD1 and DRD2 mRNA. In the nucleus accumbens (NAcc), these mixed-type MSNs that contain both D1-type and D2-type receptors are mostly contained in the NAcc shell.
The dorsal striatal MSNs play a key role in initiating and controlling movements of the body, limbs, and eyes. The ventral striatal MSNs play a key role in motivation, reward, reinforcement, and aversion. Dorsal and ventral medium spiny neuron subtypes (i.e., direct D1-type and indirect D2-type) are identical phenotypes, but their output connections differ.
== Appearance and location ==
The medium spiny neurons are medium-sized projection neurons with extensively branched dendrites. The cell body is 15–18 μm and has five primary dendrites that become branched. At first the dendrites are without spines but at about the first branch point they become densely spined. The branches produce almost spherical dendritic fields of between 200–300 μm.
About 90% of neurons in the striatum are medium projection neurons, the other 10% are interneurons. In the direct pathway the neurons project directly to the globus pallidus internal (GPi) and the substantia nigra pars reticulata (SNpr). In the indirect pathway the MSNs ultimately project to these two structures via an intermediate connection to the globus pallidus external (GPe) and ventral pallidum (VP). The GPe and VP send a GABAergic projection to the subthalamic nucleus, which then sends glutamatergic projections to the GPi and SNpr. Both the GPi and SNpr send inhibitory projections to nuclei within the thalamus.
== Function ==
MSNs are inhibitory GABAergic neurons, but the effect of direct MSNs (dMSNs) and indirect MSNs (iMSNs) on their ultimate output structures differs: dMSNs excite, while iMSNs inhibit, their basal ganglia output structures (e.g., the thalamus). Within the basal ganglia, there are several complex circuits of neuronal loops all of which include medium spiny neurons.
The cortical, thalamic, and brain-stem inputs that arrive at the medium spiny neurons show a vast divergence in that each incoming axon forms contacts with many spiny neurons and each spiny neuron receives a vast amount of input from different incoming axons. Since these inputs are glutamatergic they exhibit an excitatory influence on the inhibitory medium spiny neurons.
There are also interneurons in the striatum which regulate the excitability of the medium spiny neurons. The synaptic connections between a particular GABAergic interneuron, the parvalbumin expressing fast-spiking interneuron, and spiny neurons are close to the spiny neurons' soma, or cell body. Recall that excitatory postsynaptic potentials caused by glutamatergic inputs at the dendrites of the spiny neurons only cause an action potential when the depolarization wave is strong enough upon entering the cell soma. Since the fast-spiking interneurons influence is located so closely to this critical gate between the dendrites and the soma, they can readily regulate the generation of an action potential. Additionally, other types of GABAergic interneurons make connections with the spiny neurons. These include interneurons that express tyrosine hydroxylase and neuropeptide Y.
== Dorsal striatal MSNs ==
=== Direct pathway ===
==== Anatomy ====
The direct pathway within the basal ganglia receives excitatory input from the cortex, thalamus, and other brain regions. In the direct pathway, medium spiny neurons project to the internal division of the globus pallidus (GPi) or the substantia nigra pars reticula (SNpr or SNr). These nuclei project to the deep layer of the superior colliculus and control fast eye movements (saccades), and also project to the ventral thalamus, which in turn projects to upper motor neurons in the primary motor cortex (precentral gyrus). The SNr and GPi outputs are both tonically active inhibitory nuclei and are thus constantly inhibiting the thalamus (and thus motor cortex). However, transient activity in (inhibitory) direct pathway medium spiny neurons ultimately disinhibits thalamus projections to the motor cortex and enables movement.
=== Indirect pathway ===
==== Anatomy ====
The indirect pathway also receives excitatory input from various brain regions. Indirect pathway medium spiny neurons project to the external segment of the globus pallidus (GPe). Like the GPi, the GPe is a tonically active inhibitory nucleus. The GPe projects to the excitatory subthalamic nucleus (STN), which in turn projects to the GPi and SNr. When the indirect pathway is not activated, activity in the STN is suppressed by the GPe, which translates to decreased SNr/GPi activity downstream and thus increased thalamic and motor cortex neuron activity. When indirect pathway neurons fire, GPe neurons are inhibited, which disinhibits the STN. The STN then excites SNr/GPi neurons, suppressing thalamus/motor cortex activity.
=== Functional distinctions ===
Classic models of striatal function have posited that activation of the direct pathway leads to movement, whereas activation of the indirect pathway leads to the termination of movement. This model is supported by experiments demonstrating that optogenetically stimulating direct pathway medium spiny neurons increases locomotion, whereas stimulating indirect pathway medium spiny neurons inhibits locomotion. The balance of direct/indirect activity in movement is supported by evidence from neurodegenerative disorders, including Parkinson's disease (PD), which is characterized by loss of dopamine neurons projecting to the striatum, hypoactivity in direct pathway and hyperactivity in indirect pathway neurons, along with motor dysfunction. This results in loss of normal action selection, as loss of dopamine drives activity in the indirect pathway, globally inhibiting all motor paradigms. This may explain impaired action initiation, slowed actions (bradykinesia), and impaired voluntary motor initiation in Parkinson's patients. On the other hand, Huntington's disease, which is characterized by preferential degradation of indirect pathway medium spiny neurons, results in unwanted movements (chorea) that may result from impaired movement inhibition and predominant direct pathway activity. An alternative related hypothesis is that the striatum controls action initiation and selection via a ’center-surround’ architecture, where activation of a subset of direct pathway neurons initiates movements while closely related motor patterns represented by surrounding neurons are inhibited by lateral inhibition via indirect pathway neurons. This specific hypothesis is supported by recent calcium-imaging work showing that direct and indirect pathway medium spiny neurons encoding specific actions are located in spatially organized ensembles.
Despite the abundance of evidence for the initiation/termination model, recent evidence using transgenic mice expressing calcium indicators in either the direct or indirect pathway demonstrated that both pathways are active at action initiation, but neither are active during inactivity, a finding which has been replicated using simultaneous two-channel calcium imaging. This has led to somewhat of a paradigm shift in models of striatal functioning, such that newer models posit that the direct pathway facilitates wanted movements, whereas the indirect pathway simultaneously inhibits unwanted movements. Indeed, more sophisticated techniques and analyses, such as state-dependent optogenetics, have revealed that both pathways are heavily involved in action sequence execution, and that specifically, both striatal pathways are involved in element-level action control. However, direct pathway medium spiny neurons mostly signal sequence initiation/termination and indirect pathway medium spiny neurons may signal switching between subsequences of a given action sequence. Other evidence suggests that the direct and indirect pathway oppositely influence the termination of movement—specifically, the relative timing of their activity determines if an action will be terminated.
Recent experiments have established that the direct and indirect pathways of the dorsal striatum are not solely involved in movement. Initial experiments in an intracranial self-stimulation paradigm suggested opposing roles in reinforcement for the two pathways; specifically, stimulation of direct pathway medium spiny neurons was found to be reinforcing, whereas stimulation of indirect pathway medium spiny neurons was aversive. However, a subsequent study (using more physiologically relevant stimulation parameters) found that direct and indirect pathway stimulation was reinforcing, but that pathway-specific stimulation resulted in the development of different action strategies. Regardless, these studies suggest a critical role for reinforcement in the dorsal striatum, as opposed to the striatum only serving a role in movement control.
== Ventral striatal MSNs ==
=== Direct pathway ===
The direct pathway of the ventral striatum within the basal ganglia mediates reward-based learning and appetitive incentive salience, which is assigned to rewarding stimuli.
=== Indirect pathway ===
The indirect pathway of the ventral striatum within the basal ganglia mediates aversion-based learning and aversive motivational salience, which is assigned to aversive stimuli.
== See also ==
List of distinct cell types in the adult human body
== References ==
== Further reading ==
== External links ==
NIF Search – Medium Spiny Neuron via the Neuroscience Information Framework | Wikipedia/Medium_spiny_neuron |
Upper motor neurons (UMNs) is a term introduced by William Gowers in 1886. They are found in the cerebral cortex and brainstem and carry information down to activate interneurons and lower motor neurons, which in turn directly signal muscles to contract or relax. UMNs represent the major origin point for voluntary somatic movement.
Upper motor neurons represent the largest pyramidal cells in the motor regions of the cerebral cortex. The major cell type of the UMNs is the Betz cells residing in layer V of the primary motor cortex, located on the precentral gyrus in the posterior frontal lobe. The cell bodies of Betz cell neurons are the largest in the brain, approaching nearly 0.1 mm in diameter. The axons of the upper motor neurons project out of the precentral gyrus travelling through to the brainstem, where they will decussate (intersect) within the lower medulla oblongata to form the lateral corticospinal tract on each side of the spinal cord. The fibers that do not decussate will pass through the medulla and continue on to form the anterior corticospinal tracts.
The upper motor neuron descends in the spinal cord to the level of the appropriate spinal nerve root. At this point, the upper motor neuron synapses with the lower motor neuron or interneurons within the ventral horn of the spinal cord, each of whose axons innervate a fiber of skeletal muscle.
These neurons connect the brain to the appropriate level in the spinal cord, from which point nerve signals continue to the muscles by means of the lower motor neurons. The neurotransmitter glutamate transmits the nerve impulses from upper to lower motor neurons, where it is detected by glutamate receptors.
== Pathways ==
Upper motor neurons travel in several neural pathways through the central nervous system (CNS):
== Lesions ==
Any upper motor neuron lesion, also known as pyramidal insufficiency, occurs in the neural pathway above the anterior horn of the spinal cord. Such lesions can arise as a result of stroke, multiple sclerosis, spinal cord injury or other acquired brain injury. The resulting changes in muscle performance that can be wide and varied are described overall as upper motor neuron syndrome. Symptoms can include muscle weakness, decreased motor control including a loss of the ability to perform fine movements, increased vigor (and decreased threshold) of spinal reflexes including spasticity, clonus (involuntary, successive cycles of contraction/relaxation of a muscle), and an extensor plantar response known as the Babinski sign.
== See also ==
Lower motor neuron
Upper motor neuron lesion
Lower motor neuron lesion
== References ==
== External links ==
"motoneuron" at Dorland's Medical Dictionary | Wikipedia/Upper_motor_neuron |
Spinal neurons are specialized nerve cells located within the spinal cord. They are a crucial component of the central nervous system. These neurons play vital roles in transmitting and processing information between the brain and the rest of the body.
== Types of Spinal Neurons ==
=== Motor Neurons ===
Motor Neurons are located in the front (ventral) horns of the spinal cord's grey matter. They carry information from the brain and spinal cord to the body's muscles. This tells our body to stimulate muscle movement.
=== Sensory Neurons ===
Sensory neurons are found in the back (dorsal) horns of the spinal cord's grey matter. They carry sensory information such as touch, pressure, and pain from the body to the spinal cord and brain.
=== Interneurons ===
Interneurons are the most abundant type of neuron in the spinal cord. They process and convey information between sensory neurons and motor neurons.
== Function and Connectivity ==
Within the spinal cord, spinal neurons organize into intricate networks that enable a variety of activities.
Signal Transmission: They facilitate both deliberate and involuntary movements by transmitting messages from the brain to the body.
Reflex Actions: include certain spinal neurons, allow for rapid, reflexive reactions to stimuli without requiring direct brain involvement.
Information Processing: Before sending sensory data to the brain, spinal neurons partially analyze it.
Synaptic Connections: Through synapses and neurotransmitters, spinal neurons exchange information with neurons in other regions of the nervous system as well as with one another.
== Spinal Cord Organizion ==
Between the brain and the body, the spinal cord is the most crucial component. From the foramen magnum, where it joins the medulla, the spinal cord reaches the first or second lumbar vertebrae. It is an essential connection between the body and the brain as well as between the two. The spinal cord has a diameter of 1 to 1.5 cm and a length of 40 to 50 cm. On either side, two successive rows of nerve roots appear. Thirty-one pairs of spinal nerves are formed by the distal union of these nerve roots.
The spinal cord is a uniformly organized, cylindrical structure of white and gray matter that is separated into four regions: cervical (C), thoracic (T), lumbar (L), and sacral (S). Each area is made up of many segments. Motor and sensory nerve fibers to and from every area of the body are found in the spinal nerve. A dermatome is innervated by each segment of the spinal cord.
The spinal cord is organized into segments, each corresponding to specific regions of the body:
8 cervical (neck)
12 thoracic (chest)
5 lumbar (abdominal)
5 sacral (pelvic)
1 coccygeal (tailbone)
Clinical Significance
Numerous neurological disorders can arise from damage to spinal neurons, including:
Paralysis
Loss of sensation
Impaired reflexes
Altered motor control
The location and severity of the spinal cord injury or disease determine the particular symptoms.
In order to diagnose and treat spinal cord illnesses and to create prospective treatments for spinal cord injuries, it is essential to comprehend spinal neurons and their roles.
== References == | Wikipedia/Spinal_neuron |
In neuroscience, the axolemma (from Greek lemma 'membrane, envelope', and 'axo-' from axon) is the cell membrane of an axon, the branch of a neuron through which signals (action potentials) are transmitted. The axolemma is a three-layered, bilipid membrane. Under standard electron microscope preparations, the structure is approximately 8 nanometers thick.
== Composition ==
The skeletal framework of this structure is formed by a spectrum of hexagonal or pentagonal arrangement on the inside of the cell membrane, as well as actin connected to the transmembrane. The metric cellular matrix is bound by transmembrane proteins, including the β1-integrin, to the cytoskeleton via the membrane skeleton. The axolemma is a phospholipid bilayer membrane, and charged ions/particles cannot directly pass through it. Instead, transmembrane proteins, such as specialized energy dependent ion pumps (the sodium/potassium pump), and ion channels (ligand-gated channels, mechanically gated channels, voltage-gated channels, and leakage channels) that sit within the axolemma are required to assist these charged ions/particles across the membrane, and to generate transmembrane potentials that will generate an action potential.
== Function ==
The primary responsibility of cell membranes, including those surrounding the axon, is to regulate what goes into the cell and what goes out of the cell. The axolemma plays an important role in the nervous system, specifically the sensation, integration, and response pathways within the nervous system. Communication between neurons within the nervous system relies on excitable membranes, especially the axolemma. The axolemma is responsible for relaying signals between the neuron and it's Schwann Cells. These signals control the proliferative and myelin-producing functions of the Schwann Cells, and also partly play a role in the regulation of the size of the axon.
== The axolemma's role in the generation of action potentials ==
The variations in electrical state of the axolemma is referred to as the membrane potential – a potential being the distribution of charge between the inside and outside of the cell, which is measured in millivolts (mV). The transmembrane proteins keep the concentration of ions inside the cell and the concentration of ions outside the cell relatively balanced, with a net neutral charge, but if a difference in charge occurs right at the surface of the axolemma, either internally or externally, electrical signals, such as action potentials, can be generated.
When the cell, or axon, is at rest, the concentration of sodium (Na+) outside of the cell is greater than the concentration of Na+ inside of the cell, and the concentration of potassium (K+) inside of the cell is greater than the concentration of K+ outside of the cell. This difference in charge is referred to as the resting membrane potential – which is measured at -70mV.
The opening of channels within the axolemma, allows for Na+ to flow down its concentration gradient, and into the cell. Na+ is a positively charge ion, so the influx on Na+ causes the membrane potential to move toward zero. This is referred to as depolarization. However, the concentration gradient of Na+ is strong enough to allow Na+ to flow into the cell until the membrane potential to reach +30mV.
The membrane potential reaching +30 mV, and the concentration of Na+ being so high, causes other voltage-gated channels, that are specific to K+ to open. K+ then flows down its concentration gradient and out of the cell. Since the positively charged K+ is leaving the cell, the membrane potential goes back down toward its resting membrane potential. The movement of the membrane voltage back toward -70 mV is referred to as repolarization. However, repolarization overshoots the resting membrane potential, because the K+ channels experience a delay when closing, which causes a period of hyperpolarization.
This change in charge, voltage, and membrane potential generates an electrical signal referred to as an action potential. Action potentials are used for communication between neurons within nervous tissue.
== References == | Wikipedia/Axolemma |
Sensory neurons, also known as afferent neurons, are neurons in the nervous system, that convert a specific type of stimulus, via their receptors, into action potentials or graded receptor potentials. This process is called sensory transduction. The cell bodies of the sensory neurons are located in the dorsal root ganglia of the spinal cord.
The sensory information travels on the afferent nerve fibers in a sensory nerve, to the brain via the spinal cord. Spinal nerves transmit external sensations via sensory nerves to the brain through the spinal cord. The stimulus can come from exteroreceptors outside the body, for example those that detect light and sound, or from interoreceptors inside the body, for example those that are responsive to blood pressure or the sense of body position.
== Types and function ==
Sensory neurons in vertebrates are predominantly pseudounipolar or bipolar, and different types of sensory neurons have different sensory receptors that respond to different kinds of stimuli. There are at least six external and two internal sensory receptors:
=== External receptors ===
External receptors that respond to stimuli from outside the body are called exteroreceptors. Exteroreceptors include chemoreceptors such as olfactory receptors (smell) and taste receptors, photoreceptors (vision), thermoreceptors (temperature), nociceptors (pain), hair cells (hearing and balance), and a number of other different mechanoreceptors for touch and proprioception (stretch, distortion and stress).
==== Smell ====
The sensory neurons involved in smell are called olfactory sensory neurons. These neurons contain receptors, called olfactory receptors, that are activated by odor molecules in the air. The molecules in the air are detected by enlarged cilia and microvilli. These sensory neurons produce action potentials. Their axons form the olfactory nerve, and they synapse directly onto neurons in the cerebral cortex (olfactory bulb). They do not use the same route as other sensory systems, bypassing the brain stem and the thalamus. The neurons in the olfactory bulb that receive direct sensory nerve input, have connections to other parts of the olfactory system and many parts of the limbic system. 9.
==== Taste ====
Taste sensation is facilitated by specialized sensory neurons located in the taste buds of the tongue and other parts of the mouth and throat. These sensory neurons are responsible for detecting different taste qualities, such as sweet, sour, salty, bitter, and savory. When you eat or drink something, chemicals in the food or liquid interact with receptors on these sensory neurons, triggering signals that are sent to the brain. The brain then processes these signals and interprets them as specific taste sensations, allowing you to perceive and enjoy the flavors of the foods you consume. When taste receptor cells are stimulated by the binding of these chemical compounds (tastants), it can lead to changes in the flow of ions, such as sodium (Na+), calcium (Ca2+), and potassium (K+), across the cell membrane. In response to tastant binding, ion channels on the taste receptor cell membrane can open or close. This can lead to depolarization of the cell membrane, creating an electrical signal.
Similar to olfactory receptors, taste receptors (gustatory receptors) in taste buds interact with chemicals in food to produce an action potential.
==== Vision ====
Photoreceptor cells are capable of phototransduction, a process which converts light (electromagnetic radiation) into electrical signals. These signals are refined and controlled by the interactions with other types of neurons in the retina. The five basic classes of neurons within the retina are photoreceptor cells, bipolar cells, ganglion cells, horizontal cells, and amacrine cells. The basic circuitry of the retina incorporates a three-neuron chain consisting of the photoreceptor (either a rod or cone), bipolar cell, and the ganglion cell. The first action potential occurs in the retinal ganglion cell. This pathway is the most direct way for transmitting visual information to the brain. There are three primary types of photoreceptors: Cones are photoreceptors that respond significantly to color. In humans the three different types of cones correspond with a primary response to short wavelength (blue), medium wavelength (green), and long wavelength (yellow/red). Rods are photoreceptors that are very sensitive to the intensity of light, allowing for vision in dim lighting. The concentrations and ratio of rods to cones is strongly correlated with whether an animal is diurnal or nocturnal. In humans, rods outnumber cones by approximately 20:1, while in nocturnal animals, such as the tawny owl, the ratio is closer to 1000:1. Retinal ganglion cells are involved in the sympathetic response. Of the ~1.3 million ganglion cells present in the retina, 1-2% are believed to be photosensitive.
Issues and decay of sensory neurons associated with vision lead to disorders such as:
Macular degeneration – degeneration of the central visual field due to either cellular debris or blood vessels accumulating between the retina and the choroid, thereby disturbing and/or destroying the complex interplay of neurons that are present there.
Glaucoma – loss of retinal ganglion cells which causes some loss of vision to blindness.
Diabetic retinopathy – poor blood sugar control due to diabetes damages the tiny blood vessels in the retina.
==== Auditory ====
The auditory system is responsible for converting pressure waves generated by vibrating air molecules or sound into signals that can be interpreted by the brain.
This mechanoelectrical transduction is mediated with hair cells within the ear. Depending on the movement, the hair cell can either hyperpolarize or depolarize. When the movement is towards the tallest stereocilia, the Na+ cation channels open allowing Na+ to flow into cell and the resulting depolarization causes the Ca++ channels to open, thus releasing its neurotransmitter into the afferent auditory nerve. There are two types of hair cells: inner and outer. The inner hair cells are the sensory receptors .
Problems with sensory neurons associated with the auditory system leads to disorders such as:
Auditory processing disorder – Auditory information in the brain is processed in an abnormal way. Patients with auditory processing disorder can usually gain the information normally, but their brain cannot process it properly, leading to hearing disability.
Auditory verbal agnosia – Comprehension of speech is lost but hearing, speaking, reading, and writing ability is retained. This is caused by damage to the posterior superior temporal lobes, again not allowing the brain to process auditory input correctly.
==== Temperature ====
Thermoreceptors are sensory receptors, which respond to varying temperatures. While the mechanisms through which these receptors operate is unclear, recent discoveries have shown that mammals have at least two distinct types of thermoreceptors.
The bulboid corpuscle, is a cutaneous receptor a cold-sensitive receptor, that detects cold temperatures. The other type is a warmth-sensitive receptor.
==== Mechanoreceptors ====
Mechanoreceptors are sensory receptors which respond to mechanical forces, such as pressure or distortion.
Specialized sensory receptor cells called mechanoreceptors often encapsulate afferent fibers to help tune the afferent fibers to the different types of somatic stimulation. Mechanoreceptors also help lower thresholds for action potential generation in afferent fibers and thus make them more likely to fire in the presence of sensory stimulation.
Some types of mechanoreceptors fire action potentials when their membranes are physically stretched.
Proprioceptors are another type of mechanoreceptors which literally means "receptors for self". These receptors provide spatial information about limbs and other body parts.
Nociceptors are responsible for processing pain and temperature changes. The burning pain and irritation experienced after eating a chili pepper (due to its main ingredient, capsaicin), the cold sensation experienced after ingesting a chemical such as menthol or icillin, as well as the common sensation of pain are all a result of neurons with these receptors.
Problems with mechanoreceptors lead to disorders such as:
Neuropathic pain - a severe pain condition resulting from a damaged sensory nerve
Hyperalgesia - an increased sensitivity to pain caused by sensory ion channel, TRPM8, which is typically responds to temperatures between 23 and 26 degrees, and provides the cooling sensation associated with menthol and icillin
Phantom limb syndrome - a sensory system disorder where pain or movement is experienced in a limb that does not exist
=== Internal receptors ===
Internal receptors that respond to changes inside the body are known as interoceptors.
==== Blood ====
The aortic bodies and carotid bodies contain clusters of glomus cells – peripheral chemoreceptors that detect changes in chemical properties in the blood such as oxygen concentration. These receptors are polymodal responding to a number of different stimuli.
==== Nociceptors ====
Nociceptors respond to potentially damaging stimuli by sending signals to the spinal cord and brain. This process, called nociception, usually causes the perception of pain. They are found in internal organs as well as on the surface of the body to "detect and protect". Nociceptors detect different kinds of noxious stimuli indicating potential for damage, then initiate neural responses to withdraw from the stimulus.
Thermal nociceptors are activated by noxious heat or cold at various temperatures.
Mechanical nociceptors respond to excess pressure or mechanical deformation, such as a pinch.
Chemical nociceptors respond to a wide variety of chemicals, some of which signal a response. They are involved in the detection of some spices in food, such as the pungent ingredients in Brassica and Allium plants, which target the sensory neural receptor to produce acute pain and subsequent pain hypersensitivity.
== Connection with the central nervous system ==
Information coming from the sensory neurons in the head enters the central nervous system (CNS) through cranial nerves. Information from the sensory neurons below the head enters the spinal cord and passes towards the brain through the 31 spinal nerves. The sensory information traveling through the spinal cord follows well-defined pathways. The nervous system codes the differences among the sensations in terms of which cells are active.
== Classification ==
=== Adequate stimulus ===
A sensory receptor's adequate stimulus is the stimulus modality for which it possesses the adequate sensory transduction apparatus. Adequate stimulus can be used to classify sensory receptors:
Baroreceptors respond to pressure in blood vessels
Chemoreceptors respond to chemical stimuli
Electromagnetic radiation receptors respond to electromagnetic radiation
Infrared receptors respond to infrared radiation
Photoreceptors respond to visible light
Ultraviolet receptors respond to ultraviolet radiation
Electroreceptors respond to electric fields
Ampullae of Lorenzini respond to electric fields, salinity, and to temperature, but function primarily as electroreceptors
Hydroreceptors respond to changes in humidity
Magnetoreceptors respond to magnetic fields
Mechanoreceptors respond to mechanical stress or mechanical strain
Nociceptors respond to damage, or threat of damage, to body tissues, leading (often but not always) to pain perception
Osmoreceptors respond to the osmolarity of fluids (such as in the hypothalamus)
Proprioceptors provide the sense of position
Thermoreceptors respond to temperature, either heat, cold or both
=== Location ===
Sensory receptors can be classified by location:
Cutaneous receptors are sensory receptors found in the dermis or epidermis.
Muscle spindles contain mechanoreceptors that detect stretch in muscles.
=== Morphology ===
Somatic sensory receptors near the surface of the skin can usually be divided into two groups based on morphology:
Free nerve endings characterize the nociceptors and thermoreceptors and are called thus because the terminal branches of the neuron are unmyelinated and spread throughout the dermis and epidermis.
Encapsulated receptors consist of the remaining types of cutaneous receptors. Encapsulation exists for specialized functioning.
=== Rate of adaptation ===
A tonic receptor is a sensory receptor that adapts slowly to a stimulus and continues to produce action potentials over the duration of the stimulus. In this way it conveys information about the duration of the stimulus. Some tonic receptors are permanently active and indicate a background level. Examples of such tonic receptors are pain receptors, joint capsule, and muscle spindle.
A phasic receptor is a sensory receptor that adapts rapidly to a stimulus. The response of the cell diminishes very quickly and then stops. It does not provide information on the duration of the stimulus; instead some of them convey information on rapid changes in stimulus intensity and rate. An example of a phasic receptor is the Pacinian corpuscle.
== Drugs ==
There are many drugs currently on the market that are used to manipulate or treat sensory system disorders. For instance, gabapentin is a drug that is used to treat neuropathic pain by interacting with one of the voltage-dependent calcium channels present on non-receptive neurons. Some drugs may be used to combat other health problems, but can have unintended side effects on the sensory system. Dysfunction in the hair cell mechanotransduction complex, along with the potential loss of specialized ribbon synapses, can lead to hair cell death, often caused by ototoxic drugs like aminoglycoside antibiotics poisoning the cochlea. Through the use of these toxins, the K+ pumping hair cells cease their function. Thus, the energy generated by the endocochlear potential which drives the auditory signal transduction process is lost, leading to hearing loss.
== Neuroplasticity ==
Ever since scientists observed cortical remapping in the brain of Taub's Silver Spring monkeys, there has been a large amount of research into sensory system plasticity. Huge strides have been made in treating disorders of the sensory system. Techniques such as constraint-induced movement therapy developed by Taub have helped patients with paralyzed limbs regain use of their limbs by forcing the sensory system to grow new neural pathways. Phantom limb syndrome is a sensory system disorder in which amputees perceive that their amputated limb still exists and they may still be experiencing pain in it. The mirror box developed by V.S. Ramachandran, has enabled patients with phantom limb syndrome to relieve the perception of paralyzed or painful phantom limbs. It is a simple device which uses a mirror in a box to create an illusion in which the sensory system perceives that it is seeing two hands instead of one, therefore allowing the sensory system to control the "phantom limb". By doing this, the sensory system can gradually get acclimated to the amputated limb, and thus alleviate this syndrome.
== Other animals ==
Hydrodynamic reception is a form of mechanoreception used in a range of animal species.
== Additional images ==
== See also ==
Pseudounipolar neuron
Neural coding
Posterior column
Receptive field
Sensory system
List of distinct cell types in the adult human body
Sensory nerve
Motor nerve
Afferent nerve fiber
Efferent nerve fiber
Motor neuron
== References ==
== External links ==
Media related to Sensory neuron at Wikimedia Commons
Purves D, Augustine GJ, Fitzpatrick D, et al., eds. (2001). "Table 9.1 The major classes of somatic sensory receptors". Neuroscience (2nd ed.). Sunderland MA: Sinauer Associates. ISBN 0-87893-742-0. | Wikipedia/Afferent_neuron |
A bipolar neuron, or bipolar cell, is a type of neuron characterized by having both an axon and a dendrite extending from the soma (cell body) in opposite directions. These neurons are predominantly found in the retina and olfactory system. The embryological period encompassing weeks seven through eight marks the commencement of bipolar neuron development.
Many bipolar cells are specialized sensory neurons (afferent neurons) for the transmission of sense. As such, they are part of the sensory pathways for smell, sight, taste, hearing, touch, balance and proprioception. The other shape classifications of neurons include unipolar, pseudounipolar and multipolar. During embryonic development, pseudounipolar neurons begin as bipolar in shape but become pseudounipolar as they mature.
Common examples are the retina bipolar cell, the spiral ganglion and vestibular ganglion of the vestibulocochlear nerve (cranial nerve VIII), the extensive use of bipolar cells to transmit efferent (motor) signals to control muscles and olfactory receptor neurons in the olfactory epithelium for smell (axons form the olfactory nerve).
== In the retina ==
Bipolar neurons, classified as second-order retinal neurons, play a crucial role in translating responses to light into a neural code for vision.
Often found in the retina, bipolar cells are crucial as they serve as both direct and indirect cell pathways. The specific location of the bipolar cells allow them to facilitate the passage of signals from where they start in the receptors to where they arrive at the amacrine and ganglion cells. Bipolar cells in the retina are also unusual in that they do not fire impulses like the other cells found within the nervous system. Rather, they pass the information by graded signal changes. Bipolar cells convey impulses from photoreceptors (rods and cones) to ganglion cells, which in turn transport the visual signals to the brain through the optic nerve. Bipolar cells come in two varieties, having either an on-center or an off-center receptive field, each with a surround of the opposite sign. The off-center bipolar cells have excitatory synaptic connections with the photoreceptors, which fire continuously in the dark and are hyperpolarized (suppressed) by light. The excitatory synapses thus convey a suppressive signal to the off-center bipolar cells. On-center bipolar cells have inhibitory synapses with the photoreceptors and therefore are excited by light and suppressed in the dark.
== In the vestibular nerve ==
Bipolar neurons exist within the vestibular nerve as it is responsible for special sensory sensations including hearing, equilibrium and motion detection. The majority of the bipolar neurons belonging to the vestibular nerve exist within the vestibular ganglion with axons extending into the maculae of utricle and saccule as well as into the ampullae of the semicircular canals.
== In the spinal ganglia ==
Bipolar cells are also found in the spinal ganglia, when the cells are in an embryonic condition.
Sometimes the extensions, also called processes, come off from opposite poles of the cell, and the cell then assumes a spindle shape.
In some cases where two fibers are apparently connected with a cell, one of the fibers is really derived from an adjoining nerve cell and is passing to end in a ramification around the ganglion cell, or, again, it may be coiled helically around the nerve process which is issuing from the cell.
== In the cerebral cortex ==
Von Economo neurons, also known as spindle neurons, found in a few select parts of the cerebral cortex of apes and some other intelligent animals, possess a single axon and dendrite and as such have been described as bipolar.
== References ==
This article incorporates text in the public domain from page 722 of the 20th edition of Gray's Anatomy (1918) | Wikipedia/Bipolar_neuron |
A gamma motor neuron (γ motor neuron), also called gamma motoneuron, or fusimotor neuron, is a type of lower motor neuron that takes part in the process of muscle contraction, and represents about 30% of (Aγ) fibers going to the muscle. Like alpha motor neurons, their cell bodies are located in the anterior grey column of the spinal cord. They receive input from the reticular formation of the pons in the brainstem. Their axons are smaller than those of the alpha motor neurons, with a diameter of only 5 μm. Unlike the alpha motor neurons, gamma motor neurons do not directly adjust the lengthening or shortening of muscles. However, their role is important in keeping muscle spindles taut, thereby allowing the continued firing of alpha neurons, leading to muscle contraction. These neurons also play a role in adjusting the sensitivity of muscle spindles.
The presence of myelination in gamma motor neurons allows a conduction velocity of 4 to 24 meters per second, significantly faster than with non-myelinated axons but slower than in alpha motor neurons.
== General background of muscles ==
=== Muscle spindles ===
Muscle spindles are the sensory receptors located within muscles that allow communication to the spinal cord and brain with information of where the body is in space (proprioception) and how fast body limbs are moving with relation to space (velocity). They are mechanoreceptors in that they respond to stretch and are able to signal changes in muscle length. The sensitivity of detecting changes in muscle length are adjusted by fusimotor neurons – gamma and beta motor neurons. Muscle spindles can be made up of three different types of muscle fibers: dynamic nuclear bag fibers (bag1 fibers), static nuclear bag fibers (bag2 fibers), and nuclear chain fibers.
=== Types of lower motor neurons ===
Muscle spindles are innervated by both sensory neurons and motor neurons in order to provide proprioception and make the appropriate movements via firing of motor neurons. There are three types of lower motor neurons involved in muscle contraction: alpha motor neurons, gamma motor neurons, and beta motor neurons. Alpha motor neurons, the most abundant type, are used in the actual force for muscle contraction and therefore innervate extrafusal muscle fibers (muscle fibers outside of the muscle spindle). Gamma motor neurons, on the other hand, innervate only intrafusal muscle fibers (within the muscle spindle), whereas beta motor neurons, which are present in very low amounts, innervate both intrafusal and extrafusal muscle cells. Beta motor neurons have a conduction velocity greater than that of both other types of lower motor neurons, but there is little currently known about beta motor neurons. Alpha motor neurons are highly abundant and larger in size than gamma motor neurons.
== Alpha gamma co-activation ==
When the central nervous system sends out signals to alpha neurons to fire, signals are also sent to gamma motor neurons to do the same. This process maintains the tautness of muscle spindles and is called alpha gamma co-activation. The nuclei of spindle muscle cells are located in the middle of these spindles, but unlike extrafusal muscle fibers, the myofibril contractile apparatus of spindle fibers are located only at both ends of spindle. Efferent stimulation of the spindle by gamma motor neurons contracts the myofibrils, tautening the central region of spindle—which maintains the muscle spindle's sensitivity to muscle's length change.
Without gamma motor neurons, muscle spindles would be very loose as the muscle contracts more. This does not allow for muscle spindles to detect a precise amount of stretch since it is so limp. However, with alpha gamma co-activation and both alpha and gamma neurons firing, muscle fibers within the muscle spindles are pulled parallel to the extrafusal contraction causing the muscle movement. The firing of gamma motor neurons in sync with alpha motor neurons pulls muscle spindles from polar ends of the fibers as this is where gamma motor neurons innervate the muscle. The spindle is innervated by type Ia sensory fiber that go on to synapse with alpha motor neurons, completing the gamma-loop. The parallel pulling keeps muscle spindles taut and readily able to detect minute changes in stretch.
== Fusimotor system ==
The central nervous system controls muscle spindle sensitivity via the fusimotor system that consists of muscle spindles along with gamma motor neurons also called fusimotor neurons. Beta motor neurons innervate extrafusal as well as intrafusal muscle fibers, and are more specifically named skeletofusimotor neurons. Gamma motor neurons are the efferent (sending signals away from the central nervous system) part of the fusimotor system, whereas muscle spindles are the afferent part, as they send signals relaying information from muscles toward the spinal cord and brain.
== Gamma bias ==
Gamma bias is gamma motor neurons' consistent level of activity. Smaller neurons require a smaller amount of excitatory input to reach its threshold compared to larger neurons. Therefore, gamma motor neurons (smaller in size than alpha motor neurons) are more likely to fire than the larger alpha motor neurons. This creates a situation with relatively few alpha motor neurons firing but some gamma motor neurons constantly firing in conditions where muscle stretch or force is not occurring. The sensitivity of sensory endings (primary and secondary endings - Ia, II) of the muscle spindle are based on the level of gamma bias (i.e. how much background level of gamma motor neuron discharge is taking place.)
== Types ==
=== Static ===
Static gamma motor neurons innervate static nuclear bag fibers (bag2 fibers), a type of nuclear bag fiber and nuclear chain fibers. Both of these fiber types are part of the intrafusal muscle spindle fibers, where the static gamma motor neurons innervate onto. Nuclear chain fibers' nuclei are organized in longitudinal columns, which is where it gets its name from, whereas the nuclear bag fibers' nuclei are clumped in the midsection of the muscle spindle. There is approximately a 2:1 ratio of nuclear chain fibers to nuclear bag fibers. The static gamma motor neurons increase their firing, in response to an increase in magnitude of change in length and controls the static sensitivity of the stretch reflex. For this reason, this type of gamma motor neuron is mostly used in the maintenance of postures and slower movements such as lifting a box, rather than activities requiring rapid changes due to rapid change in muscle length.
=== Dynamic ===
Dynamic gamma motor neurons innervate the dynamic nuclear bag fibers (bag1 fibers), another type of nuclear bag fiber smaller than the static nuclear bag fibers. This type of gamma motor neuron can enhance the sensitivities of Ia sensory neurons. It is done so because the dynamic nuclear bag fibers, which are innervated by the dynamic gamma motor neurons, receive Ia sensory innervation. Furthermore, the firing of dynamic gamma motor neurons removes the slack in dynamic nuclear bags, bringing Ia fibers closer to the firing threshold. Dynamic gamma motor neurons alter muscle spindle sensitivity and increases its discharge in response to velocity, the rate of change, of muscle length rather than simply the magnitude as it is with static gamma motor neurons. Therefore, this type of gamma motor neuron can be used for activities requiring quick changes in muscle length to adjust such as balancing on a rail.
=== Effects of nuclear chain fibers ===
The effect of nuclear chain fibers on primary endings is to drive the discharge up to a frequency of around 60 Hz in a linear fashion, above which the discharge can become irregular. The activities of bag2 fibers show an initial sharp peak in discharge, which gets less as the receptor adapts. Bag2 fibers also reduce the dynamic sensitivity of the Ia afferent and sometimes also reduce the length sensitivity. Activation of bag1 fibers has the effect of increasing both the length sensitivity and the dynamic sensitivity of the primary ending.
It is believed that the secondary sensory endings serve to measure length and muscle contractions of nuclear chain fibers at the pole via the static γ-motoneurons both excite the ending and increase its length sensitivity. Bag1 and bag2 fibers receive very little innervation from secondary endings, and activation of these fibers has a minimal effect on the discharge of the secondary ending.
== Development ==
Gamma motor neurons develop similarly to alpha motor neurons at the beginning. They originate in the basal plate, which is the ventral portion of the neural tube in the developing embryo. Sonic hedgehog genes (Shh) are an important part of the development process that is secreted by the notochord creating gradients of concentrations. After the hedgehog genes, various other molecular markers and transcription factors play a role in differentiating motor neurons into the specific gamma motor neurons.
Gamma motor neurons, like all cells, express specific genetic markers at birth. Muscle spindle derived GDNF neurotrophic factors must also be present for postnatal survival. Wnt7A is a secreted signaling molecule selectively in gamma motor neurons by embryonic day 17.5 of mice. This is the earliest molecule present in gamma motor neurons that differentiates them from alpha motor neurons, illustrating the divergence of these two types of lower motor neurons.
In addition, serotonin receptor 1d (5-ht 1d) has been concluded to be a novel marker for gamma motor neurons enabling researchers to distinguish between the various types of lower motor neurons. Mice lacking this serotonin receptor 1d, displayed lower monosynaptic reflex (a reflex arc involving only a sensory and motor neuron), which may be caused by a reduced response to sensory stimulation in motor neurons. In addition, knockout mice without this serotonin receptor exhibited more coordination on a balance beam task, suggesting that less activation of motor neurons by Ia afferents during movement could reduce the unnecessary excess of muscle output.
Another distinguishing molecular marker of gamma motor neurons is transcription factor Err3. It is expressed at high levels in gamma motor neurons, but very little in alpha motor neurons. On the other hand, neuronal DNA binding protein NeuN, are present in significantly greater quantities in alpha motor neurons. Osteopontin, a protein also expressed in bones, hence the "osteo-" prefix, is a marker for alpha motor neurons. This in turn can provide scientists a way of eliminating gamma motor neurons if alpha motor neurons are of interest. One study in particular made this conclusion based on the fact that osteopontin was present in larger cell bodies, indicating the alpha motor neurons as they have larger cell bodies than gamma motor neurons.
== Muscle tone ==
Although muscles can be in a relaxed state, muscles have a general resting level of tension. This is termed muscle tone and is maintained by the motor neurons innervating the muscle. Its purpose is to maintain posture and assist in quicker movements, since if muscles were completely loose, then more neuronal firing would need to take place.
The amount of tension in the muscles depends primarily on the resting level discharge of alpha motor neurons and Ia spindle afferents. Gamma motor neurons are also involved through their action on intrafusal muscle fibers. The intrafusal muscle fibers control the resting level of the Ia afferent pathway, which in turn creates a steady level of alpha neuron activity.
Muscle tone can also be due to tonic discharge of gamma motor neurons. The activation to these neurons are mostly from the descending fibers of the facilitatory reticular formation. This leads to the stretching of muscle spindle, activation of alpha motor neurons and finally a partially contracted muscle. The cerebellum is the alpha-gamma motor neuron linkage . Therefore, with the cerebellum the muscle tension is maintained via alpha motor neurons as well as the gamma motor neurons.
== Abnormal activity ==
Hypotonia can be due to damage to alpha neurons or Ia afferents carrying sensory information to the alpha neurons. This creates a decrease in muscle tone. Opposite to this, hypertonia is caused by damage to descending pathways that terminate in the spinal cord. It increases muscle tone by increasing the total responsiveness of alpha motor neurons from its Ia sensory input.
Spasms can be caused by a disparity between how much alpha and gamma motor neurons are firing, i.e. too much gain of one or the other. The imbalance causes an inaccurate reading from muscle receptors in the muscle spindle. Therefore, the sensory neurons feeding back to the brain and spinal cord are misleading. For example, if a patient has over active gamma motor neurons, there will be a resistance to passive movement causing stiffness, also called spasticity. This is often found in individuals with damage to higher centers affecting the descending pathways. This can sometimes cause a gamma-bias (constant discharge of some gamma motor neurons) to be greater or less than usual. In the case for patients with excess gamma bias, the sensory endings within muscle spindles are discharging too frequently causing there to be more muscle activity than appropriate. Furthermore, this hyperactivity in the gamma spindle loop can cause spasticity.
Gamma motor neurons assist in keeping the muscle spindle taut, thus adjusting sensitivity. Therefore, if proper gamma motor neuronal firing does not occur, muscle movement can be adversely affected. Fine motor skills such as movements with the fingers and eyes are affected most, since any lack of tautness within the muscle spindle hinders its ability to detect the amount of stretch through the sensory endings. This means that the muscle will not be able to precisely move accordingly. Lesions controlling descending pathways in lower motor neurons to the upper limbs, can cause a loss in patient's ability to have fine movement control.
In clinical settings, it is possible to test whether someone has an abnormally low or high gamma gain simply by moving the patient's arm. Gamma gain is the process where acceleration, velocity, and length of muscle changes are scaled up equally, enabling more accurate movements to take place in the appropriate situation. If it is more difficult to bend a patient's arm at the elbow back and forth, then he/she has higher gamma gain while someone whose arm moves very easily will have lower gamma gain.
Oscilloscopes can be used to measure action potentials of an axon from a motor neuron in order to assess general muscle activity. Though it cannot distinguish alpha motor neurons from gamma motor neurons, it is useful in understanding whether one has abnormal motor neuron activity. With low rates of activity of the descending pathway, fewer and smaller motor neurons are activated, leading to a small amount of muscle force. This will appear on the oscilloscope as lower peaks on the y-axis.
== References ==
== External links ==
Motor+Neurons,+Gamma at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
"Search - Gamma Motor Neuron". Neuroscience Information Framework Project. Archived from the original on 2016-03-04. | Wikipedia/Gamma_motor_neuron |
A "red neuron" (acidophilic or "eosinophilic" neuron) is a pathological finding in neurons, generally of the central nervous system, indicative of acute neuronal injury and subsequent apoptosis or necrosis. Acidophilic neurons are often found in the first 12–24 hours after an ischemic injury such as a stroke. Since neurons are permanent cells, they are most susceptible to hypoxic injury. The red coloration is due to pyknosis or degradation of the nucleus and loss of Nissl bodies which are normally stained blue (basophilic) on hematoxylin & eosin staining (H&E stain). This leaves only the degraded proteins which stains red (eosinophilic). Acidophilic neurons also can be stained with acidic dyes other than eosin (e.g. acid fuchsin and light green yellowish).
== References == | Wikipedia/Red_neuron |
Von Economo neurons, also called spindle neurons, are a specific class of mammalian cortical neurons characterized by a large spindle-shaped soma (or body) gradually tapering into a single apical axon (the ramification that transmits signals) in one direction, with only a single dendrite (the ramification that receives signals) facing opposite. Other cortical neurons tend to have many dendrites, and the bipolar-shaped morphology of von Economo neurons is unique here.
Von Economo neurons are found in two very restricted regions in the brains of hominids (humans and other great apes): the anterior cingulate cortex (ACC) and the fronto-insular cortex (FI) (which each make up the salience network). In 2008, they were also found in the dorsolateral prefrontal cortex of humans. Von Economo neurons are also found in the brains of a number of cetaceans, African and Asian elephants, and to a lesser extent in macaque monkeys and raccoons. The appearance of von Economo neurons in distantly related clades suggests that they represent convergent evolution – specifically, as an adaptation to accommodate the increasing size of these distantly-related animals' brains.
Von Economo neurons were discovered and first described in 1925 by Austrian psychiatrist and neurologist Constantin von Economo (1876–1931).
== Function ==
Von Economo neurons are relatively large cells that may allow rapid communication across the relatively large brains of great apes, elephants, and cetaceans. Although rare in comparison to other neurons, von Economo neurons are abundant, and comparatively large, in humans; they are however three times as abundant in cetaceans.
== Evolutionary significance ==
The discovery of von Economo neurons in diverse whale species has led to the suggestion that they are "a possible obligatory neuronal adaptation in very large brains, permitting fast information processing and transfer along highly specific projections and that evolved in relation to emerging social behaviors.": 254 The apparent presence of these specialized neurons only in highly intelligent mammals may be an example of convergent evolution.
Their restriction among the primates to great apes leads to the hypothesis that they developed no earlier than 15–20 million years ago, prior to the divergence of orangutans from the African great apes. Recently, primitive forms of von Economo neurons have also been discovered in macaque monkey brains and raccoons.
== In the anterior cingulate cortex ==
In 1999, American neuroscientist John Allman and colleagues at the California Institute of Technology first published a report on von Economo neurons found in the anterior cingulate cortex (ACC) of hominids but not any other species. Neuronal volumes of ACC von Economo neurons were larger in humans and bonobos than the von Economo neurons of the chimpanzee, gorilla and orangutan.
Allman and his colleagues have delved beyond the level of brain infrastructure to investigate how von Economo neurons function at the superstructural level, focusing on their role as "air traffic controllers for emotions ... at the heart of the human social emotion circuitry, including a moral sense". Allman's team proposes that von Economo neurons help channel neural signals from deep within the cortex to relatively distant parts of the brain. Specifically, Allman's team found signals from the ACC are received in Brodmann's area 10, in the frontal polar cortex, where regulation of cognitive dissonance (disambiguation between alternatives) is thought to occur. According to Allman, this neural relay appears to convey motivation to act, and concerns the recognition of error. Self-control – and avoidance of error – is thus facilitated by the executive gatekeeping function of the ACC, as it regulates the interference patterns of neural signals between these two brain regions.
In humans, intense emotion activates the anterior cingulate cortex, as it relays neural signals transmitted from the amygdala (a primary processing center for emotions) to the frontal cortex, perhaps by functioning as a sort of lens to focus the complex texture of neural signal interference patterns. The ACC is also active during demanding tasks requiring judgement and discrimination and when errors are detected by an individual. During difficult tasks, or when experiencing intense love, anger, or lust, activation of the ACC increases. In brain imaging studies, the ACC has specifically been found to be active when mothers hear infants cry, underscoring its role in affording a heightened degree of social sensitivity.
The ACC is a relatively ancient cortical region and is involved with many autonomic functions, including motor and digestive functions, while also playing a role in the regulation of blood pressure and heart rate. Significant olfactory and gustatory capabilities of the ACC and fronto-insular cortex appear to have been usurped, during recent evolution, to serve enhanced roles related to higher cognition – ranging from planning and self-awareness to role-playing and deception. The diminished olfactory function of humans, compared with other primates, may be related to the fact that von Economo neurons located at crucial neural network hubs have only two dendrites rather than many, resulting in reduced neurological integration.
== In the fronto-insular cortex ==
At a Society for Neuroscience meeting in 2003, Allman reported on von Economo neurons his team found in another brain region, the fronto-insular cortex, a region which appears to have undergone significant evolutionary adaptations in mankind – perhaps as recently as 100,000 years ago.
This fronto-insular cortex is closely connected to the insula, a region that is roughly the size of a thumb in each hemisphere of the human brain. The insula and fronto-insular cortex are part of the insular cortex, wherein the elaborate circuitry associated with spatial awareness are found, and where self-awareness and the complexities of emotion are thought to be generated and experienced. Moreover, this region of the right hemisphere is crucial to navigation and perception of three-dimensional rotations.
== Concentrations ==
=== Anterior cingulate cortex ===
The largest number of ACC von Economo neurons are found in humans, fewer in the gracile great apes, and fewest in the robust great apes. In both humans and bonobos they are often found in clusters of 3 to 6 neurons. They are found in humans, chimpanzees, gorillas, orangutans, some cetaceans, and elephants.: 245 While total quantities of ACC von Economo neurons were not reported by Allman in his seminal research report (as they were in a later report describing their presence in the frontoinsular cortex, below), his team's initial analysis of the ACC layer V in hominids revealed an average of ~9 von Economo neurons per section for orangutans (rare, 0.6% of section cells), ~22 for gorillas (frequent, 2.3%), ~37 for chimpanzees (abundant, 3.8%), ~68 for bonobos (abundant/clusters, 4.8%), ~89 for humans (abundant/clusters, 5.6%).
=== Fronto-insular cortex ===
All of the primates examined had more von Economo neurons in the fronto-insula of the right hemisphere than in the left. In contrast to the higher number of von Economo neurons found in the ACC of the gracile bonobos and chimpanzees, the number of fronto-insular von Economo neurons was far higher in the cortex of robust gorillas (no data for orangutans was given). An adult human had 82,855 such cells, a gorilla had 16,710, a bonobo had 2,159, and a chimpanzee had a mere 1,808 – despite the fact that chimpanzees and bonobos are great apes most closely related to humans.
=== Dorsolateral prefrontal cortex ===
Von Economo neurons have been located in the dorsolateral prefrontal cortex of humans and elephants. In humans they have been observed in higher concentration in Brodmann area 9 (BA9) – mostly isolated, or in clusters of 2, while in Brodmann area 24 (BA24) they have been found mostly in clusters of 2–4.
== Clinical significance ==
Abnormal von Economo neuron development may be linked to several psychotic disorders, typically those characterized by distortions of reality, disturbances of thought, disturbances of language, and withdrawal from social contact. Altered von Economo neuron states have been implicated in both schizophrenia and autism, but research into these correlations remains at a very early stage. Frontotemporal dementia involves loss of mostly von Economo neurons. An initial study suggested that Alzheimer's disease specifically targeted von Economo neurons; this study was performed with end-stage Alzheimer brains in which cell destruction was widespread, but later it was found that Alzheimer's disease does not affect the von Economo neurons.
== See also ==
List of distinct cell types in the adult human body
== References ==
General References
Allman J, Hakeem A, Watson K (Aug 2002). "Two phylogenetic specializations in the human brain". Neuroscientist. 8 (4): 335–346. doi:10.1177/107385840200800409. PMID 12194502. S2CID 2427631.
== External links ==
TaipeiTimes.com – Know Thyself and Others
"Well-wired whales" Michael Balter (2006) ScienceNOW Daily News. 27 November
"Brain Cells for Socializing" Smithsonian, June 2009 | Wikipedia/Von_Economo_neuron |
Bioenergetics is a field in biochemistry and cell biology that concerns energy flow through living systems. This is an active area of biological research that includes the study of the transformation of energy in living organisms and the study of thousands of different cellular processes such as cellular respiration and the many other metabolic and enzymatic processes that lead to production and utilization of energy in forms such as adenosine triphosphate (ATP) molecules. That is, the goal of bioenergetics is to describe how living organisms acquire and transform energy in order to perform biological work. The study of metabolic pathways is thus essential to bioenergetics.
== Overview ==
Bioenergetics is the part of biochemistry concerned with the energy involved in making and breaking of chemical bonds in the molecules found in biological organisms. It can also be defined as the study of energy relationships and energy transformations and transductions in living organisms. The ability to harness energy from a variety of metabolic pathways is a property of all living organisms. Growth, development, anabolism and catabolism are some of the central processes in the study of biological organisms, because the role of energy is fundamental to such biological processes. Life is dependent on energy transformations; living organisms survive because of exchange of energy between living tissues/cells and the outside environment. Some organisms, such as autotrophs, can acquire energy from sunlight (through photosynthesis) without needing to consume nutrients and break them down. Other organisms, like heterotrophs, must intake nutrients from food to be able to sustain energy by breaking down chemical bonds in nutrients during metabolic processes such as glycolysis and the citric acid cycle. Importantly, as a direct consequence of the first law of thermodynamics, autotrophs and heterotrophs participate in a universal metabolic network—by eating autotrophs (plants), heterotrophs harness energy that was initially transformed by the plants during photosynthesis.
In a living organism, chemical bonds are broken and made as part of the exchange and transformation of energy. Energy is available for work (such as mechanical work) or for other processes (such as chemical synthesis and anabolic processes in growth), when weak bonds are broken and stronger bonds are made. The production of stronger bonds allows release of usable energy.
Adenosine triphosphate (ATP) is the main "energy currency" for organisms; the goal of metabolic and catabolic processes are to synthesize ATP from available starting materials (from the environment), and to break- down ATP (into adenosine diphosphate (ADP) and inorganic phosphate) by utilizing it in biological processes. In a cell, the ratio of ATP to ADP concentrations is known as the "energy charge" of the cell. A cell can use this energy charge to relay information about cellular needs; if there is more ATP than ADP available, the cell can use ATP to do work, but if there is more ADP than ATP available, the cell must synthesize ATP via oxidative phosphorylation.
Living organisms produce ATP from energy sources via oxidative phosphorylation. The terminal phosphate bonds of ATP are relatively weak compared with the stronger bonds formed when ATP is hydrolyzed (broken down by water) to adenosine diphosphate and inorganic phosphate. Here it is the thermodynamically favorable free energy of hydrolysis that results in energy release; the phosphoanhydride bond between the terminal phosphate group and the rest of the ATP molecule does not itself contain this energy. An organism's stockpile of ATP is used as a battery to store energy in cells. Utilization of chemical energy from such molecular bond rearrangement powers biological processes in every biological organism.
Living organisms obtain energy from organic and inorganic materials; i.e. ATP can be synthesized from a variety of biochemical precursors. For example, lithotrophs can oxidize minerals such as nitrates or forms of sulfur, such as elemental sulfur, sulfites, and hydrogen sulfide to produce ATP. In photosynthesis, autotrophs produce ATP using light energy, whereas heterotrophs must consume organic compounds, mostly including carbohydrates, fats, and proteins. The amount of energy actually obtained by the organism is lower than the amount present in the food; there are losses in digestion, metabolism, and thermogenesis.
Environmental materials that an organism intakes are generally combined with oxygen to release energy, although some nutrients can also be oxidized anaerobically by various organisms. The utilization of these materials is a form of slow combustion because the nutrients are reacted with oxygen (the materials are oxidized slowly enough that the organisms do not produce fire). The oxidation releases energy, which may evolve as heat or be used by the organism for other purposes, such as breaking chemical bonds.
== Types of reactions ==
An exergonic reaction is a spontaneous chemical reaction that releases energy. It is thermodynamically favored, indexed by a negative value of ΔG (Gibbs free energy). Over the course of a reaction, energy needs to be put in, and this activation energy drives the reactants from a stable state to a highly energetically unstable transition state to a more stable state that is lower in energy (see: reaction coordinate). The reactants are usually complex molecules that are broken into simpler products. The entire reaction is usually catabolic. The release of energy (called Gibbs free energy) is negative (i.e. −ΔG) because energy is released from the reactants to the products.
An endergonic reaction is an anabolic chemical reaction that consumes energy. It is the opposite of an exergonic reaction. It has a positive ΔG because it takes more energy to break the bonds of the reactant than the energy of the products offer, i.e. the products have weaker bonds than the reactants. Thus, endergonic reactions are thermodynamically unfavorable. Additionally, endergonic reactions are usually anabolic.
The free energy (ΔG) gained or lost in a reaction can be calculated as follows: ΔG = ΔH − TΔS
where ∆G = Gibbs free energy, ∆H = enthalpy, T = temperature (in kelvins), and ∆S = entropy.
== Examples of major bioenergetic processes ==
Glycolysis is the process of breaking down glucose into pyruvate, producing two molecules of ATP (per 1 molecule of glucose) in the process. When a cell has a higher concentration of ATP than ADP (i.e. has a high energy charge), the cell cannot undergo glycolysis, releasing energy from available glucose to perform biological work. Pyruvate is one product of glycolysis, and can be shuttled into other metabolic pathways (gluconeogenesis, etc.) as needed by the cell. Additionally, glycolysis produces reducing equivalents in the form of NADH (nicotinamide adenine dinucleotide), which will ultimately be used to donate electrons to the electron transport chain.
Gluconeogenesis is the opposite of glycolysis; when the cell's energy charge is low (the concentration of ADP is higher than that of ATP), the cell must synthesize glucose from carbon- containing biomolecules such as proteins, amino acids, fats, pyruvate, etc. For example, proteins can be broken down into amino acids, and these simpler carbon skeletons are used to build/ synthesize glucose.
The citric acid cycle is a process of cellular respiration in which acetyl coenzyme A, synthesized from pyruvate dehydrogenase, is first reacted with oxaloacetate to yield citrate. The remaining eight reactions produce other carbon-containing metabolites. These metabolites are successively oxidized, and the free energy of oxidation is conserved in the form of the reduced coenzymes FADH2 and NADH. These reduced electron carriers can then be re-oxidized when they transfer electrons to the electron transport chain.
Ketosis is a metabolic process where the body prioritizes ketone bodies, produced from fat, as its primary fuel source instead of glucose. This shift often occurs when glucose levels are low: during prolonged fasting, strenuous exercise, or specialized diets like ketogenic plans, the body may also adopt ketosis as an efficient alternative for energy production. This metabolic adaptation allows the body to conserve precious glucose for organs that depend on it, like the brain, while utilizing readily available fat stores for fuel.
Oxidative phosphorylation and the electron transport chain is the process where reducing equivalents such as NADPH, FADH2 and NADH can be used to donate electrons to a series of redox reactions that take place in electron transport chain complexes. These redox reactions take place in enzyme complexes situated within the mitochondrial membrane. These redox reactions transfer electrons "down" the electron transport chain, which is coupled to the proton motive force. This difference in proton concentration between the mitochondrial matrix and inner membrane space is used to drive ATP synthesis via ATP synthase.
Photosynthesis, another major bioenergetic process, is the metabolic pathway used by plants in which solar energy is used to synthesize glucose from carbon dioxide and water. This reaction takes place in the chloroplast. After glucose is synthesized, the plant cell can undergo photophosphorylation to produce ATP.
== Additional information ==
During energy transformations in living systems, order and organization must be compensated by releasing energy which will increase entropy of the surrounding.
Organisms are open systems that exchange materials and energy with the environment. They are never at equilibrium with the surrounding.
Energy is spent to create and maintain order in the cells, and surplus energy and other simpler by-products are released to create disorder such that there is an increase in entropy of the surrounding.
In a reversible process, entropy remains constant where as in an irreversible process (more common to real-world scenarios), entropy tends to increase.
During phase changes (from solid to liquid, or to gas), entropy increases because the number of possible arrangements of particles increases.
If ∆G<0, the chemical reaction is spontaneous and favourable in that direction.
If ∆G=0, the reactants and products of chemical reaction are at equilibrium.
If ∆G>0, the chemical reaction is non-spontaneous and unfavorable in that direction.
∆G is not an indicator for velocity or rate of chemical reaction at which equilibrium is reached. It depends on amount of enzyme and energy activation.
== Reaction coupling ==
Is the linkage of chemical reactions in a way that the product of one reaction becomes the substrate of another reaction.
This allows organisms to utilize energy and resources efficiently. For example, in cellular respiration, energy released by the breakdown of glucose is coupled in the synthesis of ATP.
== Cotransport ==
In August 1960, Robert K. Crane presented for the first time his discovery of the sodium-glucose cotransport as the mechanism for intestinal glucose absorption. Crane's discovery of cotransport was the first ever proposal of flux coupling in biology and was the most important event concerning carbohydrate absorption in the 20th century.
== Chemiosmotic theory ==
One of the major triumphs of bioenergetics is Peter D. Mitchell's chemiosmotic theory of how protons in aqueous solution function in the production of ATP in cell organelles such as mitochondria. This work earned Mitchell the 1978 Nobel Prize for Chemistry. Other cellular sources of ATP such as glycolysis were understood first, but such processes for direct coupling of enzyme activity to ATP production are not the major source of useful chemical energy in most cells. Chemiosmotic coupling is the major energy producing process in most cells, being utilized in chloroplasts and several single celled organisms in addition to mitochondria.
== Binding Change Mechanism ==
The binding change mechanism, proposed by Paul Boyer and John E. Walker, who were awarded the Nobel Prize in Chemistry in 1997, suggests that ATP synthesis is linked to a conformational change in ATP synthase. This change is triggered by the rotation of the gamma subunit. ATP synthesis can be achieved through several mechanisms. The first mechanism postulates that the free energy of the proton gradient is utilized to alter the conformation of polypeptide molecules in the ATP synthesis active centers. The second mechanism suggests that the change in the conformational state is also produced by the transformation of mechanical energy into chemical energy using biological mechanoemission, a process in which energy or particles (e.g., photons or ions) are emitted from a mitochondrion when it is mechanically stimulated.
== Energy balance ==
Energy homeostasis is the homeostatic control of energy balance – the difference between energy obtained through food consumption and energy expenditure – in living systems.
== See also ==
Bioenergetic systems
Cellular respiration
Photosynthesis
ATP synthase
Active transport
Myosin
Exercise physiology
Table of standard Gibbs free energies
== References ==
== Further reading ==
Juretic, D., 2021. Bioenergetics: a bridge across life and universe. CRC Press.
Lehninger, Albert L (1971). Bioenergetics: The Molecular Basis of Biological Energy Transformations (2nd ed.). Addison-Wesley. ISBN 0-8053-6103-0.
Nicholls, David G.; Ferguson, Stuart J. (2002). Bioenergetics (3rd ed.). Academic Press. ISBN 0-12-518124-8.
Green DE, Zande HD (September 1981). "Universal energy principle of biological systems and the unity of bioenergetics". Proc. Natl. Acad. Sci. U.S.A. 78 (9): 5344–7. Bibcode:1981PNAS...78.5344G. doi:10.1073/pnas.78.9.5344. PMC 348741. PMID 6946475.
== External links ==
The Molecular & Cellular Bioenergetics Gordon Research Conference (see).
American Society of Exercise Physiologists | Wikipedia/Energy_metabolism |
An artificial neuron is a mathematical function conceived as a model of a biological neuron in a neural network. The artificial neuron is the elementary unit of an artificial neural network.
The design of the artificial neuron was inspired by biological neural circuitry. Its inputs are analogous to excitatory postsynaptic potentials and inhibitory postsynaptic potentials at neural dendrites, or activation. Its weights are analogous to synaptic weights, and its output is analogous to a neuron's action potential which is transmitted along its axon.
Usually, each input is separately weighted, and the sum is often added to a term known as a bias (loosely corresponding to the threshold potential), before being passed through a nonlinear function known as an activation function. Depending on the task, these functions could have a sigmoid shape (e.g. for binary classification), but they may also take the form of other nonlinear functions, piecewise linear functions, or step functions. They are also often monotonically increasing, continuous, differentiable, and bounded. Non-monotonic, unbounded, and oscillating activation functions with multiple zeros that outperform sigmoidal and ReLU-like activation functions on many tasks have also been recently explored. The threshold function has inspired building logic gates referred to as threshold logic; applicable to building logic circuits resembling brain processing. For example, new devices such as memristors have been extensively used to develop such logic.
The artificial neuron activation function should not be confused with a linear system's transfer function.
An artificial neuron may be referred to as a semi-linear unit, Nv neuron, binary neuron, linear threshold function, or McCulloch–Pitts (MCP) neuron, depending on the structure used.
Simple artificial neurons, such as the McCulloch–Pitts model, are sometimes described as "caricature models", since they are intended to reflect one or more neurophysiological observations, but without regard to realism. Artificial neurons can also refer to artificial cells in neuromorphic engineering that are similar to natural physical neurons.
== Basic structure ==
For a given artificial neuron
k
{\displaystyle k}
, let there be
m
+
1
{\displaystyle m+1}
inputs with signals
x
0
{\displaystyle x_{0}}
through
x
m
{\displaystyle x_{m}}
and weights
w
k
0
{\displaystyle w_{k0}}
through
w
k
m
{\displaystyle w_{km}}
. Usually, the input
x
0
{\displaystyle x_{0}}
is assigned the value +1, which makes it a bias input with
w
k
0
=
b
k
{\displaystyle w_{k0}=b_{k}}
. This leaves only
m
{\displaystyle m}
actual inputs to the neuron:
x
1
{\displaystyle x_{1}}
to
x
m
{\displaystyle x_{m}}
.
The output of the
k
{\displaystyle k}
-th neuron is:
y
k
=
φ
(
∑
j
=
0
m
w
k
j
x
j
)
{\displaystyle y_{k}=\varphi \left(\sum _{j=0}^{m}w_{kj}x_{j}\right)}
,
where
φ
{\displaystyle \varphi }
(phi) is the activation function.
The output is analogous to the axon of a biological neuron, and its value propagates to the input of the next layer, through a synapse. It may also exit the system, possibly as part of an output vector.
It has no learning process as such. Its activation function weights are calculated, and its threshold value is predetermined.
== McCulloch–Pitts (MCP) neuron ==
An MCP neuron is a kind of restricted artificial neuron which operates in discrete time-steps. Each has zero or more inputs, and are written as
x
1
,
.
.
.
,
x
n
{\displaystyle x_{1},...,x_{n}}
. It has one output, written as
y
{\displaystyle y}
. Each input can be either excitatory or inhibitory. The output can either be quiet or firing. An MCP neuron also has a threshold
b
∈
{
0
,
1
,
2
,
.
.
.
}
{\displaystyle b\in \{0,1,2,...\}}
.
In an MCP neural network, all the neurons operate in synchronous discrete time-steps of
t
=
0
,
1
,
2
,
3
,
.
.
.
{\displaystyle t=0,1,2,3,...}
. At time
t
+
1
{\displaystyle t+1}
, the output of the neuron is
y
(
t
+
1
)
=
1
{\displaystyle y(t+1)=1}
if the number of firing excitatory inputs is at least equal to the threshold, and no inhibitory inputs are firing;
y
(
t
+
1
)
=
0
{\displaystyle y(t+1)=0}
otherwise.
Each output can be the input to an arbitrary number of neurons, including itself (i.e., self-loops are possible). However, an output cannot connect more than once with a single neuron. Self-loops do not cause contradictions, since the network operates in synchronous discrete time-steps.
As a simple example, consider a single neuron with threshold 0, and a single inhibitory self-loop. Its output would oscillate between 0 and 1 at every step, acting as a "clock".
Any finite state machine can be simulated by a MCP neural network. Furnished with an infinite tape, MCP neural networks can simulate any Turing machine.
== Biological models ==
Artificial neurons are designed to mimic aspects of their biological counterparts. However a significant performance gap exists between biological and artificial neural networks. In particular single biological neurons in the human brain with oscillating activation function capable of learning the XOR function have been discovered.
Dendrites – in biological neurons, dendrites act as the input vector. These dendrites allow the cell to receive signals from a large (>1000) number of neighboring neurons. As in the above mathematical treatment, each dendrite is able to perform "multiplication" by that dendrite's "weight value." The multiplication is accomplished by increasing or decreasing the ratio of synaptic neurotransmitters to signal chemicals introduced into the dendrite in response to the synaptic neurotransmitter. A negative multiplication effect can be achieved by transmitting signal inhibitors (i.e. oppositely charged ions) along the dendrite in response to the reception of synaptic neurotransmitters.
Soma – in biological neurons, the soma acts as the summation function, seen in the above mathematical description. As positive and negative signals (exciting and inhibiting, respectively) arrive in the soma from the dendrites, the positive and negative ions are effectively added in summation, by simple virtue of being mixed together in the solution inside the cell's body.
Axon – the axon gets its signal from the summation behavior which occurs inside the soma. The opening to the axon essentially samples the electrical potential of the solution inside the soma. Once the soma reaches a certain potential, the axon will transmit an all-in signal pulse down its length. In this regard, the axon behaves as the ability for us to connect our artificial neuron to other artificial neurons.
Unlike most artificial neurons, however, biological neurons fire in discrete pulses. Each time the electrical potential inside the soma reaches a certain threshold, a pulse is transmitted down the axon. This pulsing can be translated into continuous values. The rate (activations per second, etc.) at which an axon fires converts directly into the rate at which neighboring cells get signal ions introduced into them. The faster a biological neuron fires, the faster nearby neurons accumulate electrical potential (or lose electrical potential, depending on the "weighting" of the dendrite that connects to the neuron that fired). It is this conversion that allows computer scientists and mathematicians to simulate biological neural networks using artificial neurons which can output distinct values (often from −1 to 1).
=== Encoding ===
Research has shown that unary coding is used in the neural circuits responsible for birdsong production. The use of unary in biological networks is presumably due to the inherent simplicity of the coding. Another contributing factor could be that unary coding provides a certain degree of error correction.
== Physical artificial cells ==
There is research and development into physical artificial neurons – organic and inorganic.
For example, some artificial neurons can receive and release dopamine (chemical signals rather than electrical signals) and communicate with natural rat muscle and brain cells, with potential for use in BCIs/prosthetics.
Low-power biocompatible memristors may enable construction of artificial neurons which function at voltages of biological action potentials and could be used to directly process biosensing signals, for neuromorphic computing and/or direct communication with biological neurons.
Organic neuromorphic circuits made out of polymers, coated with an ion-rich gel to enable a material to carry an electric charge like real neurons, have been built into a robot, enabling it to learn sensorimotorically within the real world, rather than via simulations or virtually. Moreover, artificial spiking neurons made of soft matter (polymers) can operate in biologically relevant environments and enable the synergetic communication between the artificial and biological domains.
== History ==
The first artificial neuron was the Threshold Logic Unit (TLU), or Linear Threshold Unit, first proposed by Warren McCulloch and Walter Pitts in 1943 in A logical calculus of the ideas immanent in nervous activity. The model was specifically targeted as a computational model of the "nerve net" in the brain. As an activation function, it employed a threshold, equivalent to using the Heaviside step function. Initially, only a simple model was considered, with binary inputs and outputs, some restrictions on the possible weights, and a more flexible threshold value. Since the beginning it was already noticed that any Boolean function could be implemented by networks of such devices, what is easily seen from the fact that one can implement the AND and OR functions, and use them in the disjunctive or the conjunctive normal form.
Researchers also soon realized that cyclic networks, with feedbacks through neurons, could define dynamical systems with memory, but most of the research concentrated (and still does) on strictly feed-forward networks because of the smaller difficulty they present.
One important and pioneering artificial neural network that used the linear threshold function was the perceptron, developed by Frank Rosenblatt. This model already considered more flexible weight values in the neurons, and was used in machines with adaptive capabilities. The representation of the threshold values as a bias term was introduced by Bernard Widrow in 1960 – see ADALINE.
In the late 1980s, when research on neural networks regained strength, neurons with more continuous shapes started to be considered. The possibility of differentiating the activation function allows the direct use of the gradient descent and other optimization algorithms for the adjustment of the weights. Neural networks also started to be used as a general function approximation model. The best known training algorithm called backpropagation has been rediscovered several times but its first development goes back to the work of Paul Werbos.
== Types of activation function ==
The activation function of a neuron is chosen to have a number of properties which either enhance or simplify the network containing the neuron. Crucially, for instance, any multilayer perceptron using a linear activation function has an equivalent single-layer network; a non-linear function is therefore necessary to gain the advantages of a multi-layer network.
Below,
u
{\displaystyle u}
refers in all cases to the weighted sum of all the inputs to the neuron, i.e. for
n
{\displaystyle n}
inputs,
u
=
∑
i
=
1
n
w
i
x
i
{\displaystyle u=\sum _{i=1}^{n}w_{i}x_{i}}
where
w
{\displaystyle w}
is a vector of synaptic weights and
x
{\displaystyle x}
is a vector of inputs.
=== Step function ===
The output
y
{\displaystyle y}
of this activation function is binary, depending on whether the input meets a specified threshold,
θ
{\displaystyle \theta }
(theta). The "signal" is sent, i.e. the output is set to 1, if the activation meets or exceeds the threshold.
y
=
{
1
if
u
≥
θ
0
if
u
<
θ
{\displaystyle y={\begin{cases}1&{\text{if }}u\geq \theta \\0&{\text{if }}u<\theta \end{cases}}}
This function is used in perceptrons, and appears in many other models. It performs a division of the space of inputs by a hyperplane. It is specially useful in the last layer of a network, intended for example to perform binary classification of the inputs.
=== Linear combination ===
In this case, the output unit is simply the weighted sum of its inputs, plus a bias term. A number of such linear neurons perform a linear transformation of the input vector. This is usually more useful in the early layers of a network. A number of analysis tools exist based on linear models, such as harmonic analysis, and they can all be used in neural networks with this linear neuron. The bias term allows us to make affine transformations to the data.
=== Sigmoid ===
A fairly simple nonlinear function, the sigmoid function such as the logistic function also has an easily calculated derivative, which can be important when calculating the weight updates in the network. It thus makes the network more easily manipulable mathematically, and was attractive to early computer scientists who needed to minimize the computational load of their simulations. It was previously commonly seen in multilayer perceptrons. However, recent work has shown sigmoid neurons to be less effective than rectified linear neurons. The reason is that the gradients computed by the backpropagation algorithm tend to diminish towards zero as activations propagate through layers of sigmoidal neurons, making it difficult to optimize neural networks using multiple layers of sigmoidal neurons.
=== Rectifier ===
In the context of artificial neural networks, the rectifier or ReLU (Rectified Linear Unit) is an activation function defined as the positive part of its argument:
f
(
x
)
=
x
+
=
max
(
0
,
x
)
,
{\displaystyle f(x)=x^{+}=\max(0,x),}
where
x
{\displaystyle x}
is the input to a neuron. This is also known as a ramp function and is analogous to half-wave rectification in electrical engineering. This activation function was first introduced to a dynamical network by Hahnloser et al. in a 2000 paper in Nature with strong biological motivations and mathematical justifications. It has been demonstrated for the first time in 2011 to enable better training of deeper networks, compared to the widely used activation functions prior to 2011, i.e., the logistic sigmoid (which is inspired by probability theory; see logistic regression) and its more practical counterpart, the hyperbolic tangent.
A commonly used variant of the ReLU activation function is the Leaky ReLU which allows a small, positive gradient when the unit is not active:
f
(
x
)
=
{
x
if
x
>
0
,
a
x
otherwise
.
{\displaystyle f(x)={\begin{cases}x&{\text{if }}x>0,\\ax&{\text{otherwise}}.\end{cases}}}
where
x
{\displaystyle x}
is the input to the neuron and
a
{\displaystyle a}
is a small positive constant (set to 0.01 in the original paper).
== Pseudocode algorithm ==
The following is a simple pseudocode implementation of a single Threshold Logic Unit (TLU) which takes Boolean inputs (true or false), and returns a single Boolean output when activated. An object-oriented model is used. No method of training is defined, since several exist. If a purely functional model were used, the class TLU below would be replaced with a function TLU with input parameters threshold, weights, and inputs that returned a Boolean value.
class TLU defined as:
data member threshold : number
data member weights : list of numbers of size X
function member fire(inputs : list of booleans of size X) : boolean defined as:
variable T : number
T ← 0
for each i in 1 to X do
if inputs(i) is true then
T ← T + weights(i)
end if
end for each
if T > threshold then
return true
else:
return false
end if
end function
end class
== See also ==
Binding neuron
Connectionism
== References ==
== Further reading ==
== External links ==
Artifical [sic] neuron mimicks function of human cells
McCulloch-Pitts Neurons (Overview) | Wikipedia/Artificial_neuron |
An anaxonic neuron is a type of neuron where there is no axon or it cannot be differentiated from the dendrites. Unlike typical neurons that possess a single axon transmitting signals away from the cell body, anaxonic neurons have processes that are all morphologically similar. Being loyal to the etymology of anaxonic there are two types of anaxonic neurons in the human nervous system, the undifferentiated anaxonic neuron where the axon cannot be differentiated from the dendrites, and the unipolar brush cell (UBC), that has no axon and only a dendritic arbour. This structural peculiarity suggests specialized roles in neural circuits, particularly in modulating and integrating information rather than transmitting it over long distances.
== Morphological Characteristics ==
Anaxonic neurons are characterized by their symmetrical appearance, with multiple processes radiating from the cell body. These processes are indistinct in function, lacking the clear demarcation between axons and dendrites seen in other neuron types. This morphology implies that anaxonic neurons are primarily involved in local circuit processing, where signal integration and modulation occur without the need for long-range transmission.
== Location ==
They are found in the brain and retina, in the latter location it is found as the amacrine cell and retina horizontal cells. They are also found in invertebrates.
== Functional Roles ==
=== Signal Integration ===
Due to their structure, anaxonic neurons are believed to play a crucial role in integrating synaptic inputs within local neural circuits.They act as non-spiking interneurons. Their processes can receive and modulate signals from multiple sources, allowing for complex processing of information before it is relayed to other neurons. The National Institutes of Health BRAIN Initiative supports research into neural recording and modulation, aiming to develop tools that can elucidate the functions of various neuron types, including those involved in local circuit integration.
=== Inhibitory Modulation ===
Anaxonic neurons are often associated with Inhibitory control functions within neural networks. By releasing inhibitory neurotransmitters, they can modulate the activity of neighboring neurons, contributing to the fine-tuning of neural responses and preventing excessive excitation. Research funded by the NIH has highlighted the importance of inhibitory synapses in maintaining the balance of neural activity, which is essential for processes such as memory consolidation during sleep.
== Clinical Implications ==
Anaxonic neurons, particularly those resembling axo-axonic cells (AACs), play a vital role in regulating neuronal excitability by modulating the activity of the axon initial segment (AIS) of pyramidal neurons. These neurons form synapses directly at the AIS, where they exert strong inhibitory influence through GABAergic transmission. The functional integrity of these connections is essential for maintaining balanced neural activity. Research has shown that mutations affecting the γ2 subunit of GABA<sub>A</sub> receptors - which are highly concentrated at AIS synapses - can significantly reduce inhibitory efficacy. This leads to increased neuronal excitability and susceptibility to epileptogenesis, highlighting the critical role of anaxonic inhibitory neurons in seizure control.
=== Neural Injury and Inhibitory Dysregulation ===
Following traumatic brain injury, structural and functional changes occur in inhibitory interneurons, including those with anaxonic morphology (biology). A key pathological feature observed post-injury is the reduction of brain-derived neurotrophic factor (BDNF), which is essential for the maintenance and plasticity of GABAergic neurons. The decline in BDNF availability leads to regressive changes in interneuronal axonal terminals and dendritic complexity, ultimately impairing their inhibitory capabilities. A study on rodent models found that these deficits in GABAergic transmission can create a hyperexcitable neural environment, further predisposing the injured brain to the development of epilepsy.
Strategies aimed at enhancing GABAergic function - either through pharmalogical modulation of GABA<sub>A</sub> receptor subunits or trophic support via BDNF - could restore inhibitory balance and reduce seizure susceptibility. Continued exploration of these avenues, particularly within the context of post-traumatic and genetic epilepsies, may provide novel insights into how maintaining or restoring anaxonic neuron function contributes to neural homeostasis.
== See also ==
Interneuron
Unipolar neuron
Pseudounipolar neuron
Bipolar neuron
Multipolar neuron
== References == | Wikipedia/Anaxonic_neuron |
A pseudounipolar neuron is a type of neuron which has one extension from its cell body. This type of neuron contains an axon that has split into two branches. They develop embryologically as bipolar in shape, and are thus termed pseudounipolar instead of unipolar.
== Structure ==
A pseudounipolar neuron has one axon that projects from the cell body for relatively a very short distance, before splitting into two branches. Pseudounipolar neurons are sensory neurons that have no dendrites, the branched axon serving both functions. The peripheral branch extends from the cell body to organs in the periphery including skin, joints and muscles, and the central branch extends from the cell body to the spinal cord.
=== In the dorsal root ganglia ===
The cell body of a pseudounipolar neuron is located within a dorsal root ganglion. The axon leaves the cell body (and out of the dorsal root ganglion) into the dorsal root, where it splits into two branches. The central branch goes to the dorsal columns of the spinal cord, where it forms synapses with other neurons. The peripheral branch travels through the distal dorsal root into the spinal nerve all the way until skin, joint, and muscle.
=== In most sensory ganglia of cranial nerves ===
Pseudounipolar neurons are found in the sensory ganglia of most cranial nerves.
Specifically the:
trigeminal ganglion
geniculate ganglion
superior ganglion of the glossopharyngeal nerve
inferior ganglion of the glossopharyngeal nerve
superior ganglion of the vagus nerve
inferior ganglion of the vagus nerve
Pseudounipolar neurons in cranial nerve sensory ganglia synapse in the main sensory trigeminal nucleus, spinal trigeminal nucleus or solitary nucleus.
While the vestibulocochlear nerve has two ganglia associated with it (spiral ganglion and vestibular ganglion), both contain bipolar neurons, not pseudounipolar.
=== In the mesencephalic nucleus ===
The mesencephalic nucleus is made up of pseudounipolar neurons which migrated into the brainstem during embryological development. It is the only location in the central nervous system where the cell bodies of pseudounipolar neurons are found.
== Function ==
All pseudounipolar neurons are sensory neurons. The ones found in the dorsal root ganglia, and majority of those in cranial nerve sensory ganglia carry information about touch, vibration, proprioception, pain and temperature.
Pseudounipolar neurons in the geniculate ganglion, inferior ganglion of the glossopharyngeal nerve and inferior ganglion of the vagus nerve also carry information about taste from taste buds.
Some of the pseudounipolar neurons in the inferior ganglion of the glossopharyngeal nerve carry information from the carotid body and carotid sinus.
The pseudounipolar neurons in the mesencephalic nucleus carry proprioceptive information from the muscle of mastication.
== See also ==
Bipolar neuron
Multipolar neuron
Unipolar neuron
== References == | Wikipedia/Pseudounipolar_neuron |
Von Economo neurons, also called spindle neurons, are a specific class of mammalian cortical neurons characterized by a large spindle-shaped soma (or body) gradually tapering into a single apical axon (the ramification that transmits signals) in one direction, with only a single dendrite (the ramification that receives signals) facing opposite. Other cortical neurons tend to have many dendrites, and the bipolar-shaped morphology of von Economo neurons is unique here.
Von Economo neurons are found in two very restricted regions in the brains of hominids (humans and other great apes): the anterior cingulate cortex (ACC) and the fronto-insular cortex (FI) (which each make up the salience network). In 2008, they were also found in the dorsolateral prefrontal cortex of humans. Von Economo neurons are also found in the brains of a number of cetaceans, African and Asian elephants, and to a lesser extent in macaque monkeys and raccoons. The appearance of von Economo neurons in distantly related clades suggests that they represent convergent evolution – specifically, as an adaptation to accommodate the increasing size of these distantly-related animals' brains.
Von Economo neurons were discovered and first described in 1925 by Austrian psychiatrist and neurologist Constantin von Economo (1876–1931).
== Function ==
Von Economo neurons are relatively large cells that may allow rapid communication across the relatively large brains of great apes, elephants, and cetaceans. Although rare in comparison to other neurons, von Economo neurons are abundant, and comparatively large, in humans; they are however three times as abundant in cetaceans.
== Evolutionary significance ==
The discovery of von Economo neurons in diverse whale species has led to the suggestion that they are "a possible obligatory neuronal adaptation in very large brains, permitting fast information processing and transfer along highly specific projections and that evolved in relation to emerging social behaviors.": 254 The apparent presence of these specialized neurons only in highly intelligent mammals may be an example of convergent evolution.
Their restriction among the primates to great apes leads to the hypothesis that they developed no earlier than 15–20 million years ago, prior to the divergence of orangutans from the African great apes. Recently, primitive forms of von Economo neurons have also been discovered in macaque monkey brains and raccoons.
== In the anterior cingulate cortex ==
In 1999, American neuroscientist John Allman and colleagues at the California Institute of Technology first published a report on von Economo neurons found in the anterior cingulate cortex (ACC) of hominids but not any other species. Neuronal volumes of ACC von Economo neurons were larger in humans and bonobos than the von Economo neurons of the chimpanzee, gorilla and orangutan.
Allman and his colleagues have delved beyond the level of brain infrastructure to investigate how von Economo neurons function at the superstructural level, focusing on their role as "air traffic controllers for emotions ... at the heart of the human social emotion circuitry, including a moral sense". Allman's team proposes that von Economo neurons help channel neural signals from deep within the cortex to relatively distant parts of the brain. Specifically, Allman's team found signals from the ACC are received in Brodmann's area 10, in the frontal polar cortex, where regulation of cognitive dissonance (disambiguation between alternatives) is thought to occur. According to Allman, this neural relay appears to convey motivation to act, and concerns the recognition of error. Self-control – and avoidance of error – is thus facilitated by the executive gatekeeping function of the ACC, as it regulates the interference patterns of neural signals between these two brain regions.
In humans, intense emotion activates the anterior cingulate cortex, as it relays neural signals transmitted from the amygdala (a primary processing center for emotions) to the frontal cortex, perhaps by functioning as a sort of lens to focus the complex texture of neural signal interference patterns. The ACC is also active during demanding tasks requiring judgement and discrimination and when errors are detected by an individual. During difficult tasks, or when experiencing intense love, anger, or lust, activation of the ACC increases. In brain imaging studies, the ACC has specifically been found to be active when mothers hear infants cry, underscoring its role in affording a heightened degree of social sensitivity.
The ACC is a relatively ancient cortical region and is involved with many autonomic functions, including motor and digestive functions, while also playing a role in the regulation of blood pressure and heart rate. Significant olfactory and gustatory capabilities of the ACC and fronto-insular cortex appear to have been usurped, during recent evolution, to serve enhanced roles related to higher cognition – ranging from planning and self-awareness to role-playing and deception. The diminished olfactory function of humans, compared with other primates, may be related to the fact that von Economo neurons located at crucial neural network hubs have only two dendrites rather than many, resulting in reduced neurological integration.
== In the fronto-insular cortex ==
At a Society for Neuroscience meeting in 2003, Allman reported on von Economo neurons his team found in another brain region, the fronto-insular cortex, a region which appears to have undergone significant evolutionary adaptations in mankind – perhaps as recently as 100,000 years ago.
This fronto-insular cortex is closely connected to the insula, a region that is roughly the size of a thumb in each hemisphere of the human brain. The insula and fronto-insular cortex are part of the insular cortex, wherein the elaborate circuitry associated with spatial awareness are found, and where self-awareness and the complexities of emotion are thought to be generated and experienced. Moreover, this region of the right hemisphere is crucial to navigation and perception of three-dimensional rotations.
== Concentrations ==
=== Anterior cingulate cortex ===
The largest number of ACC von Economo neurons are found in humans, fewer in the gracile great apes, and fewest in the robust great apes. In both humans and bonobos they are often found in clusters of 3 to 6 neurons. They are found in humans, chimpanzees, gorillas, orangutans, some cetaceans, and elephants.: 245 While total quantities of ACC von Economo neurons were not reported by Allman in his seminal research report (as they were in a later report describing their presence in the frontoinsular cortex, below), his team's initial analysis of the ACC layer V in hominids revealed an average of ~9 von Economo neurons per section for orangutans (rare, 0.6% of section cells), ~22 for gorillas (frequent, 2.3%), ~37 for chimpanzees (abundant, 3.8%), ~68 for bonobos (abundant/clusters, 4.8%), ~89 for humans (abundant/clusters, 5.6%).
=== Fronto-insular cortex ===
All of the primates examined had more von Economo neurons in the fronto-insula of the right hemisphere than in the left. In contrast to the higher number of von Economo neurons found in the ACC of the gracile bonobos and chimpanzees, the number of fronto-insular von Economo neurons was far higher in the cortex of robust gorillas (no data for orangutans was given). An adult human had 82,855 such cells, a gorilla had 16,710, a bonobo had 2,159, and a chimpanzee had a mere 1,808 – despite the fact that chimpanzees and bonobos are great apes most closely related to humans.
=== Dorsolateral prefrontal cortex ===
Von Economo neurons have been located in the dorsolateral prefrontal cortex of humans and elephants. In humans they have been observed in higher concentration in Brodmann area 9 (BA9) – mostly isolated, or in clusters of 2, while in Brodmann area 24 (BA24) they have been found mostly in clusters of 2–4.
== Clinical significance ==
Abnormal von Economo neuron development may be linked to several psychotic disorders, typically those characterized by distortions of reality, disturbances of thought, disturbances of language, and withdrawal from social contact. Altered von Economo neuron states have been implicated in both schizophrenia and autism, but research into these correlations remains at a very early stage. Frontotemporal dementia involves loss of mostly von Economo neurons. An initial study suggested that Alzheimer's disease specifically targeted von Economo neurons; this study was performed with end-stage Alzheimer brains in which cell destruction was widespread, but later it was found that Alzheimer's disease does not affect the von Economo neurons.
== See also ==
List of distinct cell types in the adult human body
== References ==
General References
Allman J, Hakeem A, Watson K (Aug 2002). "Two phylogenetic specializations in the human brain". Neuroscientist. 8 (4): 335–346. doi:10.1177/107385840200800409. PMID 12194502. S2CID 2427631.
== External links ==
TaipeiTimes.com – Know Thyself and Others
"Well-wired whales" Michael Balter (2006) ScienceNOW Daily News. 27 November
"Brain Cells for Socializing" Smithsonian, June 2009 | Wikipedia/Spindle_neuron |
A unipolar neuron is a neuron in which only one process, called a neurite, extends from the cell body. The neurite then branches to form dendritic and axonal processes. Most neurons in the central nervous systems of invertebrates, including insects, are unipolar. The cell bodies of invertebrate unipolar neurons are often located around the edges of the neuropil, in the so-called cell-body rind.
Most neurons in the central nervous systems of vertebrates, including mammals, are multipolar. In multipolar neurons, multiple processes extend from the cell body including dendrites and axons. Some neurons in the vertebrate brain have a unipolar morphology: a notable example is the unipolar brush cell, found in the cerebellum and granule region of the dorsal cochlear nucleus.
A third morphological class, bipolar neurons, extend just one axon and dendritic process from the cell body. Examples of bipolar neurons include most invertebrate sensory neurons and bipolar cells of the vertebrate retina.
Some vertebrate sensory neurons are classified as pseudounipolar. Pseudounipolar neurons initially develop as bipolar cells, but at some point the two processes that extend from the cell body fuse to form a single neurite. The pseudounipolar neuron's axon then splits into two branches. Sensory neurons with cell bodies in the dorsal root ganglia of the vertebrate spinal cord are pseudo-unipolar: one branch projects to the periphery (to sensory receptors in the skin, joints, and muscle), the other to the spinal cord.
== References ==
Martin, John Harry (2003). Neuroanatomy. McGraw-Hill Professional. ISBN 0-07-138183-X.
Bullock, Theodore H.; G. Adrian Horridge (1965). Structure and Function in the Nervous Systems of Invertebrates: Volume II. W. H. Freeman. | Wikipedia/Unipolar_neuron |
A motor neuron (or motoneuron), also known as efferent neuron is a neuron whose cell body is located in the motor cortex, brainstem or the spinal cord, and whose axon (fiber) projects to the spinal cord or outside of the spinal cord to directly or indirectly control effector organs, mainly muscles and glands. There are two types of motor neuron – upper motor neurons and lower motor neurons. Axons from upper motor neurons synapse onto interneurons in the spinal cord and occasionally directly onto lower motor neurons. The axons from the lower motor neurons are efferent nerve fibers that carry signals from the spinal cord to the effectors. Types of lower motor neurons are alpha motor neurons, beta motor neurons, and gamma motor neurons.
A single motor neuron may innervate many muscle fibres and a muscle fibre can undergo many action potentials in the time taken for a single muscle twitch. Innervation takes place at a neuromuscular junction and twitches can become superimposed as a result of summation or a tetanic contraction. Individual twitches can become indistinguishable, and tension rises smoothly eventually reaching a plateau.
Although the word "motor neuron" suggests that there is a single kind of neuron that controls movement, this is not the case. Indeed, upper and lower motor neurons—which differ greatly in their origins, synapse locations, routes, neurotransmitters, and lesion characteristics—are included in the same classification as "motor neurons." Essentially, motor neurons, also known as motoneurons, are made up of a variety of intricate, finely tuned circuits found throughout the body that innervate effector muscles and glands to enable both voluntary and involuntary motions. Two motor neurons come together to form a two-neuron circuit. While lower motor neurons start in the spinal cord and go to innervate muscles and glands all throughout the body, upper motor neurons originate in the cerebral cortex and travel to the brain stem or spinal cord. It is essential to comprehend the distinctions between upper and lower motor neurons as well as the routes they follow in order to effectively detect these neuronal injuries and localise the lesions.
== Development ==
Motor neurons begin to develop early in embryonic development, and motor function continues to develop well into childhood. In the neural tube cells are specified to either the rostral-caudal axis or ventral-dorsal axis. The axons of motor neurons begin to appear in the fourth week of development from the ventral region of the ventral-dorsal axis (the basal plate). This homeodomain is known as the motor neural progenitor domain (pMN). Transcription factors here include Pax6, OLIG2, Nkx-6.1, and Nkx-6.2, which are regulated by sonic hedgehog (Shh). The OLIG2 gene being the most important due to its role in promoting Ngn2 expression, a gene that causes cell cycle exiting as well as promoting further transcription factors associated with motor neuron development.
Further specification of motor neurons occurs when retinoic acid, fibroblast growth factor, Wnts, and TGFb, are integrated into the various Hox transcription factors. There are 13 Hox transcription factors and along with the signals, determine whether a motor neuron will be more rostral or caudal in character. In the spinal column, Hox 4-11 sort motor neurons to one of the five motor columns.
== Anatomy and physiology ==
=== Upper motor neurons ===
Upper motor neurons originate in the motor cortex located in the precentral gyrus. The cells that make up the primary motor cortex are Betz cells, which are giant pyramidal cells. The axons of these cells descend from the cortex to form the corticospinal tract. Corticomotorneurons project from the primary cortex directly onto motor neurons in the ventral horn of the spinal cord. Their axons synapse on the spinal motor neurons of multiple muscles as well as on spinal interneurons. They are unique to primates and it has been suggested that their function is the adaptive control of the hands including the relatively independent control of individual fingers. Corticomotorneurons have so far only been found in the primary motor cortex and not in secondary motor areas.
=== Nerve tracts ===
Nerve tracts are bundles of axons as white matter, that carry action potentials to their effectors. In the spinal cord these descending tracts carry impulses from different regions. These tracts also serve as the place of origin for lower motor neurons. There are seven major descending motor tracts to be found in the spinal cord:
Lateral corticospinal tract
Rubrospinal tract
Lateral reticulospinal tract
Vestibulospinal tract
Medial reticulospinal tract
Tectospinal tract
Anterior corticospinal tract
=== Lower motor neurons ===
Lower motor neurons are those that originate in the spinal cord and directly or indirectly innervate effector targets. The target of these neurons varies, but in the somatic nervous system the target will be some sort of muscle fiber. There are three primary categories of lower motor neurons, which can be further divided in sub-categories.
According to their targets, motor neurons are classified into three broad categories:
Somatic motor neurons
Special visceral motor neurons
General visceral motor neurons
==== Somatic motor neurons ====
Somatic motor neurons originate in the central nervous system, project their axons to skeletal muscles (such as the muscles of the limbs, abdominal, and intercostal muscles), which are involved in locomotion. The three types of these neurons are the alpha efferent neurons, beta efferent neurons, and gamma efferent neurons. They are called efferent to indicate the flow of information from the central nervous system (CNS) to the periphery.
Alpha motor neurons innervate extrafusal muscle fibers, which are the main force-generating component of a muscle. Their cell bodies are in the ventral horn of the spinal cord and they are sometimes called ventral horn cells. A single motor neuron may synapse with 150 muscle fibers on average. The motor neuron and all of the muscle fibers to which it connects is a motor unit. Motor units are split up into 3 categories:
Slow (S) motor units stimulate small muscle fibers, which contract very slowly and provide small amounts of energy but are very resistant to fatigue, so they are used to sustain muscular contraction, such as keeping the body upright. They gain their energy via oxidative means and hence require oxygen. They are also called red fibers.
Fast fatiguing (FF) motor units stimulate larger muscle groups, which apply large amounts of force but fatigue very quickly. They are used for tasks that require large brief bursts of energy, such as jumping or running. They gain their energy via glycolytic means and hence do not require oxygen. They are called white fibers.
Fast fatigue-resistant motor units stimulate moderate-sized muscles groups that do not react as fast as the FF motor units, but can be sustained much longer (as implied by the name) and provide more force than S motor units. These use both oxidative and glycolytic means to gain energy.
In addition to voluntary skeletal muscle contraction, alpha motor neurons also contribute to muscle tone, the continuous force generated by noncontracting muscle to oppose stretching. When a muscle is stretched, sensory neurons within the muscle spindle detect the degree of stretch and send a signal to the CNS. The CNS activates alpha motor neurons in the spinal cord, which cause extrafusal muscle fibers to contract and thereby resist further stretching. This process is also called the stretch reflex.
Beta motor neurons innervate intrafusal muscle fibers of muscle spindles, with collaterals to extrafusal fibres. There are two types of beta motor neurons: Slow Contracting- These innervate extrafusal fibers. Fast Contracting- These innervate intrafusal fibers.
Gamma motor neurons innervate intrafusal muscle fibers found within the muscle spindle. They regulate the sensitivity of the spindle to muscle stretching. With activation of gamma neurons, intrafusal muscle fibers contract so that only a small stretch is required to activate spindle sensory neurons and the stretch reflex. There are two types of gamma motor neurons: Dynamic- These focus on Bag1 fibers and enhance dynamic sensitivity. Static- These focus on Bag2 fibers and enhance stretch sensitivity.
Regulatory factors of lower motor neurons
Size Principle – this relates to the soma of the motor neuron. This restricts larger neurons to receive a larger excitatory signal in order to stimulate the muscle fibers it innervates. By reducing unnecessary muscle fiber recruitment, the body is able to optimize energy consumption.
Persistent Inward Current (PIC) – recent animal study research has shown that constant flow of ions such as calcium and sodium through channels in the soma and dendrites influence the synaptic input. An alternate way to think of this is that the post-synaptic neuron is being primed before receiving an impulse.
After Hyper-polarization (AHP) – A trend has been identified that shows slow motor neurons to have more intense AHPs for a longer duration. One way to remember this is that slow muscle fibers can contract for longer, so it makes sense that their corresponding motor neurons fire at a slower rate.
==== Special visceral motor neurons ====
These are also known as branchial motor neurons, which are involved in facial expression, mastication, phonation, and swallowing. Associated cranial nerves are the oculomotor, abducens, trochlear, and hypoglossal nerves.
==== General visceral motor neurons ====
These motor neurons indirectly innervate cardiac muscle and smooth muscles of the viscera ( the muscles of the arteries): they synapse onto neurons located in ganglia of the autonomic nervous system (sympathetic and parasympathetic), located in the peripheral nervous system (PNS), which themselves directly innervate visceral muscles (and also some gland cells).
In consequence, the motor command of skeletal and branchial muscles is monosynaptic involving only one motor neuron, either somatic or branchial, which synapses onto the muscle. Comparatively, the command of visceral muscles is disynaptic involving two neurons: the general visceral motor neuron, located in the CNS, synapses onto a ganglionic neuron, located in the PNS, which synapses onto the muscle.
All vertebrate motor neurons are cholinergic, that is, they release the neurotransmitter acetylcholine. Parasympathetic ganglionic neurons are also cholinergic, whereas most sympathetic ganglionic neurons are noradrenergic, that is, they release the neurotransmitter noradrenaline. (see Table)
=== Neuromuscular junctions ===
A single motor neuron may innervate many muscle fibres and a muscle fibre can undergo many action potentials in the time taken for a single muscle twitch. As a result, if an action potential arrives before a twitch has completed, the twitches can superimpose on one another, either through summation or a tetanic contraction. In summation, the muscle is stimulated repetitively such that additional action potentials coming from the somatic nervous system arrive before the end of the twitch. The twitches thus superimpose on one another, leading to a force greater than that of a single twitch. A tetanic contraction is caused by constant, very high frequency stimulation - the action potentials come at such a rapid rate that individual twitches are indistinguishable, and tension rises smoothly eventually reaching a plateau.
The interface between a motor neuron and muscle fiber is a specialized synapse called the neuromuscular junction. Upon adequate stimulation, the motor neuron releases a flood of acetylcholine (Ach) neurotransmitters from synaptic vesicles bound to the plasma membrane of the axon terminals. The acetylcholine molecules bind to postsynaptic receptors found within the motor end plate. Once two acetylcholine receptors have been bound, an ion channel is opened and sodium ions are allowed to flow into the cell. The influx of sodium into the cell causes depolarization and triggers a muscle action potential. T tubules of the sarcolemma are then stimulated to elicit calcium ion release from the sarcoplasmic reticulum. It is this chemical release that causes the target muscle fiber to contract.
In invertebrates, depending on the neurotransmitter released and the type of receptor it binds, the response in the muscle fiber could be either excitatory or inhibitory. For vertebrates, however, the response of a muscle fiber to a neurotransmitter can only be excitatory, in other words, contractile. Muscle relaxation and inhibition of muscle contraction in vertebrates is obtained only by inhibition of the motor neuron itself. This is how muscle relaxants work by acting on the motor neurons that innervate muscles (by decreasing their electrophysiological activity) or on cholinergic neuromuscular junctions, rather than on the muscles themselves.
=== Synaptic input to motor neurons ===
Motor neurons receive synaptic input from premotor neurons. Premotor neurons can be 1) spinal interneurons that have cell bodies in the spinal cord, 2) sensory neurons that convey information from the periphery and synapse directly onto motoneurons, 3) descending neurons that convey information from the brain and brainstem. The synapses can be excitatory, inhibitory, electrical, or neuromodulatory. For any given motor neuron, determining the relative contribution of different input sources is difficult, but advances in connectomics have made it possible for fruit fly motor neurons. In the fly, motor neurons controlling the legs and wings are found in the ventral nerve cord, homologous to the spinal cord. Fly motor neurons vary by over 100X in the total number of input synapses. However, each motor neuron gets similar fractions of its synapses from each premotor source: ~70% from neurons within the VNC, ~10% from descending neurons, ~3% from sensory neurons, and ~6% from VNC neurons that also send a process up to the brain. The remaining 10% of synapses come from neuronal fragments that are unidentified by current image segmentation algorithms and require additional manual segmentation to measure.
== See also ==
Betz cell
Central chromatolysis
Motor dysfunction
Motor neuron disease
Nerve
Sensory nerve
Motor nerve
Afferent nerve fiber
Efferent nerve fiber
Sensory neuron
== References ==
== Sources ==
Sherwood, L. (2001). Human Physiology: From Cells to Systems (4th ed.). Pacific Grove, CA: Brooks-Cole. ISBN 0-534-37254-6.
Marieb, E. N.; Mallatt, J. (1997). Human Anatomy (2nd ed.). Menlo Park, CA: Benjamin/Cummings. ISBN 0-8053-4068-8. | Wikipedia/Efferent_neuron |
Lhermitte–Duclos disease (LDD) (English: ), also called dysplastic gangliocytoma of the cerebellum (DGC), is a rare, slowly growing tumor of the cerebellum, a gangliocytoma sometimes considered to be a hamartoma, characterized by diffuse hypertrophy of the granular layer of the cerebellum. It is often associated with Cowden syndrome. It was described by Jacques Jean Lhermitte and P. Duclos in 1920.
== Signs and symptoms ==
Main clinical signs and symptoms include:
headache
movement disorders
tremor
visual disturbances
abnormal EEG
Diplopia
Patients with Lhermitte–Duclos disease and Cowden's syndrome may also have multiple growths on skin. The tumor, though benign, may cause neurological injury including abnormal movements.
MICROSCOPY (lhermitte-duclos disease)
1>Enlarged circumscribed cerebellar folia
2>internal granular layer is focally indistinct and is occupied by large ganglion cells
3>myelinated tracks in outer molecular layer
4>underlying white matter is atrophic and gliotic
== Pathophysiology ==
In Lhermitte–Duclos disease, the cerebellar cortex loses its normal architecture, and forms a hamartoma in the cerebellar hemispheres. The tumors are usually found on the left cerebellar hemisphere, and consist of abnormal hypertrophic ganglion cells that are somewhat similar to Purkinje cells. The amount of white matter in the cerebellum is diminished. Like cowden syndrome, patients with Lhermitte–Duclos disease often have mutations in enzymes involved in the Akt/PKB signaling pathway, which plays a role in cell growth. Mutation in PTEN gene on chromosome no. 10q leads to increased activity of AKT and mTOR pathways, and patients should be tested for these mutations because they may be at risk of other tumors and cancers in other parts of the body.
== Diagnosis ==
== Treatment ==
Treatment is not needed in the asymptomatic patient. Symptomatic patients may benefit from surgical debulking of the tumor. Complete tumor removal is not usually needed and can be difficult due to the tumor location.
== Epidemiology ==
Lhermitte–Duclos disease is a rare entity; approximately 222 cases of LDD have been reported in medical literature. Symptoms of the disease most commonly manifest in the third and fourth decades of life, although it may onset at any age. Men and women are equally affected, and there is not any apparent geographical pattern.
== History ==
The disease was first described in 1920 by Lhermitte and Duclos.
== See also ==
Multiple hamartoma syndrome
List of cutaneous conditions
== References ==
== External links ==
Lhermitte-Duclos syndrome at Whonamedit?
MedPix: Lhermitte-Duclos — Radiology and Pathology | Wikipedia/Lhermitte–Duclos_disease |
Compartmental modelling of dendrites deals with multi-compartment modelling of the dendrites, to make the understanding of the electrical behavior of complex dendrites easier. Basically, compartmental modelling of dendrites is a very helpful tool to develop new biological neuron models. Dendrites are very important because they occupy the most membrane area in many of the neurons and give the neuron an ability to connect to thousands of other cells. Originally the dendrites were thought to have constant conductance and current but now it has been understood that they may have active Voltage-gated ion channels, which influences the firing properties of the neuron and also the response of neuron to synaptic inputs. Many mathematical models have been developed to understand the electric behavior of the dendrites. Dendrites tend to be very branchy and complex, so the compartmental approach to understand the electrical behavior of the dendrites makes it very useful.
== Introduction ==
Compartmental modelling is a very natural way of modelling dynamical systems that have certain inherent properties with conservation principles. The compartmental modelling is an elegant way, a state space formulation to elegantly capture the dynamical systems that are governed by the conservation laws. Whether it is the conservation of mass, energy, fluid flow or information flow. Basically, they are models whose state variables tend to be non-negative (such as mass, concentrations, energy). So the equations for mass balance, energy, concentration or fluid flow can be written. It ultimately goes down to networks in which the brain is the largest of them all, just like Avogadro number, very large amount of molecules that are interconnected. The brain has very interesting interconnections. On a microscopic level thermodynamics is virtually impossible to understand but from a macroscopic view we see that these follow some universal laws. In the same way brain has numerous interconnections, which is almost impossible to write a differential equation for.
General observations about how the brain functions can be made by looking at the first and second thermodynamic laws, which are universal laws. Brain is a very large-scale interconnected system; the neurons have to somehow behave like the chemical reaction system, so, it has to somehow obey the chemical thermodynamic laws. This approach may lead to more generalized model of brain.
== Multiple compartments ==
Complicated dendritic structures can be treated as multiple compartments interconnected. The dendrites are divided into small compartments and they are linked together as shown in the figure.
It is assumed that the compartment is isopotential and spatially uniform in its properties. Membrane non-uniformity such as diameter changes, and voltage differences are occurred in between the compartments but not inside them.
An example of a simple two-compartment model:
Consider a two-compartmental model with the compartments viewed as isopotential cylinders with radius
a
i
{\displaystyle a_{i}}
and length
L
i
{\displaystyle L_{i}}
.
V
i
{\displaystyle V_{i}}
is the membrane potential of ith compartment.
c
i
{\displaystyle c_{i}}
is the specific membrane capacitance.
r
M
i
{\displaystyle r_{Mi}}
is the specific membrane resistivity.
The total electrode current, assuming that the compartment has it, is given by
I
electrode
i
{\displaystyle I_{\text{electrode}}^{i}}
.
The longitudinal resistance is given by
r
L
{\displaystyle r_{L}}
.
Now according to the balance that should exist for each compartment, we can say
i
cap
i
+
i
ion
i
=
i
long
i
+
i
electrode
i
{\displaystyle i_{\text{cap}}^{i}+i_{\text{ion}}^{i}=i_{\text{long}}^{i}+i_{\text{electrode}}^{i}}
.....eq(1)
where
i
cap
i
{\displaystyle i_{\text{cap}}^{i}}
and
i
ion
i
{\displaystyle i_{\text{ion}}^{i}}
are the capacitive and ionic currents per unit area of ith compartment membrane. i.e. they can be given by
i
cap
i
=
c
i
d
V
i
d
t
{\displaystyle i_{\text{cap}}^{i}=c_{i}{\frac {dV_{i}}{dt}}}
and
i
ion
i
=
V
i
r
M
i
{\displaystyle i_{\text{ion}}^{i}={\frac {V_{i}}{r_{Mi}}}}
.....eq(2)
If we assume the resting potential is 0. Then to compute
i
long
i
{\displaystyle i_{\text{long}}^{i}}
, we need total axial resistance. As the compartments are simply cylinders we can say
R
long
=
r
L
L
1
2
π
a
1
2
+
r
L
L
2
2
π
a
2
2
{\displaystyle R_{\text{long}}={\frac {r_{L}L_{1}}{2\pi a_{1}^{2}}}+{\frac {r_{L}L_{2}}{2\pi a_{2}^{2}}}}
.....eq(3)
Using ohms law we can express current from ith to jth compartment as
i
long
1
=
g
1
,
2
(
V
2
−
V
1
)
{\displaystyle i_{\text{long}}^{1}=g_{1,2}(V_{2}-V_{1})}
and
i
long
2
=
g
2
,
1
(
V
1
−
V
2
)
{\displaystyle i_{\text{long}}^{2}=g_{2,1}(V_{1}-V_{2})}
.....eq(4)
The coupling terms
g
1
,
2
{\displaystyle g_{1,2}}
and
g
2
,
1
{\displaystyle g_{2,1}}
are obtained by inverting eq(3) and dividing by surface area of interest.
So we get
g
1
,
2
=
a
1
a
2
2
r
L
L
1
(
a
2
2
L
1
+
a
1
2
L
2
)
{\displaystyle g_{1,2}={\frac {a_{1}a_{2}^{2}}{r_{L}L_{1}(a_{2}^{2}L_{1}+a_{1}^{2}L_{2})}}}
and
g
2
,
1
=
a
2
a
1
2
r
L
L
1
(
a
1
2
L
2
+
a
2
2
L
1
)
{\displaystyle g_{2,1}={\frac {a_{2}a_{1}^{2}}{r_{L}L_{1}(a_{1}^{2}L_{2}+a_{2}^{2}L_{1})}}}
Finally,
i
electrode
I
=
I
electrode
i
A
i
{\displaystyle i_{\text{electrode}}^{I}={\frac {I_{\text{electrode}}^{i}}{A_{i}}}}
A
i
=
2
π
a
i
L
i
{\displaystyle A_{i}=2\pi a_{i}L_{i}}
is the surface area of the compartment i.
If we put all these together we get
c
1
d
V
1
d
t
+
V
1
r
M
1
=
g
1
,
2
(
V
2
−
V
1
)
+
I
electrode
1
A
1
{\displaystyle c_{1}{\frac {dV_{1}}{dt}}+{\frac {V_{1}}{r_{M1}}}=g_{1,2}(V_{2}-V_{1})+{\frac {I_{\text{electrode}}^{1}}{A_{1}}}}
c
2
d
V
2
d
t
+
V
2
r
M
2
=
g
2
,
1
(
V
1
−
V
2
)
+
I
electrode
2
A
2
{\displaystyle c_{2}{\frac {dV_{2}}{dt}}+{\frac {V_{2}}{r_{M2}}}=g_{2,1}(V_{1}-V_{2})+{\frac {I_{\text{electrode}}^{2}}{A_{2}}}}
.....eq(5)
If we use
r
1
=
1
/
g
1
,
2
{\displaystyle r_{1}=1/g_{1,2}}
and
r
2
=
1
/
g
2
,
1
{\displaystyle r_{2}=1/g_{2,1}}
then eq(5) will become
c
1
d
V
1
d
t
+
V
1
r
M
1
=
V
2
−
V
1
r
1
+
I
electrode
1
A
1
{\displaystyle c_{1}{\frac {dV_{1}}{dt}}+{\frac {V_{1}}{r_{M1}}}={\frac {V_{2}-V_{1}}{r_{1}}}+{\frac {I_{\text{electrode}}^{1}}{A_{1}}}}
c
2
d
V
2
d
t
+
V
2
r
M
2
=
V
1
−
V
2
r
2
+
I
electrode
2
A
2
{\displaystyle c_{2}{\frac {dV_{2}}{dt}}+{\frac {V_{2}}{r_{M2}}}={\frac {V_{1}-V_{2}}{r_{2}}}+{\frac {I_{\text{electrode}}^{2}}{A_{2}}}}
.....eq(6)
Now if we inject current in cell 1 only and each cylinder is identical then
r
1
=
r
2
≡
r
{\displaystyle r_{1}=r_{2}\equiv r}
Without loss in generality we can define
r
M
=
r
M
1
=
r
M
2
{\displaystyle r_{M}=r_{M1}=r_{M2}}
After some algebra we can show that
V
1
i
1
=
r
M
(
r
+
r
M
)
r
+
2
r
M
{\displaystyle {\frac {V_{1}}{i_{1}}}={\frac {r_{M}(r+r_{M})}{r+2r_{M}}}}
also
R
input,coupled
R
input,uncoupled
=
1
−
r
M
r
+
2
r
M
{\displaystyle {\frac {R_{\text{input,coupled}}}{R_{\text{input,uncoupled}}}}=1-{\frac {r_{M}}{r+2r_{M}}}}
i.e. the input resistance decreases. For increment in the potential, coupled system current should be greater than that is required for uncoupled system. This is because the second compartment drains some current.
Now, we can get a general compartmental model for a treelike structure and the equations are
C
j
d
V
j
d
t
=
−
V
j
R
j
+
∑
k
connected
j
V
k
−
V
j
R
j
k
+
I
j
{\displaystyle C_{j}{\frac {dV_{j}}{dt}}=-{\frac {V_{j}}{R_{j}}}+\sum _{k{\text{ connected }}j}{}{\frac {V_{k}-V_{j}}{R_{jk}}}+I_{j}}
=== Increased computational accuracy in multi-compartmental cable models ===
Input at the center
Each dendritic section is subdivided into segments, which are typically seen as uniform circular cylinders or tapered circular cylinders. In the traditional compartmental model, point process location is determined only to an accuracy of half segment length. This will make the model solution particularly sensitive to segment boundaries. The accuracy of the traditional approach for this reason is O(1/n) when a point current and synaptic input is present. Usually the trans-membrane current where the membrane potential is known is represented in the model at points, or nodes and is assumed to be at the center. The new approach partitions the effect of the input by distributing it to the boundaries of the segment. Hence any input is partitioned between the nodes at the proximal and distal boundaries of the segment. Therefore, this procedure makes sure that the solution obtained is not sensitive to small changes in location of these boundaries because it affects how the input is partitioned between the nodes. When these compartments are connected with continuous potentials and conservation of current at segment boundaries then a new compartmental model of a new mathematical form is obtained. This new approach also provides a model identical to the traditional model but an order more accurate. This model increases the accuracy and precision by an order of magnitude than that is achieved by point process input.
== Cable theory ==
Dendrites and axons are considered to be continuous (cable-like), rather than series of compartments.
== Some applications ==
=== Information processing ===
A theoretical framework along with a technological platform are provided by computational models to enhance the understanding of nervous system functions. There was a lot of advancement in the molecular and biophysical mechanisms underlying the neuronal activity. The same kind of advances have to be made in understanding the structure-functional relationship and rules followed by the information processing.
Previously a neuron used to be thought as a transistor. However, it is shown recently that morphology and ionic composition of different neurons provide the cell with enhanced computational capabilities. These abilities are far more advanced than those captured by a point neuron.
Some findings:
Different outputs given by the individual apical oblique dendrites of CA1 pyramidal neurons are linearly combined in the cell body. The outputs that come from these dendrites actually behave like individual computational units that use sigmoidal activation function to combine inputs.
The thin dendritic branches each act as a typical point neuron, which are capable of combining the incoming signals according to the thresholding non-linearity.
Considering the accuracy in prediction of different input patterns by a two-layer neural network, it is assumed that a simple mathematical equation can be used to describe the model. This allows the development of network models in which each neuron, instead of being modelled as a full blown compartmental cell, it is modelled as a simplified two layer neural network.
The firing pattern of the cell might contain the temporal information about incoming signals. For example, the delay between the two simulated pathways.
Single CA1 has a capability of encoding and transmitting spatio-temporal information on the incoming signals to the recipient cell.
Calcium-activated nonspecific cationic (CAN) mechanism is needed for giving constant activity and the synaptic stimulation alone does not induce persistent activity using the increasing conductance of NMDA mechanism. NMDA/ AMPA positively expands the range of persistent activity and negatively regulates the amount of CAN needed for constant activity.
=== Midbrain dopaminergic neuron ===
Movement, motivation, attention, neurological and psychiatric disorders and addictive behavior have a strong influence by Dopaminergic signalling.
The dopaminergic neurons have a low irregular basal firing frequency in 1–8 Hz range in vivo in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). This frequencies can dramatically increase in response to a cue predicting reward or unpredicted reward. The actions that preceded the reward are reinforced by this burst or phasic signal.
The low safety factor for action potential generation gives a result of low maximal steady frequencies. The transient initial frequency in response to depolarizing pulse is controlled by rate of Ca2+ accumulation in distal dendrites.
Results obtained from a mulch-compartmental model realistic with reconstructed morphology were similar. So, the salient contributions of the dendritic architecture have been captures by simpler model.
=== Mode locking ===
There are many important applications in neuroscience for Mode-locking response of excitable systems to periodic forcing. For example, The theta rhythm drives the spatially extended place cells in the hippocampus to generate a code giving information about spatial location. The role of neuronal dendrites in generating the response to periodic current injection can be explored by using a compartmental model (with linear dynamics for each compartment) coupled to an active soma model that generates action potentials.
Some findings:
The response of whole neuron model i.e. soma and dendrites, can be written in closed form. The response of the spatially extended model to periodic forcing is described by stroboscopic map. A Arnol'd tongue quasi-active model can be constructed with a linear stability analysis of the map with carefully treating the non-differentiability of soma model.
The shape of the tongues is influenced by the presence of the quasi-active membrane.
The windows in parameter space for chaotic behavior can be enlarged with the resonant dendritic membrane.
The response of the spatially extended neuron model to global forcing is different from that of point forcing.
=== Compartmental neural simulations with spatial adaptivity ===
The computational cost of the method scales not with the physical size of the system being simulated but with the amount of activity present in the simulation. Spatial adaptivity for certain problems reduces up to 80%.
=== Action potential (AP) initiation site ===
Establishing a unique site for AP initiation at the axon initial segment is no longer accepted. The APs can be initiated and conducted by different sub-regions of the neuron morphology, which widened the capabilities of individual neurons in computation.
Findings from a study of the Action Potential Initiation Site Along the Axosomatodendritic Axis of Neurons Using Compartmental Models:
Dendritic APs are initiated more effectively by synchronous spatially clustered inputs than equivalent disperse inputs.
The initiation site can also be determined by the average electrical distance from the dendritic input to the axon trigger zone, but it may be strongly modulated by the relative excitability of the two trigger zones and a number of factors.
=== A finite-state automaton model ===
Multi-neuron simulations with finite-state automaton model is capable of modelling the most important characteristics of neural membranes.
=== Constraining compartmental models ===
Can be done using extracellular action potential recordings
Can be done using Multiple Voltage Recordings and Genetic Algorithms
=== Multi-compartmental model of a CA1 pyramidal cell ===
To study changes in hippocampal excitability that result from aging-induced alterations in calcium-dependent membrane mechanisms, the multi-compartmental model of CA1 pyramidal cell can be used. We can model the aging-induced alterations in CA1 excitability can be with simple coupling mechanisms that selectively link specific types of calcium channels to specific calcium-dependent potassium channels.
=== Electrical compartmentalization ===
Spine Neck Plasticity Controls Postsynaptic Calcium Signals through Electrical Compartmentalization. The spine neck plasticity through a process of electrical compartmentalization can dynamically regulate Calcium influx into spines (a key trigger for synaptic plasticity).
=== Robust coding in motion-sensitive neurons ===
Different receptive fields in axons and dendrites underlie robust coding in motion-sensitive neurons.
=== Conductance-based neuron models ===
The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites.
== See also ==
Computational neuroscience
Dynamical system
Multi-compartment model
Connectionism
Neural network
Biological neuron models
Neural coding
Brain-computer interface
Neural engineering
Neuroinformatics
Mathematical model
Compartmental models in epidemiology
Physiologically-based pharmacokinetic modelling
== References ==
== External links ==
: Ted talk on supercomputing Archived 2014-02-11 at the Wayback Machine
: Laboratory of Biological Modelling
: Pharmacokinetics Modelling Tutorial
: Usefulness of two compartmental model in Pharmacokinetics
: Pharmacokinetics | Wikipedia/Compartmental_modelling_of_dendrites |
Pyramidal cells, or pyramidal neurons, are a type of multipolar neuron found in areas of the brain including the cerebral cortex, the hippocampus, and the amygdala. Pyramidal cells are the primary excitation units of the mammalian prefrontal cortex and the corticospinal tract. One of the main structural features of the pyramidal neuron is the conic shaped soma, or cell body, after which the neuron is named. Other key structural features of the pyramidal cell are a single axon, a large apical dendrite, multiple basal dendrites, and the presence of dendritic spines.
Pyramidal neurons are also one of two cell types where the characteristic sign, Negri bodies, are found in post-mortem rabies infection. Pyramidal neurons were first discovered and studied by Santiago Ramón y Cajal. Since then, studies on pyramidal neurons have focused on topics ranging from neuroplasticity to cognition.
== Structure ==
One of the main structural features of the pyramidal neuron is the conic shaped soma, or cell body, after which the neuron is named. Other key structural features of the pyramidal cell are a single axon, a large apical dendrite, multiple basal dendrites, and the presence of dendritic spines.
=== Apical dendrite ===
The apical dendrite rises from the apex of the pyramidal cell's soma. The apical dendrite is a single, long, thick dendrite that branches several times as distance from the soma increases and extends towards the cortical surface.
=== Basal dendrite ===
Basal dendrites arise from the base of the soma. The basal dendritic tree consists of three to five primary dendrites. As distance increases from the soma, the basal dendrites branch profusely.
Pyramidal cells are among the largest neurons in the brain. Both in humans and rodents, pyramidal cell bodies (somas) average around 20 μm in length. Pyramidal dendrites typically range in diameter from half a micrometer to several micrometers. The length of a single dendrite is usually several hundred micrometers. Due to branching, the total dendritic length of a pyramidal cell may reach several centimeters. The pyramidal cell's axon is often even longer and extensively branched, reaching many centimeters in total length.
=== Dendritic spines ===
Dendritic spines receive most of the excitatory impulses (EPSPs) that enter a pyramidal cell. Dendritic spines were first noted by Ramón y Cajal in 1888 by using Golgi's method. Ramón y Cajal was also the first person to propose the physiological role of increasing the receptive surface area of the neuron. The greater the pyramidal cell's surface area, the greater the neuron's ability to process and integrate large amounts of information. Dendritic spines are absent on the soma, while the number increases away from it. The typical apical dendrite in a rat has at least 3,000 dendritic spines. The average human apical dendrite is approximately twice the length of a rat's, so the number of dendritic spines present on a human apical dendrite could be as high as 6,000.
== Growth and development ==
=== Differentiation ===
Pyramidal specification occurs during early development of the cerebrum. Progenitor cells are committed to the neuronal lineage in the subcortical proliferative ventricular zone (VZ) and the subventricular zone (SVZ). Immature pyramidal cells undergo migration to occupy the cortical plate, where they further diversify. Endocannabinoids (eCBs) are one class of molecules that have been shown to direct pyramidal cell development and axonal pathfinding. Transcription factors such as Ctip2 and Sox5 have been shown to contribute to the direction in which pyramidal neurons direct their axons.
=== Early postnatal development ===
Pyramidal cells in rats have been shown to undergo many rapid changes during early postnatal life. Between postnatal days 3 and 21, pyramidal cells have been shown to double the size of the soma, increase the length of the apical dendrite fivefold, and increase basal dendrite length thirteen-fold. Other changes include the lowering of the membrane's resting potential, reduction of membrane resistance, and an increase in the peak values of action potentials.
== Signaling ==
Like dendrites in most other neurons, the dendrites are generally the input areas of the neuron, while the axon is the neuron's output. Both axons and dendrites are highly branched. The large amount of branching allows the neuron to send and receive signals to and from many different neurons.
Pyramidal neurons, like other neurons, have numerous voltage-gated ion channels. In pyramidal cells, there is an abundance of Na+, Ca2+, and K+ channels in the dendrites, and some channels in the soma. Ion channels within pyramidal cell dendrites have different properties from the same ion channel type within the pyramidal cell soma. Voltage-gated Ca2+ channels in pyramidal cell dendrites are activated by subthreshold EPSPs and by back-propagating action potentials. The extent of back-propagation of action potentials within pyramidal dendrites depends upon the K+ channels. K+ channels in pyramidal cell dendrites provide a mechanism for controlling the amplitude of action potentials.
The ability of pyramidal neurons to integrate information depends on the number and distribution of the synaptic inputs they receive. A single pyramidal cell receives about 30,000 excitatory inputs and 1700 inhibitory (IPSPs) inputs. Excitatory (EPSPs) inputs terminate exclusively on the dendritic spines, while inhibitory (IPSPs) inputs terminate on dendritic shafts, the soma, and even the axon. Pyramidal neurons can be excited by the neurotransmitter glutamate, and inhibited by the neurotransmitter GABA.
=== Firing classifications ===
Pyramidal neurons have been classified into different subclasses based upon their firing responses to 400-1000 millisecond current pulses. These classification are RSad, RSna, and IB neurons.
==== RSad ====
RSad pyramidal neurons, or adapting regular spiking neurons, fire with individual action potentials (APs), which are followed by a hyperpolarizing afterpotential. The afterpotential increases in duration which creates spike frequency adaptation (SFA) in the neuron.
==== RSna ====
RSna pyramidal neurons, or non-adapting regular spiking neurons, fire a train of action potentials after a pulse. These neurons show no signs of adaptation.
==== IB ====
IB pyramidal neurons, or intrinsically bursting neurons, respond to threshold pulses with a burst of two to five rapid action potentials. IB pyramidal neurons show no adaptation.
=== Molecular classifications ===
There are several studies showing that morphological and electric pyramidal cells properties could be deduced from gene expression measured by single cell sequencing. Several studies are proposing that single cell classifications in mouse and human neurons based on gene expression could explain various neuronal properties . Neuronal types in these classifications are split into excitatory, inhibitory and hundreds of corresponding sub-types. For example, pyramidal cells of layer 2-3 in human are classified as FREM3 type and often have a high amount of Ih-current generated by HCN-channel.
== Function ==
=== Corticospinal tract ===
Pyramidal neurons are the primary neural cell type in the corticospinal tract. Normal motor control depends on the development of connections between the axons in the corticospinal tract and the spinal cord. Pyramidal cell axons follow cues such as growth factors to make specific connections. With proper connections, pyramidal cells take part in the circuitry responsible for vision guided motor function.
=== Cognition ===
Pyramidal neurons in the prefrontal cortex are implicated in cognitive ability. In mammals, the complexity of pyramidal cells increases from posterior to anterior brain regions. The degree of complexity of pyramidal neurons is likely linked to the cognitive capabilities of different anthropoid species. Pyramidal cells within the prefrontal cortex appear to be responsible for processing input from the primary auditory cortex, primary somatosensory cortex, and primary visual cortex, all of which process sensory modalities. These cells might also play a critical role in complex object recognition within the visual processing areas of the cortex. Relative to other species, the larger cell size and complexity of pyramidal neurons, along with certain patterns of cellular organization and function, correlates with the evolution of human cognition.
=== Memory and learning ===
The hippocampus's pyramidal cells are essential for certain types of memory and learning. They form synapses that aid in the integration of synaptic voltages throughout their complex dendritic trees through interactions with mossy fibers from granule cells. Since it affects the postsynaptic voltages produced by mossy fiber activation, the placement of thorny excrescences on basal and apical dendrites is important for memory formation. By enabling dynamic control of the sensitivity of CA3 pyramidal cells, this clustering of mossy fiber synapses on pyramidal cells may facilitate the initiation of somatic spikes.
The interactions between pyramidal cells and an estimated 41 mossy fiber boutons, each originating from a unique granule cell, highlight the role of these boutons in information processing and synaptic connectivity, which are essential for memory and learning. Fundamentally, mossy fiber input is received by pyramidal cells in the hippocampus which integrate synaptic voltages within their dendritic architecture. The location of prickly protrusions and the clustering of synapses influence sensitivity and contribute to the processing of information pertaining to memory and learning.
== See also ==
Pyramidal tract
Chandelier cells - innervate initial segments of pyramidal axons
Rosehip neuron
== References ==
== External links ==
Pyramidal cell - Cell Centered Database
Diagram
Image
Diagram (as part of slideshow) Archived 2016-11-02 at the Wayback Machine | Wikipedia/Pyramidal_neuron |
In biochemistry, the DNA methyltransferase (DNA MTase, DNMT) family of enzymes catalyze the transfer of a methyl group to DNA. DNA methylation serves a wide variety of biological functions. All the known DNA methyltransferases use S-adenosyl methionine (SAM) as the methyl donor.
== Classification ==
=== Substrate ===
MTases can be divided into three different groups on the basis of the chemical reactions they catalyze:
m6A - those that generate N6-methyladenine EC 2.1.1.72
m4C - those that generate N4-methylcytosine EC 2.1.1.113
m5C - those that generate C5-methylcytosine EC 2.1.1.37
m6A and m4C methyltransferases are found primarily in prokaryotes (although recent evidence has suggested that m6A is abundant in eukaryotes). m5C methyltransferases are found in some lower eukaryotes, in most higher plants, and in animals beginning with the echinoderms.
The m6A methyltransferases (N-6 adenine-specific DNA methylase) (A-Mtase) are enzymes that specifically methylate the amino group at the C-6 position of adenines in DNA. They are found in the three existing types of bacterial restriction-modification systems (in type I system the A-Mtase is the product of the hsdM gene, and in type III it is the product of the mod gene). These enzymes are responsible for the methylation of specific DNA sequences in order to prevent the host from digesting its own genome via its restriction enzymes. These methylases have the same sequence specificity as their corresponding restriction enzymes. These enzymes contain a conserved motif Asp/Asn-Pro-Pro-Tyr/Phe in their N-terminal section, this conserved region could be involved in substrate binding or in the catalytic activity. The structure of N6-MTase TaqI (M.TaqI) has been resolved to 2.4 A. The molecule folds into 2 domains, an N-terminal catalytic domain, which contains the catalytic and cofactor binding sites, and comprises a central 9-stranded beta-sheet, surrounded by 5 helices; and a C-terminal DNA recognition domain, which is formed by 4 small beta-sheets and 8 alpha-helices. The N- and C-terminal domains form a cleft that accommodates the DNA substrate. A classification of N-MTases has been proposed, based on conserved motif (CM) arrangements. According to this classification, N6-MTases that have a DPPY motif (CM II) occurring after the FxGxG motif (CM I) are designated D12 class N6-adenine MTases. The type I restriction and modification system is composed of three polypeptides R, M and S. The M (hsdM) and S subunits together form a methyltransferase that methylates two adenine residues in complementary strands of a bipartite DNA recognition sequence. In the presence of the R subunit, the complex can also act as an endonuclease, binding to the same target sequence but cutting the DNA some distance from this site. Whether the DNA is cut or modified depends on the methylation state of the target sequence. When the target site is unmodified, the DNA is cut. When the target site is hemimethylated, the complex acts as a maintenance methyltransferase, modifying the DNA so that both strands become methylated. hsdM contains an alpha-helical domain at the N-terminus, the HsdM N-terminal domain.
Among the m6A methyltransferases (N-6 adenine-specific DNA methylase) there is a group of orphan MTases that do not participate in the bacterial restriction/methylation system. These enzymes have a regulatory role in gene expression and cell cycle regulation. EcoDam from E. coli and CcrM from Caulobacter crescentus are well characterized members of these family. More recently, CamA from Clostridioides difficile, was shown to play key functional roles in sporulation, biofilm formations and host-adaptation.
m4C methyltransferases (N-4 cytosine-specific DNA methylases) are enzymes that specifically methylate the amino group at the C-4 position of cytosines in DNA. Such enzymes are found as components of type II restriction-modification systems in prokaryotes. Such enzymes recognise a specific sequence in DNA and methylate a cytosine in that sequence. By this action they protect DNA from cleavage by type II restriction enzymes that recognise the same sequence
m5C methyltransferases (C-5 cytosine-specific DNA methylase) (C5 Mtase) are enzymes that specifically methylate the C-5 carbon of cytosines in DNA to produce C5-methylcytosine. In mammalian cells, cytosine-specific methyltransferases methylate certain CpG sequences, which are believed to modulate gene expression and cell differentiation. In bacteria, these enzymes are a component of restriction-modification systems and serve as valuable tools for the manipulation of DNA. The structure of HhaI methyltransferase (M.HhaI) has been resolved to 2.5 A: the molecule folds into 2 domains - a larger catalytic domain containing catalytic and cofactor binding sites, and a smaller DNA recognition domain.
Highly conserved DNA methyltransferases of the m4C, m5C, and m6A types have been reported, which appear as promising targets for the development of novel epigenetic inhibitors to fight bacterial virulence, antibiotic resistance, among other biomedical applications.
=== De novo vs. maintenance ===
De novo methyltransferases recognize something in the DNA that allows them to newly methylate cytosines. These are expressed mainly in early embryo development and they set up the pattern of methylation. De novo methyltransferases are also active when a signal-responsive cell, such as a neuron, needs to alter protein expression. As an example, when fear conditioning creates a new memory in a rat, 9.17% of the genes in the rat hippocampus neuron genome are differentially methylated.
Maintenance methyltransferases add methylation to DNA when one strand is already methylated. These work throughout the life of the organism to maintain the methylation pattern that had been established by the de novo methyltransferases.
== Mammalian ==
At least four differently active DNA methyltransferases have been identified in mammals. They are named DNMT1, two isoforms transcribed from the DNMT3a gene: DNMT3a1 and DNMT3a2, and DNMT3b. Recently, another enzyme DNMT3c has been discovered specifically expressed in the male germline in the mouse.
Manzo et al. observed differences in genomic binding of DNMT3a1, DNMT3a2 and DNMT3b. They found 3,970 regions exclusively enriched for DNMT3a1, 3,838 exclusively enriched for DNMT3a2 and 3,432 exclusively enriched for DNMT3b.
The DNMT enzymes are not only regulated in their methylating locations on the genome by where they bind to DNA, but they are also regulated by the post-translational modifications on the histone proteins of the nucleosomes around which the genomic DNA is wrapped (see Figures). Rose and Klose reviewed the relationship between DNA methylation and histone lysine methylation. For example, they indicated that H3K4me3 appears to block DNA methylation while H3K9me3 plays a role in promoting DNA methylation.
DNMT3L is a protein closely related to DNMT3a and DNMT3b in structure and critical for DNA methylation, but appears to be inactive on its own.
=== DNMT1 ===
DNMT1 is the most abundant DNA methyltransferase in mammalian cells, and considered to be the key maintenance methyltransferase in mammals. It predominantly methylates hemimethylated CpG di-nucleotides in the mammalian genome. The recognition motif for the human enzyme involves only three of the bases in the CpG dinucleotide pair: a C on one strand and CpG on the other. This relaxed substrate specificity requirement allows it to methylate unusual structures like DNA slippage intermediates at de novo rates that equal its maintenance rate. Like other DNA cytosine-5 methyltransferases the human enzyme recognizes flipped out cytosines in double stranded DNA and operates by the nucleophilic attack mechanism. In human cancer cells DNMT1 is responsible for both de novo and maintenance methylation of tumor suppressor genes. The enzyme is about 1,620 amino acids long. The first 1,100 amino acids constitute the regulatory domain of the enzyme, and the remaining residues constitute the catalytic domain. These are joined by Gly-Lys repeats. Both domains are required for the catalytic function of DNMT1.
DNMT1 has several isoforms, the somatic DNMT1, a splice variant (DNMT1b) and an oocyte-specific isoform (DNMT1o). DNMT1o is synthesized and stored in the cytoplasm of the oocyte and translocated to the cell nucleus during early embryonic development, while the somatic DNMT1 is always found in the nucleus of somatic tissue.
DNMT1 null mutant embryonic stem cells were viable and contained a small percentage of methylated DNA and methyltransferase activity. Mouse embryos homozygous for a deletion in Dnmt1 die at 10–11 days gestation.
=== TRDMT1 ===
Although this enzyme has strong sequence similarities with 5-methylcytosine methyltransferases of both prokaryotes and eukaryotes, in 2006, the enzyme was shown to methylate position 38 in aspartic acid transfer RNA and does not methylate DNA. The name for this methyltransferase has been changed from DNMT2 to TRDMT1 (tRNA aspartic acid methyltransferase 1) to better reflect its biological function. TRDMT1 is the first RNA cytosine methyltransferase to be identified in human cells.
=== DNMT3 ===
DNMT3 is a family of DNA methyltransferases that could methylate hemimethylated and unmethylated CpG at the same rate. The architecture of DNMT3 enzymes is similar to that of DNMT1, with a regulatory region attached to a catalytic domain. There are at least five members of the DNMT3 family: DNMT3a1, DNMT3a2, 3b, 3c and 3L.
DNMT3a1, DNMT3a2 and DNMT3b can mediate methylation of CpG sites in gene promoters, resulting in gene repression. These DNA methyltransferases can also methylate CpG sites within the coding regions of genes, where such methylation can increase gene transcription. Work with DNMT3a1 showed it preferentially localized to CpG islands bivalently marked by H3K4me3 (a transcription promoting mark) and H3K27me3 (a transcription repressive mark), coinciding with the promoters of many transcription factors. Work with DNMT3a2, in neurons, found that the DNA methylation changes caused by DNMT3a2 predominantly occur in intergenic and intronic regions. These intergenic and intronic DNA methylations were thought to likely regulate enhancer activity, alternative splicing or the expression of non-coding RNAs.
DNMT3a1 can co-localize with heterochromatin protein (HP1) and methyl-CpG-binding protein (MeCBP), among a number of other factors. They can also interact with DNMT1, which might be a co-operative event during DNA methylation. DNMT3a prefers CpG methylation to CpA, CpT, and CpC methylation, though there appears to be some sequence preference of methylation for DNMT3a and DNMT3b. DNMT3a methylates CpG sites at a rate much slower than DNMT1, but greater than DNMT3b.
The expression of DNMT3a2 differs from DNMT3a1 and DNMT3b because DNMT3a2 expression occurs in the pattern of an immediate early gene. DNMT3a2 is induced to express in neurons, for instance, by new neuronal activity. This may be of importance in establishing long-term memory. In a rat, high levels of new DNA methylations in neurons of the hippocampus occur after a memorable event is imposed on a rat, such as contextual fear conditioning. Bayraktar and Kreutz found that DNMT inhibitors, applied in the brain, prevented long-term memories from forming.
DNMT3L contains DNA methyltransferase motifs and is required for establishing maternal genomic imprints, despite being catalytically inactive. DNMT3L is expressed during gametogenesis when genomic imprinting takes place. The loss of DNMT3L leads to bi-allelic expression of genes normally not expressed by the maternal allele. DNMT3L interacts with DNMT3a and DNMT3b and co-localized in the nucleus. Though DNMT3L appears incapable of methylation, it may participate in transcriptional repression.
== Clinical significance ==
=== DNMT inhibitors ===
Because of the epigenetic effects of the DNMT family, some DNMT inhibitors are under investigation for treatment of some cancers:
Vidaza (azacitidine) in phase III trials for myelodysplastic syndromes and AML
Dacogen (decitabine) in phase III trials for AML and CML. EU approved in 2012 for AML.
guadecitabine, an experimental drug under development by Astex Pharmaceuticals and Otsuka Pharmaceutical. It failed to meet primary endpoints in a 2018 Phase III AML trial.
== See also ==
Methyltransferase
DNA methylation
PRMT4 pathway
Cell cycle regulated Methyltransferase
== References ==
== Further reading ==
== External links ==
Information about DNA methyltransferases and DNA methylation at epigeneticstation.com
Data for a DNA methyltransferase (DNMT) Antibody
DNA+Modification+Methyltransferases at the U.S. National Library of Medicine Medical Subject Headings (MeSH) | Wikipedia/DNA_methyltransferase |
Neurilemma (also known as neurolemma, sheath of Schwann, or Schwann's sheath) is the outermost nucleated cytoplasmic layer of Schwann cells (also called neurilemmocytes) that surrounds the axon of the neuron. It forms the outermost layer of the nerve fiber in the peripheral nervous system.
The neurilemma is underlain by the myelin sheath (also known as the medullary sheath). In the central nervous system, axons are myelinated by oligodendrocytes, thus lack neurilemma. The myelin sheaths of oligodendrocytes do not have neurilemma because excess cytoplasm is directed centrally toward the oligodendrocyte cell body.
Neurilemma serves a protective function for peripheral nerve fibers. Damaged nerve fibers may regenerate if the cell body is not damaged and the neurilemma remains intact. The neurilemma forms a regeneration tube through which the growing axon re-establishes its original connection.
Neurilemoma is a tumor of the neurilemma.
== References ==
== External links ==
Histology at dmacc.edu | Wikipedia/Neurilemma |
Compartmental modelling of dendrites deals with multi-compartment modelling of the dendrites, to make the understanding of the electrical behavior of complex dendrites easier. Basically, compartmental modelling of dendrites is a very helpful tool to develop new biological neuron models. Dendrites are very important because they occupy the most membrane area in many of the neurons and give the neuron an ability to connect to thousands of other cells. Originally the dendrites were thought to have constant conductance and current but now it has been understood that they may have active Voltage-gated ion channels, which influences the firing properties of the neuron and also the response of neuron to synaptic inputs. Many mathematical models have been developed to understand the electric behavior of the dendrites. Dendrites tend to be very branchy and complex, so the compartmental approach to understand the electrical behavior of the dendrites makes it very useful.
== Introduction ==
Compartmental modelling is a very natural way of modelling dynamical systems that have certain inherent properties with conservation principles. The compartmental modelling is an elegant way, a state space formulation to elegantly capture the dynamical systems that are governed by the conservation laws. Whether it is the conservation of mass, energy, fluid flow or information flow. Basically, they are models whose state variables tend to be non-negative (such as mass, concentrations, energy). So the equations for mass balance, energy, concentration or fluid flow can be written. It ultimately goes down to networks in which the brain is the largest of them all, just like Avogadro number, very large amount of molecules that are interconnected. The brain has very interesting interconnections. On a microscopic level thermodynamics is virtually impossible to understand but from a macroscopic view we see that these follow some universal laws. In the same way brain has numerous interconnections, which is almost impossible to write a differential equation for.
General observations about how the brain functions can be made by looking at the first and second thermodynamic laws, which are universal laws. Brain is a very large-scale interconnected system; the neurons have to somehow behave like the chemical reaction system, so, it has to somehow obey the chemical thermodynamic laws. This approach may lead to more generalized model of brain.
== Multiple compartments ==
Complicated dendritic structures can be treated as multiple compartments interconnected. The dendrites are divided into small compartments and they are linked together as shown in the figure.
It is assumed that the compartment is isopotential and spatially uniform in its properties. Membrane non-uniformity such as diameter changes, and voltage differences are occurred in between the compartments but not inside them.
An example of a simple two-compartment model:
Consider a two-compartmental model with the compartments viewed as isopotential cylinders with radius
a
i
{\displaystyle a_{i}}
and length
L
i
{\displaystyle L_{i}}
.
V
i
{\displaystyle V_{i}}
is the membrane potential of ith compartment.
c
i
{\displaystyle c_{i}}
is the specific membrane capacitance.
r
M
i
{\displaystyle r_{Mi}}
is the specific membrane resistivity.
The total electrode current, assuming that the compartment has it, is given by
I
electrode
i
{\displaystyle I_{\text{electrode}}^{i}}
.
The longitudinal resistance is given by
r
L
{\displaystyle r_{L}}
.
Now according to the balance that should exist for each compartment, we can say
i
cap
i
+
i
ion
i
=
i
long
i
+
i
electrode
i
{\displaystyle i_{\text{cap}}^{i}+i_{\text{ion}}^{i}=i_{\text{long}}^{i}+i_{\text{electrode}}^{i}}
.....eq(1)
where
i
cap
i
{\displaystyle i_{\text{cap}}^{i}}
and
i
ion
i
{\displaystyle i_{\text{ion}}^{i}}
are the capacitive and ionic currents per unit area of ith compartment membrane. i.e. they can be given by
i
cap
i
=
c
i
d
V
i
d
t
{\displaystyle i_{\text{cap}}^{i}=c_{i}{\frac {dV_{i}}{dt}}}
and
i
ion
i
=
V
i
r
M
i
{\displaystyle i_{\text{ion}}^{i}={\frac {V_{i}}{r_{Mi}}}}
.....eq(2)
If we assume the resting potential is 0. Then to compute
i
long
i
{\displaystyle i_{\text{long}}^{i}}
, we need total axial resistance. As the compartments are simply cylinders we can say
R
long
=
r
L
L
1
2
π
a
1
2
+
r
L
L
2
2
π
a
2
2
{\displaystyle R_{\text{long}}={\frac {r_{L}L_{1}}{2\pi a_{1}^{2}}}+{\frac {r_{L}L_{2}}{2\pi a_{2}^{2}}}}
.....eq(3)
Using ohms law we can express current from ith to jth compartment as
i
long
1
=
g
1
,
2
(
V
2
−
V
1
)
{\displaystyle i_{\text{long}}^{1}=g_{1,2}(V_{2}-V_{1})}
and
i
long
2
=
g
2
,
1
(
V
1
−
V
2
)
{\displaystyle i_{\text{long}}^{2}=g_{2,1}(V_{1}-V_{2})}
.....eq(4)
The coupling terms
g
1
,
2
{\displaystyle g_{1,2}}
and
g
2
,
1
{\displaystyle g_{2,1}}
are obtained by inverting eq(3) and dividing by surface area of interest.
So we get
g
1
,
2
=
a
1
a
2
2
r
L
L
1
(
a
2
2
L
1
+
a
1
2
L
2
)
{\displaystyle g_{1,2}={\frac {a_{1}a_{2}^{2}}{r_{L}L_{1}(a_{2}^{2}L_{1}+a_{1}^{2}L_{2})}}}
and
g
2
,
1
=
a
2
a
1
2
r
L
L
1
(
a
1
2
L
2
+
a
2
2
L
1
)
{\displaystyle g_{2,1}={\frac {a_{2}a_{1}^{2}}{r_{L}L_{1}(a_{1}^{2}L_{2}+a_{2}^{2}L_{1})}}}
Finally,
i
electrode
I
=
I
electrode
i
A
i
{\displaystyle i_{\text{electrode}}^{I}={\frac {I_{\text{electrode}}^{i}}{A_{i}}}}
A
i
=
2
π
a
i
L
i
{\displaystyle A_{i}=2\pi a_{i}L_{i}}
is the surface area of the compartment i.
If we put all these together we get
c
1
d
V
1
d
t
+
V
1
r
M
1
=
g
1
,
2
(
V
2
−
V
1
)
+
I
electrode
1
A
1
{\displaystyle c_{1}{\frac {dV_{1}}{dt}}+{\frac {V_{1}}{r_{M1}}}=g_{1,2}(V_{2}-V_{1})+{\frac {I_{\text{electrode}}^{1}}{A_{1}}}}
c
2
d
V
2
d
t
+
V
2
r
M
2
=
g
2
,
1
(
V
1
−
V
2
)
+
I
electrode
2
A
2
{\displaystyle c_{2}{\frac {dV_{2}}{dt}}+{\frac {V_{2}}{r_{M2}}}=g_{2,1}(V_{1}-V_{2})+{\frac {I_{\text{electrode}}^{2}}{A_{2}}}}
.....eq(5)
If we use
r
1
=
1
/
g
1
,
2
{\displaystyle r_{1}=1/g_{1,2}}
and
r
2
=
1
/
g
2
,
1
{\displaystyle r_{2}=1/g_{2,1}}
then eq(5) will become
c
1
d
V
1
d
t
+
V
1
r
M
1
=
V
2
−
V
1
r
1
+
I
electrode
1
A
1
{\displaystyle c_{1}{\frac {dV_{1}}{dt}}+{\frac {V_{1}}{r_{M1}}}={\frac {V_{2}-V_{1}}{r_{1}}}+{\frac {I_{\text{electrode}}^{1}}{A_{1}}}}
c
2
d
V
2
d
t
+
V
2
r
M
2
=
V
1
−
V
2
r
2
+
I
electrode
2
A
2
{\displaystyle c_{2}{\frac {dV_{2}}{dt}}+{\frac {V_{2}}{r_{M2}}}={\frac {V_{1}-V_{2}}{r_{2}}}+{\frac {I_{\text{electrode}}^{2}}{A_{2}}}}
.....eq(6)
Now if we inject current in cell 1 only and each cylinder is identical then
r
1
=
r
2
≡
r
{\displaystyle r_{1}=r_{2}\equiv r}
Without loss in generality we can define
r
M
=
r
M
1
=
r
M
2
{\displaystyle r_{M}=r_{M1}=r_{M2}}
After some algebra we can show that
V
1
i
1
=
r
M
(
r
+
r
M
)
r
+
2
r
M
{\displaystyle {\frac {V_{1}}{i_{1}}}={\frac {r_{M}(r+r_{M})}{r+2r_{M}}}}
also
R
input,coupled
R
input,uncoupled
=
1
−
r
M
r
+
2
r
M
{\displaystyle {\frac {R_{\text{input,coupled}}}{R_{\text{input,uncoupled}}}}=1-{\frac {r_{M}}{r+2r_{M}}}}
i.e. the input resistance decreases. For increment in the potential, coupled system current should be greater than that is required for uncoupled system. This is because the second compartment drains some current.
Now, we can get a general compartmental model for a treelike structure and the equations are
C
j
d
V
j
d
t
=
−
V
j
R
j
+
∑
k
connected
j
V
k
−
V
j
R
j
k
+
I
j
{\displaystyle C_{j}{\frac {dV_{j}}{dt}}=-{\frac {V_{j}}{R_{j}}}+\sum _{k{\text{ connected }}j}{}{\frac {V_{k}-V_{j}}{R_{jk}}}+I_{j}}
=== Increased computational accuracy in multi-compartmental cable models ===
Input at the center
Each dendritic section is subdivided into segments, which are typically seen as uniform circular cylinders or tapered circular cylinders. In the traditional compartmental model, point process location is determined only to an accuracy of half segment length. This will make the model solution particularly sensitive to segment boundaries. The accuracy of the traditional approach for this reason is O(1/n) when a point current and synaptic input is present. Usually the trans-membrane current where the membrane potential is known is represented in the model at points, or nodes and is assumed to be at the center. The new approach partitions the effect of the input by distributing it to the boundaries of the segment. Hence any input is partitioned between the nodes at the proximal and distal boundaries of the segment. Therefore, this procedure makes sure that the solution obtained is not sensitive to small changes in location of these boundaries because it affects how the input is partitioned between the nodes. When these compartments are connected with continuous potentials and conservation of current at segment boundaries then a new compartmental model of a new mathematical form is obtained. This new approach also provides a model identical to the traditional model but an order more accurate. This model increases the accuracy and precision by an order of magnitude than that is achieved by point process input.
== Cable theory ==
Dendrites and axons are considered to be continuous (cable-like), rather than series of compartments.
== Some applications ==
=== Information processing ===
A theoretical framework along with a technological platform are provided by computational models to enhance the understanding of nervous system functions. There was a lot of advancement in the molecular and biophysical mechanisms underlying the neuronal activity. The same kind of advances have to be made in understanding the structure-functional relationship and rules followed by the information processing.
Previously a neuron used to be thought as a transistor. However, it is shown recently that morphology and ionic composition of different neurons provide the cell with enhanced computational capabilities. These abilities are far more advanced than those captured by a point neuron.
Some findings:
Different outputs given by the individual apical oblique dendrites of CA1 pyramidal neurons are linearly combined in the cell body. The outputs that come from these dendrites actually behave like individual computational units that use sigmoidal activation function to combine inputs.
The thin dendritic branches each act as a typical point neuron, which are capable of combining the incoming signals according to the thresholding non-linearity.
Considering the accuracy in prediction of different input patterns by a two-layer neural network, it is assumed that a simple mathematical equation can be used to describe the model. This allows the development of network models in which each neuron, instead of being modelled as a full blown compartmental cell, it is modelled as a simplified two layer neural network.
The firing pattern of the cell might contain the temporal information about incoming signals. For example, the delay between the two simulated pathways.
Single CA1 has a capability of encoding and transmitting spatio-temporal information on the incoming signals to the recipient cell.
Calcium-activated nonspecific cationic (CAN) mechanism is needed for giving constant activity and the synaptic stimulation alone does not induce persistent activity using the increasing conductance of NMDA mechanism. NMDA/ AMPA positively expands the range of persistent activity and negatively regulates the amount of CAN needed for constant activity.
=== Midbrain dopaminergic neuron ===
Movement, motivation, attention, neurological and psychiatric disorders and addictive behavior have a strong influence by Dopaminergic signalling.
The dopaminergic neurons have a low irregular basal firing frequency in 1–8 Hz range in vivo in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). This frequencies can dramatically increase in response to a cue predicting reward or unpredicted reward. The actions that preceded the reward are reinforced by this burst or phasic signal.
The low safety factor for action potential generation gives a result of low maximal steady frequencies. The transient initial frequency in response to depolarizing pulse is controlled by rate of Ca2+ accumulation in distal dendrites.
Results obtained from a mulch-compartmental model realistic with reconstructed morphology were similar. So, the salient contributions of the dendritic architecture have been captures by simpler model.
=== Mode locking ===
There are many important applications in neuroscience for Mode-locking response of excitable systems to periodic forcing. For example, The theta rhythm drives the spatially extended place cells in the hippocampus to generate a code giving information about spatial location. The role of neuronal dendrites in generating the response to periodic current injection can be explored by using a compartmental model (with linear dynamics for each compartment) coupled to an active soma model that generates action potentials.
Some findings:
The response of whole neuron model i.e. soma and dendrites, can be written in closed form. The response of the spatially extended model to periodic forcing is described by stroboscopic map. A Arnol'd tongue quasi-active model can be constructed with a linear stability analysis of the map with carefully treating the non-differentiability of soma model.
The shape of the tongues is influenced by the presence of the quasi-active membrane.
The windows in parameter space for chaotic behavior can be enlarged with the resonant dendritic membrane.
The response of the spatially extended neuron model to global forcing is different from that of point forcing.
=== Compartmental neural simulations with spatial adaptivity ===
The computational cost of the method scales not with the physical size of the system being simulated but with the amount of activity present in the simulation. Spatial adaptivity for certain problems reduces up to 80%.
=== Action potential (AP) initiation site ===
Establishing a unique site for AP initiation at the axon initial segment is no longer accepted. The APs can be initiated and conducted by different sub-regions of the neuron morphology, which widened the capabilities of individual neurons in computation.
Findings from a study of the Action Potential Initiation Site Along the Axosomatodendritic Axis of Neurons Using Compartmental Models:
Dendritic APs are initiated more effectively by synchronous spatially clustered inputs than equivalent disperse inputs.
The initiation site can also be determined by the average electrical distance from the dendritic input to the axon trigger zone, but it may be strongly modulated by the relative excitability of the two trigger zones and a number of factors.
=== A finite-state automaton model ===
Multi-neuron simulations with finite-state automaton model is capable of modelling the most important characteristics of neural membranes.
=== Constraining compartmental models ===
Can be done using extracellular action potential recordings
Can be done using Multiple Voltage Recordings and Genetic Algorithms
=== Multi-compartmental model of a CA1 pyramidal cell ===
To study changes in hippocampal excitability that result from aging-induced alterations in calcium-dependent membrane mechanisms, the multi-compartmental model of CA1 pyramidal cell can be used. We can model the aging-induced alterations in CA1 excitability can be with simple coupling mechanisms that selectively link specific types of calcium channels to specific calcium-dependent potassium channels.
=== Electrical compartmentalization ===
Spine Neck Plasticity Controls Postsynaptic Calcium Signals through Electrical Compartmentalization. The spine neck plasticity through a process of electrical compartmentalization can dynamically regulate Calcium influx into spines (a key trigger for synaptic plasticity).
=== Robust coding in motion-sensitive neurons ===
Different receptive fields in axons and dendrites underlie robust coding in motion-sensitive neurons.
=== Conductance-based neuron models ===
The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites.
== See also ==
Computational neuroscience
Dynamical system
Multi-compartment model
Connectionism
Neural network
Biological neuron models
Neural coding
Brain-computer interface
Neural engineering
Neuroinformatics
Mathematical model
Compartmental models in epidemiology
Physiologically-based pharmacokinetic modelling
== References ==
== External links ==
: Ted talk on supercomputing Archived 2014-02-11 at the Wayback Machine
: Laboratory of Biological Modelling
: Pharmacokinetics Modelling Tutorial
: Usefulness of two compartmental model in Pharmacokinetics
: Pharmacokinetics | Wikipedia/Compartmental_neuron_models |
The Baconian method is the investigative method developed by Francis Bacon, one of the founders of modern science, and thus a first formulation of a modern scientific method. The method was put forward in Bacon's book Novum Organum (1620), or 'New Method', to replace the old methods put forward in Aristotle's Organon. It influenced the early modern rejection of medieval Aristotelianism.
== Description in the Novum Organum ==
=== Bacon's view of induction ===
Bacon's method is an example of the application of inductive reasoning. However, Bacon's method of induction is much more complex than the essential inductive process of making generalisations from observations. Bacon's method begins with description of the requirements for making the careful, systematic observations necessary to produce quality facts. He then proceeds to use induction, the ability to generalise from a set of facts to one or more axioms. However, he stresses the necessity of not generalising beyond what the facts truly demonstrate. The next step may be to gather additional data, or the researcher may use existing data and the new axioms to establish additional axioms. Specific types of facts can be particularly useful, such as negative instances, exceptional instances and data from experiments. The whole process is repeated in a stepwise fashion to build an increasingly complex base of knowledge, but one which is always supported by observed facts, or more generally speaking, empirical data.
He argues in the Novum Organum that our only hope for building true knowledge is through this careful method. Old knowledge-building methods were often not based in facts, but on broad, ill-proven deductions and metaphysical conjecture. Even when theories were based in fact, they were often broad generalisations and/or abstractions from few instances of casually gathered observations. Using Bacon's process, man could start fresh, setting aside old superstitions, over-generalisations, and traditional (often unproven) "facts". Researchers could slowly but accurately build an essential base of knowledge from the ground up. Describing then-existing knowledge, Bacon claims:
There is the same degree of licentiousness and error in forming axioms as [there is] in abstracting notions, and [also] in the first principles, which depend in common induction [versus Bacon's induction]; still more is this the case in axioms and inferior propositions derived from syllogisms.
While he advocated a very empirical, observational, reasoned method that did away with metaphysical conjecture, Bacon was a religious man, believed in God, and believed his work had a religious role. He contended, like other researchers at the time, that by doing this careful work man could begin to understand God's wonderful creation, to reclaim the knowledge that had been lost in Adam and Eve's "fall", and to make the most of his God-given talents.
=== Role of the English Reformation ===
There is a wider array of seminal works about the interaction of Puritanism and early science. Among others, Dorothy Stimson, Richard Foster Jones, and Robert Merton saw Puritanism as a major driver of the reforms initiated by Bacon and the development of science overall. Steven Matthews is cautious about the interaction with a single confession, as the English Reformation allowed a higher doctrinal diversity compared to the continent. However, Matthews is quite outspoken that "Bacon's entire understanding of what we call 'science,' and what he called 'natural philosophy,' was fashioned around the basic tenets of his belief system."
=== Approach to causality ===
The method consists of procedures for isolating and further investigating the form nature, or cause, of a phenomenon, including the method of agreement, method of difference, and method of concomitant variation.
Bacon suggests that you draw up a list of all things in which the phenomenon you are trying to explain occurs, as well as a list of things in which it does not occur. Then you rank your lists according to the degree in which the phenomenon occurs in each one. Then you should be able to deduce what factors match the occurrence of the phenomenon in one list and don't occur in the other list, and also what factors change in accordance with the way the data had been ranked.
Thus, if an army is successful when commanded by Essex, and not successful when not commanded by Essex: and when it is more or less successful according to the degree of involvement of Essex as its commander, then it is scientifically reasonable to say that being commanded by Essex is causally related to the army's success.
From this Bacon suggests that the underlying cause of the phenomenon, what he calls the "form", can be approximated by interpreting the results of one's observations. This approximation Bacon calls the "First Vintage". It is not a final conclusion about the formal cause of the phenomenon but merely a hypothesis. It is only the first stage in the attempt to find the form and it must be scrutinised and compared to other hypotheses. In this manner, the truth of natural philosophy is approached "by gradual degrees", as stated in his Novum Organum.
=== Refinements ===
The "Baconian method" does not end at the First Vintage. Bacon described numerous classes of Instances with Special Powers, cases in which the phenomenon one is attempting to explain is particularly relevant. These instances, of which Bacon describes 27 in the Novum Organum, aid and accelerate the process of induction.
Aside from the First Vintage and the Instances with Special Powers, Bacon enumerates additional "aids to the intellect" which presumably are the next steps in his method. These additional aids, however, were never explained beyond their initial limited appearance in Novum Organum.
== Natural history ==
The Natural History of Pliny the Elder was a classical Roman encyclopedia work. Induction, for Bacon's followers, meant a type of rigour applied to factual matters. Reasoning should not be applied in plain fashion to just any collection of examples, an approach identified as "Plinian". In considering natural facts, a fuller survey was required to form a basis for going further. Bacon made it clear he was looking for more than "a botany" with discursive accretions.
In concrete terms, the cabinet of curiosities, exemplifying the Plinian approach, was to be upgraded from a source of wonderment to a challenge to science. The main source in Bacon's works for the approach was his Sylva Sylvarum, and it suggested a more systematic collection of data in the search for causal explanations.
Underlying the method, as applied in this context, are therefore the "tables of natural history" and the ways in which they are to be constructed. Bacon's background in the common law has been proposed as a source for this concept of investigation.
As a general intellectual programme, Bacon's ideas on "natural history" have been seen as a broad influence on British writers later in the 17th century, in particular in economic thought and within the Royal Society.
== Idols of the mind (idola mentis) ==
Bacon also listed what he called the idols (false images) of the mind. He described these as things which obstructed the path of correct scientific reasoning.
Idols of the Tribe (Idola tribus): This is humans' tendency to perceive more order and regularity in systems than truly exists, and is due to people following their preconceived ideas about things.
Idols of the Cave (Idola specus): This is due to individuals' personal weaknesses in reasoning due to particular personalities, likes and dislikes.
Idols of the Marketplace (Idola fori): This is due to confusion in the use of language and taking some words in science to have a different meaning than their common usage.
Idols of the Theatre (Idola theatri): This is the following of academic dogma and not asking questions about the world.
== Influence ==
The physician Thomas Browne (1605–1682) was one of the first scientists to adhere to the empiricism of the Baconian method. His encyclopaedia Pseudodoxia Epidemica (1st edition 1646 – 5th edition 1672) includes numerous examples of Baconian investigative methodology, while its preface echoes lines from Bacon's On Truth from The Advancement of Learning (1605). Isaac Newton's saying hypotheses non fingo (I don't frame hypotheses) occurs in later editions of the Principia. It represents his preference for rules that could be demonstrated, as opposed to unevidenced hypotheses.
The Baconian method was further developed and promoted by John Stuart Mill. His 1843 book, A System of Logic, was an effort to shed further light on issues of causation. In this work, he formulated the five principles of inductive reasoning now known as Mill's methods.
== Frankfurt School critique of Baconian method ==
Max Horkheimer and Theodor Adorno observe that Bacon shuns "knowledge that tendeth but to satisfaction" in favor of effective procedures. While the Baconian method disparages idols of the mind, its requirement for effective procedures compels it to adopt a credulous, submissive stance toward worldly power.
Power confronts the individual as the universal, as the reason which informs reality.
Knowledge, which is power, knows no limits, either in its enslavement of creation or in its deference to worldly masters.
Horkheimer and Adorno offer a plea to recover the virtues of the "metaphysical apologia", which is able to reveal the injustice of effective procedures rather than merely employing them.
The metaphysical apologia at least betrayed the injustice of the established order through the incongruence of concept and reality. The impartiality of scientific language deprived what was powerless of the strength to make itself heard and merely provided the existing order with a neutral sign for itself. Such neutrality is more metaphysical than metaphysics.
== See also ==
Corroborating evidence
== Notes ==
== References ==
Klein, Juergen (December 7, 2012). "Francis Bacon". In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy. | Wikipedia/Baconian_method |
A vesicular transport protein, or vesicular transporter, is a membrane protein that regulates or facilitates the movement of specific molecules across a vesicle's membrane. As a result, vesicular transporters govern the concentration of molecules within a vesicle.
== Types ==
Examples include:
Archain
ARFs
Clathrin
Caveolin
Dynamin and related proteins, such as the EHD protein family
Rab proteins
SNAREs
Vesicular transport adaptor proteins e.g. Sorting nexins
Synaptotagmin
TRAPP complex
Synaptophysin
Auxilin
== Pathways ==
There are multiple pathways, each using its own coat and GTPase.
COP 1 (Cytosolic coat protein complex ) : retrograde transport; Golgi ----> Endoplasmic reticulum
COP 2 (Cytosolic coat protein complex ) : anterograde transport; RER -----> cis-Golgi
Clathrin : trans-Golgi ----> Lysosomes, Plasma membrane ----> Endosomes (receptor-mediated endocytosis)
== See also ==
Membrane transport protein
Wikipedia:MeSH D12.776#MeSH D12.776.543.990 --- vesicular transport proteins
== References == | Wikipedia/Vesicular_transport_protein |
Free radical damage to DNA can occur as a result of exposure to ionizing radiation or to radiomimetic compounds. Damage to DNA as a result of free radical attack is called indirect DNA damage because the radicals formed can diffuse throughout the body and affect other organs. Malignant melanoma can be caused by indirect DNA damage because it is found in parts of the body not exposed to sunlight. DNA is vulnerable to radical attack because of the very labile hydrogens that can be abstracted and the prevalence of double bonds in the DNA bases that free radicals can easily add to.
== Damage via radiation exposure ==
Radiolysis of intracellular water by ionizing radiation creates peroxides, which are relatively stable precursors to hydroxyl radicals. 60%–70% of cellular DNA damage is caused by hydroxyl radicals, yet hydroxyl radicals are so reactive that they can only diffuse one or two molecular diameters before reacting with cellular components. Thus, hydroxyl radicals must be formed immediately adjacent to nucleic acids in order to react. Radiolysis of water creates peroxides that can act as diffusable, latent forms of hydroxyl radicals. Some metal ions in the vicinity of DNA generate the hydroxyl radicals from peroxide.
H2O + hν → H2O+ + e−
H2O + e− → H2O−
H2O+ → H+ + OH·
H2O− → OH− + H·
2 OH· →H2O2
Free radical damage to DNA is thought to cause mutations that may lead to some cancers.
== The Fenton reaction ==
The Fenton reaction results in the creation of hydroxyl radicals from hydrogen peroxide and an Iron (II) catalyst. Iron(III) is regenerated via the Haber–Weiss reaction. Transition metals with a free coordination site are capable of reducing peroxides to hydroxyl radicals. Iron is believed to be the metal responsible for the creation of hydroxyl radicals because it exists at the highest concentration of any transition metal in most living organisms. The Fenton reaction is possible because transition metals can exist in more than one oxidation state and their valence electrons may be unpaired, allowing them to participate in one-electron redox reactions.
Fe2+ + H2O2 → Fe3+ + OH· + OH−
The creation of hydroxyl radicals by iron(II) catalysis is important because iron(II) can be found coordinated with, and therefore in close proximity to, DNA. This reaction allows for hydrogen peroxide created by radiolysis of water to diffuse to the nucleus and react with Iron (II) to produce hydroxyl radicals, which in turn react with DNA. The location and binding of Iron (II) to DNA may play an important role in determining the substrate and nature of the radical attack on the DNA. The Fenton reaction generates two types of oxidants, Type I and Type II. Type I oxidants are moderately sensitive to peroxides and ethanol. Type I and Type II oxidants preferentially cleave at the specific sequences.
== Radical hydroxyl attack ==
Hydroxyl radicals can attack the deoxyribose DNA backbone and bases, potentially causing a plethora of lesions that can be cytotoxic or mutagenic. Cells have developed complex and efficient repair mechanisms to fix the lesions. In the case of free radical attack on DNA, base-excision repair is the repair mechanism used. Hydroxyl radical reactions with the deoxyribose sugar backbone are initiated by hydrogen abstraction from a deoxyribose carbon, and the predominant consequence is eventual strand breakage and base release. The hydroxyl radical reacts with the various hydrogen atoms of the deoxyribose in the order 5′ H > 4′ H > 3′ H ≈ 2′ H ≈ 1′ H. This order of reactivity parallels the exposure to solvent of the deoxyribose hydrogens.
Hydroxyl radicals react with DNA bases via addition to the electron-rich, pi bonds. These pi bonds in the bases are located between C5-C6 of pyrimidines and N7-C8 in purines. Upon addition of the hydroxyl radical, many stable products can be formed. In general, radical hydroxyl attacks on base moieties do not cause altered sugars or strand breaks except when the modifications labilize the N-glycosyl bond, allowing the formation of baseless sites that are subject to beta-elimination.
== Abasic sites ==
Hydrogen abstraction from the 1’-deoxyribose carbon by the hydroxyl radical creates a 1 ‘-deoxyribosyl radical. The radical can then react with molecular oxygen, creating a peroxyl radical which can be reduced and dehydrated to yield a 2’-deoxyribonolactone and free base. A deoxyribonolactone is mutagenic and resistant to repair enzymes. Thus, an abasic site is created.
== Radical damage through radiomimetic compounds ==
Radical damage to DNA can also occur through the interaction of DNA with certain natural products known as radiomimetic compounds, molecular compounds which affect DNA in similar ways to radiation exposure. Radiomimetic compounds induce double-strand breaks in DNA via highly specific, concerted free-radical attacks on the deoxyribose moieties in both strands of DNA.
== General mechanism ==
Many radiomimetic compounds are enediynes, which undergo the Bergman cyclization reaction to produce a 1,4-didehydrobenzene diradical. The 1,4-didehydrobenzene diradical is highly reactive, and will abstract hydrogens from any possible hydrogen-donor.
In the presence of DNA, the 1,4-didehydrobenzene diradical abstracts hydrogens from the deoxyribose sugar backbone, predominantly at the C-1’, C-4’ and C-5’ positions. Hydrogen abstraction causes radical formation at the reacted carbon. The carbon radical reacts with molecular oxygen, which leads to a strand break in the DNA through a variety of mechanisms. 1,4-Didehydrobenzene is able to position itself in such a way that it can abstract proximal hydrogens from both strands of DNA. This produces a double-strand break in the DNA, which can lead to cellular apoptosis if not repaired.
Enediynes generally undergo the Bergman cyclization at temperatures exceeding 200 °C. However, incorporating the enediyne into a 10-membered cyclic hydrocarbon makes the reaction more thermodynamically favorable by releasing the ring strain of the reactants. This allows for the Bergman cyclization to occur at 37 °C, the biological temperature of humans. Molecules which incorporate enediynes into these larger ring structures have been found to be extremely cytotoxic.
== Natural products ==
Enediynes are present in many complicated natural products. They were originally discovered in the early 1980s during a search for new anticancer products produced by microorganisms. Calicheamicin was one of the first such products identified and was originally found in a soil sample taken from Kerrville, Texas. These compounds are synthesized by bacteria as defense mechanisms due to their ability to cleave DNA through the formation of 1,4-didehydrobenzene from the enediyne component of the molecule.
Calicheamicin and other related compounds share several common characteristics. The extended structures attached to the enediyne allow the compound to specifically bind DNA, in most cases to the minor groove of the double helix. Additionally, part of the molecule is known as the “trigger” which, under specific physiological conditions, activates the enediyne, known as the “warhead” and 1,4-didehydrobenzene is generated.
Three classes of enediynes have since been identified: calicheamicin, dynemicin, and chromoprotein-based products.
The calicheamicin types are defined by a methyl trisulfide group that is involved in triggering the molecule by the following mechanism.
Calicheamicin and the closely related esperamicin have been used as anticancer drugs due to their high toxicity and specificity.
Dynemicin and its relatives are characterized by the presence of an anthraquinone and enediyne core. The anthraquinone component allows for specific binding of DNA at the 3’ side of purine bases through intercalation, a site that is different from calicheamicin. Its ability to cleave DNA is greatly increased in the presence of NADPH and thiol compounds. This compound has also found prominence as an antitumor agent.
Chromoprotein enediynes are characterized by an unstable chromophore enediyne bound to an apoprotein.
The chromophore is unreactive when bound to the apoprotein. Upon its release, it reacts to form 1,4-didehydrobenzene and subsequently cleaves DNA.
== Antitumor ability ==
Most enediynes, including the ones listed above, have been used as potent antitumor antibiotics due to their ability to efficiently cleave DNA. Calicheamicin and esperamicin are the two most commonly used types due to their high specificity when binding to DNA, which minimizes unfavorable side reactions. They have been shown to be especially useful for treating acute myeloid leukemia.
Additionally, calicheamicin is able to cleave DNA at low concentrations, proving to be up to 1000 times more effective than adriamycin at combating certain types of tumors.
The free radical mechanism to treat certain types of cancers extends beyond enediynes. Tirapazamine generates a free radical under anoxic conditions instead of the trigger mechanism of an enediyne. The free radical then continues on to cleave DNA in a similar manner to 1,4-didehydrobenzene in order to treat cancerous cells. It is currently in Phase III trials.
== Evolution of Meiosis ==
Meiosis is a central feature of sexual reproduction in eukaryotes. The need to repair oxidative DNA damage caused by oxidative free radicals has been hypothesized to be a major driving force in the evolution of meiosis
== References == | Wikipedia/Free_radical_damage_to_DNA |
A DNA repair-deficiency disorder is a medical condition due to reduced functionality of DNA repair.
DNA repair defects can cause an accelerated aging disease or an increased risk of cancer, or sometimes both.
== DNA repair defects and accelerated aging ==
DNA repair defects are seen in nearly all of the diseases described as accelerated aging disease, in which various tissues, organs or systems of the human body age prematurely. Because the accelerated aging diseases display different aspects of aging, but never every aspect, they are often called segmental progerias by biogerontologists.
=== Human disorders with accelerated aging ===
Ataxia-telangiectasia
Bloom syndrome
Cockayne syndrome
Fanconi anemia
Progeria (Hutchinson–Gilford progeria syndrome)
Rothmund–Thomson syndrome
Trichothiodystrophy
Werner syndrome
Xeroderma pigmentosum
=== Examples ===
Some examples of DNA repair defects causing progeroid syndromes in humans or mice are shown in Table 1.
=== DNA repair defects distinguished from "accelerated aging" ===
Most of the DNA repair deficiency diseases show varying degrees of "accelerated aging" or cancer (often some of both). But elimination of any gene essential for base excision repair kills the embryo—it is too lethal to display symptoms (much less symptoms of cancer or "accelerated aging").
Rothmund-Thomson syndrome and xeroderma pigmentosum display symptoms dominated by vulnerability to cancer, whereas progeria and Werner syndrome show the most features of "accelerated aging". Hereditary nonpolyposis colorectal cancer (HNPCC) is very often caused by a defective MSH2 gene leading to defective mismatch repair, but displays no symptoms of "accelerated aging". On the other hand, Cockayne Syndrome and trichothiodystrophy show mainly features of accelerated aging, but apparently without an increased risk of cancer Some DNA repair defects manifest as neurodegeneration rather than as cancer or "accelerated aging". (Also see the "DNA damage theory of aging" for a discussion of the evidence that DNA damage is the primary underlying cause of aging.)
=== Debate concerning "accelerated aging" ===
Some biogerontologists question that such a thing as "accelerated aging" actually exists, at least partly on the grounds that all of the so-called accelerated aging diseases are segmental progerias. Many disease conditions such as diabetes, high blood pressure, etc., are associated with increased mortality. Without reliable biomarkers of aging it is hard to support the claim that a disease condition represents more than accelerated mortality.
Against this position other biogerontologists argue that premature aging phenotypes are identifiable symptoms associated with mechanisms of molecular damage. The fact that these phenotypes are widely recognized justifies classification of the relevant diseases as "accelerated aging". Such conditions, it is argued, are readily distinguishable from genetic diseases associated with increased mortality, but not associated with an aging phenotype, such as cystic fibrosis and sickle cell anemia. It is further argued that segmental aging phenotype is a natural part of aging insofar as genetic variation leads to some people being more disposed than others to aging-associated diseases such as cancer and Alzheimer's disease.
== DNA repair defects and increased cancer risk ==
Individuals with an inherited impairment in DNA repair capability are often at increased risk of cancer. When a mutation is present in a DNA repair gene, the repair gene will either not be expressed or be expressed in an altered form. Then the repair function will likely be deficient, and, as a consequence, damages will tend to accumulate. Such DNA damages can cause errors during DNA synthesis leading to mutations, some of which may give rise to cancer. Germ-line DNA repair mutations that increase the risk of cancer are listed in the Table.
== See also ==
Biogerontology
Degenerative disease
DNA damage theory of aging
Genetic disorder
Senescence
== References ==
== External links ==
BRCA - Companion Reviews and Search Terms
BRCA1 - Companion Reviews and Search Terms
BRCA2 - Companion Reviews and Search Terms
ATM - Companion Reviews and Search Terms
NBS1 - Companion Reviews and Search Terms
Bloom s syndrome - Companion Reviews and Search Terms
Fanconi s anemia - Companion Reviews and Search Terms
WRN - Companion Reviews and Search Terms
RECQ- Companion Reviews and Search Terms
RECQL4 - Companion Reviews and Search Terms
FANCJ - Companion Reviews and Search Terms
FANCM - Companion Reviews and Search Terms
FANCN - Companion Reviews and Search Terms
XPB - Companion Reviews and Search Terms
XPD - Companion Reviews and Search Terms
XPG - Companion Reviews and Search Terms
MSH6 - Companion Reviews and Search Terms
MUTYH - Companion Reviews and Search Terms
DNA repair and toxicology - Companion Reviews and Search Terms
Neoplasia inherited - Companion Reviews and Search Terms
Neoplasia carcinogenesis - Companion Reviews and Search Terms
Segmental Progeria | Wikipedia/DNA_repair-deficiency_disorder |
DNA oxidation is the process of oxidative damage of deoxyribonucleic acid. As described in detail by Burrows et al., 8-oxo-2'-deoxyguanosine (8-oxo-dG) is the most common oxidative lesion observed in duplex DNA because guanine has a lower one-electron reduction potential than the other nucleosides in DNA. The one electron reduction potentials of the nucleosides (in volts versus NHE) are guanine 1.29, adenine 1.42, cytosine 1.6 and thymine 1.7. About 1 in 40,000 guanines in the genome are present as 8-oxo-dG under normal conditions. This means that >30,000 8-oxo-dGs may exist at any given time in the genome of a human cell. Another product of DNA oxidation is 8-oxo-dA. 8-oxo-dA occurs at about 1/10 the frequency of 8-oxo-dG. The reduction potential of guanine may be reduced by as much as 50%, depending on the particular neighboring nucleosides stacked next to it within DNA.
Excess DNA oxidation is linked to certain diseases and cancers, while normal levels of oxidized nucleotides, due to normal levels of ROS, may be necessary for memory and learning.
== Oxidized bases in DNA ==
More than 20 oxidatively damaged DNA base lesions were identified in 2003 by Cooke et al. and these overlap the 12 oxidized bases reported in 1992 by Dizdaroglu. Two of the most frequently oxidized bases found by Dizdaroglu after ionizing radiation (causing oxidative stress) were the two oxidation products of guanine shown in the figure. One of these products was 8-OH-Gua (8-hydroxyguanine). (The article 8-oxo-2'-deoxyguanosine refers to the same damaged base since the keto form 8-oxo-Gua described there may undergo a tautomeric shift to the enol form 8-OH-Gua shown here.) The other product was FapyGua (2,6-diamino-4-hydroxy-5-formamidopyrimidine). Another frequent oxidation product was 5-OH-Hyd (5-hydroxyhydantoin) derived from cytosine.
== Removal of oxidized bases ==
Most oxidized bases are removed from DNA by enzymes operating within the base excision repair pathway. Removal of oxidized bases in DNA is fairly rapid. For example, 8-oxo-dG was increased 10-fold in the livers of mice subjected to ionizing radiation, but the excess 8-oxo-dG was removed with a half-life of 11 minutes.
== Steady-state levels of DNA damage ==
Steady-state levels of endogenous DNA damages represent the balance between formation and repair. Swenberg et al. measured average amounts of steady state endogenous DNA damages in mammalian cells. The seven most common damages they found are shown in Table 1. Only one directly oxidized base, 8-hydroxyguanine, at about 2,400 8-OH-G per cell, was among the most frequent DNA damages present in the steady-state.
== Increased 8-oxo-dG in carcinogenesis and disease ==
As reviewed by Valavanidis et al. increased levels of 8-oxo-dG in a tissue can serve as a biomarker of oxidative stress. They also noted that increased levels of 8-oxo-dG are frequently found associated with carcinogenesis and disease.
In the figure shown in this section, the colonic epithelium from a mouse on a normal diet has a low level of 8-oxo-dG in its colonic crypts (panel A). However, a mouse likely undergoing colonic tumorigenesis (due to deoxycholate added to its diet) has a high level of 8-oxo-dG in its colonic epithelium (panel B). Deoxycholate increases intracellular production of reactive oxygen resulting in increased oxidative stress, and this may contribute to tumorigenesis and carcinogenesis. Of 22 mice fed the diet supplemented with deoxycholate, 20 (91%) developed colonic tumors after 10 months on the diet, and the tumors in 10 of these mice (45% of mice) included an adenocarcinoma (cancer). Cooke et al. point out that a number of diseases, such as Alzheimer's disease and systemic lupus erythematosus, have elevated 8-oxo-dG but no increased carcinogenesis.
== Indirect role of oxidative damage in carcinogenesis ==
Valavanidis et al. pointed out that oxidative DNA damage, such as 8-oxo-dG, may contribute to carcinogenesis by two mechanisms. The first mechanism involves modulation of gene expression, whereas the second is through the induction of mutations.
=== Epigenetic alterations ===
Epigenetic alteration, for instance by methylation of CpG islands in a promoter region of a gene, can repress expression of the gene (see DNA methylation in cancer). In general, epigenetic alteration can modulate gene expression. As reviewed by Bernstein and Bernstein, the repair of various types of DNA damages can, with low frequency, leave remnants of the different repair processes and thereby cause epigenetic alterations. 8-oxo-dG is primarily repaired by base excision repair (BER). Li et al. reviewed studies indicating that one or more BER proteins also participate(s) in epigenetic alterations involving DNA methylation, demethylation or reactions coupled to histone modification. Nishida et al. examined 8-oxo-dG levels and also evaluated promoter methylation of 11 tumor suppressor genes (TSGs) in 128 liver biopsy samples. These biopsies were taken from patients with chronic hepatitis C, a condition causing oxidative damages in the liver. Among 5 factors evaluated, only increased levels of 8-oxo-dG was highly correlated with promoter methylation of TSGs (p<0.0001). This promoter methylation could have reduced expression of these tumor suppressor genes and contributed to carcinogenesis.
=== Mutagenesis ===
Yasui et al. examined the fate of 8-oxo-dG when this oxidized derivative of deoxyguanosine was inserted into the thymidine kinase gene in a chromosome within human lymphoblastoid cells in culture. They inserted 8-oxo-dG into about 800 cells, and could detect the products that occurred after the insertion of this altered base, as determined from the clones produced after growth of the cells. 8-oxo-dG was restored to G in 86% of the clones, probably reflecting accurate base excision repair or translesion synthesis without mutation. G:C to T:A transversions occurred in 5.9% of the clones, single base deletions in 2.1% and G:C to C:G transversions in 1.2%. Together, these more common mutations totaled 9.2% of the 14% of mutations generated at the site of the 8-oxo-dG insertion. Among the other mutations in the 800 clones analyzed, there were also 3 larger deletions, of sizes 6, 33 and 135 base pairs. Thus 8-oxo-dG, if not repaired, can directly cause frequent mutations, some of which may contribute to carcinogenesis.
== Role of DNA oxidation in gene regulation ==
As reviewed by Wang et al., oxidized guanine appears to have multiple regulatory roles in gene expression. As noted by Wang et al., genes prone to be actively transcribed are densely distributed in high GC-content regions of the genome. They then described three modes of gene regulation by DNA oxidation at guanine. In one mode, it appears that oxidative stress may produce 8-oxo-dG in a promoter of a gene. The oxidative stress may also inactivate OGG1. The inactive OGG1, which no longer excises 8-oxo-dG, nevertheless targets and complexes with 8-oxo-dG, and causes a sharp (~70o) bend in the DNA. This allows the assembly of a transcriptional initiation complex, up-regulating transcription of the associated gene. The experimental basis establishing this mode was also reviewed by Seifermann and Epe
A second mode of gene regulation by DNA oxidation at a guanine, occurs when an 8-oxo-dG is formed in a guanine rich, potential G-quadruplex-forming sequence (PQS) in the coding strand of a promoter, after which active OGG1 excises the 8-oxo-dG and generates an apurinic/apyrimidinic site (AP site). The AP site enables melting of the duplex to unmask the PQS, adopting a G-quadruplex fold (G4 structure/motif) that has a regulatory role in transcription activation.
A third mode of gene regulation by DNA oxidation at a guanine, occurs when 8-oxo-dG is complexed with OGG1 and then recruits chromatin remodelers to modulate gene expression. Chromodomain helicase DNA-binding protein 4 (CHD4), a component of the (NuRD) complex, is recruited by OGG1 to oxidative DNA damage sites. CHD4 then attracts DNA and histone methylating enzymes that repress transcription of associated genes.
Seifermann and Epe noted that the highly selective induction of 8-oxo-dG in the promoter sequences observed in transcription induction may be difficult to explain as a consequence of general oxidative stress. However, there appears to be a mechanism for site-directed generation of oxidized bases in promoter regions. Perillo et al., showed that the lysine-specific histone demethylase LSD1 generates a local burst of reactive oxygen species (ROS) that induces oxidation of nearby nucleotides when carrying out its function. As a specific example, after treatment of cells with an estrogen, LSD1 produced H2O2 as a by-product of its enzymatic activity. The oxidation of DNA by LSD1 in the course of the demethylation of histone H3 at lysine 9 was shown to be required for the recruitment of OGG1 and also topoisomerase IIβ to the promoter region of bcl-2, an estrogen-responsive gene, and subsequent transcription initiation.
8-oxo-dG does not occur randomly in the genome. In mouse embryonic fibroblasts, a 2 to 5-fold enrichment of 8-oxo-dG was found in genetic control regions, including promoters, 5'-untranslated regions and 3'-untranslated regions compared to 8-oxo-dG levels found in gene bodies and in intergenic regions. In rat pulmonary artery endothelial cells, when 22,414 protein-coding genes were examined for locations of 8-oxo-dG, the majority of 8-oxo-dGs (when present) were found in promoter regions rather than within gene bodies. Among hundreds of genes whose expression levels were affected by hypoxia, those with newly acquired promoter 8-oxo-dGs were upregulated, and those genes whose promoters lost 8-oxo-dGs were almost all downregulated.
== Positive role of 8-oxo-dG in memory ==
Oxidation of guanine, particularly within CpG sites, may be especially important in learning and memory. Methylation of cytosines occurs at 60–90% of CpG sites depending on the tissue type. In the mammalian brain, ~62% of CpGs are methylated. Methylation of CpG sites tends to stably silence genes. More than 500 of these CpG sites are de-methylated in neuron DNA during memory formation and memory consolidation in the hippocampus and cingulate cortex regions of the brain. As indicated below, the first step in de-methylation of methylated cytosine at a CpG site is oxidation of the guanine to form 8-oxo-dG.
=== Role of oxidized guanine in DNA de-methylation ===
The first figure in this section shows a CpG site where the cytosine is methylated to form 5-methylcytosine (5mC) and the guanine is oxidized to form 8-oxo-2'-deoxyguanosine (in the figure this is shown in the tautomeric form 8-OHdG). When this structure is formed, the base excision repair enzyme OGG1 targets 8-OHdG and binds to the lesion without immediate excision. OGG1, present at a 5mCp-8-OHdG site recruits TET1, and TET1 oxidizes the 5mC adjacent to the 8-OHdG. This initiates de-methylation of 5mC. TET1 is a key enzyme involved in de-methylating 5mCpG. However, TET1 is only able to act on 5mCpG if the guanine was first oxidized to form 8-hydroxy-2'-deoxyguanosine (8-OHdG or its tautomer 8-oxo-dG), resulting in a 5mCp-8-OHdG dinucleotide (see first figure in this section). This initiates the de-methylation pathway on the methylated cytosine, finally resulting in an unmethylated cytosine, shown in the second figure in this section.
Altered protein expression in neurons, due to changes in methylation of DNA, (likely controlled by 8-oxo-dG-dependent de-methylation of CpG sites in gene promoters within neuron DNA) has been established as central to memory formation.
== Neurological conditions ==
=== Bipolar disorder ===
Evidence that oxidative stress induced DNA damage plays a role in bipolar disorder has been reviewed by Raza et al. Bipolar patients have elevated levels of oxidatively induced DNA base damages even during periods of stable mental state. The level of the base excision repair enzyme OGG1 that removes certain oxidized bases from DNA is also reduced compared to healthy individuals.
=== Depressive disorder ===
Major depressive disorder is associated with an increase in oxidative DNA damage. Increases in oxidative modifications of purines and pyrimidines in depressive patients may be due to impaired repair of oxidative DNA damages.
=== Schizophrenia ===
Postmortem studies of elderly patients with chronic schizophrenia showed that oxidative DNA damage is increased in the hippocampus region of the brain. The mean proportion of neurons with the oxidized DNA base
8-oxo-dG was 10-fold higher in patients with schizophrenia than in comparison individuals. Evidence indicating a role of oxidative DNA damage in schizophrenia has been reviewed by Raza et al. and Markkanen et al.
== RNA Oxidation ==
RNAs in native milieu are exposed to various insults. Among these threats, oxidative stress is one of the major causes of damage to RNAs. The level of oxidative stress that a cell endures is reflected by the quantity of reactive oxygen species (ROS). ROS are generated from normal oxygen metabolism in cells and are recognized as a list of active molecules, such as O2•−, 1O2, H2O2 and, •OH . A nucleic acid can be oxidized by ROS through a Fenton reaction. To date, around 20 oxidative lesions have been discovered in DNA. RNAs are likely to be more sensitive to ROS for the following reasons: i) the basically single-stranded structure exposes more sites to ROS; ii) compared with nuclear DNA, RNAs are less compartmentalized; iii) RNAs distribute broadly in cells not only in the nucleus as DNAs do, but also in large portions in the cytoplasm. This theory has been supported by a series of discoveries from rat livers, human leukocytes, etc. Actually, monitoring a system by applying the isotopical label [18O]-H2O2 shows greater oxidation in cellular RNA than in DNA.
Oxidation randomly damages RNAs, and each attack bring problems to the normal cellular metabolism. Although alteration of genetic information on mRNA is relatively rare, oxidation on mRNAs in vitro and in vivo results in low translation efficiency and aberrant protein products.
Though the oxidation strikes the nucleic strands randomly, particular residues are more susceptible to ROS, such hotspot sites being hit by ROS at a high rate. Among all the lesions discovered thus far, one of the most abundant in DNA and RNA is the 8-hydroxyguanine. Moreover, 8-hydroxyguanine is the only one measurable among all the RNA lesions. Besides its abundance, 8-hydroxydeoxyguanosine (8-oxodG) and 8-hydroxyguanosine (8-oxoG) are identified as the most detrimental oxidation lesions for their mutagenic effect, in which this non-canonical counterpart can faultily pair with both adenine and cytosine at the same efficiency. This mis-pairing brings about the alteration of genetic information through the synthesis of DNA and RNA. In RNA, oxidation levels are mainly estimated through 8-oxoG-based assays. So far, approaches developed to directly measure 8-oxoG level include HPLC-based analysis and assays employing monoclonal anti-8-oxoG antibody. The HPLC-based method measures 8-oxoG with an electrochemical detector (ECD) and total G with a UV detector. The ratio that results from comparing the two numbers provides the extent that the total G is oxidized. Monoclonal anti-8-oxoG mouse antibody is broadly applied to directly detect this residue on either tissue sections or membrane, offering a more visual way to study its distribution in tissues and in discrete subsets of DNA or RNA. The established indirect techniques are mainly grounded on this lesion’s mutagenic aftermath, such as the lacZ assay. This method was first set up and described by Taddei and was a potentially powerful tool to understand the oxidation situation at both the RNA sequence level and single nucleotide level.
Another source of oxidized RNAs is mis-incorporation of oxidized counterpart of single nucleotides. Indeed, the RNA precursor pool size is hundreds of sizes bigger than DNA’s.
== Potential factors for RNA quality control ==
There have been furious debates on whether the issue of RNA quality control does exist. However, with the concern of various lengths of half lives of diverse RNA species ranging from several minutes to hours, degradation of defective RNA can not easily be attributed to its transient character anymore. Indeed, reaction with ROS takes only few minutes, which is even shorter than the average life-span of the most unstable RNAs. Adding the fact that stable RNA take the lion’s share of total RNA, RNA error deleting becomes hypercritical and should not be neglected anymore. This theory is upheld by the fact that level of oxidized RNA decreases after removal of the oxidative challenge.
Some potential factors include ribonucleases, which are suspected to selectively degrade damaged RNAs under stresses. Also enzymes working at RNA precursor pool level, are known to control quality of RNA sequence by changing error precursor to the form that can't be included directly into nascent strand.
== References == | Wikipedia/DNA_oxidation |
Methylated-DNA--protein-cysteine methyltransferase (MGMT), also known as O6-alkylguanine DNA alkyltransferase AGT, is a protein that in humans is encoded by the MGMT gene.
MGMT is crucial for genome stability. It repairs the naturally occurring mutagenic DNA lesion O6-methylguanine back to guanine and prevents mismatch and errors during DNA replication and transcription. Accordingly, loss of MGMT increases the carcinogenic risk in mice after exposure to alkylating agents.
The two bacterial isozymes are Ada and Ogt.
== Function and mechanism ==
Although alkylating mutagens preferentially modify the guanine base at the N7 position, O6-alkyl-guanine is a major carcinogenic lesion in DNA. This DNA adduct is removed by the repair protein O6-alkylguanine DNA alkyltransferase through an SN2 mechanism. This protein is not a true enzyme since it removes the alkyl group from the lesion in a stoichiometric reaction and the active enzyme is not regenerated after it is alkylated (referred to as a suicide enzyme). The methyl-acceptor residue in the protein is a cysteine.
→
M
G
M
T
{\displaystyle \mathrm {\ {\xrightarrow {MGMT}}} }
Demethylation of 6-O-methylguanosine to Guanosine
== Clinical significance ==
In patients with glioblastoma, a severe type of brain tumor, the cancer medicine temozolomide is more effective in those with a methylation of the gene's promoter. Overall, MGMT methylation is associated with prolonged patient survival in clinical prediction models. For testing of the MGMT promoter methylation status in the clinical setting, DNA-based methods such as methylation-specific polymerase chain reaction (MS-PCR) or pyrosequencing are preferred over immunohistochemical or RNA- based assays.
In patients with pituitary tumours, MGMT can predict the clinical and radiological response to treatment with temozolomide. In this context the MGMT status is optimally assessed by immunohistochemistry, with MGMT depleted tumours expected to demonstrate a response. Promotor methylation status (of MGMT) does not predict temozolomide response because, in pituitary tumours, the promotor is almost always unmethylated.
MGMT has also been shown to be a useful tool increasing gene therapy efficiency. By using a two component vector consisting of a transgene of interest and MGMT, in vivo drug selection can be utilized to select for successfully transduced cells.
Mutagens in the environment, in tobacco smoke, food, as well as endogenous metabolic products generate reactive electrophilic species that alkylate or specifically methylate DNA, generating 6-O-methylguanine (m6G).
In 1985 Yarosh summarized the early work that established m6G as the alkylated base in DNA that was the most mutagenic and carcinogenic. In 1994 Rasouli-Nia et al. showed that about one mutation was induced for every eight unrepaired m6Gs in DNA. Mutations can cause progression to cancer by a process of natural selection.
=== Expression in cancer ===
=== Epigenetic repression ===
Only a minority of sporadic cancers with a DNA repair deficiency have a mutation in a DNA repair gene. However, a majority of sporadic cancers with a DNA repair deficiency do have one or more epigenetic alterations that reduce or silence DNA repair gene expression. For example, in a study of 113 sequential colorectal cancers, only four had a missense mutation in the DNA repair gene MGMT, while the majority had reduced MGMT expression due to methylation of the MGMT promoter region (an epigenetic alteration).
MGMT can be epigenetically repressed in a number of ways. When MGMT expression is repressed in cancers, this is often due to methylation of its promoter region. However, expression can also be repressed by di-methylation of lysine 9 of histone 3 or by over-expression of a number of microRNAs including miR-181d, miR-767-3p and miR-603.
MGMT (O-6-methylguanine-DNA methyltransferase) is an important cancer biomarker because it is involved in the repair of DNA damage and is often silenced or inactivated in cancer cells. The loss of MGMT function leads to a higher rate of mutations, promoting the formation and progression of tumors. The presence or absence of MGMT expression in a cancer sample can indicate a patient's response to alkylating chemotherapy, which is a common treatment for certain types of cancer. Hence, MGMT can be used as a prognostic marker to predict the likelihood of treatment response and to guide the selection of appropriate therapies. A number of point-of-care devices are under development to monitor the methylation status of MGMT.
=== Deficiency in field defects ===
A field defect is an area or "field" of epithelium that has been preconditioned by epigenetic changes and/or mutations so as to predispose it towards development of cancer. A field defect is illustrated in the photo and diagram shown of a colon segment having a colon cancer and four small polyps within the same area as well. As pointed out by Rubin, "The vast majority of studies in cancer research has been done on well-defined tumors in vivo, or on discrete neoplastic foci in vitro. Yet there is evidence that more than 80% of the somatic mutations found in mutator phenotype human colorectal tumors occur before the onset of terminal clonal expansion." Similarly, Vogelstein et al. point out that more than half of somatic mutations identified in tumors occurred in a pre-neoplastic phase (in a field defect), during growth of apparently normal cells.
In the Table above, MGMT deficiencies were noted in the field defects (histologically normal tissues) surrounding most of the cancers. If MGMT is epigenetically reduced or silenced, it would not likely confer a selective advantage upon a stem cell. However, reduced or absent expression of MGMT would cause increased rates of mutation, and one or more of the mutated genes may provide the cell with a selective advantage. The expression-deficient MGMT gene could then be carried along as a selectively neutral or only slightly deleterious passenger (hitch-hiker) gene when the mutated stem cell generates an expanded clone. The continued presence of a clone with an epigenetically repressed MGMT would continue to generate further mutations, some of which could produce a tumor.
=== Deficiency with exogenous damage ===
MGMT deficiency alone may not be sufficient to cause progression to cancer. Mice with a homozygous mutation in MGMT did not develop more cancers than wild-type mice when grown without stress. However, stressful treatment of mice with azoxymethane and dextran sulphate caused more than four colonic tumors per MGMT mutant mouse, but less than one tumor per wild-type mouse.
=== Repression in coordination with other DNA repair genes ===
In a cancer, multiple DNA repair genes are often found to be simultaneously repressed. In one example, involving MGMT, Jiang et al. conducted a study where they evaluated the mRNA expression of 27 DNA repair genes in 40 astrocytomas compared to normal brain tissues from non-astrocytoma individuals. Among the 27 DNA repair genes evaluated, 13 DNA repair genes, MGMT, NTHL1, OGG1, SMUG1, ERCC1, ERCC2, ERCC3, ERCC4, MLH1, MLH3, RAD50, XRCC4 and XRCC5 were all significantly down-regulated in all three grades (II, III and IV) of astrocytomas. The repression of these 13 genes in lower grade as well as in higher grade astrocytomas suggested that they may be important in early as well as in later stages of astrocytoma. In another example, Kitajima et al. found that immunoreactivity for MGMT and MLH1 expression was closely correlated in 135 specimens of gastric cancer and loss of MGMT and hMLH1 appeared to be synchronously accelerated during tumor progression.
Deficient expression of multiple DNA repair genes are often found in cancers, and may contribute to the thousands of mutations usually found in cancers (see mutation frequencies in cancers).
== Interactions ==
O6-methylguanine-DNA methyltransferase has been shown to interact with estrogen receptor alpha.
== See also ==
Ada
ALKBH1
Ogt
6-O-Methylguanine
DNA methyltransferase
Methyltransferase
== References ==
== Further reading == | Wikipedia/O-6-methylguanine-DNA_methyltransferase |
Pyrimidine dimers represent molecular lesions originating from thymine or cytosine bases within DNA, resulting from photochemical reactions. These lesions, commonly linked to direct DNA damage, are induced by ultraviolet light (UV), particularly UVC, result in the formation of covalent bonds between adjacent nitrogenous bases along the nucleotide chain near their carbon–carbon double bonds, the photo-coupled dimers are fluorescent. Such dimerization, which can also occur in double-stranded RNA (dsRNA) involving uracil or cytosine, leads to the creation of cyclobutane pyrimidine dimers (CPDs) and 6–4 photoproducts. These pre-mutagenic lesions modify the DNA helix structure, resulting in abnormal non-canonical base pairing and, consequently, adjacent thymines or cytosines in DNA will form a cyclobutane ring when joined together and cause a distortion in the DNA. This distortion prevents DNA replication and transcription mechanisms beyond the dimerization site.
While up to 100 such reactions per second may transpire in a skin cell exposed to sunlight resulting in DNA damage, they are typically rectified promptly through DNA repair, such as through photolyase reactivation or nucleotide excision repair, with the latter being prevalent in humans. Conversely, certain bacteria utilize photolyase, powered by sunlight, to repair pyrimidine dimer-induced DNA damage. Unrepaired lesions may lead to erroneous nucleotide incorporation by polymerase machinery. Overwhelming DNA damage can precipitate mutations within an organism's genome, potentially culminating in cancer cell formation. Unrectified lesions may also interfere with polymerase function, induce transcription or replication errors, or halt replication. Notably, pyrimidine dimers contribute to sunburn and melanin production, and are a primary factor in melanoma development in humans.
== Types of pyrimidine dimers ==
Pyrimidine dimers encompass several types, each with distinct structures and implications for DNA integrity.
Cyclobutane pyrimidine dimer (CPD) is a dimer which features a four-membered ring formed by the fusion of two double-bonded carbons from adjacent pyrimidines. CPDs disrupt the formation of the base pair during DNA replication, potentially leading to mutations.
The 6–4 photoproduct (6–4 pyrimidine–pyrimidone, or 6–4 pyrimidine–pyrimidinone) is an alternate dimer configuration consisting of a single covalent bond linking the carbon at the 6 (C6) position of one pyrimidine ring and carbon at the 4 (C4) position of the adjoining base's ring. This type of conversion occurs at one third the frequency of CPDs and has a higher mutagenic risk.
A third type of molecular lesion is a Dewar pyrimidinone, resulting from the reversible isomerization of a 6–4 photoproduct under further light exposure.
== Mutagenesis ==
Mutagenesis, the process of mutation formation, is significantly influenced by translesion polymerases which often introduce mutations at sites of pyrimidine dimers. This occurrence is noted both in prokaryotes, through the SOS response to mutagenesis, and in eukaryotes. Despite thymine-thymine CPDs being the most common lesions induced by UV, translesion polymerases show a tendency to incorporate adenines, resulting in the accurate replication of thymine dimers more often than not. Conversely, cytosines that are part of CPDs are susceptible to deamination, leading to a cytosine to thymine transition, thereby contributing to the mutation process.
== DNA repair ==
Pyrimidine dimers introduce local conformational changes in the DNA structure, which allow recognition of the lesion by repair enzymes. In most organisms (excluding placental mammals such as humans) they can be repaired by photoreactivation. Photoreactivation is a repair process in which photolyase enzymes reverse CPDs using photochemical reactions. In addition, some photolyases can also repair 6-4 photoproducts of UV induced DNA damage. Photolyase enzymes utilize flavin adenine dinucleotide (FAD) as a cofactor in the repair process.
The UV dose that reduces a population of wild-type yeast cells to 37% survival is equivalent (assuming a Poisson distribution of hits) to the UV dose that causes an average of one lethal hit to each of the cells of the population. The number of pyrimidine dimers induced per haploid genome at this dose was measured as 27,000. A mutant yeast strain defective in the three pathways by which pyrimidine dimers were known to be repaired in yeast was also tested for UV sensitivity. It was found in this case that only one or, at most, two unrepaired pyrimidine dimers per haploid genome are lethal to the cell. These findings thus indicate that the repair of thymine dimers in wild-type yeast is highly efficient.
Nucleotide excision repair, sometimes termed "dark reactivation", is a more general mechanism for repair of lesions and is the most common form of DNA repair for pyrimidine dimers in humans. This process works by using cellular machinery to locate the dimerized nucleotides and excise the lesion. Once the CPD is removed, there is a gap in the DNA strand that must be filled. DNA machinery uses the undamaged complementary strand to synthesize nucleotides off of and consequently fill in the gap on the previously damaged strand.
Xeroderma pigmentosum (XP) is a rare genetic disease in humans in which genes that encode for NER proteins are mutated and result in decreased ability to combat pyrimidine dimers that form as a result of UV damage. Individuals with XP are also at a much higher risk of cancer than others, with a greater than 5,000 fold increased risk of developing skin cancers. Some common features and symptoms of XP include skin discoloration, and the formation of multiple tumors proceeding UV exposure.
A few organisms have other ways to perform repairs:
Spore photoproduct lyase is found in spore-forming bacteria. It returns thymine dimers to their original state.
Deoxyribodipyrimidine endonucleosidase is found in bacteriophage T4. It is a base excision repair enzyme specific for pyrimidine dimers. It is then able to cut open the AP site.
Another type of repair mechanism that is conserved in humans and other non-mammals is translesion synthesis. Typically, the lesion associated with the pyrimidine dimer blocks cellular machinery from synthesizing past the damaged site. However, in translesion synthesis, the CPD is bypassed by translesion polymerases, and replication and or transcription machinery can continue past the lesion. One specific translesion DNA polymerase, DNA polymerase η, is deficient in individuals with XPD.
== Effect of topical sunscreen and effect of absorbed sunscreen ==
Direct DNA damage is reduced by sunscreen, which also reduces the risk of developing a sunburn. When the sunscreen is at the surface of the skin, it filters the UV rays, which attenuates the intensity. Even when the sunscreen molecules have penetrated into the skin, they protect against direct DNA damage, because the UV light is absorbed by the sunscreen and not by the DNA. Sunscreen primarily works by absorbing the UV light from the sun through the use of organic compounds, such as oxybenzone or avobenzone. These compounds are able to absorb UV energy from the sun and transition into higher-energy states. Eventually, these molecules return to lower energy states, and in doing so, the initial energy from the UV light can be transformed into heat. This process of absorption works to reduce the risk of DNA damage and the formation of pyrimidine dimers. UVA light makes up 95% of the UV light that reaches earth, whereas UVB light makes up only about 5%. UVB light is the form of UV light that is responsible for tanning and burning. Sunscreens work to protect from both UVA and UVB rays. Overall, sunburns exemplify DNA damage caused by UV rays, and this damage can come in the form of free radical species, as well as dimerization of adjacent nucleotides.
== See also ==
DNA repair
== References == | Wikipedia/Direct_DNA_damage |
Neuronal PAS domain protein 4 is a protein that in humans is encoded by the NPAS4 gene. The NPAS4 gene is a neuronal activity-dependent immediate early gene that has been identified as a transcription factor. The protein regulates the transcription of genes that control inhibitory synapse development, synaptic plasticity and most recently reported also behavior.
== Function ==
NPAS4 is a member of the basic helix-loop-helix-PER-ARNT-SIM (bHLH-PAS) class of transcriptional regulators, which are involved in a wide range of physiologic and developmental events (Ooe et al., 2004 [PubMed 14701734]).[supplied by OMIM, Mar 2008].
NPAS4 has been shown by Dr. Brenda Bloodgood to play critical roles in regulating the plasticity of inhibitory neurons. She found that NPAS4 helps to regulate plasticity by orchestrating a redistribution of inhibitory synapses, wherein they are lost from proximal apical dendrites of CA1 pyramidal neurons and increased on the somata.
== References ==
== Further reading ==
This article incorporates text from the United States National Library of Medicine, which is in the public domain. | Wikipedia/Neuronal_PAS_domain_protein_4 |
DNA mismatch repair (MMR) is a system for recognizing and repairing erroneous insertion, deletion, and mis-incorporation of bases that can arise during DNA replication and recombination, as well as repairing some forms of DNA damage.
Mismatch repair is strand-specific. During DNA synthesis the newly synthesised (daughter) strand will commonly include errors. In order to begin repair, the mismatch repair machinery distinguishes the newly synthesised strand from the template (parental). In gram-negative bacteria, transient hemimethylation distinguishes the strands (the parental is methylated and daughter is not). However, in other prokaryotes and eukaryotes, the exact mechanism is not clear. It is suspected that, in eukaryotes, newly synthesized lagging-strand DNA transiently contains nicks (before being sealed by DNA ligase) and provides a signal that directs mismatch proofreading systems to the appropriate strand. This implies that these nicks must be present in the leading strand, and evidence for this has recently been found.
Recent work has shown that nicks are sites for RFC-dependent loading of the replication sliding clamp, proliferating cell nuclear antigen (PCNA), in an orientation-specific manner, such that one face of the donut-shape protein is juxtaposed toward the 3'-OH end at the nick. Loaded PCNA then directs the action of the MutLalpha endonuclease to the daughter strand in the presence of a mismatch and MutSalpha or MutSbeta.
Any mutational event that disrupts the superhelical structure of DNA carries with it the potential to compromise the genetic stability of a cell. The fact that the damage detection and repair systems are as complex as the replication machinery itself highlights the importance evolution has attached to DNA fidelity.
Examples of mismatched bases include a G/T or A/C pairing (see DNA repair). Mismatches are commonly due to tautomerization of bases during DNA replication. The damage is repaired by recognition of the deformity caused by the mismatch, determining the template and non-template strand, and excising the wrongly incorporated base and replacing it with the correct nucleotide. The removal process involves more than just the mismatched nucleotide itself. A few or up to thousands of base pairs of the newly synthesized DNA strand can be removed.
== Mismatch repair proteins ==
Mismatch repair is a highly conserved process from prokaryotes to eukaryotes. The first evidence for mismatch repair was obtained from S. pneumoniae (the hexA and hexB genes). Subsequent work on E. coli has identified a number of genes that, when mutationally inactivated, cause hypermutable strains. The gene products are, therefore, called the "Mut" proteins, and are the major active components of the mismatch repair system. Three of these proteins are essential in detecting the mismatch and directing repair machinery to it: MutS, MutH and MutL (MutS is a homologue of HexA and MutL of HexB).
MutS forms a dimer (MutS2) that recognises the mismatched base on the daughter strand and binds the mutated DNA. MutH binds at hemimethylated sites along the daughter DNA, but its action is latent, being activated only upon contact by a MutL dimer (MutL2), which binds the MutS-DNA complex and acts as a mediator between MutS2 and MutH, activating the latter. The DNA is looped out to search for the nearest d(GATC) methylation site to the mismatch, which could be up to 1 kb away. Upon activation by the MutS-DNA complex, MutH nicks the daughter strand near the hemimethylated site. MutL recruits UvrD helicase (DNA Helicase II) to separate the two strands with a specific 3' to 5' polarity. The entire MutSHL complex then slides along the DNA in the direction of the mismatch, liberating the strand to be excised as it goes. An exonuclease trails the complex and digests the ss-DNA tail. The exonuclease recruited is dependent on which side of the mismatch MutH incises the strand – 5' or 3'. If the nick made by MutH is on the 5' end of the mismatch, either RecJ or ExoVII (both 5' to 3' exonucleases) is used. If, however, the nick is on the 3' end of the mismatch, ExoI (a 3' to 5' enzyme) is used.
The entire process ends past the mismatch site – i.e., both the site itself and its surrounding nucleotides are fully excised. The single-strand gap created by the exonuclease can then be repaired by DNA Polymerase III (assisted by single-strand-binding protein), which uses the other strand as a template, and finally sealed by DNA ligase. DNA methylase then rapidly methylates the daughter strand.
=== MutS homologs ===
When bound, the MutS2 dimer bends the DNA helix and shields approximately 20 base pairs. It has weak ATPase activity, and binding of ATP leads to the formation of tertiary structures on the surface of the molecule. The crystal structure of MutS reveals that it is exceptionally asymmetric, and, while its active conformation is a dimer, only one of the two halves interacts with the mismatch site.
In eukaryotes, MutS homologs form two major heterodimers: Msh2/Msh6 (MutSα) and Msh2/Msh3 (MutSβ). The MutSα pathway is involved primarily in base substitution and small-loop mismatch repair. The MutSβ pathway is also involved in small-loop repair, in addition to large-loop (~10 nucleotide loops) repair. However, MutSβ does not repair base substitutions.
=== MutL homologs ===
MutL also has weak ATPase activity (it uses ATP for purposes of movement). It forms a complex with MutS and MutH, increasing the MutS footprint on the DNA.
However, the processivity (the distance the enzyme can move along the DNA before dissociating) of UvrD is only ~40–50 bp. Because the distance between the nick created by MutH and the mismatch can average ~600 bp, if there is not another UvrD loaded the unwound section is then free to re-anneal to its complementary strand, forcing the process to start over. However, when assisted by MutL, the rate of UvrD loading is greatly increased. While the processivity (and ATP utilisation) of the individual UvrD molecules remains the same, the total effect on the DNA is boosted considerably; the DNA has no chance to re-anneal, as each UvrD unwinds 40-50 bp of DNA, dissociates, and then is immediately replaced by another UvrD, repeating the process. This exposes large sections of DNA to exonuclease digestion, allowing for quick excision (and later replacement) of the incorrect DNA.
Eukaryotes have five MutL homologs designated as MLH1, MLH2, MLH3, PMS1, and PMS2. They form heterodimers that mimic MutL in E. coli. The human homologs of prokaryotic MutL form three complexes referred to as MutLα, MutLβ, and MutLγ. The MutLα complex is made of MLH1 and PMS2 subunits, the MutLβ heterodimer is made of MLH1 and PMS1, whereas MutLγ is made of MLH1 and MLH3. MutLα acts as an endonuclease that introduces strand breaks in the daughter strand upon activation by mismatch and other required proteins, MutSα and PCNA. These strand interruptions serve as entry points for an exonuclease activity that removes mismatched DNA. Roles played by MutLβ and MutLγ in mismatch repair are less-understood.
=== MutH: an endonuclease present in E. coli and Salmonella ===
MutH is a very weak endonuclease that is activated once bound to MutL (which itself is bound to MutS). It nicks unmethylated DNA and the unmethylated strand of hemimethylated DNA but does not nick fully methylated DNA. Experiments have shown that mismatch repair is random if neither strand is methylated. These behaviours led to the proposal that MutH determines which strand contains the mismatch.
MutH has no eukaryotic homolog. Its endonuclease function is taken up by MutL homologs, which have some specialized 5'-3' exonuclease activity. The strand bias for removing mismatches from the newly synthesized daughter strand in eukaryotes may be provided by the free 3' ends of Okazaki fragments in the new strand created during replication.
=== PCNA β-sliding clamp ===
PCNA and the β-sliding clamp associate with MutSα/β and MutL, respectively. Although initial reports suggested that the PCNA-MutSα complex may enhance mismatch recognition, it has been recently demonstrated that there is no apparent change in affinity of MutSα for a mismatch in the presence or absence of PCNA. Furthermore, mutants of MutSα that are unable to interact with PCNA in vitro exhibit the capacity to carry out mismatch recognition and mismatch excision to near wild type levels. Such mutants are defective in the repair reaction directed by a 5' strand break, suggesting for the first time MutSα function in a post-excision step of the reaction.
== Clinical significance ==
=== Inherited defects in mismatch repair ===
Mutations in the human homologues of the Mut proteins affect genomic stability, which can result in microsatellite instability (MSI), implicated in some human cancers. In specific, the hereditary nonpolyposis colorectal cancers (HNPCC or Lynch syndrome) are attributed to damaging germline variants in the genes encoding the MutS and MutL homologues MSH2 and MLH1 respectively, which are thus classified as tumour suppressor genes. One subtype of HNPCC, the Muir-Torre Syndrome (MTS), is associated with skin tumors. If both inherited copies (alleles) of a MMR gene bear damaging genetic variants, this results in a very rare and severe condition: the mismatch repair cancer syndrome (or constitutional mismatch repair deficiency, CMMR-D), manifesting as multiple occurrences of tumors at an early age, often colon and brain tumors.
=== Epigenetic silencing of mismatch repair genes ===
Sporadic cancers with a DNA repair deficiency only rarely have a mutation in a DNA repair gene, but they instead tend to have epigenetic alterations such as promoter methylation that inhibit DNA repair gene expression. About 13% of colorectal cancers are deficient in DNA mismatch repair, commonly due to loss of MLH1 (9.8%), or sometimes MSH2, MSH6 or PMS2 (all ≤1.5%). For most MLH1-deficient sporadic colorectal cancers, the deficiency was due to MLH1 promoter methylation. Other cancer types have higher frequencies of MLH1 loss (see table below), which are again largely a result of methylation of the promoter of the MLH1 gene. A different epigenetic mechanism underlying MMR deficiencies might involve over-expression of a microRNA, for example miR-155 levels inversely correlate with expression of MLH1 or MSH2 in colorectal cancer.
=== MMR failures in field defects ===
A field defect (field cancerization) is an area of epithelium that has been preconditioned by epigenetic or genetic changes, predisposing it towards development of cancer. As pointed out by Rubin " ...there is evidence that more than 80% of the somatic mutations found in mutator phenotype human colorectal tumors occur before the onset of terminal clonal expansion." Similarly, Vogelstein et al. point out that more than half of somatic mutations identified in tumors occurred in a pre-neoplastic phase (in a field defect), during growth of apparently normal cells.
MLH1 deficiencies were common in the field defects (histologically normal tissues) surrounding tumors; see Table above. Epigenetically silenced or mutated MLH1 would likely not confer a selective advantage upon a stem cell, however, it would cause increased mutation rates, and one or more of the mutated genes may provide the cell with a selective advantage. The deficientMLH1 gene could then be carried along as a selectively near-neutral passenger (hitch-hiker) gene when the mutated stem cell generates an expanded clone. The continued presence of a clone with an epigenetically repressed MLH1 would continue to generate further mutations, some of which could produce a tumor.
=== MSI and immune checkpoint blockade response ===
MMR and mismatch repair mutations were initially observed to associate with immune checkpoint blockade efficacy in a study examining responders to anti-PD1. The association between MSI positivity and positive response to anti-PD1 was subsequently validated in a prospective clinical trial and approved by the FDA.
=== MMR components in humans ===
In humans, seven DNA mismatch repair (MMR) proteins (MLH1, MLH3, MSH2, MSH3, MSH6, PMS1 and PMS2) work coordinately in sequential steps to initiate repair of DNA mismatches. In addition, there are Exo1-dependent and Exo1-independent MMR subpathways.
Other gene products involved in mismatch repair (subsequent to initiation by MMR genes) in humans include DNA polymerase delta, PCNA, RPA, HMGB1, RFC and DNA ligase I, plus histone and chromatin modifying factors.
In certain circumstances, the MMR pathway may recruit an error-prone DNA polymerase eta (POLH). This happens in B-lymphocytes during somatic hypermutation, where POLH is used to introduce genetic variation into antibody genes. However, this error-prone MMR pathway may be triggered in other types of human cells upon exposure to genotoxins and indeed it is broadly active in various human cancers, causing mutations that bear a signature of POLH activity.
=== MMR and mutation frequency ===
Recognizing and repairing mismatches and indels is important for cells because failure to do so results in microsatellite instability (MSI) and an elevated spontaneous mutation rate (mutator phenotype). In comparison to other cancer types, MMR-deficient (MSI) cancer has a very high frequency of mutations, close to melanoma and lung cancer, cancer types caused by much exposure to UV radiation and mutagenic chemicals.
In addition to a very high mutation burden, MMR deficiencies result in an unusual distribution of somatic mutations across the human genome: this suggests that MMR preferentially protects the gene-rich, early-replicating euchromatic regions. In contrast, the gene-poor, late-replicating heterochromatic genome regions exhibit high mutation rates in many human tumors.
The histone modification H3K36me3, an epigenetic mark of active chromatin, has the ability to recruit the MSH2-MSH6 (hMutSα) complex. Consistently, regions of the human genome with high levels of H3K36me3 accumulate less mutations due to MMR activity.
=== Loss of multiple DNA repair pathways in tumors ===
Lack of MMR often occurs in coordination with loss of other DNA repair genes. For example, MMR genes MLH1 and MLH3 as well as 11 other DNA repair genes (such as MGMT and many NER pathway genes) were significantly down-regulated in lower grade as well as in higher grade astrocytomas, in contrast to normal brain tissue. Moreover, MLH1 and MGMT expression was closely correlated in 135 specimens of gastric cancer and loss of MLH1 and MGMT appeared to be synchronously accelerated during tumor progression.
Deficient expression of multiple DNA repair genes is often found in cancers, and may contribute to the thousands of mutations usually found in cancers (see Mutation frequencies in cancers).
== In mitochondria ==
Although several DNA repair pathways have been reported to occur in the mitochondria, currently the DNA mismatch repair pathway is the pathway that is most comprehensively described. The proteins acting in the maintenance of mitochondrial DNA are encoded by nuclear genes and translocated to the mitochondria. The mitochondria of human cells are able to repair DNA base pair mismatches using a pathway that is distinct from the DNA mismatch repair pathway of the nucleus. This distinct mitochondrial mismatch repair pathway includes the activity of the Y box binding protein 1 (designated YB-1 or YBX1), that is considered to act in the mismatch binding and recognition steps of mismatch repair. DNA repair mechanisms that are specific to the mitochondria may reflect the proximity of the mitochondrial DNA to the system of oxidative phosphorylation and consequently to the DNA-damaging reactive oxygen species formed in association with ATP production.
== Aging ==
A popular idea, that has failed to gain significant experimental support, is the idea that mutation, as distinct from DNA damage, is the primary cause of aging. Mice defective in the mutL homolog Pms2 have about a 100-fold elevated mutation frequency in all tissues, but do not appear to age more rapidly. These mice display mostly normal development and life, except for early onset carcinogenesis and male infertility.
== See also ==
Base excision repair
Nucleotide excision repair
== References ==
== Further reading ==
== External links ==
DNA Repair Archived 2018-02-12 at the Wayback Machine
DNA+Mismatch+Repair at the U.S. National Library of Medicine Medical Subject Headings (MeSH) | Wikipedia/DNA_mismatch_repair |
Apoptosis regulator BAX, also known as bcl-2-like protein 4, is a protein that in humans is encoded by the BAX gene. BAX is a member of the Bcl-2 gene family. BCL2 family members form hetero- or homodimers and act as anti- or pro-apoptotic regulators that are involved in a wide variety of cellular activities. This protein forms a heterodimer with BCL2, and functions as an apoptotic activator. This protein is reported to interact with, and increase the opening of, the mitochondrial voltage-dependent anion channel (VDAC), which leads to the loss in membrane potential and the release of cytochrome c. The expression of this gene is regulated by the tumor suppressor P53 and has been shown to be involved in P53-mediated apoptosis.
== Structure ==
The BAX gene was the first identified pro-apoptotic member of the Bcl-2 protein family. Bcl-2 family members share one or more of the four characteristic domains of homology entitled the Bcl-2 homology (BH) domains (named BH1, BH2, BH3 and BH4), and can form hetero- or homodimers. These domains are composed of nine α-helices, with a hydrophobic α-helix core surrounded by amphipathic helices and a transmembrane C-terminal α-helix anchored to the mitochondrial outer membrane (MOM). A hydrophobic groove formed along the C-terminal of α2 to the N-terminal of α5, and some residues from α8, binds the BH3 domain of other BAX or BCL-2 proteins in its active form. In the protein's inactive form, the groove binds its transmembrane domain, transitioning it from a membrane-bound to a cytosolic protein. A smaller hydrophobic groove formed by the α1 and α6 helices is located on the opposite side of the protein from the major groove, and may serve as a BAX activation site.
Orthologs of the BAX gene have been identified in most mammals for which complete genome data are available.
== Function ==
In healthy mammalian cells, the majority of BAX is found in the cytosol, but upon initiation of apoptotic signaling, Bax undergoes a conformational shift. Upon induction of apoptosis, BAX becomes organelle membrane-associated, and in particular, mitochondrial membrane associated.
BAX is believed to interact with, and induce the opening of the mitochondrial voltage-dependent anion channel, VDAC. Alternatively, growing evidence also suggests that activated BAX and/or Bak form an oligomeric pore, MAC in the MOM (mitochondrial outer membrane). This results in the release of cytochrome c and other pro-apoptotic factors from the mitochondria, often referred to as mitochondrial outer membrane permeabilization, leading to activation of caspases. This defines a direct role for BAX in mitochondrial outer membrane permeabilization. BAX activation is stimulated by various abiotic factors, including heat, hydrogen peroxide, low or high pH, and mitochondrial membrane remodeling. In addition, it can become activated by binding BCL-2, as well as non-BCL-2 proteins such as p53 and Bif-1. Conversely, BAX can become inactivated by interacting with VDAC2, Pin1, and IBRDC2.
== Clinical significance ==
The expression of BAX is upregulated by the tumor suppressor protein p53, and BAX has been shown to be involved in p53-mediated apoptosis. The p53 protein is a transcription factor that, when activated as part of the cell's response to stress, regulates many downstream target genes, including BAX. Wild-type p53 has been demonstrated to upregulate the transcription of a chimeric reporter plasmid utilizing the consensus promoter sequence of BAX approximately 50-fold over mutant p53. Thus it is likely that p53 promotes BAX's apoptotic faculties in vivo as a primary transcription factor. However, p53 also has a transcription-independent role in apoptosis. In particular, p53 interacts with BAX, promoting its activation as well as its insertion into the mitochondrial membrane.
Drugs that activate BAX, such as ABT-737, a BH3 mimetic, hold promise as anticancer treatments by inducing apoptosis in cancer cells. For instance, binding of HA-BAD to BCL-xL and concomitant disruption of BAX:BCL-xL interaction was found to partly reverse paclitaxel resistance in human ovarian cancer cells. Meanwhile, excessive apoptosis in such conditions as ischemia reperfusion injury and amyotrophic lateral sclerosis may benefit from drug inhibitors of BAX.
== Interactions ==
Bcl-2-associated X protein has been shown to interact with:
== See also ==
== References ==
== External links ==
Human BAX genome location and BAX gene details page in the UCSC Genome Browser.
Overview of all the structural information available in the PDB for UniProt: Q07812 (Human Apoptosis regulator BAX) at the PDBe-KB.
Overview of all the structural information available in the PDB for UniProt: Q07813 (Mouse Apoptosis regulator BAX) at the PDBe-KB. | Wikipedia/BAX_protein |
In molecular genetics, a DNA adduct is a segment of DNA bound to a cancer-causing chemical. This process could lead to the development of cancerous cells, or carcinogenesis. DNA adducts in scientific experiments are used as biomarkers of exposure. They are especially useful in quantifying an organism's exposure to a carcinogen. The presence of such an adduct indicates prior exposure to a potential carcinogen, but it does not necessarily indicate the presence of cancer in the subject animal.
DNA adducts are researched in laboratory settings. A typical experimental design for studying DNA adducts is to induce them with known carcinogens. A scientific journal will often incorporate the name of the carcinogen with their experimental design. For example, the term "DMBA-DNA adduct" in a scientific journal refers to a piece of DNA that has DMBA (7,12-dimethylbenz(a)anthracene) attached to it.
== Carcinogens' impact ==
Several diseases, including cancer, develop from mutated DNA. These mutations are caused by carcinogens through external and internal factors. Carcinogens are chemical or physical agents that cause DNA damage, which may later develop into cancer. They can initiate mutagenesis in DNA by interfering with the replication process. These interactions typically cause chemical adducts to form in the cell. This allows for DNA adducts to serve as biomarkers of exposure to carcinogens from the environment. They are attractive biomarkers because they are stable, abundant, and easily characterizable. Exposure to them can directly or indirectly cause DNA damage. In the direct case, a carcinogen can bind to DNA and cause it to distort or become cross-linked. Although DNA repair happens under normal circumstances, sometimes the DNA will not repair itself. This could be the start of a mutation, or mutagenesis. Repeated mutations can lead to carcinogenesis – the beginnings of cancer.
The presence of endogenous carcinogens contributes to levels of DNA adducts in a patient. This can bias the quantification of carcinogens that are from environmental exposure. Ongoing research on DNA adducts seeks to overcome these complications. It is the hope that in future medical practices DNA adducts may serve to guide therapeutic treatments that are more targeted and effective.
=== Mechanism of DNA damage ===
Adduct formation is determined by the structures of reactive chemicals, the movement(s) of electrophiles, and the capacity of the compounds to bind with DNA, potentially driving adduct formation to specific nucleophilic sites. The N3 and N7 locations (nucleotide positioning) of guanine and adenine are believed to be the most nucleophilic, and hence, they form adducts selectively over exocyclic oxygen atoms. The generation of DNA adducts is also influenced by certain steric factors. Guanine's N7 position is exposed in the major groove of double-helical DNA, making it more suitable for adduction than when compared to adenine's N3 position, which is orientated in the minor groove.
Many compounds require enzyme metabolic activation to become mutagenic and cause DNA damage. Furthermore, reactive intermediates can be produced in the body as a result of oxidative stress, thus harming the DNA. Some chemical carcinogens, metabolites, as well as endogenous compounds generated by inflammatory processes cause oxidative stress. This can result in the formation of a reactive oxygen species (ROS) or reactive nitrogen species (RNS). ROS and RNS are known to cause DNA damage via oxidative processes. Figure 2 shows each of the reactive sites for the nucleic acids involved in adduction and damage, with each form of transfer distinguished by arrow color. These positions are of interest to researchers studying DNA adduct formation. Research has indicated that many different chemicals may change human DNA and that lifestyle and host characteristics can impact the extent of DNA damage. Humans are constantly exposed to a diverse combination of potentially dangerous substances that might cause DNA damage.
== Chemicals that form DNA adducts ==
acetaldehyde, a significant constituent of tobacco smoke
cisplatin, which binds to DNA and causes crosslinking (leading to cell death)
DMBA (7,12-dimethylbenz(a)anthracene)
malondialdehyde, a naturally-occurring product of lipid peroxidation
polycyclic aromatic hydrocarbons (PAHs)
nitro-PAHs
Nitrosamines
Aflatoxins
Mustards
aromatic amines
heterocyclic aromatic amines (HAAs)
methylating agents
other alkylating agents
Haloalkanes
== Detection methods ==
32P-postlabeling assay:
32P-postlabeling assays screen for DNA adducts by transferring 32P-ATP into a carcinogenic labeled nucleotide sequence, with selectivity favoring modified nucleotides.
Liquid chromatography–mass spectrometry (LC–MS):
Liquid chromatography–mass spectrometry to a greater extent has replaced the 32P-postlabeling assay as the method of choice for the detection of structurally characterized DNA adducts.
Fluorescence labeling:
Certain DNA adducts can also be detected by the means of fluorescence because they contain fluorescent chromophores.
Enzyme linked immunosorbent assay (ELISA):
ELISA contains an antigen in solution that can bind with DNA adducts. Any remaining free antigen will fluoresce. This allows ELISA to quantify DNA adducts as well as map an inverse relationship between DNA damage and the intensity of the samples fluorescence.
== DNA adduct as biomarkers of exposure ==
=== Beef diet ===
Human consumption of more than 2.5–3.5 oz (70–100 g) of red meat (beef, lamb or pork) a day increases the risk of colon cancer, but eating chicken does not have this risk. The increased risk of colon cancer from red meat may be due to higher increases in DNA adducts from digestion of red meat. When rats were fed either beef or chicken, three types of DNA adducts in colon tissue were significantly higher after consumption of beef than after consumption of chicken. These adducts were a type of methyl-cytosine (possibly N3-methyl-cytosine), an adduct of two malondialdehyde molecules with guanine, and carboxyl-adenine.
=== Tobacco use ===
Human exposure to tobacco smoke has been associated with an increased risk of lung cancer. Tobacco smoke can impose great risk to DNA, with chemicals such as formaldehyde and acetaldehyde reacting directly with DNA to form adducts. In addition, there are other tobacco-specific carcinogens to consider in humans that are activated metabolically, such as nicotine-derived nitrosamine ketone (NNK) and N'-nitrosonornicotine (NNN). These carcinogens end up forming adducts when reacted with DNA, with those being called pyridyl oxobutyl (POB) adducts.
Further analysis has been conducted on the topic, determining that 1,3-Butadiene (BD) is a human carcinogen that is found in cigarette smoke among other synthetic polymer industries. Tests were conducted to understand the differences in the level of urinary BD-DNA adducts among various ethnic groups – white, Japanese American, and Native Hawaiian. It was determined that Japanese American smokers exhibited heightened levels of urinary BD-induced guanine adducts than white and Native Hawaiian individuals, while there were no differences in outcome by ethnicity among non-smokers. Understanding the epigenetic and genetic factors driving these differences in urinary BD-DNA adduct presence is the next step for this research, serving as a link between sociology and the life sciences.
=== Airborne particulate matter ===
Particulate matter (PM), broadly known as air pollution, is considered a group 1 carcinogen by the International Agency for Research on Cancer; while it is unclear if a direct link between cancer and PM exposure exists, it is likely that PM exposure leads to some degree of cell damage. Upon further investigation, it was determined that PM exposure causes oxidative stress – creating reactive oxygen species, forming DNA adducts, and inducing double-strand breaks (DSBs). In regards to DNA adduct formation, this analysis was conducted after looking at leukocytes from residents of heavily-populated cities (e.g. pollution, long-term traffic); a common component of PMs, polycyclic aromatic hydrocarbon (PAH), was one of the many molecules considered to be highly correlated with the presence of DNA bulky lesions in these individuals. These findings support the theory that DNA adduct presence indicates a level of carcinogenic activity.
== See also ==
Adduct
Adductomics
== References == | Wikipedia/DNA_adduct |
The origin and function of meiosis are currently not well understood scientifically, and would provide fundamental insight into the evolution of sexual reproduction in eukaryotes. There is no current consensus among biologists on the questions of how sex in eukaryotes arose in evolution, what basic function sexual reproduction serves, and why it is maintained, given the basic two-fold cost of sex. It is clear that it evolved over 1.2 billion years ago, and that almost all species which are descendants of the original sexually reproducing species are still sexual reproducers, including plants, fungi, and animals.
Meiosis is a key event of the sexual cycle in eukaryotes. It is the stage of the life cycle when a cell gives rise to haploid cells (gametes) each having half as many chromosomes as the parental cell. Two such haploid gametes, ordinarily arising from different individual organisms, fuse by the process of fertilization, thus completing the sexual cycle.
Meiosis is ubiquitous among eukaryotes. It occurs in single-celled organisms such as yeast, as well as in multicellular organisms, such as humans. Eukaryotes arose from prokaryotes more than 2.2 billion years ago and the earliest eukaryotes were likely single-celled organisms. To understand sex in eukaryotes, it is necessary to understand (1) how meiosis arose in single celled eukaryotes, and (2) the function of meiosis.
== Origin of meiosis ==
There are two conflicting theories on how meiosis arose. One is that meiosis evolved from prokaryotic sex (bacterial recombination) as eukaryotes evolved from prokaryotes. The other is that meiosis arose from mitosis.
=== From prokaryotic sex ===
In prokaryotic sex, DNA from one prokaryote is taken up by another prokaryote and its information integrated into the DNA of the recipient prokaryote. In extant prokaryotes the donor DNA can be transferred either by transformation or conjugation. Transformation in which DNA from one prokaryote is released into the surrounding medium and then taken up by another prokaryotic cell may have been the earliest form of sexual interaction. One theory on how meiosis arose is that it evolved from transformation. According to this view, the evolutionary transition from prokaryotic sex to eukaryotic sex was continuous.
Transformation, like meiosis, is a complex process requiring the function of numerous gene products. A key similarity between prokaryotic sex and eukaryotic sex is that DNA originating from two different individuals (parents) join up so that homologous sequences are aligned with each other, and this is followed by exchange of genetic information (a process called genetic recombination). After the new recombinant chromosome is formed it is passed on to progeny.
When genetic recombination occurs between DNA molecules originating from different parents, the recombination process is catalyzed in prokaryotes and eukaryotes by enzymes that have similar functions and that are evolutionarily related. One of the most important enzymes catalyzing this process in bacteria is referred to as RecA, and this enzyme has two functionally similar counterparts that act in eukaryotic meiosis, RAD51 and DMC1.
Support for the theory that meiosis arose from prokaryotic transformation comes from the increasing evidence that early diverging lineages of eukaryotes have the core genes for meiosis. This implies that the precursor to meiosis was already present in the prokaryotic ancestor of eukaryotes. For instance the common intestinal parasite Giardia intestinalis, a simple eukaryotic protozoan was, until recently, thought to be descended from an early diverging eukaryotic lineage that lacked sex. However, it has since been shown that G. intestinalis contains within its genome a core set of genes that function in meiosis, including five genes that function only in meiosis. In addition, G. intestinalis was recently found to undergo a specialized, sex-like process involving meiosis gene homologs. This evidence, and other similar examples, suggest that a primitive form of meiosis, was present in the common ancestor of all eukaryotes, an ancestor that arose from an antecedent prokaryote.
=== From mitosis ===
Mitosis is the normal process in eukaryotes for cell division; duplicating chromosomes and segregating one of the two copies into each of the two daughter cells, in contrast with meiosis. The mitosis theory states that meiosis evolved from mitosis. According to this theory, early eukaryotes evolved mitosis first, became established, and only then did meiosis and sexual reproduction arise.
Supporting this idea are observations of some features, such as the meiotic spindles that draw chromosome sets into separate daughter cells upon cell division, as well as processes regulating cell division that employ the same, or similar molecular machinery. Yet there is no compelling evidence for a period in the early evolution of eukaryotes, during which meiosis and accompanying sexual capability did not yet exist.
In addition, as noted by Wilkins and Holliday, there are four novel steps needed in meiosis that are not present in mitosis. These are: (1) pairing of homologous chromosomes, (2) extensive recombination between homologs; (3) suppression of sister chromatid separation in the first meiotic division; and (4) avoiding chromosome replication during the second meiotic division. Although the introduction of these steps seems to be complicated, Wilkins and Holliday argue that only one new step, homolog synapsis, was particularly initiated in the evolution of meiosis from mitosis. Meanwhile, two of the other novel features could have been simple modifications, and extensive recombination could have evolved later.
=== Coevolution with mitosis ===
If meiosis arose from prokaryotic transformation, during the early evolution of eukaryotes, mitosis and meiosis could have evolved in parallel. Both processes use shared molecular components, where mitosis evolved from the molecular machinery used by prokaryotes for DNA replication and segregation, and meiosis evolved from the prokaryotic sexual process of transformation. However, meiosis also made use of the evolving molecular machinery for DNA replication and segregation.
== Function ==
=== Stress-induced sex ===
Abundant evidence indicates that facultative sexual eukaryotes tend to undergo sexual reproduction under stressful conditions. For instance, the budding yeast Saccharomyces cerevisiae (a single-celled fungus) reproduces mitotically (asexually) as diploid cells when nutrients are abundant, but switches to meiosis (sexual reproduction) under starvation conditions. The unicellular green alga, Chlamydomonas reinhardtii grows as vegetative cells in nutrient rich growth medium, but depletion of a source of nitrogen in the medium leads to gamete fusion, zygote formation and meiosis. The fission yeast Schizosaccharomyces pombe, treated with H2O2 to cause oxidative stress, substantially increases the proportion of cells which undergo meiosis. The simple multicellular eukaryote Volvox carteri undergoes sex in response to oxidative stress or stress from heat shock. These examples, and others, suggest that, in simple single-celled and multicellular eukaryotes, meiosis is an adaptation to respond to stress.
Prokaryotic sex also appears to be an adaptation to stress. For instance, transformation occurs near the end of logarithmic growth, when amino acids become limiting in Bacillus subtilis, or in Haemophilus influenzae when cells are grown to the end of logarithmic phase. In Streptococcus mutans and other streptococci, transformation is associated with high cell density and biofilm formation. In Streptococcus pneumoniae, transformation is induced by the DNA damaging agent mitomycin C. These, and other, examples indicate that prokaryotic sex, like meiosis in simple eukaryotes, is an adaptation to stressful conditions. This observation suggests that the natural selection pressures maintaining meiosis in eukaryotes are similar to the selective pressures maintaining prokaryotic sex. This similarity suggests continuity, rather than a gap, in the evolution of sex from prokaryotes to eukaryotes.
Stress is, however, a general concept. What is it specifically about stress that needs to be overcome by meiosis? And what is the specific benefit provided by meiosis that enhances survival under stressful conditions?
=== DNA repair ===
In one theory, meiosis is primarily an adaptation for repairing DNA damage. Environmental stresses often lead to oxidative stress within the cell, which is well known to cause DNA damage through the production of reactive forms of oxygen, known as reactive oxygen species (ROS). DNA damages, if not repaired, can kill a cell by blocking DNA replication, or transcription of essential genes.
When only one strand of the DNA is damaged, the lost information (nucleotide sequence) can ordinarily be recovered by repair processes that remove the damaged sequence and fill the resulting gap by copying from the opposite intact strand of the double helix. However, ROS also cause a type of damage that is difficult to repair, referred to as double-strand damage. One common example of double-strand damage is the double-strand break. In this case, genetic information (nucleotide sequence) is lost from both strands in the damaged region, and proper information can only be obtained from another intact chromosome homologous to the damaged chromosome. The process that the cell uses to accurately accomplish this type of repair is called recombinational repair.
Meiosis is distinct from mitosis in that a central feature of meiosis is the alignment of homologous chromosomes followed by recombination between them. The two chromosomes which pair are referred to as non-sister chromosomes, since they did not arise simply from the replication of a parental chromosome. Recombination between non-sister chromosomes at meiosis is known to be a recombinational repair process that can repair double-strand breaks and other types of double-strand damage. In contrast, recombination between sister chromosomes cannot repair double-strand damages arising prior to the replication which produced them. Thus on this view, the adaptive advantage of meiosis is that it facilitates recombinational repair of DNA damage that is otherwise difficult to repair, and that occurs as a result of stress, particularly oxidative stress. If left unrepaired, this damage would likely be lethal to gametes and inhibit production of viable progeny.
Even in multicellular eukaryotes, such as humans, oxidative stress is a problem for cell survival. In this case, oxidative stress is a byproduct of oxidative cellular respiration occurring during metabolism in all cells. In humans, on average, about 50 DNA double-strand breaks occur per cell in each cell generation. Meiosis, which facilitates recombinational repair between non-sister chromosomes, can efficiently repair these prevalent damages in the DNA passed on to germ cells, and consequently prevent loss of fertility in humans. Thus with the theory that meiosis arose from prokaryotic sex, recombinational repair is the selective advantage of meiosis in both single celled eukaryotes and multicellular eukaryotes, such as humans.
An argument against this hypothesis is that adequate repair mechanisms including those involving recombination already exist in prokaryotes. Prokaryotes do have DNA repair mechanism enriched with recombinational repair, and the existence of prokaryotic life in severe environment indicates the extreme efficiency of this mechanism to help them survive many DNA damages related to the environment. This implies that an extra costly repair in the form of meiosis would be unnecessary. However, most of these mechanisms cannot be as accurate as meiosis and are possibly more mutagenic than the repair mechanism provided by meiosis. They primarily do not require a second homologous chromosome for the recombination that promotes a more extensive repair. Thus, despite the efficiency of recombinational repair involving sister chromatids, the repair still needs to be improved, and another type of repair is required. Moreover, due to the more extensive homologous recombinational repair in meiosis in comparison to the repair in mitosis, meiosis as a repair mechanism can accurately remove any damage that arises at any stage of the cell cycle more than mitotic repair mechanism can do and was, therefore, naturally selected. In contrast, the sister chromatid in mitotic recombination could have been exposed to similar amount of stress, and, thus, this type of recombination, instead of eliminating the damage, could actually spread the damage and decrease fitness.
=== Prophase I arrest ===
Female mammals and birds are born possessing all the oocytes needed for future ovulations, and these oocytes are arrested at the prophase I stage of meiosis. In humans, as an example, oocytes are formed between three and four months of gestation within the fetus and are therefore present at birth. During this prophase I arrested stage (dictyate), which may last for many years, four copies of the genome are present in the oocytes. The arrest of ooctyes at the four genome copy stage was proposed to provide the informational redundancy needed to repair damage in the DNA of the germline. The repair process used likely involves homologous recombinational repair. Prophase arrested oocytes have a high capability for efficient repair of DNA damages. The adaptive function of the DNA repair capability during meiosis appears to be a key quality control mechanism in the female germ line and a critical determinant of fertility.
=== Genetic diversity ===
Another hypothesis to explain the function of meiosis is that stress is a signal to the cell that the environment is becoming adverse. Under this new condition, it may be beneficial to produce progeny that differ from the parent in their genetic make up. Among these varied progeny, some may be more adapted to the changed condition than their parents. Meiosis generates genetic variation in the diploid cell, in part by the exchange of genetic information between the pairs of chromosomes after they align (recombination). Thus, on this view, an advantage of meiosis is that it facilitates the generation of genomic diversity among progeny, allowing adaptation to adverse changes in the environment.
However, in the presence of a fairly stable environment, individuals surviving to reproductive age have genomes that function well in their current environment. This raises the question of why such individuals should risk shuffling their genes with those of another individual, as occurs during meiotic recombination? Considerations such as this have led many investigators to question whether genetic diversity is a major adaptive advantage of sex.
== See also ==
DNA repair
Giardia
Oxidative stress
Asexual reproduction, ways to avoid the two-fold cost of sexual reproduction
Apomixis
Parthenogenesis
== References == | Wikipedia/Origin_and_function_of_meiosis |
Cell most often refers to:
Cell (biology), the functional basic unit of life
Cellphone, a phone connected to a cellular network
Clandestine cell, a penetration-resistant form of a secret or outlawed organization
Electrochemical cell, a device used to convert chemical energy to electrical energy
Prison cell, a room used to hold people in prisons
Cell may also refer to:
== Arts, entertainment, and media ==
=== Fictional entities ===
Cell (comics), a Marvel comic book character
Cell (Dragon Ball), a character in the manga series Dragon Ball
=== Literature ===
Cell (novel), a 2006 horror novel by Stephen King
"Cells", poem, about a hungover soldier in gaol, by Rudyard Kipling
The Cell (play), an Australian play by Robert Wales
=== Music ===
Cell (music), a small rhythmic and melodic design that can be isolated, or can make up one part of a thematic context
Cell (American band)
Cell (Japanese band)
Cell (album), a 2004 album by Plastic Tree
Cells, a 1998 album by Cex
Cells, a 2012 album by Fake Blood
"Cells", an art song composed by G. F. Cobb and named after the poem by Kipling
"Cells", a song by Bloem de Ligny
"Cells", a song by I Monster from the album Neveroddoreven
"Cells", a song by The Servant
The Cells, an American rock band
"The Cell" (song), a 2006 song by Jandek
=== Other arts, entertainment, and media ===
The Cell (film), a 2000 psychological thriller film starring Jennifer Lopez
Cell (film), a 2016 film based on the Stephen King novel
Animation cel, a transparent sheet on which objects are drawn or painted for traditional, hand-drawn animation
"The Cell" (The Vampire Diaries), an episode of the TV series The Vampire Diaries
"The Cell" (The Walking Dead), a 2016 television episode of The Walking Dead
The Cell (BBC Four), Adam Rutherford's 3-part documentary series that aired on BBC Four
The Cell, the original title of the TV series Sleeper Cell
== Groups of people ==
Cell, a group of people in a cell group, a form of Christian church organization
Cellular organizational structure, such as in business management
== Rooms ==
Monastic cell, a small room, hut, or cave in which a religious recluse lives, alternatively the small precursor of a monastery with only a few monks or nuns
== Science, mathematics, and technology ==
=== Computing and telecommunications ===
Cell (EDA), a term used in an electronic circuit design schematics
Cell (microprocessor), a microprocessor architecture developed by Sony, Toshiba, and IBM
Cell, a unit in a database table or spreadsheet, formed by the intersection of a row and a column
Cell, in wireless local area networking standards (including Wi-Fi), a wireless connection within a limited area, referred to as a cell or Basic Service Set
Cell, a fixed-length data frame used in the Asynchronous Transfer Mode protocol
Cell (network), area of radio coverage in a cellular network
Memory cell (computing), the basic unit of (volatile or non-volatile) computer memory
=== Mathematics ===
Cell (geometry), a three-dimensional element, part of a higher-dimensional object
Cell, an element of an abstract cell complex
Cell, a basic unit of a cellular automaton
Cell, an element of a CW complex
Cell, a k-face of a simplicial complex
=== Other uses in science and technology ===
Cell (journal), a scientific journal
Fuel cell, a device used to convert chemical energy from a fuel like hydrogen to electricity
Galvanic cell or voltaic cell, a particular kind of electrochemical cell
Photodetector, or photo cell, a sensor which detects light
Solar cell, a component of photovoltaic systems used to convert the energy of light into electricity
Storm cell, the smallest unit of a storm-producing system
== See also ==
All pages with titles beginning with Cell
All pages with titles containing Cell
CEL (disambiguation)
Cellular (disambiguation)
Macrocell | Wikipedia/cell |
A cellular network or mobile network is a telecommunications network where the link to and from end nodes is wireless and the network is distributed over land areas called cells, each served by at least one fixed-location transceiver (such as a base station). These base stations provide the cell with the network coverage which can be used for transmission of voice, data, and other types of content via radio waves. Each cell's coverage area is determined by factors such as the power of the transceiver, the terrain, and the frequency band being used. A cell typically uses a different set of frequencies from neighboring cells, to avoid interference and provide guaranteed service quality within each cell.
When joined together, these cells provide radio coverage over a wide geographic area. This enables numerous devices, including mobile phones, tablets, laptops equipped with mobile broadband modems, and wearable devices such as smartwatches, to communicate with each other and with fixed transceivers and telephones anywhere in the network, via base stations, even if some of the devices are moving through more than one cell during transmission. The design of cellular networks allows for seamless handover, enabling uninterrupted communication when a device moves from one cell to another.
Modern cellular networks utilize advanced technologies such as Multiple Input Multiple Output (MIMO), beamforming, and small cells to enhance network capacity and efficiency.
Cellular networks offer a number of desirable features:
More capacity than a single large transmitter, since the same frequency can be used for multiple links as long as they are in different cells
Mobile devices use less power than a single transmitter or satellite since the cell towers are closer
Larger coverage area than a single terrestrial transmitter, since additional cell towers can be added indefinitely and are not limited by the horizon
Capability of utilizing higher frequency signals (and thus more available bandwidth / faster data rates) that are not able to propagate at long distances
With data compression and multiplexing, several video (including digital video) and audio channels may travel through a higher frequency signal on a single wideband carrier
Major telecommunications providers have deployed voice and data cellular networks over most of the inhabited land area of Earth. This allows mobile phones and other devices to be connected to the public switched telephone network and public Internet access. In addition to traditional voice and data services, cellular networks now support Internet of Things (IoT) applications, connecting devices such as smart meters, vehicles, and industrial sensors.
The evolution of cellular networks from 1G to 5G has progressively introduced faster speeds, lower latency, and support for a larger number of devices, enabling advanced applications in fields such as healthcare, transportation, and smart cities.
Private cellular networks can be used for research or for large organizations and fleets, such as dispatch for local public safety agencies or a taxicab company, as well as for local wireless communications in enterprise and industrial settings such as factories, warehouses, mines, power plants, substations, oil and gas facilities and ports.
== Concept ==
In a cellular radio system, a land area to be supplied with radio service is divided into cells in a pattern dependent on terrain and reception characteristics. These cell patterns roughly take the form of regular shapes, such as hexagons, squares, or circles although hexagonal cells are conventional. Each of these cells is assigned with multiple frequencies (f1 – f6) which have corresponding radio base stations. The group of frequencies can be reused in other cells, provided that the same frequencies are not reused in adjacent cells, which would cause co-channel interference.
The increased capacity in a cellular network, compared with a network with a single transmitter, comes from the mobile communication switching system developed by Amos Joel of Bell Labs that permitted multiple callers in a given area to use the same frequency by switching calls to the nearest available cellular tower having that frequency available. This strategy is viable because a given radio frequency can be reused in a different area for an unrelated transmission. In contrast, a single transmitter can only handle one transmission for a given frequency. Inevitably, there is some level of interference from the signal from the other cells which use the same frequency. Consequently, there must be at least one cell gap between cells which reuse the same frequency in a standard frequency-division multiple access (FDMA) system.
Consider the case of a taxi company, where each radio has a manually operated channel selector knob to tune to different frequencies. As drivers move around, they change from channel to channel. The drivers are aware of which frequency approximately covers some area. When they do not receive a signal from the transmitter, they try other channels until finding one that works. The taxi drivers only speak one at a time when invited by the base station operator. This is a form of time-division multiple access (TDMA).
== History ==
The idea to establish a standard cellular phone network was first proposed on December 11, 1947. This proposal was put forward by Douglas H. Ring, a Bell Labs engineer, in an internal memo suggesting the development of a cellular telephone system by AT&T.
The first commercial cellular network, the 1G generation, was launched in Japan by Nippon Telegraph and Telephone (NTT) in 1979, initially in the metropolitan area of Tokyo. However, NTT did not initially commercialize the system; the early launch was motivated by an effort to understand a practical cellular system rather than by an interest to profit from it. In 1981, the Nordic Mobile Telephone system was created as the first network to cover an entire country. The network was released in 1981 in Sweden and Norway, then in early 1982 in Finland and Denmark. Televerket, a state-owned corporation responsible for telecommunications in Sweden, launched the system.
In September 1981, Jan Stenbeck, a financier and businessman, launched Comvik, a new Swedish telecommunications company. Comvik was the first European telecommunications firm to challenge the state's telephone monopoly on the industry. According to some sources, Comvik was the first to launch a commercial automatic cellular system before Televerket launched its own in October 1981. However, at the time of the new network’s release, the Swedish Post and Telecom Authority threatened to shut down the system after claiming that the company had used an unlicensed automatic gear that could interfere with its own networks. In December 1981, Sweden awarded Comvik with a license to operate its own automatic cellular network in the spirit of market competition.
The Bell System had developed cellular technology since 1947, and had cellular networks in operation in Chicago, Illinois, and Dallas, Texas, prior to 1979; however, regulatory battles delayed AT&T's deployment of cellular service to 1983, when its Regional Holding Company Illinois Bell first provided cellular service.
First-generation cellular network technology continued to expand its reach to the rest of the world. In 1990, Millicom Inc., a telecommunications service provider, strategically partnered with Comvik’s international cellular operations to become Millicom International Cellular SA. The company went on to establish a 1G systems foothold in Ghana, Africa under the brand name Mobitel. In 2006, the company’s Ghana operations were renamed to Tigo.
The wireless revolution began in the early 1990s, leading to the transition from analog to digital networks. The MOSFET invented at Bell Labs between 1955 and 1960, was adapted for cellular networks by the early 1990s, with the wide adoption of power MOSFET, LDMOS (RF amplifier), and RF CMOS (RF circuit) devices leading to the development and proliferation of digital wireless mobile networks.
The first commercial digital cellular network, the 2G generation, was launched in 1991. This sparked competition in the sector as the new operators challenged the incumbent 1G analog network operators.
== Cell signal encoding ==
To distinguish signals from several different transmitters, a number of channel access methods have been developed, including frequency-division multiple access (FDMA, used by analog and D-AMPS systems), time-division multiple access (TDMA, used by GSM) and code-division multiple access (CDMA, first used for PCS, and the basis of 3G).
With FDMA, the transmitting and receiving frequencies used by different users in each cell are different from each other. Each cellular call was assigned a pair of frequencies (one for base to mobile, the other for mobile to base) to provide full-duplex operation. The original AMPS systems had 666 channel pairs, 333 each for the CLEC "A" system and ILEC "B" system. The number of channels was expanded to 416 pairs per carrier, but ultimately the number of RF channels limits the number of calls that a cell site could handle. FDMA is a familiar technology to telephone companies, which used frequency-division multiplexing to add channels to their point-to-point wireline plants before time-division multiplexing rendered FDM obsolete.
With TDMA, the transmitting and receiving time slots used by different users in each cell are different from each other. TDMA typically uses digital signaling to store and forward bursts of voice data that are fit into time slices for transmission, and expanded at the receiving end to produce a somewhat normal-sounding voice at the receiver. TDMA must introduce latency (time delay) into the audio signal. As long as the latency time is short enough that the delayed audio is not heard as an echo, it is not problematic. TDMA is a familiar technology for telephone companies, which used time-division multiplexing to add channels to their point-to-point wireline plants before packet switching rendered FDM obsolete.
The principle of CDMA is based on spread spectrum technology developed for military use during World War II and improved during the Cold War into direct-sequence spread spectrum that was used for early CDMA cellular systems and Wi-Fi. DSSS allows multiple simultaneous phone conversations to take place on a single wideband RF channel, without needing to channelize them in time or frequency. Although more sophisticated than older multiple access schemes (and unfamiliar to legacy telephone companies because it was not developed by Bell Labs), CDMA has scaled well to become the basis for 3G cellular radio systems.
Other available methods of multiplexing such as MIMO, a more sophisticated version of antenna diversity, combined with active beamforming provides much greater spatial multiplexing ability compared to original AMPS cells, that typically only addressed one to three unique spaces. Massive MIMO deployment allows much greater channel reuse, thus increasing the number of subscribers per cell site, greater data throughput per user, or some combination thereof. Quadrature Amplitude Modulation (QAM) modems offer an increasing number of bits per symbol, allowing more users per megahertz of bandwidth (and decibels of SNR), greater data throughput per user, or some combination thereof.
== Frequency reuse ==
The key characteristic of a cellular network is the ability to reuse frequencies to increase both coverage and capacity. As described above, adjacent cells must use different frequencies, however, there is no problem with two cells sufficiently far apart operating on the same frequency, provided the masts and cellular network users' equipment do not transmit with too much power.
The elements that determine frequency reuse are the reuse distance and the reuse factor. The reuse distance, D is calculated as
D
=
R
3
N
{\displaystyle D=R{\sqrt {3N}}}
,
where R is the cell radius and N is the number of cells per cluster. Cells may vary in radius from 1 to 30 kilometres (0.62 to 18.64 mi). The boundaries of the cells can also overlap between adjacent cells and large cells can be divided into smaller cells.
The frequency reuse factor is the rate at which the same frequency can be used in the network. It is 1/K (or K according to some books) where K is the number of cells which cannot use the same frequencies for transmission. Common values for the frequency reuse factor are 1/3, 1/4, 1/7, 1/9 and 1/12 (or 3, 4, 7, 9 and 12, depending on notation).
In case of N sector antennas on the same base station site, each with different direction, the base station site can serve N different sectors. N is typically 3. A reuse pattern of N/K denotes a further division in frequency among N sector antennas per site. Some current and historical reuse patterns are 3/7 (North American AMPS), 6/4 (Motorola NAMPS), and 3/4 (GSM).
If the total available bandwidth is B, each cell can only use a number of frequency channels corresponding to a bandwidth of B/K, and each sector can use a bandwidth of B/NK.
Code-division multiple access-based systems use a wider frequency band to achieve the same rate of transmission as FDMA, but this is compensated for by the ability to use a frequency reuse factor of 1, for example using a reuse pattern of 1/1. In other words, adjacent base station sites use the same frequencies, and the different base stations and users are separated by codes rather than frequencies. While N is shown as 1 in this example, that does not mean the CDMA cell has only one sector, but rather that the entire cell bandwidth is also available to each sector individually.
Recently also orthogonal frequency-division multiple access based systems such as LTE are being deployed with a frequency reuse of 1. Since such systems do not spread the signal across the frequency band,
inter-cell radio resource management is important to coordinate resource allocation between different cell sites and to limit the inter-cell interference. There are various means of inter-cell interference coordination (ICIC) already defined in the standard. Coordinated scheduling, multi-site MIMO or multi-site beamforming are other examples for inter-cell radio resource management that might be standardized in the future.
== Directional antennas ==
Cell towers frequently use a directional signal to improve reception in higher-traffic areas. In the United States, the Federal Communications Commission (FCC) limits omnidirectional cell tower signals to 100 watts of power. If the tower has directional antennas, the FCC allows the cell operator to emit up to 500 watts of effective radiated power (ERP).
Although the original cell towers created an even, omnidirectional signal, were at the centers of the cells and were omnidirectional, a cellular map can be redrawn with the cellular telephone towers located at the corners of the hexagons where three cells converge. Each tower has three sets of directional antennas aimed in three different directions with 120 degrees for each cell (totaling 360 degrees) and receiving/transmitting into three different cells at different frequencies. This provides a minimum of three channels, and three towers for each cell and greatly increases the chances of receiving a usable signal from at least one direction.
The numbers in the illustration are channel numbers, which repeat every 3 cells. Large cells can be subdivided into smaller cells for high volume areas.
Cell phone companies also use this directional signal to improve reception along highways and inside buildings like stadiums and arenas.
== Broadcast messages and paging ==
Practically every cellular system has some kind of broadcast mechanism. This can be used directly for distributing information to multiple mobiles. Commonly, for example in mobile telephony systems, the most important use of broadcast information is to set up channels for one-to-one communication between the mobile transceiver and the base station. This is called paging. The three different paging procedures generally adopted are sequential, parallel and selective paging.
The details of the process of paging vary somewhat from network to network, but normally we know a limited number of cells where the phone is located (this group of cells is called a Location Area in the GSM or UMTS system, or Routing Area if a data packet session is involved; in LTE, cells are grouped into Tracking Areas). Paging takes place by sending the broadcast message to all of those cells. Paging messages can be used for information transfer. This happens in pagers, in CDMA systems for sending SMS messages, and in the UMTS system where it allows for low downlink latency in packet-based connections.
In LTE/4G, the Paging procedure is initiated by the MME when data packets need to be delivered to the UE.
Paging types supported by the MME are:
Basic.
SGs_CS and SGs_PS.
QCI_1 through QCI_9.
== Movement from cell to cell and handing over ==
In a primitive taxi system, when the taxi moved away from a first tower and closer to a second tower, the taxi driver manually switched from one frequency to another as needed. If communication was interrupted due to a loss of a signal, the taxi driver asked the base station operator to repeat the message on a different frequency.
In a cellular system, as the distributed mobile transceivers move from cell to cell during an ongoing continuous communication, switching from one cell frequency to a different cell frequency is done electronically without interruption and without a base station operator or manual switching. This is called the handover or handoff. Typically, a new channel is automatically selected for the mobile unit on the new base station which will serve it. The mobile unit then automatically switches from the current channel to the new channel and communication continues.
The exact details of the mobile system's move from one base station to the other vary considerably from system to system (see the example below for how a mobile phone network manages handover).
== Mobile phone network ==
The most common example of a cellular network is a mobile phone (cell phone) network. A mobile phone is a portable telephone which receives or makes calls through a cell site (base station) or transmitting tower. Radio waves are used to transfer signals to and from the cell phone.
Modern mobile phone networks use cells because radio frequencies are a limited, shared resource. Cell-sites and handsets change frequency under computer control and use low power transmitters so that the usually limited number of radio frequencies can be simultaneously used by many callers with less interference.
A cellular network is used by the mobile phone operator to achieve both coverage and capacity for their subscribers. Large geographic areas are split into smaller cells to avoid line-of-sight signal loss and to support a large number of active phones in that area. All of the cell sites are connected to telephone exchanges (or switches), which in turn connect to the public telephone network.
In cities, each cell site may have a range of up to approximately 1⁄2 mile (0.80 km), while in rural areas, the range could be as much as 5 miles (8.0 km). It is possible that in clear open areas, a user may receive signals from a cell site 25 miles (40 km) away. In rural areas with low-band coverage and tall towers, basic voice and messaging service may reach 50 miles (80 km), with limitations on bandwidth and number of simultaneous calls.
Since almost all mobile phones use cellular technology, including GSM, CDMA, and AMPS (analog), the term "cell phone" is in some regions, notably the US, used interchangeably with "mobile phone". However, satellite phones are mobile phones that do not communicate directly with a ground-based cellular tower but may do so indirectly by way of a satellite.
There are a number of different digital cellular technologies, including: Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), cdmaOne, CDMA2000, Evolution-Data Optimized (EV-DO), Enhanced Data Rates for GSM Evolution (EDGE), Universal Mobile Telecommunications System (UMTS), Digital Enhanced Cordless Telecommunications (DECT), Digital AMPS (IS-136/TDMA), and Integrated Digital Enhanced Network (iDEN). The transition from existing analog to the digital standard followed a very different path in Europe and the US. As a consequence, multiple digital standards surfaced in the US, while Europe and many countries converged towards the GSM standard.
=== Structure of the mobile phone cellular network ===
A simple view of the cellular mobile-radio network consists of the following:
A network of radio base stations forming the base station subsystem.
The core circuit switched network for handling voice calls and text
A packet switched network for handling mobile data
The public switched telephone network to connect subscribers to the wider telephony network
This network is the foundation of the GSM system network. There are many functions that are performed by this network in order to make sure customers get the desired service including mobility management, registration, call set-up, and handover.
Any phone connects to the network via an RBS (Radio Base Station) at a corner of the corresponding cell which in turn connects to the Mobile switching center (MSC). The MSC provides a connection to the public switched telephone network (PSTN). The link from a phone to the RBS is called an uplink while the other way is termed downlink.
Radio channels effectively use the transmission medium through the use of the following multiplexing and access schemes: frequency-division multiple access (FDMA), time-division multiple access (TDMA), code-division multiple access (CDMA), and space-division multiple access (SDMA).
=== Small cells ===
Small cells, which have a smaller coverage area than base stations, are categorised as follows:
Microcell -> less than 2 kilometres,
Picocell -> less than 200 metres,
Femtocell -> around 10 metres,
Attocell -> 1–4 metres
=== Cellular handover in mobile phone networks ===
As the phone user moves from one cell area to another cell while a call is in progress, the mobile station will search for a new channel to attach to in order not to drop the call. Once a new channel is found, the network will command the mobile unit to switch to the new channel and at the same time switch the call onto the new channel.
With CDMA, multiple CDMA handsets share a specific radio channel. The signals are separated by using a pseudonoise code (PN code) that is specific to each phone. As the user moves from one cell to another, the handset sets up radio links with multiple cell sites (or sectors of the same site) simultaneously. This is known as "soft handoff" because, unlike with traditional cellular technology, there is no one defined point where the phone switches to the new cell.
In IS-95 inter-frequency handovers and older analog systems such as NMT it will typically be impossible to test the target channel directly while communicating. In this case, other techniques have to be used such as pilot beacons in IS-95. This means that there is almost always a brief break in the communication while searching for the new channel followed by the risk of an unexpected return to the old channel.
If there is no ongoing communication or the communication can be interrupted, it is possible for the mobile unit to spontaneously move from one cell to another and then notify the base station with the strongest signal.
=== Cellular frequency choice in mobile phone networks ===
The effect of frequency on cell coverage means that different frequencies serve better for different uses. Low frequencies, such as 450 MHz NMT, serve very well for countryside coverage. GSM 900 (900 MHz) is suitable for light urban coverage. GSM 1800 (1.8 GHz) starts to be limited by structural walls. UMTS, at 2.1 GHz is quite similar in coverage to GSM 1800.
Higher frequencies are a disadvantage when it comes to coverage, but it is a decided advantage when it comes to capacity. Picocells, covering e.g. one floor of a building, become possible, and the same frequency can be used for cells which are practically neighbors.
Cell service area may also vary due to interference from transmitting systems, both within and around that cell. This is true especially in CDMA based systems. The receiver requires a certain signal-to-noise ratio, and the transmitter should not send with too high transmission power in view to not cause interference with other transmitters. As the receiver moves away from the transmitter, the power received decreases, so the power control algorithm of the transmitter increases the power it transmits to restore the level of received power. As the interference (noise) rises above the received power from the transmitter, and the power of the transmitter cannot be increased anymore, the signal becomes corrupted and eventually unusable. In CDMA-based systems, the effect of interference from other mobile transmitters in the same cell on coverage area is very marked and has a special name, cell breathing.
One can see examples of cell coverage by studying some of the coverage maps provided by real operators on their web sites or by looking at independently crowdsourced maps such as Opensignal or CellMapper. In certain cases they may mark the site of the transmitter; in others, it can be calculated by working out the point of strongest coverage.
A cellular repeater is used to extend cell coverage into larger areas. They range from wideband repeaters for consumer use in homes and offices to smart or digital repeaters for industrial needs.
=== Cell size ===
The following table shows the dependency of the coverage area of one cell on the frequency of a CDMA2000 network:
== See also ==
Lists and technical information:
Mobile technologies
2G networks (the first digital networks, 1G and 0G were analog):
GSM
Circuit Switched Data (CSD)
GPRS
EDGE(IMT-SC)
Evolved EDGE
Digital AMPS
Cellular Digital Packet Data (CDPD)
cdmaOne (IS-95)
Circuit Switched Data (CSD)
Personal Handy-phone System (PHS)
Personal Digital Cellular
3G networks:
UMTS
W-CDMA (air interface)
TD-CDMA (air interface)
TD-SCDMA (air interface)
HSPA
HSDPA
HSPA+
CDMA2000
OFDMA (air interface)
EVDO
SVDO
4G networks:
IMT Advanced
LTE (TD-LTE)
LTE Advanced
LTE Advanced Pro
WiMAX
WiMAX-Advanced (WirelessMAN-Advanced)
Ultra Mobile Broadband (never commercialized)
MBWA (IEEE 802.20, Mobile Broadband Wireless Access, HC-SDMA, iBurst, has been shut down)
5G networks:
5G NR
5G-Advanced
Starting with EVDO the following techniques can also be used to improve performance:
MIMO, SDMA and Beamforming
Cellular frequencies
CDMA frequency bands
GSM frequency bands
UMTS frequency bands
LTE frequency bands
5G NR frequency bands
Deployed networks by technology
List of UMTS networks
List of CDMA2000 networks
List of LTE networks
List of deployed WiMAX networks
List of 5G NR networks
Deployed networks by country (including technology and frequencies)
List of mobile network operators of Europe
List of mobile network operators of the Americas
List of mobile network operators of the Asia Pacific region
List of mobile network operators of the Middle East and Africa
List of mobile network operators (summary)
Mobile country code - code, frequency, and technology for each operator in each country
Comparison of mobile phone standards
List of mobile phone brands by country (manufacturers)
Equipment:
Cellular repeater
Cellular router
Professional mobile radio (PMR)
OpenBTS
Remote radio head
Baseband unit
Radio access network
Mobile cell sites
Other:
Antenna diversity
Cellular traffic
MIMO (multiple-input and multiple-output)
Mobile edge computing
Mobile phone radiation and health
Network simulation
Personal Communications Service
Radio resource management (RRM)
Routing in cellular networks
Signal strength
Title 47 of the Code of Federal Regulations
== References ==
== Further reading ==
P. Key, D. Smith. Teletraffic Engineering in a competitive world. Elsevier Science B.V., Amsterdam Netherlands, 1999. ISBN 978-0444502681. Chapter 1 (Plenary) and 3 (mobile).
William C. Y. Lee, Mobile Cellular Telecommunications Systems (1989), McGraw-Hill. ISBN 978-0-071-00790-0.
== External links ==
Raciti, Robert C. (July 1995). "CELLULAR TECHNOLOGY". Nova Southeastern University. Archived from the original on 15 July 2013. Retrieved 2 April 2012.
A History of Cellular Networks
What are cellular networks? 1G to 6G Features & Evolution
Technical Details with Call Flow about LTE Paging Procedure. | Wikipedia/Cell_(network) |
Genetics is the study of genes, genetic variation, and heredity in organisms. It is an important branch in biology because heredity is vital to organisms' evolution. Gregor Mendel, a Moravian Augustinian friar working in the 19th century in Brno, was the first to study genetics scientifically. Mendel studied "trait inheritance", patterns in the way traits are handed down from parents to offspring over time. He observed that organisms (pea plants) inherit traits by way of discrete "units of inheritance". This term, still used today, is a somewhat ambiguous definition of what is referred to as a gene.
Trait inheritance and molecular inheritance mechanisms of genes are still primary principles of genetics in the 21st century, but modern genetics has expanded to study the function and behavior of genes. Gene structure and function, variation, and distribution are studied within the context of the cell, the organism (e.g. dominance), and within the context of a population. Genetics has given rise to a number of subfields, including molecular genetics, epigenetics, and population genetics. Organisms studied within the broad field span the domains of life (archaea, bacteria, and eukarya).
Genetic processes work in combination with an organism's environment and experiences to influence development and behavior, often referred to as nature versus nurture. The intracellular or extracellular environment of a living cell or organism may increase or decrease gene transcription. A classic example is two seeds of genetically identical corn, one placed in a temperate climate and one in an arid climate (lacking sufficient waterfall or rain). While the average height the two corn stalks could grow to is genetically determined, the one in the arid climate only grows to half the height of the one in the temperate climate due to lack of water and nutrients in its environment.
== Etymology ==
The word genetics stems from the ancient Greek γενετικός genetikos meaning "genitive"/"generative", which in turn derives from γένεσις genesis meaning "origin".
== History ==
The observation that living things inherit traits from their parents has been used since prehistoric times to improve crop plants and animals through selective breeding. The modern science of genetics, seeking to understand this process, began with the work of the Augustinian friar Gregor Mendel in the mid-19th century.
Prior to Mendel, Imre Festetics, a Hungarian noble, who lived in Kőszeg before Mendel, was the first who used the word "genetic" in hereditarian context, and is considered the first geneticist. He described several rules of biological inheritance in his work The genetic laws of nature (Die genetischen Gesetze der Natur, 1819). His second law is the same as that which Mendel published. In his third law, he developed the basic principles of mutation (he can be considered a forerunner of Hugo de Vries). Festetics argued that changes observed in the generation of farm animals, plants, and humans are the result of scientific laws. Festetics empirically deduced that organisms inherit their characteristics, not acquire them. He recognized recessive traits and inherent variation by postulating that traits of past generations could reappear later, and organisms could produce progeny with different attributes. These observations represent an important prelude to Mendel's theory of particulate inheritance insofar as it features a transition of heredity from its status as myth to that of a scientific discipline, by providing a fundamental theoretical basis for genetics in the twentieth century.
Other theories of inheritance preceded Mendel's work. A popular theory during the 19th century, and implied by Charles Darwin's 1859 On the Origin of Species, was blending inheritance: the idea that individuals inherit a smooth blend of traits from their parents. Mendel's work provided examples where traits were definitely not blended after hybridization, showing that traits are produced by combinations of distinct genes rather than a continuous blend. Blending of traits in the progeny is now explained by the action of multiple genes with quantitative effects. Another theory that had some support at that time was the inheritance of acquired characteristics: the belief that individuals inherit traits strengthened by their parents. This theory (commonly associated with Jean-Baptiste Lamarck) is now known to be wrong—the experiences of individuals do not affect the genes they pass to their children. Other theories included Darwin's pangenesis (which had both acquired and inherited aspects) and Francis Galton's reformulation of pangenesis as both particulate and inherited.
=== Mendelian genetics ===
Modern genetics started with Mendel's studies of the nature of inheritance in plants. In his paper "Versuche über Pflanzenhybriden" ("Experiments on Plant Hybridization"), presented in 1865 to the Naturforschender Verein (Society for Research in Nature) in Brno, Mendel traced the inheritance patterns of certain traits in pea plants and described them mathematically. Although this pattern of inheritance could only be observed for a few traits, Mendel's work suggested that heredity was particulate, not acquired, and that the inheritance patterns of many traits could be explained through simple rules and ratios.
The importance of Mendel's work did not gain wide understanding until 1900, after his death, when Hugo de Vries and other scientists rediscovered his research. William Bateson, a proponent of Mendel's work, coined the word genetics in 1905. The adjective genetic, derived from the Greek word genesis—γένεσις, "origin", predates the noun and was first used in a biological sense in 1860. Bateson both acted as a mentor and was aided significantly by the work of other scientists from Newnham College at Cambridge, specifically the work of Becky Saunders, Nora Darwin Barlow, and Muriel Wheldale Onslow. Bateson popularized the usage of the word genetics to describe the study of inheritance in his inaugural address to the Third International Conference on Plant Hybridization in London in 1906.
After the rediscovery of Mendel's work, scientists tried to determine which molecules in the cell were responsible for inheritance. In 1900, Nettie Stevens began studying the mealworm. Over the next 11 years, she discovered that females only had the X chromosome and males had both X and Y chromosomes. She was able to conclude that sex is a chromosomal factor and is determined by the male. In 1911, Thomas Hunt Morgan argued that genes are on chromosomes, based on observations of a sex-linked white eye mutation in fruit flies. In 1913, his student Alfred Sturtevant used the phenomenon of genetic linkage to show that genes are arranged linearly on the chromosome.
=== Molecular genetics ===
Although genes were known to exist on chromosomes, chromosomes are composed of both protein and DNA, and scientists did not know which of the two is responsible for inheritance. In 1928, Frederick Griffith discovered the phenomenon of transformation: dead bacteria could transfer genetic material to "transform" other still-living bacteria. Sixteen years later, in 1944, the Avery–MacLeod–McCarty experiment identified DNA as the molecule responsible for transformation. The role of the nucleus as the repository of genetic information in eukaryotes had been established by Hämmerling in 1943 in his work on the single celled alga Acetabularia. The Hershey–Chase experiment in 1952 confirmed that DNA (rather than protein) is the genetic material of the viruses that infect bacteria, providing further evidence that DNA is the molecule responsible for inheritance.
James Watson and Francis Crick determined the structure of DNA in 1953, using the X-ray crystallography work of Rosalind Franklin and Maurice Wilkins that indicated DNA has a helical structure (i.e., shaped like a corkscrew). Their double-helix model had two strands of DNA with the nucleotides pointing inward, each matching a complementary nucleotide on the other strand to form what look like rungs on a twisted ladder. This structure showed that genetic information exists in the sequence of nucleotides on each strand of DNA. The structure also suggested a simple method for replication: if the strands are separated, new partner strands can be reconstructed for each based on the sequence of the old strand. This property is what gives DNA its semi-conservative nature where one strand of new DNA is from an original parent strand.
Although the structure of DNA showed how inheritance works, it was still not known how DNA influences the behavior of cells. In the following years, scientists tried to understand how DNA controls the process of protein production. It was discovered that the cell uses DNA as a template to create matching messenger RNA, molecules with nucleotides very similar to DNA. The nucleotide sequence of a messenger RNA is used to create an amino acid sequence in protein; this translation between nucleotide sequences and amino acid sequences is known as the genetic code.
With the newfound molecular understanding of inheritance came an explosion of research. A notable theory arose from Tomoko Ohta in 1973 with her amendment to the neutral theory of molecular evolution through publishing the nearly neutral theory of molecular evolution. In this theory, Ohta stressed the importance of natural selection and the environment to the rate at which genetic evolution occurs. One important development was chain-termination DNA sequencing in 1977 by Frederick Sanger. This technology allows scientists to read the nucleotide sequence of a DNA molecule. In 1983, Kary Banks Mullis developed the polymerase chain reaction, providing a quick way to isolate and amplify a specific section of DNA from a mixture. The efforts of the Human Genome Project, Department of Energy, NIH, and parallel private efforts by Celera Genomics led to the sequencing of the human genome in 2003.
== Features of inheritance ==
=== Discrete inheritance and Mendel's laws ===
At its most fundamental level, inheritance in organisms occurs by passing discrete heritable units, called genes, from parents to offspring. This property was first observed by Gregor Mendel, who studied the segregation of heritable traits in pea plants, showing for example that flowers on a single plant were either purple or white—but never an intermediate between the two colors. The discrete versions of the same gene controlling the inherited appearance (phenotypes) are called alleles.
In the case of the pea, which is a diploid species, each individual plant has two copies of each gene, one copy inherited from each parent. Many species, including humans, have this pattern of inheritance. Diploid organisms with two copies of the same allele of a given gene are called homozygous at that gene locus, while organisms with two different alleles of a given gene are called heterozygous. The set of alleles for a given organism is called its genotype, while the observable traits of the organism are called its phenotype. When organisms are heterozygous at a gene, often one allele is called dominant as its qualities dominate the phenotype of the organism, while the other allele is called recessive as its qualities recede and are not observed. Some alleles do not have complete dominance and instead have incomplete dominance by expressing an intermediate phenotype, or codominance by expressing both alleles at once.
When a pair of organisms reproduce sexually, their offspring randomly inherit one of the two alleles from each parent. These observations of discrete inheritance and the segregation of alleles are collectively known as Mendel's first law or the Law of Segregation. However, the probability of getting one gene over the other can change due to dominant, recessive, homozygous, or heterozygous genes. For example, Mendel found that if you cross heterozygous organisms your odds of getting the dominant trait is 3:1. Real geneticist study and calculate probabilities by using theoretical probabilities, empirical probabilities, the product rule, the sum rule, and more.
=== Notation and diagrams ===
Geneticists use diagrams and symbols to describe inheritance. A gene is represented by one or a few letters. Often a "+" symbol is used to mark the usual, non-mutant allele for a gene.
In fertilization and breeding experiments (and especially when discussing Mendel's laws) the parents are referred to as the "P" generation and the offspring as the "F1" (first filial) generation. When the F1 offspring mate with each other, the offspring are called the "F2" (second filial) generation. One of the common diagrams used to predict the result of cross-breeding is the Punnett square.
When studying human genetic diseases, geneticists often use pedigree charts to represent the inheritance of traits. These charts map the inheritance of a trait in a family tree.
=== Multiple gene interactions ===
Organisms have thousands of genes, and in sexually reproducing organisms these genes generally assort independently of each other. This means that the inheritance of an allele for yellow or green pea color is unrelated to the inheritance of alleles for white or purple flowers. This phenomenon, known as "Mendel's second law" or the "law of independent assortment," means that the alleles of different genes get shuffled between parents to form offspring with many different combinations. Different genes often interact to influence the same trait. In the Blue-eyed Mary (Omphalodes verna), for example, there exists a gene with alleles that determine the color of flowers: blue or magenta. Another gene, however, controls whether the flowers have color at all or are white. When a plant has two copies of this white allele, its flowers are white—regardless of whether the first gene has blue or magenta alleles. This interaction between genes is called epistasis, with the second gene epistatic to the first.
Many traits are not discrete features (e.g. purple or white flowers) but are instead continuous features (e.g. human height and skin color). These complex traits are products of many genes. The influence of these genes is mediated, to varying degrees, by the environment an organism has experienced. The degree to which an organism's genes contribute to a complex trait is called heritability. Measurement of the heritability of a trait is relative—in a more variable environment, the environment has a bigger influence on the total variation of the trait. For example, human height is a trait with complex causes. It has a heritability of 89% in the United States. In Nigeria, however, where people experience a more variable access to good nutrition and health care, height has a heritability of only 62%.
== Molecular basis for inheritance ==
=== DNA and chromosomes ===
The molecular basis for genes is deoxyribonucleic acid (DNA). DNA is composed of deoxyribose (sugar molecule), a phosphate group, and a base (amine group). There are four types of bases: adenine (A), cytosine (C), guanine (G), and thymine (T). The phosphates make phosphodiester bonds with the sugars to make long phosphate-sugar backbones. Bases specifically pair together (T&A, C&G) between two backbones and make like rungs on a ladder. The bases, phosphates, and sugars together make a nucleotide that connects to make long chains of DNA. Genetic information exists in the sequence of these nucleotides, and genes exist as stretches of sequence along the DNA chain. These chains coil into a double a-helix structure and wrap around proteins called Histones which provide the structural support. DNA wrapped around these histones are called chromosomes. Viruses sometimes use the similar molecule RNA instead of DNA as their genetic material.
DNA normally exists as a double-stranded molecule, coiled into the shape of a double helix. Each nucleotide in DNA preferentially pairs with its partner nucleotide on the opposite strand: A pairs with T, and C pairs with G. Thus, in its two-stranded form, each strand effectively contains all necessary information, redundant with its partner strand. This structure of DNA is the physical basis for inheritance: DNA replication duplicates the genetic information by splitting the strands and using each strand as a template for synthesis of a new partner strand.
Genes are arranged linearly along long chains of DNA base-pair sequences. In bacteria, each cell usually contains a single circular genophore, while eukaryotic organisms (such as plants and animals) have their DNA arranged in multiple linear chromosomes. These DNA strands are often extremely long; the largest human chromosome, for example, is about 247 million base pairs in length. The DNA of a chromosome is associated with structural proteins that organize, compact, and control access to the DNA, forming a material called chromatin; in eukaryotes, chromatin is usually composed of nucleosomes, segments of DNA wound around cores of histone proteins. The full set of hereditary material in an organism (usually the combined DNA sequences of all chromosomes) is called the genome.
DNA is most often found in the nucleus of cells, but Ruth Sager helped in the discovery of nonchromosomal genes found outside of the nucleus. In plants, these are often found in the chloroplasts and in other organisms, in the mitochondria. These nonchromosomal genes can still be passed on by either partner in sexual reproduction and they control a variety of hereditary characteristics that replicate and remain active throughout generations.
While haploid organisms have only one copy of each chromosome, most animals and many plants are diploid, containing two of each chromosome and thus two copies of every gene. The two alleles for a gene are located on identical loci of the two homologous chromosomes, each allele inherited from a different parent.
Many species have so-called sex chromosomes that determine the sex of each organism. In humans and many other animals, the Y chromosome contains the gene that triggers the development of the specifically male characteristics. In evolution, this chromosome has lost most of its content and also most of its genes, while the X chromosome is similar to the other chromosomes and contains many genes. This being said, Mary Frances Lyon discovered that there is X-chromosome inactivation during reproduction to avoid passing on twice as many genes to the offspring. Lyon's discovery led to the discovery of X-linked diseases.
=== Reproduction ===
When cells divide, their full genome is copied and each daughter cell inherits one copy. This process, called mitosis, is the simplest form of reproduction and is the basis for asexual reproduction. Asexual reproduction can also occur in multicellular organisms, producing offspring that inherit their genome from a single parent. Offspring that are genetically identical to their parents are called clones.
Eukaryotic organisms often use sexual reproduction to generate offspring that contain a mixture of genetic material inherited from two different parents. The process of sexual reproduction alternates between forms that contain single copies of the genome (haploid) and double copies (diploid). Haploid cells fuse and combine genetic material to create a diploid cell with paired chromosomes. Diploid organisms form haploids by dividing, without replicating their DNA, to create daughter cells that randomly inherit one of each pair of chromosomes. Most animals and many plants are diploid for most of their lifespan, with the haploid form reduced to single cell gametes such as sperm or eggs.
Although they do not use the haploid/diploid method of sexual reproduction, bacteria have many methods of acquiring new genetic information. Some bacteria can undergo conjugation, transferring a small circular piece of DNA to another bacterium. Bacteria can also take up raw DNA fragments found in the environment and integrate them into their genomes, a phenomenon known as transformation. These processes result in horizontal gene transfer, transmitting fragments of genetic information between organisms that would be otherwise unrelated. Natural bacterial transformation occurs in many bacterial species, and can be regarded as a sexual process for transferring DNA from one cell to another cell (usually of the same species). Transformation requires the action of numerous bacterial gene products, and its primary adaptive function appears to be repair of DNA damages in the recipient cell.
=== Recombination and genetic linkage ===
The diploid nature of chromosomes allows for genes on different chromosomes to assort independently or be separated from their homologous pair during sexual reproduction wherein haploid gametes are formed. In this way new combinations of genes can occur in the offspring of a mating pair. Genes on the same chromosome would theoretically never recombine. However, they do, via the cellular process of chromosomal crossover. During crossover, chromosomes exchange stretches of DNA, effectively shuffling the gene alleles between the chromosomes. This process of chromosomal crossover generally occurs during meiosis, a series of cell divisions that creates haploid cells. Meiotic recombination, particularly in microbial eukaryotes, appears to serve the adaptive function of repair of DNA damages.
The first cytological demonstration of crossing over was performed by Harriet Creighton and Barbara McClintock in 1931. Their research and experiments on corn provided cytological evidence for the genetic theory that linked genes on paired chromosomes do in fact exchange places from one homolog to the other.
The probability of chromosomal crossover occurring between two given points on the chromosome is related to the distance between the points. For an arbitrarily long distance, the probability of crossover is high enough that the inheritance of the genes is effectively uncorrelated. For genes that are closer together, however, the lower probability of crossover means that the genes demonstrate genetic linkage; alleles for the two genes tend to be inherited together. The amounts of linkage between a series of genes can be combined to form a linear linkage map that roughly describes the arrangement of the genes along the chromosome.
== Gene expression ==
=== Genetic code ===
Genes express their functional effect through the production of proteins, which are molecules responsible for most functions in the cell. Proteins are made up of one or more polypeptide chains, each composed of a sequence of amino acids. The DNA sequence of a gene is used to produce a specific amino acid sequence. This process begins with the production of an RNA molecule with a sequence matching the gene's DNA sequence, a process called transcription.
This messenger RNA molecule then serves to produce a corresponding amino acid sequence through a process called translation. Each group of three nucleotides in the sequence, called a codon, corresponds either to one of the twenty possible amino acids in a protein or an instruction to end the amino acid sequence; this correspondence is called the genetic code. The flow of information is unidirectional: information is transferred from nucleotide sequences into the amino acid sequence of proteins, but it never transfers from protein back into the sequence of DNA—a phenomenon Francis Crick called the central dogma of molecular biology.
The specific sequence of amino acids results in a unique three-dimensional structure for that protein, and the three-dimensional structures of proteins are related to their functions. Some are simple structural molecules, like the fibers formed by the protein collagen. Proteins can bind to other proteins and simple molecules, sometimes acting as enzymes by facilitating chemical reactions within the bound molecules (without changing the structure of the protein itself). Protein structure is dynamic; the protein hemoglobin bends into slightly different forms as it facilitates the capture, transport, and release of oxygen molecules within mammalian blood.
A single nucleotide difference within DNA can cause a change in the amino acid sequence of a protein. Because protein structures are the result of their amino acid sequences, some changes can dramatically change the properties of a protein by destabilizing the structure or changing the surface of the protein in a way that changes its interaction with other proteins and molecules. For example, sickle-cell anemia is a human genetic disease that results from a single base difference within the coding region for the β-globin section of hemoglobin, causing a single amino acid change that changes hemoglobin's physical properties.
Sickle-cell versions of hemoglobin stick to themselves, stacking to form fibers that distort the shape of red blood cells carrying the protein. These sickle-shaped cells no longer flow smoothly through blood vessels, having a tendency to clog or degrade, causing the medical problems associated with this disease.
Some DNA sequences are transcribed into RNA but are not translated into protein products—such RNA molecules are called non-coding RNA. In some cases, these products fold into structures which are involved in critical cell functions (e.g. ribosomal RNA and transfer RNA). RNA can also have regulatory effects through hybridization interactions with other RNA molecules (such as microRNA).
=== Nature and nurture ===
Although genes contain all the information an organism uses to function, the environment plays an important role in determining the ultimate phenotypes an organism displays. The phrase "nature and nurture" refers to this complementary relationship. The phenotype of an organism depends on the interaction of genes and the environment. An interesting example is the coat coloration of the Siamese cat. In this case, the body temperature of the cat plays the role of the environment. The cat's genes code for dark hair, thus the hair-producing cells in the cat make cellular proteins resulting in dark hair. But these dark hair-producing proteins are sensitive to temperature (i.e. have a mutation causing temperature-sensitivity) and denature in higher-temperature environments, failing to produce dark-hair pigment in areas where the cat has a higher body temperature. In a low-temperature environment, however, the protein's structure is stable and produces dark-hair pigment normally. The protein remains functional in areas of skin that are colder—such as its legs, ears, tail, and face—so the cat has dark hair at its extremities.
Environment plays a major role in effects of the human genetic disease phenylketonuria. The mutation that causes phenylketonuria disrupts the ability of the body to break down the amino acid phenylalanine, causing a toxic build-up of an intermediate molecule that, in turn, causes severe symptoms of progressive intellectual disability and seizures. However, if someone with the phenylketonuria mutation follows a strict diet that avoids this amino acid, they remain normal and healthy.
A common method for determining how genes and environment ("nature and nurture") contribute to a phenotype involves studying identical and fraternal twins, or other siblings of multiple births. Identical siblings are genetically the same since they come from the same zygote. Meanwhile, fraternal twins are as genetically different from one another as normal siblings. By comparing how often a certain disorder occurs in a pair of identical twins to how often it occurs in a pair of fraternal twins, scientists can determine whether that disorder is caused by genetic or postnatal environmental factors. One famous example involved the study of the Genain quadruplets, who were identical quadruplets all diagnosed with schizophrenia.
=== Gene regulation ===
The genome of a given organism contains thousands of genes, but not all these genes need to be active at any given moment. A gene is expressed when it is being transcribed into mRNA and there exist many cellular methods of controlling the expression of genes such that proteins are produced only when needed by the cell. Transcription factors are regulatory proteins that bind to DNA, either promoting or inhibiting the transcription of a gene. Within the genome of Escherichia coli bacteria, for example, there exists a series of genes necessary for the synthesis of the amino acid tryptophan. However, when tryptophan is already available to the cell, these genes for tryptophan synthesis are no longer needed. The presence of tryptophan directly affects the activity of the genes—tryptophan molecules bind to the tryptophan repressor (a transcription factor), changing the repressor's structure such that the repressor binds to the genes. The tryptophan repressor blocks the transcription and expression of the genes, thereby creating negative feedback regulation of the tryptophan synthesis process.
Differences in gene expression are especially clear within multicellular organisms, where cells all contain the same genome but have very different structures and behaviors due to the expression of different sets of genes. All the cells in a multicellular organism derive from a single cell, differentiating into variant cell types in response to external and intercellular signals and gradually establishing different patterns of gene expression to create different behaviors. As no single gene is responsible for the development of structures within multicellular organisms, these patterns arise from the complex interactions between many cells.
Within eukaryotes, there exist structural features of chromatin that influence the transcription of genes, often in the form of modifications to DNA and chromatin that are stably inherited by daughter cells. These features are called "epigenetic" because they exist "on top" of the DNA sequence and retain inheritance from one cell generation to the next. Because of epigenetic features, different cell types grown within the same medium can retain very different properties. Although epigenetic features are generally dynamic over the course of development, some, like the phenomenon of paramutation, have multigenerational inheritance and exist as rare exceptions to the general rule of DNA as the basis for inheritance.
== Genetic change ==
=== Mutations ===
During the process of DNA replication, errors occasionally occur in the polymerization of the second strand. These errors, called mutations, can affect the phenotype of an organism, especially if they occur within the protein coding sequence of a gene. Error rates are usually very low—1 error in every 10–100 million bases—due to the "proofreading" ability of DNA polymerases. Processes that increase the rate of changes in DNA are called mutagenic: mutagenic chemicals promote errors in DNA replication, often by interfering with the structure of base-pairing, while UV radiation induces mutations by causing damage to the DNA structure. Chemical damage to DNA occurs naturally as well and cells use DNA repair mechanisms to repair mismatches and breaks. The repair does not, however, always restore the original sequence. A particularly important source of DNA damages appears to be reactive oxygen species produced by cellular aerobic respiration, and these can lead to mutations.
In organisms that use chromosomal crossover to exchange DNA and recombine genes, errors in alignment during meiosis can also cause mutations. Errors in crossover are especially likely when similar sequences cause partner chromosomes to adopt a mistaken alignment; this makes some regions in genomes more prone to mutating in this way. These errors create large structural changes in DNA sequence—duplications, inversions, deletions of entire regions—or the accidental exchange of whole parts of sequences between different chromosomes, chromosomal translocation.
=== Natural selection and evolution ===
Mutations alter an organism's genotype and occasionally this causes different phenotypes to appear. Most mutations have little effect on an organism's phenotype, health, or reproductive fitness. Mutations that do have an effect are usually detrimental, but occasionally some can be beneficial. Studies in the fly Drosophila melanogaster suggest that if a mutation changes a protein produced by a gene, about 70 percent of these mutations are harmful with the remainder being either neutral or weakly beneficial.
Population genetics studies the distribution of genetic differences within populations and how these distributions change over time. Changes in the frequency of an allele in a population are mainly influenced by natural selection, where a given allele provides a selective or reproductive advantage to the organism, as well as other factors such as mutation, genetic drift, genetic hitchhiking, artificial selection and migration.
Over many generations, the genomes of organisms can change significantly, resulting in evolution. In the process called adaptation, selection for beneficial mutations can cause a species to evolve into forms better able to survive in their environment. New species are formed through the process of speciation, often caused by geographical separations that prevent populations from exchanging genes with each other.
By comparing the homology between different species' genomes, it is possible to calculate the evolutionary distance between them and when they may have diverged. Genetic comparisons are generally considered a more accurate method of characterizing the relatedness between species than the comparison of phenotypic characteristics. The evolutionary distances between species can be used to form evolutionary trees; these trees represent the common descent and divergence of species over time, although they do not show the transfer of genetic material between unrelated species (known as horizontal gene transfer and most common in bacteria).
== Research and technology ==
=== Model organisms ===
Although geneticists originally studied inheritance in a wide variety of organisms, the range of species studied has narrowed. One reason is that when significant research already exists for a given organism, new researchers are more likely to choose it for further study, and so eventually a few model organisms became the basis for most genetics research. Common research topics in model organism genetics include the study of gene regulation and the involvement of genes in development and cancer. Organisms were chosen, in part, for convenience—short generation times and easy genetic manipulation made some organisms popular genetics research tools. Widely used model organisms include the gut bacterium Escherichia coli, the plant Arabidopsis thaliana, baker's yeast (Saccharomyces cerevisiae), the nematode Caenorhabditis elegans, the common fruit fly (Drosophila melanogaster), the zebrafish (Danio rerio), and the common house mouse (Mus musculus).
=== Medicine ===
Medical genetics seeks to understand how genetic variation relates to human health and disease. When searching for an unknown gene that may be involved in a disease, researchers commonly use genetic linkage and genetic pedigree charts to find the location on the genome associated with the disease. At the population level, researchers take advantage of Mendelian randomization to look for locations in the genome that are associated with diseases, a method especially useful for multigenic traits not clearly defined by a single gene. Once a candidate gene is found, further research is often done on the corresponding (or homologous) genes of model organisms. In addition to studying genetic diseases, the increased availability of genotyping methods has led to the field of pharmacogenetics: the study of how genotype can affect drug responses.
Individuals differ in their inherited tendency to develop cancer, and cancer is a genetic disease. The process of cancer development in the body is a combination of events. Mutations occasionally occur within cells in the body as they divide. Although these mutations will not be inherited by any offspring, they can affect the behavior of cells, sometimes causing them to grow and divide more frequently. There are biological mechanisms that attempt to stop this process; signals are given to inappropriately dividing cells that should trigger cell death, but sometimes additional mutations occur that cause cells to ignore these messages. An internal process of natural selection occurs within the body and eventually mutations accumulate within cells to promote their own growth, creating a cancerous tumor that grows and invades various tissues of the body. Normally, a cell divides only in response to signals called growth factors and stops growing once in contact with surrounding cells and in response to growth-inhibitory signals. It usually then divides a limited number of times and dies, staying within the epithelium where it is unable to migrate to other organs. To become a cancer cell, a cell has to accumulate mutations in a number of genes (three to seven). A cancer cell can divide without growth factor and ignores inhibitory signals. Also, it is immortal and can grow indefinitely, even after it makes contact with neighboring cells. It may escape from the epithelium and ultimately from the primary tumor. Then, the escaped cell can cross the endothelium of a blood vessel and get transported by the bloodstream to colonize a new organ, forming deadly metastasis. Although there are some genetic predispositions in a small fraction of cancers, the major fraction is due to a set of new genetic mutations that originally appear and accumulate in one or a small number of cells that will divide to form the tumor and are not transmitted to the progeny (somatic mutations). The most frequent mutations are a loss of function of p53 protein, a tumor suppressor, or in the p53 pathway, and gain of function mutations in the Ras proteins, or in other oncogenes.
=== Research methods ===
DNA can be manipulated in the laboratory. Restriction enzymes are commonly used enzymes that cut DNA at specific sequences, producing predictable fragments of DNA. DNA fragments can be visualized through use of gel electrophoresis, which separates fragments according to their length.
The use of ligation enzymes allows DNA fragments to be connected. By binding ("ligating") fragments of DNA together from different sources, researchers can create recombinant DNA, the DNA often associated with genetically modified organisms. Recombinant DNA is commonly used in the context of plasmids: short circular DNA molecules with a few genes on them. In the process known as molecular cloning, researchers can amplify the DNA fragments by inserting plasmids into bacteria and then culturing them on plates of agar (to isolate clones of bacteria cells). "Cloning" can also refer to the various means of creating cloned ("clonal") organisms.
DNA can also be amplified using a procedure called the polymerase chain reaction (PCR). By using specific short sequences of DNA, PCR can isolate and exponentially amplify a targeted region of DNA. Because it can amplify from extremely small amounts of DNA, PCR is also often used to detect the presence of specific DNA sequences.
=== DNA sequencing and genomics ===
DNA sequencing, one of the most fundamental technologies developed to study genetics, allows researchers to determine the sequence of nucleotides in DNA fragments. The technique of chain-termination sequencing, developed in 1977 by a team led by Frederick Sanger, is still routinely used to sequence DNA fragments. Using this technology, researchers have been able to study the molecular sequences associated with many human diseases.
As sequencing has become less expensive, researchers have sequenced the genomes of many organisms using a process called genome assembly, which uses computational tools to stitch together sequences from many different fragments. These technologies were used to sequence the human genome in the Human Genome Project completed in 2003. New high-throughput sequencing technologies are dramatically lowering the cost of DNA sequencing, with many researchers hoping to bring the cost of resequencing a human genome down to a thousand dollars.
Next-generation sequencing (or high-throughput sequencing) came about due to the ever-increasing demand for low-cost sequencing. These sequencing technologies allow the production of potentially millions of sequences concurrently. The large amount of sequence data available has created the subfield of genomics, research that uses computational tools to search for and analyze patterns in the full genomes of organisms. Genomics can also be considered a subfield of bioinformatics, which uses computational approaches to analyze large sets of biological data. A common problem to these fields of research is how to manage and share data that deals with human subject and personally identifiable information.
== Society and culture ==
On 19 March 2015, a group of leading biologists urged a worldwide ban on clinical use of methods, particularly the use of CRISPR and zinc finger, to edit the human genome in a way that can be inherited. In April 2015, Chinese researchers reported results of basic research to edit the DNA of non-viable human embryos using CRISPR.
== See also ==
== References ==
== Further reading ==
== External links ==
Quotations related to Genetics at Wikiquote
Genetics at Wikibooks
Library resources in your library and in other libraries about Genetics
Genetics on In Our Time at the BBC | Wikipedia/genetics |
p53, also known as tumor protein p53, cellular tumor antigen p53 (UniProt name), or transformation-related protein 53 (TRP53) is a regulatory transcription factor protein that is often mutated in human cancers. The p53 proteins (originally thought to be, and often spoken of as, a single protein) are crucial in vertebrates, where they prevent cancer formation. As such, p53 has been described as "the guardian of the genome" because of its role in conserving stability by preventing genome mutation. Hence TP53 is classified as a tumor suppressor gene.
The TP53 gene is the most frequently mutated gene (>50%) in human cancer, indicating that the TP53 gene plays a crucial role in preventing cancer formation. TP53 gene encodes proteins that bind to DNA and regulate gene expression to prevent mutations of the genome. In addition to the full-length protein, the human TP53 gene encodes at least 12 protein isoforms.
== Gene ==
In humans, the TP53 gene is located on the short arm of chromosome 17 (17p13.1). The gene spans 20 kb, with a non-coding exon 1 and a very long first intron of 10 kb, overlapping the Hp53int1 gene. The coding sequence contains five regions showing a high degree of conservation in vertebrates, predominantly in exons 2, 5, 6, 7 and 8, but the sequences found in invertebrates show only distant resemblance to mammalian TP53. TP53 orthologs have been identified in most mammals for which complete genome data are available. Elephants, with 20 genes for TP53, rarely get cancer.
In humans, a common polymorphism involves the substitution of an arginine for a proline at codon position 72 of exon 4. Many studies have investigated a genetic link between this variation and cancer susceptibility; however, the results have been controversial. For instance, a meta-analysis from 2009 failed to show a link for cervical cancer. A 2011 study found that the TP53 proline mutation did have a profound effect on pancreatic cancer risk among males. A study of Arab women found that proline homozygosity at TP53 codon 72 is associated with a decreased risk for breast cancer. One study suggested that TP53 codon 72 polymorphisms, MDM2 SNP309, and A2164G may collectively be associated with non-oropharyngeal cancer susceptibility and that MDM2 SNP309 in combination with TP53 codon 72 may accelerate the development of non-oropharyngeal cancer in women. A 2011 study found that TP53 codon 72 polymorphism was associated with an increased risk of lung cancer.
Meta-analyses from 2011 found no significant associations between TP53 codon 72 polymorphisms and both colorectal cancer risk and endometrial cancer risk. A 2011 study of a Brazilian birth cohort found an association between the non-mutant arginine TP53 and individuals without a family history of cancer. Another 2011 study found that the p53 homozygous (Pro/Pro) genotype was associated with a significantly increased risk for renal cell carcinoma.
== Structure ==
p53 has seven domains:
an acidic N-terminus transcription-activation domain (TAD), also known as activation domain 1 (AD1), which activates transcription factors. The N-terminus contains two complementary transcriptional activation domains, with a major one at residues 1–42 and a minor one at residues 55–75, specifically involved in the regulation of several pro-apoptotic genes.
activation domain 2 (AD2) important for apoptotic activity: residues 43–63.
proline rich domain important for the apoptotic activity of p53 by nuclear exportation via MAPK: residues 64–92.
central DNA-binding core domain (DBD). Contains one zinc atom and several arginine amino acids: residues 102–292. This region is responsible for binding the p53 co-repressor LMO3.
Nuclear Localization Signaling (NLS) domain, residues 316–325.
homo-oligomerisation domain (OD): residues 307–355. Tetramerization is essential for the activity of p53 in vivo.
C-terminal involved in downregulation of DNA binding of the central domain: residues 356–393.
Mutations that deactivate p53 in cancer usually occur in the DBD. Most of these mutations destroy the ability of the protein to bind to its target DNA sequences, and thus prevents transcriptional activation of these genes. As such, mutations in the DBD are recessive loss-of-function mutations. Molecules of p53 with mutations in the OD dimerise with wild-type p53, and prevent them from activating transcription. Therefore, OD mutations have a dominant negative effect on the function of p53.
Wild-type p53 is a labile protein, comprising folded and unstructured regions that function in a synergistic manner.
SDS-PAGE analysis indicates that p53 is a 53-kilodalton (kDa) protein. However, the actual mass of the full-length p53 protein (p53α) based on the sum of masses of the amino acid residues is only 43.7 kDa. This difference is due to the high number of proline residues in the protein, which slow its migration on SDS-PAGE, thus making it appear heavier than it actually is.
== Oligomerization states ==
p53 initially forms dimers cotranslationally during protein synthesis on ribosomes. Each dimer comprises two p53 monomers linked via their oligomerization domains.
Dimers further associate posttranslationally into tetramers (a dimer of dimers). The tetramerization domain (residues 325–356) stabilizes this structure. Tetramers are the active form for DNA binding and transcriptional regulation.
== Function ==
=== DNA damage and repair ===
p53 plays a role in regulation or progression through the cell cycle, apoptosis, and genomic stability by means of several mechanisms:
It can activate DNA repair proteins when DNA has sustained damage Thus, it may be an important factor in aging.
It can arrest growth by holding the cell cycle at the G1/S regulation point on DNA damage recognition—if it holds the cell here for long enough, the DNA repair proteins will have time to fix the damage and the cell will be allowed to continue the cell cycle.
It can initiate apoptosis (a form of programmed cell death) if DNA damage proves to be irreparable.
It is essential for the senescence response to short telomeres.
WAF1/CIP1 encodes for p21 and hundreds of other down-stream genes. p21 (WAF1) binds to the G1-S/CDK (CDK4/CDK6, CDK2, and CDK1) complexes (molecules important for the G1/S transition in the cell cycle) inhibiting their activity.
When p21(WAF1) is complexed with CDK2, the cell cannot continue to the next stage of cell division. A mutant p53 will no longer bind DNA in an effective way, and, as a consequence, the p21 protein will not be available to act as the "stop signal" for cell division. Studies of human embryonic stem cells (hESCs) commonly describe the nonfunctional p53-p21 axis of the G1/S checkpoint pathway with subsequent relevance for cell cycle regulation and the DNA damage response (DDR). Importantly, p21 mRNA is clearly present and upregulated after the DDR in hESCs, but p21 protein is not detectable. In this cell type, p53 activates numerous microRNAs (like miR-302a, miR-302b, miR-302c, and miR-302d) that directly inhibit the p21 expression in hESCs.
The p21 protein binds directly to cyclin-CDK complexes that drive forward the cell cycle and inhibits their kinase activity, thereby causing cell cycle arrest to allow repair to take place. p21 can also mediate growth arrest associated with differentiation and a more permanent growth arrest associated with cellular senescence. The p21 gene contains several p53 response elements that mediate direct binding of the p53 protein, resulting in transcriptional activation of the gene encoding the p21 protein.
The p53 and RB1 pathways are linked via p14ARF, raising the possibility that the pathways may regulate each other.
p53 expression can be stimulated by UV light, which also causes DNA damage. In this case, p53 can initiate events leading to tanning.
=== Stem cells ===
Levels of p53 play an important role in the maintenance of stem cells throughout development and the rest of human life.
In human embryonic stem cells (hESCs)s, p53 is maintained at low inactive levels. This is because activation of p53 leads to rapid differentiation of hESCs. Studies have shown that knocking out p53 delays differentiation and that adding p53 causes spontaneous differentiation, showing how p53 promotes differentiation of hESCs and plays a key role in cell cycle as a differentiation regulator. When p53 becomes stabilized and activated in hESCs, it increases p21 to establish a longer G1. This typically leads to abolition of S-phase entry, which stops the cell cycle in G1, leading to differentiation. Work in mouse embryonic stem cells has recently shown however that the expression of P53 does not necessarily lead to differentiation. p53 also activates miR-34a and miR-145, which then repress the hESCs pluripotency factors, further instigating differentiation.
In adult stem cells, p53 regulation is important for maintenance of stemness in adult stem cell niches. Mechanical signals such as hypoxia affect levels of p53 in these niche cells through the hypoxia inducible factors, HIF-1α and HIF-2α. While HIF-1α stabilizes p53, HIF-2α suppresses it. Suppression of p53 plays important roles in cancer stem cell phenotype, induced pluripotent stem cells and other stem cell roles and behaviors, such as blastema formation. Cells with decreased levels of p53 have been shown to reprogram into stem cells with a much greater efficiency than normal cells. Papers suggest that the lack of cell cycle arrest and apoptosis gives more cells the chance to be reprogrammed. Decreased levels of p53 were also shown to be a crucial aspect of blastema formation in the legs of salamanders. p53 regulation is very important in acting as a barrier between stem cells and a differentiated stem cell state, as well as a barrier between stem cells being functional and being cancerous.
=== Other ===
Apart from the cellular and molecular effects above, p53 has a tissue-level anticancer effect that works by inhibiting angiogenesis. As tumors grow they need to recruit new blood vessels to supply them, and p53 inhibits that by (i) interfering with regulators of tumor hypoxia that also affect angiogenesis, such as HIF1 and HIF2, (ii) inhibiting the production of angiogenic promoting factors, and (iii) directly increasing the production of angiogenesis inhibitors, such as arresten.
p53 by regulating Leukemia Inhibitory Factor has been shown to facilitate implantation in the mouse and possibly human reproduction.
The immune response to infection also involves p53 and NF-κB. Checkpoint control of the cell cycle and of apoptosis by p53 is inhibited by some infections such as Mycoplasma bacteria, raising the specter of oncogenic infection.
== Regulation ==
p53 acts as a cellular stress sensor. It is normally kept at low levels by being constantly marked for degradation by the E3 ubiquitin ligase protein MDM2. p53 is activated in response to myriad stressors – including DNA damage (induced by either UV, IR, or chemical agents such as hydrogen peroxide), oxidative stress, osmotic shock, ribonucleotide depletion, viral lung infections and deregulated oncogene expression. This activation is marked by two major events. First, the half-life of the p53 protein is increased drastically, leading to a quick accumulation of p53 in stressed cells. Second, a conformational change forces p53 to be activated as a transcription regulator in these cells. The critical event leading to the activation of p53 is the phosphorylation of its N-terminal domain. The N-terminal transcriptional activation domain contains a large number of phosphorylation sites and can be considered as the primary target for protein kinases transducing stress signals.
The protein kinases that are known to target this transcriptional activation domain of p53 can be roughly divided into two groups. A first group of protein kinases belongs to the MAPK family (JNK1-3, ERK1-2, p38 MAPK), which is known to respond to several types of stress, such as membrane damage, oxidative stress, osmotic shock, heat shock, etc. A second group of protein kinases (ATR, ATM, CHK1 and CHK2, DNA-PK, CAK, TP53RK) is implicated in the genome integrity checkpoint, a molecular cascade that detects and responds to several forms of DNA damage caused by genotoxic stress. Oncogenes also stimulate p53 activation, mediated by the protein p14ARF.
In unstressed cells, p53 levels are kept low through a continuous degradation of p53. A protein called Mdm2 (also called HDM2 in humans), binds to p53, preventing its action and transports it from the nucleus to the cytosol. Mdm2 also acts as an ubiquitin ligase and covalently attaches ubiquitin to p53 and thus marks p53 for degradation by the proteasome. However, ubiquitylation of p53 is reversible. On activation of p53, Mdm2 is also activated, setting up a feedback loop. p53 levels can show oscillations (or repeated pulses) in response to certain stresses, and these pulses can be important in determining whether the cells survive the stress, or die.
MI-63 binds to MDM2, reactivating p53 in situations where p53's function has become inhibited.
A ubiquitin specific protease, USP7 (or HAUSP), can cleave ubiquitin off p53, thereby protecting it from proteasome-dependent degradation via the ubiquitin ligase pathway. This is one means by which p53 is stabilized in response to oncogenic insults. USP42 has also been shown to deubiquitinate p53 and may be required for the ability of p53 to respond to stress.
Recent research has shown that HAUSP is mainly localized in the nucleus, though a fraction of it can be found in the cytoplasm and mitochondria. Overexpression of HAUSP results in p53 stabilization. However, depletion of HAUSP does not result in a decrease in p53 levels but rather increases p53 levels due to the fact that HAUSP binds and deubiquitinates Mdm2. It has been shown that HAUSP is a better binding partner to Mdm2 than p53 in unstressed cells.
USP10, however, has been shown to be located in the cytoplasm in unstressed cells and deubiquitinates cytoplasmic p53, reversing Mdm2 ubiquitination. Following DNA damage, USP10 translocates to the nucleus and contributes to p53 stability. Also USP10 does not interact with Mdm2.
Phosphorylation of the N-terminal end of p53 by the above-mentioned protein kinases disrupts Mdm2-binding. Other proteins, such as Pin1, are then recruited to p53 and induce a conformational change in p53, which prevents Mdm2-binding even more. Phosphorylation also allows for binding of transcriptional coactivators, like p300 and PCAF, which then acetylate the C-terminal end of p53, exposing the DNA binding domain of p53, allowing it to activate or repress specific genes. Deacetylase enzymes, such as Sirt1 and Sirt7, can deacetylate p53, leading to an inhibition of apoptosis. Some oncogenes can also stimulate the transcription of proteins that bind to MDM2 and inhibit its activity.
Epigenetic marks like histone methylation can also regulate p53, for example, p53 interacts directly with a repressive Trim24 cofactor that binds histones in regions of the genome that are epigenetically repressed. Trim24 prevents p53 from activating its targets, but only in these regions, effectively giving p53 the ability to 'read out' the histone profile at key target genes and act in a gene-specific manner.
== Role in disease ==
If the TP53 gene is damaged, tumor suppression is severely compromised. People who inherit only one functional copy of the TP53 gene will most likely develop tumors in early adulthood, a disorder known as Li–Fraumeni syndrome.
The TP53 gene can also be modified by mutagens (chemicals, radiation, or viruses), increasing the likelihood for uncontrolled cell division. More than 50 percent of human tumors contain a mutation or deletion of the TP53 gene. Loss of p53 creates genomic instability that most often results in an aneuploidy phenotype.
Increasing the amount of p53 may seem a solution for treatment of tumors or prevention of their spreading. This, however, is not a usable method of treatment, since it can cause premature aging. Restoring endogenous normal p53 function holds some promise. Research has shown that this restoration can lead to regression of certain cancer cells without damaging other cells in the process. The ways by which tumor regression occurs depends mainly on the tumor type. For example, restoration of endogenous p53 function in lymphomas may induce apoptosis, while cell growth may be reduced to normal levels. Thus, pharmacological reactivation of p53 presents itself as a viable cancer treatment option. The first commercial gene therapy, Gendicine, was approved in China in 2003 for the treatment of head and neck squamous cell carcinoma. It delivers a functional copy of the p53 gene using an engineered adenovirus.
Certain pathogens can also affect the p53 protein that the TP53 gene expresses. One such example, human papillomavirus (HPV), encodes a protein, E6, which binds to the p53 protein and inactivates it. This mechanism, in synergy with the inactivation of the cell cycle regulator pRb by the HPV protein E7, allows for repeated cell division manifested clinically as warts. Certain HPV types, in particular types 16 and 18, can also lead to progression from a benign wart to low or high-grade cervical dysplasia, which are reversible forms of precancerous lesions. Persistent infection of the cervix over the years can cause irreversible changes leading to carcinoma in situ and eventually invasive cervical cancer. This results from the effects of HPV genes, particularly those encoding E6 and E7, which are the two viral oncoproteins that are preferentially retained and expressed in cervical cancers by integration of the viral DNA into the host genome.
The p53 protein is continually produced and degraded in cells of healthy people, resulting in damped oscillation (see a stochastic model of this process in ). The degradation of the p53 protein is associated with binding of MDM2. In a negative feedback loop, MDM2 itself is induced by the p53 protein. Mutant p53 proteins often fail to induce MDM2, causing p53 to accumulate at very high levels. Moreover, the mutant p53 protein itself can inhibit normal p53 protein levels. In some cases, single missense mutations in p53 have been shown to disrupt p53 stability and function.
Suppression of p53 in human breast cancer cells is shown to lead to increased CXCR5 chemokine receptor gene expression and activated cell migration in response to chemokine CXCL13.
One study found that p53 and Myc proteins were key to the survival of Chronic Myeloid Leukaemia (CML) cells. Targeting p53 and Myc proteins with drugs gave positive results on mice with CML.
== Mutations ==
Most p53 mutations are detected by DNA sequencing. However, it is known that single missense mutations can have a large spectrum from rather mild to very severe functional effects.
The large spectrum of cancer phenotypes due to mutations in the TP53 gene is also supported by the fact that different isoforms of p53 proteins have different cellular mechanisms for prevention against cancer. Mutations in TP53 can give rise to different isoforms, preventing their overall functionality in different cellular mechanisms and thereby extending the cancer phenotype from mild to severe. Recent studies show that p53 isoforms are differentially expressed in different human tissues, and the loss-of-function or gain-of-function mutations within the isoforms can cause tissue-specific cancer or provide cancer stem cell potential in different tissues. TP53 mutation also hits energy metabolism and increases glycolysis in breast cancer cells.
The dynamics of p53 proteins, along with its antagonist Mdm2, indicate that the levels of p53, in units of concentration, oscillate as a function of time. This "damped" oscillation is both clinically documented and mathematically modelled. Mathematical models also indicate that the p53 concentration oscillates much faster once teratogens, such as double-stranded breaks (DSB) or UV radiation, are introduced to the system. This supports and models the current understanding of p53 dynamics, where DNA damage induces p53 activation (see p53 regulation for more information). Current models can also be useful for modelling the mutations in p53 isoforms and their effects on p53 oscillation, thereby promoting de novo tissue-specific pharmacological drug discovery.
== Discovery ==
p53 was identified in 1979 by Lionel Crawford, David P. Lane, Arnold Levine, and Lloyd Old, working at Imperial Cancer Research Fund (UK) Princeton University/UMDNJ (Cancer Institute of New Jersey), and Memorial Sloan Kettering Cancer Center, respectively. It had been hypothesized to exist before as the target of the SV40 virus, a strain that induced development of tumors. The name p53 is in fact a misnomer, as it describes the apparent molecular mass measured when it was first discovered, though it was later realised this was an overestimate: the correct molecular mass is only 43.7 kDa.
The TP53 gene from the mouse was first cloned by Peter Chumakov of The Academy of Sciences of the USSR in 1982, and independently in 1983 by Moshe Oren in collaboration with David Givol (Weizmann Institute of Science). The human TP53 gene was cloned in 1984 and the full length clone in 1985.
It was initially presumed to be an oncogene due to the use of mutated cDNA following purification of tumor cell mRNA. Its role as a tumor suppressor gene was revealed in 1989 by Bert Vogelstein at the Johns Hopkins School of Medicine and Arnold Levine at Princeton University. p53 went on to be identified as a transcription factor by Guillermina Lozano working at MD Anderson Cancer Center.
Warren Maltzman, of the Waksman Institute of Rutgers University first demonstrated that TP53 was responsive to DNA damage in the form of ultraviolet radiation. In a series of publications in 1991–92, Michael Kastan of Johns Hopkins University, reported that TP53 was a critical part of a signal transduction pathway that helped cells respond to DNA damage.
In 1993, p53 was voted molecule of the year by Science magazine.
== Isoforms ==
As with 95% of human genes, TP53 encodes more than one protein. All these p53 proteins are called the p53 isoforms. These proteins range in size from 3.5 to 43.7 kDa. Several isoforms were discovered in 2005, and so far 12 human p53 isoforms have been identified (p53α, p53β, p53γ, ∆40p53α, ∆40p53β, ∆40p53γ, ∆133p53α, ∆133p53β, ∆133p53γ, ∆160p53α, ∆160p53β, ∆160p53γ). Furthermore, p53 isoforms are expressed in a tissue dependent manner and p53α is never expressed alone.
The full length p53 isoform proteins can be subdivided into different protein domains. Starting from the N-terminus, there are first the amino-terminal transcription-activation domains (TAD 1, TAD 2), which are needed to induce a subset of p53 target genes. This domain is followed by the proline rich domain (PXXP), whereby the motif PXXP is repeated (P is a proline and X can be any amino acid). It is required among others for p53 mediated apoptosis. Some isoforms lack the proline rich domain, such as Δ133p53β,γ and Δ160p53α,β,γ; hence some isoforms of p53 are not mediating apoptosis, emphasizing the diversifying roles of the TP53 gene. Afterwards there is the DNA binding domain (DBD), which enables the proteins to sequence specific binding. The C-terminus domain completes the protein. It includes the nuclear localization signal (NLS), the nuclear export signal (NES) and the oligomerisation domain (OD). The NLS and NES are responsible for the subcellular regulation of p53. Through the OD, p53 can form a tetramer and then bind to DNA. Among the isoforms, some domains can be missing, but all of them share most of the highly conserved DNA-binding domain.
The isoforms are formed by different mechanisms. The beta and the gamma isoforms are generated by multiple splicing of intron 9, which leads to a different C-terminus. Furthermore, the usage of an internal promoter in intron 4 causes the ∆133 and ∆160 isoforms, which lack the TAD domain and a part of the DBD. Moreover, alternative initiation of translation at codon 40 or 160 bear the ∆40p53 and ∆160p53 isoforms.
Due to the isoformic nature of p53 proteins, there have been several sources of evidence showing that mutations within the TP53 gene giving rise to mutated isoforms are causative agents of various cancer phenotypes, from mild to severe, due to single mutation in the TP53 gene (refer to section Experimental analysis of p53 mutations for more details).
== Interactions ==
p53 has been shown to interact with:
== See also ==
Eprenetapopt, a reactivator of some mutant forms of p53
Pifithrin, an inhibitor of p53
== Notes ==
== References ==
== External links ==
"p53 Knowledgebase". Lane Group at the Institute of Molecular and Cell Biology (IMCB), Singapore. Archived from the original on 2006-01-03. Retrieved 2008-04-06.
GeneReviews/NCBI/NIH/UW entry on Li-Fraumeni Syndrome
TUMOR PROTEIN p53 @ OMIM
p53 restoration of function
p53 @ The Atlas of Genetics and Cytogenetics in Oncology and Haematology
TP53 Gene @ GeneCards
p53 News provided by insciences organisation
Goodsel DS (2002-07-01). "p53 Tumor Suppressor". Molecule of the Month. RCSB Protein Data Bank. Retrieved 2008-04-06.
Soussi T. "p53 Web Site". Retrieved 2008-04-06.
Living LFS A non-profit Li-Fraumeni Syndrome patient support organization
The George Pantziarka TP53 Trust A support group from the UK for people with Li-Fraumeni Syndrome or other TP53-related disorders
IARC TP53 Somatic Mutations database maintained at IARC, Lyon, by Magali Olivier
PDBe-KB provides an overview of all the structure information available in the PDB for Human P53.
scientific animation conformational changes of p53 upon binding to DNA | Wikipedia/P53_protein |
Telomere-binding proteins (also known as TERF, TRBF, TRF) function to bind telomeric DNA in various species. In particular, telomere-binding protein refers to TTAGGG repeat binding factor-1 (TERF1) and TTAGGG repeat binding factor-2 (TERF2). Telomere sequences in humans are composed of TTAGGG sequences which provide protection and replication of chromosome ends to prevent degradation. Telomere-binding proteins can generate a T-loop to protect chromosome ends. TRFs are double-stranded proteins which are known to induce bending, looping, and pairing of DNA which aids in the formation of T-loops. They directly bind to TTAGGG repeat sequence in the DNA. There are also subtelomeric regions present for regulation. However, in humans, there are six subunits forming a complex known as shelterin.
== Structure ==
There are six subunits forming the telomere-binding protein complex known as shelterin: TERF1, TERF2, POT1, TIN2, RAP1 and TPP1. Both TERF1 and TERF2 bind the telomeric repeat sequences in the duplex region of the genome in vivo. The DNA-binding proteins include TERF1, TERF2, and POT1, which have specific sequences, altering binding affinity or regulatory mechanisms. TIN2, RAP1, TPP1 are adaptor proteins influencing signalling complexes.
Both TRFs are separate homodimer proteins, similar to the Myb helix-turn-helix motif with DNA binding folds at the C-terminus. There are highly conserved regions located in the centre with relation to the formation of homodimers. However, they differ in the N-terminus as TERF2 contains a basic motif while TERF1 is acidic so they do not dimerize. There is a 120˚ angular bend in TERF1 when binding to the telomeric site.
== Function ==
The complex recognizes the TTAGGG telomeric sequences, indicating the end of a chromosome. Telomere-binding proteins function to generate a T-loop, which is a specialized loop structure to cap the telomeric ends. Telomerase activity is regulated by protection of telomeres 1 (POT1). They serve as a protective safeguard against premature degradation as the telomere ends are no longer hidden from damage detection. Telomere-binding proteins not present may cause the exposed telomeres to undergo a DNA repair response, having mistakenly identified the ends as a double-stranded break. This is due to the 3’ overhang, which gradually shortens over time. A process known as uncapping occurs, in which the shelterin complex dissociates from the telomere when shrunk to a critical length.
=== TERF1 ===
TERF1 is present during all stages of the cell cycle, acting as a negative regulator in tandem with TERF2 while in contrast to telomerase. Its main function seems to be observed in controlling the telomere lengths via inhibition of telomerase. Removal of TERF1 will therefore lead to an increase in telomere length. TERF1 may reduce the accessibility of telomerase towards the end of the DNA length, which results in its inhibition. There may be potential post-translation modifications of TERF1 by adding ribose to induce regulation of telomerase. After the lengthening of the telomere, TERF1 reassembles to form an inaccessible T-loop structure.
It has homology to the Myb transcription factors as the protein-DNA complex requires both Myb repeats. TERF1 binds near the N-terminus on a highly conserved domain to form a homodimer interaction. Since TERF1 bends the telomeric site, it may be a critical step in properly functioning telomeres to maintain its length. TERF1 also serves to prevent problematic secondary structures from hindering progression by interacting with helicase for unobstructed unwinding.
=== TERF2 ===
TERF2 is a homolog to TERF1, exhibiting many functional and biochemical similarities. TERF2, like TERF1 has some relation to the Myb DNA binding motif. It serves as a secondary negative regulator, as overexpression of TERF2 produces a shortened telomere. TERF2 may also conceal the ends of the telomere in order to prevent detection from degradation. There is more conservation across species in TERF2 possibly due to higher risk of senescence when mutated.
TERF2 binds directly to the DNA sequence, forming a T-loop structure. Therefore, TERF2 plays a role in inducing loop formation by folding the 3’ TTAGGG sequence back into the duplex sequence. When removed, degradation of telomeric 3’ overhangs can be observed. However, this requires the work of excision repair exonuclease ERCC1/XPF so inhibition of TERF2 alone may not necessarily lead to immediate shortening. Upon deletion of TERF2, there is co-localization with TERF1 with the association of DNA damage response factors. Under regular cell conditions, TERF2 is known to suppress the ATM pathway, however, the mechanisms of which, are currently unclear.
== Interactions ==
=== Shelterin complex subunits ===
TERF1 and TERF2 have particular roles known to be associated with other subunits within the shelterin complex. They interact with TIN2 to recruit TPP1 binding by allowing TIN2 to form a bridge. As a result, a cascade of interactions follows by recruiting POT1 and RAP1 and the shelterin complex is complete to protect and regulate the telomeric ends.
TERF2 requires stabilization for proper functioning through the interaction of TERF1 and TIN2. This suggests that a deficiency in either of the three former proteins will lead to a dysfunctional cell. Despite being a negative regulator of telomerase, there are currently no known effects of TRFs on expression of telomerase.
=== Damage response factors ===
When TERF2 is absent or non-functioning, ATM kinase is activated at chromosome ends to trigger a DNA damage response, similar to a response to a double-stranded break. This will then recruit damage response factors such as H2AFX and 53BP1 when telomeres are shortened and deprotected. Upon activation of ATM kinase, p53 is triggered to induce cell cycle arrest and initiate apoptosis. As well, damage detection will mediate non-homologous end joining (NHEJ), producing an end-to-end fusion of double-stranded breaks. However, it is not yet known how telomeres can detect the presence of damage.
=== NER pathway ===
TERF2 also has implications in the nucleotide excision repair (NER) pathway based on experiments on K5-Terf2 mice. It is suggested that individuals with critically short telomeres are more prone to skin cancer via UV-exposure. As a result, TERF2, with roles in telomere-length controls, may affect UV-damage repair. For example, XPF nuclease, a component of NER, localizes to telomeres when the damage repair response is triggered. The presence of TERF2 then initiates XPF activity leading to the excision of telomeric ends causing a reduction in length.
== Clinical implications ==
=== Skin tumours ===
TERF2 may play a role in cancers as their expression has been shown to increase in human tumours. A study of tumours performed on mice induced overexpression of TERF2 in the skin. When exposed to light, notable observations showed hyperpigmentation and skin tumour similar to human syndrome xeroderma pigmentosum. They found significantly shortened telomeres with increased instability of the overall chromosome when analyzing cells. Telomere shortening was attributed to XPF, an excision repair nuclease, with link to TERF2 causing genomic instability.
=== Oral cancer ===
Oral cancer also has a link to telomere-binding proteins, with TERF2 in particular. The overexpression of TERF2 has been a notable similarity across patients with oral malignancies in humans. Similar to UV-damaged cells, there was an overall genomic instability leading to uncapping of the telomeric ends. The imbalance of TERF2 and telomerase have significant implications in cancer-inducing mechanisms. By targeting the telomere-binding proteins which serve to protect the ends, it may prove fruitful in future drug therapy.
== References == | Wikipedia/Telomere-binding_protein |
Centromere protein B also known as major centromere autoantigen B is an autoantigen protein of the cell nucleus. In humans, centromere protein B is encoded by the CENPB gene.
== Function ==
Centromere protein B is a highly conserved protein that facilitates centromere formation. It is a DNA-binding protein that is derived from transposases of the pogo DNA transposon family. It contains a helix-loop-helix DNA binding motif at the N-terminus and a dimerization domain at the C-terminus. The DNA binding domain recognizes and binds a 17-bp sequence (CENP-B box) in the centromeric alpha satellite DNA. This protein is proposed to play an important role in the assembly of specific centromere structures in interphase nuclei and on mitotic chromosomes. It is also considered a major centromere autoantigen recognized by sera from patients with anti-centromere antibodies.
== Clinical significance ==
Centromere protein B is a potential biomarker of small-cell lung cancer.
== See also ==
Centromere
== References ==
== Further reading ==
== External links ==
Centromere+protein+B at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
This article incorporates text from the United States National Library of Medicine, which is in the public domain. | Wikipedia/Centromere_protein_B |
Centromere-associated protein E is a protein that in humans is encoded by the CENPE gene.
Centromere-associated protein E is a kinesin-like motor protein that accumulates in the G2 phase of the cell cycle. Unlike other centromere-associated proteins, it is not present during interphase and first appears at the centromere region of chromosomes during prometaphase. CENPE is proposed to be one of the motors responsible for mammalian chromosome movement and/or spindle elongation.
CENPE is also called Kinesin-7.
== Clinical significance ==
Mutations in CENPE result in autosomal recessive primary microcephaly type 13, which includes skeletal abnormalities and immunodeficiency.
== See also ==
CENPF
CENPJ
CENPT
== References ==
== Further reading == | Wikipedia/Centromere_protein_E |
In geography, the temperate climates of Earth occur in the middle latitudes (approximately 23.5° to 66.5° N/S of the Equator), which span between the tropics and the polar regions of Earth. These zones generally have wider temperature ranges throughout the year and more distinct seasonal changes compared to tropical climates, where such variations are often small; they usually differ only in the amount of precipitation.
In temperate climates, not only do latitudinal positions influence temperature changes, but various sea currents, prevailing wind direction, continentality (how large a landmass is) and altitude also shape temperate climates.
The Köppen climate classification defines a climate as "temperate" C, when the mean temperature is above −3 °C (26.6 °F) but below 18 °C (64.4 °F) in the coldest month to account for the persistence of frost. However, some adaptations of Köppen set the minimum at 0 °C (32.0 °F). Continental climates are classified as D and considered to be varieties of temperate climates, having more extreme temperatures, with mean temperatures in the coldest month usually being below −3 °C (26.6 °F).
== Zones and climates ==
The north temperate zone extends from the Tropic of Cancer (approximately 23.5° north latitude) to the Arctic Circle (approximately 66.5° north latitude). The south temperate zone extends from the Tropic of Capricorn (approximately 23.5° south latitude) to the Antarctic Circle (at approximately 66.5° south latitude).
In some climate classifications, the temperate zone may be divided into several smaller climate zones, based on monthly temperatures, the coldest month, and rainfall. These can include the subtropical zone (humid subtropical and Mediterranean climate), and the cool temperate zone (oceanic and continental climates).
=== Subtropical zone ===
These climates are typically found in the more equatorial regions of the temperate zone, between 23.5° and 35° north or south. They are influenced more by the tropics than by other temperate climate types, usually experiencing warmer temperatures throughout the year, with longer, hotter summers and shorter, milder winters. Freezing precipitation is uncommon in this part of the temperate zone.
==== Humid subtropical (Cfa) and monsoon subtropical (Cwa) climates ====
Humid subtropical climates generally have long, hot and humid summers with frequent convective showers in summer, and a peak seasonal rainfall in the hottest months. Winters are normally mild and above freezing in the humid subtropics. Warm ocean currents are usually found in coastal areas with humid subtropical climates. This type of climate is normally located along leeward lower east coasts of continents such as in southeast and central Argentina, Uruguay and south of Brazil, Northern Vietnam, the southeast portions of East Asia, southern and portions of the northeast and midwestern United States and portions of, South Africa, Ethiopia, and eastern Australia. In some areas with a humid subtropical climate (most notably southeast China and North India), there is an even sharper wet-dry season, called a monsoon subtropical climate or subtropical monsoon (Cwa). In these regions, winters are quite chilly and dry and summers have very heavy rainfall. Some Cwa areas in southern China report more than 80% of annual precipitation in the five warmest months (southwest monsoon).
==== Mediterranean climates (Csa, Csb) ====
Mediterranean climates have the opposite rainfall pattern to dry-winter climates, with a dry summer and wet winter. This climate occurs mostly at the western edges and coasts of the continents and are bounded by arid deserts on their equatorward sides that brings dry winds causing the dry season of summer, and oceanic climates to the poleward sides that are influenced by cool ocean currents and air masses that bring the rainfall of winter. The five main Mediterranean regions of the world are the Mediterranean basin in North Africa, Southern Europe, and West Asia, coastal California in the United States, the South and West states of Australia, the Western Cape of South Africa and the south and southwestern coast of Chile.
==== Subtropical highland climates (Cwb, Cfb) ====
Subtropical highland climates are climate variants often grouped together with oceanic climates found in some mountainous areas of either the tropics or subtropics. They have characteristically mild temperatures year-round, featuring the four seasons in the subtropics and no marked seasons in the tropics, the latter usually remaining mild to cool through most of the year. Subtropical highland climates under the Cfb classification usually have rainfall spread relatively evenly in all months of the year similar to most oceanic climates while climates under the Cwb classification have significant monsoon influence, usually having dry winters and wet summers.
=== Middle latitude zone ===
These climates occur in the middle latitudes, between approximately 35° and 66.5° north and south of the equator. There is an equal climatic influence from both the polar and tropical zones in this climate region. Two types of climates are in this zone, a milder oceanic one and more severe seasonal continental one. Most prototypical temperate climates have a distinct four-season pattern, especially in the continental climate sector.
==== Oceanic climates (Cfb) ====
Oceanic climates are created by the on-shore flow from the cool high latitude oceans to their west. This causes the climate to have mild summers and cool (but not cold) winters, and relative humidity and precipitation evenly distributed throughout the year. These climates are frequently cloudy and cool, and winters are milder than those in the continental climate.
Regions with oceanic climates include northwestern Europe, northwestern North America, southeastern and southwestern South America, southeastern Australia and most of New Zealand.
==== Humid continental climates (Dfa, Dfb, Dwa, Dwb, Dsa, Dsb) ====
Humid continental climates are considered as a variety of temperate climates due to lying in the temperate zones, although they are classified separately from other temperate climates in the Köppen climate classification. In contrast to oceanic climates, they are created by large land masses and seasonal changes in wind direction. This causes humid continental climates to have severe temperatures for the season compared to other temperate climates, meaning a hot summer and cold winter. Precipitation may be evenly distributed throughout the year, while in some locations there is a summer accent on rainfall.
Regions with humid continental climates include southeastern Canada, the upper portions of the eastern United States, portions of eastern Europe, parts of China, Japan and the Korean Peninsula.
=== Subpolar zone ===
These are temperate climates that compared to the subtropics are on the poleward edge of the temperate zone. Therefore, they still have four marked seasons including a warmer one, but are far more influenced by the polar zones than any other but the very polar climates (tundra and ice cap climate).
==== Subpolar oceanic and cold subtropical highland climates (Cfc, Cwc) ====
Areas with subpolar oceanic climates feature an oceanic climate but are usually located closer to polar regions. As a result of their location, these regions tend to be on the cool end of oceanic climates. Snowfall tends to be more common here than in other oceanic climates. Subpolar oceanic climates are less prone to temperature extremes than subarctic climates or continental climates, featuring milder winters than these climates but still with similar summers. This variant of an oceanic climate is found in parts of coastal Iceland, the Faroe Islands, parts of Scotland, northwestern coastal areas of Norway such as Lofoten and reaching to 70° north on some islands, uplands near the coast of southwestern Norway, the Aleutian Islands of Alaska and northern parts of the Alaskan Panhandle, some parts of Southern Argentina and Chile (though most regions are still classified as continental subantarctic), and a few highland areas of Tasmania, the Australian Alps and Southern Alps of New Zealand. This type of climate is even found in tropical areas such as the Papuan Highlands in Indonesia. Cfc is the categorization for this regime. Even in the middle of summer, temperatures exceeding 20°C (68 °F) are exceptional weather events in the most maritime of those locations impacted by this regime. In some parts of this climate, temperatures as high as 30°C (86°F) have been recorded on rare occasions, while temperatures as low as −15 °C (5 °F) have still been recorded on rare occasions.
A cold variant of the monsoon-influenced subtropical highland climate similar to subpolar oceanic climates occurs in small areas in the Chinese provinces of Sichuan and Yunnan, and parts of the Altiplano between Bolivia, Peru and Chile, where summers are sufficiently short to be Cwc with fewer than four months over 10 °C (50 °F) due to the high altitudes at these locations. El Alto, Bolivia, is one of the few confirmed towns that features this variation of the subtropical highland climate.
==== Cold summer mediterranean climates (Csc) ====
Cold summer mediterranean climates (Csc) are present in high-elevation areas around coastal Csb climate areas, where the strong maritime influence prevents the average winter monthly temperature from dropping below 0 °C. Despite the maritime influence, they are classified alongside other mediterranean climates in the Köppen classification rather than oceanic climates like subtropical highland climates due to the opposite rainfall pattern. This climate is rare and is predominantly found in climate fringes and isolated areas of the Cascades and Andes Mountains, as the dry-summer climate extends further poleward in the Americas than elsewhere.
== Human aspects ==
=== Demography, fauna and flora ===
The vast majority of the world's human population resides in temperate zones, especially in the Northern Hemisphere, due to its greater mass of land and lack of extreme temperatures. The biggest described number of taxa in a temperate region is found in southern Africa, where some 24,000 taxa (species and infraspecific taxa) have been described.
=== Agriculture ===
Farming is a large-scale practice in the temperate regions (except for boreal/subarctic regions) due to the plentiful rainfall and warm summers, because most agricultural activity occurs in the spring and summer, cold winters have a small effect on agricultural production. Extreme winters or summers have a huge impact on the productivity of agriculture which is less common.
=== Urbanization ===
Temperate regions have the majority of the world's population, which leads to large cities. There are a couple of factors why the climate of large city landscapes differs from the climate of rural areas. One factor is the strength of the absorption rate of buildings and asphalt, which is higher than that of natural land. The other large factor is the burning of fossil fuels from buildings and vehicles. These factors have led to the average climate of cities to be warmer than surrounding areas.
== See also ==
Geographical zone
Habitat
Köppen climate classification
Middle latitudes
Polar circle
Subtropics
Tropics
Subarctic
Highland temperate climate
Humid temperate climate
Subhumid temperate climate
== References == | Wikipedia/Temperate_climate |
The neutral theory of molecular evolution holds that most evolutionary changes occur at the molecular level, and most of the variation within and between species are due to random genetic drift of mutant alleles that are selectively neutral. The theory applies only for evolution at the molecular level, and is compatible with phenotypic evolution being shaped by natural selection as postulated by Charles Darwin.
The neutral theory allows for the possibility that most mutations are deleterious, but holds that because these are rapidly removed by natural selection, they do not make significant contributions to variation within and between species at the molecular level. A neutral mutation is one that does not affect an organism's ability to survive and reproduce.
The neutral theory assumes that most mutations that are not deleterious are neutral rather than beneficial. Because only a fraction of gametes are sampled in each generation of a species, the neutral theory suggests that a mutant allele can arise within a population and reach fixation by chance, rather than by selective advantage.
The theory was introduced by the Japanese biologist Motoo Kimura in 1968, and independently by two American biologists Jack Lester King and Thomas Hughes Jukes in 1969, and described in detail by Kimura in his 1983 monograph The Neutral Theory of Molecular Evolution. The proposal of the neutral theory was followed by an extensive "neutralist–selectionist" controversy over the interpretation of patterns of molecular divergence and gene polymorphism, peaking in the 1970s and 1980s.
Neutral theory is frequently used as the null hypothesis, as opposed to adaptive explanations, for describing the emergence of morphological or genetic features in organisms and populations. This has been suggested in a number of areas, including in explaining genetic variation between populations of one nominal species, the emergence of complex subcellular machinery, and the convergent emergence of several typical microbial morphologies.
== Origins ==
While some scientists, such as Freese (1962) and Freese and Yoshida (1965), had suggested that neutral mutations were probably widespread, the original mathematical derivation of the theory had been published by R.A. Fisher in 1930. Fisher, however, gave a reasoned argument for believing that, in practice, neutral gene substitutions would be very rare. A coherent theory of neutral evolution was first proposed by Motoo Kimura in 1968 and by King and Jukes independently in 1969. Kimura initially focused on differences among species; King and Jukes focused on differences within species.
Many molecular biologists and population geneticists also contributed to the development of the neutral theory. The principles of population genetics, established by J.B.S. Haldane, R.A. Fisher, and Sewall Wright, created a mathematical approach to analyzing gene frequencies that contributed to the development of Kimura's theory.
Haldane's dilemma regarding the cost of selection was used as motivation by Kimura. Haldane estimated that it takes about 300 generations for a beneficial mutation to become fixed in a mammalian lineage, meaning that the number of substitutions (1.5 per year) in the evolution between humans and chimpanzees was too high to be explained by beneficial mutations.
== Functional constraint ==
The neutral theory holds that as functional constraint diminishes, the probability that a mutation is neutral rises, and so should the rate of sequence divergence.
When comparing various proteins, extremely high evolutionary rates were observed in proteins such as fibrinopeptides and the C chain of the proinsulin molecule, which both have little to no functionality compared to their active molecules. Kimura and Ohta also estimated that the alpha and beta chains on the surface of a hemoglobin protein evolve at a rate almost ten times faster than the inside pockets, which would imply that the overall molecular structure of hemoglobin is less significant than the inside where the iron-containing heme groups reside.
There is evidence that rates of nucleotide substitution are particularly high in the third position of a codon, where there is little functional constraint. This view is based in part on the degenerate genetic code, in which sequences of three nucleotides (codons) may differ and yet encode the same amino acid (GCC and GCA both encode alanine, for example). Consequently, many potential single-nucleotide changes are in effect "silent" or "unexpressed" (see synonymous or silent substitution). Such changes are presumed to have little or no biological effect.
== Quantitative theory ==
Kimura also developed the infinite sites model (ISM) to provide insight into evolutionary rates of mutant alleles. If
v
{\displaystyle v}
were to represent the rate of mutation of gametes per generation of
N
{\displaystyle N}
individuals, each with two sets of chromosomes, the total number of new mutants in each generation is
2
N
v
{\displaystyle 2Nv}
. Now let
k
{\displaystyle k}
represent the evolution rate in terms of a mutant allele
μ
{\displaystyle \mu }
becoming fixed in a population.
k
=
2
N
v
μ
{\displaystyle k=2Nv\mu }
According to ISM, selectively neutral mutations appear at rate
μ
{\displaystyle \mu }
in each of the
2
N
{\displaystyle 2N}
copies of a gene, and fix with probability
1
/
(
2
N
)
{\displaystyle 1/(2N)}
. Because any of the
2
N
{\displaystyle 2N}
genes have the ability to become fixed in a population,
1
/
2
N
{\displaystyle 1/2N}
is equal to
μ
{\displaystyle \mu }
, resulting in the rate of evolutionary rate equation:
k
=
v
{\displaystyle k=v}
This means that if all mutations were neutral, the rate at which fixed differences accumulate between divergent populations is predicted to be equal to the per-individual mutation rate, independent of population size. When the proportion of mutations that are neutral is constant, so is the divergence rate between populations. This provides a rationale for the molecular clock, which predated neutral theory. The ISM also demonstrates a constancy that is observed in molecular lineages.
This stochastic process is assumed to obey equations describing random genetic drift by means of accidents of sampling, rather than for example genetic hitchhiking of a neutral allele due to genetic linkage with non-neutral alleles. After appearing by mutation, a neutral allele may become more common within the population via genetic drift. Usually, it will be lost, or in rare cases it may become fixed, meaning that the new allele becomes standard in the population.
According to the neutral theory of molecular evolution, the amount of genetic variation within a species should be proportional to the effective population size.
== The "neutralist–selectionist" debate ==
A heated debate arose when Kimura's theory was published, largely revolving around the relative percentages of polymorphic and fixed alleles that are "neutral" versus "non-neutral".
A genetic polymorphism means that different forms of particular genes, and hence of the proteins that they produce, are co-existing within a species. Selectionists claimed that such polymorphisms are maintained by balancing selection, while neutralists view the variation of a protein as a transient phase of molecular evolution. Studies by Richard K. Koehn and W. F. Eanes demonstrated a correlation between polymorphism and molecular weight of their molecular subunits. This is consistent with the neutral theory assumption that larger subunits should have higher rates of neutral mutation. Selectionists, on the other hand, contribute environmental conditions to be the major determinants of polymorphisms rather than structural and functional factors.
According to the neutral theory of molecular evolution, the amount of genetic variation within a species should be proportional to the effective population size. Levels of genetic diversity vary much less than census population sizes, giving rise to the "paradox of variation" . While high levels of genetic diversity were one of the original arguments in favor of neutral theory, the paradox of variation has been one of the strongest arguments against neutral theory.
There are a large number of statistical methods for testing whether neutral theory is a good description of evolution (e.g., McDonald-Kreitman test), and many authors claimed detection of selection. Some researchers have nevertheless argued that the neutral theory still stands, while expanding the definition of neutral theory to include background selection at linked sites.
== Nearly neutral theory ==
Tomoko Ohta also emphasized the importance of nearly neutral mutations, in particularly slightly deleterious mutations. The Nearly neutral theory stems from the prediction of neutral theory that the balance between selection and genetic drift depends on effective population size. Nearly neutral mutations are those that carry selection coefficients less than the inverse of twice the effective population size. The population dynamics of nearly neutral mutations are only slightly different from those of neutral mutations unless the absolute magnitude of the selection coefficient is greater than 1/N, where N is the effective population size in respect of selection. The effective population size affects whether slightly deleterious mutations can be treated as neutral or as deleterious. In large populations, selection can decrease the frequency of slightly deleterious mutations, therefore acting as if they are deleterious. However, in small populations, genetic drift can more easily overcome selection, causing slightly deleterious mutations to act as if they are neutral and drift to fixation or loss.
== Constructive neutral evolution ==
The groundworks for the theory of constructive neutral evolution (CNE) was laid by two papers in the 1990s. Constructive neutral evolution is a theory which suggests that complex structures and processes can emerge through neutral transitions. Although a separate theory altogether, the emphasis on neutrality as a process whereby neutral alleles are randomly fixed by genetic drift finds some inspiration from the earlier attempt by the neutral theory to invoke its importance in evolution. Conceptually, there are two components A and B (which may represent two proteins) which interact with each other. A, which performs a function for the system, does not depend on its interaction with B for its functionality, and the interaction itself may have randomly arisen in an individual with the ability to disappear without an effect on the fitness of A. This present yet currently unnecessary interaction is therefore called an "excess capacity" of the system. However, a mutation may occur which compromises the ability of A to perform its function independently. However, the A:B interaction that has already emerged sustains the capacity of A to perform its initial function. Therefore, the emergence of the A:B interaction "presuppresses" the deleterious nature of the mutation, making it a neutral change in the genome that is capable of spreading through the population via random genetic drift. Hence, A has gained a dependency on its interaction with B. In this case, the loss of B or the A:B interaction would have a negative effect on fitness and so purifying selection would eliminate individuals where this occurs. While each of these steps are individually reversible (for example, A may regain the capacity to function independently or the A:B interaction may be lost), a random sequence of mutations tends to further reduce the capacity of A to function independently and a random walk through the dependency space may very well result in a configuration in which a return to functional independence of A is far too unlikely to occur, which makes CNE a one-directional or "ratchet-like" process. CNE, which does not invoke adaptationist mechanisms for the origins of more complex systems (which involve more parts and interactions contributing to the whole), has seen application in the understanding of the evolutionary origins of the spliceosomal eukaryotic complex, RNA editing, additional ribosomal proteins beyond the core, the emergence of long-noncoding RNA from junk DNA, and so forth. In some cases, ancestral sequence reconstruction techniques have afforded the ability for experimental demonstration of some proposed examples of CNE, as in heterooligomeric ring protein complexes in some fungal lineages.
CNE has also been put forwards as the null hypothesis for explaining complex structures, and thus adaptationist explanations for the emergence of complexity must be rigorously tested on a case-by-case basis against this null hypothesis prior to acceptance. Grounds for invoking CNE as a null include that it does not presume that changes offered an adaptive benefit to the host or that they were directionally selected for, while maintaining the importance of more rigorous demonstrations of adaptation when invoked so as to avoid the excessive flaws of adaptationism criticized by Gould and Lewontin.
== Empirical evidence for the neutral theory ==
Predictions derived from the neutral theory are generally supported in studies of molecular evolution. One of corollaries of the neutral theory is that the efficiency of positive selection is higher in populations or species with higher effective population sizes. This relationship between the effective population size and selection efficiency was evidenced by genomic studies of species including chimpanzee and human and domesticated species. In small populations (e.g., a population bottleneck during a speciation event), slightly deleterious mutations should accumulate. Data from various species supports this prediction in that the ratio of nonsynonymous to synonymous nucleotide substitutions between species generally exceeds that within species. In addition, nucleotide and amino acid substitutions generally accumulate over time in a linear fashion, which is consistent with neutral theory. Arguments against the neutral theory cite evidence of widespread positive selection and selective sweeps in genomic data. Empirical support for the neutral theory may vary depending on the type of genomic data studied and the statistical tools used to detect positive selection. For example, Bayesian methods for the detection of selected codon sites and McDonald-Kreitman tests have been criticized for their rate of erroneous identification of positive selection.
== See also ==
Adaptive evolution in the human genome
Coalescent theory
Evolution of biological complexity
Masatoshi Nei
Molecular evolution
Tomoko Ohta
Unified neutral theory of biodiversity
== References ==
== External links ==
Misconceptions about natural selection and adaptation: the neutral theory at http://evolution.berkeley.edu.
"Celebrating 50 years of the Neutral Theory". Molecular Biology and Evolution. July 2018. | Wikipedia/Neutral_theory_of_molecular_evolution |
The nearly neutral theory of molecular evolution is a modification of the neutral theory of molecular evolution that accounts for the fact that not all mutations are either so deleterious such that they can be ignored, or else neutral. Slightly deleterious mutations are reliably purged only when their selection coefficient are greater than one divided by the effective population size. In larger populations, a higher proportion of mutations exceed this threshold for which genetic drift cannot overpower selection, leading to fewer fixation events and so slower molecular evolution.
The nearly neutral theory was proposed by Tomoko Ohta in 1973. The population-size-dependent threshold for purging mutations has been called the "drift barrier" by Michael Lynch, and used to explain differences in genomic architecture among species.
== Origins ==
According to the neutral theory of molecular evolution, the rate at which molecular changes accumulate between species should be equal to the rate of neutral mutations and hence relatively constant across species. However, this is a per-generation rate. Since larger organisms have longer generation times, the neutral theory predicts that their rate of molecular evolution should be slower. However, molecular evolutionists found that rates of protein evolution were fairly independent of generation time.
Noting that population size is generally inversely proportional to generation time, Tomoko Ohta proposed that if most amino acid substitutions are slightly deleterious, this would increase the rate of effectively neutral mutation rate in small populations, which could offset the effect of long generation times. However, because noncoding DNA substitutions tend to be more neutral, independent of population size, their rate of evolution is correctly predicted to depend on population size / generation time, unlike the rate of non-synonymous changes.
In this case, the faster rate of neutral evolution in proteins expected in small populations (due to a more lenient threshold for purging deleterious mutations) is offset by longer generation times (and vice versa), but in large populations with short generation times, noncoding DNA evolves faster while protein evolution is retarded by selection (which is more significant than drift for large populations) In 1973, Ohta published a short letter in Nature suggesting that a wide variety of molecular evidence supported the theory that most mutation events at the molecular level are slightly deleterious rather than strictly neutral.
Between then and the early 1990s, many studies of molecular evolution used a "shift model" in which the negative effect on the fitness of a population due to deleterious mutations shifts back to an original value when a mutation reaches fixation. In the early 1990s, Ohta developed a "fixed model" that included both beneficial and deleterious mutations, so that no artificial "shift" of overall population fitness was necessary. According to Ohta, however, the nearly neutral theory largely fell out of favor in the late 1980s, because the mathematically simpler neutral theory for the widespread molecular systematics research that flourished after the advent of rapid DNA sequencing. As more detailed systematics studies started to compare the evolution of genome regions subject to strong selection versus weaker selection in the 1990s, the nearly neutral theory and the interaction between selection and drift have once again become an important focus of research.
== Theory ==
The rate of substitution,
ρ
{\displaystyle \rho }
is
ρ
=
u
g
N
e
P
¯
f
i
x
{\displaystyle \rho =ugN_{e}{\bar {P}}_{fix}}
,
where
u
{\displaystyle u}
is the mutation rate,
g
{\displaystyle g}
is the generation time, and
N
e
{\displaystyle N_{e}}
is the effective population size. The last term is the probability that a new mutation will become fixed. Early models assumed that
u
{\displaystyle u}
is constant between species, and that
g
{\displaystyle g}
increases with
N
e
{\displaystyle N_{e}}
. Kimura’s equation for the probability of fixation in a haploid population gives:
P
f
i
x
=
1
−
e
−
s
1
−
e
−
s
N
e
{\displaystyle P_{fix}={\frac {1-e^{-s}}{1-e^{-sN_{e}}}}}
,
where
s
{\displaystyle s}
is the selection coefficient of a mutation. When
|
s
|
≪
1
N
e
{\displaystyle |s|\ll {\frac {1}{N_{e}}}}
(completely neutral),
P
f
i
x
=
1
N
e
{\displaystyle P_{fix}={\frac {1}{N_{e}}}}
, and when
−
s
≫
1
N
e
{\displaystyle -s\gg {\frac {1}{N_{e}}}}
(extremely deleterious),
P
f
i
x
{\displaystyle P_{fix}}
decreases almost exponentially with
N
e
{\displaystyle N_{e}}
. Mutations with
−
s
≃
1
N
e
{\displaystyle -s\simeq {\frac {1}{N_{e}}}}
are called nearly neutral mutations. These mutations can fix in small-
N
e
{\displaystyle N_{e}}
populations through genetic drift. In large-
N
e
{\displaystyle N_{e}}
populations, these mutations are purged by selection. If nearly neutral mutations are common, then the proportion for which
P
f
i
x
≪
1
N
e
{\displaystyle P_{fix}\ll {\frac {1}{N_{e}}}}
is dependent on
N
e
{\displaystyle N_{e}}
The effect of nearly neutral mutations can depend on fluctuations in
s
{\displaystyle s}
. Early work used a “shift model” in which
s
{\displaystyle s}
can vary between generations but the mean fitness of the population is reset to zero after fixation. This basically assumes the distribution of
s
{\displaystyle s}
is constant (in this sense, the argument in the previous paragraphs can be regarded as based on the “shift model”). This assumption can lead to indefinite improvement or deterioration of protein function. Alternatively, the later “fixed model” fixes the distribution of mutations’ effect on protein function, but allows the mean fitness of population to evolve. This allows the distribution of
s
{\displaystyle s}
to change with the mean fitness of population.
The “fixed model” provides a slightly different explanation for the rate of protein evolution. In large
N
e
{\displaystyle N_{e}}
populations, advantageous mutations are quickly picked up by selection, increasing the mean fitness of the population. In response, the mutation rate of nearly neutral mutations is reduced because these mutations are restricted to the tail of the distribution of selection coefficients.
The “fixed model” expands the nearly neutral theory. Tachida classified evolution under the “fixed model” based on the product of
N
e
{\displaystyle N_{e}}
and the variance in the distribution of
s
{\displaystyle s}
: a large product corresponds to adaptive evolution, an intermediate product corresponds to nearly neutral evolution, and a small product corresponds to almost neutral evolution. According to this classification, slightly advantageous mutations can contribute to nearly neutral evolution.
== The "drift barrier" theory ==
Michael Lynch has proposed that variation in the ability to purge slightly deleterious mutations (i.e. variation in
N
e
{\displaystyle N_{e}}
) can explain variation in genomic architecture among species, e.g. the size of the genome, or the mutation rate. Specifically, larger populations will have lower mutation rates, more streamlined genomic architectures, and generally more finely tuned adaptations. However, if robustness to the consequences of each possible error in processes such as transcription and translation substantially reduces the cost of making such errors, larger populations might evolve lower rates of global proofreading, and hence have higher rates of error. This may explain why Escherichia coli has higher rates of transcription error than Saccharomyces cerevisiae. This is supported by the fact that transcriptional error rates in E. coli depend on protein abundance (which is responsible for modulating the locus-specific strength of selection), but do so only for high-error-rate C to U deamination errors in S. cerevisiae.
== See also ==
History of molecular evolution
== References ==
== External links ==
The Nearly Neutral Theory of Molecular Evolution - Perspectives on Molecular Evolution | Wikipedia/Nearly_neutral_theory_of_molecular_evolution |
Ras, from "Rat sarcoma virus", is a family of related proteins that are expressed in all animal cell lineages and organs. All Ras protein family members belong to a class of protein called small GTPase, and are involved in transmitting signals within cells (cellular signal transduction). Ras is the prototypical member of the Ras superfamily of proteins, which are all related in three-dimensional structure and regulate diverse cell behaviours.
When Ras is 'switched on' by incoming signals, it subsequently switches on other proteins, which ultimately turn on genes involved in cell growth, differentiation, and survival. Mutations in Ras genes can lead to the production of permanently activated Ras proteins, which can cause unintended and overactive signaling inside the cell, even in the absence of incoming signals.
Because these signals result in cell growth and division, overactive Ras signaling can ultimately lead to cancer. The three Ras genes in humans (HRAS, KRAS, and NRAS) are the most common oncogenes in human cancer; mutations that permanently activate Ras are found in 20 to 25% of all human tumors and up to 90% in certain types of cancer (e.g., pancreatic cancer). For this reason, Ras inhibitors are being studied as a treatment for cancer and other diseases with Ras overexpression.
== History ==
The first two Ras genes, HRAS and KRAS, were identified from studies of two cancer-causing viruses, the Harvey sarcoma virus and Kirsten sarcoma virus, by Edward M. Scolnick and colleagues at the National Institutes of Health (NIH). These viruses were discovered originally in rats during the 1960s by Jennifer Harvey and Werner H. Kirsten, respectively, hence the name Rat sarcoma. In 1982, activated and transforming human ras genes were discovered in human cancer cells by Geoffrey M. Cooper at Harvard, Mariano Barbacid and Stuart A. Aaronson at the NIH, Robert Weinberg at MIT, and Michael Wigler at Cold Spring Harbor Laboratory. A third ras gene was subsequently discovered by researchers in the group of Robin Weiss at the Institute of Cancer Research, and Michael Wigler at Cold Spring Harbor Laboratory, named NRAS, for its initial identification in human neuroblastoma cells.
The three human ras genes encode extremely similar proteins made up of chains of 188 to 189 amino acids. Their gene symbols are HRAS, NRAS and KRAS, the latter of which produces the K-Ras4A and K-Ras4B isoforms from alternative splicing.
== Structure ==
Ras contains six beta strands and five alpha helices.
It consists of two domains: a G domain of 166 amino acids (about 20 kDa) that binds guanosine nucleotides, and a C-terminal membrane targeting region (CAAX-COOH, also known as CAAX box), which is lipid-modified by farnesyl transferase, RCE1, and ICMT.
The G domain contains five G motifs that bind GDP/GTP directly.
The G1 motif, or the P-loop, binds the beta phosphate of GDP and GTP.
The G2 motif, also called Switch I or SW1, contains threonine35, which binds the terminal phosphate (γ-phosphate) of GTP and the divalent magnesium ion bound in the active site.
The G3 motif, also called Switch II or SW2, has a DXXGQ motif. The D is aspartate57, which is specific for guanine versus adenine binding, and Q is glutamine61, the crucial residue that activates a catalytic water molecule for hydrolysis of GTP to GDP.
The G4 motif contains a LVGNKxDL motif, and provides specific interaction to guanine.
The G5 motif contains a SAK consensus sequence. The A is alanine146, which provides specificity for guanine rather than adenine.
The two switch motifs, G2 (SW1) and G3 (SW2), are the main parts of the protein that move when GTP is hydrolyzed into GDP. This conformational change by the two switch motifs is what mediates the basic functionality as a molecular switch protein. This GTP-bound state of Ras is the "on" state, and the GDP-bound state is the "off" state. The two switch motifs have a number of conformations when binding GTP or GDP or no nucleotide (when bound to SOS1, which releases the nucleotide).
Ras also binds a magnesium ion which helps to coordinate nucleotide binding.
== Function ==
Ras proteins function as binary molecular switches that control intracellular signaling networks. Ras-regulated signal pathways control such processes as actin cytoskeletal integrity, cell proliferation, cell differentiation, cell adhesion, apoptosis, and cell migration. Ras and Ras-related proteins are often deregulated in cancers, leading to increased invasion and metastasis, and decreased apoptosis.
Ras activates several pathways, of which the mitogen-activated protein (MAP) kinase cascade has been well-studied. This cascade transmits signals downstream and results in the transcription of genes involved in cell growth and division. Another Ras-activated signaling pathway is the PI3K/AKT/mTOR pathway, which stimulates protein synthesis, cellular migration and growth, and inhibits apoptosis.
=== Activation and deactivation ===
Ras is a guanosine-nucleotide-binding protein. Specifically, it is a single-subunit small GTPase, which is related in structure to the Gα subunit of heterotrimeric G proteins (large GTPases). G proteins function as binary signaling switches with "on" and "off" states. In the "off" state it is bound to the nucleotide guanosine diphosphate (GDP), while in the "on" state, Ras is bound to guanosine triphosphate (GTP), which has an extra phosphate group as compared to GDP. This extra phosphate holds the two switch regions in a "loaded-spring" configuration (specifically the Thr-35 and Gly-60). When released, the switch regions relax which causes a conformational change into the inactive state. Hence, activation and deactivation of Ras and other small G proteins are controlled by cycling between the active GTP-bound and inactive GDP-bound forms.
The process of exchanging the bound nucleotide is facilitated by guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs). As per its classification, Ras has an intrinsic GTPase activity, which means that the protein on its own will hydrolyze a bound GTP molecule into GDP. However this process is too slow for efficient function, and hence the GAP for Ras, RasGAP, may bind to and stabilize the catalytic machinery of Ras, supplying additional catalytic residues ("arginine finger") such that a water molecule is optimally positioned for nucleophilic attack on the gamma-phosphate of GTP. An inorganic phosphate is released and the Ras molecule is now bound to a GDP. Since the GDP-bound form is "off" or "inactive" for signaling, GTPase Activating Protein inactivates Ras by activating its GTPase activity. Thus, GAPs accelerate Ras inactivation.
GEFs catalyze a "push and pull" reaction which releases GDP from Ras. They insert close to the P-loop and magnesium cation binding site and inhibit the interaction of these with the gamma phosphate anion. Acidic (negative) residues in switch II "pull" a lysine in the P-loop away from the GDP which "pushes" switch I away from the guanine. The contacts holding GDP in place are broken and it is released into the cytoplasm. Because intracellular GTP is abundant relative to GDP (approximately 10 fold more) GTP predominantly re-enters the nucleotide binding pocket of Ras and reloads the spring. Thus GEFs facilitate Ras activation. Well known GEFs include Son of Sevenless (Sos) and cdc25 which include the RasGEF domain.
The balance between GEF and GAP activity determines the guanine nucleotide status of Ras, thereby regulating Ras activity.
In the GTP-bound conformation, Ras has a high affinity for numerous effectors which allow it to carry out its functions. These include PI3K. Other small GTPases may bind adaptors such as arfaptin or second messenger systems such as adenylyl cyclase. The Ras binding domain is found in many effectors and invariably binds to one of the switch regions, because these change conformation between the active and inactive forms. However, they may also bind to the rest of the protein surface.
Other proteins exist that may change the activity of Ras family proteins. One example is GDI (GDP Disassociation Inhibitor). These function by slowing the exchange of GDP for GTP, thus prolonging the inactive state of Ras family members. Other proteins that augment this cycle may exist.
=== Membrane attachment ===
Ras is attached to the cell membrane owing to its prenylation and palmitoylation (HRAS and NRAS) or the combination of prenylation and a polybasic sequence adjacent to the prenylation site (KRAS). The C-terminal CaaX box of Ras first gets farnesylated at its Cys residue in the cytosol, allowing Ras to loosely insert into the membrane of the endoplasmatic reticulum and other cellular membranes. The Tripeptide (aaX) is then cleaved from the C-terminus by a specific prenyl-protein specific endoprotease and the new C-terminus is methylated by a methyltransferase. KRas processing is completed at this stage. Dynamic electrostatic interactions between its positively charged basic sequence with negative charges at the inner leaflet of the plasma membrane account for its predominant localization at the cell surface at steady-state. NRAS and HRAS are further processed on the surface of the Golgi apparatus by palmitoylation of one or two Cys residues, respectively, adjacent to the CaaX box. The proteins thereby become stably membrane anchored (lipid-rafts) and are transported to the plasma membrane on vesicles of the secretory pathway. Depalmitoylation by acyl-protein thioesterases eventually releases the proteins from the membrane, allowing them to enter another cycle of palmitoylation and depalmitoylation. This cycle is believed to prevent the leakage of NRAS and HRAS to other membranes over time and to maintain their steady-state localization along the Golgi apparatus, secretory pathway, plasma membrane and inter-linked endocytosis pathway.
== Members ==
The clinically most notable members of the Ras subfamily are HRAS, KRAS and NRAS, mainly for being implicated in many types of cancer.
However, there are many other members of this subfamily as well:
DIRAS1; DIRAS2; DIRAS3; ERAS; GEM; MRAS; NKIRAS1; NKIRAS2; RALA; RALB; RAP1A; RAP1B; RAP2A; RAP2B; RAP2C; RASD1; RASD2; RASL10A; RASL10B; RASL11A; RASL11B; RASL12; REM1; REM2; RERG; RERGL; RRAD; RRAS; RRAS2
== Ras in cancer ==
Mutations in the Ras family of proto-oncogenes (comprising H-Ras, N-Ras and K-Ras) are very common, being found in 20% to 30% of all human tumors. It is reasonable to speculate that a pharmacological approach that curtails Ras activity may represent a possible method to inhibit certain cancer types. Ras point mutations are the single most common abnormality of human proto-oncogenes.
Ras inhibitor trans-farnesylthiosalicylic acid (FTS, Salirasib) exhibits profound anti-oncogenic effects in many cancer cell lines.
=== Inappropriate activation ===
Inappropriate activation of the gene has been shown to play a key role in improper signal transduction, proliferation and malignant transformation.
Mutations in a number of different genes as well as RAS itself can have this effect. Oncogenes such as p210BCR-ABL or the growth receptor erbB are upstream of Ras, so if they are constitutively activated their signals will transduce through Ras.
The tumour suppressor gene NF1 encodes a Ras-GAP – its mutation in neurofibromatosis will mean that Ras is less likely to be inactivated. Ras can also be amplified, although this only occurs occasionally in tumours.
Finally, Ras oncogenes can be activated by point mutations so that the GTPase reaction can no longer be stimulated by GAP – this increases the half life of active Ras-GTP mutants.
=== Constitutively active Ras ===
Constitutively active Ras (RasD) is one which contains mutations that prevent GTP hydrolysis, thus locking Ras in a permanently 'On' state.
The most common mutations are found at residue G12 in the P-loop and the catalytic residue Q61.
The glycine to valine mutation at residue 12 renders the GTPase domain of Ras insensitive to inactivation by GAP and thus stuck in the "on state". Ras requires a GAP for inactivation as it is a relatively poor catalyst on its own, as opposed to other G-domain-containing proteins such as the alpha subunit of heterotrimeric G proteins.
Residue 61 is responsible for stabilizing the transition state for GTP hydrolysis. Because enzyme catalysis in general is achieved by lowering the energy barrier between substrate and product, mutation of Q61 to K (Glutamine to Lysine) necessarily reduces the rate of intrinsic Ras GTP hydrolysis to physiologically meaningless levels.
See also "dominant negative" mutants such as S17N and D119N.
=== Ras-targeted cancer treatments ===
Reovirus was noted to be a potential cancer therapeutic when studies suggested it reproduces well in certain cancer cell lines. It replicates specifically in cells that have an activated Ras pathway (a cellular signaling pathway that is involved in cell growth and differentiation). Reovirus replicates in and eventually kills Ras-activated tumour cells and as cell death occurs, progeny virus particles are free to infect surrounding cancer cells. This cycle of infection, replication and cell death is believed to be repeated until all tumour cells carrying an activated Ras pathway are destroyed.
Another tumor-lysing virus that specifically targets tumor cells with an activated Ras pathway is a type II herpes simplex virus (HSV-2) based agent, designated FusOn-H2. Activating mutations of the Ras protein and upstream elements of the Ras protein may play a role in more than two-thirds of all human cancers, including most metastatic disease. Reolysin, a formulation of reovirus, and FusOn-H2 are currently in clinical trials or under development for the treatment of various cancers. In addition, a treatment based on siRNA anti-mutated K-RAS (G12D) called siG12D LODER is currently in clinical trials for the treatment of locally advanced pancreatic cancer (NCT01188785, NCT01676259).
In glioblastoma mouse models SHP2 levels were heightened in cancerous brain cells. Inhibiting SHP2 in turn inhibited Ras dephosphorylation. This reduced tumor sizes and accompanying rise in survival rates.
Other strategies have attempted to manipulate the regulation of the above-mentioned localization of Ras. Farnesyltransferase inhibitors have been developed to stop the farnesylation of Ras and therefore weaken its affinity to membranes. Other inhibitors are targeting the palmitoylation cycle of Ras through inhibiting depalmitoylation by acyl-protein thioesterases, potentially leading to a destabilization of the Ras cycle.
A novel inhibitor finding strategy for mutated Ras molecules was described in. The Ras mutations in the 12th residue position inhibit the bound of the regulatory GAP molecule to the mutated Ras, causing uncontrolled cell growth. The novel strategy proposes finding small glue molecules, which attach the mutated Ras to the GAP, prohibiting uncontrolled cell growth and restoring the normal function. For this goal a theoretical Ras-GAP conformation was designed with a several Å gap between the molecules, and a high-throughput in silico docking was performed for finding gluing agents. As a proof of concept, two novel molecules were described with satisfying biological activity.
== In other species ==
In most of the cell types of most species, most Ras is the GDP type. This is true for Xenopus oocytes and mouse fibroblasts.
=== Xenopus laevis ===
As mentioned above most X. oocyte Ras is the GDP conjugate. Mammal Ras induces meiosis in X. laevis oocytes almost certainly by potentiating insulin-induced meiosis, but not progesterone-induced. Protein synthesis does not seem to be a part of this step. Injection increases synthesis of diacylglycerol from phosphatidylcholine. Some meiosis effects are antagonized by rap1 (and by a Ras modified to dock incorrectly). Both rap1 and the modified Ras are co-antagonists with p120Ras GAP in this pathway.
=== Drosophila melanogaster ===
Expressed in all tissues of Drosophila melanogaster but mostly in neural cells. Overexpression is somewhat lethal and, during development, produces eye and wing abnormalities. (This parallels - and may be the reason for - similar abnormalities due to mutated receptor tyrosine kinases.) The D. genes for rases in mammals produce abnormalities.
=== Aplysia ===
Most expression in Aplysia spp. is in neural cells.
=== Caenorhabditis elegans ===
The gene in C. elegans is let 60. Also appears to play a role in receptor tyrosine kinase formation in this model. Overexpression yields a multivulval development due to its involvement in that region's normal development; overexpression in effector sites in lethal.
=== Dictyostelium discoideum ===
Essential in Dictyostelium discoideum. This is evidenced by severe developmental failure in deficient ras expression and by significant impairment of various life activities when artificially expressed, such as: increased concentration of inositol phosphates; likely reduction of cAMP binding to chemotaxis receptors; and that is likely the reason cGMP synthesis is impaired. Adenylate cyclase activity is unaffected by ras.
== References ==
== Further reading ==
== External links ==
"Brain tumour findings offer hope of new strategy Canadian Cancer Society says" at ncic.cancer.ca
"Novel cancer treatment gets NCI support" at arstechnica.com
ras+Proteins at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
ras+Genes at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
Drosophila Ras oncogene at 85D - The Interactive Fly
"Animation of ras activation by EGFR"
"Rascore: A tool for analyzing RAS protein structures" | Wikipedia/Ras_proteins |
DNA ligase 1 also DNA ligase I, is an enzyme that in humans is encoded by the LIG1 gene. DNA ligase 1 is the only known eukaryotic DNA ligase involved in both DNA replication and repair, making it the most studied of the ligases.
== Discovery ==
It was known that DNA replication occurred through a double strand break, but the enzyme responsible for ligating the strands back together, and mechanism of action, was unknown until Lehman, Gellert, Richardson, and Hurwitz laboratories, made significant contributions to the discovery of DNA ligase in 1967.
== Recruitment and regulation ==
LIG1 encodes a, 120kDa enzyme, 919 residues long, known as DNA ligase 1. The DNA ligase 1 polypeptide contains an N-terminal replication factory-targeting sequence (RFTS), followed by a nuclear localization sequence (NLS), and three functional domains. The three domains consist of an N-terminal DNA binding domain (DBD), and catalytic nucleotidyltransferase (NTase), and C-terminal oligonucleotide / oligosaccharide binding (OB) domains. Although the N-terminus of the peptide has no catalytic activity it is needed for activity within the cells. The N-terminus of the protein contains a replication factory-targeting sequence that is used to recruit it to sites of DNA replication known as replication factories.
Activation and recruitment of DNA ligase 1 seem to be associated with posttranslational modifications. N-terminal domain is completed through phosphorylation of four serine residues on this domain, Ser51, Ser76, and Ser91 by cyclin-dependent kinase (CDK) and Ser66 by casein kinase II (CKII). Phosphorylation of these residues (Ser66 in particular) has been shown to possibly regulate the interaction between the RFTS to the proliferating cell nuclear antigen (PCNA) when ligase 1 is recruited to the replication factories during S-phase. Rossi et al. proposed that when Ser66 is dephosphorylated, the RFTS of ligase 1 interact with PCNA, which was confirmed in vitro by Tom et al. Both data sets provide plausible evidence the N-terminal region of ligase I plays a regulatory role in the enzymes in vivo function in the nucleus. Moreover, the identification of a cyclin binding (Cy) motif in the catalytic C-terminus domain was shown by mutational analysis to play a role in the phosphorylation of serines 91 and 76. Together, the N-terminal serines are substrates of the CDK and CKII, which appear to play an important regulatory role DNA ligase I recruitment to the replication factory during S-phase of the cell cycle.
== Function and mechanism ==
LIG1 encodes DNA ligase 1, which functions in DNA replication and the base excision repair process.
Eukaryotic DNA ligase 1 catalyzes a reaction that is chemically universal to all ligases. DNA ligase 1 utilizes adenosine triphosphate (ATP) to catalyze the energetically favorable ligation events in both DNA replication and repair. During the synthesis phase (S-phase) of the eukaryotic cell cycle, DNA replication occurs. DNA ligase 1 is responsible for joining Okazaki fragments formed during discontinuous DNA synthesis on the DNA's lagging strand after DNA polymerase δ has replaced the RNA primer nucleotides with DNA nucleotides. If the Okazaki fragments are not properly ligated together, the unligated DNA (containing a ‘nick’) could easily degrade to a double strand break, a phenomenon known to cause genetic mutations. In order to ligate these fragments together, the ligase progresses through three steps:
Addition of an adenosine monophosphate (AMP) group to the enzyme, referred to as adenylylation,
Adenosine monophosphate transfer to the DNA and
Nick sealing, or phosphodiester bond formation.
During adenylylation, there is a nucleophilic attack on the alpha phosphate of ATP from a catalytic lysine resulting in the production of inorganic pyrophosphate (PPi) and a covalently bound lysine-AMP intermediate in the active site of DNA ligase 1.
During the AMP transfer step, the DNA ligase becomes associated with the DNA, locates a nick and catalyzes a reaction at the 5’ phosphate site of the DNA nick. An anionic oxygen on the 5’ phosphate of the DNA nick serves as the nucleophile, attacking the alpha phosphate of the covalently bound AMP causing the AMP to be covalently bound intermediate (DNA-AMP intermediate).
In order for the phosphodiester bond to be formed, the DNA-AMP intermediate must be cleaved off. To accomplish this task, there is a nucleophilic attack on the 5’-phosphate from the upstream 3’-hydroxyl which results in the formation of the phosphodiester bond. During this nucleophilic attack, the AMP group is pushed off the 5’ phosphate as the leaving group allowing for the nick to seal and the AMP to be released, completing one cycle of DNA ligation.
Under suboptimal conditions the ligase can disassociate from the DNA before the full reaction is complete. It has been shown that magnesium levels can slow the nick sealing process, causing the ligase to disassociate from the DNA, leaving an aborted adenylylated intermediate incapable of being fixed without the aid of a phosphodiesterase. Aprataxin (a phosphodiesterase) has been shown to act on aborted DNA intermediates via hydrolysis of the AMP-phosphate bond, restoring the DNA to its initial state before the ligase had reacted.
== Role in damaged base repair ==
DNA ligase 1 functions to ligate single stranded DNA breaks in the final step of the base excision repair (BER) pathway. The nitrogenous bases of DNA are commonly damaged by environmental hazards such as reactive oxygen species, toxins, and ionizing radiation. BER is the major repair pathway responsible for excising and replacing damaged bases. Ligase I is involved in the LP-BER pathway, whereas ligase III is involved in the major SN-BER pathway(2). LP-BER proceeds in 4 catalytic steps. First, a DNA glycosylase cleaves the N-glycosidic bond, releasing the damaged base and creating an AP site– a site that lacks a purine or pyrimidine base. In the next step, an AP endonuclease creates a nick at the 5' end of the AP site, generating a hanging deoxyribose phosphate (dRP) residue in place of the AP site. DNA polymerase then synthesizes several new bases in the 5' to 3' direction, generating a hanging stretch of DNA with the dRP at its 5' end. It is at this step that SN-BER and LP-BER diverge in mechanism – in SNBER, only a single nucleotide is added and DNA Polymerase acts as a lyase to excise the AP site. In LP-BER, several bases are synthesized, generating a hanging flap of DNA, which is cleaved by a flap endonuclease. This leaves behind a nicked DNA strand that is sensed and ligated by DNA ligase. The action of ligase 1 is stimulated by other LP-BER enzymes, particularly AP-endonuclease and DNA polymerase.
== Clinical significance ==
Mutations in LIG1 that lead to DNA ligase 1 deficiency result in immunodeficiency and increased sensitivity to DNA-damaging agents.
There are rare reports of patients exhibiting ligase 1 deficiency which resulted from inherited mutant alleles. The first case manifested as stunted growth and development and an immunodeficiency. A mouse model was made based on cell lines derived from the patient, confirming that the mutant ligase confers replication errors leading to genomic instability. Notably the mutant mice also showed increases in tumorigenesis. Molecular, cellular, and clinical features of 5 patients from 3 kindreds with biallelic mutations were reported. The patients exhibited hypogammaglobulinemia, lymphopenia, increased proportions of circulating γδT cells, and very large red cells (macrocytosis.) Clinical severity ranged from a mild antibody deficiency to a combined immunodeficiency requiring hematopoietic stem cell transplantation. Chemical and radiation defects were demonstrated to impair the DNA repair pathways. Defects in DNA ligase 1 can thus lead to different forms of autosomal recessive, partial DNA ligase 1 deficiency leading to an immunodeficiency of variable severity.
Ligase I has also been found to be upregulated in proliferating tumor cells, as opposed to benign tumor cell lines and normal human cells. Furthermore, it has been shown that inhibiting ligase I expression in these cells can have a cytotoxic effect, suggesting that ligase I inhibitors may be viable chemotherapeutic agents.
Deficiencies in aprataxin, a phosphodiesterase responsible for reconditioning the DNA (after DNA ligase I aborts the adenylylated DNA intermediate), has been linked to neurodegeneration. This suggests that DNA is incapable of reentering the repair pathway without additional back-up machinery to correct for ligase errors.
With the structure of DNA being well known and many of the components necessary for its manipulation, repair, and usage becoming identified and characterized, researchers are beginning to look into the development of nanoscopic machinery that would be incorporated into a living organism that would possess the ability to treat diseases, fight cancer, and release medications based on a biological stimulus provided by the organism to the nanoscopic machinery. DNA ligase would most likely have to be incorporated into such a machine.
== References ==
== Further reading ==
== External links ==
Overview of all the structural information available in the PDB for UniProt: P18858 (DNA ligase 1) at the PDBe-KB. | Wikipedia/DNA_ligase_1 |
DNA ligase 3 also DNA ligase III, is an enzyme that, in humans, is encoded by the LIG3 gene. LIG3 encodes ATP-dependent DNA ligases that seal interruptions in the phosphodiester backbone of duplex DNA.
There are three families of ATP-dependent DNA ligases in eukaryotes. These enzymes utilize the same three step reaction mechanism; (i) formation of a covalent enzyme-adenylate intermediate; (ii) transfer of the adenylate group to the 5' phosphate terminus of a DNA nick; (iii) phosphodiester bond formation. Unlike LIG1 and LIG4 family members that are found in almost all eukaryotes, LIG3 family members are less widely distributed. LIG3 encodes several distinct DNA ligase species by alternative translation initiation and alternative splicing mechanisms that are described below.
== Structure, DNA binding and catalytic activities ==
Eukaryotic ATP-dependent DNA ligases have related catalytic region that contains three domains, a DNA binding domain, an adenylation domain and an oligonucleotide / oligosaccharide binding-fold domain. When these enzymes engage a nick in duplex DNA, these domains encircle the DNA duplex with each one making contact with the DNA. The structure of the catalytic region of DNA ligase III complexed with a nicked DNA has been determined by X-ray crystallography and is remarkably similar to that formed by the catalytic region of human DNA ligase I bound to nicked DNA. A unique feature of the DNA ligases encoded by the LIG3 gene is an N-terminal zinc finger that resembles the two zinc fingers at the N-terminus of poly (ADP-ribose) polymerase 1 (PARP1). As with the PARP1 zinc fingers, the DNA ligase III zinc finger is involved in binding to DNA strand breaks. Within the DNA ligase III polypeptide, the zinc finger co-operates with the DNA binding domain to form a DNA binding module. In addition, the adenylation domain and an oligonucleotide/oligosaccharide binding-fold domain form a second DNA binding module. In the jackknife model proposed by the Ellenberger laboratory, the zinc finger-DNA binding domain module serves as a strand break sensor that binds to DNA single strand interruptions irrespective of the nature of the strand break termini. If these breaks are ligatable, they are transferred to the adenylation domain-oligonucleotide/oligosaccharide binding-fold domain module that binds specifically to ligatable nicks. Compared with DNA ligases I and IV, DNA ligase III is the most active enzyme in the intermolecular joining of DNA duplexes. This activity is predominantly dependent upon the DNA ligase III zinc finger suggesting that the two DNA binding modules of DNA ligase III may be able to simultaneously engage duplex DNA ends.
== Alternative splicing ==
The alternative translation initiation and splicing mechanisms alter the amino- and carboxy-terminal sequences that flank the DNA ligase III catalytic region. In the alternative splicing mechanism, the exon encoding a C-terminal breast cancer susceptibility protein 1 C-terminal (BRCT) domain at the C-terminus of DNA ligase III-alpha is replaced by a short positively charged sequence that acts as a nuclear localization signal, generating DNA ligase III-beta. This alternatively spliced variant has, to date, only been detected in male germs cells. Based on its expression pattern during spermatogenesis, it appears likely that DNA ligase IIIbeta is involved in meiotic recombination and/or DNA repair in haploid sperm but this has not been definitively demonstrated. Although an internal ATG is the preferred site for translation initiation within the DNA ligase III open reading frame, translation initiations does also occur at the first ATG within the open reading frame, resulting in the synthesis of a polypeptide with an N-terminal mitochondrial targeting sequence.
== Cellular function ==
As mentioned above, DNA ligase III-alpha mRNA encodes nuclear and mitochondrial versions of DNA ligase III-alpha. Nuclear DNA ligase III-alpha exists and functions in a stable complex with the DNA repair protein XRCC1. These proteins interact via their C-terminal BRCT domains. XRCC1 has no enzymatic activity but instead appears to acts as a scaffold protein by interacting with a large number of proteins involved in base excision and single-strand break repair. The participation of XRCC1 in these pathways is consistent with the phenotype of xrcc1 cells. In contrast to nuclear DNA ligase III-alpha, mitochondrial DNA ligase III-alpha functions independently of XRCC1, which is not found in mitochondria. It appears that nuclear DNA ligase III-alpha forms a complex with XRCC1 in the cytoplasm and the subsequent nuclear targeting of the resultant complex is directed by the XRCC1 nuclear localization signal. While mitochondrial DNA ligase III-alpha also interacts with XRCC1, it is likely that the activity of the mitochondrial targeting sequence of DNA ligase III-alpha is greater than the activity of the XRCC1 nuclear localization signal and that the DNA ligase III-alpha/XRCC1 complex is disrupted when mitochondrial DNA ligase III-alpha passes through the mitochondrial membrane.
Since the LIG3 gene encodes the only DNA ligase in mitochondria, inactivation of the LIG3 gene results in loss of mitochondrial DNA that in turn leads to loss of mitochondrial function. Fibroblasts with inactivated Lig3 gene can be propagated in the media supplemented with uridine and pyruvate. However, these cells lack mtDNA. Physiological levels of mitochondrial DNA ligase III appear excessive, and cells with 100-fold reduced mitochondrial content of mitochondrial DNA ligase III-alpha maintain normal mtDNA copy number. The essential role of DNA ligase III-alpha in mitochondrial DNA metabolism can be fulfilled by other DNA ligases, including the NAD-dependent DNA ligase of E. coli, if they are targeted to mitochondria. Thus, viable cells that lack nuclear DNA ligase III-alpha can be generated. While DNA ligase I is the predominant enzyme that joins Okazaki fragments during DNA replication, it is now evident that the DNA ligase III-alpha/XRCC1 complex enables cells that either lack or have reduced DNA ligase I activity to complete DNA replication. Given the biochemical and cell biology studies linking the DNA ligase III-alpha/XRCC1 complex with excision repair and the repair of DNA single strand breaks, it was surprising that the cells lacking nuclear DNA ligase III-alpha did not exhibit significantly increased sensitivity to DNA damaging agent. These studies suggest that there is significant functional redundancy between DNA ligase I and DNA ligase III-alpha in these nuclear DNA repair pathways. In mammalian cells, most DNA double strand breaks are repaired by DNA ligase IV-dependent non-homologous end joining (NHEJ). DNA ligase III-alpha participates in a minor alternative NHEJ pathway that generates chromosomal translocations. Unlike the other nuclear DNA repair functions, it appears that the role of DNA ligase III-alpha in alternative NHEJ is independent of XRCC1.
== Clinical significance ==
Unlike the LIG1 and LIG4 genes, inherited mutations in the LIG3 gene have not been identified in the human population. DNA ligase III-alpha has, however, been indirectly implicated in cancer and neurodegenerative diseases. In cancer, DNA ligase III-alpha is frequently overexpressed and this serves as a biomarker to identify cells that are more dependent upon the alternative NHEJ pathway for the repair of DNA double strand breaks. Although the increased activity of the alternative NHEJ pathway causes genomic instability that drives disease progression, it also constitutes a novel target for the development of cancer cell-specific therapeutic strategies. Several genes encoding proteins that interact directly with DNA ligase III-alpha or indirectly via interactions with XRCC1 have been identified as being mutated in inherited neurodegenerative diseases. Thus, it appears that DNA transactions involving DNA ligase III-alpha play an important role in maintaining the viability of neuronal cells.
LIG3 has a role in microhomology-mediated end joining (MMEJ) repair of double strand breaks. It is one of 6 enzymes required for this error prone DNA repair pathway. LIG3 is upregulated in chronic myeloid leukemia, multiple myeloma, and breast cancer.
Cancers are very often deficient in expression of one or more DNA repair genes, but over-expression of a DNA repair gene is less usual in cancer. For instance, at least 36 DNA repair enzymes, when mutationally defective in germ line cells, cause increased risk of cancer (hereditary cancer syndromes). (Also see DNA repair-deficiency disorder.) Similarly, at least 12 DNA repair genes have frequently been found to be epigenetically repressed in one or more cancers. (See also Epigenetically reduced DNA repair and cancer.) Ordinarily, deficient expression of a DNA repair enzyme results in increased un-repaired DNA damages which, through replication errors (translesion synthesis), lead to mutations and cancer. However, LIG3 mediated MMEJ repair is highly inaccurate, so in this case, over-expression, rather than under-expression, apparently leads to cancer.
== Notes ==
== References ==
== External links ==
Overview of all the structural information available in the PDB for UniProt: P49916 (DNA ligase 3) at the PDBe-KB. | Wikipedia/DNA_ligase_3 |
DNA ligase 4 also DNA ligase IV, is an enzyme that in humans is encoded by the LIG4 gene.
== Function ==
DNA ligase 4 is an ATP-dependent DNA ligase that joins double-strand breaks during the non-homologous end joining pathway of double-strand break repair. It is also essential for V(D)J recombination. Lig4 forms a complex with XRCC4, and further interacts with the DNA-dependent protein kinase (DNA-PK) and XLF/Cernunnos, which are also required for NHEJ. The crystal structure of the Lig4/XRCC4 complex has been resolved. Defects in this gene are the cause of LIG4 syndrome. The yeast homolog of Lig4 is Dnl4.
== LIG4 syndrome ==
In humans, deficiency of DNA ligase 4 results in a clinical condition known as LIG4 syndrome. This syndrome is characterized by cellular radiation sensitivity, growth retardation, developmental delay, microcephaly, facial dysmorphisms, increased disposition to leukemia, variable degrees of immunodeficiency and reduced number of blood cells.
== Haematopoietic stem cell aging ==
Accumulation of DNA damage leading to stem cell exhaustion is regarded as an important aspect of aging. Deficiency of lig4 in pluripotent stem cells impairs Non-homologous end joining (NHEJ) and results in accumulation of DNA double-strand breaks and enhanced apoptosis. Lig4 deficiency in the mouse causes a progressive loss of haematopoietic stem cells and bone marrow cellularity during aging. The sensitivity of haematopoietic stem cells to lig4 deficiency suggests that lig4-mediated NHEJ is a key determinant of the ability of stem cells to maintain themselves against physiological stress over time.
== Interactions ==
LIG4 has been shown to interact with XRCC4 via its BRCT domain. This interaction stabilizes LIG4 protein in cells; cells that are deficient for XRCC4, such as XR-1 cells, have reduced levels of LIG4.
== Mechanism ==
LIG4 is an ATP-dependent DNA ligase. LIG4 uses ATP to adenylate itself and then transfers the AMP group to the 5' phosphate of one DNA end. Nucleophilic attack by the 3' hydroxyl group of a second DNA end and release of AMP yield the ligation product. Adenylation of LIG4 is stimulated by XRCC4 and XLF.
== References ==
== Further reading == | Wikipedia/DNA_ligase_4 |
Drug design, often referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies on computer modeling techniques. This type of modeling is sometimes referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design. In addition to small molecules, biopharmaceuticals including peptides and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also been developed.
== Definition ==
The phrase "drug design" is similar to ligand design (i.e., design of a molecule that will bind tightly to its target). Although design techniques for prediction of binding affinity are reasonably successful, there are many other properties, such as bioavailability, metabolic half-life, and side effects, that first must be optimized before a ligand can become a safe and effective drug. These other characteristics are often difficult to predict with rational design techniques.
Due to high attrition rates, especially during clinical phases of drug development, more attention is being focused early in the drug design process on selecting candidate drugs whose physicochemical properties are predicted to result in fewer complications during development and hence more likely to lead to an approved, marketed drug. Furthermore, in vitro experiments complemented with computation methods are increasingly used in early drug discovery to select compounds with more favorable ADME (absorption, distribution, metabolism, and excretion) and toxicological profiles.
== Drug targets ==
A biomolecular target (most commonly a protein or a nucleic acid) is a key molecule involved in a particular metabolic or signaling pathway that is associated with a specific disease condition or pathology or to the infectivity or survival of a microbial pathogen. Potential drug targets are not necessarily disease causing but must by definition be disease modifying. In some cases, small molecules will be designed to enhance or inhibit the target function in the specific disease modifying pathway. Small molecules (for example receptor agonists, antagonists, inverse agonists, or modulators; enzyme activators or inhibitors; or ion channel openers or blockers) will be designed that are complementary to the binding site of target. Small molecules (drugs) can be designed so as not to affect any other important "off-target" molecules (often referred to as antitargets) since drug interactions with off-target molecules may lead to undesirable side effects. Due to similarities in binding sites, closely related targets identified through sequence homology have the highest chance of cross reactivity and hence highest side effect potential.
Most commonly, drugs are organic small molecules produced through chemical synthesis, but biopolymer-based drugs (also known as biopharmaceuticals) produced through biological processes are becoming increasingly more common. In addition, mRNA-based gene silencing technologies may have therapeutic applications. For example, nanomedicines based on mRNA can streamline and expedite the drug development process, enabling transient and localized expression of immunostimulatory molecules. In vitro transcribed (IVT) mRNA allows for delivery to various accessible cell types via the blood or alternative pathways. The use of IVT mRNA serves to convey specific genetic information into a person's cells, with the primary objective of preventing or altering a particular disease.
=== Drug discovery ===
==== Phenotypic drug discovery ====
Phenotypic drug discovery is a traditional drug discovery method, also known as forward pharmacology or classical pharmacology. It uses the process of phenotypic screening on collections of synthetic small molecules, natural products, or extracts within chemical libraries to pinpoint substances exhibiting beneficial therapeutic effects. This method is to first discover the in vivo or in vitro functional activity of drugs (such as extract drugs or natural products), and then perform target identification. Phenotypic discovery uses a practical and target-independent approach to generate initial leads, aiming to discover pharmacologically active compounds and therapeutics that operate through novel drug mechanisms. This method allows the exploration of disease phenotypes to find potential treatments for conditions with unknown, complex, or multifactorial origins, where the understanding of molecular targets is insufficient for effective intervention.
==== Rational drug discovery ====
Rational drug design (also called reverse pharmacology) begins with a hypothesis that modulation of a specific biological target may have therapeutic value. In order for a biomolecule to be selected as a drug target, two essential pieces of information are required. The first is evidence that modulation of the target will be disease modifying. This knowledge may come from, for example, disease linkage studies that show an association between mutations in the biological target and certain disease states. The second is that the target is capable of binding to a small molecule and that its activity can be modulated by the small molecule.
Once a suitable target has been identified, the target is normally cloned and produced and purified. The purified protein is then used to establish a screening assay. In addition, the three-dimensional structure of the target may be determined.
The search for small molecules that bind to the target is begun by screening libraries of potential drug compounds. This may be done by using the screening assay (a "wet screen"). In addition, if the structure of the target is available, a virtual screen may be performed of candidate drugs. Ideally, the candidate drug compounds should be "drug-like", that is they should possess properties that are predicted to lead to oral bioavailability, adequate chemical and metabolic stability, and minimal toxic effects. Several methods are available to estimate druglikeness such as Lipinski's Rule of Five and a range of scoring methods such as lipophilic efficiency. Several methods for predicting drug metabolism have also been proposed in the scientific literature.
Due to the large number of drug properties that must be simultaneously optimized during the design process, multi-objective optimization techniques are sometimes employed. Finally because of the limitations in the current methods for prediction of activity, drug design is still very much reliant on serendipity and bounded rationality.
== Computer-aided drug design ==
The most fundamental goal in drug design is to predict whether a given molecule will bind to a target and if so how strongly. Molecular mechanics or molecular dynamics is most often used to estimate the strength of the intermolecular interaction between the small molecule and its biological target. These methods are also used to predict the conformation of the small molecule and to model conformational changes in the target that may occur when the small molecule binds to it. Semi-empirical, ab initio quantum chemistry methods, or density functional theory are often used to provide optimized parameters for the molecular mechanics calculations and also provide an estimate of the electronic properties (electrostatic potential, polarizability, etc.) of the drug candidate that will influence binding affinity.
Molecular mechanics methods may also be used to provide semi-quantitative prediction of the binding affinity. Also, knowledge-based scoring function may be used to provide binding affinity estimates. These methods use linear regression, machine learning, neural nets or other statistical techniques to derive predictive binding affinity equations by fitting experimental affinities to computationally derived interaction energies between the small molecule and the target.
Ideally, the computational method will be able to predict affinity before a compound is synthesized and hence in theory only one compound needs to be synthesized, saving enormous time and cost. The reality is that present computational methods are imperfect and provide, at best, only qualitatively accurate estimates of affinity. In practice, it requires several iterations of design, synthesis, and testing before an optimal drug is discovered. Computational methods have accelerated discovery by reducing the number of iterations required and have often provided novel structures.
Computer-aided drug design may be used at any of the following stages of drug discovery:
hit identification using virtual screening (structure- or ligand-based design)
hit-to-lead optimization of affinity and selectivity (structure-based design, QSAR, etc.)
lead optimization of other pharmaceutical properties while maintaining affinity
In order to overcome the insufficient prediction of binding affinity calculated by recent scoring functions, the protein-ligand interaction and compound 3D structure information are used for analysis. For structure-based drug design, several post-screening analyses focusing on protein-ligand interaction have been developed for improving enrichment and effectively mining potential candidates:
Consensus scoring
Selecting candidates by voting of multiple scoring functions
May lose the relationship between protein-ligand structural information and scoring criterion
Cluster analysis
Represent and cluster candidates according to protein-ligand 3D information
Needs meaningful representation of protein-ligand interactions.
== Types ==
There are two major types of drug design. The first is referred to as ligand-based drug design and the second, structure-based drug design.
=== Ligand-based ===
Ligand-based drug design (or indirect drug design) relies on knowledge of other molecules that bind to the biological target of interest. These other molecules may be used to derive a pharmacophore model that defines the minimum necessary structural characteristics a molecule must possess in order to bind to the target. A model of the biological target may be built based on the knowledge of what binds to it, and this model in turn may be used to design new molecular entities that interact with the target. Alternatively, a quantitative structure-activity relationship (QSAR), in which a correlation between calculated properties of molecules and their experimentally determined biological activity, may be derived. These QSAR relationships in turn may be used to predict the activity of new analogs.
=== Structure-based ===
Structure-based drug design (or direct drug design) relies on knowledge of the three dimensional structure of the biological target obtained through methods such as x-ray crystallography or NMR spectroscopy. If an experimental structure of a target is not available, it may be possible to create a homology model of the target based on the experimental structure of a related protein. Using the structure of the biological target, candidate drugs that are predicted to bind with high affinity and selectivity to the target may be designed using interactive graphics and the intuition of a medicinal chemist. Alternatively, various automated computational procedures may be used to suggest new drug candidates.
Current methods for structure-based drug design can be divided roughly into three main categories. The first method is identification of new ligands for a given receptor by searching large databases of 3D structures of small molecules to find those fitting the binding pocket of the receptor using fast approximate docking programs. This method is known as virtual screening.
A second category is de novo design of new ligands. In this method, ligand molecules are built up within the constraints of the binding pocket by assembling small pieces in a stepwise manner. These pieces can be either individual atoms or molecular fragments. The key advantage of such a method is that novel structures, not contained in any database, can be suggested. A third method is the optimization of known ligands by evaluating proposed analogs within the binding cavity.
==== Binding site identification ====
Binding site identification is the first step in structure based design. If the structure of the target or a sufficiently similar homolog is determined in the presence of a bound ligand, then the ligand should be observable in the structure in which case location of the binding site is trivial. However, there may be unoccupied allosteric binding sites that may be of interest. Furthermore, it may be that only apoprotein (protein without ligand) structures are available and the reliable identification of unoccupied sites that have the potential to bind ligands with high affinity is non-trivial. In brief, binding site identification usually relies on identification of concave surfaces on the protein that can accommodate drug sized molecules that also possess appropriate "hot spots" (hydrophobic surfaces, hydrogen bonding sites, etc.) that drive ligand binding.
==== Scoring functions ====
Structure-based drug design attempts to use the structure of proteins as a basis for designing new ligands by applying the principles of molecular recognition. Selective high affinity binding to the target is generally desirable since it leads to more efficacious drugs with fewer side effects. Thus, one of the most important principles for designing or obtaining potential new ligands is to predict the binding affinity of a certain ligand to its target (and known antitargets) and use the predicted affinity as a criterion for selection.
One early general-purposed empirical scoring function to describe the binding energy of ligands to receptors was developed by Böhm. This empirical scoring function took the form:
Δ
G
bind
=
Δ
G
0
+
Δ
G
hb
Σ
h
−
b
o
n
d
s
+
Δ
G
ionic
Σ
i
o
n
i
c
−
i
n
t
+
Δ
G
lipophilic
|
A
|
+
Δ
G
rot
N
R
O
T
{\displaystyle \Delta G_{\text{bind}}=\Delta G_{\text{0}}+\Delta G_{\text{hb}}\Sigma _{h-bonds}+\Delta G_{\text{ionic}}\Sigma _{ionic-int}+\Delta G_{\text{lipophilic}}\left\vert A\right\vert +\Delta G_{\text{rot}}{\mathit {NROT}}}
where:
ΔG0 – empirically derived offset that in part corresponds to the overall loss of translational and rotational entropy of the ligand upon binding.
ΔGhb – contribution from hydrogen bonding
ΔGionic – contribution from ionic interactions
ΔGlip – contribution from lipophilic interactions where |Alipo| is surface area of lipophilic contact between the ligand and receptor
ΔGrot – entropy penalty due to freezing a rotatable in the ligand bond upon binding
A more general thermodynamic "master" equation is as follows:
Δ
G
bind
=
−
R
T
ln
K
d
K
d
=
[
Ligand
]
[
Receptor
]
[
Complex
]
Δ
G
bind
=
Δ
G
desolvation
+
Δ
G
motion
+
Δ
G
configuration
+
Δ
G
interaction
{\displaystyle {\begin{array}{lll}\Delta G_{\text{bind}}=-RT\ln K_{\text{d}}\\[1.3ex]K_{\text{d}}={\dfrac {[{\text{Ligand}}][{\text{Receptor}}]}{[{\text{Complex}}]}}\\[1.3ex]\Delta G_{\text{bind}}=\Delta G_{\text{desolvation}}+\Delta G_{\text{motion}}+\Delta G_{\text{configuration}}+\Delta G_{\text{interaction}}\end{array}}}
where:
desolvation – enthalpic penalty for removing the ligand from solvent
motion – entropic penalty for reducing the degrees of freedom when a ligand binds to its receptor
configuration – conformational strain energy required to put the ligand in its "active" conformation
interaction – enthalpic gain for "resolvating" the ligand with its receptor
The basic idea is that the overall binding free energy can be decomposed into independent components that are known to be important for the binding process. Each component reflects a certain kind of free energy alteration during the binding process between a ligand and its target receptor. The Master Equation is the linear combination of these components. According to Gibbs free energy equation, the relation between dissociation equilibrium constant, Kd, and the components of free energy was built.
Various computational methods are used to estimate each of the components of the master equation. For example, the change in polar surface area upon ligand binding can be used to estimate the desolvation energy. The number of rotatable bonds frozen upon ligand binding is proportional to the motion term. The configurational or strain energy can be estimated using molecular mechanics calculations. Finally the interaction energy can be estimated using methods such as the change in non polar surface, statistically derived potentials of mean force, the number of hydrogen bonds formed, etc. In practice, the components of the master equation are fit to experimental data using multiple linear regression. This can be done with a diverse training set including many types of ligands and receptors to produce a less accurate but more general "global" model or a more restricted set of ligands and receptors to produce a more accurate but less general "local" model.
== Examples ==
A particular example of rational drug design involves the use of three-dimensional information about biomolecules obtained from such techniques as X-ray crystallography and NMR spectroscopy. Computer-aided drug design in particular becomes much more tractable when there is a high-resolution structure of a target protein bound to a potent ligand. This approach to drug discovery is sometimes referred to as structure-based drug design. The first unequivocal example of the application of structure-based drug design leading to an approved drug is the carbonic anhydrase inhibitor dorzolamide, which was approved in 1995.
Another case study in rational drug design is imatinib, a tyrosine kinase inhibitor designed specifically for the bcr-abl fusion protein that is characteristic for Philadelphia chromosome-positive leukemias (chronic myelogenous leukemia and occasionally acute lymphocytic leukemia). Imatinib is substantially different from previous drugs for cancer, as most agents of chemotherapy simply target rapidly dividing cells, not differentiating between cancer cells and other tissues.
Additional examples include:
== Drug screening ==
Types of drug screening include phenotypic screening, high-throughput screening, and virtual screening. Phenotypic screening is characterized by the process of screening drugs using cellular or animal disease models to identify compounds that alter the phenotype and produce beneficial disease-related effects. Emerging technologies in high-throughput screening substantially enhance processing speed and decrease the required detection volume. Virtual screening is completed by computer, enabling a large number of molecules can be screened with a short cycle and low cost. Virtual screening uses a range of computational methods that empower chemists to reduce extensive virtual libraries into more manageable sizes.
== Case studies ==
== Criticism ==
It has been argued that the highly rigid and focused nature of rational drug design suppresses serendipity in drug discovery.
== See also ==
== References ==
== External links ==
Drug+Design at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
[Drug Design Org](https://www.drugdesign.org/chapters/drug-design/) | Wikipedia/Computer-aided_drug_design |
AAA (ATPases Associated with diverse cellular Activities) proteins (speak: triple-A ATPases) are a large group of protein family sharing a common conserved module of approximately 230 amino acid residues. This is a large, functionally diverse protein family belonging to the AAA+ protein superfamily of ring-shaped P-loop NTPases, which exert their activity through the energy-dependent remodeling or translocation of macromolecules.
AAA proteins couple chemical energy provided by ATP hydrolysis to conformational changes which are transduced into mechanical force exerted on a macromolecular substrate.
AAA proteins are functionally and organizationally diverse, and vary in activity, stability, and mechanism. Members of the AAA family are found in all organisms and they are essential for many cellular functions. They are involved in processes such as DNA replication, protein degradation, membrane fusion, microtubule severing, peroxisome biogenesis, signal transduction and the regulation of gene expression.
== Structure ==
The AAA proteins contain two domains, an N-terminal alpha/beta domain that binds and hydrolyzes nucleotides (a Rossmann fold) and a C-terminal alpha-helical domain. The N-terminal domain is 200-250 amino acids long and contains Walker A and Walker B motifs, and is shared in common with other P-loop NTPases, the superfamily which includes the AAA family. Most AAA proteins have additional domains that are used for oligomerization, substrate binding and/or regulation. These domains can lie N- or C-terminal to the AAA module.
=== Classification ===
Some classes of AAA proteins have an N-terminal non-ATPase domain which is followed by either one or two AAA domains (D1 and D2). In some proteins with two AAA domains, both are evolutionarily well conserved (like in Cdc48/p97). In others, either the D2 domain (like in Pex1p and Pex6p) or the D1 domain (in Sec18p/NSF) is better conserved in evolution.
While the classical AAA family was based on motifs, the family has been expanded using structural information and is now termed the AAA family.
=== Evolutionary relationships ===
AAA proteins are divided into seven basic clades, based on secondary structure elements included within or near the core AAA fold: clamp loader, initiator, classic, superfamily III helicase, HCLR, H2-insert, and PS-II insert.
== Quaternary structure ==
AAA ATPases assemble into oligomeric assemblies (often homo-hexamers) that form a ring-shaped structure with a central pore. These proteins produce a molecular motor that couples ATP binding and hydrolysis to changes in conformational states that can be propagated through the assembly in order to act upon a target substrate, either translocating or remodelling the substrate.
The central pore may be involved in substrate processing. In the hexameric configuration, the ATP-binding site is positioned at the interface between the subunits. Upon ATP binding and hydrolysis, AAA enzymes undergo conformational changes in the AAA-domains as well as in the N-domains. These motions can be transmitted to substrate protein.
== Molecular mechanism ==
ATP hydrolysis by AAA ATPases is proposed to involve nucleophilic attack on the ATP gamma-phosphate by an activated water molecule, leading to movement of the N-terminal and C-terminal AAA subdomains relative to each other. This movement allows the exertion of mechanical force, amplified by other ATPase domains within the same oligomeric structure. The additional domains in the protein allow for regulation or direction of the force towards different goals.
== Prokaryotic AAAs ==
AAA proteins are not restricted to eukaryotes. Prokaryotes have AAA which combine chaperone with proteolytic activity, for example in ClpAPS complex, which mediates protein degradation and recognition in E. coli. The basic recognition of proteins by AAAs is thought to occur through unfolded protein domains in the substrate protein. In HslU, a bacterial ClpX/ClpY homologue of the HSP100 family of AAA proteins, the N- and C-terminal subdomains move towards each other when nucleotides are bound and hydrolysed. The terminal domains are most distant in the nucleotide-free state and closest in the ADP-bound state. Thereby the opening of the central cavity is affected.
== Functions ==
AAA proteins are involved in protein degradation, membrane fusion, DNA replication, microtubule dynamics, intracellular transport, transcriptional activation, protein refolding, disassembly of protein complexes and protein aggregates.
=== Molecular motion ===
Dyneins, one of the three major classes of motor protein, are AAA proteins which couple their ATPase activity to molecular motion along microtubules.
The AAA-type ATPase Cdc48p/p97 is perhaps the best-studied AAA protein. Misfolded secretory proteins are exported from the endoplasmic reticulum (ER) and degraded by the ER-associated degradation pathway (ERAD). Nonfunctional membrane and luminal proteins are extracted from the ER and degraded in the cytosol by proteasomes. Substrate retrotranslocation and extraction is assisted by the Cdc48p(Ufd1p/Npl4p) complex on the cytosolic side of the membrane. On the cytosolic side, the substrate is ubiquitinated by ER-based E2 and E3 enzymes before degradation by the 26S proteasome.
=== Targeting to multivesicular bodies ===
Multivesicular bodies are endosomal compartments that sort ubiquitinated membrane proteins by incorporating them into vesicles. This process involves the sequential action of three multiprotein complexes, ESCRT I to III (ESCRT standing for 'endosomal sorting complexes required for transport'). Vps4p is a AAA-type ATPase involved in this MVB sorting pathway. It had originally been identified as a ”class E” vps (vacuolar protein sorting) mutant and was subsequently shown to catalyse the dissociation of ESCRT complexes. Vps4p is anchored via Vps46p to the endosomal membrane. Vps4p assembly is assisted by the conserved Vta1p protein, which regulates its oligomerization status and ATPase activity.
=== Proteasome functions ===
AAA proteases use the energy from ATP hydrolysis to translocate a protein inside the proteasome for degradation. Cdc48p/p97 functions as a hexameric AAA+ ATPase that provides the mechanical force necessary for substrate dislocation. Its activity is tightly regulated by ATP binding and hydrolysis, which induce conformational changes required for protein unfolding and extraction. The HbYX motif plays a crucial role in regulating this process by mediating interactions between Cdc48p/p97 and downstream effectors such as the 20S proteasome or specific cofactors (e.g., Ufd1/Npl4). This interaction facilitates substrate transfer from Cdc48p/p97 to the proteasome, ensuring efficient protein degradation.
Given its pivotal role in protein homeostasis, Cdc48p/p97 has been implicated in a wide range of cellular processes beyond ERAD, including autophagy, mitochondrial quality control, and DNA repair. The dysregulation of its function, particularly through mutations affecting the ATPase domain or HbYX-mediated interactions, has been linked to neurodegenerative diseases and cancer.
== Human proteins containing this domain ==
=== AAA ATPase family (HGNC) ===
AFG3L2; ATAD1; ATAD2; ATAD2B; ATAD3A; ATAD3B;
ATAD3C; ATAD5; BCS1L; CHTF18; CLBP; CLPP; CLPX; FIGN; FIGNL1; FIGNL2;
IQCA1; KATNA1; KATNAL1; KATNAL2; LONP1; LONP2; MDN1; NSF; NVL;
ORC1; ORC4; PEX1; PEX6; PSMC1; PSMC2 (Nbla10058); PSMC3; PSMC4;
PSMC5; PSMC6; RFC1; RFC2; RFC3; RFC4; RFC5; RUVBL1; RUVBL2;
SPAST; SPATA5 (SPAF); SPATA5L1; SPG7; TRIP13; VCP; VPS4A; VPS4B;
WRNIP1; YME1L1 (FTSH);
==== Torsins ====
TOR1A; TOR1B; TOR2A; TOR3A; TOR4A;
=== Other ===
AK6 (CINAP); CDC6;
=== Pseudogenes ===
AFG3L1P;
== Further reading ==
Snider J, Houry WA (February 2008). "AAA+ proteins: diversity in function, similarity in structure". Biochemical Society Transactions. 36 (Pt 1): 72–77. doi:10.1042/BST0360072. PMID 18208389. S2CID 13407283.
White SR, Lauring B (December 2007). "AAA+ ATPases: achieving diversity of function with conserved machinery". Traffic. 8 (12): 1657–1667. doi:10.1111/j.1600-0854.2007.00642.x. PMID 17897320. S2CID 29221806.
== References == | Wikipedia/AAA_protein |
DNA polymerase III holoenzyme is the primary enzyme complex involved in prokaryotic DNA replication. It was discovered by Thomas Kornberg (son of Arthur Kornberg) and Malcolm Gefter in 1970. The complex has high processivity (i.e. the number of nucleotides added per binding event) and, specifically referring to the replication of the E.coli genome, works in conjunction with four other DNA polymerases (Pol I, Pol II, Pol IV, and Pol V). Being the primary holoenzyme involved in replication activity, the DNA Pol III holoenzyme also has proofreading capabilities that corrects replication mistakes by means of exonuclease activity reading 3'→5' and synthesizing 5'→3'. DNA Pol III is a component of the replisome, which is located at the replication fork.
== Components ==
The replisome is composed of the following:
2 DNA Pol III enzymes, each comprising α, ε and θ subunits. (It has been proven that there is a third copy of Pol III at the replisome.)
the α subunit (encoded by the dnaE gene) has the polymerase activity.
the ε subunit (dnaQ) has 3'→5' exonuclease activity.
the θ subunit (holE) stimulates the ε subunit's proofreading.
2 β units (dnaN) which act as sliding DNA clamps, they keep the polymerase bound to the DNA.
2 τ units (dnaX) which act to dimerize two of the core enzymes (α, ε, and θ subunits).
1 γ unit (also dnaX) which acts as a clamp loader for the lagging strand Okazaki fragments, helping the two β subunits to form a unit and bind to DNA. The γ unit is made up of 5 γ subunits which include 3 γ subunits, 1 δ subunit (holA), and 1 δ' subunit (holB). The δ is involved in copying of the lagging strand.
Χ (holC) and Ψ (holD) which form a 1:1 complex and bind to γ or τ. X can also mediate the switch from RNA primer to DNA.
== Activity ==
DNA polymerase III synthesizes base pairs at a rate of around 1000 nucleotides per second. DNA Pol III activity begins after strand separation at the origin of replication. Because DNA synthesis cannot start de novo, an RNA primer, complementary to part of the single-stranded DNA, is synthesized by primase (an RNA polymerase):
("!" for RNA, '"$" for DNA, "*" for polymerase)
-------->
* * * *
! ! ! ! _ _ _ _
_ _ _ _ | RNA | <--ribose (sugar)-phosphate backbone
G U A U | Pol | <--RNA primer
* * * * |_ _ _ _| <--hydrogen bonding
C A T A G C A T C C <--template ssDNA (single-stranded DNA)
_ _ _ _ _ _ _ _ _ _ <--deoxyribose (sugar)-phosphate backbone
$ $ $ $ $ $ $ $ $ $
=== Addition onto 3'OH ===
As replication progresses and the replisome moves forward, DNA polymerase III arrives at the RNA primer and begins replicating the DNA, adding onto the 3'OH of the primer:
* * * *
! ! ! ! _ _ _ _
_ _ _ _ | DNA | <--deoxyribose (sugar)-phosphate backbone
G U A U | Pol | <--RNA primer
* * * * |_III_ _| <--hydrogen bonding
C A T A G C A T C C <--template ssDNA (single-stranded DNA)
_ _ _ _ _ _ _ _ _ _ <--deoxyribose (sugar)-phosphate backbone
$ $ $ $ $ $ $ $ $ $
=== Synthesis of DNA ===
DNA polymerase III will then synthesize a continuous or discontinuous strand of DNA, depending if this is occurring on the leading or lagging strand (Okazaki fragment) of the DNA. DNA polymerase III has a high processivity and therefore, synthesizes DNA very quickly. This high processivity is due in part to the β-clamps that "hold" onto the DNA strands.
----------->
* * * *
! ! ! ! $ $ $ $ $ $ _ _ _ _
_ _ _ _ _ _ _ _ _ _| DNA | <--deoxyribose (sugar)-phosphate backbone
G U A U C G T A G G| Pol | <--RNA primer
* * * * * * * * * *|_III_ _| <--hydrogen bonding
C A T A G C A T C C <--template ssDNA (single-stranded DNA)
_ _ _ _ _ _ _ _ _ _ <--deoxyribose (sugar)-phosphate backbone
$ $ $ $ $ $ $ $ $ $
=== Removal of primer ===
After replication of the desired region, the RNA primer is removed by DNA polymerase I via the process of nick translation. The removal of the RNA primer allows DNA ligase to ligate the DNA-DNA nick between the new fragment and the previous strand. DNA polymerase I & III, along with many other enzymes are all required for the high fidelity, high-processivity of DNA replication.
== See also ==
Beta clamp
DNA polymerase
DNA replication
== References ==
== External links ==
Overview at Oregon State University
DNA+Polymerase+III at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
Clamping down on pathogenic bacteria – how to shut down a key DNA polymerase complex | Wikipedia/DNA_polymerase_III |
DNA polymerase iota is an enzyme that in humans is encoded by the POLI gene. It is found in higher eukaryotes, and is believed to have arisen from a gene duplication from Pol η. Pol ι, is a Y family polymerase that is involved in translesion synthesis. It can bypass 6-4 pyrimidine adducts and abasic sites and has a high frequency of wrong base incorporation. Like many other Y family polymerases Pol ι, has low processivity, a large DNA binding pocket and doesn't undergo conformational changes when DNA binds. These attributes are what allow Pol ι to carry out its task as a translesion polymerase. Pol ι only uses Hoogsteen base pairing, during DNA synthesis, it will add adenine opposite to thymine in the syn conformation and can add both cytosine and thymine in the anti conformation across guanine, which it flips to the syn conformation.
== Xeroderma pigmentosum variant ==
Xeroderma pigmentosum variant (XPV) cells lack DNA polymerase eta (η). Instead these cells use DNA polymerase iota (ι). Exposure of XPV cells to UV light causes a very high frequency and unique spectrum of UV-induced mutations that can ultimately lead to malignant transformation.
== References ==
== Further reading == | Wikipedia/DNA_Polymerase_Iota |
Hepatitis B virus DNA polymerase is a hepatitis B viral protein. It is a DNA polymerase that can use either DNA or RNA templates and a ribonuclease H that cuts RNA in the duplex. Both functions are supplied by the reverse transcriptase (RT) domain.
== Structure ==
The hepadnaviral P protein is organized into four domains: an N-terminal domain called the terminal protein (TP) (InterPro: IPR000201), a spacer domain which has no apparent function to the polymerase, a reverse transcriptase (RT) domain related to every other reverse transcriptase domain, and a C-terminal Ribonuclease H (RNase H) domain (InterPro: IPR001462).
Uniquely, the hepadnavirus terminal protein (TP) domain contains a tyrosine residue that serves as a primer for the synthesis of the (−) DNA strand.
== Function ==
The Hepatitis B virus (HBV) polymerase is a multifunctional enzyme, with both RNA-dependent and DNA-dependent polymerase functions, as well as an RNase H function. It acts on the HBV pre-genomic RNA (pgRNA) to reverse transcribe it to form a new rcDNA molecule within a new capsid. (The pgRNA has another function of being translated into the viral polymerase and core proteins).
HBV core protein dimers are required for packaging of the pgRNA/polymerase complex. Then, after viral polymerase binds to the packaging signal (Hɛ) found at the 5′ end of the pgRNA, they are incorporated into the viral capsid.
Inside the capsid, the pgRNA undergoes reverse transcription, which is initiated by protein priming at the tyrosine residue of the HBV polymerase. Thus, the (−) DNA strand is made. At the same time, the RNA template is degraded by the RNase H activity of the polymerase. A short RNA of about 15–18 nucleotides at the 5′ end of the pgRNA (including the 5′ DR1 sequence) is not degraded and it is used as primer for (+) DNA strand synthesis.
The resulting RC-DNA is partially double stranded. The (−) DNA strand is longer than a genome length, with a covalently bound polymerase and a redundant flap at the 5′ end. However, the (+) DNA strand synthesis is uncompleted by the polymerase, and there is a gap exists down to the 3′ end of the (+) DNA strand.
== References == | Wikipedia/Hepatitis_B_virus_DNA_polymerase |
Φ29 DNA polymerase is an enzyme from the bacteriophage Φ29. It is being increasingly used in molecular biology for multiple displacement DNA amplification procedures, and has a number of features that make it particularly suitable for this application. It was discovered and characterized by Spanish scientists Luis Blanco and Margarita Salas.
== Φ29 DNA replication ==
Φ29 is a bacteriophage of Bacillus subtilis with a sequenced, linear, 19,285 base pair DNA genome. Each 5' end is covalently linked to a terminal protein, which is essential in the replication process by acting as a primer for the viral DNA polymerase.
A symmetrical mode of replication has been suggested, whereby protein-primed initiation occurs non-simultaneously from either end of the chromosome; this involves two replication origins and two distinct polymerase monomers. Synthesis is continual and involves a strand displacement mechanism. This was demonstrated by the ability of the enzyme to continue to copy the singly primed circular genome of the M13 phage more than tenfold in a single strand (over 70kb in a single strand).
In vitro experiments have shown that Φ29 replication can proceed to completion with the sole phage protein requirements of the polymerase and the terminal protein.
The polymerase catalyses the formation of the initiation complex between the terminal protein and the chromosome ends at an adenine residue. From here, continual synthesis can occur.
== The polymerase ==
The polymerase is a monomeric protein with two distinct functional domains. Site-directed mutagenesis experiments support the proposition that this protein displays a structural and functional similarity to the Klenow fragment of the Escherichia coli Polymerase I enzyme; it comprises a C-terminal polymerase domain and a spatially separated N-terminal domain with a 3'-5' exonuclease activity.
The isolated enzyme has no intrinsic helicase activity but may carry out an equivalent function by way of its strong binding to single stranded DNA, particularly in preference to double stranded nucleic acid. This is the property of this enzyme that makes is favorably applicable to Multiple Displacement Amplification. The enzyme facilitates the "debranching" of double stranded DNA. Deoxyribonucleoside triphosphate cleavage that occurs as part of the polymerization process probably supplies the energy required for this unwinding mechanism. The continuous nature of strand synthesis (compared to the asymmetric synthesis seen in other organisms) probably contributes to this enhanced processivity.
Proofreading activity conferred by the exonuclease domain was demonstrated by showing the preferential excision of a mismatched nucleotide from the 3' terminus of the newly synthesized strand. The exonuclease activity of the enzyme is, like its polymerization activity, highly processive and can degrade single-stranded oligonucleotides without dissociation. Co-operation or a 'delicate competition' between these two functional domains is essential, so as to ensure accurate elongation at an optimal rate. The exonuclease activity of the enzyme does impede its polymerization capacity; inactivation of the exonuclease activity by site-directed mutagenesis meant that a 350 fold lower dNTP concentration was required to achieve the same rates of primer elongation seen in the wild type enzyme.
== Whole genome amplification ==
Φ29 polymerase enzyme is already used in multiple displacement amplification (MDA) procedures (including in a number of commercial kits) whereby fragments tens of kilobases in length can be produced from non-specific hexameric primers annealing at intervals along the genome. The enzyme has many desirable properties that make it appropriate for whole genome amplification (WGA) by this method.
High processivity.
Proofreading activity. It is believed to be 1 or 2 orders of magnitude less error prone than Taq polymerase.
Generates large fragments, over 10kb.
Produces more DNA than PCR-based methods, by about an order of magnitude.
Requires minimal amount of template; 10 ng suffices.
Novel replication mechanism; multiple-strand displacement amplification.
Random primers (hexamers) can be used, no need to design specific primers/target specific regions.
No need for thermal cycling.
Good coverage and a reduced amplification bias when compared to PCR-based approaches. There is speculation that it is the least biased of the WGA methods in use.
== References ==
== Further reading ==
Linck L, Resch-Genger U (2010). "Identification of efficient fluorophores for the direct labeling of DNA via rolling circle amplification (RCA) polymerase φ29". Eur J Med Chem. 45 (12): 5561–6. doi:10.1016/j.ejmech.2010.09.005. PMID 20926164.
de Vega M, Lázaro JM, Mencía M, Blanco L, Salas M (2010). "Improvement of φ29 DNA polymerase amplification performance by fusion of DNA binding motifs". Proc Natl Acad Sci U S A. 107 (38): 16506–11. Bibcode:2010PNAS..10716506D. doi:10.1073/pnas.1011428107. PMC 2944734. PMID 20823261.
Pérez-Arnaiz P, Lázaro JM, Salas M, de Vega M (2010). "phi29 DNA polymerase active site: role of residue Val250 as metal-dNTP complex ligand and in protein-primed initiation". J Mol Biol. 395 (2): 223–33. doi:10.1016/j.jmb.2009.10.061. hdl:10486/709525. PMID 19883660.
Pérez-Arnaiz P, Lázaro JM, Salas M, de Vega M (2009). "Functional importance of bacteriophage phi29 DNA polymerase residue Tyr148 in primer-terminus stabilisation at the 3'-5' exonuclease active site". J Mol Biol. 391 (5): 797–807. doi:10.1016/j.jmb.2009.06.068. hdl:10486/709542. PMID 19576228.
Johne R, Müller H, Rector A, van Ranst M, Stevens H (2009). "Rolling-circle amplification of viral DNA genomes using phi29 polymerase". Trends Microbiol. 17 (5): 205–11. doi:10.1016/j.tim.2009.02.004. PMID 19375325.
Lagunavicius A, Merkiene E, Kiveryte Z, Savaneviciute A, Zimbaite-Ruskuliene V, Radzvilavicius T, Janulaitis A (2009). "Novel application of Phi29 DNA polymerase: RNA detection and analysis in vitro and in situ by target RNA-primed RCA". RNA. 15 (5): 765–71. doi:10.1261/rna.1279909. PMC 2673074. PMID 19244362.
Rodríguez I, Lázaro JM, Salas M, de Vega M (2009). "Involvement of the TPR2 subdomain movement in the activities of phi29 DNA polymerase". Nucleic Acids Res. 37 (1): 193–203. doi:10.1093/nar/gkn928. PMC 2615600. PMID 19033368.
Sahu S, LaBean TH, Reif JH (2008). "A DNA nanotransport device powered by polymerase phi29". Nano Lett. 8 (11): 3870–8. CiteSeerX 10.1.1.151.6316. doi:10.1021/nl802294d. PMID 18939810.
Xu Y, Gao S, Bruno JF, Luft BJ, Dunn JJ (2008). "Rapid detection and identification of a pathogen's DNA using Phi29 DNA polymerase". Biochem. Biophys. Res. Commun. 375 (4): 522–5. doi:10.1016/j.bbrc.2008.08.082. PMC 2900840. PMID 18755142.
Kumar G, Garnova E, Reagin M, Vidali A (2008). "Improved multiple displacement amplification with phi29 DNA polymerase for genotyping of single human cells". BioTechniques. 44 (7): 879–90. doi:10.2144/000112755. PMID 18533898.
Salas M, Blanco L, Lázaro JM, de Vega M (2008). "The bacteriophage phi29 DNA polymerase". IUBMB Life. 60 (1): 82–5. doi:10.1002/iub.19. PMID 18379997. S2CID 39622915.
Silander K, Saarela J (2008). "Whole Genome Amplification with Phi29 DNA Polymerase to Enable Genetic or Genomic Analysis of Samples of Low DNA Yield". Genomics Protocols. Methods in Molecular Biology. Vol. 439. pp. 1–18. doi:10.1007/978-1-59745-188-8_1. ISBN 978-1-58829-871-3. PMID 18370092.
Lagunavicius A, Kiveryte Z, Zimbaite-Ruskuliene V, Radzvilavicius T, Janulaitis A (2008). "Duality of polynucleotide substrates for Phi29 DNA polymerase: 3'-->5' RNase activity of the enzyme". RNA. 14 (3): 503–13. doi:10.1261/rna.622108. PMC 2248250. PMID 18230765.
Pérez-Arnaiz P, Longás E, Villar L, Lázaro JM, Salas M, de Vega M (2007). "Involvement of phage phi29 DNA polymerase and terminal protein subdomains in conferring specificity during initiation of protein-primed DNA replication". Nucleic Acids Res. 35 (21): 7061–73. doi:10.1093/nar/gkm749. PMC 2175359. PMID 17913744.
Berman AJ, Kamtekar S, Goodman JL, Lázaro JM, de Vega M, Blanco L, Salas M, Steitz TA (2007). "Structures of phi29 DNA polymerase complexed with substrate: the mechanism of translocation in B-family polymerases". EMBO J. 26 (14): 3494–505. doi:10.1038/sj.emboj.7601780. PMC 1933411. PMID 17611604.
Knierim D, Maiss E (2007). "Application of Phi29 DNA polymerase in identification and full-length clone inoculation of tomato yellow leaf curl Thailand virus and tobacco leaf curl Thailand virus". Arch Virol. 152 (5): 941–54. doi:10.1007/s00705-006-0914-9. PMID 17226067. S2CID 12464800.
Owor BE, Shepherd DN, Taylor NJ, Edema R, Monjane AL, Thomson JA, Martin DP, Varsani A (2007). "Successful application of FTA Classic Card technology and use of bacteriophage phi29 DNA polymerase for large-scale field sampling and cloning of complete maize streak virus genomes". J Virol Methods. 140 (1–2): 100–5. doi:10.1016/j.jviromet.2006.11.004. PMID 17174409.
Sato M, Ohtsuka M, Ohmi Y (2004). "Repeated GenomiPhi, phi29 DNA polymerase-based rolling circle amplification, is useful for generation of large amounts of plasmid DNA". Nucleic Acids Symp Ser (Oxf). 48 (48): 147–8. doi:10.1093/nass/48.1.147. PMID 17150521.
Pérez-Arnaiz P, Lázaro JM, Salas M, de Vega M (2006). "Involvement of phi29 DNA polymerase thumb subdomain in the proper coordination of synthesis and degradation during DNA replication". Nucleic Acids Res. 34 (10): 3107–15. doi:10.1093/nar/gkl402. PMC 1475753. PMID 16757576.
Kamtekar S, Berman AJ, Wang J, Lázaro JM, de Vega M, Blanco L, Salas M, Steitz TA (2006). "The phi29 DNA polymerase:protein-primer structure suggests a model for the initiation to elongation transition". EMBO J. 25 (6): 1335–43. doi:10.1038/sj.emboj.7601027. PMC 1422159. PMID 16511564.
Hutchison CA, Smith HO, Pfannkoch C, Venter JC (2005). "Cell-free cloning using phi29 DNA polymerase". Proc Natl Acad Sci U S A. 102 (48): 17332–6. Bibcode:2005PNAS..10217332H. doi:10.1073/pnas.0508809102. PMC 1283157. PMID 16286637.
Sato M, Ohtsuka M, Ohmi Y (2005). "Usefulness of repeated GenomiPhi, a phi29 DNA polymerase-based rolling circle amplification kit, for generation of large amounts of plasmid DNA". Biomol Eng. 22 (4): 129–32. doi:10.1016/j.bioeng.2005.05.001. PMID 16023891.
Rodríguez I, Lázaro JM, Blanco L, Kamtekar S, Berman AJ, Wang J, Steitz TA, Salas M, de Vega M (2005). "A specific subdomain in phi29 DNA polymerase confers both processivity and strand-displacement capacity". Proc Natl Acad Sci U S A. 102 (18): 6407–12. Bibcode:2005PNAS..102.6407R. doi:10.1073/pnas.0500597102. PMC 1088371. PMID 15845765.
Truniger V, Bonnin A, Lázaro JM, de Vega M, Salas M (2005). "Involvement of the "linker" region between the exonuclease and polymerization domains of phi29 DNA polymerase in DNA and TP binding". Gene. 348: 89–99. doi:10.1016/j.gene.2004.12.041. PMID 15777661.
Umetani N, de Maat MF, Mori T, Takeuchi H, Hoon DS (2005). "Synthesis of universal unmethylated control DNA by nested whole genome amplification with phi29 DNA polymerase". Biochem. Biophys. Res. Commun. 329 (1): 219–23. doi:10.1016/j.bbrc.2005.01.088. PMID 15721296.
Gadkar V, Rillig MC (2005). "Application of Phi29 DNA polymerase mediated whole genome amplification on single spores of arbuscular mycorrhizal (AM) fungi". FEMS Microbiol Lett. 242 (1): 65–71. doi:10.1016/j.femsle.2004.10.041. PMID 15621421.
Kamtekar S, Berman AJ, Wang J, Lázaro JM, de Vega M, Blanco L, Salas M, Steitz TA (2004). "Insights into strand displacement and processivity from the crystal structure of the protein-primed DNA polymerase of bacteriophage phi29". Mol Cell. 16 (4): 609–18. doi:10.1016/j.molcel.2004.10.019. PMID 15546620.
Adachi E, Shimamura K, Wakamatsu S, Kodama H (2004). "Amplification of plant genomic DNA by Phi29 DNA polymerase for use in physical mapping of the hypermethylated genomic region". Plant Cell Rep. 23 (3): 144–7. doi:10.1007/s00299-004-0806-y. PMID 15168072. S2CID 11041367.
Rodríguez I, Lázaro JM, Salas M, De Vega M (2004). "phi29 DNA polymerase-terminal protein interaction. Involvement of residues specifically conserved among protein-primed DNA polymerases". J Mol Biol. 337 (4): 829–41. doi:10.1016/j.jmb.2004.02.018. PMID 15033354.
Inoue-Nagata AK, Albuquerque LC, Rocha WB, Nagata T (2004). "A simple method for cloning the complete begomovirus genome using the bacteriophage phi29 DNA polymerase". J Virol Methods. 116 (2): 209–11. doi:10.1016/j.jviromet.2003.11.015. PMID 14738990.
Truniger V, Lázaro JM, Salas M (2004). "Function of the C-terminus of phi29 DNA polymerase in DNA and terminal protein binding". Nucleic Acids Res. 32 (1): 361–70. doi:10.1093/nar/gkh184. PMC 373294. PMID 14729920.
Truniger V, Lázaro JM, Salas M (2004). "Two positively charged residues of phi29 DNA polymerase, conserved in protein-primed DNA polymerases, are involved in stabilisation of the incoming nucleotide". J Mol Biol. 335 (2): 481–94. doi:10.1016/j.jmb.2003.10.024. PMID 14672657.
Rodríguez I, Lázaro JM, Salas M, de Vega M (2003). "phi29 DNA polymerase residue Phe128 of the highly conserved (S/T)Lx(2)h motif is required for a stable and functional interaction with the terminal protein". J Mol Biol. 325 (1): 85–97. doi:10.1016/S0022-2836(02)01130-0. PMID 12473453.
Nelson JR, Cai YC, Giesler TL, Farchaus JW, Sundaram ST, Ortiz-Rivera M, Hosta LP, Hewitt PL, Mamone JA, Palaniappan C, Fuller CW (2002). "TempliPhi, phi29 DNA polymerase based rolling circle amplification of templates for DNA sequencing". BioTechniques. Suppl: 44–7. PMID 12083397.
Truniger V, Lázaro JM, Blanco L, Salas M (2002). "A highly conserved lysine residue in phi29 DNA polymerase is important for correct binding of the templating nucleotide during initiation of phi29 DNA replication". J Mol Biol. 318 (1): 83–96. doi:10.1016/S0022-2836(02)00022-0. PMID 12054770.
Truniger V, Lázaro JM, Esteban FJ, Blanco L, Salas M (2002). "A positively charged residue of phi29 DNA polymerase, highly conserved in DNA polymerases from families A and B, is involved in binding the incoming nucleotide". Nucleic Acids Res. 30 (7): 1483–92. doi:10.1093/nar/30.7.1483. PMC 101840. PMID 11917008.
Eisenbrandt R, Lázaro JM, Salas M, de Vega M (2002). "Phi29 DNA polymerase residues Tyr59, His61 and Phe69 of the highly conserved ExoII motif are essential for interaction with the terminal protein". Nucleic Acids Res. 30 (6): 1379–86. doi:10.1093/nar/30.6.1379. PMC 101362. PMID 11884636.
Elías-Arnanz M, Salas M (1999). "Resolution of head-on collisions between the transcription machinery and bacteriophage phi29 DNA polymerase is dependent on RNA polymerase translocation". EMBO J. 18 (20): 5675–82. doi:10.1093/emboj/18.20.5675. PMC 1171634. PMID 10523310.
de Vega M, Blanco L, Salas M (1999). "Processive proofreading and the spatial relationship between polymerase and exonuclease active sites of bacteriophage phi29 DNA polymerase". J Mol Biol. 292 (1): 39–51. doi:10.1006/jmbi.1999.3052. PMID 10493855.
Bonnin A, Lázaro JM, Blanco L, Salas M (1999). "A single tyrosine prevents insertion of ribonucleotides in the eukaryotic-type phi29 DNA polymerase". J Mol Biol. 290 (1): 241–51. doi:10.1006/jmbi.1999.2900. PMID 10388570.
Truniger V, Blanco L, Salas M (1999). "Role of the "YxGG/A" motif of Phi29 DNA polymerase in protein-primed replication". J Mol Biol. 286 (1): 57–69. doi:10.1006/jmbi.1998.2477. PMID 9931249.
de Vega M, Blanco L, Salas M (1998). "phi29 DNA polymerase residue Ser122, a single-stranded DNA ligand for 3'-5' exonucleolysis, is required to interact with the terminal protein". J Biol Chem. 273 (44): 28966–77. doi:10.1074/jbc.273.44.28966. PMID 9786901.
Saturno J, Lázaro JM, Blanco L, Salas M (1998). "Role of the first aspartate residue of the "YxDTDS" motif of phi29 DNA polymerase as a metal ligand during both TP-primed and DNA-primed DNA synthesis". J Mol Biol. 283 (3): 633–42. doi:10.1006/jmbi.1998.2121. PMID 9784372.
Murthy V, Meijer WJ, Blanco L, Salas M (1998). "DNA polymerase template switching at specific sites on the phi29 genome causes the in vivo accumulation of subgenomic phi29 DNA molecules". Mol Microbiol. 29 (3): 787–98. doi:10.1046/j.1365-2958.1998.00972.x. PMID 9723918.
Illana B, Zaballos A, Blanco L, Salas M (1998). "The RGD sequence in phage phi29 terminal protein is required for interaction with phi29 DNA polymerase". Virology. 248 (1): 12–9. doi:10.1006/viro.1998.9276. PMID 9705251.
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de Vega M, Lazaro JM, Salas M, Blanco L (1996). "Primer-terminus stabilization at the 3'-5' exonuclease active site of phi29 DNA polymerase. Involvement of two amino acid residues highly conserved in proofreading DNA polymerases". EMBO J. 15 (5): 1182–92. doi:10.1002/j.1460-2075.1996.tb00457.x. PMC 450017. PMID 8605889. | Wikipedia/Φ29_DNA_polymerase |
Nucleoproteins are proteins conjugated with nucleic acids (either DNA or RNA). Typical nucleoproteins include ribosomes, nucleosomes and viral nucleocapsid proteins.
== Structures ==
Nucleoproteins tend to be positively charged, facilitating interaction with the negatively charged nucleic acid chains. The tertiary structures and biological functions of many nucleoproteins are understood. Important techniques for determining the structures of nucleoproteins include X-ray diffraction, nuclear magnetic resonance and cryo-electron microscopy.
=== Viruses ===
Virus genomes (either DNA or RNA) are extremely tightly packed into the viral capsid. Many viruses are therefore little more than an organised collection of nucleoproteins with their binding sites pointing inwards. Structurally characterised viral nucleoproteins include influenza, rabies, Ebola, Bunyamwera, Schmallenberg, Hazara, Crimean-Congo hemorrhagic fever, and Lassa.
== Deoxyribonucleoproteins ==
A deoxyribonucleoprotein (DNP) is a complex of DNA and protein. The prototypical examples are nucleosomes, complexes in which genomic DNA is wrapped around clusters of eight histone proteins in eukaryotic cell nuclei to form chromatin. Protamines replace histones during spermatogenesis.
=== Functions ===
The most widespread deoxyribonucleoproteins are nucleosomes, in which the component is nuclear DNA. The proteins combined with DNA are histones and protamines; the resulting nucleoproteins are located in chromosomes. Thus, the entire chromosome, i.e. chromatin in eukaryotes consists of such nucleoproteins.
In eukaryotic cells, DNA is associated with about an equal mass of histone proteins in a highly condensed nucleoprotein complex called chromatin. Deoxyribonucleoproteins in this kind of complex interact to generate a multiprotein regulatory complex in which the intervening DNA is looped or wound. The deoxyribonucleoproteins participate in regulating DNA replication and transcription.
Deoxyribonucleoproteins are also involved in homologous recombination, a process for repairing DNA that appears to be nearly universal. A central intermediate step in this process is the interaction of multiple copies of a recombinase protein with single-stranded DNA to form a DNP filament. Recombinases employed in this process are produced by archaea (RadA recombinase), by bacteria (RecA recombinase) and by eukaryotes from yeast to humans (Rad51 and Dmc1 recombinases).
== Ribonucleoproteins ==
A ribonucleoprotein (RNP) is a complex of ribonucleic acid and RNA-binding protein. These complexes play an integral part in a number of important biological functions that include transcription, translation and regulating gene expression and regulating the metabolism of RNA. A few examples of RNPs include the ribosome, the enzyme telomerase, vault ribonucleoproteins, RNase P, hnRNP and small nuclear RNPs (snRNPs), which have been implicated in pre-mRNA splicing (spliceosome) and are among the main components of the nucleolus. Some viruses are simple ribonucleoproteins, containing only one molecule of RNA and a number of identical protein molecules. Others are ribonucleoprotein or deoxyribonucleoprotein complexes containing a number of different proteins, and exceptionally more nucleic acid molecules. Currently, over 2000 RNPs can be found in the RCSB Protein Data Bank (PDB). Furthermore, the Protein-RNA Interface Data Base (PRIDB) possesses a collection of information on RNA-protein interfaces based on data drawn from the PDB. Some common features of protein-RNA interfaces were deduced based on known structures. For example, RNP in snRNPs have an RNA-binding motif in its RNA-binding protein. Aromatic amino acid residues in this motif result in stacking interactions with RNA. Lysine residues in the helical portion of RNA-binding proteins help to stabilize interactions with nucleic acids. This nucleic acid binding is strengthened by electrostatic attraction between the positive lysine side chains and the negative nucleic acid phosphate backbones. Additionally, it is possible to model RNPs computationally. Although computational methods of deducing RNP structures are less accurate than experimental methods, they provide a rough model of the structure which allows for predictions of the identity of significant amino acids and nucleotide residues. Such information helps in understanding the overall function the RNP.'RNP' can also refer to ribonucleoprotein particles. Ribonucleoprotein particles are distinct intracellular foci for post-transcriptional regulation. These particles play an important role in influenza A virus replication. The influenza viral genome is composed of eight ribonucleoprotein particles formed by a complex of negative-sense RNA bound to a viral nucleoprotein. Each RNP carries with it an RNA polymerase complex. When the nucleoprotein binds to the viral RNA, it is able to expose the nucleotide bases which allow the viral polymerase to transcribe RNA. At this point, once the virus enters a host cell it will be prepared to begin the process of replication.
=== Anti-RNP antibodies ===
Anti-RNP antibodies are autoantibodies associated with mixed connective tissue disease and are also detected in nearly 40% of Lupus erythematosus patients. Two types of anti-RNP antibodies are closely related to Sjögren's syndrome: SS-A (Ro) and SS-B (La). Autoantibodies against snRNP are called Anti-Smith antibodies and are specific for SLE. The presence of a significant level of anti-U1-RNP also serves a possible indicator of MCTD when detected in conjunction with several other factors.
=== Functions ===
The ribonucleoproteins play a role of protection. mRNAs never occur as free RNA molecules in the cell. They always associate with ribonucleoproteins and function as ribonucleoprotein complexes.
In the same way, the genomes of negative-strand RNA viruses never exist as free RNA molecule. The ribonucleoproteins protect their genomes from RNase. Nucleoproteins are often the major antigens for viruses because they have strain-specific and group-specific antigenic determinants.
== See also ==
DNA-binding protein
RNA-binding protein
== References ==
== External links ==
PRIDB Protein-RNA Interface Database | Wikipedia/Ribonucleoprotein |
Taq polymerase is a thermostable DNA polymerase I named after the thermophilic eubacterial microorganism Thermus aquaticus, from which it was originally isolated by master's student Alice Chien et al. in 1976. Its name is often abbreviated to Taq or Taq pol. It is frequently used in the polymerase chain reaction (PCR), a method for greatly amplifying the quantity of short segments of DNA.
T. aquaticus is a bacterium that lives in hot springs and hydrothermal vents, and Taq polymerase was identified as an enzyme able to withstand the protein-denaturing conditions (high temperature) required during PCR. Therefore, it replaced the DNA polymerase from E. coli originally used in PCR.
== Enzymatic properties ==
Taq's optimum temperature for activity is 75–80 °C, with a half-life of greater than 2 hours at 92.5 °C, 40 minutes at 95 °C and 9 minutes at 97.5 °C, and can replicate a 1000 base pair strand of DNA in less than 10 seconds at 72 °C. At 75–80 °C, Taq reaches its optimal polymerization rate of about 150 nucleotides per second per enzyme molecule, and any deviations from the optimal temperature range inhibit the extension rate of the enzyme. A single Taq synthesizes about 60 nucleotides per second at 70 °C, 24 nucleotides/sec at 55 °C, 1.5 nucleotides/sec at 37 °C, and 0.25 nucleotides/sec at 22 °C. At temperatures above 90 °C, Taq demonstrates very little or no activity at all, but the enzyme itself does not denature and remains intact. Presence of certain ions in the reaction vessel also affects specific activity of the enzyme. Small amounts of potassium chloride (KCl) and magnesium ion (Mg2+) promote Taq's enzymatic activity. Taq polymerase is maximally activated at 50mM KCl, while optimal Mg2+ concentration is determined by the concentration of nucleoside triphosphates (dNTPs). High concentrations of KCl and Mg2+ inhibit Taq's activity. The common metal ion chelator EDTA directly binds to Taq in the absence of these metal ions.
One of Taq's drawbacks is its lack of 3' to 5' exonuclease proofreading activity resulting in relatively low replication fidelity. Originally its error rate was measured at about 1 in 9,000 nucleotides. Some thermostable DNA polymerases have been isolated from other thermophilic bacteria and archaea, such as Pfu DNA polymerase, possessing a proofreading activity, and are being used instead of (or in combination with) Taq for high-fidelity amplification. Fidelity can vary widely between Taqs, which has profound effects in downstream sequencing applications.
Taq makes DNA products that have A (adenine) overhangs at their 3' ends. This may be useful in TA cloning, whereby a cloning vector (such as a plasmid) that has a T (thymine) 3' overhang is used, which complements with the A overhang of the PCR product, thus enabling ligation of the PCR product into the plasmid vector.
== In PCR ==
In the early 1980s, Kary Mullis was working at Cetus Corporation on the application of synthetic DNAs to biotechnology. He was familiar with the use of DNA oligonucleotides as probes for binding to target DNA strands, as well as their use as primers for DNA sequencing and cDNA synthesis. In 1983, he began using two primers, one to hybridize to each strand of a target DNA, and adding DNA polymerase to the reaction. This led to exponential DNA replication, greatly amplifying discrete segments of DNA between the primers.
However, after each round of replication the mixture needs to be heated above 90 °C to denature the newly formed DNA, allowing the strands to separate and act as templates in the next round of amplification. This heating step also inactivates the DNA polymerase that was in use before the discovery of Taq polymerase, the Klenow fragment (sourced from E. coli). Taq polymerase is well-suited for this application because it is able to withstand the temperature of 95 °C which is required for DNA strand separation without denaturing.
Use of the thermostable Taq enables running the PCR at high temperature (~60 °C and above), which facilitates high specificity of the primers and reduces the production of nonspecific products, such as primer dimer. Also, use of a thermostable polymerase eliminates the need to add new enzyme to each round of thermocycling. A single closed tube in a relatively simple machine can be used to carry out the entire process. Thus, the use of Taq polymerase was the key idea that made PCR applicable to a large variety of molecular biology problems concerning DNA analysis.
== Patent issues ==
Hoffmann-La Roche eventually bought the PCR and Taq patents from Cetus for $330 million, from which it may have received up to $2 billion in royalties. In 1989, Science Magazine named Taq polymerase its first "Molecule of the Year". Kary Mullis received the Nobel Prize in Chemistry in 1993, the only one awarded for research performed at a biotechnology company. By the early 1990s, the PCR technique with Taq polymerase was being used in many areas, including basic molecular biology research, clinical testing, and forensics. It also began to find a pressing application in direct detection of the HIV in AIDS.
In December 1999, U.S. District Judge Vaughn Walker ruled that the 1990 patent involving Taq polymerase was issued, in part, on misleading information and false claims by scientists with Cetus Corporation. The ruling supported a challenge by Promega Corporation against Hoffman-La Roche, which purchased the Taq patents in 1991. Judge Walker cited previous discoveries by other laboratories, including the laboratory of John Trela at the University of Cincinnati department of biological sciences, as the basis for the ruling.
== Domain structure ==
Taq Pol A has an overall structure similar to that of E. coli PolA. The middle 3'–5' exonuclease domain responsible for proofreading has been dramatically changed and is not functional. It has a functional 5'-3' exonuclease domain at the amino terminal, described below. The remaining two domains act in coordination, via coupled domain motion.
=== Exonuclease domain ===
Taq polymerase exonuclease is a domain found in the amino-terminal of Taq DNA polymerase I (thermostable). It assumes a ribonuclease H-like motif. The domain confers 5'-3' exonuclease activity to the polymerase.
Unlike the same domain in E. coli, which would degrade primers and must be removed by digestion for PCR use, this domain is not said to degrade the primer. This activity is used in the TaqMan probe: as the daughter strands are formed, the probes complementary to the template come in contact with the polymerase and are cleaved into fluorescent pieces.
=== Binding with DNA ===
Taq polymerase is bound at its polymerase active-site cleft with the blunt end of duplex DNA. As the Taq polymerase is in contact with the bound DNA, its side chains form hydrogen bonds with the purines and pyrimidines of the DNA. The same region of Taq polymerase that has bonded to DNA also binds with exonuclease. These structures bound to the Taq polymerase have different interactions.
=== Mutants ===
A site-directed mutagenesis experiment that improves the vestigial 3'-5' exonuclease activity by a factor of 2 has been reported, but it was never reported whether doing so decreases the error rate. Following a similar line of thought, chimera proteins have been made by cherry-picking domains from E. coli, Taq, and T. neapolitana polymerase I. Swapping out the vestigial domain for a functional one from E. coli created a protein with proof-reading ability but a lower optimal temperature and low thermostability.
Versions of the polymerase without the 5'-3' exonuclease domain has been produced, among which Klentaq or the Stoffel fragment are best known. The complete lack of exonuclease activity make these variants suitable for primers that exhibit secondary structure as well as for copying circular molecules. Other variations include using Klentaq with a high-fidelity polymerase, a Thermosequenase that recognizes substrates like T7 DNA polymerase does, mutants with higher tolerances to inhibitors, or "domain-tagged" versions that have an extra helix-hairpin-helix motif around the catalytic site to hold the DNA more tightly despite adverse conditions.
=== Significance in disease detection ===
Because of the improvements Taq polymerase provided in PCR DNA replication: higher specificity, fewer nonspecific products, and simpler processes and equipment, it has been instrumental in the efforts made to detect diseases. "The use of Polymerase Chain Reaction (PCR) in infectious disease diagnosis, has resulted in an ability to diagnose early and treat appropriately diseases due to fastidious pathogens, determine the antimicrobial susceptibility of slow growing organisms, and ascertain the quantum of infection." The implementation of Taq polymerase has saved countless lives. It has served an essential role in the detection of many of the world's worst diseases, including: tuberculosis, streptococcal pharyngitis, atypical pneumonia, AIDS, measles, hepatitis, and ulcerative urogenital infections. PCR, the method used to recreate copies of specific DNA samples, makes disease detection possible by targeting a specific DNA sequence of a targeted pathogen from a patient's sample and amplifying trace amounts of the indicative sequences by copying them up to billions of times. Although this is the most accurate method of disease detection, especially for HIV, it is not performed as often as alternative, inferior tests because of the relatively high cost, labor, and time required.
The reliance upon Taq polymerase as a catalyst for the PCR replication process has been highlighted during the COVID-19 Pandemic of 2020. Shortages of the necessary enzyme have impaired the ability of countries worldwide to produce test kits for the virus. Without Taq polymerase, the disease detection process is much slower and tedious.
Despite the advantages of using Taq polymerase in PCR disease detection, the enzyme is not without its shortcomings. Retroviral diseases (HIV, HTLV-1, and HTLV-II) often include mutations from guanine to adenine in their genome. Mutations such as these are what allow PCR tests to detect the diseases but Taq polymerase’s relatively low fidelity rate makes the same G-to-A mutation occur and possibly yield a false positive test result.
== See also ==
== References == | Wikipedia/Taq_DNA_polymerase |
The 5S ribosomal RNA (5S rRNA) is an approximately 120 nucleotide-long ribosomal RNA molecule with a mass of 40 kDa. It is a structural and functional component of the large subunit of the ribosome in all domains of life (bacteria, archaea, and eukaryotes), with the exception of mitochondrial ribosomes of fungi and animals. The designation 5S refers to the molecule's sedimentation coefficient in an ultracentrifuge, which is measured in Svedberg units (S).
== Biosynthesis ==
In prokaryotes, the 5S rRNA gene is typically located in the rRNA operons downstream of the small and the large subunit rRNA, and co-transcribed into a polycistronic precursor. A particularity of eukaryotic nuclear genomes is the occurrence of multiple 5S rRNA gene copies (5S rDNA) clustered in tandem repeats, with copy number varying from species to species.
Eukaryotic 5S rRNA is synthesized by RNA polymerase III, whereas other eukaryotic rRNAs are cleaved from a 45S precursor transcribed by RNA polymerase I. In Xenopus oocytes, it has been shown that fingers 4–7 of the nine-zinc finger transcription factor TFIIIA can bind to the central region of 5S RNA. Binding between 5S rRNA and TFIIIA serves to both repress further transcription of the 5S RNA gene and stabilize the 5S RNA transcript until it is required for ribosome assembly.
== Structure ==
The secondary structure of 5S rRNA consists of five helices (denoted I–V in roman numerals), four loops (B-E), and one hinge (A), which form together a Y-like structure. Loops C and D are terminal hairpins and loops B and E are internal. According to phylogenetic studies, helices I and III are likely ancestral. Helix III includes two highly conserved adenosines. Helix V, with its hairpin structure, is thought to interact with TFIIIA.
== Location within the ribosome ==
Using a variety of molecular techniques, including immuno-electron microscopy, cryo-electron microscopy, intermolecular chemical cross-linking, and X-ray crystallography, the location of the 5S rRNA within the large ribosomal subunit has been determined to great precision. In bacteria and archaea, the large ribosomal subunit (LSU) itself is composed of two RNA moieties, the 5S rRNA and another larger RNA known as 23S rRNA, along with numerous associated proteins.
In eukaryotes, the LSU contains 5S, 5.8S, and 28S rRNAs and even more proteins.
The structure of LSU in 3-dimensions shows one relatively smooth surface and the opposite surface having three projections, notably the L1 protuberance, the central protuberance (CP), and the L7/L12 stalk. The L1 protuberance and L7/L12 stalk are arranged laterally surrounding CP. The 5S rRNA is located in the CP and participates in formation and structure of this projection. The other major constituents of the central protuberance include the 23S rRNA (or alternatively 28S in eukaryotes) and several proteins including L5, L18, L25, and L27.
== Ribosomal functions ==
The exact function of 5S rRNA is not yet clear. In Escherichia coli, 5S rRNA gene deletions reduce the protein synthesis rate and have a more profound detrimental effect on cell fitness than deletions of a comparable number of copies of other (16S and 23S) rRNA genes.
Crystallographic studies indicate that 5S rRNA-binding proteins and other proteins of the central protuberance of the LSU plays a role in binding tRNAs. Also, the topographical and physical proximity between 5S rRNA and 23S rRNA, which forms the peptidyl transferase and GTPase-associating center, suggests that 5S rRNA acts as a mediator between the two functional centers of the ribosome by forming, together with 5S rRNA-binding proteins and other components of the central protuberance, intersubunit bridges and tRNA-binding sites.
== Roles in ribosomal assembly ==
In eukaryotes, the cytosolic ribosome is assembled from four rRNAs and over 80 proteins. Once transcribed, the 3' ends of 5S rRNA can only be trimmed to mature length by functional homologues of RNase T, for example Rex1p in Saccharomyces cerevisiae. The 60S and 40S ribosomal subunits are exported from the nucleus to the cytoplasm where they join to form the mature and translation-competent 80S ribosome. When exactly 5S rRNA is integrated into the ribosome remains controversial, but it is generally accepted that 5S rRNA is incorporated into the 90S particle, which is a precursor to 60S particle, as part of a small ribosome-independent RNP complex formed by 5S rRNA and ribosomal protein L5.
== Interactions with proteins ==
Several important proteins which interact with 5S rRNA are listed below.
=== La protein ===
Interaction of 5S rRNA with the La protein prevents the RNA from degradation by exonucleases in the cell. La protein is found in the nucleus in all eukaryotic organisms and associates with several types of RNAs transcribed by RNA pol III. La protein interacts with these RNAs (including the 5S rRNA) through their 3' oligo-uridine tract, aiding stability and folding of the RNA.
=== L5 protein ===
In eukaryotic cells, ribosomal protein L5 associates and stabilizes the 5S rRNA forming a pre-ribosomal ribonucleoprotein particle (RNP) that is found in both cytosol and the nucleus. L5 deficiency prevents transport of 5S rRNA to the nucleus and results in decreased ribosomal assembly.
=== Other ribosomal proteins ===
In prokaryotes the 5S rRNA binds to the L5, L18 and L25 ribosomal proteins, whereas in eukaryotes 5S rRNA is only known to bind the L5 ribosomal protein. In T. brucei, the causative agent of sleeping sickness, 5S rRNA interacts with two closely related RNA-binding proteins, P34 and P37, whose loss results in a lower global level of 5S rRNA.
== Presence in organelle ribosomes ==
Translation machineries of mitochondria and plastids (organelles of endosymbiotic bacterial origin), and their bacterial relatives share many features but also display marked differences. Organelle genomes encode SSU and LSU rRNAs without exception, yet the distribution of 5S rRNA genes (rrn5) is most uneven. Rrn5 is easily identified and common in genomes of most plastids. In contrast, mitochondrial rrn5 initially appeared to be restricted to plants and a small number of protists. Additional, more divergent organellar 5S rRNAs were only identified with specialized covariance models that incorporate information on the pronounced sequence composition bias and structural variation. This analysis pinpointed additional 5S rRNA genes not only in mitochondrial genomes of most protist lineages, but also in genomes of certain apicoplasts (non-photosynthetic plastids of pathogenic protozoa such as Toxoplasma gondii and Eimeria tenella).
Mitochondrial 5S rRNAs of most stramenopiles comprise the largest diversity of secondary structures. The permuted mitochondrial 5S rRNAs in brown algae represent the most unconventional case, where the closing helix I, which otherwise brings together the molecule's 5′ and 3′ ends, is replaced by a (closed) hairpin resulting in an open three-way junction.
Current evidence indicates that mitochondrial DNA of only a few groups, notably animals, fungi, alveolates and euglenozoans lacks the gene. The central protuberance, otherwise occupied by 5S rRNA and its associated proteins (see Figure 2), was remodeled in various ways. In the fungal mitochondrial ribosomes, 5S rRNA is replaced by LSU rRNA expansion sequences. In kinetoplastids (euglenozoans), the central protuberance is made entirely of evolutionarily novel mitochondrial ribosomal proteins. Lastly, animal mitochondrial ribosomes have coopted a specific mitochondrial tRNA (Val in vertebrates) to substitute the missing 5S rRNA.
== See also ==
50S
Ribosome
Translation (biology)
== References ==
== External links ==
Page for 5S ribosomal RNA at Rfam
5SData Archived 2010-04-27 at the Wayback Machine
5S+Ribosomal+RNA at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
5S_rRNA human gene location in the UCSC Genome Browser.
Halococcus morrhuae (archaebacterium) 5S rRNA | Wikipedia/5S_ribosomal_DNA |
Extrachromosomal DNA (abbreviated ecDNA) is any DNA that is found off the chromosomes, either inside or outside the nucleus of a cell. Most DNA in an individual genome is found in chromosomes contained in the nucleus. Multiple forms of extrachromosomal DNA exist, and, while some of these serve important biological functions, they can also play a role in diseases such as cancer.
In prokaryotes, nonviral extrachromosomal DNA is primarily found in plasmids, whereas, in eukaryotes extrachromosomal DNA is primarily found in organelles. Mitochondrial DNA is a main source of this extrachromosomal DNA in eukaryotes. The fact that this organelle contains its own DNA supports the hypothesis that mitochondria originated as bacterial cells engulfed by ancestral eukaryotic cells. Extrachromosomal DNA is often used in research into replication because it is easy to identify and isolate.
Although extrachromosomal circular DNA (eccDNA) is found in normal eukaryotic cells, extrachromosomal DNA (ecDNA) is a distinct entity that has been identified in the nuclei of cancer cells and has been shown to carry many copies of driver oncogenes. ecDNA is considered to be a primary mechanism of gene amplification, resulting in many copies of driver oncogenes and very aggressive cancers.
Extrachromosomal DNA in the cytoplasm has been found to be structurally different from nuclear DNA. Cytoplasmic DNA is less methylated than DNA found within the nucleus. It was also confirmed that the sequences of cytoplasmic DNA were different from nuclear DNA in the same organism, showing that cytoplasmic DNAs are not simply fragments of nuclear DNA. In cancer cells, ecDNA have been shown to be primarily isolated to the nucleus (reviewed in ).
In addition to DNA found outside the nucleus in cells, infection by viral genomes also provides an example of extrachromosomal DNA.
== Prokaryotic ==
Although prokaryotic organisms do not possess a membrane-bound nucleus like eukaryotes, they do contain a nucleoid region in which the main chromosome is found. Extrachromosomal DNA exists in prokaryotes outside the nucleoid region as circular or linear plasmids. Bacterial plasmids are typically short sequences, consisting of 1 to a few hundred kilobase (kb) segments, and contain an origin of replication which allows the plasmid to replicate independently of the bacterial chromosome. The total number of a particular plasmid within a cell is referred to as the copy number and can range from as few as two copies per cell to as many as several hundred copies per cell. Circular bacterial plasmids are classified according to the special functions that the genes encoded on the plasmid provide. Fertility plasmids, or f plasmids, allow for conjugation to occur whereas resistance plasmids, or r plasmids, contain genes that convey resistance to a variety of different antibiotics such as ampicillin and tetracycline. Virulence plasmids contain the genetic elements necessary for bacteria to become pathogenic. Degradative plasmids that contain genes that allow bacteria to degrade a variety of substances such as aromatic compounds and xenobiotics. Bacterial plasmids can also function in pigment production, nitrogen fixation and the resistance to heavy metals.
Naturally occurring circular plasmids can be modified to contain multiple resistance genes and several unique restriction sites, making them valuable tools as cloning vectors in biotechnology. Circular bacterial plasmids are also the basis for the production of DNA vaccines. Plasmid DNA vaccines are genetically engineered to contain a gene which encodes for an antigen or a protein produced by a pathogenic virus, bacterium or other parasites. Once delivered into the host, the products of the plasmid genes will then stimulate both the innate immune response and the adaptive immune response of the host. The plasmids are often coated with some type of adjuvant prior to delivery to enhance the immune response from the host.
Linear bacterial plasmids have been identified in several species of spirochete bacteria, including members of the genus Borrelia (to which the pathogen responsible for Lyme disease belongs), several species of the gram positive soil bacteria of the genus Streptomyces, and in the gram negative species Thiobacillus versutus, a bacterium that oxidizes sulfur. Linear plasmids of prokaryotes are found either containing a hairpin loop or a covalently bonded protein attached to the telomeric ends of the DNA molecule. The adenine-thymine rich hairpin loops of the Borrelia bacteria range in size from 5 kilobase pairs (kb) to over 200 kb and contain the genes responsible for producing a group of major surface proteins, or antigens, on the bacteria that allow it to evade the immune response of its infected host. The linear plasmids which contain a protein that has been covalently attached to the 5’ end of the DNA strands are known as invertrons and can range in size from 9 kb to over 600 kb consisting of inverted terminal repeats. The linear plasmids with a covalently attached protein may assist with bacterial conjugation and integration of the plasmids into the genome. These types of linear plasmids represent the largest class of extrachromosomal DNA as they are not only present in certain bacterial cells, but all linear extrachromosomal DNA molecules found in eukaryotic cells also take on this invertron structure with a protein attached to the 5’ end.
The long, linear "borgs" that co-occur with a species of archaeon – which may host them and shares many of their genes – could be an unknown form of extrachromosomal DNA structures.
== Eukaryotic ==
=== Mitochondrial ===
Mitochondria present in eukaryotic cells contain multiple copies of mitochondrial DNA (mtDNA) in the mitochondrial matrix. In multicellular animals, including humans, the circular mtDNA chromosome contains 13 genes that encode proteins that are part of the electron transport chain and 24 genes for mitochondrial RNAs; these genes are broken down into 2 rRNA genes and 22 tRNA genes. The size of an animal mtDNA plasmid is roughly 16.6 kb and, although it contains genes for tRNA and mRNA synthesis, proteins coded for by nuclear genes are still required for the mtDNA to replicate or for mitochondrial proteins to be translated. There is only one region of the mitochondrial chromosome that does not contain a coding sequence, the 1 kb region known as the D-loop to which nuclear regulatory proteins bind. The number of mtDNA molecules per mitochondrion varies from species to species, as well as between cells with different energy demands. For example, muscle and liver cells contain more copies of mtDNA per mitochondrion than blood and skin cells do. Due to the proximity of the electron transport chain within the mitochondrial inner membrane and the production of reactive oxygen species (ROS), and due to the fact that the mtDNA molecule is not bound by or protected by histones, the mtDNA is more susceptible to DNA damage than nuclear DNA. In cases where mtDNA damage does occur, the DNA can either be repaired via base excision repair pathways, or the damaged mtDNA molecule is destroyed (without causing damage to the mitochondrion since there are multiple copies of mtDNA per mitochondrion).
The standard genetic code by which nuclear genes are translated is universal, meaning that each 3-base sequence of DNA codes for the same amino acid regardless of what species from which the DNA comes. However, this code is quite universal and is slightly different in mitochondrial DNA of fungi, animals, protists and plants. While most of the 3-base sequences (codons) in the mtDNA of these organisms do code for the same amino acids as those of the nuclear genetic code, a few are different.
The coding differences are thought to be a result of chemical modifications in the transfer RNAs that interact with the messenger RNAs produced as a result of transcribing the mtDNA sequences.
=== Chloroplast ===
Eukaryotic chloroplasts, as well as the other plant plastids, also contain extrachromosomal DNA molecules. Most chloroplasts house all of their genetic material in a single ringed chromosome, however in some species there is evidence of multiple smaller ringed plasmids. A recent theory that questions the current standard model of ring shaped chloroplast DNA (cpDNA), suggests that cpDNA may more commonly take a linear shape. A single molecule of cpDNA can contain anywhere from 100 to 200 genes and varies in size from species to species. The size of cpDNA in higher plants is around 120–160 kb. The genes found on the cpDNA code for mRNAs that are responsible for producing necessary components of the photosynthetic pathway as well as coding for tRNAs, rRNAs, RNA polymerase subunits, and ribosomal protein subunits. Like mtDNA, cpDNA is not fully autonomous and relies upon nuclear gene products for replication and production of chloroplast proteins. Chloroplasts contain multiple copies of cpDNA and the number can vary not only from species to species or cell type to cell type, but also within a single cell depending upon the age and stage of development of the cell. For example, cpDNA content in the chloroplasts of young cells, during the early stages of development where the chloroplasts are in the form of indistinct proplastids, are much higher than those present when that cell matures and expands, containing fully mature plastids.
=== Circular ===
Extrachromosomal circular DNA (eccDNA) are present in all eukaryotic cells, are usually derived from genomic DNA, and consist of repetitive sequences of DNA found in both coding and non-coding regions of chromosomes. EccDNA can vary in size from less than 2000 base pairs to more than 20,000 base pairs. In plants, eccDNA contain repeated sequences similar to those that are found in the centromeric regions of the chromosomes and in repetitive satellite DNA. In animals, eccDNA molecules have been shown to contain repetitive sequences that are seen in satellite DNA, 5S ribosomal DNA and telomere DNA. Certain organisms, such as yeast, rely on chromosomal DNA replication to produce eccDNA whereas eccDNA formation can occur in other organisms, such as mammals, independently of the replication process. The function of eccDNA have not been widely studied, but it has been proposed that the production of eccDNA elements from genomic DNA sequences add to the plasticity of the eukaryotic genome and can influence genome stability, cell aging and the evolution of chromosomes.
A distinct type of extrachromosomal DNA, denoted as ecDNA, is commonly observed in human cancer cells. ecDNA found in cancer cells contain one or more genes that confer a selective advantage. ecDNA are much larger than eccDNA, and are visible by light microscopy. ecDNA in cancers generally range in size from 1-3 MB and beyond. Large ecDNA molecules have been found in the nuclei of human cancer cells and are shown to carry many copies of driver oncogenes, which are transcribed in tumor cells. Based on this evidence it is thought that ecDNA contributes to cancer growth.
Specialized tools exist that allow ecDNA to be identified, such as
software developed by Paul Mischel and Vineet Bafna that allows ecDNA to be identified in microscopic images
"Circle-Seq, a method for physically isolating ecDNA from cells, removing any remaining linear DNA with enzymes, and sequencing the circular DNA that remains", developed by Birgitte Regenberg and her team at the University of Copenhagen.
== Viral ==
Viral DNA are an example of extrachromosomal DNA. Understanding viral genomes is very important for understanding the evolution and mutation of the virus. Some viruses, such as HIV and oncogenic viruses, incorporate their own DNA into the genome of the host cell. Viral genomes can be made up of single stranded DNA (ssDNA), double stranded DNA (dsDNA) and can be found in both linear and circular form.
One example of infection of a virus constituting as extrachromosomal DNA is the human papillomavirus (HPV). The HPV DNA genome undergoes three distinct stages of replication: establishment, maintenance and amplification. HPV infects epithelial cells in the anogenital tract and oral cavity. Normally, HPV is detected and cleared by the immune system. The recognition of viral DNA is an important part of immune responses. For this virus to persist, the circular genome must be replicated and inherited during cell division.
=== Recognition by host cell ===
Cells can recognize foreign cytoplasmic DNA. Understanding the recognition pathways has implications towards prevention and treatment of diseases. Cells have sensors that can specifically recognize viral DNA such as the Toll-like receptor (TLR) pathway.
The Toll Pathway was recognized, first in insects, as a pathway that allows certain cell types to act as sensors capable of detecting a variety of bacterial or viral genomes and PAMPS (pathogen-associated molecular patterns). PAMPs are known to be potent activators of innate immune signaling. There are approximately 10 human Toll-Like Receptors (TLRs). Different TLRs in human detect different PAMPS: lipopolysaccharides by TLR4, viral dsRNA by TLR3, viral ssRNA by TLR7/TLR8, viral or bacterial unmethylated DNA by TLR9. TLR9 has evolved to detect CpG DNA commonly found in bacteria and viruses and to initiate the production of IFN (type I interferons ) and other cytokines.
== Inheritance ==
Inheritance of extrachromosomal DNA differs from the inheritance of nuclear DNA found in chromosomes. Unlike chromosomes, ecDNA does not contain centromeres and therefore exhibits a non-Mendelian inheritance pattern that gives rise to heterogeneous cell populations. In humans, virtually all of the cytoplasm is inherited from the egg of the mother. For this reason, organelle DNA, including mtDNA, is inherited from the mother. Mutations in mtDNA or other cytoplasmic DNA will also be inherited from the mother. This uniparental inheritance is an example of non-Mendelian inheritance. Plants also show uniparental mtDNA inheritance. Most plants inherit mtDNA maternally with one noted exception being the redwood Sequoia sempervirens that inherit mtDNA paternally.
There are two theories why the paternal mtDNA is rarely transmitted to the offspring. One is simply the fact that paternal mtDNA is at such a lower concentration than the maternal mtDNA and thus it is not detectable in the offspring. A second, more complex theory, involves the digestion of the paternal mtDNA to prevent its inheritance. It is theorized that the uniparental inheritance of mtDNA, which has a high mutation rate, might be a mechanism to maintain the homoplasmy of cytoplasmic DNA.
== Clinical significance ==
Sometimes called EEs, extrachromosomal elements, have been associated with genomic instability in eukaryotes. Small polydispersed DNAs (spcDNAs), a type of eccDNA, are commonly found in conjunction with genome instability. SpcDNAs are derived from repetitive sequences such as satellite DNA, retrovirus-like DNA elements, and transposable elements in the genome. They are thought to be the products of gene rearrangements.
Extrachromosomal DNA (ecDNA) found in cancer have historically been referred to as Double minute chromosomes (DMs), which present as paired chromatin bodies under light microscopy. Double minute chromosomes represent ~30% of the cancer-containing spectrum of ecDNA, including single bodies and have been found to contain identical gene content as single bodies. The ecDNA notation encompasses all forms of the large, oncogene-containing, extrachromosomal DNA found in cancer cells. This type of ecDNA is commonly seen in cancer cells of various histologies, but virtually never in normal cells. ecDNA are thought to be produced through double-strand breaks in chromosomes or over-replication of DNA in an organism. Studies show that in cases of cancer and other genomic instability, higher levels of EEs can be observed.
Mitochondrial DNA can play a role in the onset of disease in a variety of ways. Point mutations in or alternative gene arrangements of mtDNA have been linked to several diseases that affect the heart, central nervous system, endocrine system, gastrointestinal tract, eye, and kidney. Loss of the amount of mtDNA present in the mitochondria can lead to a whole subset of diseases known as mitochondrial depletion syndromes (MDDs) which affect the liver, central and peripheral nervous systems, smooth muscle and hearing in humans. There have been mixed, and sometimes conflicting, results in studies that attempt to link mtDNA copy number to the risk of developing certain cancers. Studies have been conducted that show an association between both increased and decreased mtDNA levels and the increased risk of developing breast cancer. A positive association between increased mtDNA levels and an increased risk for developing kidney tumors has been observed but there does not appear to be a link between mtDNA levels and the development of stomach cancer.
Extrachromosomal DNA is found in Apicomplexa, which is a group of protozoa. The malaria parasite (genus Plasmodium), the AIDS-related pathogen (Taxoplasma and Cryptosporidium) are both members of the Apicomplexa group. Mitochondrial DNA (mtDNA) was found in the malaria parasite. There are two forms of extrachromosomal DNA found in the malaria parasites. One of these is 6-kb linear DNA and the second is 35-kb circular DNA. These DNA molecules have been researched as potential nucleotide target sites for antibiotics.
== Role of ecDNA in cancer ==
Gene amplification is among the most common mechanisms of oncogene activation. Gene amplifications in cancer are often on extrachromosomal, circular elements. One of the primary functions of ecDNA in cancer is to enable the tumor to rapidly reach high copy numbers, while also promoting rapid, massive cell-to-cell genetic heterogeneity. The most commonly amplified oncogenes in cancer are found on ecDNA and have been shown to be highly dynamic, re-integrating into non-native chromosomes as homogeneous staining regions (HSRs) and altering copy numbers and composition in response to various drug treatments.
ecDNA is responsible for a large number of the more advanced and most serious cancers, as well as for the resistance to anti-cancer drugs.
The circular shape of ecDNA differs from the linear structure of chromosomal DNA in meaningful ways that influence cancer pathogenesis. Oncogenes encoded on ecDNA have massive transcriptional output, ranking in the top 1% of genes in the entire transcriptome. In contrast to bacterial plasmids or mitochondrial DNA, ecDNA are chromatinized, containing high levels of active histone marks, but a paucity of repressive histone marks. The ecDNA chromatin architecture lacks the higher-order compaction that is present on chromosomal DNA and is among the most accessible DNA in the entire cancer genome.
EcDNAs could be clustered together within the nucleus, which can be referred to as ecDNA hubs. Spacially, ecDNA hubs could cause intermolecular enhancer–gene interactions to promote oncogene overexpression.
== References ==
== Further reading == | Wikipedia/EcDNA |
In genetics, the mutation rate is the frequency of new mutations in a single gene, nucleotide sequence, or organism over time. Mutation rates are not constant and are not limited to a single type of mutation; there are many different types of mutations. Mutation rates are given for specific classes of mutations. Point mutations are a class of mutations which are changes to a single base. Missense, nonsense, and synonymous mutations are three subtypes of point mutations. The rate of these types of substitutions can be further subdivided into a mutation spectrum which describes the influence of the genetic context on the mutation rate.
There are several natural units of time for each of these rates, with rates being characterized either as mutations per base pair per cell division, per gene per generation, or per genome per generation. The mutation rate of an organism is an evolved characteristic and is strongly influenced by the genetics of each organism, in addition to strong influence from the environment. The upper and lower limits to which mutation rates can evolve is the subject of ongoing investigation. However, the mutation rate does vary over the genome.
When the mutation rate in humans increases certain health risks can occur, for example, cancer and other hereditary diseases. Having knowledge of mutation rates is vital to understanding the future of cancers and many hereditary diseases.
== Background ==
Different genetic variants within a species are referred to as alleles, therefore a new mutation can create a new allele. In population genetics, each allele is characterized by a selection coefficient, which measures the expected change in an allele's frequency over time. The selection coefficient can either be negative, corresponding to an expected decrease, positive, corresponding to an expected increase, or zero, corresponding to no expected change. The distribution of fitness effects of new mutations is an important parameter in population genetics and has been the subject of extensive investigation. Although measurements of this distribution have been inconsistent in the past, it is now generally thought that the majority of mutations are mildly deleterious, that many have little effect on an organism's fitness, and that a few can be favorable.
Because of natural selection, unfavorable mutations will typically be eliminated from a population while favorable changes are generally kept for the next generation, and neutral changes accumulate at the rate they are created by mutations. This process happens by reproduction. In a particular generation the 'best fit' survive with higher probability, passing their genes to their offspring. The sign of the change in this probability defines mutations to be beneficial, neutral or harmful to organisms.
== Measurement ==
An organism's mutation rates can be measured by a number of techniques.
One way to measure the mutation rate is by the fluctuation test, also known as the Luria–Delbrück experiment. This experiment demonstrated that bacteria mutations occur in the absence of selection instead of the presence of selection.
This is very important to mutation rates because it proves experimentally mutations can occur without selection being a component—in fact, mutation and selection are completely distinct evolutionary forces. Different DNA sequences can have different propensities to mutation (see below) and may not occur randomly.
The most commonly measured class of mutations are substitutions, because they are relatively easy to measure with standard analyses of DNA sequence data. However substitutions have a substantially different rate of mutation (10−8 to 10−9 per generation for most cellular organisms) than other classes of mutation, which are frequently much higher (~10−3 per generation for satellite DNA expansion/contraction).
=== Substitution rates ===
Many sites in an organism's genome may admit mutations with small fitness effects. These sites are typically called neutral sites. Theoretically mutations under no selection become fixed between organisms at precisely the mutation rate. Fixed synonymous mutations, i.e. synonymous substitutions, are changes to the sequence of a gene that do not change the protein produced by that gene. They are often used as estimates of that mutation rate, despite the fact that some synonymous mutations have fitness effects. As an example, mutation rates have been directly inferred from the whole genome sequences of experimentally evolved replicate lines of Escherichia coli B.
=== Mutation accumulation lines ===
A particularly labor-intensive way of characterizing the mutation rate is the mutation accumulation line.
Mutation accumulation lines have been used to characterize mutation rates with the Bateman-Mukai Method and direct sequencing of well-studied experimental organisms ranging from intestinal bacteria (E. coli), roundworms (C. elegans), yeast (S. cerevisiae), fruit flies (D. melanogaster), and small ephemeral plants (A. thaliana).
== Variation in mutation rates ==
Mutation rates differ between species and even between different regions of the genome of a single species. Mutation rates can also differ even between genotypes of the same species; for example, bacteria have been observed to evolve hypermutability as they adapt to new selective conditions. These different rates of nucleotide substitution are measured in substitutions (fixed mutations) per base pair per generation. For example, mutations in intergenic, or non-coding, DNA tend to accumulate at a faster rate than mutations in DNA that is actively in use in the organism (gene expression). That is not necessarily due to a higher mutation rate, but to lower levels of purifying selection. A region which mutates at predictable rate is a candidate for use as a molecular clock.
If the rate of neutral mutations in a sequence is assumed to be constant (clock-like), and if most differences between species are neutral rather than adaptive, then the number of differences between two different species can be used to estimate how long ago two species diverged (see molecular clock). In fact, the mutation rate of an organism may change in response to environmental stress. For example, UV light damages DNA, which may result in error prone attempts by the cell to perform DNA repair.
The human mutation rate is higher in the male germ line (sperm) than the female (egg cells), but estimates of the exact rate have varied by an order of magnitude or more. This means that a human genome accumulates around 64 new mutations per generation because each full generation involves a number of cell divisions to generate gametes. Human mitochondrial DNA has been estimated to have mutation rates of ~3× or ~2.7×10−5 per base per 20 year generation (depending on the method of estimation); these rates are considered to be significantly higher than rates of human genomic mutation at ~2.5×10−8 per base per generation. Using data available from whole genome sequencing, the human genome mutation rate is similarly estimated to be ~1.1×10−8 per site per generation.
The rate for other forms of mutation also differs greatly from point mutations. An individual microsatellite locus often has a mutation rate on the order of 10−4, though this can differ greatly with length.
Some sequences of DNA may be more susceptible to mutation. For example, stretches of DNA in human sperm which lack methylation are more prone to mutation.
In general, the mutation rate in unicellular eukaryotes (and bacteria) is roughly 0.003 mutations per genome per cell generation. However, some species, especially the ciliate of the genus Paramecium have an unusually low mutation rate. For instance, Paramecium tetraurelia has a base-substitution mutation rate of ~2 × 10−11 per site per cell division. This is the lowest mutation rate observed in nature so far, being about 75× lower than in other eukaryotes with a similar genome size, and even 10× lower than in most prokaryotes. The low mutation rate in Paramecium has been explained by its transcriptionally silent germ-line nucleus, consistent with the hypothesis that replication fidelity is higher at lower gene expression levels.
The highest per base pair per generation mutation rates are found in viruses, which can have either RNA or DNA genomes. DNA viruses have mutation rates between 10−6 to 10−8 mutations per base per generation, and RNA viruses have mutation rates between 10−3 to 10−5 per base per generation.
== Mutation spectrum ==
A mutation spectrum is a distribution of rates or frequencies for the mutations relevant in some context, based on the recognition that rates of occurrence are not all the same. In any context, the mutation spectrum reflects the details of mutagenesis and is affected by conditions such as the presence of chemical mutagens or genetic backgrounds with mutator alleles or damaged DNA repair systems. The most fundamental and expansive concept of a mutation spectrum is the distribution of rates for all individual mutations that might happen in a genome (e.g., ). From this full de novo spectrum, for instance, one may calculate the relative rate of mutation in coding vs non-coding regions. Typically the concept of a spectrum of mutation rates is simplified to cover broad classes such as transitions and transversions (figure), i.e., different mutational conversions across the genome are aggregated into classes, and there is an aggregate rate for each class.
In many contexts, a mutation spectrum is defined as the observed frequencies of mutations identified by some selection criterion, e.g., the distribution of mutations associated clinically with a particular type of cancer, or the distribution of adaptive changes in a particular context such as antibiotic resistance (e.g.,
).
Whereas the spectrum of de novo mutation rates reflects mutagenesis alone, this kind of spectrum may also reflect effects of selection and ascertainment biases (e.g., both kinds of spectrum are used in ).
== Evolution ==
The theory on the evolution of mutation rates identifies three principal forces involved: the generation of more deleterious mutations with higher mutation, the generation of more advantageous mutations with higher mutation, and the metabolic costs and reduced replication rates that are required to prevent mutations. Different conclusions are reached based on the relative importance attributed to each force. The optimal mutation rate of organisms may be determined by a trade-off between costs of a high mutation rate, such as deleterious mutations, and the metabolic costs of maintaining systems to reduce the mutation rate (such as increasing the expression of DNA repair enzymes. or, as reviewed by Bernstein et al. having increased energy use for repair, coding for additional gene products and/or having slower replication). Secondly, higher mutation rates increase the rate of beneficial mutations, and evolution may prevent a lowering of the mutation rate in order to maintain optimal rates of adaptation. As such, hypermutation enables some cells to rapidly adapt to changing conditions in order to avoid the entire population from becoming extinct. Finally, natural selection may fail to optimize the mutation rate because of the relatively minor benefits of lowering the mutation rate, and thus the observed mutation rate is the product of neutral processes.
Studies have shown that treating RNA viruses such as poliovirus with ribavirin produce results consistent with the idea that the viruses mutated too frequently to maintain the integrity of the information in their genomes. This is termed error catastrophe.
The characteristically high mutation rate of HIV (Human Immunodeficiency Virus) of 3 x 10−5 per base and generation, coupled with its short replication cycle leads to a high antigen variability, allowing it to evade the immune system.
== See also ==
Mutation
Critical mutation rate
Mutation frequency
Dysgenics
Allele frequency
Rate of evolution
Genetics
Cancer
== References ==
== External links ==
Media related to Mutation rate at Wikimedia Commons | Wikipedia/Mutation_rate |
Satellite DNA consists of very large arrays of tandemly repeating, non-coding DNA. Satellite DNA is the main component of functional centromeres, and form the main structural constituent of heterochromatin.
The name "satellite DNA" refers to the phenomenon that repetitions of a short DNA sequence tend to produce a different frequency of the bases adenine, cytosine, guanine, and thymine, and thus have a different density from bulk DNA such that they form a second or "satellite" band(s) when genomic DNA is separated along a cesium chloride density gradient using buoyant density centrifugation.
Sequences with a greater ratio of A+T display a lower density while those with a greater ratio of G+C display a higher density than the bulk of genomic DNA. Some repetitive sequences are ~50% G+C/A+T and thus have buoyant densities the same as bulk genomic DNA. These satellites are called "cryptic" satellites because they form a band hidden within the main band of genomic DNA. "Isopycnic" is another term used for cryptic satellites.
== Satellite DNA families in humans ==
Satellite DNA, together with minisatellite and microsatellite DNA, constitute the tandem repeats. The size of satellite DNA arrays varies greatly between individuals.
The major satellite DNA families in humans are called:
== Length ==
A repeated pattern can be between 1 base pair (bp) long (a mononucleotide repeat) to several thousand base pairs long, and the total size of a satellite DNA block can be several megabases without interruption. Long repeat units have been described containing domains of shorter repeated segments and mononucleotides (1-5 bp), arranged in clusters of microsatellites, wherein differences among individual copies of the longer repeat units were clustered. Most satellite DNA is localized to the telomeric or the centromeric region of the chromosome. The nucleotide sequence of the repeats is fairly well conserved across species. However, variation in the length of the repeat is common.
Low-resolution sequencing-based studies have demonstrated variation in human population satellite array lengths as well as in the frequency of certain sequence and structural variations (11–13, 29). However, due to a lack of full centromere assemblies, base-level understanding of satellite array variation and evolution has remained weak. For example, minisatellite DNA is a short region (1-5 kb) of repeating elements with length >9 nucleotides. Whereas microsatellites in DNA sequences are considered to have a length of 1-8 nucleotides. The difference in how many of the repeats is present in the region (length of the region) is the basis for DNA profiling.
== Origin ==
Microsatellites are thought to have originated by polymerase slippage during DNA replication. This comes from the observation that microsatellite alleles usually are length polymorphic; specifically, the length differences observed between microsatellite alleles are generally multiples of the repeat unit length.
== Structure ==
Satellite DNA adopts higher-order three-dimensional structures in a naturally occurring complex satellite DNA from the land crab Gecarcinus lateralis, whose genome contains 3% of a GC-rich satellite band consisting of a ~2100 bp "repeat unit" sequence motif called RU. The RU was arranged in long tandem arrays with approximately 16,000 copies per genome. Several RU sequences were cloned and sequenced to reveal conserved regions of conventional DNA sequences over stretches greater than 550 bp, interspersed with five "divergent domains" within each copy of RU.
Four divergent domains consisted of microsatellite repeats, biased in base composition, with purines on one strand and pyrimidines on the other. Some contained mononucleotide repeats of C:G base pairs approximately 20 bp in length. These strand-biased microsatellite domains ranged in length from approximately 20 bp to greater than 250 bp. The most prevalent repeated sequences in the embedded microsatellite regions were CT:AG, CCT:AGG, CCCT:AGGG, and CGCAC:GTGCG These repeating sequences were shown to adopt altered structures including triple-stranded DNA, Z-DNA, stem-loop, and other conformations under superhelical stress.
Between the strand-biased microsatellite repeats and C:G mononucleotide repeats, all sequence variations retained one or two base pairs with A (purine) interrupting the pyrimidine-rich strand and T (pyrimidine) interrupting the purine-rich strand. These interruptions in compositional bias adopted highly distorted conformations as shown by their response to structrural nuclease enzymes including S1, P1, and mung bean nucleases.
The most complex compositionally-biased microsatellite domain of RU included the sequence TTAA:TTAA as well as a mirror repeat. It produced the strongest signal in response to nucleases compared to all other altered structures in experimental observations. That particular strand-biased divergent domain was subcloned and its altered helical structure was studied in greater detail.
A fifth divergent domain in the RU sequence was characterized by variations of a symmetrical DNA sequence motif of alternating purines and pyrimidines shown to adopt a left-handed Z-DNA or stem-loop structure under superhelical stress. The conserved symmetrical Z-DNA was abbreviated Z4Z5NZ15NZ5Z4, where Z represents alternating purine/pyrimidine sequences. A stem-loop structure was centered in the Z15 element at the highly conserved palindromic sequence CGCACGTGCG:CGCACGTGCG and was flanked by extended palindromic Z-DNA sequences over a 35 bp region. Many RU variants showed deletions of at least 10 bp outside the Z4Z5NZ15NZ5Z4 structural element, while others had additional Z-DNA sequences lengthening the alternating purine and pyrimidine domain to over 50 bp.
One extended RU sequence (EXT) was shown to have six tandem copies of a 142 bp amplified (AMPL) sequence motif inserted into a region bordered by inverted repeats where most copies contained just one AMPL sequence element. There were no nuclease-sensitive altered structures or significant sequence divergence in the relatively conventional AMPL sequence. A truncated RU sequence (TRU), 327 bp shorter than most clones, arose from a single base change leading to a second EcoRI restriction site in TRU.
Another crab, the hermit crab Pagurus pollicaris, was shown to have a family of AT-rich satellites with inverted repeat structures that comprised 30% of the entire genome. Another cryptic satellite from the same crab with the sequence CCTA:TAGG
was found inserted into some of the palindromes.
== See also ==
Buoyant density centrifugation
DNA profiling
DNA supercoil
Eukaryotic chromosome fine structure
Gene expression
Polymerase chain reaction
Tengiz Beridze, scientist who discovered satellite DNA in plants
== References ==
== Further reading ==
Beridze, Thengiz (1986). Satellite DNA. Springer-Verlag. ISBN 978-0-387-15876-1.
Hoy, Marjorie A. (2003). Insect molecular genetics: an introduction to principles and applications. Academic Press. p. 53. ISBN 978-0-12-357031-4.
== External links ==
Satellite+DNA at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
Search tools:
SERF De Novo Genome Analysis and Tandem Repeats Finder
TRF Tandem Repeats Finder | Wikipedia/Satellite_DNA |
Mitochondrial DNA (mtDNA and mDNA) is the DNA located in the mitochondria organelles in a eukaryotic cell that converts chemical energy from food into adenosine triphosphate (ATP). Mitochondrial DNA is a small portion of the DNA contained in a eukaryotic cell; most of the DNA is in the cell nucleus, and, in plants and algae, the DNA also is found in plastids, such as chloroplasts. Mitochondrial DNA is responsible for coding of 13 essential subunits of the complex oxidative phosphorylation (OXPHOS) system which has a role in cellular energy conversion.
Human mitochondrial DNA was the first significant part of the human genome to be sequenced. This sequencing revealed that human mtDNA has 16,569 base pairs and encodes 13 proteins. As in other vertebrates, the human mitochondrial genetic code differs slightly from nuclear DNA.
Since animal mtDNA evolves faster than nuclear genetic markers, it represents a mainstay of phylogenetics and evolutionary biology. It also permits tracing the relationships of populations, and so has become important in anthropology and biogeography.
== Origin ==
Nuclear and mitochondrial DNA are thought to have separate evolutionary origins, with the mtDNA derived from the circular genomes of bacteria engulfed by the ancestors of modern eukaryotic cells. This theory is called the endosymbiotic theory. In the cells of extant organisms, the vast majority of the proteins in the mitochondria (numbering approximately 1500 different types in mammals) are coded by nuclear DNA, but the genes for some, if not most, of them are thought to be of bacterial origin, having been transferred to the eukaryotic nucleus during evolution.
The reasons mitochondria have retained some genes are debated. The existence in some species of mitochondrion-derived organelles lacking a genome suggests that complete gene loss is possible, and transferring mitochondrial genes to the nucleus has several advantages. The difficulty of targeting remotely produced hydrophobic protein products to the mitochondrion is one hypothesis for why some genes are retained in mtDNA; colocalisation for redox regulation is another, citing the desirability of localised control over mitochondrial machinery. Recent analysis of a wide range of mtDNA genomes suggests that both these features may dictate mitochondrial gene retention.
== Genome structure and diversity ==
Across all organisms, there are six main mitochondrial genome types, classified by structure (i.e. circular versus linear), size, presence of introns or plasmid like structures, and whether the genetic material is a singular molecule or collection of homogeneous or heterogeneous molecules.
In many unicellular organisms (e.g., the ciliate Tetrahymena and the green alga Chlamydomonas reinhardtii), and in rare cases also in multicellular organisms (e.g. in some species of Cnidaria), the mtDNA is linear DNA. Most of these linear mtDNAs possess telomerase-independent telomeres (i.e., the ends of the linear DNA) with different modes of replication, which have made them interesting objects of research because many of these unicellular organisms with linear mtDNA are known pathogens.
=== Animals ===
Most (bilaterian) animals have a circular mitochondrial genome. Medusozoa and calcarea clades however include species with linear mitochondrial chromosomes. With a few exceptions, animals have 37 genes in their mitochondrial DNA: 13 for proteins, 22 for tRNAs, and 2 for rRNAs.
Mitochondrial genomes for animals average about 16,000 base pairs in length. The anemone Isarachnanthus nocturnus has the largest mitochondrial genome of any animal at 80,923 bp. The smallest known mitochondrial genome in animals belongs to the comb jelly Vallicula multiformis, which consist of 9,961 bp.
In February 2020, a jellyfish-related parasite – Henneguya salminicola – was discovered that lacks a mitochondrial genome but retains structures deemed mitochondrion-related organelles. Moreover, nuclear DNA genes involved in aerobic respiration and mitochondrial DNA replication and transcription were either absent or present only as pseudogenes. This is the first multicellular organism known to have this absence of aerobic respiration and live completely free of oxygen dependency.
=== Plants and fungi ===
There are three different mitochondrial genome types in plants and fungi. The first type is a circular genome that has introns (type 2) and may range from 19 to 1000 kbp in length. The second genome type is a circular genome (about 20–1000 kbp) that also has a plasmid-like structure (1 kb) (type 3). The final genome type found in plants and fungi is a linear genome made up of homogeneous DNA molecules (type 5).
Great variation in mtDNA gene content and size exists among fungi and plants, although there appears to be a core subset of genes present in all eukaryotes (except for the few that have no mitochondria at all). In Fungi, however, there is no single gene shared among all mitogenomes.
Some plant species have enormous mitochondrial genomes, with Silene conica mtDNA containing as many as 11,300,000 base pairs. Surprisingly, even those huge mtDNAs contain the same number and kinds of genes as related plants with much smaller mtDNAs.
The genome of the mitochondrion of the cucumber (Cucumis sativus) consists of three circular chromosomes (lengths 1556, 84 and 45 kilobases), which are entirely or largely autonomous with regard to their replication.
=== Protists ===
Protists contain the most diverse mitochondrial genomes, with five different types found in this kingdom. Type 2, type 3, and type 5 of the plant and fungal genomes also exist in some protists, as do two unique genome types. One of these unique types is a heterogeneous collection of circular DNA molecules (type 4) while the other is a heterogeneous collection of linear molecules (type 6). Genome types 4 and 6 each range from 1–200 kbp in size.
The smallest mitochondrial genome sequenced to date is the 5,967 bp mtDNA of the parasite Plasmodium falciparum.
Endosymbiotic gene transfer, the process by which genes that were coded in the mitochondrial genome are transferred to the cell's main genome, likely explains why more complex organisms such as humans have smaller mitochondrial genomes than simpler organisms such as protists.
== Replication ==
The two strands of the human mitochondrial DNA are distinguished as the heavy strand and the light strand. The regulation of mitochondrial DNA replication and transcription initiation is located in a single intergenic noncoding region (NCR). In human, the 1,100 base pairs NCR region contains three promoters of two L-strand promoters (LSP and LSP2) and one H-strand promoter (HSP). Unlike bidirectional and specific origin initiation of nuclear DNA replication, mitochondrial DNA has two strand-specific, unidirectional origins of replication of the leading H strand (OH) which located in NCR and the lagging L strand (OL) which located in the tRNA gene cluster.
Mitochondrial DNA is replicated by the DNA polymerase gamma complex which is composed of a 140 kDa catalytic DNA polymerase encoded by the POLG gene and two 55 kDa accessory subunits encoded by the POLG2 gene. The replisome machinery is formed by DNA polymerase, TWINKLE and mitochondrial SSB proteins. TWINKLE is a helicase, which unwinds short stretches of dsDNA in the 5' to 3' direction. All these polypeptides are encoded in the nuclear genome.
During embryogenesis, replication of mtDNA is strictly down-regulated from the fertilized oocyte through the preimplantation embryo. The resulting reduction in per-cell copy number of mtDNA plays a role in the mitochondrial bottleneck, exploiting cell-to-cell variability to ameliorate the inheritance of damaging mutations. According to Justin St. John and colleagues, "At the blastocyst stage, the onset of mtDNA replication is specific to the cells of the trophectoderm. In contrast, the cells of the inner cell mass restrict mtDNA replication until they receive the signals to differentiate to specific cell types."
== DNA repair ==
Although several DNA repair pathways have been reported to occur in the mitochondria, currently the base excision repair pathway is the pathway most comprehensively described. Proteins that are employed in the maintenance of mitochondrial DNA are encoded by nuclear genes and translocated to the mitochondria. The mitochondria of human cells are capable of repairing DNA base pair mismatches by a pathway that is distinct from the DNA mismatch repair pathway of the nucleus. This distinct mitochondrial pathway includes the activity of the Y box binding protein 1 (designated YB-1 or YBX1), that likely acts in the mismatch binding and recognition steps of mismatch repair. DNA repair mechanisms specific to the mitochondria may reflect the proximity of the mitochondrial DNA to the oxidative phosphorylation system and consequently to the DNA-damaging reactive oxygen species formed during ATP production.
== Genes on the human mtDNA and their transcription ==
The two strands of the human mitochondrial DNA are distinguished as the heavy strand and the light strand. The heavy strand is rich in guanine and encodes 12 subunits of the oxidative phosphorylation system, two ribosomal RNAs (12S and 16S), and 14 transfer RNAs (tRNAs). The light strand encodes one subunit and 8 tRNAs. So, altogether mtDNA encodes for two rRNAs, 22 tRNAs, and 13 protein subunits, all of which are involved in the oxidative phosphorylation process.
The complete sequence of the human mitochondrial DNA in graphic form
Between most (but not all) protein-coding regions, tRNAs are present (see the human mitochondrial genome map). During transcription, the tRNAs acquire their characteristic L-shape that gets recognized and cleaved by specific enzymes. With the mitochondrial RNA processing, individual mRNA, rRNA, and tRNA sequences are released from the primary transcript. Folded tRNAs therefore act as secondary structure punctuations.
Transcription is done by the single-subunit mitochondrial RNA polymerase (POLRMT). In association with two of accessory factors, mitochondrial transcription factor A (TFAM) and mitochondrial transcription factor B2 (TFB2M), the POLRMT complex recognizes promoters and initiates transcription. Transcription resulted in polycistronic transcripts that are processed in discrete mitochondrial RNA granules into individual mRNAs, tRNAs, and rRNAs.
=== Regulation of transcription ===
The promoters for the initiation of the transcription of the heavy and light strands are located in the main non-coding region of the mtDNA called the displacement loop, the D-loop. There is evidence that the transcription of the mitochondrial rRNAs is regulated by the heavy-strand promoter 1 (HSP1), and the transcription of the polycistronic transcripts coding for the protein subunits are regulated by HSP2.
Measurement of the levels of the mtDNA-encoded RNAs in bovine tissues has shown that there are major differences in the expression of the mitochondrial RNAs relative to total tissue RNA. Among the 12 tissues examined the highest level of expression was observed in the heart, followed by brain and steroidogenic tissue samples.
As demonstrated by the effect of the trophic hormone ACTH on adrenal cortex cells, the expression of the mitochondrial genes may be strongly regulated by external factors, apparently to enhance the synthesis of mitochondrial proteins necessary for energy production. Interestingly, while the expression of protein-encoding genes was stimulated by ACTH, the levels of the mitochondrial 16S rRNA showed no significant change.
== Mitochondrial inheritance ==
In most multicellular organisms, mtDNA is inherited from the mother (maternally inherited). Mechanisms for this include simple dilution (an egg contains on average 200,000 mtDNA molecules, whereas a healthy human sperm has been reported to contain on average 5 molecules), degradation of sperm mtDNA in the male genital tract and the fertilized egg; and, at least in a few organisms, failure of sperm mtDNA to enter the egg. Whatever the mechanism, this single parent (uniparental inheritance) pattern of mtDNA inheritance is found in most animals, most plants, and also in fungi.
In a study published in 2018, human babies were reported to inherit mtDNA from both their fathers and their mothers resulting in mtDNA heteroplasmy, a finding that has been rejected by other scientists.
=== Female inheritance ===
In sexual reproduction, mitochondria are normally inherited exclusively from the mother; the mitochondria in mammalian sperm are usually destroyed by the egg cell after fertilization. Also, mitochondria are present solely in the midpiece, which is used for propelling the sperm cells, and sometimes the midpiece, along with the tail, is lost during fertilization. In 1999 it was reported that paternal sperm mitochondria (containing mtDNA) are marked with ubiquitin to select them for later destruction inside the embryo. Some in vitro fertilization techniques, particularly injecting a sperm into an oocyte, may interfere with this.
The fact that mitochondrial DNA is mostly maternally inherited enables genealogical researchers to trace maternal lineage far back in time. (Y-chromosomal DNA, paternally inherited, is used in an analogous way to determine the patrilineal history.) This is usually accomplished on human mitochondrial DNA by sequencing the hypervariable control regions (HVR1 or HVR2), and sometimes the complete molecule of the mitochondrial DNA, as a genealogical DNA test. HVR1, for example, consists of about 440 base pairs. These 440 base pairs are compared to the same regions of other individuals (either specific people or subjects in a database) to determine maternal lineage. Most often, the comparison is made with the revised Cambridge Reference Sequence. Vilà et al. have published studies tracing the matrilineal descent of domestic dogs from wolves.
The concept of the Mitochondrial Eve is based on the same type of analysis, attempting to discover the origin of humanity by tracking the lineage back in time.
=== The mitochondrial bottleneck ===
Entities subject to uniparental inheritance and with little to no recombination may be expected to be subject to Muller's ratchet, the accumulation of deleterious mutations until functionality is lost. Animal populations of mitochondria avoid this through a developmental process known as the mtDNA bottleneck. The bottleneck exploits random processes in the cell to increase the cell-to-cell variability in mutant load as an organism develops: a single egg cell with some proportion of mutant mtDNA thus produces an embryo in which different cells have different mutant loads. Cell-level selection may then act to remove those cells with more mutant mtDNA, leading to a stabilisation or reduction in mutant load between generations. The mechanism underlying the bottleneck is debated, with a recent mathematical and experimental metastudy providing evidence for a combination of the random partitioning of mtDNAs at cell divisions and the random turnover of mtDNA molecules within the cell.
=== Male inheritance ===
Male mitochondrial DNA inheritance has been discovered in Plymouth Rock chickens. Evidence supports rare instances of male mitochondrial inheritance in some mammals as well. Specifically, documented occurrences exist for mice, where the male-inherited mitochondria were subsequently rejected. It has also been found in sheep, and in cloned cattle. Rare cases of male mitochondrial inheritance have been documented in humans. Although many of these cases involve cloned embryos or subsequent rejection of the paternal mitochondria, others document in vivo inheritance and persistence under lab conditions.
Doubly uniparental inheritance of mtDNA is observed in bivalve mollusks. In those species, females have only one type of mtDNA (F), whereas males have F-type mtDNA in their somatic cells, but M-type mtDNA (which can be as much as 30% divergent) in germline cells. Paternally inherited mitochondria have additionally been reported in some insects such as fruit flies, honeybees, and periodical cicadas.
=== Mitochondrial donation ===
An IVF technique known as mitochondrial donation or mitochondrial replacement therapy (MRT) results in offspring containing mtDNA from a donor female, and nuclear DNA from the mother and father. In the spindle transfer procedure, the nucleus of an egg is inserted into the cytoplasm of an egg from a donor female which has had its nucleus removed but still contains the donor female's mtDNA. The composite egg is then fertilized with the male's sperm. The procedure is used when a woman with genetically defective mitochondria wishes to procreate and produce offspring with healthy mitochondria. The first known child to be born as a result of mitochondrial donation was a boy born to a Jordanian couple in Mexico on 6 April 2016.
== Mutations and disease ==
=== Susceptibility ===
The concept that mtDNA is particularly susceptible to reactive oxygen species generated by the respiratory chain due to its proximity remains controversial. mtDNA does not accumulate any more oxidative base damage than nuclear DNA. It has been reported that at least some types of oxidative DNA damage are repaired more efficiently in mitochondria than they are in the nucleus. mtDNA is packaged with proteins which appear to be as protective as proteins of the nuclear chromatin. Moreover, mitochondria evolved a unique mechanism which maintains mtDNA integrity through degradation of excessively damaged genomes followed by replication of intact/repaired mtDNA. This mechanism is not present in the nucleus and is enabled by multiple copies of mtDNA present in mitochondria. The outcome of mutation in mtDNA may be an alteration in the coding instructions for some proteins, which may have an effect on organism metabolism and/or fitness.
=== Genetic illness ===
Mutations of mitochondrial DNA can lead to a number of illnesses including exercise intolerance and Kearns–Sayre syndrome (KSS), which causes a person to lose full function of heart, eye, and muscle movements. Some evidence suggests that they might be major contributors to the aging process and age-associated pathologies. Particularly in the context of disease, the proportion of mutant mtDNA molecules in a cell is termed heteroplasmy. The within-cell and between-cell distributions of heteroplasmy dictate the onset and severity of disease and are influenced by complicated stochastic processes within the cell and during development.
Mutations in mitochondrial tRNAs can be responsible for severe diseases like the MELAS and MERRF syndromes.
Mutations in nuclear genes that encode proteins that mitochondria use can also contribute to mitochondrial diseases. These diseases do not follow mitochondrial inheritance patterns but instead follow Mendelian inheritance patterns.
=== Use in disease diagnosis ===
Recently a mutation in mtDNA has been used to help diagnose prostate cancer in patients with negative prostate biopsy.
mtDNA alterations can be detected in the bio-fluids of patients with cancer. mtDNA is characterized by the high rate of polymorphisms and mutations. Some of these are increasingly recognized as an important cause of human pathology such as oxidative phosphorylation (OXPHOS) disorders, maternally inherited diabetes and deafness (MIDD), Type 2 diabetes mellitus, Neurodegenerative disease, heart failure, and cancer.
=== Relationship with ageing ===
Though the idea is controversial, some evidence suggests a link between aging and mitochondrial genome dysfunction. In essence, mutations in mtDNA upset a careful balance of reactive oxygen species (ROS) production and enzymatic ROS scavenging (by enzymes like superoxide dismutase, catalase, glutathione peroxidase and others). However, some mutations that increase ROS production (e.g., by reducing antioxidant defenses) in worms increase, rather than decrease, their longevity. Also, naked mole rats, rodents about the size of mice, live about eight times longer than mice despite having reduced, compared to mice, antioxidant defenses and increased oxidative damage to biomolecules. Once, there was thought to be a positive feedback loop at work (a 'Vicious Cycle'); as mitochondrial DNA accumulates genetic damage caused by free radicals, the mitochondria lose function and leak free radicals into the cytosol. A decrease in mitochondrial function reduces overall metabolic efficiency. However, this concept was conclusively disproved when it was demonstrated that mice, which were genetically altered to accumulate mtDNA mutations at an accelerated rate to age prematurely, but their tissues do not produce more ROS as predicted by the 'Vicious Cycle' hypothesis. Supporting a link between longevity and mitochondrial DNA, some studies have found correlations between biochemical properties of the mitochondrial DNA and the longevity of species. The application of a mitochondrial-specific ROS scavenger, which lead to a significant longevity of the mice studied, suggests that mitochondria may still be well-implicated in ageing. Extensive research is being conducted to further investigate this link and methods to combat ageing. Presently, gene therapy and nutraceutical supplementation are popular areas of ongoing research. Bjelakovic et al. analyzed the results of 78 studies between 1977 and 2012, involving a total of 296,707 participants, and concluded that antioxidant supplements do not reduce all-cause mortality nor extend lifespan, while some of them, such as beta carotene, vitamin E, and higher doses of vitamin A, may actually increase mortality.
In a recent study, it was shown that dietary restriction can reverse ageing alterations by affecting the accumulation of mtDNA damage in several organs of rats. For example, dietary restriction prevented age-related accumulation of mtDNA damage in the cortex and decreased it in the lung and testis.
=== Neurodegenerative diseases ===
Increased mtDNA damage is a feature of several neurodegenerative diseases.
The brains of individuals with Alzheimer's disease have elevated levels of oxidative DNA damage in both nuclear DNA and mtDNA, but the mtDNA has approximately 10-fold higher levels than nuclear DNA. It has been proposed that aged mitochondria is the critical factor in the origin of neurodegeneration in Alzheimer's disease. Analysis of the brains of AD patients suggested an impaired function of the DNA repair pathway, which would cause reduce the overall quality of mtDNA.
In Huntington's disease, mutant huntingtin protein causes mitochondrial dysfunction involving inhibition of mitochondrial electron transport, higher levels of reactive oxygen species and increased oxidative stress. Mutant huntingtin protein promotes oxidative damage to mtDNA, as well as nuclear DNA, that may contribute to Huntington's disease pathology.
The DNA oxidation product 8-oxoguanine (8-oxoG) is a well-established marker of oxidative DNA damage. In persons with amyotrophic lateral sclerosis (ALS), the enzymes that normally repair 8-oxoG DNA damages in the mtDNA of spinal motor neurons are impaired. Thus oxidative damage to mtDNA of motor neurons may be a significant factor in the etiology of ALS.
=== Correlation of the mtDNA base composition with animal life spans ===
Over the past decade, an Israeli research group led by Professor Vadim Fraifeld has shown that strong and significant correlations exist between the mtDNA base composition and animal species-specific maximum life spans. As demonstrated in their work, higher mtDNA guanine + cytosine content (GC%) strongly associates with longer maximum life spans across animal species. An additional observation is that the mtDNA GC% correlation with the maximum life spans is independent of the well-known correlation between animal species' metabolic rate and maximum life spans. The mtDNA GC% and resting metabolic rate explain the differences in animal species' maximum life spans in a multiplicative manner (i.e., species maximum life span = their mtDNA GC% * metabolic rate). To support the scientific community in carrying out comparative analyses between mtDNA features and longevity across animals, a dedicated database was built named MitoAge.
=== mtDNA mutational spectrum is sensitive to species-specific life-history traits ===
De novo mutations arise either due to mistakes during DNA replication or due to unrepaired damage caused in turn by endogenous and exogenous mutagens. It has been long believed that mtDNA can be particularly sensitive to damage caused by reactive oxygen species (ROS), however, G>T substitutions, the hallmark of the oxidative damage in the nuclear genome, are very rare in mtDNA and do not increase with age. Comparing the mtDNA mutational spectra of hundreds of mammalian species, it has been recently demonstrated that species with extended lifespans have an increased rate of A>G substitutions on single-stranded heavy chains. This discovery led to the hypothesis that A>G is a mitochondria-specific marker of age-associated oxidative damage. This finding provides a mutational (contrary to the selective one) explanation for the observation that long-lived species have GC-rich mtDNA: long-lived species become GC-rich simply because of their biased process of mutagenesis. An association between mtDNA mutational spectrum and species-specific life-history traits in mammals opens a possibility to link these factors together discovering new life-history-specific mutagens in different groups of organisms.
=== Relationship with non-B (non-canonical) DNA structures ===
Deletion breakpoints frequently occur within or near regions showing non-canonical (non-B) conformations, namely hairpins, cruciforms, and cloverleaf-like elements. Moreover, data supports the involvement of helix-distorting intrinsically curved regions and long G-tetrads in eliciting instability events. In addition, higher breakpoint densities were consistently observed within GC-skewed regions and in the close vicinity of the degenerate sequence motif YMMYMNNMMHM.
== Use in forensics ==
Unlike nuclear DNA, which is inherited from both parents and in which genes are rearranged in the process of recombination, there is usually no change in mtDNA from parent to offspring. Although mtDNA also recombines, it does so with copies of itself within the same mitochondrion. Because of this and because the mutation rate of animal mtDNA is higher than that of nuclear DNA, mtDNA is a powerful tool for tracking ancestry through females (matrilineage) and has been used in this role to track the ancestry of many species back hundreds of generations.
mtDNA testing can be used by forensic scientists in cases where nuclear DNA is severely degraded. Autosomal cells only have two copies of nuclear DNA but can have hundreds of copies of mtDNA due to the multiple mitochondria present in each cell. This means highly degraded evidence that would not be beneficial for STR analysis could be used in mtDNA analysis. mtDNA may be present in bones, teeth, or hair, which could be the only remains left in the case of severe degradation. In contrast to STR analysis, mtDNA sequencing uses Sanger sequencing. The known sequence and questioned sequence are both compared to the Revised Cambridge Reference Sequence to generate their respective haplotypes. If the known sample sequence and questioned sequence originated from the same matriline, one would expect to see identical sequences and identical differences from the rCRS. Cases arise where there are no known samples to collect and the unknown sequence can be searched in a database such as EMPOP. The Scientific Working Group on DNA Analysis Methods recommends three conclusions for describing the differences between a known mtDNA sequence and a questioned mtDNA sequence: exclusion for two or more differences between the sequences, inconclusive if there is one nucleotide difference, or inability to exclude if there are no nucleotide differences between the two sequences.
The rapid mutation rate (in animals) makes mtDNA useful for assessing the genetic relationships of individuals or groups within a species and also for identifying and quantifying the phylogeny (evolutionary relationships; see phylogenetics) among different species. To do this, biologists determine and then compare the mtDNA sequences from different individuals or species. Data from the comparisons is used to construct a network of relationships among the sequences, which provides an estimate of the relationships among the individuals or species from which the mtDNAs were taken. mtDNA can be used to estimate the relationship between both closely related and distantly related species. Due to the high mutation rate of mtDNA in animals, the 3rd positions of the codons change relatively rapidly and thus provide information about the genetic distances among closely related individuals or species. On the other hand, the substitution rate of mt-proteins is very low, thus amino acid changes accumulate slowly (with corresponding slow changes at 1st and 2nd codon positions) and thus they provide information about the genetic distances of distantly related species. Statistical models that treat substitution rates among codon positions separately, can thus be used to simultaneously estimate phylogenies that contain both closely and distantly related species
Mitochondrial DNA was admitted into evidence for the first time ever in a United States courtroom in 1996 during State of Tennessee v. Paul Ware.
In the 1998 United States court case of Commonwealth of Pennsylvania v. Patricia Lynne Rorrer, mitochondrial DNA was admitted into evidence in the State of Pennsylvania for the first time. The case was featured in episode 55 of season 5 of the true crime drama series Forensic Files (season 5).
Mitochondrial DNA was first admitted into evidence in California, United States, in the successful prosecution of David Westerfield for the 2002 kidnapping and murder of 7-year-old Danielle van Dam in San Diego: it was used for both human and dog identification. This was the first trial in the U.S. to admit canine DNA.
The remains of King Richard III, who died in 1485, were identified by comparing his mtDNA with that of two matrilineal descendants of his sister who were alive in 2013, 527 years after he died.
== Use in evolutionary biology and systematic biology ==
mtDNA is conserved across eukaryotic organisms given the critical role of mitochondria in cellular respiration. However, due to less efficient DNA repair (compared to nuclear DNA), it has a relatively high mutation rate (but slow compared to other DNA regions such as microsatellites) which makes it useful for studying the evolutionary relationships—phylogeny—of organisms. Biologists can determine and then compare mtDNA sequences among different species and use the comparisons to build an evolutionary tree for the species examined.
For instance, while most nuclear genes are nearly identical between humans and chimpanzees, their mitochondrial genomes are 9.8% different. Human and gorilla mitochondrial genomes are 11.8% different, suggesting that humans may be more closely related to chimpanzees than gorillas.
== mtDNA in nuclear DNA ==
Whole genome sequences of more than 66,000 people revealed that most of them had some mitochondrial DNA inserted into their nuclear genomes. More than 90% of these nuclear-mitochondrial segments (NUMTs) were inserted after humans diverged from the other apes. Results indicate such transfers currently occur as frequently as once in every ≈4,000 human births.
It appears that organellar DNA is much more often transferred to nuclear DNA than previously thought. This observation also supports the idea of the endosymbiont theory that eukaryotes have evolved from endosymbionts which turned into organelles while transferring most of their DNA to the nucleus so that the organellar genome shrunk in the process.
== History ==
Mitochondrial DNA was discovered in the 1960s by Margit M. K. Nass and Sylvan Nass by electron microscopy as DNase-sensitive threads inside mitochondria, and by Ellen Haslbrunner, Hans Tuppy and Gottfried Schatz by biochemical assays on highly purified mitochondrial fractions.
== Mitochondrial sequence databases ==
Several specialized databases have been founded to collect mitochondrial genome sequences and other information. Although most of them focus on sequence data, some of them include phylogenetic or functional information.
AmtDB: a database of ancient human mitochondrial genomes.
InterMitoBase: an annotated database and analysis platform of protein-protein interactions for human mitochondria. (apparently last updated in 2010, but still available)
MitoBreak: the mitochondrial DNA breakpoints database.
MitoFish and MitoAnnotator: a mitochondrial genome database of fish. See also Cawthorn et al.
Mitome: a database for comparative mitochondrial genomics in metazoan animals (no longer available)
MitoRes: a resource of nuclear-encoded mitochondrial genes and their products in metazoa (apparently no longer being updated)
MitoSatPlant: Mitochondrial microsatellites database of viridiplantae.
MitoZoa 2.0: a database for comparative and evolutionary analyses of mitochondrial genomes in Metazoa. (no longer available)
== MtDNA-phenotype association databases ==
Genome-wide association studies can reveal associations of mtDNA genes and their mutations with phenotypes including lifespan and disease risks. In 2021, the largest, UK Biobank-based, genome-wide association study of mitochondrial DNA unveiled 260 new associations with phenotypes including lifespan and disease risks for e.g. type 2 diabetes.
=== Mitochondrial mutation databases ===
Several specialized databases exist that report polymorphisms and mutations in the human mitochondrial DNA, together with the assessment of their pathogenicity.
MitImpact: A collection of pre-computed pathogenicity predictions for all nucleotide changes that cause non-synonymous substitutions in human mitochondrial protein-coding genes MitImpact 3D - IRCCS-CSS Bioinformatics lab.
MITOMAP: A compendium of polymorphisms and mutations in human mitochondrial DNA WebHome < MITOMAP < Foswiki.
== See also ==
== References ==
== External links ==
Media related to Mitochondrial DNA at Wikimedia Commons | Wikipedia/MtDNA |
Deoxyribonucleic acid ( ; DNA) is a polymer composed of two polynucleotide chains that coil around each other to form a double helix. The polymer carries genetic instructions for the development, functioning, growth and reproduction of all known organisms and many viruses. DNA and ribonucleic acid (RNA) are nucleic acids. Alongside proteins, lipids and complex carbohydrates (polysaccharides), nucleic acids are one of the four major types of macromolecules that are essential for all known forms of life.
The two DNA strands are known as polynucleotides as they are composed of simpler monomeric units called nucleotides. Each nucleotide is composed of one of four nitrogen-containing nucleobases (cytosine [C], guanine [G], adenine [A] or thymine [T]), a sugar called deoxyribose, and a phosphate group. The nucleotides are joined to one another in a chain by covalent bonds (known as the phosphodiester linkage) between the sugar of one nucleotide and the phosphate of the next, resulting in an alternating sugar-phosphate backbone. The nitrogenous bases of the two separate polynucleotide strands are bound together, according to base pairing rules (A with T and C with G), with hydrogen bonds to make double-stranded DNA. The complementary nitrogenous bases are divided into two groups, the single-ringed pyrimidines and the double-ringed purines. In DNA, the pyrimidines are thymine and cytosine; the purines are adenine and guanine.
Both strands of double-stranded DNA store the same biological information. This information is replicated when the two strands separate. A large part of DNA (more than 98% for humans) is non-coding, meaning that these sections do not serve as patterns for protein sequences. The two strands of DNA run in opposite directions to each other and are thus antiparallel. Attached to each sugar is one of four types of nucleobases (or bases). It is the sequence of these four nucleobases along the backbone that encodes genetic information. RNA strands are created using DNA strands as a template in a process called transcription, where DNA bases are exchanged for their corresponding bases except in the case of thymine (T), for which RNA substitutes uracil (U). Under the genetic code, these RNA strands specify the sequence of amino acids within proteins in a process called translation.
Within eukaryotic cells, DNA is organized into long structures called chromosomes. Before typical cell division, these chromosomes are duplicated in the process of DNA replication, providing a complete set of chromosomes for each daughter cell. Eukaryotic organisms (animals, plants, fungi and protists) store most of their DNA inside the cell nucleus as nuclear DNA, and some in the mitochondria as mitochondrial DNA or in chloroplasts as chloroplast DNA. In contrast, prokaryotes (bacteria and archaea) store their DNA only in the cytoplasm, in circular chromosomes. Within eukaryotic chromosomes, chromatin proteins, such as histones, compact and organize DNA. These compacting structures guide the interactions between DNA and other proteins, helping control which parts of the DNA are transcribed.
== Properties ==
DNA is a long polymer made from repeating units called nucleotides. The structure of DNA is dynamic along its length, being capable of coiling into tight loops and other shapes. In all species it is composed of two helical chains, bound to each other by hydrogen bonds. Both chains are coiled around the same axis, and have the same pitch of 34 ångströms (3.4 nm). The pair of chains have a radius of 10 Å (1.0 nm). According to another study, when measured in a different solution, the DNA chain measured 22–26 Å (2.2–2.6 nm) wide, and one nucleotide unit measured 3.3 Å (0.33 nm) long. The buoyant density of most DNA is 1.7g/cm3.
DNA does not usually exist as a single strand, but instead as a pair of strands that are held tightly together. These two long strands coil around each other, in the shape of a double helix. The nucleotide contains both a segment of the backbone of the molecule (which holds the chain together) and a nucleobase (which interacts with the other DNA strand in the helix). A nucleobase linked to a sugar is called a nucleoside, and a base linked to a sugar and to one or more phosphate groups is called a nucleotide. A biopolymer comprising multiple linked nucleotides (as in DNA) is called a polynucleotide.
The backbone of the DNA strand is made from alternating phosphate and sugar groups. The sugar in DNA is 2-deoxyribose, which is a pentose (five-carbon) sugar. The sugars are joined by phosphate groups that form phosphodiester bonds between the third and fifth carbon atoms of adjacent sugar rings. These are known as the 3′-end (three prime end), and 5′-end (five prime end) carbons, the prime symbol being used to distinguish these carbon atoms from those of the base to which the deoxyribose forms a glycosidic bond.
Therefore, any DNA strand normally has one end at which there is a phosphate group attached to the 5′ carbon of a ribose (the 5′ phosphoryl) and another end at which there is a free hydroxyl group attached to the 3′ carbon of a ribose (the 3′ hydroxyl). The orientation of the 3′ and 5′ carbons along the sugar-phosphate backbone confers directionality (sometimes called polarity) to each DNA strand. In a nucleic acid double helix, the direction of the nucleotides in one strand is opposite to their direction in the other strand: the strands are antiparallel. The asymmetric ends of DNA strands are said to have a directionality of five prime end (5′ ), and three prime end (3′), with the 5′ end having a terminal phosphate group and the 3′ end a terminal hydroxyl group. One major difference between DNA and RNA is the sugar, with the 2-deoxyribose in DNA being replaced by the related pentose sugar ribose in RNA.
The DNA double helix is stabilized primarily by two forces: hydrogen bonds between nucleotides and base-stacking interactions among aromatic nucleobases. The four bases found in DNA are adenine (A), cytosine (C), guanine (G) and thymine (T). These four bases are attached to the sugar-phosphate to form the complete nucleotide, as shown for adenosine monophosphate. Adenine pairs with thymine and guanine pairs with cytosine, forming A-T and G-C base pairs.
=== Nucleobase classification ===
The nucleobases are classified into two types: the purines, A and G, which are fused five- and six-membered heterocyclic compounds, and the pyrimidines, the six-membered rings C and T. A fifth pyrimidine nucleobase, uracil (U), usually takes the place of thymine in RNA and differs from thymine by lacking a methyl group on its ring. In addition to RNA and DNA, many artificial nucleic acid analogues have been created to study the properties of nucleic acids, or for use in biotechnology.
=== Non-canonical bases ===
Modified bases occur in DNA. The first of these recognized was 5-methylcytosine, which was found in the genome of Mycobacterium tuberculosis in 1925. The reason for the presence of these noncanonical bases in bacterial viruses (bacteriophages) is to avoid the restriction enzymes present in bacteria. This enzyme system acts at least in part as a molecular immune system protecting bacteria from infection by viruses. Modifications of the bases cytosine and adenine, the more common and modified DNA bases, play vital roles in the epigenetic control of gene expression in plants and animals.
A number of noncanonical bases are known to occur in DNA. Most of these are modifications of the canonical bases plus uracil.
Modified Adenine
N6-carbamoyl-methyladenine
N6-methyadenine
Modified Guanine
7-Deazaguanine
7-Methylguanine
Modified Cytosine
N4-Methylcytosine
5-Carboxylcytosine
5-Formylcytosine
5-Glycosylhydroxymethylcytosine
5-Hydroxycytosine
5-Methylcytosine
Modified Thymidine
α-Glutamythymidine
α-Putrescinylthymine
Uracil and modifications
Base J
Uracil
5-Dihydroxypentauracil
5-Hydroxymethyldeoxyuracil
Others
Deoxyarchaeosine
2,6-Diaminopurine (2-Aminoadenine)
=== Grooves ===
Twin helical strands form the DNA backbone. Another double helix may be found tracing the spaces, or grooves, between the strands. These voids are adjacent to the base pairs and may provide a binding site. As the strands are not symmetrically located with respect to each other, the grooves are unequally sized. The major groove is 22 ångströms (2.2 nm) wide, while the minor groove is 12 Å (1.2 nm) in width. Due to the larger width of the major groove, the edges of the bases are more accessible in the major groove than in the minor groove. As a result, proteins such as transcription factors that can bind to specific sequences in double-stranded DNA usually make contact with the sides of the bases exposed in the major groove. This situation varies in unusual conformations of DNA within the cell (see below), but the major and minor grooves are always named to reflect the differences in width that would be seen if the DNA was twisted back into the ordinary B form.
=== Base pairing ===
In a DNA double helix, each type of nucleobase on one strand bonds with just one type of nucleobase on the other strand. This is called complementary base pairing. Purines form hydrogen bonds to pyrimidines, with adenine bonding only to thymine in two hydrogen bonds, and cytosine bonding only to guanine in three hydrogen bonds. This arrangement of two nucleotides binding together across the double helix (from six-carbon ring to six-carbon ring) is called a Watson-Crick base pair. DNA with high GC-content is more stable than DNA with low GC-content. A Hoogsteen base pair (hydrogen bonding the 6-carbon ring to the 5-carbon ring) is a rare variation of base-pairing. As hydrogen bonds are not covalent, they can be broken and rejoined relatively easily. The two strands of DNA in a double helix can thus be pulled apart like a zipper, either by a mechanical force or high temperature. As a result of this base pair complementarity, all the information in the double-stranded sequence of a DNA helix is duplicated on each strand, which is vital in DNA replication. This reversible and specific interaction between complementary base pairs is critical for all the functions of DNA in organisms.
==== ssDNA vs. dsDNA ====
Most DNA molecules are actually two polymer strands, bound together in a helical fashion by noncovalent bonds; this double-stranded (dsDNA) structure is maintained largely by the intrastrand base stacking interactions, which are strongest for G,C stacks. The two strands can come apart—a process known as melting—to form two single-stranded DNA (ssDNA) molecules. Melting occurs at high temperatures, low salt and high pH (low pH also melts DNA, but since DNA is unstable due to acid depurination, low pH is rarely used).
The stability of the dsDNA form depends not only on the GC-content (% G,C basepairs) but also on sequence (since stacking is sequence specific) and also length (longer molecules are more stable). The stability can be measured in various ways; a common way is the melting temperature (also called Tm value), which is the temperature at which 50% of the double-strand molecules are converted to single-strand molecules; melting temperature is dependent on ionic strength and the concentration of DNA. As a result, it is both the percentage of GC base pairs and the overall length of a DNA double helix that determines the strength of the association between the two strands of DNA. Long DNA helices with a high GC-content have more strongly interacting strands, while short helices with high AT content have more weakly interacting strands. In biology, parts of the DNA double helix that need to separate easily, such as the TATAAT Pribnow box in some promoters, tend to have a high AT content, making the strands easier to pull apart.
In the laboratory, the strength of this interaction can be measured by finding the melting temperature Tm necessary to break half of the hydrogen bonds. When all the base pairs in a DNA double helix melt, the strands separate and exist in solution as two entirely independent molecules. These single-stranded DNA molecules have no single common shape, but some conformations are more stable than others.
=== Amount ===
In humans, the total female diploid nuclear genome per cell extends for 6.37 Gigabase pairs (Gbp), is 208.23 cm long and weighs 6.51 picograms (pg). Male values are 6.27 Gbp, 205.00 cm, 6.41 pg. Each DNA polymer can contain hundreds of millions of nucleotides, such as in chromosome 1. Chromosome 1 is the largest human chromosome with approximately 220 million base pairs, and would be 85 mm long if straightened.
In eukaryotes, in addition to nuclear DNA, there is also mitochondrial DNA (mtDNA) which encodes certain proteins used by the mitochondria. The mtDNA is usually relatively small in comparison to the nuclear DNA. For example, the human mitochondrial DNA forms closed circular molecules, each of which contains 16,569 DNA base pairs, with each such molecule normally containing a full set of the mitochondrial genes. Each human mitochondrion contains, on average, approximately 5 such mtDNA molecules. Each human cell contains approximately 100 mitochondria, giving a total number of mtDNA molecules per human cell of approximately 500. However, the amount of mitochondria per cell also varies by cell type, and an egg cell can contain 100,000 mitochondria, corresponding to up to 1,500,000 copies of the mitochondrial genome (constituting up to 90% of the DNA of the cell).
=== Sense and antisense ===
A DNA sequence is called a "sense" sequence if it is the same as that of a messenger RNA copy that is translated into protein. The sequence on the opposite strand is called the "antisense" sequence. Both sense and antisense sequences can exist on different parts of the same strand of DNA (i.e. both strands can contain both sense and antisense sequences). In both prokaryotes and eukaryotes, antisense RNA sequences are produced, but the functions of these RNAs are not entirely clear. One proposal is that antisense RNAs are involved in regulating gene expression through RNA-RNA base pairing.
A few DNA sequences in prokaryotes and eukaryotes, and more in plasmids and viruses, blur the distinction between sense and antisense strands by having overlapping genes. In these cases, some DNA sequences do double duty, encoding one protein when read along one strand, and a second protein when read in the opposite direction along the other strand. In bacteria, this overlap may be involved in the regulation of gene transcription, while in viruses, overlapping genes increase the amount of information that can be encoded within the small viral genome.
=== Supercoiling ===
DNA can be twisted like a rope in a process called DNA supercoiling. With DNA in its "relaxed" state, a strand usually circles the axis of the double helix once every 10.4 base pairs, but if the DNA is twisted the strands become more tightly or more loosely wound. If the DNA is twisted in the direction of the helix, this is positive supercoiling, and the bases are held more tightly together. If they are twisted in the opposite direction, this is negative supercoiling, and the bases come apart more easily. In nature, most DNA has slight negative supercoiling that is introduced by enzymes called topoisomerases. These enzymes are also needed to relieve the twisting stresses introduced into DNA strands during processes such as transcription and DNA replication.
=== Alternative DNA structures ===
DNA exists in many possible conformations that include A-DNA, B-DNA, and Z-DNA forms, although only B-DNA and Z-DNA have been directly observed in functional organisms. The conformation that DNA adopts depends on the hydration level, DNA sequence, the amount and direction of supercoiling, chemical modifications of the bases, the type and concentration of metal ions, and the presence of polyamines in solution.
The first published reports of A-DNA X-ray diffraction patterns—and also B-DNA—used analyses based on Patterson functions that provided only a limited amount of structural information for oriented fibers of DNA. An alternative analysis was proposed by Wilkins et al. in 1953 for the in vivo B-DNA X-ray diffraction-scattering patterns of highly hydrated DNA fibers in terms of squares of Bessel functions. In the same journal, James Watson and Francis Crick presented their molecular modeling analysis of the DNA X-ray diffraction patterns to suggest that the structure was a double helix.
Although the B-DNA form is most common under the conditions found in cells, it is not a well-defined conformation but a family of related DNA conformations that occur at the high hydration levels present in cells. Their corresponding X-ray diffraction and scattering patterns are characteristic of molecular paracrystals with a significant degree of disorder.
Compared to B-DNA, the A-DNA form is a wider right-handed spiral, with a shallow, wide minor groove and a narrower, deeper major groove. The A form occurs under non-physiological conditions in partly dehydrated samples of DNA, while in the cell it may be produced in hybrid pairings of DNA and RNA strands, and in enzyme-DNA complexes. Segments of DNA where the bases have been chemically modified by methylation may undergo a larger change in conformation and adopt the Z form. Here, the strands turn about the helical axis in a left-handed spiral, the opposite of the more common B form. These unusual structures can be recognized by specific Z-DNA binding proteins and may be involved in the regulation of transcription.
=== Alternative DNA chemistry ===
For many years, exobiologists have proposed the existence of a shadow biosphere, a postulated microbial biosphere of Earth that uses radically different biochemical and molecular processes than currently known life. One of the proposals was the existence of lifeforms that use arsenic instead of phosphorus in DNA. A report in 2010 of the possibility in the bacterium GFAJ-1 was announced, though the research was disputed, and evidence suggests the bacterium actively prevents the incorporation of arsenic into the DNA backbone and other biomolecules.
=== Quadruplex structures ===
At the ends of the linear chromosomes are specialized regions of DNA called telomeres. The main function of these regions is to allow the cell to replicate chromosome ends using the enzyme telomerase, as the enzymes that normally replicate DNA cannot copy the extreme 3′ ends of chromosomes. These specialized chromosome caps also help protect the DNA ends, and stop the DNA repair systems in the cell from treating them as damage to be corrected. In human cells, telomeres are usually lengths of single-stranded DNA containing several thousand repeats of a simple TTAGGG sequence.
These guanine-rich sequences may stabilize chromosome ends by forming structures of stacked sets of four-base units, rather than the usual base pairs found in other DNA molecules. Here, four guanine bases, known as a guanine tetrad, form a flat plate. These flat four-base units then stack on top of each other to form a stable G-quadruplex structure. These structures are stabilized by hydrogen bonding between the edges of the bases and chelation of a metal ion in the centre of each four-base unit. Other structures can also be formed, with the central set of four bases coming from either a single strand folded around the bases, or several different parallel strands, each contributing one base to the central structure.
In addition to these stacked structures, telomeres also form large loop structures called telomere loops, or T-loops. Here, the single-stranded DNA curls around in a long circle stabilized by telomere-binding proteins. At the very end of the T-loop, the single-stranded telomere DNA is held onto a region of double-stranded DNA by the telomere strand disrupting the double-helical DNA and base pairing to one of the two strands. This triple-stranded structure is called a displacement loop or D-loop.
=== Branched DNA ===
In DNA, fraying occurs when non-complementary regions exist at the end of an otherwise complementary double-strand of DNA. However, branched DNA can occur if a third strand of DNA is introduced and contains adjoining regions able to hybridize with the frayed regions of the pre-existing double-strand. Although the simplest example of branched DNA involves only three strands of DNA, complexes involving additional strands and multiple branches are also possible. Branched DNA can be used in nanotechnology to construct geometric shapes, see the section on uses in technology below.
=== Artificial bases ===
Several artificial nucleobases have been synthesized, and successfully incorporated in the eight-base DNA analogue named Hachimoji DNA. Dubbed S, B, P, and Z, these artificial bases are capable of bonding with each other in a predictable way (S–B and P–Z), maintain the double helix structure of DNA, and be transcribed to RNA. Their existence could be seen as an indication that there is nothing special about the four natural nucleobases that evolved on Earth. On the other hand, DNA is tightly related to RNA which does not only act as a transcript of DNA but also performs as molecular machines many tasks in cells. For this purpose it has to fold into a structure. It has been shown that to allow to create all possible structures at least four bases are required for the corresponding RNA, while a higher number is also possible but this would be against the natural principle of least effort.
=== Acidity ===
The phosphate groups of DNA give it similar acidic properties to phosphoric acid and it can be considered as a strong acid. It will be fully ionized at a normal cellular pH, releasing protons which leave behind negative charges on the phosphate groups. These negative charges protect DNA from breakdown by hydrolysis by repelling nucleophiles which could hydrolyze it.
=== Macroscopic appearance ===
Pure DNA extracted from cells forms white, stringy clumps.
== Chemical modifications and altered DNA packaging ==
=== Base modifications and DNA packaging ===
The expression of genes is influenced by how the DNA is packaged in chromosomes, in a structure called chromatin. Base modifications can be involved in packaging, with regions that have low or no gene expression usually containing high levels of methylation of cytosine bases. DNA packaging and its influence on gene expression can also occur by covalent modifications of the histone protein core around which DNA is wrapped in the chromatin structure or else by remodeling carried out by chromatin remodeling complexes (see Chromatin remodeling). There is, further, crosstalk between DNA methylation and histone modification, so they can coordinately affect chromatin and gene expression.
For one example, cytosine methylation produces 5-methylcytosine, which is important for X-inactivation of chromosomes. The average level of methylation varies between organisms—the worm Caenorhabditis elegans lacks cytosine methylation, while vertebrates have higher levels, with up to 1% of their DNA containing 5-methylcytosine. Despite the importance of 5-methylcytosine, it can deaminate to leave a thymine base, so methylated cytosines are particularly prone to mutations. Other base modifications include adenine methylation in bacteria, the presence of 5-hydroxymethylcytosine in the brain, and the glycosylation of uracil to produce the "J-base" in kinetoplastids.
=== Damage ===
DNA can be damaged by many sorts of mutagens, which change the DNA sequence. Mutagens include oxidizing agents, alkylating agents and also high-energy electromagnetic radiation such as ultraviolet light and X-rays. The type of DNA damage produced depends on the type of mutagen. For example, UV light can damage DNA by producing thymine dimers, which are cross-links between pyrimidine bases. On the other hand, oxidants such as free radicals or hydrogen peroxide produce multiple forms of damage, including base modifications, particularly of guanosine, and double-strand breaks. A typical human cell contains about 150,000 bases that have suffered oxidative damage. Of these oxidative lesions, the most dangerous are double-strand breaks, as these are difficult to repair and can produce point mutations, insertions, deletions from the DNA sequence, and chromosomal translocations. These mutations can cause cancer. Because of inherent limits in the DNA repair mechanisms, if humans lived long enough, they would all eventually develop cancer. DNA damages that are naturally occurring, due to normal cellular processes that produce reactive oxygen species, the hydrolytic activities of cellular water, etc., also occur frequently. Although most of these damages are repaired, in any cell some DNA damage may remain despite the action of repair processes. These remaining DNA damages accumulate with age in mammalian postmitotic tissues. This accumulation appears to be an important underlying cause of aging.
Many mutagens fit into the space between two adjacent base pairs, this is called intercalation. Most intercalators are aromatic and planar molecules; examples include ethidium bromide, acridines, daunomycin, and doxorubicin. For an intercalator to fit between base pairs, the bases must separate, distorting the DNA strands by unwinding of the double helix. This inhibits both transcription and DNA replication, causing toxicity and mutations. As a result, DNA intercalators may be carcinogens, and in the case of thalidomide, a teratogen. Others such as benzo[a]pyrene diol epoxide and aflatoxin form DNA adducts that induce errors in replication. Nevertheless, due to their ability to inhibit DNA transcription and replication, other similar toxins are also used in chemotherapy to inhibit rapidly growing cancer cells.
== Biological functions ==
DNA usually occurs as linear chromosomes in eukaryotes, and circular chromosomes in prokaryotes. The set of chromosomes in a cell makes up its genome; the human genome has approximately 3 billion base pairs of DNA arranged into 46 chromosomes. The information carried by DNA is held in the sequence of pieces of DNA called genes. Transmission of genetic information in genes is achieved via complementary base pairing. For example, in transcription, when a cell uses the information in a gene, the DNA sequence is copied into a complementary RNA sequence through the attraction between the DNA and the correct RNA nucleotides. Usually, this RNA copy is then used to make a matching protein sequence in a process called translation, which depends on the same interaction between RNA nucleotides. In an alternative fashion, a cell may copy its genetic information in a process called DNA replication. The details of these functions are covered in other articles; here the focus is on the interactions between DNA and other molecules that mediate the function of the genome.
=== Genes and genomes ===
Genomic DNA is tightly and orderly packed in the process called DNA condensation, to fit the small available volumes of the cell. In eukaryotes, DNA is located in the cell nucleus, with small amounts in mitochondria and chloroplasts. In prokaryotes, the DNA is held within an irregularly shaped body in the cytoplasm called the nucleoid. The genetic information in a genome is held within genes, and the complete set of this information in an organism is called its genotype. A gene is a unit of heredity and is a region of DNA that influences a particular characteristic in an organism. Genes contain an open reading frame that can be transcribed, and regulatory sequences such as promoters and enhancers, which control transcription of the open reading frame.
In many species, only a small fraction of the total sequence of the genome encodes protein. For example, only about 1.5% of the human genome consists of protein-coding exons, with over 50% of human DNA consisting of non-coding repetitive sequences. The reasons for the presence of so much noncoding DNA in eukaryotic genomes and the extraordinary differences in genome size, or C-value, among species, represent a long-standing puzzle known as the "C-value enigma". However, some DNA sequences that do not code protein may still encode functional non-coding RNA molecules, which are involved in the regulation of gene expression.
Some noncoding DNA sequences play structural roles in chromosomes. Telomeres and centromeres typically contain few genes but are important for the function and stability of chromosomes. An abundant form of noncoding DNA in humans are pseudogenes, which are copies of genes that have been disabled by mutation. These sequences are usually just molecular fossils, although they can occasionally serve as raw genetic material for the creation of new genes through the process of gene duplication and divergence.
=== Transcription and translation ===
A gene is a sequence of DNA that contains genetic information and can influence the phenotype of an organism. Within a gene, the sequence of bases along a DNA strand defines a messenger RNA sequence, which then defines one or more protein sequences. The relationship between the nucleotide sequences of genes and the amino-acid sequences of proteins is determined by the rules of translation, known collectively as the genetic code. The genetic code consists of three-letter 'words' called codons formed from a sequence of three nucleotides (e.g. ACT, CAG, TTT).
In transcription, the codons of a gene are copied into messenger RNA by RNA polymerase. This RNA copy is then decoded by a ribosome that reads the RNA sequence by base-pairing the messenger RNA to transfer RNA, which carries amino acids. Since there are 4 bases in 3-letter combinations, there are 64 possible codons (43 combinations). These encode the twenty standard amino acids, giving most amino acids more than one possible codon. There are also three 'stop' or 'nonsense' codons signifying the end of the coding region; these are the TAG, TAA, and TGA codons, (UAG, UAA, and UGA on the mRNA).
=== Replication ===
Cell division is essential for an organism to grow, but, when a cell divides, it must replicate the DNA in its genome so that the two daughter cells have the same genetic information as their parent. The double-stranded structure of DNA provides a simple mechanism for DNA replication. Here, the two strands are separated and then each strand's complementary DNA sequence is recreated by an enzyme called DNA polymerase. This enzyme makes the complementary strand by finding the correct base through complementary base pairing and bonding it onto the original strand. As DNA polymerases can only extend a DNA strand in a 5′ to 3′ direction, different mechanisms are used to copy the antiparallel strands of the double helix. In this way, the base on the old strand dictates which base appears on the new strand, and the cell ends up with a perfect copy of its DNA.
=== Extracellular nucleic acids ===
Naked extracellular DNA (eDNA), most of it released by cell death, is nearly ubiquitous in the environment. Its concentration in soil may be as high as 2 μg/L, and its concentration in natural aquatic environments may be as high at 88 μg/L. Various possible functions have been proposed for eDNA: it may be involved in horizontal gene transfer; it may provide nutrients; and it may act as a buffer to recruit or titrate ions or antibiotics. Extracellular DNA acts as a functional extracellular matrix component in the biofilms of several bacterial species. It may act as a recognition factor to regulate the attachment and dispersal of specific cell types in the biofilm; it may contribute to biofilm formation; and it may contribute to the biofilm's physical strength and resistance to biological stress.
Cell-free fetal DNA is found in the blood of the mother, and can be sequenced to determine a great deal of information about the developing fetus.
Under the name of environmental DNA eDNA has seen increased use in the natural sciences as a survey tool for ecology, monitoring the movements and presence of species in water, air, or on land, and assessing an area's biodiversity.
=== Neutrophil extracellular traps ===
Neutrophil extracellular traps (NETs) are networks of extracellular fibers, primarily composed of DNA, which allow neutrophils, a type of white blood cell, to kill extracellular pathogens while minimizing damage to the host cells.
== Interactions with proteins ==
All the functions of DNA depend on interactions with proteins. These protein interactions can be non-specific, or the protein can bind specifically to a single DNA sequence. Enzymes can also bind to DNA and of these, the polymerases that copy the DNA base sequence in transcription and DNA replication are particularly important.
=== DNA-binding proteins ===
Structural proteins that bind DNA are well-understood examples of non-specific DNA-protein interactions. Within chromosomes, DNA is held in complexes with structural proteins. These proteins organize the DNA into a compact structure called chromatin. In eukaryotes, this structure involves DNA binding to a complex of small basic proteins called histones, while in prokaryotes multiple types of proteins are involved. The histones form a disk-shaped complex called a nucleosome, which contains two complete turns of double-stranded DNA wrapped around its surface. These non-specific interactions are formed through basic residues in the histones, making ionic bonds to the acidic sugar-phosphate backbone of the DNA, and are thus largely independent of the base sequence. Chemical modifications of these basic amino acid residues include methylation, phosphorylation, and acetylation. These chemical changes alter the strength of the interaction between the DNA and the histones, making the DNA more or less accessible to transcription factors and changing the rate of transcription. Other non-specific DNA-binding proteins in chromatin include the high-mobility group proteins, which bind to bent or distorted DNA. These proteins are important in bending arrays of nucleosomes and arranging them into the larger structures that make up chromosomes.
A distinct group of DNA-binding proteins is the DNA-binding proteins that specifically bind single-stranded DNA. In humans, replication protein A is the best-understood member of this family and is used in processes where the double helix is separated, including DNA replication, recombination, and DNA repair. These binding proteins seem to stabilize single-stranded DNA and protect it from forming stem-loops or being degraded by nucleases.
In contrast, other proteins have evolved to bind to particular DNA sequences. The most intensively studied of these are the various transcription factors, which are proteins that regulate transcription. Each transcription factor binds to one particular set of DNA sequences and activates or inhibits the transcription of genes that have these sequences close to their promoters. The transcription factors do this in two ways. Firstly, they can bind the RNA polymerase responsible for transcription, either directly or through other mediator proteins; this locates the polymerase at the promoter and allows it to begin transcription. Alternatively, transcription factors can bind enzymes that modify the histones at the promoter. This changes the accessibility of the DNA template to the polymerase.
As these DNA targets can occur throughout an organism's genome, changes in the activity of one type of transcription factor can affect thousands of genes. Consequently, these proteins are often the targets of the signal transduction processes that control responses to environmental changes or cellular differentiation and development. The specificity of these transcription factors' interactions with DNA come from the proteins making multiple contacts to the edges of the DNA bases, allowing them to "read" the DNA sequence. Most of these base-interactions are made in the major groove, where the bases are most accessible.
=== DNA-modifying enzymes ===
==== Nucleases and ligases ====
Nucleases are enzymes that cut DNA strands by catalyzing the hydrolysis of the phosphodiester bonds. Nucleases that hydrolyse nucleotides from the ends of DNA strands are called exonucleases, while endonucleases cut within strands. The most frequently used nucleases in molecular biology are the restriction endonucleases, which cut DNA at specific sequences. For instance, the EcoRV enzyme shown to the left recognizes the 6-base sequence 5′-GATATC-3′ and makes a cut at the horizontal line. In nature, these enzymes protect bacteria against phage infection by digesting the phage DNA when it enters the bacterial cell, acting as part of the restriction modification system. In technology, these sequence-specific nucleases are used in molecular cloning and DNA fingerprinting.
Enzymes called DNA ligases can rejoin cut or broken DNA strands. Ligases are particularly important in lagging strand DNA replication, as they join the short segments of DNA produced at the replication fork into a complete copy of the DNA template. They are also used in DNA repair and genetic recombination.
==== Topoisomerases and helicases ====
Topoisomerases are enzymes with both nuclease and ligase activity. These proteins change the amount of supercoiling in DNA. Some of these enzymes work by cutting the DNA helix and allowing one section to rotate, thereby reducing its level of supercoiling; the enzyme then seals the DNA break. Other types of these enzymes are capable of cutting one DNA helix and then passing a second strand of DNA through this break, before rejoining the helix. Topoisomerases are required for many processes involving DNA, such as DNA replication and transcription.
Helicases are proteins that are a type of molecular motor. They use the chemical energy in nucleoside triphosphates, predominantly adenosine triphosphate (ATP), to break hydrogen bonds between bases and unwind the DNA double helix into single strands. These enzymes are essential for most processes where enzymes need to access the DNA bases.
==== Polymerases ====
Polymerases are enzymes that synthesize polynucleotide chains from nucleoside triphosphates. The sequence of their products is created based on existing polynucleotide chains—which are called templates. These enzymes function by repeatedly adding a nucleotide to the 3′ hydroxyl group at the end of the growing polynucleotide chain. As a consequence, all polymerases work in a 5′ to 3′ direction. In the active site of these enzymes, the incoming nucleoside triphosphate base-pairs to the template: this allows polymerases to accurately synthesize the complementary strand of their template. Polymerases are classified according to the type of template that they use.
In DNA replication, DNA-dependent DNA polymerases make copies of DNA polynucleotide chains. To preserve biological information, it is essential that the sequence of bases in each copy are precisely complementary to the sequence of bases in the template strand. Many DNA polymerases have a proofreading activity. Here, the polymerase recognizes the occasional mistakes in the synthesis reaction by the lack of base pairing between the mismatched nucleotides. If a mismatch is detected, a 3′ to 5′ exonuclease activity is activated and the incorrect base removed. In most organisms, DNA polymerases function in a large complex called the replisome that contains multiple accessory subunits, such as the DNA clamp or helicases.
RNA-dependent DNA polymerases are a specialized class of polymerases that copy the sequence of an RNA strand into DNA. They include reverse transcriptase, which is a viral enzyme involved in the infection of cells by retroviruses, and telomerase, which is required for the replication of telomeres. For example, HIV reverse transcriptase is an enzyme for AIDS virus replication. Telomerase is an unusual polymerase because it contains its own RNA template as part of its structure. It synthesizes telomeres at the ends of chromosomes. Telomeres prevent fusion of the ends of neighboring chromosomes and protect chromosome ends from damage.
Transcription is carried out by a DNA-dependent RNA polymerase that copies the sequence of a DNA strand into RNA. To begin transcribing a gene, the RNA polymerase binds to a sequence of DNA called a promoter and separates the DNA strands. It then copies the gene sequence into a messenger RNA transcript until it reaches a region of DNA called the terminator, where it halts and detaches from the DNA. As with human DNA-dependent DNA polymerases, RNA polymerase II, the enzyme that transcribes most of the genes in the human genome, operates as part of a large protein complex with multiple regulatory and accessory subunits.
== Genetic recombination ==
A DNA helix usually does not interact with other segments of DNA, and in human cells, the different chromosomes even occupy separate areas in the nucleus called "chromosome territories". This physical separation of different chromosomes is important for the ability of DNA to function as a stable repository for information, as one of the few times chromosomes interact is in chromosomal crossover which occurs during sexual reproduction, when genetic recombination occurs. Chromosomal crossover is when two DNA helices break, swap a section and then rejoin.
Recombination allows chromosomes to exchange genetic information and produces new combinations of genes, which increases the efficiency of natural selection and can be important in the rapid evolution of new proteins. Genetic recombination can also be involved in DNA repair, particularly in the cell's response to double-strand breaks.
The most common form of chromosomal crossover is homologous recombination, where the two chromosomes involved share very similar sequences. Non-homologous recombination can be damaging to cells, as it can produce chromosomal translocations and genetic abnormalities. The recombination reaction is catalyzed by enzymes known as recombinases, such as RAD51. The first step in recombination is a double-stranded break caused by either an endonuclease or damage to the DNA. A series of steps catalyzed in part by the recombinase then leads to joining of the two helices by at least one Holliday junction, in which a segment of a single strand in each helix is annealed to the complementary strand in the other helix. The Holliday junction is a tetrahedral junction structure that can be moved along the pair of chromosomes, swapping one strand for another. The recombination reaction is then halted by cleavage of the junction and re-ligation of the released DNA. Only strands of like polarity exchange DNA during recombination. There are two types of cleavage: east-west cleavage and north–south cleavage. The north–south cleavage nicks both strands of DNA, while the east–west cleavage has one strand of DNA intact. The formation of a Holliday junction during recombination makes it possible for genetic diversity, genes to exchange on chromosomes, and expression of wild-type viral genomes.
== Evolution ==
DNA contains the genetic information that allows all forms of life to function, grow and reproduce. However, it is unclear how long in the 4-billion-year history of life DNA has performed this function, as it has been proposed that the earliest forms of life may have used RNA as their genetic material. RNA may have acted as the central part of early cell metabolism as it can both transmit genetic information and carry out catalysis as part of ribozymes. This ancient RNA world where nucleic acid would have been used for both catalysis and genetics may have influenced the evolution of the current genetic code based on four nucleotide bases. This would occur, since the number of different bases in such an organism is a trade-off between a small number of bases increasing replication accuracy and a large number of bases increasing the catalytic efficiency of ribozymes. However, there is no direct evidence of ancient genetic systems, as recovery of DNA from most fossils is impossible because DNA survives in the environment for less than one million years, and slowly degrades into short fragments in solution. Claims for older DNA have been made, most notably a report of the isolation of a viable bacterium from a salt crystal 250 million years old, but these claims are controversial.
Building blocks of DNA (adenine, guanine, and related organic molecules) may have been formed extraterrestrially in outer space. Complex DNA and RNA organic compounds of life, including uracil, cytosine, and thymine, have also been formed in the laboratory under conditions mimicking those found in outer space, using starting chemicals, such as pyrimidine, found in meteorites. Pyrimidine, like polycyclic aromatic hydrocarbons (PAHs), the most carbon-rich chemical found in the universe, may have been formed in red giants or in interstellar cosmic dust and gas clouds.
Ancient DNA has been recovered from ancient organisms at a timescale where genome evolution can be directly observed, including from extinct organisms up to millions of years old, such as the woolly mammoth.
== Uses in technology ==
=== Genetic engineering ===
Methods have been developed to purify DNA from organisms, such as phenol-chloroform extraction, and to manipulate it in the laboratory, such as restriction digests and the polymerase chain reaction. Modern biology and biochemistry make intensive use of these techniques in recombinant DNA technology. Recombinant DNA is a man-made DNA sequence that has been assembled from other DNA sequences. They can be transformed into organisms in the form of plasmids or in the appropriate format, by using a viral vector. The genetically modified organisms produced can be used to produce products such as recombinant proteins, used in medical research, or be grown in agriculture.
=== DNA profiling ===
Forensic scientists can use DNA in blood, semen, skin, saliva or hair found at a crime scene to identify a matching DNA of an individual, such as a perpetrator. This process is formally termed DNA profiling, also called DNA fingerprinting. In DNA profiling, the lengths of variable sections of repetitive DNA, such as short tandem repeats and minisatellites, are compared between people. This method is usually an extremely reliable technique for identifying a matching DNA. However, identification can be complicated if the scene is contaminated with DNA from several people. DNA profiling was developed in 1984 by British geneticist Sir Alec Jeffreys, and first used in forensic science to convict Colin Pitchfork in the 1988 Enderby murders case.
The development of forensic science and the ability to now obtain genetic matching on minute samples of blood, skin, saliva, or hair has led to re-examining many cases. Evidence can now be uncovered that was scientifically impossible at the time of the original examination. Combined with the removal of the double jeopardy law in some places, this can allow cases to be reopened where prior trials have failed to produce sufficient evidence to convince a jury. People charged with serious crimes may be required to provide a sample of DNA for matching purposes. The most obvious defense to DNA matches obtained forensically is to claim that cross-contamination of evidence has occurred. This has resulted in meticulous strict handling procedures with new cases of serious crime.
DNA profiling is also used successfully to positively identify victims of mass casualty incidents, bodies or body parts in serious accidents, and individual victims in mass war graves, via matching to family members.
DNA profiling is also used in DNA paternity testing to determine if someone is the biological parent or grandparent of a child with the probability of parentage is typically 99.99% when the alleged parent is biologically related to the child. Normal DNA sequencing methods happen after birth, but there are new methods to test paternity while a mother is still pregnant.
=== DNA enzymes or catalytic DNA ===
Deoxyribozymes, also called DNAzymes or catalytic DNA, were first discovered in 1994. They are mostly single stranded DNA sequences isolated from a large pool of random DNA sequences through a combinatorial approach called in vitro selection or systematic evolution of ligands by exponential enrichment (SELEX). DNAzymes catalyze variety of chemical reactions including RNA-DNA cleavage, RNA-DNA ligation, amino acids phosphorylation-dephosphorylation, carbon-carbon bond formation, etc. DNAzymes can enhance catalytic rate of chemical reactions up to 100,000,000,000-fold over the uncatalyzed reaction. The most extensively studied class of DNAzymes is RNA-cleaving types which have been used to detect different metal ions and designing therapeutic agents. Several metal-specific DNAzymes have been reported including the GR-5 DNAzyme (lead-specific), the CA1-3 DNAzymes (copper-specific), the 39E DNAzyme (uranyl-specific) and the NaA43 DNAzyme (sodium-specific). The NaA43 DNAzyme, which is reported to be more than 10,000-fold selective for sodium over other metal ions, was used to make a real-time sodium sensor in cells.
=== Bioinformatics ===
Bioinformatics involves the development of techniques to store, data mine, search and manipulate biological data, including DNA nucleic acid sequence data. These have led to widely applied advances in computer science, especially string searching algorithms, machine learning, and database theory. String searching or matching algorithms, which find an occurrence of a sequence of letters inside a larger sequence of letters, were developed to search for specific sequences of nucleotides. The DNA sequence may be aligned with other DNA sequences to identify homologous sequences and locate the specific mutations that make them distinct. These techniques, especially multiple sequence alignment, are used in studying phylogenetic relationships and protein function. Data sets representing entire genomes' worth of DNA sequences, such as those produced by the Human Genome Project, are difficult to use without the annotations that identify the locations of genes and regulatory elements on each chromosome. Regions of DNA sequence that have the characteristic patterns associated with protein- or RNA-coding genes can be identified by gene finding algorithms, which allow researchers to predict the presence of particular gene products and their possible functions in an organism even before they have been isolated experimentally. Entire genomes may also be compared, which can shed light on the evolutionary history of particular organism and permit the examination of complex evolutionary events.
=== DNA nanotechnology ===
DNA nanotechnology uses the unique molecular recognition properties of DNA and other nucleic acids to create self-assembling branched DNA complexes with useful properties. DNA is thus used as a structural material rather than as a carrier of biological information. This has led to the creation of two-dimensional periodic lattices (both tile-based and using the DNA origami method) and three-dimensional structures in the shapes of polyhedra. Nanomechanical devices and algorithmic self-assembly have also been demonstrated, and these DNA structures have been used to template the arrangement of other molecules such as gold nanoparticles and streptavidin proteins. DNA and other nucleic acids are the basis of aptamers, synthetic oligonucleotide ligands for specific target molecules used in a range of biotechnology and biomedical applications.
=== History and anthropology ===
Because DNA collects mutations over time, which are then inherited, it contains historical information, and, by comparing DNA sequences, geneticists can infer the evolutionary history of organisms, their phylogeny. This field of phylogenetics is a powerful tool in evolutionary biology. If DNA sequences within a species are compared, population geneticists can learn the history of particular populations. This can be used in studies ranging from ecological genetics to anthropology.
=== Information storage ===
DNA as a storage device for information has enormous potential since it has much higher storage density compared to electronic devices. However, high costs, slow read and write times (memory latency), and insufficient reliability has prevented its practical use.
== History ==
DNA was first isolated by the Swiss physician Friedrich Miescher who, in 1869, discovered a microscopic substance in the pus of discarded surgical bandages. As it resided in the nuclei of cells, he called it "nuclein". In 1878, Albrecht Kossel isolated the non-protein component of "nuclein", nucleic acid, and later isolated its five primary nucleobases.
In 1909, Phoebus Levene identified the base, sugar, and phosphate nucleotide unit of RNA (then named "yeast nucleic acid"). In 1929, Levene identified deoxyribose sugar in "thymus nucleic acid" (DNA). Levene suggested that DNA consisted of a string of four nucleotide units linked together through the phosphate groups ("tetranucleotide hypothesis"). Levene thought the chain was short and the bases repeated in a fixed order. In 1927, Nikolai Koltsov proposed that inherited traits would be inherited via a "giant hereditary molecule" made up of "two mirror strands that would replicate in a semi-conservative fashion using each strand as a template". In 1928, Frederick Griffith in his experiment discovered that traits of the "smooth" form of Pneumococcus could be transferred to the "rough" form of the same bacteria by mixing killed "smooth" bacteria with the live "rough" form. This system provided the first clear suggestion that DNA carries genetic information.
In 1933, while studying virgin sea urchin eggs, Jean Brachet suggested that DNA is found in the cell nucleus and that RNA is present exclusively in the cytoplasm. At the time, "yeast nucleic acid" (RNA) was thought to occur only in plants, while "thymus nucleic acid" (DNA) only in animals. The latter was thought to be a tetramer, with the function of buffering cellular pH.
In 1937, William Astbury produced the first X-ray diffraction patterns that showed that DNA had a regular structure.
In 1943, Oswald Avery, along with co-workers Colin MacLeod and Maclyn McCarty, identified DNA as the transforming principle, supporting Griffith's suggestion (Avery–MacLeod–McCarty experiment). Erwin Chargaff developed and published observations now known as Chargaff's rules, stating that in DNA from any species of any organism, the amount of guanine should be equal to cytosine and the amount of adenine should be equal to thymine.
Late in 1951, Francis Crick started working with James Watson at the Cavendish Laboratory within the University of Cambridge. DNA's role in heredity was confirmed in 1952 when Alfred Hershey and Martha Chase in the Hershey–Chase experiment showed that DNA is the genetic material of the enterobacteria phage T2.
In May 1952, Raymond Gosling, a graduate student working under the supervision of Rosalind Franklin, took an X-ray diffraction image, labeled as "Photo 51", at high hydration levels of DNA. This photo was given to Watson and Crick by Maurice Wilkins and was critical to their obtaining the correct structure of DNA. Franklin told Crick and Watson that the backbones had to be on the outside. Before then, Linus Pauling, and Watson and Crick, had erroneous models with the chains inside and the bases pointing outwards. Franklin's identification of the space group for DNA crystals revealed to Crick that the two DNA strands were antiparallel. In February 1953, Linus Pauling and Robert Corey proposed a model for nucleic acids containing three intertwined chains, with the phosphates near the axis, and the bases on the outside. Watson and Crick completed their model, which is now accepted as the first correct model of the double helix of DNA. On 28 February 1953 Crick interrupted patrons' lunchtime at The Eagle pub in Cambridge, England to announce that he and Watson had "discovered the secret of life".
The 25 April 1953 issue of the journal Nature published a series of five articles giving the Watson and Crick double-helix structure DNA and evidence supporting it. The structure was reported in a letter titled "MOLECULAR STRUCTURE OF NUCLEIC ACIDS A Structure for Deoxyribose Nucleic Acid", in which they said, "It has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material." This letter was followed by a letter from Franklin and Gosling, which was the first publication of their own X-ray diffraction data and of their original analysis method. Then followed a letter by Wilkins and two of his colleagues, which contained an analysis of in vivo B-DNA X-ray patterns, and which supported the presence in vivo of the Watson and Crick structure.
In April 2023, scientists, based on new evidence, concluded that Rosalind Franklin was a contributor and "equal player" in the discovery process of DNA, rather than otherwise, as may have been presented subsequently after the time of the discovery.
In 1962, after Franklin's death, Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine. Nobel Prizes are awarded only to living recipients. A debate continues about who should receive credit for the discovery.
In an influential presentation in 1957, Crick laid out the central dogma of molecular biology, which foretold the relationship between DNA, RNA, and proteins, and articulated the "adaptor hypothesis". Final confirmation of the replication mechanism that was implied by the double-helical structure followed in 1958 through the Meselson–Stahl experiment. Further work by Crick and co-workers showed that the genetic code was based on non-overlapping triplets of bases, called codons, allowing Har Gobind Khorana, Robert W. Holley, and Marshall Warren Nirenberg to decipher the genetic code. These findings represent the birth of molecular biology.
In 1986, DNA analysis was first used in a criminal investigation when police in the UK requested Alec Jeffreys of the University of Leicester to prove or disprove the involvement in a particular case of a suspect who claimed innocence in the matter. Although the suspect had already confessed to committing a recent rape-murder, he was denying any involvement in a similar crime committed three years earlier. Yet the details of the two cases were so alike that the police concluded both crimes had been committed by the same person. However, all charges against the suspect were dropped when Jeffreys' DNA testing exonerated the suspect — from both the earlier murder and the one to which he'd confessed. Further such DNA profiling led to positive identification of another suspect who, in 1988, was found guilty of both rape-murders.
== See also ==
== References ==
== Further reading ==
== External links ==
DNA binding site prediction on protein
DNA the Double Helix Game From the official Nobel Prize web site
DNA under electron microscope
Dolan DNA Learning Center
Double Helix: 50 years of DNA, Nature
Proteopedia DNA
Proteopedia Forms_of_DNA
ENCODE threads explorer ENCODE home page at Nature
Double Helix 1953–2003 National Centre for Biotechnology Education
Genetic Education Modules for Teachers – DNA from the Beginning Study Guide
PDB Molecule of the Month DNA
"Clue to chemistry of heredity found". The New York Times, June 1953. First American newspaper coverage of the discovery of the DNA structure
DNA from the Beginning Another DNA Learning Center site on DNA, genes, and heredity from Mendel to the human genome project.
The Register of Francis Crick Personal Papers 1938 – 2007 at Mandeville Special Collections Library, University of California, San Diego
Seven-page, handwritten letter that Crick sent to his 12-year-old son Michael in 1953 describing the structure of DNA. See Crick's medal goes under the hammer, Nature, 5 April 2013. | Wikipedia/DsDNA |
The vertebrate mitochondrial code (translation table 2) is the genetic code found in the mitochondria of all vertebrata.
== Evolution ==
AGA and AGG were thought to have become mitochondrial stop codons early in vertebrate evolution. However, at least in humans it has now been shown that AGA and AGG sequences are not recognized as termination codons. A -1 mitoribosome frameshift occurs at the AGA and AGG codons predicted to terminate the CO1 and ND6 open reading frames (ORFs), and consequently both ORFs terminate in the standard UAG codon.
== Incomplete stop codons ==
Mitochondrial genes in some vertebrates (including humans) have incomplete stop codons ending in U or UA, which become complete termination codons (UAA) upon subsequent polyadenylation.
== Translation table ==
A The codon AUG both codes for methionine and serves as an initiation site: the first AUG in an mRNA's coding region is where translation into protein begins.
== Differences from the standard code ==
=== Alternative initiation codons ===
Bos: AUA
Homo: AUA, AUU
Mus: AUA, AUU, AUC
Coturnix, Gallus: also GUG
== See also ==
List of genetic codes
== References ==
This article contains public domain text from the NCBI page compiled by Andrzej Elzanowski and Jim Ostell. | Wikipedia/Vertebrate_mitochondrial_code |
Deoxyribonucleic acid ( ; DNA) is a polymer composed of two polynucleotide chains that coil around each other to form a double helix. The polymer carries genetic instructions for the development, functioning, growth and reproduction of all known organisms and many viruses. DNA and ribonucleic acid (RNA) are nucleic acids. Alongside proteins, lipids and complex carbohydrates (polysaccharides), nucleic acids are one of the four major types of macromolecules that are essential for all known forms of life.
The two DNA strands are known as polynucleotides as they are composed of simpler monomeric units called nucleotides. Each nucleotide is composed of one of four nitrogen-containing nucleobases (cytosine [C], guanine [G], adenine [A] or thymine [T]), a sugar called deoxyribose, and a phosphate group. The nucleotides are joined to one another in a chain by covalent bonds (known as the phosphodiester linkage) between the sugar of one nucleotide and the phosphate of the next, resulting in an alternating sugar-phosphate backbone. The nitrogenous bases of the two separate polynucleotide strands are bound together, according to base pairing rules (A with T and C with G), with hydrogen bonds to make double-stranded DNA. The complementary nitrogenous bases are divided into two groups, the single-ringed pyrimidines and the double-ringed purines. In DNA, the pyrimidines are thymine and cytosine; the purines are adenine and guanine.
Both strands of double-stranded DNA store the same biological information. This information is replicated when the two strands separate. A large part of DNA (more than 98% for humans) is non-coding, meaning that these sections do not serve as patterns for protein sequences. The two strands of DNA run in opposite directions to each other and are thus antiparallel. Attached to each sugar is one of four types of nucleobases (or bases). It is the sequence of these four nucleobases along the backbone that encodes genetic information. RNA strands are created using DNA strands as a template in a process called transcription, where DNA bases are exchanged for their corresponding bases except in the case of thymine (T), for which RNA substitutes uracil (U). Under the genetic code, these RNA strands specify the sequence of amino acids within proteins in a process called translation.
Within eukaryotic cells, DNA is organized into long structures called chromosomes. Before typical cell division, these chromosomes are duplicated in the process of DNA replication, providing a complete set of chromosomes for each daughter cell. Eukaryotic organisms (animals, plants, fungi and protists) store most of their DNA inside the cell nucleus as nuclear DNA, and some in the mitochondria as mitochondrial DNA or in chloroplasts as chloroplast DNA. In contrast, prokaryotes (bacteria and archaea) store their DNA only in the cytoplasm, in circular chromosomes. Within eukaryotic chromosomes, chromatin proteins, such as histones, compact and organize DNA. These compacting structures guide the interactions between DNA and other proteins, helping control which parts of the DNA are transcribed.
== Properties ==
DNA is a long polymer made from repeating units called nucleotides. The structure of DNA is dynamic along its length, being capable of coiling into tight loops and other shapes. In all species it is composed of two helical chains, bound to each other by hydrogen bonds. Both chains are coiled around the same axis, and have the same pitch of 34 ångströms (3.4 nm). The pair of chains have a radius of 10 Å (1.0 nm). According to another study, when measured in a different solution, the DNA chain measured 22–26 Å (2.2–2.6 nm) wide, and one nucleotide unit measured 3.3 Å (0.33 nm) long. The buoyant density of most DNA is 1.7g/cm3.
DNA does not usually exist as a single strand, but instead as a pair of strands that are held tightly together. These two long strands coil around each other, in the shape of a double helix. The nucleotide contains both a segment of the backbone of the molecule (which holds the chain together) and a nucleobase (which interacts with the other DNA strand in the helix). A nucleobase linked to a sugar is called a nucleoside, and a base linked to a sugar and to one or more phosphate groups is called a nucleotide. A biopolymer comprising multiple linked nucleotides (as in DNA) is called a polynucleotide.
The backbone of the DNA strand is made from alternating phosphate and sugar groups. The sugar in DNA is 2-deoxyribose, which is a pentose (five-carbon) sugar. The sugars are joined by phosphate groups that form phosphodiester bonds between the third and fifth carbon atoms of adjacent sugar rings. These are known as the 3′-end (three prime end), and 5′-end (five prime end) carbons, the prime symbol being used to distinguish these carbon atoms from those of the base to which the deoxyribose forms a glycosidic bond.
Therefore, any DNA strand normally has one end at which there is a phosphate group attached to the 5′ carbon of a ribose (the 5′ phosphoryl) and another end at which there is a free hydroxyl group attached to the 3′ carbon of a ribose (the 3′ hydroxyl). The orientation of the 3′ and 5′ carbons along the sugar-phosphate backbone confers directionality (sometimes called polarity) to each DNA strand. In a nucleic acid double helix, the direction of the nucleotides in one strand is opposite to their direction in the other strand: the strands are antiparallel. The asymmetric ends of DNA strands are said to have a directionality of five prime end (5′ ), and three prime end (3′), with the 5′ end having a terminal phosphate group and the 3′ end a terminal hydroxyl group. One major difference between DNA and RNA is the sugar, with the 2-deoxyribose in DNA being replaced by the related pentose sugar ribose in RNA.
The DNA double helix is stabilized primarily by two forces: hydrogen bonds between nucleotides and base-stacking interactions among aromatic nucleobases. The four bases found in DNA are adenine (A), cytosine (C), guanine (G) and thymine (T). These four bases are attached to the sugar-phosphate to form the complete nucleotide, as shown for adenosine monophosphate. Adenine pairs with thymine and guanine pairs with cytosine, forming A-T and G-C base pairs.
=== Nucleobase classification ===
The nucleobases are classified into two types: the purines, A and G, which are fused five- and six-membered heterocyclic compounds, and the pyrimidines, the six-membered rings C and T. A fifth pyrimidine nucleobase, uracil (U), usually takes the place of thymine in RNA and differs from thymine by lacking a methyl group on its ring. In addition to RNA and DNA, many artificial nucleic acid analogues have been created to study the properties of nucleic acids, or for use in biotechnology.
=== Non-canonical bases ===
Modified bases occur in DNA. The first of these recognized was 5-methylcytosine, which was found in the genome of Mycobacterium tuberculosis in 1925. The reason for the presence of these noncanonical bases in bacterial viruses (bacteriophages) is to avoid the restriction enzymes present in bacteria. This enzyme system acts at least in part as a molecular immune system protecting bacteria from infection by viruses. Modifications of the bases cytosine and adenine, the more common and modified DNA bases, play vital roles in the epigenetic control of gene expression in plants and animals.
A number of noncanonical bases are known to occur in DNA. Most of these are modifications of the canonical bases plus uracil.
Modified Adenine
N6-carbamoyl-methyladenine
N6-methyadenine
Modified Guanine
7-Deazaguanine
7-Methylguanine
Modified Cytosine
N4-Methylcytosine
5-Carboxylcytosine
5-Formylcytosine
5-Glycosylhydroxymethylcytosine
5-Hydroxycytosine
5-Methylcytosine
Modified Thymidine
α-Glutamythymidine
α-Putrescinylthymine
Uracil and modifications
Base J
Uracil
5-Dihydroxypentauracil
5-Hydroxymethyldeoxyuracil
Others
Deoxyarchaeosine
2,6-Diaminopurine (2-Aminoadenine)
=== Grooves ===
Twin helical strands form the DNA backbone. Another double helix may be found tracing the spaces, or grooves, between the strands. These voids are adjacent to the base pairs and may provide a binding site. As the strands are not symmetrically located with respect to each other, the grooves are unequally sized. The major groove is 22 ångströms (2.2 nm) wide, while the minor groove is 12 Å (1.2 nm) in width. Due to the larger width of the major groove, the edges of the bases are more accessible in the major groove than in the minor groove. As a result, proteins such as transcription factors that can bind to specific sequences in double-stranded DNA usually make contact with the sides of the bases exposed in the major groove. This situation varies in unusual conformations of DNA within the cell (see below), but the major and minor grooves are always named to reflect the differences in width that would be seen if the DNA was twisted back into the ordinary B form.
=== Base pairing ===
In a DNA double helix, each type of nucleobase on one strand bonds with just one type of nucleobase on the other strand. This is called complementary base pairing. Purines form hydrogen bonds to pyrimidines, with adenine bonding only to thymine in two hydrogen bonds, and cytosine bonding only to guanine in three hydrogen bonds. This arrangement of two nucleotides binding together across the double helix (from six-carbon ring to six-carbon ring) is called a Watson-Crick base pair. DNA with high GC-content is more stable than DNA with low GC-content. A Hoogsteen base pair (hydrogen bonding the 6-carbon ring to the 5-carbon ring) is a rare variation of base-pairing. As hydrogen bonds are not covalent, they can be broken and rejoined relatively easily. The two strands of DNA in a double helix can thus be pulled apart like a zipper, either by a mechanical force or high temperature. As a result of this base pair complementarity, all the information in the double-stranded sequence of a DNA helix is duplicated on each strand, which is vital in DNA replication. This reversible and specific interaction between complementary base pairs is critical for all the functions of DNA in organisms.
==== ssDNA vs. dsDNA ====
Most DNA molecules are actually two polymer strands, bound together in a helical fashion by noncovalent bonds; this double-stranded (dsDNA) structure is maintained largely by the intrastrand base stacking interactions, which are strongest for G,C stacks. The two strands can come apart—a process known as melting—to form two single-stranded DNA (ssDNA) molecules. Melting occurs at high temperatures, low salt and high pH (low pH also melts DNA, but since DNA is unstable due to acid depurination, low pH is rarely used).
The stability of the dsDNA form depends not only on the GC-content (% G,C basepairs) but also on sequence (since stacking is sequence specific) and also length (longer molecules are more stable). The stability can be measured in various ways; a common way is the melting temperature (also called Tm value), which is the temperature at which 50% of the double-strand molecules are converted to single-strand molecules; melting temperature is dependent on ionic strength and the concentration of DNA. As a result, it is both the percentage of GC base pairs and the overall length of a DNA double helix that determines the strength of the association between the two strands of DNA. Long DNA helices with a high GC-content have more strongly interacting strands, while short helices with high AT content have more weakly interacting strands. In biology, parts of the DNA double helix that need to separate easily, such as the TATAAT Pribnow box in some promoters, tend to have a high AT content, making the strands easier to pull apart.
In the laboratory, the strength of this interaction can be measured by finding the melting temperature Tm necessary to break half of the hydrogen bonds. When all the base pairs in a DNA double helix melt, the strands separate and exist in solution as two entirely independent molecules. These single-stranded DNA molecules have no single common shape, but some conformations are more stable than others.
=== Amount ===
In humans, the total female diploid nuclear genome per cell extends for 6.37 Gigabase pairs (Gbp), is 208.23 cm long and weighs 6.51 picograms (pg). Male values are 6.27 Gbp, 205.00 cm, 6.41 pg. Each DNA polymer can contain hundreds of millions of nucleotides, such as in chromosome 1. Chromosome 1 is the largest human chromosome with approximately 220 million base pairs, and would be 85 mm long if straightened.
In eukaryotes, in addition to nuclear DNA, there is also mitochondrial DNA (mtDNA) which encodes certain proteins used by the mitochondria. The mtDNA is usually relatively small in comparison to the nuclear DNA. For example, the human mitochondrial DNA forms closed circular molecules, each of which contains 16,569 DNA base pairs, with each such molecule normally containing a full set of the mitochondrial genes. Each human mitochondrion contains, on average, approximately 5 such mtDNA molecules. Each human cell contains approximately 100 mitochondria, giving a total number of mtDNA molecules per human cell of approximately 500. However, the amount of mitochondria per cell also varies by cell type, and an egg cell can contain 100,000 mitochondria, corresponding to up to 1,500,000 copies of the mitochondrial genome (constituting up to 90% of the DNA of the cell).
=== Sense and antisense ===
A DNA sequence is called a "sense" sequence if it is the same as that of a messenger RNA copy that is translated into protein. The sequence on the opposite strand is called the "antisense" sequence. Both sense and antisense sequences can exist on different parts of the same strand of DNA (i.e. both strands can contain both sense and antisense sequences). In both prokaryotes and eukaryotes, antisense RNA sequences are produced, but the functions of these RNAs are not entirely clear. One proposal is that antisense RNAs are involved in regulating gene expression through RNA-RNA base pairing.
A few DNA sequences in prokaryotes and eukaryotes, and more in plasmids and viruses, blur the distinction between sense and antisense strands by having overlapping genes. In these cases, some DNA sequences do double duty, encoding one protein when read along one strand, and a second protein when read in the opposite direction along the other strand. In bacteria, this overlap may be involved in the regulation of gene transcription, while in viruses, overlapping genes increase the amount of information that can be encoded within the small viral genome.
=== Supercoiling ===
DNA can be twisted like a rope in a process called DNA supercoiling. With DNA in its "relaxed" state, a strand usually circles the axis of the double helix once every 10.4 base pairs, but if the DNA is twisted the strands become more tightly or more loosely wound. If the DNA is twisted in the direction of the helix, this is positive supercoiling, and the bases are held more tightly together. If they are twisted in the opposite direction, this is negative supercoiling, and the bases come apart more easily. In nature, most DNA has slight negative supercoiling that is introduced by enzymes called topoisomerases. These enzymes are also needed to relieve the twisting stresses introduced into DNA strands during processes such as transcription and DNA replication.
=== Alternative DNA structures ===
DNA exists in many possible conformations that include A-DNA, B-DNA, and Z-DNA forms, although only B-DNA and Z-DNA have been directly observed in functional organisms. The conformation that DNA adopts depends on the hydration level, DNA sequence, the amount and direction of supercoiling, chemical modifications of the bases, the type and concentration of metal ions, and the presence of polyamines in solution.
The first published reports of A-DNA X-ray diffraction patterns—and also B-DNA—used analyses based on Patterson functions that provided only a limited amount of structural information for oriented fibers of DNA. An alternative analysis was proposed by Wilkins et al. in 1953 for the in vivo B-DNA X-ray diffraction-scattering patterns of highly hydrated DNA fibers in terms of squares of Bessel functions. In the same journal, James Watson and Francis Crick presented their molecular modeling analysis of the DNA X-ray diffraction patterns to suggest that the structure was a double helix.
Although the B-DNA form is most common under the conditions found in cells, it is not a well-defined conformation but a family of related DNA conformations that occur at the high hydration levels present in cells. Their corresponding X-ray diffraction and scattering patterns are characteristic of molecular paracrystals with a significant degree of disorder.
Compared to B-DNA, the A-DNA form is a wider right-handed spiral, with a shallow, wide minor groove and a narrower, deeper major groove. The A form occurs under non-physiological conditions in partly dehydrated samples of DNA, while in the cell it may be produced in hybrid pairings of DNA and RNA strands, and in enzyme-DNA complexes. Segments of DNA where the bases have been chemically modified by methylation may undergo a larger change in conformation and adopt the Z form. Here, the strands turn about the helical axis in a left-handed spiral, the opposite of the more common B form. These unusual structures can be recognized by specific Z-DNA binding proteins and may be involved in the regulation of transcription.
=== Alternative DNA chemistry ===
For many years, exobiologists have proposed the existence of a shadow biosphere, a postulated microbial biosphere of Earth that uses radically different biochemical and molecular processes than currently known life. One of the proposals was the existence of lifeforms that use arsenic instead of phosphorus in DNA. A report in 2010 of the possibility in the bacterium GFAJ-1 was announced, though the research was disputed, and evidence suggests the bacterium actively prevents the incorporation of arsenic into the DNA backbone and other biomolecules.
=== Quadruplex structures ===
At the ends of the linear chromosomes are specialized regions of DNA called telomeres. The main function of these regions is to allow the cell to replicate chromosome ends using the enzyme telomerase, as the enzymes that normally replicate DNA cannot copy the extreme 3′ ends of chromosomes. These specialized chromosome caps also help protect the DNA ends, and stop the DNA repair systems in the cell from treating them as damage to be corrected. In human cells, telomeres are usually lengths of single-stranded DNA containing several thousand repeats of a simple TTAGGG sequence.
These guanine-rich sequences may stabilize chromosome ends by forming structures of stacked sets of four-base units, rather than the usual base pairs found in other DNA molecules. Here, four guanine bases, known as a guanine tetrad, form a flat plate. These flat four-base units then stack on top of each other to form a stable G-quadruplex structure. These structures are stabilized by hydrogen bonding between the edges of the bases and chelation of a metal ion in the centre of each four-base unit. Other structures can also be formed, with the central set of four bases coming from either a single strand folded around the bases, or several different parallel strands, each contributing one base to the central structure.
In addition to these stacked structures, telomeres also form large loop structures called telomere loops, or T-loops. Here, the single-stranded DNA curls around in a long circle stabilized by telomere-binding proteins. At the very end of the T-loop, the single-stranded telomere DNA is held onto a region of double-stranded DNA by the telomere strand disrupting the double-helical DNA and base pairing to one of the two strands. This triple-stranded structure is called a displacement loop or D-loop.
=== Branched DNA ===
In DNA, fraying occurs when non-complementary regions exist at the end of an otherwise complementary double-strand of DNA. However, branched DNA can occur if a third strand of DNA is introduced and contains adjoining regions able to hybridize with the frayed regions of the pre-existing double-strand. Although the simplest example of branched DNA involves only three strands of DNA, complexes involving additional strands and multiple branches are also possible. Branched DNA can be used in nanotechnology to construct geometric shapes, see the section on uses in technology below.
=== Artificial bases ===
Several artificial nucleobases have been synthesized, and successfully incorporated in the eight-base DNA analogue named Hachimoji DNA. Dubbed S, B, P, and Z, these artificial bases are capable of bonding with each other in a predictable way (S–B and P–Z), maintain the double helix structure of DNA, and be transcribed to RNA. Their existence could be seen as an indication that there is nothing special about the four natural nucleobases that evolved on Earth. On the other hand, DNA is tightly related to RNA which does not only act as a transcript of DNA but also performs as molecular machines many tasks in cells. For this purpose it has to fold into a structure. It has been shown that to allow to create all possible structures at least four bases are required for the corresponding RNA, while a higher number is also possible but this would be against the natural principle of least effort.
=== Acidity ===
The phosphate groups of DNA give it similar acidic properties to phosphoric acid and it can be considered as a strong acid. It will be fully ionized at a normal cellular pH, releasing protons which leave behind negative charges on the phosphate groups. These negative charges protect DNA from breakdown by hydrolysis by repelling nucleophiles which could hydrolyze it.
=== Macroscopic appearance ===
Pure DNA extracted from cells forms white, stringy clumps.
== Chemical modifications and altered DNA packaging ==
=== Base modifications and DNA packaging ===
The expression of genes is influenced by how the DNA is packaged in chromosomes, in a structure called chromatin. Base modifications can be involved in packaging, with regions that have low or no gene expression usually containing high levels of methylation of cytosine bases. DNA packaging and its influence on gene expression can also occur by covalent modifications of the histone protein core around which DNA is wrapped in the chromatin structure or else by remodeling carried out by chromatin remodeling complexes (see Chromatin remodeling). There is, further, crosstalk between DNA methylation and histone modification, so they can coordinately affect chromatin and gene expression.
For one example, cytosine methylation produces 5-methylcytosine, which is important for X-inactivation of chromosomes. The average level of methylation varies between organisms—the worm Caenorhabditis elegans lacks cytosine methylation, while vertebrates have higher levels, with up to 1% of their DNA containing 5-methylcytosine. Despite the importance of 5-methylcytosine, it can deaminate to leave a thymine base, so methylated cytosines are particularly prone to mutations. Other base modifications include adenine methylation in bacteria, the presence of 5-hydroxymethylcytosine in the brain, and the glycosylation of uracil to produce the "J-base" in kinetoplastids.
=== Damage ===
DNA can be damaged by many sorts of mutagens, which change the DNA sequence. Mutagens include oxidizing agents, alkylating agents and also high-energy electromagnetic radiation such as ultraviolet light and X-rays. The type of DNA damage produced depends on the type of mutagen. For example, UV light can damage DNA by producing thymine dimers, which are cross-links between pyrimidine bases. On the other hand, oxidants such as free radicals or hydrogen peroxide produce multiple forms of damage, including base modifications, particularly of guanosine, and double-strand breaks. A typical human cell contains about 150,000 bases that have suffered oxidative damage. Of these oxidative lesions, the most dangerous are double-strand breaks, as these are difficult to repair and can produce point mutations, insertions, deletions from the DNA sequence, and chromosomal translocations. These mutations can cause cancer. Because of inherent limits in the DNA repair mechanisms, if humans lived long enough, they would all eventually develop cancer. DNA damages that are naturally occurring, due to normal cellular processes that produce reactive oxygen species, the hydrolytic activities of cellular water, etc., also occur frequently. Although most of these damages are repaired, in any cell some DNA damage may remain despite the action of repair processes. These remaining DNA damages accumulate with age in mammalian postmitotic tissues. This accumulation appears to be an important underlying cause of aging.
Many mutagens fit into the space between two adjacent base pairs, this is called intercalation. Most intercalators are aromatic and planar molecules; examples include ethidium bromide, acridines, daunomycin, and doxorubicin. For an intercalator to fit between base pairs, the bases must separate, distorting the DNA strands by unwinding of the double helix. This inhibits both transcription and DNA replication, causing toxicity and mutations. As a result, DNA intercalators may be carcinogens, and in the case of thalidomide, a teratogen. Others such as benzo[a]pyrene diol epoxide and aflatoxin form DNA adducts that induce errors in replication. Nevertheless, due to their ability to inhibit DNA transcription and replication, other similar toxins are also used in chemotherapy to inhibit rapidly growing cancer cells.
== Biological functions ==
DNA usually occurs as linear chromosomes in eukaryotes, and circular chromosomes in prokaryotes. The set of chromosomes in a cell makes up its genome; the human genome has approximately 3 billion base pairs of DNA arranged into 46 chromosomes. The information carried by DNA is held in the sequence of pieces of DNA called genes. Transmission of genetic information in genes is achieved via complementary base pairing. For example, in transcription, when a cell uses the information in a gene, the DNA sequence is copied into a complementary RNA sequence through the attraction between the DNA and the correct RNA nucleotides. Usually, this RNA copy is then used to make a matching protein sequence in a process called translation, which depends on the same interaction between RNA nucleotides. In an alternative fashion, a cell may copy its genetic information in a process called DNA replication. The details of these functions are covered in other articles; here the focus is on the interactions between DNA and other molecules that mediate the function of the genome.
=== Genes and genomes ===
Genomic DNA is tightly and orderly packed in the process called DNA condensation, to fit the small available volumes of the cell. In eukaryotes, DNA is located in the cell nucleus, with small amounts in mitochondria and chloroplasts. In prokaryotes, the DNA is held within an irregularly shaped body in the cytoplasm called the nucleoid. The genetic information in a genome is held within genes, and the complete set of this information in an organism is called its genotype. A gene is a unit of heredity and is a region of DNA that influences a particular characteristic in an organism. Genes contain an open reading frame that can be transcribed, and regulatory sequences such as promoters and enhancers, which control transcription of the open reading frame.
In many species, only a small fraction of the total sequence of the genome encodes protein. For example, only about 1.5% of the human genome consists of protein-coding exons, with over 50% of human DNA consisting of non-coding repetitive sequences. The reasons for the presence of so much noncoding DNA in eukaryotic genomes and the extraordinary differences in genome size, or C-value, among species, represent a long-standing puzzle known as the "C-value enigma". However, some DNA sequences that do not code protein may still encode functional non-coding RNA molecules, which are involved in the regulation of gene expression.
Some noncoding DNA sequences play structural roles in chromosomes. Telomeres and centromeres typically contain few genes but are important for the function and stability of chromosomes. An abundant form of noncoding DNA in humans are pseudogenes, which are copies of genes that have been disabled by mutation. These sequences are usually just molecular fossils, although they can occasionally serve as raw genetic material for the creation of new genes through the process of gene duplication and divergence.
=== Transcription and translation ===
A gene is a sequence of DNA that contains genetic information and can influence the phenotype of an organism. Within a gene, the sequence of bases along a DNA strand defines a messenger RNA sequence, which then defines one or more protein sequences. The relationship between the nucleotide sequences of genes and the amino-acid sequences of proteins is determined by the rules of translation, known collectively as the genetic code. The genetic code consists of three-letter 'words' called codons formed from a sequence of three nucleotides (e.g. ACT, CAG, TTT).
In transcription, the codons of a gene are copied into messenger RNA by RNA polymerase. This RNA copy is then decoded by a ribosome that reads the RNA sequence by base-pairing the messenger RNA to transfer RNA, which carries amino acids. Since there are 4 bases in 3-letter combinations, there are 64 possible codons (43 combinations). These encode the twenty standard amino acids, giving most amino acids more than one possible codon. There are also three 'stop' or 'nonsense' codons signifying the end of the coding region; these are the TAG, TAA, and TGA codons, (UAG, UAA, and UGA on the mRNA).
=== Replication ===
Cell division is essential for an organism to grow, but, when a cell divides, it must replicate the DNA in its genome so that the two daughter cells have the same genetic information as their parent. The double-stranded structure of DNA provides a simple mechanism for DNA replication. Here, the two strands are separated and then each strand's complementary DNA sequence is recreated by an enzyme called DNA polymerase. This enzyme makes the complementary strand by finding the correct base through complementary base pairing and bonding it onto the original strand. As DNA polymerases can only extend a DNA strand in a 5′ to 3′ direction, different mechanisms are used to copy the antiparallel strands of the double helix. In this way, the base on the old strand dictates which base appears on the new strand, and the cell ends up with a perfect copy of its DNA.
=== Extracellular nucleic acids ===
Naked extracellular DNA (eDNA), most of it released by cell death, is nearly ubiquitous in the environment. Its concentration in soil may be as high as 2 μg/L, and its concentration in natural aquatic environments may be as high at 88 μg/L. Various possible functions have been proposed for eDNA: it may be involved in horizontal gene transfer; it may provide nutrients; and it may act as a buffer to recruit or titrate ions or antibiotics. Extracellular DNA acts as a functional extracellular matrix component in the biofilms of several bacterial species. It may act as a recognition factor to regulate the attachment and dispersal of specific cell types in the biofilm; it may contribute to biofilm formation; and it may contribute to the biofilm's physical strength and resistance to biological stress.
Cell-free fetal DNA is found in the blood of the mother, and can be sequenced to determine a great deal of information about the developing fetus.
Under the name of environmental DNA eDNA has seen increased use in the natural sciences as a survey tool for ecology, monitoring the movements and presence of species in water, air, or on land, and assessing an area's biodiversity.
=== Neutrophil extracellular traps ===
Neutrophil extracellular traps (NETs) are networks of extracellular fibers, primarily composed of DNA, which allow neutrophils, a type of white blood cell, to kill extracellular pathogens while minimizing damage to the host cells.
== Interactions with proteins ==
All the functions of DNA depend on interactions with proteins. These protein interactions can be non-specific, or the protein can bind specifically to a single DNA sequence. Enzymes can also bind to DNA and of these, the polymerases that copy the DNA base sequence in transcription and DNA replication are particularly important.
=== DNA-binding proteins ===
Structural proteins that bind DNA are well-understood examples of non-specific DNA-protein interactions. Within chromosomes, DNA is held in complexes with structural proteins. These proteins organize the DNA into a compact structure called chromatin. In eukaryotes, this structure involves DNA binding to a complex of small basic proteins called histones, while in prokaryotes multiple types of proteins are involved. The histones form a disk-shaped complex called a nucleosome, which contains two complete turns of double-stranded DNA wrapped around its surface. These non-specific interactions are formed through basic residues in the histones, making ionic bonds to the acidic sugar-phosphate backbone of the DNA, and are thus largely independent of the base sequence. Chemical modifications of these basic amino acid residues include methylation, phosphorylation, and acetylation. These chemical changes alter the strength of the interaction between the DNA and the histones, making the DNA more or less accessible to transcription factors and changing the rate of transcription. Other non-specific DNA-binding proteins in chromatin include the high-mobility group proteins, which bind to bent or distorted DNA. These proteins are important in bending arrays of nucleosomes and arranging them into the larger structures that make up chromosomes.
A distinct group of DNA-binding proteins is the DNA-binding proteins that specifically bind single-stranded DNA. In humans, replication protein A is the best-understood member of this family and is used in processes where the double helix is separated, including DNA replication, recombination, and DNA repair. These binding proteins seem to stabilize single-stranded DNA and protect it from forming stem-loops or being degraded by nucleases.
In contrast, other proteins have evolved to bind to particular DNA sequences. The most intensively studied of these are the various transcription factors, which are proteins that regulate transcription. Each transcription factor binds to one particular set of DNA sequences and activates or inhibits the transcription of genes that have these sequences close to their promoters. The transcription factors do this in two ways. Firstly, they can bind the RNA polymerase responsible for transcription, either directly or through other mediator proteins; this locates the polymerase at the promoter and allows it to begin transcription. Alternatively, transcription factors can bind enzymes that modify the histones at the promoter. This changes the accessibility of the DNA template to the polymerase.
As these DNA targets can occur throughout an organism's genome, changes in the activity of one type of transcription factor can affect thousands of genes. Consequently, these proteins are often the targets of the signal transduction processes that control responses to environmental changes or cellular differentiation and development. The specificity of these transcription factors' interactions with DNA come from the proteins making multiple contacts to the edges of the DNA bases, allowing them to "read" the DNA sequence. Most of these base-interactions are made in the major groove, where the bases are most accessible.
=== DNA-modifying enzymes ===
==== Nucleases and ligases ====
Nucleases are enzymes that cut DNA strands by catalyzing the hydrolysis of the phosphodiester bonds. Nucleases that hydrolyse nucleotides from the ends of DNA strands are called exonucleases, while endonucleases cut within strands. The most frequently used nucleases in molecular biology are the restriction endonucleases, which cut DNA at specific sequences. For instance, the EcoRV enzyme shown to the left recognizes the 6-base sequence 5′-GATATC-3′ and makes a cut at the horizontal line. In nature, these enzymes protect bacteria against phage infection by digesting the phage DNA when it enters the bacterial cell, acting as part of the restriction modification system. In technology, these sequence-specific nucleases are used in molecular cloning and DNA fingerprinting.
Enzymes called DNA ligases can rejoin cut or broken DNA strands. Ligases are particularly important in lagging strand DNA replication, as they join the short segments of DNA produced at the replication fork into a complete copy of the DNA template. They are also used in DNA repair and genetic recombination.
==== Topoisomerases and helicases ====
Topoisomerases are enzymes with both nuclease and ligase activity. These proteins change the amount of supercoiling in DNA. Some of these enzymes work by cutting the DNA helix and allowing one section to rotate, thereby reducing its level of supercoiling; the enzyme then seals the DNA break. Other types of these enzymes are capable of cutting one DNA helix and then passing a second strand of DNA through this break, before rejoining the helix. Topoisomerases are required for many processes involving DNA, such as DNA replication and transcription.
Helicases are proteins that are a type of molecular motor. They use the chemical energy in nucleoside triphosphates, predominantly adenosine triphosphate (ATP), to break hydrogen bonds between bases and unwind the DNA double helix into single strands. These enzymes are essential for most processes where enzymes need to access the DNA bases.
==== Polymerases ====
Polymerases are enzymes that synthesize polynucleotide chains from nucleoside triphosphates. The sequence of their products is created based on existing polynucleotide chains—which are called templates. These enzymes function by repeatedly adding a nucleotide to the 3′ hydroxyl group at the end of the growing polynucleotide chain. As a consequence, all polymerases work in a 5′ to 3′ direction. In the active site of these enzymes, the incoming nucleoside triphosphate base-pairs to the template: this allows polymerases to accurately synthesize the complementary strand of their template. Polymerases are classified according to the type of template that they use.
In DNA replication, DNA-dependent DNA polymerases make copies of DNA polynucleotide chains. To preserve biological information, it is essential that the sequence of bases in each copy are precisely complementary to the sequence of bases in the template strand. Many DNA polymerases have a proofreading activity. Here, the polymerase recognizes the occasional mistakes in the synthesis reaction by the lack of base pairing between the mismatched nucleotides. If a mismatch is detected, a 3′ to 5′ exonuclease activity is activated and the incorrect base removed. In most organisms, DNA polymerases function in a large complex called the replisome that contains multiple accessory subunits, such as the DNA clamp or helicases.
RNA-dependent DNA polymerases are a specialized class of polymerases that copy the sequence of an RNA strand into DNA. They include reverse transcriptase, which is a viral enzyme involved in the infection of cells by retroviruses, and telomerase, which is required for the replication of telomeres. For example, HIV reverse transcriptase is an enzyme for AIDS virus replication. Telomerase is an unusual polymerase because it contains its own RNA template as part of its structure. It synthesizes telomeres at the ends of chromosomes. Telomeres prevent fusion of the ends of neighboring chromosomes and protect chromosome ends from damage.
Transcription is carried out by a DNA-dependent RNA polymerase that copies the sequence of a DNA strand into RNA. To begin transcribing a gene, the RNA polymerase binds to a sequence of DNA called a promoter and separates the DNA strands. It then copies the gene sequence into a messenger RNA transcript until it reaches a region of DNA called the terminator, where it halts and detaches from the DNA. As with human DNA-dependent DNA polymerases, RNA polymerase II, the enzyme that transcribes most of the genes in the human genome, operates as part of a large protein complex with multiple regulatory and accessory subunits.
== Genetic recombination ==
A DNA helix usually does not interact with other segments of DNA, and in human cells, the different chromosomes even occupy separate areas in the nucleus called "chromosome territories". This physical separation of different chromosomes is important for the ability of DNA to function as a stable repository for information, as one of the few times chromosomes interact is in chromosomal crossover which occurs during sexual reproduction, when genetic recombination occurs. Chromosomal crossover is when two DNA helices break, swap a section and then rejoin.
Recombination allows chromosomes to exchange genetic information and produces new combinations of genes, which increases the efficiency of natural selection and can be important in the rapid evolution of new proteins. Genetic recombination can also be involved in DNA repair, particularly in the cell's response to double-strand breaks.
The most common form of chromosomal crossover is homologous recombination, where the two chromosomes involved share very similar sequences. Non-homologous recombination can be damaging to cells, as it can produce chromosomal translocations and genetic abnormalities. The recombination reaction is catalyzed by enzymes known as recombinases, such as RAD51. The first step in recombination is a double-stranded break caused by either an endonuclease or damage to the DNA. A series of steps catalyzed in part by the recombinase then leads to joining of the two helices by at least one Holliday junction, in which a segment of a single strand in each helix is annealed to the complementary strand in the other helix. The Holliday junction is a tetrahedral junction structure that can be moved along the pair of chromosomes, swapping one strand for another. The recombination reaction is then halted by cleavage of the junction and re-ligation of the released DNA. Only strands of like polarity exchange DNA during recombination. There are two types of cleavage: east-west cleavage and north–south cleavage. The north–south cleavage nicks both strands of DNA, while the east–west cleavage has one strand of DNA intact. The formation of a Holliday junction during recombination makes it possible for genetic diversity, genes to exchange on chromosomes, and expression of wild-type viral genomes.
== Evolution ==
DNA contains the genetic information that allows all forms of life to function, grow and reproduce. However, it is unclear how long in the 4-billion-year history of life DNA has performed this function, as it has been proposed that the earliest forms of life may have used RNA as their genetic material. RNA may have acted as the central part of early cell metabolism as it can both transmit genetic information and carry out catalysis as part of ribozymes. This ancient RNA world where nucleic acid would have been used for both catalysis and genetics may have influenced the evolution of the current genetic code based on four nucleotide bases. This would occur, since the number of different bases in such an organism is a trade-off between a small number of bases increasing replication accuracy and a large number of bases increasing the catalytic efficiency of ribozymes. However, there is no direct evidence of ancient genetic systems, as recovery of DNA from most fossils is impossible because DNA survives in the environment for less than one million years, and slowly degrades into short fragments in solution. Claims for older DNA have been made, most notably a report of the isolation of a viable bacterium from a salt crystal 250 million years old, but these claims are controversial.
Building blocks of DNA (adenine, guanine, and related organic molecules) may have been formed extraterrestrially in outer space. Complex DNA and RNA organic compounds of life, including uracil, cytosine, and thymine, have also been formed in the laboratory under conditions mimicking those found in outer space, using starting chemicals, such as pyrimidine, found in meteorites. Pyrimidine, like polycyclic aromatic hydrocarbons (PAHs), the most carbon-rich chemical found in the universe, may have been formed in red giants or in interstellar cosmic dust and gas clouds.
Ancient DNA has been recovered from ancient organisms at a timescale where genome evolution can be directly observed, including from extinct organisms up to millions of years old, such as the woolly mammoth.
== Uses in technology ==
=== Genetic engineering ===
Methods have been developed to purify DNA from organisms, such as phenol-chloroform extraction, and to manipulate it in the laboratory, such as restriction digests and the polymerase chain reaction. Modern biology and biochemistry make intensive use of these techniques in recombinant DNA technology. Recombinant DNA is a man-made DNA sequence that has been assembled from other DNA sequences. They can be transformed into organisms in the form of plasmids or in the appropriate format, by using a viral vector. The genetically modified organisms produced can be used to produce products such as recombinant proteins, used in medical research, or be grown in agriculture.
=== DNA profiling ===
Forensic scientists can use DNA in blood, semen, skin, saliva or hair found at a crime scene to identify a matching DNA of an individual, such as a perpetrator. This process is formally termed DNA profiling, also called DNA fingerprinting. In DNA profiling, the lengths of variable sections of repetitive DNA, such as short tandem repeats and minisatellites, are compared between people. This method is usually an extremely reliable technique for identifying a matching DNA. However, identification can be complicated if the scene is contaminated with DNA from several people. DNA profiling was developed in 1984 by British geneticist Sir Alec Jeffreys, and first used in forensic science to convict Colin Pitchfork in the 1988 Enderby murders case.
The development of forensic science and the ability to now obtain genetic matching on minute samples of blood, skin, saliva, or hair has led to re-examining many cases. Evidence can now be uncovered that was scientifically impossible at the time of the original examination. Combined with the removal of the double jeopardy law in some places, this can allow cases to be reopened where prior trials have failed to produce sufficient evidence to convince a jury. People charged with serious crimes may be required to provide a sample of DNA for matching purposes. The most obvious defense to DNA matches obtained forensically is to claim that cross-contamination of evidence has occurred. This has resulted in meticulous strict handling procedures with new cases of serious crime.
DNA profiling is also used successfully to positively identify victims of mass casualty incidents, bodies or body parts in serious accidents, and individual victims in mass war graves, via matching to family members.
DNA profiling is also used in DNA paternity testing to determine if someone is the biological parent or grandparent of a child with the probability of parentage is typically 99.99% when the alleged parent is biologically related to the child. Normal DNA sequencing methods happen after birth, but there are new methods to test paternity while a mother is still pregnant.
=== DNA enzymes or catalytic DNA ===
Deoxyribozymes, also called DNAzymes or catalytic DNA, were first discovered in 1994. They are mostly single stranded DNA sequences isolated from a large pool of random DNA sequences through a combinatorial approach called in vitro selection or systematic evolution of ligands by exponential enrichment (SELEX). DNAzymes catalyze variety of chemical reactions including RNA-DNA cleavage, RNA-DNA ligation, amino acids phosphorylation-dephosphorylation, carbon-carbon bond formation, etc. DNAzymes can enhance catalytic rate of chemical reactions up to 100,000,000,000-fold over the uncatalyzed reaction. The most extensively studied class of DNAzymes is RNA-cleaving types which have been used to detect different metal ions and designing therapeutic agents. Several metal-specific DNAzymes have been reported including the GR-5 DNAzyme (lead-specific), the CA1-3 DNAzymes (copper-specific), the 39E DNAzyme (uranyl-specific) and the NaA43 DNAzyme (sodium-specific). The NaA43 DNAzyme, which is reported to be more than 10,000-fold selective for sodium over other metal ions, was used to make a real-time sodium sensor in cells.
=== Bioinformatics ===
Bioinformatics involves the development of techniques to store, data mine, search and manipulate biological data, including DNA nucleic acid sequence data. These have led to widely applied advances in computer science, especially string searching algorithms, machine learning, and database theory. String searching or matching algorithms, which find an occurrence of a sequence of letters inside a larger sequence of letters, were developed to search for specific sequences of nucleotides. The DNA sequence may be aligned with other DNA sequences to identify homologous sequences and locate the specific mutations that make them distinct. These techniques, especially multiple sequence alignment, are used in studying phylogenetic relationships and protein function. Data sets representing entire genomes' worth of DNA sequences, such as those produced by the Human Genome Project, are difficult to use without the annotations that identify the locations of genes and regulatory elements on each chromosome. Regions of DNA sequence that have the characteristic patterns associated with protein- or RNA-coding genes can be identified by gene finding algorithms, which allow researchers to predict the presence of particular gene products and their possible functions in an organism even before they have been isolated experimentally. Entire genomes may also be compared, which can shed light on the evolutionary history of particular organism and permit the examination of complex evolutionary events.
=== DNA nanotechnology ===
DNA nanotechnology uses the unique molecular recognition properties of DNA and other nucleic acids to create self-assembling branched DNA complexes with useful properties. DNA is thus used as a structural material rather than as a carrier of biological information. This has led to the creation of two-dimensional periodic lattices (both tile-based and using the DNA origami method) and three-dimensional structures in the shapes of polyhedra. Nanomechanical devices and algorithmic self-assembly have also been demonstrated, and these DNA structures have been used to template the arrangement of other molecules such as gold nanoparticles and streptavidin proteins. DNA and other nucleic acids are the basis of aptamers, synthetic oligonucleotide ligands for specific target molecules used in a range of biotechnology and biomedical applications.
=== History and anthropology ===
Because DNA collects mutations over time, which are then inherited, it contains historical information, and, by comparing DNA sequences, geneticists can infer the evolutionary history of organisms, their phylogeny. This field of phylogenetics is a powerful tool in evolutionary biology. If DNA sequences within a species are compared, population geneticists can learn the history of particular populations. This can be used in studies ranging from ecological genetics to anthropology.
=== Information storage ===
DNA as a storage device for information has enormous potential since it has much higher storage density compared to electronic devices. However, high costs, slow read and write times (memory latency), and insufficient reliability has prevented its practical use.
== History ==
DNA was first isolated by the Swiss physician Friedrich Miescher who, in 1869, discovered a microscopic substance in the pus of discarded surgical bandages. As it resided in the nuclei of cells, he called it "nuclein". In 1878, Albrecht Kossel isolated the non-protein component of "nuclein", nucleic acid, and later isolated its five primary nucleobases.
In 1909, Phoebus Levene identified the base, sugar, and phosphate nucleotide unit of RNA (then named "yeast nucleic acid"). In 1929, Levene identified deoxyribose sugar in "thymus nucleic acid" (DNA). Levene suggested that DNA consisted of a string of four nucleotide units linked together through the phosphate groups ("tetranucleotide hypothesis"). Levene thought the chain was short and the bases repeated in a fixed order. In 1927, Nikolai Koltsov proposed that inherited traits would be inherited via a "giant hereditary molecule" made up of "two mirror strands that would replicate in a semi-conservative fashion using each strand as a template". In 1928, Frederick Griffith in his experiment discovered that traits of the "smooth" form of Pneumococcus could be transferred to the "rough" form of the same bacteria by mixing killed "smooth" bacteria with the live "rough" form. This system provided the first clear suggestion that DNA carries genetic information.
In 1933, while studying virgin sea urchin eggs, Jean Brachet suggested that DNA is found in the cell nucleus and that RNA is present exclusively in the cytoplasm. At the time, "yeast nucleic acid" (RNA) was thought to occur only in plants, while "thymus nucleic acid" (DNA) only in animals. The latter was thought to be a tetramer, with the function of buffering cellular pH.
In 1937, William Astbury produced the first X-ray diffraction patterns that showed that DNA had a regular structure.
In 1943, Oswald Avery, along with co-workers Colin MacLeod and Maclyn McCarty, identified DNA as the transforming principle, supporting Griffith's suggestion (Avery–MacLeod–McCarty experiment). Erwin Chargaff developed and published observations now known as Chargaff's rules, stating that in DNA from any species of any organism, the amount of guanine should be equal to cytosine and the amount of adenine should be equal to thymine.
Late in 1951, Francis Crick started working with James Watson at the Cavendish Laboratory within the University of Cambridge. DNA's role in heredity was confirmed in 1952 when Alfred Hershey and Martha Chase in the Hershey–Chase experiment showed that DNA is the genetic material of the enterobacteria phage T2.
In May 1952, Raymond Gosling, a graduate student working under the supervision of Rosalind Franklin, took an X-ray diffraction image, labeled as "Photo 51", at high hydration levels of DNA. This photo was given to Watson and Crick by Maurice Wilkins and was critical to their obtaining the correct structure of DNA. Franklin told Crick and Watson that the backbones had to be on the outside. Before then, Linus Pauling, and Watson and Crick, had erroneous models with the chains inside and the bases pointing outwards. Franklin's identification of the space group for DNA crystals revealed to Crick that the two DNA strands were antiparallel. In February 1953, Linus Pauling and Robert Corey proposed a model for nucleic acids containing three intertwined chains, with the phosphates near the axis, and the bases on the outside. Watson and Crick completed their model, which is now accepted as the first correct model of the double helix of DNA. On 28 February 1953 Crick interrupted patrons' lunchtime at The Eagle pub in Cambridge, England to announce that he and Watson had "discovered the secret of life".
The 25 April 1953 issue of the journal Nature published a series of five articles giving the Watson and Crick double-helix structure DNA and evidence supporting it. The structure was reported in a letter titled "MOLECULAR STRUCTURE OF NUCLEIC ACIDS A Structure for Deoxyribose Nucleic Acid", in which they said, "It has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material." This letter was followed by a letter from Franklin and Gosling, which was the first publication of their own X-ray diffraction data and of their original analysis method. Then followed a letter by Wilkins and two of his colleagues, which contained an analysis of in vivo B-DNA X-ray patterns, and which supported the presence in vivo of the Watson and Crick structure.
In April 2023, scientists, based on new evidence, concluded that Rosalind Franklin was a contributor and "equal player" in the discovery process of DNA, rather than otherwise, as may have been presented subsequently after the time of the discovery.
In 1962, after Franklin's death, Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine. Nobel Prizes are awarded only to living recipients. A debate continues about who should receive credit for the discovery.
In an influential presentation in 1957, Crick laid out the central dogma of molecular biology, which foretold the relationship between DNA, RNA, and proteins, and articulated the "adaptor hypothesis". Final confirmation of the replication mechanism that was implied by the double-helical structure followed in 1958 through the Meselson–Stahl experiment. Further work by Crick and co-workers showed that the genetic code was based on non-overlapping triplets of bases, called codons, allowing Har Gobind Khorana, Robert W. Holley, and Marshall Warren Nirenberg to decipher the genetic code. These findings represent the birth of molecular biology.
In 1986, DNA analysis was first used in a criminal investigation when police in the UK requested Alec Jeffreys of the University of Leicester to prove or disprove the involvement in a particular case of a suspect who claimed innocence in the matter. Although the suspect had already confessed to committing a recent rape-murder, he was denying any involvement in a similar crime committed three years earlier. Yet the details of the two cases were so alike that the police concluded both crimes had been committed by the same person. However, all charges against the suspect were dropped when Jeffreys' DNA testing exonerated the suspect — from both the earlier murder and the one to which he'd confessed. Further such DNA profiling led to positive identification of another suspect who, in 1988, was found guilty of both rape-murders.
== See also ==
== References ==
== Further reading ==
== External links ==
DNA binding site prediction on protein
DNA the Double Helix Game From the official Nobel Prize web site
DNA under electron microscope
Dolan DNA Learning Center
Double Helix: 50 years of DNA, Nature
Proteopedia DNA
Proteopedia Forms_of_DNA
ENCODE threads explorer ENCODE home page at Nature
Double Helix 1953–2003 National Centre for Biotechnology Education
Genetic Education Modules for Teachers – DNA from the Beginning Study Guide
PDB Molecule of the Month DNA
"Clue to chemistry of heredity found". The New York Times, June 1953. First American newspaper coverage of the discovery of the DNA structure
DNA from the Beginning Another DNA Learning Center site on DNA, genes, and heredity from Mendel to the human genome project.
The Register of Francis Crick Personal Papers 1938 – 2007 at Mandeville Special Collections Library, University of California, San Diego
Seven-page, handwritten letter that Crick sent to his 12-year-old son Michael in 1953 describing the structure of DNA. See Crick's medal goes under the hammer, Nature, 5 April 2013. | Wikipedia/SsDNA |
Extrachromosomal circular DNA (eccDNA) is a type of double-stranded circular DNA structure that was first discovered in 1964 by Alix Bassel and Yasuo Hotta. In contrast to previously identified circular DNA structures (e.g., bacterial plasmids, mitochondrial DNA, circular bacterial chromosomes, or chloroplast DNA), eccDNA are circular DNA found in the eukaryotic nuclei of plant and animal (including human) cells. Extrachromosomal circular DNA is derived from chromosomal DNA, can range in size from 50 base pairs to several mega-base pairs in length, and can encode regulatory elements and full-length genes. eccDNA has been observed in various eukaryotic species and it is proposed to be a byproduct of programmed DNA recombination events, such as V(D)J recombination.
== Historical Background ==
In 1964, Bassel and Hotta published their initial discovery of eccDNA that they made while researching Franklin Stahl’s chromosomal theory. In their experiments, they visualized isolated wheat nuclei and boar sperm by using electron microscopy. Their research found that boar sperm cells contained eccDNA of various sizes. In 1965, Arthur Spriggs’ research group identified eccDNA in the samples of five pediatric patients’ embryonic tumors and one adult patient’s bronchial carcinoma. In the following years, additional research led to the discovery of eccDNA in various species listed in Table 1:
=== 21st Century Research ===
In the 21st century, researchers have focused on better characterizing the specific subtypes of eccDNA, as well as the structure and function of these molecules within biological systems:
In 2012, Shibata et al. discovered a specific type of eccDNA called microDNA. The researchers found tens of thousands of microDNAs in mouse tissues and cell lines, as well as human cell lines.
In 2017, Turner et al. identified using whole-genome sequencing (WGS), cytogenetic analysis, and structural modeling that extrachromosomal circular DNA is highly amplified and common in various types of cancers. They found that eccDNA molecules have significant heterogeneity between different cells even if they are derived from the same individual. Furthermore, these eccDNA molecules contained tumor-driving genes and were reported to be rarely found in non-cancerous tissues.
In 2018, Møller et al. used healthy human muscle and blood cell samples to identify over 100,000 types of eccDNA, which suggested that eccDNA could be found within somatic cells ubiquitously.
In 2019, Wu et al. found that ecDNA (subtype of eccDNA) associates with chromatin, but unlike chromosomes it does not have higher-order compaction, which increases its accessibility.
In 2021, Wang et al. elaborated on the formation of eccDNAs and identified the immunostimulant function of eccDNAs. They also developed an improved eccDNA purification protocol that decreases linear DNA contamination within purified samples.
=== eccDNA Purification ===
Historically, eccDNA was purified using a two-step procedure that involved first isolating crude extrachromosomal DNA and subsequently digesting linear DNA via exonuclease digestion. Yet, this technique often results in linear DNA contamination because exonuclease digestion is not sufficient to remove all linear DNA. In 2021, Wang et al. developed a three-step eccDNA enrichment method that improved eccDNA purification:
The cells were first dehydrated in > 90% methanol. To extract crude extrachromosomal DNA, the cells were lysed with a pH 11.8 alkaline lysis buffer, neutralized with a neutralization buffer, and precipitated using a precipitation buffer. A commercial plasmid purification kit's silica column was used to isolate DNA from other cell components.
The eluted DNA was digested with the restriction enzyme PacI to linearize mitochondrial DNA (mtDNA) and an exonuclease that can digest linear DNA.
Finally, circular DNA was selectively recovered by a commercial solution and silica beads to remove linear DNA that was not removed by exonuclease digestion.
=== Double minutes (DM) vs. extrachromosomal circular DNA (eccDNA) ===
Initially, the term double minutes (DM) was commonly used to refer to extrachromosomal circular DNA because it often appeared as a pair in early studies. As research has continued, different subtypes of extrachromosomal circular DNA have been identified that are not double minutes (e.g., microDNA). In 2014, Barreto et al. identified that double minutes only comprise roughly 30% of extrachromosomal DNA. Thus, the term extrachromosomal circular DNA (eccDNA) is becoming more widely used, while the term double minutes is now reserved for a specific subtype of eccDNA.
== Structure ==
eccDNA are circular DNA that have been found in human, plant, and animal cells and are present in the cell nucleus in addition to the chromosomal DNA. eccDNA is distinguishable from other circular DNA in cells, such as mitochondrial DNA (mtDNA), because it ranges in size from a few hundred bases to megabases and is derived from genomic DNA. For example, eccDNA can be formed from exons of protein coding genes, like mucin and titin. Researchers have hypothesized that eccDNA may contribute to the expression of different isoforms of a gene by interfering with or promoting the transcription of specific exons.
eccDNA has been classified as one of four different categories of circular DNA based on size and sequence, including small polydispersed circular DNA (spcDNA), telomeric circles (t-circles), microDNA (100-400 bp), and extrachromosomal DNA (ecDNA). Each of these types has its own unique biological characteristics (see Table 2):
=== eccDNA biogenesis ===
While the exact mechanism for eccDNA generation is still unknown, some studies have suggested that eccDNA generation might be linked to DNA damage repair, hyper-transcription, homologous recombination, and replication stress. There are multiple proposed mechanisms for eccDNA formation: (1) replication slippage creates a loop on the template strand that is then excised and ligated into a circle leaving a microdeletion on the chromosome, (2) replication slippage creates a loop in the product strand that is excised and ligated into a circle that does not generate a microdeletion in the chromosome, (3) the ODERA mechanism of eccDNA formation, and (4) a double stranded break in a repeat region is repaired by homologous recombination, during which the fragment forms a circle and the chromosome suffers a microdeletion
Research conducted in 2021 demonstrated that apoptotic cells are a source of eccDNAs; this was concluded on account of the study showing that apoptotic DNA fragmentation (ADF) is a prerequisite for eccDNA formation through purification methods.
eccDNA can be generated as a result of micro-nuclei formation, indicating chromosomal instability. It has been proposed that premature apoptosis and/or errors in chromosomal segregation during mitosis could lead to micro-nuclei formation.
=== eccDNA in non-cancerous cells ===
To test whether eccDNAs occur in non-cancer cells, mouse embryonic stem cells and Southern Blot analysis were used; the results confirmed that eccDNA is found in both cancerous and non-cancerous cells. It is also known that eccDNA is unlikely to be derived from specific genome regions; sequencing data from 2021 reports that the data suggests eccDNAs are widespread across the entirety of the genome. Genome mapping of full-length eccDNAs demonstrated their different genomic alignment patterns, which includes at adjacent, overlapped, or nested positions on the same chromosome or across different chromosomes. eccDNAs originate mostly from single, continuous genomic loci, meaning that one single genomic fragment self-circularizes to form the eccDNA, rather than being formed from ligation of different genomic fragments. These two variants can be classified as continuous and non-continuous eccDNAs, respectively. To further understand the reason behind the circularization of fragmented DNA, the three various mammalian ligase enzymes were tested: Lig1, Lig3, and Lig4. Using knockout models in the CH12F3 mouse B-lymphocyte cell line, research conducted in 2021 identified Lig3 as the main ligase for eccDNA generation in these cells.
== Function ==
The exact function of eccDNA has been debated, but some studies have suggested that eccDNAs might contribute to gene amplification in cancer, immune function, and aging.
=== eccDNA function in immune system ===
According to research conducted in 2021, another function of eccDNAs is their role as possible immunostimulants. eccDNA significantly induces type I interferons (IFNα, IFNβ), interleukin-6 (IL-6), and tumor necrosis factor (TNF), even more so than linear DNA and other generally potent cytokine inducers at their highest concentration levels. Similar patterns are observed with macrophages as the data showed that eccDNAs are very potent immunostimulants in activating both bone marrow-derived dendritic cells and bone marrow-derived macrophages. Additionally, experiments altered the eccDNA structure with one nick per eccDNA segment and subsequently treated with enzymes to generate linear versions of the eccDNA. In these experiments, cytokine transcription, an important marker for immune system activity, was shown to be much higher in the non-treated eccDNA compared to the linearized treatment, conferring that the circular structure of eccDNA rather than the genetic sequence itself gives the eccDNA its immune function.
=== eccDNA function in cancer ===
Some known functions of eccDNA include contributions to intercellular genetic heterogeneity in tumors, and more specifically the amplification of oncogenes and drug-resistant genes. This also supports that the genes on eccDNA are expressed. Overall, eccDNA has been linked to cancer and drug resistance, aging, gene compensation, and for this reason it continues to be a significant topic of discussion.
== Applications ==
=== Role in cancer ===
A subtype of eccDNA, such as ecDNA, ribosomal DNA locus (Extrachromosomal rDNA circle), and double minutes have been associated with genomic instability. Double minute ecDNAs are fragments of extrachromosomal DNA, which were originally observed in a large number of human tumors including breast, lung, ovary, colon, and most notably, neuroblastoma. They are a manifestation of gene amplification during the development of tumors, which give the cells selective advantages for growth and survival. Double minutes, like actual chromosomes, are composed of chromatin and replicate in the nucleus of the cell during cell division. Unlike typical chromosomes, they are composed of circular fragments of DNA, up to only a few million base pairs in size and contain no centromere or telomere.
Double minute chromosomes (DMs), which present as paired chromatin bodies under light microscopy, have been shown to be a subset of ecDNA. Double minute chromosomes represent about 30% of the cancer-containing spectrum of ecDNA, including single bodies, and have been found to contain identical gene content as single bodies. The ecDNA notation encompasses all forms of the large gene-containing extrachromosomal DNA found in cancer cells. This type of ecDNA is commonly seen in cancer cells of various histologies, but virtually never in normal tissue. ecDNA are thought to be produced through double-strand breaks in chromosomes or over replication of DNA in an organism.
The circular shape of ecDNA differs from the linear structure of chromosomal DNA in meaningful ways that influence cancer pathogenesis. Oncogenes encoded on ecDNA have massive transcriptional output, ranking in the top 1% of genes in the entire transcriptome. In contrast to bacterial plasmids or mitochondrial DNA, ecDNA are chromatinized, containing high levels of active histone marks, but a paucity of repressive histone marks. The ecDNA chromatin architecture lacks the higher-order compaction that is present on chromosomal DNA and is among the most accessible DNA in the entire cancer genome.
From eccDNA, matrix attachment regions (MARs) were found to activate amplification of oncogenes. Transfection of these MARs into human embryonic kidney 293T cells resulted in an increase in gene expression, suggesting that these eccDNA-derived MARs are involved in oncogene activation. eccDNA also appears to play a role in other cancers such as breast cancer, where oncogenes in human epidermal growth factor receptor 2 (HER2)-positive breast cancer genes in eccDNA are amplified. This eccDNA has also shown the ability to acquire resistance to therapies for receptor tyrosine kinases (RTKs), like HER26.
=== Role in aging ===
Yeast are model organisms for studying aging, and eccDNAs have been shown to accumulate in old cells and play a role in causing aging in yeast. Speculation continues on the generality of this concept in higher species, like mammals.
== See also ==
Extrachromosomal DNA
Extrachromosomal rDNA circle
Double minute
microDNA
Selfish genetic elements
== References ==
ref 36 Altungöz; Yüksel (September 2023). "Gene amplifications and extrachromosomal circular DNAs: function and biogenesis". Molecular Biology Reports. 50 (9): 7693–7703. doi:10.1007/s11033-023-08649-1. PMID 37433908 – via Springer.
== Further reading ==
Yüksel A, Altungöz O (September 2023). "Gene amplifications and extrachromosomal circular DNAs: function and biogenesis". Mol Biology Reports. 50 (9): 7693–7703. doi:10.1007/s11033-023-08649-1. PMID 37433908. | Wikipedia/Extrachromosomal_circular_DNA |
The mold, protozoan, and coelenterate mitochondrial code and the mycoplasma/spiroplasma code (translation table 4) is the genetic code used by various organisms, in some cases with slight variations, notably the use of UGA as a tryptophan codon rather than a stop codon.
== The code ==
AAs = FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG
Starts = --MM---------------M------------MMMM---------------M------------
Base1 = TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG
Base2 = TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG
Base3 = TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG
Bases: adenine (A), cytosine (C), guanine (G) and thymine (T) or uracil (U).
Amino acids: Alanine (Ala, A), Arginine (Arg, R), Asparagine (Asn, N), Aspartic acid (Asp, D), Cysteine (Cys, C), Glutamic acid (Glu, E), Glutamine (Gln, Q), Glycine (Gly, G), Histidine (His, H), Isoleucine (Ile, I), Leucine (Leu, L), Lysine (Lys, K), Methionine (Met, M), Phenylalanine (Phe, F), Proline (Pro, P), Serine (Ser, S), Threonine (Thr, T), Tryptophan (Trp, W), Tyrosine (Tyr, Y), Valine (Val, V).
== Differences from the standard code ==
=== Alternative initiation codons ===
Trypanosoma: UUA, UUG, CUG ;
Leishmania: AUU, AUA ;
Tetrahymena: AUU, AUA, AUG ;
Paramecium: AUU, AUA, AUG, AUC, GUG, GUA(?).
(Pritchard et al., 1990)
== Systematic range ==
Bacteria: The code is used in Entomoplasmatales and Mycoplasmatales (Bove et al. 1989). The situation in the Acholeplasmatales is unclear. Based on a study of ribosomal protein genes, it had been concluded that UGA does not code for tryptophan in plant-pathogenic mycoplasma-like organisms (MLO) and the Acholeplasmataceae (Lim and Sears, 1992) and there seems to be only a single tRNA-CCA for tryptophan in Acholeplasma laidlawii (Tanaka et al. 1989). In contrast, in a study of codon usage in Phytoplasmas, it was found that 30 out of 78 open reading frames analysed translated better with this code (UGA for tryptophan) than with the bacterial, archaeal and plant plastid code while the remainder showed no differences between the two codes (Melamed et al. 2003). In addition, the coding reassignment of UGA Stop → Trp can be found in an alpha-proteobacterial symbiont of cicadas: Candidatus Hodgkinia cicadicola (McCutcheon et al. 2009). Mycoplasma pneumoniae also uses the codon UGA to code for tryptophan rather than using it as a stop codon.
Fungi: Emericella nidulans, Neurospora crassa, Podospora anserina, Acremonium (Fox, 1987), Candida parapsilosis (Guelin et al., 1991), Trichophyton rubrum (de Bievre and Dujon, 1992), Dekkera/Brettanomyces, Eeniella (Hoeben et al., 1993), and probably Ascobolus immersus, Aspergillus amstelodami, Claviceps purpureaand Cochliobolus heterostrophus.
Protists: the red algae of Gigartinales (Boyen et al. 1994), the protozoa Trypanosoma brucei, Leishmania tarentolae, Paramecium tetraurelia, Tetrahymena pyriformis and probably Plasmodium gallinaceum (Aldritt et al., 1989), and the stramenopile Cafileria marina.
Metazoa: Coelenterata (Ctenophora and Cnidaria).
Other: this code is also used for the kinetoplast DNA (maxicircles, minicircles). Kinetoplasts are modified mitochondria (or their parts).
== See also ==
List of genetic codes
== References ==
This article incorporates text from the United States National Library of Medicine, which is in the public domain. | Wikipedia/The_mold,_protozoan,_and_coelenterate_mitochondrial_code_and_the_mycoplasma/spiroplasma_code |
A DNA vaccine is a type of vaccine that transfects a specific antigen-coding DNA sequence into the cells of an organism as a mechanism to induce an immune response.
DNA vaccines work by injecting genetically engineered plasmid containing the DNA sequence encoding the antigen(s) against which an immune response is sought, so the cells directly produce the antigen, thus causing a protective immunological response. DNA vaccines have theoretical advantages over conventional vaccines, including the "ability to induce a wider range of types of immune response". Several DNA vaccines have been tested for veterinary use. In some cases, protection from disease in animals has been obtained, in others not. Research is ongoing over the approach for viral, bacterial and parasitic diseases in humans, as well as for cancers. In August 2021, Indian authorities gave emergency approval to ZyCoV-D. Developed by Cadila Healthcare, it is the first DNA vaccine approved for humans.
== History ==
Conventional vaccines contain either specific antigens from a pathogen, or attenuated viruses which stimulate an immune response in the vaccinated organism. DNA vaccines are members of the genetic vaccines, because they contain a genetic information (DNA or RNA) that codes for the cellular production (protein biosynthesis) of an antigen. DNA vaccines contain DNA that codes for specific antigens from a pathogen. The DNA is injected into the body and taken up by cells, whose normal metabolic processes synthesize proteins based on the genetic code in the plasmid that they have taken up. Because these proteins contain regions of amino acid sequences that are characteristic of bacteria or viruses, they are recognized as foreign and when they are processed by the host cells and displayed on their surface, the immune system is alerted, which then triggers immune responses. Alternatively, the DNA may be encapsulated in protein to facilitate cell entry. If this capsid protein is included in the DNA, the resulting vaccine can combine the potency of a live vaccine without reversion risks.
In 1983, Enzo Paoletti and Dennis Panicali at the New York Department of Health devised a strategy to produce recombinant DNA vaccines by using genetic engineering to transform ordinary smallpox vaccine into vaccines that may be able to prevent other diseases. They altered the DNA of cowpox virus by inserting a gene from other viruses (namely Herpes simplex virus, hepatitis B and influenza). In 1993, Jeffrey Ulmer and co-workers at Merck Research Laboratories demonstrated that direct injection of mice with plasmid DNA encoding a flu antigen protected the animals against subsequent experimental infection with influenza virus. In 2016 a DNA vaccine for the Zika virus began testing in humans at the National Institutes of Health. The study was planned to involve up to 120 subjects aged between 18 and 35. Separately, Inovio Pharmaceuticals and GeneOne Life Science began tests of a different DNA vaccine against Zika in Miami. The NIH vaccine is injected into the upper arm under high pressure. Manufacturing the vaccines in volume remained unsolved as of August 2016. Clinical trials for DNA vaccines to prevent HIV are underway.
In August 2021, Indian authorities gave emergency approval to ZyCoV-D. Developed by Cadila Healthcare, it is the first DNA vaccine against COVID-19.
== Applications ==
As of 2021 no DNA vaccines have been approved for human use in the United States. Few experimental trials have evoked a response strong enough to protect against disease and the technique's usefulness remains to be proven in humans.
A veterinary DNA vaccine to protect horses from West Nile virus has been approved. Another West Nile virus vaccine has been tested successfully on American robins.
DNA immunization is also being investigated as a means of developing antivenom sera. DNA immunization can be used as a technology platform for monoclonal antibody induction.
== Advantages ==
No risk for infections
Antigen presentation by both MHC class I and class II molecules
Polarise T-cell response toward type 1 or type 2
Immune response focused on the antigen of interest
Ease of development and production
Stability for storage and shipping
Cost-effectiveness
Obviates need for peptide synthesis, expression and purification of recombinant proteins and use of toxic adjuvants
Long-term persistence of immunogen
In vivo expression ensures protein more closely resembles normal eukaryotic structure, with accompanying post-translational modifications
== Disadvantages ==
Limited to protein immunogens (not useful for non-protein based antigens such as bacterial polysaccharides)
Potential for atypical processing of bacterial and parasite proteins
Potential when using nasal spray administration of plasmid DNA nanoparticles to transfect non-target cells, such as brain cells
Cross-contamination when manufacturing different types of live vaccines in same facility
== Plasmid vectors ==
=== Vector design ===
DNA vaccines elicit the best immune response when high-expression vectors are used. These are plasmids that usually consist of a strong viral promoter to drive the in vivo transcription and translation of the gene (or complementary DNA) of interest. Intron A may sometimes be included to improve mRNA stability and hence increase protein expression. Plasmids also include a strong polyadenylation/transcriptional termination signal, such as bovine growth hormone or rabbit beta-globulin polyadenylation sequences. Polycistronic vectors (with multiple genes of interest) are sometimes constructed to express more than one immunogen, or to express an immunogen and an immunostimulatory protein.
Because the plasmid – carrying relatively small genetic code up to about 200 Kbp – is the "vehicle" from which the immunogen is expressed, optimising vector design for maximal protein expression is essential. One way of enhancing protein expression is by optimising the codon usage of pathogenic mRNAs for eukaryotic cells. Pathogens often have different AT-contents than the target species, so altering the gene sequence of the immunogen to reflect the codons more commonly used in the target species may improve its expression.
Another consideration is the choice of promoter. The SV40 promoter was conventionally used until research showed that vectors driven by the Rous Sarcoma Virus (RSV) promoter had much higher expression rates. More recently, expression and immunogenicity have been further increased in model systems by the use of the cytomegalovirus (CMV) immediate early promoter, and a retroviral cis-acting transcriptional element. Additional modifications to improve expression rates include the insertion of enhancer sequences, synthetic introns, adenovirus tripartite leader (TPL) sequences and modifications to the polyadenylation and transcriptional termination sequences. An example of DNA vaccine plasmid is pVAC, which uses SV40 promoter.
Structural instability phenomena are of particular concern for plasmid manufacture, DNA vaccination and gene therapy. Accessory regions pertaining to the plasmid backbone may engage in a wide range of structural instability phenomena. Well-known catalysts of genetic instability include direct, inverted and tandem repeats, which are conspicuous in many commercially available cloning and expression vectors. Therefore, the reduction or complete elimination of extraneous noncoding backbone sequences would pointedly reduce the propensity for such events to take place and consequently the overall plasmid's recombinogenic potential.
=== Mechanism of plasmids ===
Once the plasmid inserts itself into the transfected cell nucleus, it codes for a peptide string of a foreign antigen. On its surface the cell displays the foreign antigen with both histocompatibility complex (MHC) classes I and class II molecules. The antigen-presenting cell then travels to the lymph nodes and presents the antigen peptide and costimulatory molecule signalling to T-cell, initiating the immune response.
=== Vaccine insert design ===
Immunogens can be targeted to various cellular compartments to improve antibody or cytotoxic T-cell responses. Secreted or plasma membrane-bound antigens are more effective at inducing antibody responses than cytosolic antigens, while cytotoxic T-cell responses can be improved by targeting antigens for cytoplasmic degradation and subsequent entry into the major histocompatibility complex (MHC) class I pathway. This is usually accomplished by the addition of N-terminal ubiquitin signals.
The conformation of the protein can also affect antibody responses. "Ordered" structures (such as viral particles) are more effective than unordered structures. Strings of minigenes (or MHC class I epitopes) from different pathogens raise cytotoxic T-cell responses to some pathogens, especially if a TH epitope is also included.
== Delivery ==
DNA vaccines have been introduced into animal tissues by multiple methods. In 1999, the two most popular approaches were injection of DNA in saline: by using a standard hypodermic needle, or by using a gene gun delivery. Several other techniques have been documented in the intervening years.
=== Saline injection ===
Injection in saline is normally conducted intramuscularly (IM) in skeletal muscle, or intradermally (ID), delivering DNA to extracellular spaces. This can be assisted either 1) by electroporation; 2) by temporarily damaging muscle fibres with myotoxins such as bupivacaine; or 3) by using hypertonic solutions of saline or sucrose. Immune responses to this method can be affected by factors including needle type, needle alignment, speed of injection, volume of injection, muscle type, and age, sex and physiological condition of the recipient.
=== Gene gun ===
Gene gun delivery ballistically accelerates plasmid DNA (pDNA) that has been absorbed onto gold or tungsten microparticles into the target cells, using compressed helium as an accelerant.
=== Mucosal surface delivery ===
Alternatives included aerosol instillation of naked DNA on mucosal surfaces, such as the nasal and lung mucosa, and topical administration of pDNA to the eye and vaginal mucosa. Mucosal surface delivery has also been achieved using cationic liposome-DNA preparations, biodegradable microspheres, attenuated Salmonalla, Shigella or Listeria vectors for oral administration to the intestinal mucosa and recombinant adenovirus vectors.
=== Polymer vehicle ===
A hybrid vehicle composed of bacteria cell and synthetic polymers has been employed for DNA vaccine delivery. An E. coli inner core and poly(beta-amino ester) outer coat function synergistically to increase efficiency by addressing barriers associated with antigen-presenting cell gene delivery which include cellular uptake and internalization, phagosomal escape and intracellular cargo concentration. Tested in mice, the hybrid vector was found to induce immune response.
=== ELI immunization ===
Another approach to DNA vaccination is expression library immunization (ELI). Using this technique, potentially all the genes from a pathogen can be delivered at one time, which may be useful for pathogens that are difficult to attenuate or culture. ELI can be used to identify which genes induce a protective response. This has been tested with Mycoplasma pulmonis, a murine lung pathogen with a relatively small genome. Even partial expression libraries can induce protection from subsequent challenge.
=== Helpful tabular comparison ===
== Dosage ==
The delivery method determines the dose required to raise an effective immune response. Saline injections require variable amounts of DNA, from 10 μg to 1 mg, whereas gene gun deliveries require 100 to 1000 times less. Generally, 0.2 μg – 20 μg are required, although quantities as low as 16 ng have been reported. These quantities vary by species. Mice for example, require approximately 10 times less DNA than primates. Saline injections require more DNA because the DNA is delivered to the extracellular spaces of the target tissue (normally muscle), where it has to overcome physical barriers (such as the basal lamina and large amounts of connective tissue) before it is taken up by the cells, while gene gun deliveries drive/force DNA directly into the cells, resulting in less "wastage".
== Immune response ==
=== Helper T cell responses ===
DNA immunization can raise multiple TH responses, including lymphoproliferation and the generation of a variety of cytokine profiles. A major advantage of DNA vaccines is the ease with which they can be manipulated to bias the type of T-cell help towards a TH1 or TH2 response. Each type has distinctive patterns of lymphokine and chemokine expression, specific types of immunoglobulins, patterns of lymphocyte trafficking and types of innate immune responses.
==== Other types of T-cell help ====
The type of T-cell help raised is influenced by the delivery method and the type of immunogen expressed, as well as the targeting of different lymphoid compartments. Generally, saline needle injections (either IM or ID) tend to induce TH1 responses, while gene gun delivery raises TH2 responses. This is true for intracellular and plasma membrane-bound antigens, but not for secreted antigens, which seem to generate TH2 responses, regardless of the method of delivery.
Generally the type of T-cell help raised is stable over time, and does not change when challenged or after subsequent immunizations that would normally have raised the opposite type of response in a naïve specimen. However, Mor et al.. (1995) immunized and boosted mice with pDNA encoding the circumsporozoite protein of the mouse malarial parasite Plasmodium yoelii (PyCSP) and found that the initial TH2 response changed, after boosting, to a TH1 response.
==== Basis for different types of T-cell help ====
How these different methods operate, the forms of antigen expressed, and the different profiles of T-cell help is not understood. It was thought that the relatively large amounts of DNA used in IM injection were responsible for the induction of TH1 responses. However, evidence shows no dose-related differences in TH type. The type of T-cell help raised is determined by the differentiated state of antigen presenting cells. Dendritic cells can differentiate to secrete IL-12 (which supports TH1 cell development) or IL-4 (which supports TH2 responses). pDNA injected by needle is endocytosed into the dendritic cell, which is then stimulated to differentiate for TH1 cytokine (IL-12) production, while the gene gun bombards the DNA directly into the cell, thus bypassing TH1 stimulation.
==== Practical uses of polarised T-cell help ====
Polarisation in T-cell help is useful in influencing allergic responses and autoimmune diseases. In autoimmune diseases, the goal is to shift the self-destructive TH1 response (with its associated cytotoxic T cell activity) to a non-destructive TH2 response. This has been successfully applied in predisease priming for the desired type of response in preclinical models and is somewhat successful in shifting the response for an established disease.
=== Cytotoxic T-cell responses ===
One of the advantages of DNA vaccines is that they are able to induce cytotoxic T lymphocytes (CTL) without the inherent risk associated with live vaccines. CTL responses can be raised against immunodominant and immunorecessive CTL epitopes, as well as subdominant CTL epitopes, in a manner that appears to mimic natural infection. This may prove to be a useful tool in assessing CTL epitopes and their role in providing immunity.
Cytotoxic T-cells recognise small peptides (8-10 amino acids) complexed to MHC class I molecules. These peptides are derived from cytosolic proteins that are degraded and delivered to the nascent MHC class I molecule within the endoplasmic reticulum (ER). Targeting gene products directly to the ER (by the addition of an ER insertion signal sequence at the N-terminus) should thus enhance CTL responses. This was successfully demonstrated using recombinant vaccinia viruses expressing influenza proteins, but the principle should also be applicable to DNA vaccines. Targeting antigens for intracellular degradation (and thus entry into the MHC class I pathway) by the addition of ubiquitin signal sequences, or mutation of other signal sequences, was shown to be effective at increasing CTL responses.
CTL responses can be enhanced by co-inoculation with co-stimulatory molecules such as B7-1 or B7-2 for DNA vaccines against influenza nucleoprotein, or GM-CSF for DNA vaccines against the murine malaria model P. yoelii. Co-inoculation with plasmids encoding co-stimulatory molecules IL-12 and TCA3 were shown to increase CTL activity against HIV-1 and influenza nucleoprotein antigens.
=== Humoral (antibody) response ===
Antibody responses elicited by DNA vaccinations are influenced by multiple variables, including antigen type; antigen location (i.e. intracellular vs. secreted); number, frequency and immunization dose; site and method of antigen delivery.
==== Kinetics of antibody response ====
Humoral responses after a single DNA injection can be much longer-lived than after a single injection with a recombinant protein. Antibody responses against hepatitis B virus (HBV) envelope protein (HBsAg) have been sustained for up to 74 weeks without boost, while lifelong maintenance of protective response to influenza haemagglutinin was demonstrated in mice after gene gun delivery. Antibody-secreting cells (ASC) migrate to the bone marrow and spleen for long-term antibody production, and generally localise there after one year.
Comparisons of antibody responses generated by natural (viral) infection, immunization with recombinant protein and immunization with pDNA are summarised in Table 4. DNA-raised antibody responses rise much more slowly than when natural infection or recombinant protein immunization occurs. As many as 12 weeks may be required to reach peak titres in mice, although boosting can decrease the interval. This response is probably due to the low levels of antigen expressed over several weeks, which supports both primary and secondary phases of antibody response. DNA vaccine expressing HBV small and middle envelope protein was injected into adults with chronic hepatitis. The vaccine resulted in specific interferon gamma cell production. Also specific T-cells for middle envelop proteins antigens were developed. The immune response of the patients was not robust enough to control HBV infection
Additionally, the titres of specific antibodies raised by DNA vaccination are lower than those obtained after vaccination with a recombinant protein. However, DNA immunization-induced antibodies show greater affinity to native epitopes than recombinant protein-induced antibodies. In other words, DNA immunization induces a qualitatively superior response. Antibodies can be induced after one vaccination with DNA, whereas recombinant protein vaccinations generally require a boost. DNA immunization can be used to bias the TH profile of the immune response and thus the antibody isotype, which is not possible with either natural infection or recombinant protein immunization. Antibody responses generated by DNA are useful as a preparative tool. For example, polyclonal and monoclonal antibodies can be generated for use as reagents.
== Mechanistic basis for DNA-raised immune responses ==
=== DNA uptake mechanism ===
When DNA uptake and subsequent expression was first demonstrated in vivo in muscle cells, these cells were thought to be unique because of their extensive network of T-tubules. Using electron microscopy, it was proposed that DNA uptake was facilitated by caveolae (or, non-clathrin coated pits). However, subsequent research revealed that other cells (such as keratinocytes, fibroblasts and epithelial Langerhans cells) could also internalize DNA. The mechanism of DNA uptake is not known.
Two theories dominate – that in vivo uptake of DNA occurs non-specifically, in a method similar to phago- or pinocytosis, or through specific receptors. These might include a 30kDa surface receptor, or macrophage scavenger receptors. The 30kDa surface receptor binds specifically to 4500-bp DNA fragments (which are then internalised) and is found on professional APCs and T-cells. Macrophage scavenger receptors bind to a variety of macromolecules, including polyribonucleotides and are thus candidates for DNA uptake. Receptor-mediated DNA uptake could be facilitated by the presence of polyguanylate sequences. Gene gun delivery systems, cationic liposome packaging, and other delivery methods bypass this entry method, but understanding it may be useful in reducing costs (e.g. by reducing the requirement for cytofectins), which could be important in animal husbandry.
=== Antigen presentation by bone marrow-derived cells ===
Studies using chimeric mice have shown that antigen is presented by bone-marrow derived cells, which include dendritic cells, macrophages and specialised B-cells called professional antigen presenting cells (APC). After gene gun inoculation to the skin, transfected Langerhans cells migrate to the draining lymph node to present antigens. After IM and ID injections, dendritic cells present antigen in the draining lymph node and transfected macrophages have been found in the peripheral blood.
Besides direct transfection of dendritic cells or macrophages, cross priming occurs following IM, ID and gene gun DNA deliveries. Cross-priming occurs when a bone marrow-derived cell presents peptides from proteins synthesised in another cell in the context of MHC class 1. This can prime cytotoxic T-cell responses and seems to be important for a full primary immune response.
=== Target site role ===
IM and ID DNA delivery initiate immune responses differently. In the skin, keratinocytes, fibroblasts and Langerhans cells take up and express antigens and are responsible for inducing a primary antibody response. Transfected Langerhans cells migrate out of the skin (within 12 hours) to the draining lymph node where they prime secondary B- and T-cell responses. In skeletal muscle, striated muscle cells are most frequently transfected, but seem to be unimportant in immune response. Instead, IM inoculated DNA "washes" into the draining lymph node within minutes, where distal dendritic cells are transfected and then initiate an immune response. Transfected myocytes seem to act as a "reservoir" of antigen for trafficking professional APCs.
=== Maintenance of immune response ===
DNA vaccination generates an effective immune memory via the display of antigen-antibody complexes on follicular dendritic cells (FDC), which are potent B-cell stimulators. T-cells can be stimulated by similar, germinal centre dendritic cells. FDC are able to generate an immune memory because antibodies production "overlaps" long-term expression of antigen, allowing antigen-antibody immunocomplexes to form and be displayed by FDC.
=== Interferons ===
Both helper and cytotoxic T-cells can control viral infections by secreting interferons. Cytotoxic T cells usually kill virally infected cells. However, they can also be stimulated to secrete antiviral cytokines such as IFN-γ and TNF-α, which do not kill the cell, but limit viral infection by down-regulating the expression of viral components. DNA vaccinations can be used to curb viral infections by non-destructive IFN-mediated control. This was demonstrated for hepatitis B. IFN-γ is critically important in controlling malaria infections and is a consideration for anti-malarial DNA vaccines.
== Immune response modulation ==
=== Cytokine modulation ===
An effective vaccine must induce an appropriate immune response for a given pathogen. DNA vaccines can polarise T-cell help towards TH1 or TH2 profiles and generate CTL and/or antibody when required. This can be accomplished by modifications to the form of antigen expressed (i.e. intracellular vs. secreted), the method and route of delivery or the dose. It can also be accomplished by the co-administration of plasmid DNA encoding immune regulatory molecules, i.e. cytokines, lymphokines or co-stimulatory molecules. These "genetic adjuvants" can be administered as a:
mixture of 2 plasmids, one encoding the immunogen and the other encoding the cytokine
single bi- or polycistronic vector, separated by spacer regions
plasmid-encoded chimera, or fusion protein
In general, co-administration of pro-inflammatory agents (such as various interleukins, tumor necrosis factor, and GM-CSF) plus TH2-inducing cytokines increase antibody responses, whereas pro-inflammatory agents and TH1-inducing cytokines decrease humoral responses and increase cytotoxic responses (more important in viral protection). Co-stimulatory molecules such as B7-1, B7-2 and CD40L are sometimes used.
This concept was applied in topical administration of pDNA encoding IL-10. Plasmid encoding B7-1 (a ligand on APCs) successfully enhanced the immune response in tumour models. Mixing plasmids encoding GM-CSF and the circumsporozoite protein of P. yoelii (PyCSP) enhanced protection against subsequent challenge (whereas plasmid-encoded PyCSP alone did not). It was proposed that GM-CSF caused dendritic cells to present antigen more efficiently and enhance IL-2 production and TH cell activation, thus driving the increased immune response. This can be further enhanced by first priming with a pPyCSP and pGM-CSF mixture, followed by boosting with a recombinant poxvirus expressing PyCSP. However, co-injection of plasmids encoding GM-CSF (or IFN-γ, or IL-2) and a fusion protein of P. chabaudi merozoite surface protein 1 (C-terminus)-hepatitis B virus surface protein (PcMSP1-HBs) abolished protection against challenge, compared to protection acquired by delivery of pPcMSP1-HBs alone.
The advantages of genetic adjuvants are their low cost and simple administration, as well as avoidance of unstable recombinant cytokines and potentially toxic, "conventional" adjuvants (such as alum, calcium phosphate, monophosphoryl lipid A, cholera toxin, cationic and mannan-coated liposomes, QS21, carboxymethyl cellulose and ubenimex). However, the potential toxicity of prolonged cytokine expression is not established. In many commercially important animal species, cytokine genes have not been identified and isolated. In addition, various plasmid-encoded cytokines modulate the immune system differently according to the delivery time. For example, some cytokine plasmid DNAs are best delivered after immunogen pDNA, because pre- or co-delivery can decrease specific responses and increase non-specific responses.
=== Immunostimulatory CpG motifs ===
Plasmid DNA itself appears to have an adjuvant effect on the immune system. Bacterially derived DNA can trigger innate immune defence mechanisms, the activation of dendritic cells and the production of TH1 cytokines. This is due to recognition of certain CpG dinucleotide sequences that are immunostimulatory. CpG stimulatory (CpG-S) sequences occur twenty times more frequently in bacterially-derived DNA than in eukaryotes. This is because eukaryotes exhibit "CpG suppression" – i.e. CpG dinucleotide pairs occur much less frequently than expected. Additionally, CpG-S sequences are hypomethylated. This occurs frequently in bacterial DNA, while CpG motifs occurring in eukaryotes are methylated at the cytosine nucleotide. In contrast, nucleotide sequences that inhibit the activation of an immune response (termed CpG neutralising, or CpG-N) are over represented in eukaryotic genomes. The optimal immunostimulatory sequence is an unmethylated CpG dinucleotide flanked by two 5’ purines and two 3’ pyrimidines. Additionally, flanking regions outside this immunostimulatory hexamer must be guanine-rich to ensure binding and uptake into target cells.
The innate system works with the adaptive immune system to mount a response against the DNA encoded protein. CpG-S sequences induce polyclonal B-cell activation and the upregulation of cytokine expression and secretion. Stimulated macrophages secrete IL-12, IL-18, TNF-α, IFN-α, IFN-β and IFN-γ, while stimulated B-cells secrete IL-6 and some IL-12.
Manipulation of CpG-S and CpG-N sequences in the plasmid backbone of DNA vaccines can ensure the success of the immune response to the encoded antigen and drive the immune response toward a TH1 phenotype. This is useful if a pathogen requires a TH response for protection. CpG-S sequences have also been used as external adjuvants for both DNA and recombinant protein vaccination with variable success rates. Other organisms with hypomethylated CpG motifs have demonstrated the stimulation of polyclonal B-cell expansion. The mechanism behind this may be more complicated than simple methylation – hypomethylated murine DNA has not been found to mount an immune response.
Most of the evidence for immunostimulatory CpG sequences comes from murine studies. Extrapolation of this data to other species requires caution – individual species may require different flanking sequences, as binding specificities of scavenger receptors vary across species. Additionally, species such as ruminants may be insensitive to immunostimulatory sequences due to their large gastrointestinal load.
=== Alternative boosts ===
DNA-primed immune responses can be boosted by the administration of recombinant protein or recombinant poxviruses. "Prime-boost" strategies with recombinant protein have successfully increased both neutralising antibody titre, and antibody avidity and persistence, for weak immunogens, such as HIV-1 envelope protein. Recombinant virus boosts have been shown to be very efficient at boosting DNA-primed CTL responses. Priming with DNA focuses the immune response on the required immunogen, while boosting with the recombinant virus provides a larger amount of expressed antigen, leading to a large increase in specific CTL responses.
Prime-boost strategies have been successful in inducing protection against malarial challenge in a number of studies. Primed mice with plasmid DNA encoding Plasmodium yoelii circumsporozoite surface protein (PyCSP), then boosted with a recombinant vaccinia virus expressing the same protein had significantly higher levels of antibody, CTL activity and IFN-γ, and hence higher levels of protection, than mice immunized and boosted with plasmid DNA alone. This can be further enhanced by priming with a mixture of plasmids encoding PyCSP and murine GM-CSF, before boosting with recombinant vaccinia virus. An effective prime-boost strategy for the simian malarial model P. knowlesi has also been demonstrated. Rhesus monkeys were primed with a multicomponent, multistage DNA vaccine encoding two liver-stage antigens – the circumsporozoite surface protein (PkCSP) and sporozoite surface protein 2 (PkSSP2) – and two blood stage antigens – the apical merozoite surface protein 1 (PkAMA1) and merozoite surface protein 1 (PkMSP1p42). They were then boosted with a recombinant canarypox virus encoding all four antigens (ALVAC-4). Immunized monkeys developed antibodies against sporozoites and infected erythrocytes, and IFN-γ-secreting T-cell responses against peptides from PkCSP. Partial protection against sporozoite challenge was achieved, and mean parasitemia was significantly reduced, compared to control monkeys. These models, while not ideal for extrapolation to P. falciparum in humans, will be important in pre-clinical trials.
=== Enhancing immune responses ===
==== DNA ====
The efficiency of DNA immunization can be improved by stabilising DNA against degradation, and increasing the efficiency of delivery of DNA into antigen-presenting cells. This has been demonstrated by coating biodegradable cationic microparticles (such as poly(lactide-co-glycolide) formulated with cetyltrimethylammonium bromide) with DNA. Such DNA-coated microparticles can be as effective at raising CTL as recombinant viruses, especially when mixed with alum. Particles 300 nm in diameter appear to be most efficient for uptake by antigen presenting cells.
==== Alphavirus vectors ====
Recombinant alphavirus-based vectors have been used to improve DNA vaccination efficiency. The gene encoding the antigen of interest is inserted into the alphavirus replicon, replacing structural genes but leaving non-structural replicase genes intact. The Sindbis virus and Semliki Forest virus have been used to build recombinant alphavirus replicons. Unlike conventional DNA vaccinations alphavirus vectors kill transfected cells and are only transiently expressed. Alphavirus replicase genes are expressed in addition to the vaccine insert. It is not clear how alphavirus replicons raise an immune response, but it may be due to the high levels of protein expressed by this vector, replicon-induced cytokine responses, or replicon-induced apoptosis leading to enhanced antigen uptake by dendritic cells.
== See also ==
Vector DNA
HIV vaccine
Gene therapy
mRNA vaccine
== References ==
=== Further reading === | Wikipedia/DNA_vaccination |
A ribosomal protein (r-protein or rProtein) is any of the proteins that, in conjunction with rRNA, make up the ribosomal subunits involved in the cellular process of translation. E. coli, other bacteria and Archaea have a 30S small subunit and a 50S large subunit, whereas humans and yeasts have a 40S small subunit and a 60S large subunit. Equivalent subunits are frequently numbered differently between bacteria, Archaea, yeasts and humans.
A large part of the knowledge about these organic molecules has come from the study of E. coli ribosomes. All ribosomal proteins have been isolated and many specific antibodies have been produced. These, together with electronic microscopy and the use of certain reactives, have allowed for the determination of the topography of the proteins in the ribosome. More recently, a near-complete (near)atomic picture of the ribosomal proteins is emerging from the latest high-resolution cryo-EM data (including PDB: 5AFI).
== Conservation ==
Ribosomal proteins are among the most highly conserved proteins across all life forms. Among the 40 proteins found in various small ribosomal subunits (RPSs), 15 subunits are universally conserved across prokaryotes and eukaryotes. However, 7 subunits are only found in bacteria (bS21, bS6, bS16, bS18, bS20, bS21, and bTHX), while 17 subunits are only found in archaea and eukaryotes. Typically 22 proteins are found in bacterial small subunits and 32 in yeast, human and most likely most other eukaryotic species. Twenty-seven (out of 32) proteins of the eukaryotic small ribosomal subunit proteins are also present in archaea (no ribosomal protein is exclusively found in archaea), confirming that they are more closely related to eukaryotes than to bacteria.
Among the large ribosomal subunit (RPLs), 18 proteins are universal, i.e. found in both bacteria, eukaryotes, and archaea. 14 proteins are only found in bacteria, while 27 proteins are only found in archaea and eukaryotes. Again, archaea have no proteins unique to them.
== Essentiality ==
Despite their high conservation over billions of years of evolution, the absence of several ribosomal proteins in certain species shows that ribosomal subunits have been added and lost over the course of evolution. This is also reflected by the fact that several ribosomal proteins do not appear to be essential when deleted. For instance, in E. coli nine ribosomal proteins (uL15, bL21, uL24, bL27, uL29, uL30, bL34, uS9, and uS17) are nonessential for survival when deleted. Taken together with previous results, 22 of the 54 E. coli ribosomal protein genes can be individually deleted from the genome. Similarly, 16 ribosomal proteins (uL1, bL9, uL15, uL22, uL23, bL28, uL29, bL32, bL33.1, bL33.2, bL34, bL35, bL36, bS6, bS20, and bS21) were successfully deleted in Bacillus subtilis. In conjunction with previous reports, 22 ribosomal proteins have been shown to be nonessential in B. subtilis, at least for cell proliferation.
== Assembly ==
=== In E. coli ===
The ribosome of E. coli has about 22 proteins in the small subunit (labelled S1 to S22) and 33 proteins in the large subunit (somewhat counter-intuitively called L1 to L36). All of them are different with three exceptions: one protein is found in both subunits (S20 and L26), L7 and L12 are acetylated and methylated forms of the same protein, and L8 is a complex of L7/L12 and L10. In addition, L31 is known to exist in two forms, the full length at 7.9 kilodaltons (kDa) and fragmented at 7.0 kDa. This is why the number of proteins in a ribosome is of 56. Except for S1 (with a molecular weight of 61.2 kDa), the other proteins range in weight between 4.4 and 29.7 kDa.
Recent de novo proteomics experiments where the authors characterized in vivo ribosome-assembly intermediates and associated assembly factors from wild-type Escherichia coli cells using a general quantitative mass spectrometry (qMS) approach have confirmed the presence of all the known small and large subunit components and have identified a total of 21 known and potentially new ribosome-assembly-factors that co-localise with various ribosomal particles.
==== Disposition in the small ribosomal subunit ====
In the small (30S) subunit of E. coli ribosomes, the proteins denoted uS4, uS7, uS8, uS15, uS17, bS20 bind independently to 16S rRNA. After assembly of these primary binding proteins, uS5, bS6, uS9, uS12, uS13, bS16, bS18, and uS19 bind to the growing ribosome. These proteins also potentiate the addition of uS2, uS3, uS10, uS11, uS14, and bS21. Protein binding to helical junctions is important for initiating the correct tertiary fold of RNA and to organize the overall structure. Nearly all the proteins contain one or more globular domains. Moreover, nearly all contain long extensions that can contact the RNA in far-reaching regions. Additional stabilization results from the proteins' basic residues, as these neutralize the charge repulsion of the RNA backbone. Protein–protein interactions also exist to hold structure together by electrostatic and hydrogen bonding interactions. Theoretical investigations pointed to correlated effects of protein-binding onto binding affinities during the assembly process
In one study, the net charges (at pH 7.4) of the ribosomal proteins comprising the highly conserved S10-spc cluster were found to have an inverse relationship with the halophilicity/halotolerance levels in bacteria and archaea. In non-halophilic bacteria, the S10-spc proteins are generally basic, contrasting with the overall acidic whole proteomes of the extremely halophiles. The universal uL2 lying in the oldest part of the ribosome, is always positively charged irrespective of the strain/organism it belongs to.
=== In eukaryotes ===
Ribosomes in eukaryotes contain 79–80 proteins and four ribosomal RNA (rRNA) molecules.
General or specialized chaperones solubilize the ribosomal proteins and facilitate their import into the nucleus. Assembly of the eukaryotic ribosome appears to be driven by the ribosomal proteins in vivo when assembly is also aided by chaperones. Most ribosomal proteins assemble with rRNA co-transcriptionally, becoming associated more stably as assembly proceeds, and the active sites of both subunits are constructed last.
== Table of ribosomal proteins ==
In the past, different nomenclatures were used for the same ribosomal protein in different organisms. Not only were the names not consistent across domains; the names also differed between organisms within a domain, such as humans and S. cerevisiae, both eukaryotes. This was due to researchers assigning names before the sequences were known, causing trouble for later research. The following tables use the unified nomenclature by Ban et al., 2014. The same nomenclature is used by UniProt's "family" curation.
In general, cellular ribosomal proteins are to be called simply using the cross domain name, e.g. "uL14" for what is currently called L23 in humans. A suffix is used for the organellar versions, so that "uL14m" refers to the human mitochondrial uL14 (MRPL14). Organelle-specific proteins use their own cross-domain prefixes, for example "mS33" for MRPS33: Table S3, S4 and "cL37" for PSRP5.: Table S2, S3 (See the two proceeding citations, also partially by Ban N, for the organelle nomenclatures.)
== See also ==
Alpha operon ribosome binding site
Ribosomal protein L20 leader
Mitochondrial ribosome, for a list of its protein subunits
== References ==
== Further reading ==
== External links ==
30S Ribosomal proteins at biochem.umd.edu
Ribosomal+Protein at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
Ribosomal protein nomenclature visualization from Ban et al., with annotated structures of cellular and organellar ribosomes | Wikipedia/Ribosomal_protein |
The invertebrate mitochondrial code (translation table 5) is a genetic code used by the mitochondrial genome of invertebrates. Mitochondria contain their own DNA and reproduce independently from their host cell. Variation in translation of the mitochondrial genetic code occurs when DNA codons result in non-standard amino acids has been identified in invertebrates, most notably arthropods. This variation has been helpful as a tool to improve upon the phylogenetic tree of invertebrates, like flatworms.
== The code ==
AAs = FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIMMTTTTNNKKSSSSVVVVAAAADDEEGGGG
Starts = ---M----------------------------MMMM---------------M------------
Base1 = TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGG
Base2 = TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGG
Base3 = TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG
Bases: adenine (A), cytosine (C), guanine (G) and thymine (T) or uracil (U).
Amino acids: Alanine (Ala, A), Arginine (Arg, R), Asparagine (Asn, N), Aspartic acid (Asp, D), Cysteine (Cys, C), Glutamic acid (Glu, E), Glutamine (Gln, Q), Glycine (Gly, G), Histidine (His, H), Isoleucine (Ile, I), Leucine (Leu, L), Lysine (Lys, K), Methionine (Met, M), Phenylalanine (Phe, F), Proline (Pro, P), Serine (Ser, S), Threonine (Thr, T), Tryptophan (Trp, W), Tyrosine (Tyr, Y), Valine (Val, V).
== Differences from the standard code ==
Note: The codon AGG is absent in Drosophila.
=== Alternative initiation codons ===
ATA/AUA
ATT/AUU
ATC/AUC: Apis
GTG/GUG: Polyplacophora
TTG/UUG: Ascaris, Caenorhabditis.
== Systematic range ==
Nematoda: Ascaris, Caenorhabditis;
Mollusca: Bivalvia); Polyplacophora;
Arthropoda/Crustacea: Artemia;
Arthropoda/Insecta: Drosophila [Locusta migratoria (migratory locust), Apis mellifera (honeybee)].
== Other variations ==
Several arthropods translate the codon AGG as lysine instead of serine (as in the Pterobranchia Mitochondrial Code) or arginine (as in the standard genetic code).
GUG may possibly function as an initiator in Drosophila. AUU is not used as an initiator in Mytilus
"An exceptional mechanism must operate for initiation of translation of the cytochrome oxidase subunit I mRNA in both D. melanogaster and D. yakuba, since its only plausible initiation codon, AUA, is out of frame with the rest of the gene. Initiation appears to require the "reading" of an AUAA quadruplet, which would be equivalent to initiation at AUA followed immediately by a specific ribosomal frameshift. Another possible mechanism ... is that the mRNA is "edited" to bring the AUA initiation into frame."
== See also ==
List of genetic codes
== References ==
This article incorporates text from the United States National Library of Medicine, which is in the public domain. | Wikipedia/Invertebrate_mitochondrial_code |
Survival of motor neuron or survival motor neuron (SMN) is a protein that in humans is encoded by the SMN1 and SMN2 genes.
SMN is found in the cytoplasm of all animal cells and also in the nuclear gems. It functions in transcriptional regulation, telomerase regeneration and cellular trafficking. SMN deficiency, primarily due to mutations in SMN1, results in widespread splicing defects, especially in spinal motor neurons, and is one cause of spinal muscular atrophy. Research also showed a possible role of SMN in neuronal migration and/or differentiation.
== Function ==
The SMN protein contains GEMIN2-binding, Tudor and YG-Box domains. It localizes to both the cytoplasm and the nucleus. Within the nucleus, the protein localizes to subnuclear bodies called gems which are found near coiled bodies containing high concentrations of small ribonucleoproteins (snRNPs). This protein forms heteromeric complexes with proteins such as GEMIN2 and GEMIN4, and also interacts with several proteins known to be involved in the biogenesis of snRNPs, such as hnRNP U protein and the small nucleolar RNA binding protein.
== SMN complex ==
SMN complex refers to the entire multi-protein complex involved in the assembly of snRNPs, the essential components of spliceosomal machinery. The complex, apart from the "proper" survival of motor neuron protein, includes at least six other proteins (gem-associated protein 2, 3, 4, 5, 6 and 7.
== Interactions ==
SMN has been shown to interact with:
== Evolutionary conservation ==
SMN is evolutionarily conserved including the Fungi kingdom, though only fungal organisms with a great number of introns have the Smn gene (or the splicing factor spf30 paralogue). Surprisingly, these are filamentous fungus which have mycelia, so suggesting analogy to the neuronal axons.
== See also ==
Gideon Dreyfuss
== References ==
== External links ==
SMN+protein+(spinal+muscular+atrophy) at the U.S. National Library of Medicine Medical Subject Headings (MeSH) | Wikipedia/Survival_of_motor_neuron |
Protein misfolding cyclic amplification (PMCA) is an amplification technique (conceptually like polymerase chain reaction (PCR) but not involving nucleotides) to multiply misfolded prions originally developed by Soto and colleagues. It is a test for spongiform encephalopathies like chronic wasting disease (CWD) or bovine spongiform encephalopathy (BSE).
== Technique ==
The technique initially incubates a small amount of abnormal prion with an excess of normal protein, so that some conversion takes place. The growing chain of misfolded protein is then blasted with ultrasound, breaking it down into smaller chains and so rapidly increasing the amount of abnormal protein available to cause conversions. By repeating the cycle, the mass of normal protein is rapidly changed into the prion being tested for.
== Development ==
PMCA was originally developed to, in vitro, mimic prion replication with a similar efficiency to the in vivo process, but with accelerated kinetics. PMCA is conceptually analogous to the polymerase chain reaction - in both systems a template grows at the expense of a substrate in a cyclic reaction, combining growing and multiplication of the template units.
== Replication ==
PMCA has been applied to replicate the misfolded protein from diverse species. The newly generated protein exhibits the same biochemical, biological, and structural properties as brain-derived PrPSc and strikingly it is infectious to wild type animals, producing a disease with similar characteristics as the illness produced by brain-isolated prions.
== Automation ==
The technology has been automated, leading to a dramatic increase in the efficiency of amplification. Now, a single cycle results in a 2500-fold increase in sensitivity of detection over western blotting, whereas 2 and 7 consecutive cycles result in 6 million and 3 billion-fold increases in sensitivity of detection over western blotting, a technique widely used in BSE surveillance in several countries.
== Sensitivity ==
It has been shown that PMCA is capable of detecting as little as a single molecule of oligomeric infectious PrPSc. PMCA possesses the ability to generate millions infectious units, starting with the equivalent to one PrPSc oligomer; well below the infectivity threshold. This data demonstrates that PMCA has a similar power of amplification as PCR techniques used to amplify DNA. It opens a great promise for development of a highly sensitive detection of PrPSc, and for understanding the molecular basis of prion replication. Indeed, PMCA has been used by various groups to PrPSc in blood of animals experimentally infected with prions during both the symptomatic and pre-symptomatic phases as well as in urine.
== Uses ==
The PMCA technology has been used by several groups to understand the molecular mechanism of prion replication, the nature of the infectious agent, the phenomenon of prion strains and species barrier, the effect of cellular components, to detect PrPSc in tissues and biological fluids and to screen for inhibitors against prion replication. Recent studies by the groups of Supattapone and Ma were able to produce prion replication in vitro by PMCA using purified PrPC and recombinant PrPC with the sole addition of synthetic polyanions and lipids. These studies have shown that infectious prions can be produced in the absence of any other cellular component and constitute some of the strongest evidence in favor of the prion hypothesis.
Research in 2020 concluded that protein misfolding cyclic amplification could be used to distinguish between two progressive neurodegenerative diseases, Parkinson's disease and multiple system atrophy, being the first process to give an objective diagnosis of Multiple System Atrophy instead of just a differential diagnosis.
== See also ==
Real-Time Quaking-Induced Conversion
Western blotting
== References == | Wikipedia/Protein_misfolding_cyclic_amplification |
Mitochondrial import inner membrane translocase subunit TIM14 is an enzyme that in humans is encoded by the DNAJC19 gene on chromosome 3. TIM14 belongs to the DnaJ family, which has been involved in Hsp40/Hsp70 chaperone systems. As a mitochondrial chaperone, TIM14 functions as part of the TIM23 complex import motor to facilitate the import of nuclear-encoded proteins into the mitochondria. TIM14 also complexes with prohibitin complexes to regulate mitochondrial morphogenesis, and has been implicated in dilated cardiomyopathy with ataxia.
== Structure ==
The DNAJC19 gene is located on the q arm of chromosome 3 at position 26.33 and it spans 6,065 base pairs. The DNAJC19 gene produces a 6.29 kDa protein composed of 59 amino acids. The protein encoded by the DNAJC19 gene possesses an unusual structure compared to the rest of the DNAJ protein family. Notably, the DNAJ domain of TIM14 is located at the C-terminal rather than the N-terminal, and the transmembrane domain confers membrane-bound localization for TIM14 while other DNAJ proteins are cytosolic. TIM14 orthologs in other species, such as the yeast Tim14 and Mdj2p proteins, confirm localization to the mitochondrial inner membrane.
== Function ==
TIM14 is required for the ATP-dependent import of mitochondrial pre-proteins into the mitochondrial matrix. The J-domain of TIM14 stimulates mtHsp70 ATPase activity to power this transport.
Additionally, TIM14 helps regulate mitochondrial morphology by complexing with prohibitins to perform disphosphoglycerolipid cardiolipin (CL) remodeling. CL is a key phospholipid in mitochondrial membranes that modulates the fusion and fission of mitochondrial membranes, as well as mitophagy and apoptosis.
== Clinical significance ==
Defects in DNAJC19 have been observed primarily in cases of dilated cardiomyopathy with ataxia (DCMA), though it has also been associated with growth failure, microcytic anemia, and male genital anomalies. DNAJC19 was first implicated in DCMA in a study on the consanguineous Hutterite population, which has since been confirmed in other European populations. In the clinic, DNAJC19 mutations can be detected by screening for elevated levels of 3-methylglutaconic acid, mitochondrial distress, dilated cardiomyopathy, prolongation of the QT interval in the electrocardiogram, and cerebellar ataxia.
== Interactions ==
TIM14 interacts with:
TIMM44,
mtHsp70,
TIMM16/PAM16, and
PHB2.
== References ==
== Further reading ==
This article incorporates text from the United States National Library of Medicine, which is in the public domain. | Wikipedia/DNAJC19 |
DnaJ homolog subfamily C member 3 is a protein that in humans is encoded by the DNAJC3 gene.
== Function ==
The protein encoded by this gene contains multiple tetratricopeptide repeat (TPR) motifs as well as the highly conserved J domain found in DNAJ chaperone family members. It is a member of the tetratricopeptide repeat family of proteins and acts as an inhibitor of the interferon-induced, dsRNA-activated protein kinase (PKR).
== Clinical significance ==
An important role for DNAJC3 has been attributed to diabetes mellitus as well as multi system neurodegeneration. Diabetes mellitus and neurodegeneration are common diseases for which shared genetic factors are still only partly known. It was shown that loss of the BiP (immunoglobulin heavy-chain binding protein) co-chaperone DNAJC3 leads to diabetes mellitus and widespread neurodegeneration. Accordingly, three siblings were investigated with juvenile-onset diabetes and central and peripheral neurodegeneration, including ataxia, upper-motor-neuron damage, peripheral neuropathy, hearing loss, and cerebral atrophy. Subsequently, exome sequencing identified a homozygous stop mutation in DNAJC3. Further screening of a diabetes database with 226,194 individuals yielded eight phenotypically similar individuals and one family carrying a homozygous DNAJC3 deletion. DNAJC3 was absent in fibroblasts from all affected subjects in both families. To delineate the phenotypic and mutational spectrum and the genetic variability of DNAJC3, 8,603 exomes were further analyzed, including 506 from families affected by diabetes, ataxia, upper-motor-neuron damage, peripheral neuropathy, or hearing loss. This analysis revealed only one further loss-of-function allele in DNAJC3 and no further associations in subjects with only a subset of the features of the main phenotype. Notably, the DNAJC3 protein is also considered as an important marker for stress in the endoplasmatic reticulum.
== Interactions ==
DNAJC3 has been shown to interact with:
EIF2AK2,
EIF2AK3, and
PRKRIR.
== References ==
== Further reading == | Wikipedia/DNAJC3 |
DnaJ homolog subfamily A member 3, mitochondrial, also known as Tumorous imaginal disc 1 (TID1), is a protein that in humans is encoded by the DNAJA3 gene on chromosome 16. This protein belongs to the DNAJ/Hsp40 protein family, which is known for binding and activating Hsp70 chaperone proteins to perform protein folding, degradation, and complex assembly. As a mitochondrial protein, it is involved in maintaining membrane potential and mitochondrial DNA (mtDNA) integrity, as well as cellular processes such as cell movement, growth, and death. Furthermore, it is associated with a broad range of diseases, including neurodegenerative diseases, inflammatory diseases, and cancers.
== Structure ==
As a member of the DNAJ/Hsp40 protein family, DNAJA3 contains a conserved DnaJ domain, which includes an HPD motif that interacts with Hsp70 to perform its cochaperone function. The DnaJ domain is composed of tetrahelical regions containing a tripeptide of histidine, proline and aspartic acid situated between two helices. In addition, this protein contains a glycine/phenylalanine (G/F) rich linker region and a central cysteine-rich region similar to a zinc finger repeat, both characteristic of type I DnaJ molecular chaperones. The mitochondrial targeting sequence at its N-terminal directs the localization of the protein to the mitochondrial matrix.
DNAJA3 possesses two alternatively spliced forms: a long isoform of 43 kDa and a short isoform of 40 kDa. The long isoform contains an additional 33 residues at its C-terminal compared to the short isoform, and this region is predicted to hinder the long isoform from regulating membrane potential.
== Function ==
DNAJA3 is a member of the DNAJ/Hsp40 protein family, which stimulates the ATPase activity of Hsp70 chaperones and plays critical roles in protein folding, degradation, and multiprotein complex assembly. DNAJA3 localizes to the mitochondria, where it interacts with the mitochondrial Hsp70 chaperone (mtHsp70) to carry out the chaperone system. This protein is crucial for maintaining a homogeneous distribution of mitochondrial membrane potential and the integrity of mtDNA. DNAJA3 homogenizes membrane potential through regulation of complex I aggregation, though the mechanism for maintaining mtDNA remains unknown. These functions then allow DNAJA3 to mediate mitochondrial fission through DRP1 and, by extension, cellular processes such as cell movement, growth, proliferation, differentiation, senescence, and apoptosis. However, though both isoforms of DNAJA3 are involved with cell survival, they are also observed to influence two opposing outcomes. The proapoptotic long isoform induces apoptosis by stimulating cytochrome C release and caspase activation in the mitochondria, whereas the antiapoptotic short isoform prevents cytochrome C release and, thus, apoptosis. In neuromuscular junctions, only the short isoform clusters acetylcholine receptors for efficient synaptic transmission. The two isoforms also differ in their specific mitochondrial localization, which may partially account for their different functions.
Before localization to the mitochondria, DNAJA3 is transiently retained in the cytosol, where it can also interact with cytosolic proteins and possibly function to transport these proteins.
== Clinical significance ==
This protein is implicated in several cancers, including skin cancer, breast cancer, and colorectal cancer. It is a key player in tumor suppression through interactions with oncogenic proteins, including ErbB2 and the p53 tumor suppressor protein. Under hypoxic conditions, DNAJA3 may directly influence p53 complex assembly or modification, or indirectly ubiquitinylate p53 through ubiquitin ligases like MDM2. Moreover, both p53 and DNAJA3 must be present in the mitochondria in order to induce apoptosis in the cell. In head and neck squamous cell carcinoma (HNSCC) cancer, DNAJA3 suppresses cell proliferation, anchorage-independent growth, cell motility, and cell invasion by attenuating EGFR and, downstream the signaling pathway, AKT. Thus, treatments promoting DNAJA3 expression and function may greatly aid the elimination of tumors.
Additionally, DNAJA3 is implicated in neurodegenerative diseases like Parkinson's disease by virtue of its key roles in chaperoning mitochondrial proteins and mediating mitochondrial morphology in conjunction with mtHsp70. Another disease, psoriasis, is a chronic inflammatory skin disease that results from the absence of DNAJA3 activity, which then results in the activation of MK5, increased phosphorylation of HSP27, increased actin cytoskeleton organization, and hyperthickened skin.
== Interactions ==
DNAJA3 has been shown to interact with:
ErbB-2 receptor tyrosine kinase
MK5
HSPA9
HSPA8,
JAK2, and
RASA1
== References ==
== Further reading == | Wikipedia/DNAJA3 |
Ubiquitin-like proteins (UBLs) are a family of small proteins involved in post-translational modification of other proteins in a cell, usually with a regulatory function. The UBL protein family derives its name from the first member of the class to be discovered, ubiquitin (Ub), best known for its role in regulating protein degradation through covalent modification of other proteins. Following the discovery of ubiquitin, many additional evolutionarily related members of the group were described, involving parallel regulatory processes and similar chemistry. UBLs are involved in a widely varying array of cellular functions including autophagy, protein trafficking, inflammation and immune responses, transcription, DNA repair, RNA splicing, and cellular differentiation.
== Discovery ==
Ubiquitin itself was first discovered in the 1970s and originally named "ubiquitous immunopoietic polypeptide". Subsequently, other proteins with sequence similarity to ubiquitin were occasionally reported in the literature, but the first shown to share the key feature of covalent protein modification was ISG15, discovered in 1987. A succession of reports in the mid 1990s is recognized as a turning point in the field, with the discovery of SUMO (small ubiquitin-like modifier, also known as Sentrin or SENP1) reported around the same time by a variety of investigators in 1996, NEDD8 in 1997, and Apg12 in 1998. A systematic survey has since identified over 10,000 distinct genes for ubiquitin or ubiquitin-like proteins represented in eukaryotic genomes.
== Structure and classification ==
Members of the UBL family are small, non-enzymatic proteins that share a common structure exemplified by ubiquitin, which has 76 amino acid residues arranged into a "beta-grasp" protein fold consisting of a five-strand antiparallel beta sheet surrounding an alpha helix. The beta-grasp fold is widely distributed in other proteins of both eukaryotic and prokaryotic origin. Collectively, ubiquitin and ubiquitin-like proteins are sometimes referred to as "ubiquitons".
UBLs can be divided into two categories depending on their ability to be covalently conjugated to other molecules. UBLs that are capable of conjugation (sometimes known as Type I) have a characteristic sequence motif consisting of one to two glycine residues at the C-terminus, through which covalent conjugation occurs. Typically, UBLs are expressed as inactive precursors and must be activated by proteolysis of the C-terminus to expose the active glycine. Almost all such UBLs are ultimately linked to another protein, but there is at least one exception; ATG8 is linked to phosphatidylethanolamine. UBLs that do not exhibit covalent conjugation (Type II) often occur as protein domains genetically fused to other domains in a single larger polypeptide chain, and may be proteolytically processed to release the UBL domain or may function as protein-protein interaction domains. UBL domains of larger proteins are sometimes known as UBX domains.
== Distribution ==
Ubiquitin is, as its name suggests, ubiquitous in eukaryotes; it is traditionally considered to be absent in bacteria and archaea, though a few examples have been described in archaea. UBLs are also widely distributed in eukaryotes, but their distribution varies among lineages; for example, ISG15, involved in the regulation of the immune system, is not present in lower eukaryotes. Other families exhibit diversification in some lineages; a single member of the SUMO family is found in the yeast genome, but there are at least four in vertebrate genomes, which show some functional redundancy, and there are at least eight in the genome of the model plant Arabidopsis thaliana.
=== In humans ===
The human genome encodes at least eight families of UBLs, not including ubiquitin itself, that are considered Type I UBLs and are known to covalently modify other proteins: SUMO, NEDD8, ATG8, ATG12, URM1, UFM1, FAT10, and ISG15. One additional protein, known as FUBI, is encoded as a fusion protein in the FAU gene, and is proteolytically processed to generate a free glycine C-terminus, but has not been experimentally demonstrated to form covalent protein modifications.
=== In plants ===
Plant genomes are known to encode at least seven families of UBLs in addition to ubiquitin: SUMO, RUB (the plant homolog of NEDD8), ATG8, ATG12, MUB, UFM1, and HUB1, as well as a number of Type II UBLs. Some UBL families and their associated regulatory proteins in plants have undergone dramatic expansion, likely due to both whole genome duplication and other forms of gene duplication; the ubiquitin, SUMO, ATG8, and MUB families have been estimated to account for almost 90% of plants' UBL genes. Proteins associated with ubiquitin and SUMO signaling are highly enriched in the genomes of embryophytes.
=== In prokaryotes ===
In comparison to eukaryotes, prokaryotic proteins with relationships to UBLs are phylogenetically restricted. Prokaryotic ubiquitin-like protein (Pup) occurs in some actinobacteria and has functions closely analogous to ubiquitin in labeling proteins for proteasomal degradation; however it is intrinsically disordered and its evolutionary relationship to UBLs is unclear. A related protein UBact in some Gram-negative lineages has recently been described. By contrast, the protein TtuB in bacteria of the genus Thermus does share the beta-grasp fold with eukaryotic UBLs; it is reported to have dual functions as both a sulfur carrier protein and a covalently conjugated protein modification. In archaea, the small archaeal modifier proteins (SAMPs) share the beta-grasp fold and have been shown to play a ubiquitin-like role in protein degradation. Recently, a seemingly complete set of genes corresponding to a eukaryote-like ubiquitin pathway was identified in an uncultured archaeon in 2011, and at least three lineages of archaea—"Euryarchaeota", Thermoproteota (formerly Crenarchaeota), and "Aigarchaeota"—are believed to possess such systems. In addition, some pathogenic bacteria have evolved proteins that mimic those in eukaryotic UBL pathways and interact with UBLs in the host cell, interfering with their signaling function.
== Regulation ==
Regulation of UBLs that are capable of covalent conjugation in eukaryotes is elaborate but typically parallel for each member of the family, best characterized for ubiquitin itself. The process of ubiquitination is a tightly regulated three-step sequence: activation, performed by ubiquitin-activating enzymes (E1); conjugation, performed by ubiquitin-conjugating enzymes (E2); and ligation, performed by ubiquitin ligases (E3). The result of this process is the formation of a covalent bond between the C-terminus of ubiquitin and a residue (typically a lysine) on the target protein. Many UBL families have a similar three-step process catalyzed by a distinct set of enzymes specific to that family. Deubiquitination or deconjugation - that is, removal of ubiquitin from a protein substrate - is performed by deubiquitinating enzymes (DUBs); UBLs can also be degraded through the action of ubiquitin-specific proteases (ULPs). The range of UBLs on which these enzymes can act is variable and can be difficult to predict. Some UBLs, such as SUMO and NEDD8, have family-specific DUBs and ULPs.
Ubiquitin is capable of forming polymeric chains, with additional ubiquitin molecules covalently attached to the first, which in turn is attached to its protein substrate. These chains may be linear or branched, and different regulatory signals may be sent by differences in the length and branching of the ubiquitin chain. Although not all UBL families are known to form chains, SUMO, NEDD8, and URM1 chains have all been experimentally detected. Additionally, ubiquitin can itself be modified by UBLs, known to occur with SUMO and NEDD8. The best-characterized intersections between distinct UBL families involve ubiquitin and SUMO.
== Cellular functions ==
UBLs as a class are involved in a very large variety of cellular processes. Furthermore, individual UBL families vary in the scope of their activities and the diversity of the proteins to which they are conjugated. The best known function of ubiquitin is identifying proteins to be degraded by the proteasome, but ubiquitination can play a role in other processes such as endocytosis and other forms of protein trafficking, transcription and transcription factor regulation, cell signaling, histone modification, and DNA repair. Most other UBLs have similar roles in regulating cellular processes, usually with a more restricted known range than that of ubiquitin itself. SUMO proteins have the widest variety of cellular protein targets after ubiquitin and are involved in processes including transcription, DNA repair, and the cellular stress response. NEDD8 is best known for its role in regulating cullin proteins, which in turn regulate ubiquitin-mediated protein degradation, though it likely also has other functions. Two UBLs, ATG8 and ATG12, are involved in the process of autophagy; both are unusual in that ATG12 has only two known protein substrates and ATG8 is conjugated not to a protein but to a phospholipid, phosphatidylethanolamine.
== Evolution ==
The evolution of UBLs and their associated suites of regulatory proteins has been of interest since shortly after they were recognized as a family. Phylogenetic studies of the beta-grasp protein fold superfamily suggest that eukaryotic UBLs are monophyletic, indicating a shared evolutionary origin. UBL regulatory systems - including UBLs themselves and the cascade of enzymes that interact with them - are believed to share a common evolutionary origin with prokaryotic biosynthesis pathways for the cofactors thiamine and molybdopterin; the bacterial sulfur transfer proteins ThiS and MoaD from these pathways share the beta-grasp fold with UBLs, while sequence similarity and a common catalytic mechanism link pathway members ThiF and MoeB to ubiquitin-activating enzymes. Interestingly, the eukaryotic protein URM1 functions as both a UBL and a sulfur-carrier protein, and has been described as a molecular fossil establishing this evolutionary link.
Comparative genomics surveys of UBL families and related proteins suggest that UBL signaling was already well-developed in the last eukaryotic common ancestor and ultimately originates from ancestral archaea, a theory supported by the observation that some archaeal genomes possess the necessary genes for a fully functioning ubiquitination pathway. Two different diversification events within the UBL family have been identified in eukaryotic lineages, corresponding to the origin of multicellularity in both animal and plant lineages.
== References == | Wikipedia/Ubiquitin-like_protein |
DnaJ homolog subfamily B member 6 is a protein that in humans is encoded by the DNAJB6 gene.
== Function ==
This gene encodes a member of the DNAJ protein family. DNAJ family members are characterized by a highly conserved amino acid stretch called the 'J-domain' and function as one of the two major classes of molecular chaperones involved in a wide range of cellular events, such as protein folding and oligomeric protein complex assembly. This family member may also play a role in polyglutamine aggregation in specific neurons. Alternative splicing of this gene results in multiple transcript variants; however, not all variants have been fully described.
== Interactions ==
DNAJB6 has been shown to interact with keratin 18. It has been also shown that the aggregation of Aβ42 (a process involved in e.g. Alzheimer's disease) is retarded by DNAJB6 in a concentration-dependent manner, extending to very low sub-stoichiometric molar ratios of chaperone to peptide. Dominant mutations in DNAJB6 have also been found to cause a late-onset muscle disease termed limb-girdle muscular dystrophy type D1 (LGMDD1), which is characterized by protein aggregation and vacuolar myopathology.
== References ==
== Further reading ==
== External links ==
DNAJB6 human gene location in the UCSC Genome Browser.
DNAJB6 human gene details in the UCSC Genome Browser. | Wikipedia/DNAJB6 |
Lysosomal storage diseases (LSDs; ) are a group of over 70 rare inherited metabolic disorders that result from defects in lysosomal function. Lysosomes are sacs of enzymes within cells that digest large molecules and pass the fragments on to other parts of the cell for recycling. This process requires several critical enzymes. If one of these enzymes is defective due to a mutation, the large molecules accumulate within the cell, eventually killing it.
Lysosomal storage disorders are caused by lysosomal dysfunction usually as a consequence of deficiency of a single enzyme required for the metabolism of lipids, glycoproteins (sugar-containing proteins), or mucopolysaccharides. Individually, lysosomal storage diseases occur with incidences of less than 1:100,000; however, as a group, the incidence is about 1:5,000 – 1:10,000. Most of these disorders are autosomal recessively inherited such as Niemann–Pick disease, type C, but a few are X-linked recessively inherited, such as Fabry disease and Hunter syndrome (MPS II).
The lysosome is commonly referred to as the cell's recycling center because it processes unwanted material into substances that the cell can use. Lysosomes break down this unwanted matter by enzymes, highly specialized proteins essential for survival. Lysosomal disorders are usually triggered when a particular enzyme exists in too small an amount or is missing altogether. When this happens, substances accumulate in the cell. In other words, when the lysosome does not function normally, excess products destined for breakdown and recycling are stored in the cell.
Like other genetic disorders, individuals inherit lysosomal storage diseases from their parents. Although each disorder results from different gene mutations that translate into a deficiency in enzyme activity, they all share a common biochemical characteristic – all lysosomal disorders originate from an abnormal accumulation of substances inside the lysosome.
Lysosomal storage diseases affect mostly children and they often die at a young age, many within a few months or years of birth.
== Classification ==
=== Standard classification ===
The lysosomal storage diseases are generally classified by the nature of the primary stored material involved, and can be broadly broken into the following: (ICD-10 codes are provided where available)
(E75) Lipid storage disorders
Gangliosidoses (including Tay–Sachs disease (E75.0-E75.1) - they are a subtype of sphingolipidoses
Sphingolipidoses that are not gangliosidoses, including Gaucher's and Niemann–Pick diseases (E75.2-E75.3)
Leukodystrophies
(E76.0) Mucopolysaccharidoses, including Hunter syndrome and Hurler disease
(E77) Glycoprotein storage disorders
(E77.0-E77.1, E75.11) Mucolipidoses; Mucolipidosis IV is a gangliosidosis
Also, glycogen storage disease type II (Pompe disease) is a defect in lysosomal metabolism as well, although it is otherwise classified into E74.0 in ICD-10. Cystinosis is an lysosomal storage disease characterized by the abnormal accumulation of the amino acid cystine.
=== By type of defect protein ===
Alternatively to the protein targets, lysosomal storage diseases may be classified by the type of protein that is deficient and is causing buildup.
=== Lysosomal storage disorders ===
Lysosomal storage diseases include:
== Signs and symptoms ==
The symptoms of lysosomal storage diseases vary depending on the particular disorder and other variables such as the age of onset, and can be mild to severe. They can include developmental delay, movement disorders, seizures, dementia, deafness, and/or blindness. Some people with lysosomal storage diseases have enlarged livers or spleens, pulmonary and cardiac problems, and bones that grow abnormally.
== Diagnosis ==
The majority of patients are initially screened by enzyme assay, which is the most efficient method to arrive at a definitive diagnosis. In some families where the disease-causing mutations are known, and in certain genetic isolates, mutation analysis may be performed. In addition, after a diagnosis is made by biochemical means, mutation analysis may be performed for certain disorders.
== Treatment ==
No cures for lysosomal storage diseases are known, and treatment is mostly symptomatic, although bone marrow transplantation and enzyme replacement therapy (ERT) have been tried with some success. ERT can minimize symptoms and prevent permanent damage to the body. In addition, umbilical cord blood transplantation is being performed at specialized centers for a number of these diseases. In addition, substrate reduction therapy, a method used to decrease the production of storage material, is currently being evaluated for some of these diseases. Furthermore, chaperone therapy, a technique used to stabilize the defective enzymes produced by patients, is being examined for certain of these disorders. The experimental technique of gene therapy may offer cures in the future.
Ambroxol has recently been shown to increase activity of the lysosomal enzyme glucocerebrosidase, so it may be a useful therapeutic agent for both Gaucher disease and Parkinson's disease. Ambroxol triggers the secretion of lysosomes from cells by inducing a pH-dependent calcium release from acidic calcium stores. Hence, relieving the cell from accumulating degradation products is a proposed mechanism by which this drug may help.
== History ==
Tay–Sachs disease was the first of these disorders to be described, in 1881, followed by Gaucher disease in 1882. In the late 1950s and early 1960s, de Duve and colleagues, using cell fractionation techniques, cytological studies, and biochemical analyses, identified and characterized the lysosome as a cellular organelle responsible for intracellular digestion and recycling of macromolecules. This was the scientific breakthrough that would lead to the understanding of the physiological basis of the lysosomal storage diseases. Pompe disease was the first disease to be identified as an lysosomal storage disease in 1963, with L. Hers reporting the cause as a deficiency of α-glucosidase. Hers also suggested that other diseases, such as the mucopolysaccharidosis, might be due to enzyme deficiencies.
== See also ==
Mannosidosis
Molecular chaperone therapy
== References ==
== External links == | Wikipedia/Lysosomal_storage_diseases |
A hidden Markov model (HMM) is a Markov model in which the observations are dependent on a latent (or hidden) Markov process (referred to as
X
{\displaystyle X}
). An HMM requires that there be an observable process
Y
{\displaystyle Y}
whose outcomes depend on the outcomes of
X
{\displaystyle X}
in a known way. Since
X
{\displaystyle X}
cannot be observed directly, the goal is to learn about state of
X
{\displaystyle X}
by observing
Y
{\displaystyle Y}
. By definition of being a Markov model, an HMM has an additional requirement that the outcome of
Y
{\displaystyle Y}
at time
t
=
t
0
{\displaystyle t=t_{0}}
must be "influenced" exclusively by the outcome of
X
{\displaystyle X}
at
t
=
t
0
{\displaystyle t=t_{0}}
and that the outcomes of
X
{\displaystyle X}
and
Y
{\displaystyle Y}
at
t
<
t
0
{\displaystyle t<t_{0}}
must be conditionally independent of
Y
{\displaystyle Y}
at
t
=
t
0
{\displaystyle t=t_{0}}
given
X
{\displaystyle X}
at time
t
=
t
0
{\displaystyle t=t_{0}}
. Estimation of the parameters in an HMM can be performed using maximum likelihood estimation. For linear chain HMMs, the Baum–Welch algorithm can be used to estimate parameters.
Hidden Markov models are known for their applications to thermodynamics, statistical mechanics, physics, chemistry, economics, finance, signal processing, information theory, pattern recognition—such as speech, handwriting, gesture recognition, part-of-speech tagging, musical score following, partial discharges and bioinformatics.
== Definition ==
Let
X
n
{\displaystyle X_{n}}
and
Y
n
{\displaystyle Y_{n}}
be discrete-time stochastic processes and
n
≥
1
{\displaystyle n\geq 1}
. The pair
(
X
n
,
Y
n
)
{\displaystyle (X_{n},Y_{n})}
is a hidden Markov model if
X
n
{\displaystyle X_{n}}
is a Markov process whose behavior is not directly observable ("hidden");
P
(
Y
n
∈
A
|
X
1
=
x
1
,
…
,
X
n
=
x
n
)
=
P
(
Y
n
∈
A
|
X
n
=
x
n
)
{\displaystyle \operatorname {\mathbf {P} } {\bigl (}Y_{n}\in A\ {\bigl |}\ X_{1}=x_{1},\ldots ,X_{n}=x_{n}{\bigr )}=\operatorname {\mathbf {P} } {\bigl (}Y_{n}\in A\ {\bigl |}\ X_{n}=x_{n}{\bigr )}}
,
for every
n
≥
1
{\displaystyle n\geq 1}
,
x
1
,
…
,
x
n
{\displaystyle x_{1},\ldots ,x_{n}}
, and every Borel set
A
{\displaystyle A}
.
Let
X
t
{\displaystyle X_{t}}
and
Y
t
{\displaystyle Y_{t}}
be continuous-time stochastic processes. The pair
(
X
t
,
Y
t
)
{\displaystyle (X_{t},Y_{t})}
is a hidden Markov model if
X
t
{\displaystyle X_{t}}
is a Markov process whose behavior is not directly observable ("hidden");
P
(
Y
t
0
∈
A
∣
{
X
t
∈
B
t
}
t
≤
t
0
)
=
P
(
Y
t
0
∈
A
∣
X
t
0
∈
B
t
0
)
{\displaystyle \operatorname {\mathbf {P} } (Y_{t_{0}}\in A\mid \{X_{t}\in B_{t}\}_{t\leq t_{0}})=\operatorname {\mathbf {P} } (Y_{t_{0}}\in A\mid X_{t_{0}}\in B_{t_{0}})}
,
for every
t
0
{\displaystyle t_{0}}
, every Borel set
A
{\displaystyle A}
, and every family of Borel sets
{
B
t
}
t
≤
t
0
{\displaystyle \{B_{t}\}_{t\leq t_{0}}}
.
=== Terminology ===
The states of the process
X
n
{\displaystyle X_{n}}
(resp.
X
t
)
{\displaystyle X_{t})}
are called hidden states, and
P
(
Y
n
∈
A
∣
X
n
=
x
n
)
{\displaystyle \operatorname {\mathbf {P} } {\bigl (}Y_{n}\in A\mid X_{n}=x_{n}{\bigr )}}
(resp.
P
(
Y
t
∈
A
∣
X
t
∈
B
t
)
)
{\displaystyle \operatorname {\mathbf {P} } {\bigl (}Y_{t}\in A\mid X_{t}\in B_{t}{\bigr )})}
is called emission probability or output probability.
== Examples ==
=== Drawing balls from hidden urns ===
In its discrete form, a hidden Markov process can be visualized as a generalization of the urn problem with replacement (where each item from the urn is returned to the original urn before the next step). Consider this example: in a room that is not visible to an observer there is a genie. The room contains urns X1, X2, X3, ... each of which contains a known mix of balls, with each ball having a unique label y1, y2, y3, ... . The genie chooses an urn in that room and randomly draws a ball from that urn. It then puts the ball onto a conveyor belt, where the observer can observe the sequence of the balls but not the sequence of urns from which they were drawn. The genie has some procedure to choose urns; the choice of the urn for the n-th ball depends only upon a random number and the choice of the urn for the (n − 1)-th ball. The choice of urn does not directly depend on the urns chosen before this single previous urn; therefore, this is called a Markov process. It can be described by the upper part of Figure 1.
The Markov process cannot be observed, only the sequence of labeled balls, thus this arrangement is called a hidden Markov process. This is illustrated by the lower part of the diagram shown in Figure 1, where one can see that balls y1, y2, y3, y4 can be drawn at each state. Even if the observer knows the composition of the urns and has just observed a sequence of three balls, e.g. y1, y2 and y3 on the conveyor belt, the observer still cannot be sure which urn (i.e., at which state) the genie has drawn the third ball from. However, the observer can work out other information, such as the likelihood that the third ball came from each of the urns.
=== Weather guessing game ===
Consider two friends, Alice and Bob, who live far apart from each other and who talk together daily over the telephone about what they did that day. Bob is only interested in three activities: walking in the park, shopping, and cleaning his apartment. The choice of what to do is determined exclusively by the weather on a given day. Alice has no definite information about the weather, but she knows general trends. Based on what Bob tells her he did each day, Alice tries to guess what the weather must have been like.
Alice believes that the weather operates as a discrete Markov chain. There are two states, "Rainy" and "Sunny", but she cannot observe them directly, that is, they are hidden from her. On each day, there is a certain chance that Bob will perform one of the following activities, depending on the weather: "walk", "shop", or "clean". Since Bob tells Alice about his activities, those are the observations. The entire system is that of a hidden Markov model (HMM).
Alice knows the general weather trends in the area, and what Bob likes to do on average. In other words, the parameters of the HMM are known. They can be represented as follows in Python:
In this piece of code, start_probability represents Alice's belief about which state the HMM is in when Bob first calls her (all she knows is that it tends to be rainy on average). The particular probability distribution used here is not the equilibrium one, which is (given the transition probabilities) approximately {'Rainy': 0.57, 'Sunny': 0.43}. The transition_probability represents the change of the weather in the underlying Markov chain. In this example, there is only a 30% chance that tomorrow will be sunny if today is rainy. The emission_probability represents how likely Bob is to perform a certain activity on each day. If it is rainy, there is a 50% chance that he is cleaning his apartment; if it is sunny, there is a 60% chance that he is outside for a walk.
A similar example is further elaborated in the Viterbi algorithm page.
== Structural architecture ==
The diagram below shows the general architecture of an instantiated HMM. Each oval shape represents a random variable that can adopt any of a number of values. The random variable x(t) is the hidden state at time t (with the model from the above diagram, x(t) ∈ { x1, x2, x3 }). The random variable y(t) is the observation at time t (with y(t) ∈ { y1, y2, y3, y4 }). The arrows in the diagram (often called a trellis diagram) denote conditional dependencies.
From the diagram, it is clear that the conditional probability distribution of the hidden variable x(t) at time t, given the values of the hidden variable x at all times, depends only on the value of the hidden variable x(t − 1); the values at time t − 2 and before have no influence. This is called the Markov property. Similarly, the value of the observed variable y(t) depends on only the value of the hidden variable x(t) (both at time t).
In the standard type of hidden Markov model considered here, the state space of the hidden variables is discrete, while the observations themselves can either be discrete (typically generated from a categorical distribution) or continuous (typically from a Gaussian distribution). The parameters of a hidden Markov model are of two types, transition probabilities and emission probabilities (also known as output probabilities). The transition probabilities control the way the hidden state at time t is chosen given the hidden state at time
t
−
1
{\displaystyle t-1}
.
The hidden state space is assumed to consist of one of N possible values, modelled as a categorical distribution. (See the section below on extensions for other possibilities.) This means that for each of the N possible states that a hidden variable at time t can be in, there is a transition probability from this state to each of the N possible states of the hidden variable at time
t
+
1
{\displaystyle t+1}
, for a total of
N
2
{\displaystyle N^{2}}
transition probabilities. The set of transition probabilities for transitions from any given state must sum to 1. Thus, the
N
×
N
{\displaystyle N\times N}
matrix of transition probabilities is a Markov matrix. Because any transition probability can be determined once the others are known, there are a total of
N
(
N
−
1
)
{\displaystyle N(N-1)}
transition parameters.
In addition, for each of the N possible states, there is a set of emission probabilities governing the distribution of the observed variable at a particular time given the state of the hidden variable at that time. The size of this set depends on the nature of the observed variable. For example, if the observed variable is discrete with M possible values, governed by a categorical distribution, there will be
M
−
1
{\displaystyle M-1}
separate parameters, for a total of
N
(
M
−
1
)
{\displaystyle N(M-1)}
emission parameters over all hidden states. On the other hand, if the observed variable is an M-dimensional vector distributed according to an arbitrary multivariate Gaussian distribution, there will be M parameters controlling the means and
M
(
M
+
1
)
2
{\displaystyle {\frac {M(M+1)}{2}}}
parameters controlling the covariance matrix, for a total of
N
(
M
+
M
(
M
+
1
)
2
)
=
N
M
(
M
+
3
)
2
=
O
(
N
M
2
)
{\displaystyle N\left(M+{\frac {M(M+1)}{2}}\right)={\frac {NM(M+3)}{2}}=O(NM^{2})}
emission parameters. (In such a case, unless the value of M is small, it may be more practical to restrict the nature of the covariances between individual elements of the observation vector, e.g. by assuming that the elements are independent of each other, or less restrictively, are independent of all but a fixed number of adjacent elements.)
== Inference ==
Several inference problems are associated with hidden Markov models, as outlined below.
=== Probability of an observed sequence ===
The task is to compute in a best way, given the parameters of the model, the probability of a particular output sequence. This requires summation over all possible state sequences:
The probability of observing a sequence
Y
=
y
(
0
)
,
y
(
1
)
,
…
,
y
(
L
−
1
)
,
{\displaystyle Y=y(0),y(1),\dots ,y(L-1),}
of length L is given by
P
(
Y
)
=
∑
X
P
(
Y
∣
X
)
P
(
X
)
,
{\displaystyle P(Y)=\sum _{X}P(Y\mid X)P(X),}
where the sum runs over all possible hidden-node sequences
X
=
x
(
0
)
,
x
(
1
)
,
…
,
x
(
L
−
1
)
.
{\displaystyle X=x(0),x(1),\dots ,x(L-1).}
Applying the principle of dynamic programming, this problem, too, can be handled efficiently using the forward algorithm.
=== Probability of the latent variables ===
A number of related tasks ask about the probability of one or more of the latent variables, given the model's parameters and a sequence of observations
y
(
1
)
,
…
,
y
(
t
)
{\displaystyle y(1),\dots ,y(t)}
.
==== Filtering ====
The task is to compute, given the model's parameters and a sequence of observations, the distribution over hidden states of the last latent variable at the end of the sequence, i.e. to compute
P
(
x
(
t
)
∣
y
(
1
)
,
…
,
y
(
t
)
)
{\displaystyle P(x(t)\mid y(1),\dots ,y(t))}
. This task is used when the sequence of latent variables is thought of as the underlying states that a process moves through at a sequence of points in time, with corresponding observations at each point. Then, it is natural to ask about the state of the process at the end.
This problem can be handled efficiently using the forward algorithm. An example is when the algorithm is applied to a Hidden Markov Network to determine
P
(
h
t
∣
v
1
:
t
)
{\displaystyle \mathrm {P} {\big (}h_{t}\mid v_{1:t}{\big )}}
.
==== Smoothing ====
This is similar to filtering but asks about the distribution of a latent variable somewhere in the middle of a sequence, i.e. to compute
P
(
x
(
k
)
∣
y
(
1
)
,
…
,
y
(
t
)
)
{\displaystyle P(x(k)\mid y(1),\dots ,y(t))}
for some
k
<
t
{\displaystyle k<t}
. From the perspective described above, this can be thought of as the probability distribution over hidden states for a point in time k in the past, relative to time t.
The forward-backward algorithm is a good method for computing the smoothed values for all hidden state variables.
==== Most likely explanation ====
The task, unlike the previous two, asks about the joint probability of the entire sequence of hidden states that generated a particular sequence of observations (see illustration on the right). This task is generally applicable when HMM's are applied to different sorts of problems from those for which the tasks of filtering and smoothing are applicable. An example is part-of-speech tagging, where the hidden states represent the underlying parts of speech corresponding to an observed sequence of words. In this case, what is of interest is the entire sequence of parts of speech, rather than simply the part of speech for a single word, as filtering or smoothing would compute.
This task requires finding a maximum over all possible state sequences, and can be solved efficiently by the Viterbi algorithm.
=== Statistical significance ===
For some of the above problems, it may also be interesting to ask about statistical significance. What is the probability that a sequence drawn from some null distribution will have an HMM probability (in the case of the forward algorithm) or a maximum state sequence probability (in the case of the Viterbi algorithm) at least as large as that of a particular output sequence? When an HMM is used to evaluate the relevance of a hypothesis for a particular output sequence, the statistical significance indicates the false positive rate associated with failing to reject the hypothesis for the output sequence.
== Learning ==
The parameter learning task in HMMs is to find, given an output sequence or a set of such sequences, the best set of state transition and emission probabilities. The task is usually to derive the maximum likelihood estimate of the parameters of the HMM given the set of output sequences. No tractable algorithm is known for solving this problem exactly, but a local maximum likelihood can be derived efficiently using the Baum–Welch algorithm or the Baldi–Chauvin algorithm. The Baum–Welch algorithm is a special case of the expectation-maximization algorithm.
If the HMMs are used for time series prediction, more sophisticated Bayesian inference methods, like Markov chain Monte Carlo (MCMC) sampling are proven to be favorable over finding a single maximum likelihood model both in terms of accuracy and stability. Since MCMC imposes significant computational burden, in cases where computational scalability is also of interest, one may alternatively resort to variational approximations to Bayesian inference, e.g. Indeed, approximate variational inference offers computational efficiency comparable to expectation-maximization, while yielding an accuracy profile only slightly inferior to exact MCMC-type Bayesian inference.
== Applications ==
HMMs can be applied in many fields where the goal is to recover a data sequence that is not immediately observable (but other data that depend on the sequence are). Applications include:
Computational finance
Single-molecule kinetic analysis
Neuroscience
Cryptanalysis
Speech recognition, including Siri
Speech synthesis
Part-of-speech tagging
Document separation in scanning solutions
Machine translation
Partial discharge
Gene prediction
Handwriting recognition
Alignment of bio-sequences
Time series analysis
Activity recognition
Protein folding
Sequence classification
Metamorphic virus detection
Sequence motif discovery (DNA and proteins)
DNA hybridization kinetics
Chromatin state discovery
Transportation forecasting
Solar irradiance variability
== History ==
Hidden Markov models were described in a series of statistical papers by Leonard E. Baum and other authors in the second half of the 1960s. One of the first applications of HMMs was speech recognition, starting in the mid-1970s. From the linguistics point of view, hidden Markov models are equivalent to stochastic regular grammar.
In the second half of the 1980s, HMMs began to be applied to the analysis of biological sequences, in particular DNA. Since then, they have become ubiquitous in the field of bioinformatics.
== Extensions ==
=== General state spaces ===
In the hidden Markov models considered above, the state space of the hidden variables is discrete, while the observations themselves can either be discrete (typically generated from a categorical distribution) or continuous (typically from a Gaussian distribution). Hidden Markov models can also be generalized to allow continuous state spaces. Examples of such models are those where the Markov process over hidden variables is a linear dynamical system, with a linear relationship among related variables and where all hidden and observed variables follow a Gaussian distribution. In simple cases, such as the linear dynamical system just mentioned, exact inference is tractable (in this case, using the Kalman filter); however, in general, exact inference in HMMs with continuous latent variables is infeasible, and approximate methods must be used, such as the extended Kalman filter or the particle filter.
Nowadays, inference in hidden Markov models is performed in nonparametric settings, where the dependency structure enables identifiability of the model and the learnability limits are still under exploration.
=== Bayesian modeling of the transitions probabilities ===
Hidden Markov models are generative models, in which the joint distribution of observations and hidden states, or equivalently both the prior distribution of hidden states (the transition probabilities) and conditional distribution of observations given states (the emission probabilities), is modeled. The above algorithms implicitly assume a uniform prior distribution over the transition probabilities. However, it is also possible to create hidden Markov models with other types of prior distributions. An obvious candidate, given the categorical distribution of the transition probabilities, is the Dirichlet distribution, which is the conjugate prior distribution of the categorical distribution. Typically, a symmetric Dirichlet distribution is chosen, reflecting ignorance about which states are inherently more likely than others. The single parameter of this distribution (termed the concentration parameter) controls the relative density or sparseness of the resulting transition matrix. A choice of 1 yields a uniform distribution. Values greater than 1 produce a dense matrix, in which the transition probabilities between pairs of states are likely to be nearly equal. Values less than 1 result in a sparse matrix in which, for each given source state, only a small number of destination states have non-negligible transition probabilities. It is also possible to use a two-level prior Dirichlet distribution, in which one Dirichlet distribution (the upper distribution) governs the parameters of another Dirichlet distribution (the lower distribution), which in turn governs the transition probabilities. The upper distribution governs the overall distribution of states, determining how likely each state is to occur; its concentration parameter determines the density or sparseness of states. Such a two-level prior distribution, where both concentration parameters are set to produce sparse distributions, might be useful for example in unsupervised part-of-speech tagging, where some parts of speech occur much more commonly than others; learning algorithms that assume a uniform prior distribution generally perform poorly on this task. The parameters of models of this sort, with non-uniform prior distributions, can be learned using Gibbs sampling or extended versions of the expectation-maximization algorithm.
An extension of the previously described hidden Markov models with Dirichlet priors uses a Dirichlet process in place of a Dirichlet distribution. This type of model allows for an unknown and potentially infinite number of states. It is common to use a two-level Dirichlet process, similar to the previously described model with two levels of Dirichlet distributions. Such a model is called a hierarchical Dirichlet process hidden Markov model, or HDP-HMM for short. It was originally described under the name "Infinite Hidden Markov Model" and was further formalized in "Hierarchical Dirichlet Processes".
=== Discriminative approach ===
A different type of extension uses a discriminative model in place of the generative model of standard HMMs. This type of model directly models the conditional distribution of the hidden states given the observations, rather than modeling the joint distribution. An example of this model is the so-called maximum entropy Markov model (MEMM), which models the conditional distribution of the states using logistic regression (also known as a "maximum entropy model"). The advantage of this type of model is that arbitrary features (i.e. functions) of the observations can be modeled, allowing domain-specific knowledge of the problem at hand to be injected into the model. Models of this sort are not limited to modeling direct dependencies between a hidden state and its associated observation; rather, features of nearby observations, of combinations of the associated observation and nearby observations, or in fact of arbitrary observations at any distance from a given hidden state can be included in the process used to determine the value of a hidden state. Furthermore, there is no need for these features to be statistically independent of each other, as would be the case if such features were used in a generative model. Finally, arbitrary features over pairs of adjacent hidden states can be used rather than simple transition probabilities. The disadvantages of such models are: (1) The types of prior distributions that can be placed on hidden states are severely limited; (2) It is not possible to predict the probability of seeing an arbitrary observation. This second limitation is often not an issue in practice, since many common usages of HMM's do not require such predictive probabilities.
A variant of the previously described discriminative model is the linear-chain conditional random field. This uses an undirected graphical model (aka Markov random field) rather than the directed graphical models of MEMM's and similar models. The advantage of this type of model is that it does not suffer from the so-called label bias problem of MEMM's, and thus may make more accurate predictions. The disadvantage is that training can be slower than for MEMM's.
=== Other extensions ===
Yet another variant is the factorial hidden Markov model, which allows for a single observation to be conditioned on the corresponding hidden variables of a set of
K
{\displaystyle K}
independent Markov chains, rather than a single Markov chain. It is equivalent to a single HMM, with
N
K
{\displaystyle N^{K}}
states (assuming there are
N
{\displaystyle N}
states for each chain), and therefore, learning in such a model is difficult: for a sequence of length
T
{\displaystyle T}
, a straightforward Viterbi algorithm has complexity
O
(
N
2
K
T
)
{\displaystyle O(N^{2K}\,T)}
. To find an exact solution, a junction tree algorithm could be used, but it results in an
O
(
N
K
+
1
K
T
)
{\displaystyle O(N^{K+1}\,K\,T)}
complexity. In practice, approximate techniques, such as variational approaches, could be used.
All of the above models can be extended to allow for more distant dependencies among hidden states, e.g. allowing for a given state to be dependent on the previous two or three states rather than a single previous state; i.e. the transition probabilities are extended to encompass sets of three or four adjacent states (or in general
K
{\displaystyle K}
adjacent states). The disadvantage of such models is that dynamic-programming algorithms for training them have an
O
(
N
K
T
)
{\displaystyle O(N^{K}\,T)}
running time, for
K
{\displaystyle K}
adjacent states and
T
{\displaystyle T}
total observations (i.e. a length-
T
{\displaystyle T}
Markov chain). This extension has been widely used in bioinformatics, in the modeling of DNA sequences.
Another recent extension is the triplet Markov model, in which an auxiliary underlying process is added to model some data specificities. Many variants of this model have been proposed. One should also mention the interesting link that has been established between the theory of evidence and the triplet Markov models and which allows to fuse data in Markovian context and to model nonstationary data. Alternative multi-stream data fusion strategies have also been proposed in recent literature, e.g.,
Finally, a different rationale towards addressing the problem of modeling nonstationary data by means of hidden Markov models was suggested in 2012. It consists in employing a small recurrent neural network (RNN), specifically a reservoir network, to capture the evolution of the temporal dynamics in the observed data. This information, encoded in the form of a high-dimensional vector, is used as a conditioning variable of the HMM state transition probabilities. Under such a setup, eventually is obtained a nonstationary HMM, the transition probabilities of which evolve over time in a manner that is inferred from the data, in contrast to some unrealistic ad-hoc model of temporal evolution.
In 2023, two innovative algorithms were introduced for the Hidden Markov Model. These algorithms enable the computation of the posterior distribution of the HMM without the necessity of explicitly modeling the joint distribution, utilizing only the conditional distributions. Unlike traditional methods such as the Forward-Backward and Viterbi algorithms, which require knowledge of the joint law of the HMM and can be computationally intensive to learn, the Discriminative Forward-Backward and Discriminative Viterbi algorithms circumvent the need for the observation's law. This breakthrough allows the HMM to be applied as a discriminative model, offering a more efficient and versatile approach to leveraging Hidden Markov Models in various applications.
The model suitable in the context of longitudinal data is named latent Markov model. The basic version of this model has been extended to include individual covariates, random effects and to model more complex data structures such as multilevel data. A complete overview of the latent Markov models, with special attention to the model assumptions and to their practical use is provided in
== Measure theory ==
Given a Markov transition matrix and an invariant distribution on the states, a probability measure can be imposed on the set of subshifts. For example, consider the Markov chain given on the left on the states
A
,
B
1
,
B
2
{\displaystyle A,B_{1},B_{2}}
, with invariant distribution
π
=
(
2
/
7
,
4
/
7
,
1
/
7
)
{\displaystyle \pi =(2/7,4/7,1/7)}
. By ignoring the distinction between
B
1
,
B
2
{\displaystyle B_{1},B_{2}}
, this space of subshifts is projected on
A
,
B
1
,
B
2
{\displaystyle A,B_{1},B_{2}}
into another space of subshifts on
A
,
B
{\displaystyle A,B}
, and this projection also projects the probability measure down to a probability measure on the subshifts on
A
,
B
{\displaystyle A,B}
.
The curious thing is that the probability measure on the subshifts on
A
,
B
{\displaystyle A,B}
is not created by a Markov chain on
A
,
B
{\displaystyle A,B}
, not even multiple orders. Intuitively, this is because if one observes a long sequence of
B
n
{\displaystyle B^{n}}
, then one would become increasingly sure that the
Pr
(
A
∣
B
n
)
→
2
3
{\displaystyle \Pr(A\mid B^{n})\to {\frac {2}{3}}}
, meaning that the observable part of the system can be affected by something infinitely in the past.
Conversely, there exists a space of subshifts on 6 symbols, projected to subshifts on 2 symbols, such that any Markov measure on the smaller subshift has a preimage measure that is not Markov of any order (example 2.6).
== See also ==
== References ==
== External links ==
=== Concepts ===
Teif, V. B.; Rippe, K. (2010). "Statistical–mechanical lattice models for protein–DNA binding in chromatin". J. Phys.: Condens. Matter. 22 (41): 414105. arXiv:1004.5514. Bibcode:2010JPCM...22O4105T. doi:10.1088/0953-8984/22/41/414105. PMID 21386588. S2CID 103345.
A Revealing Introduction to Hidden Markov Models by Mark Stamp, San Jose State University.
Fitting HMM's with expectation-maximization – complete derivation
A step-by-step tutorial on HMMs Archived 2017-08-13 at the Wayback Machine (University of Leeds)
Hidden Markov Models (an exposition using basic mathematics)
Hidden Markov Models (by Narada Warakagoda)
Hidden Markov Models: Fundamentals and Applications Part 1, Part 2 (by V. Petrushin)
Lecture on a Spreadsheet by Jason Eisner, Video and interactive spreadsheet | Wikipedia/Markov_state_model |
In medicine, proteinopathy ([pref. protein]; -pathy [suff. disease]; proteinopathies pl.; proteinopathic adj), or proteopathy, protein conformational disorder, or protein misfolding disease, is a class of diseases in which certain proteins become structurally abnormal, and thereby disrupt the function of cells, tissues and organs of the body.
Often the proteins fail to fold into their normal configuration; in this misfolded state, the proteins can become toxic in some way (a toxic gain-of-function) or they can lose their normal function. The proteinopathies include such diseases as Creutzfeldt–Jakob disease (and a variant associated with mad cow disease) and other prion diseases, Alzheimer's disease, Parkinson's disease, amyloidosis, multiple system atrophy, and a wide range of other disorders. The term proteopathy was first proposed in 2000 by Lary Walker and Harry LeVine.
The concept of proteopathy can trace its origins to the mid-19th century, when, in 1854, Rudolf Virchow coined the term amyloid ("starch-like") to describe a substance in cerebral corpora amylacea that exhibited a chemical reaction resembling that of cellulose. In 1859, Friedreich and Kekulé demonstrated that, rather than consisting of cellulose, "amyloid" actually is rich in protein. Subsequent research has shown that many different proteins can form amyloid, and that all amyloids show birefringence in cross-polarized light after staining with the dye Congo red, as well as a fibrillar ultrastructure when viewed with an electron microscope. However, some proteinaceous lesions lack birefringence and contain few or no classical amyloid fibrils, such as the diffuse deposits of amyloid beta (Aβ) protein in the brains of people with Alzheimer's. Furthermore, evidence has emerged that small, non-fibrillar protein aggregates known as oligomers are toxic to the cells of an affected organ, and that amyloidogenic proteins in their fibrillar form may be relatively benign.
== Pathophysiology ==
In most, if not all proteinopathies, a change in the 3-dimensional folding conformation increases the tendency of a specific protein to bind to itself. In this aggregated form, the protein is resistant to clearance and can interfere with the normal capacity of the affected organs. In some cases, misfolding of the protein results in a loss of its usual function. For example, cystic fibrosis is caused by a defective cystic fibrosis transmembrane conductance regulator (CFTR) protein, and in amyotrophic lateral sclerosis / frontotemporal lobar degeneration (FTLD), certain gene-regulating proteins inappropriately aggregate in the cytoplasm, and thus are unable to perform their normal tasks within the nucleus.
Because proteins share a common structural feature known as the polypeptide backbone, all proteins have the potential to misfold under some circumstances. However, only a relatively small number of proteins are linked to proteopathic disorders, possibly due to structural idiosyncrasies of the vulnerable proteins. For example, proteins that are normally unfolded or relatively unstable as monomers (that is, as single, unbound protein molecules) are more likely to misfold into an abnormal conformation. In nearly all instances, the disease-causing molecular configuration involves an increase in beta-sheet secondary structure of the protein.
The abnormal proteins in some proteopathies have been shown to fold into multiple 3-dimensional shapes; these variant, proteinaceous structures are defined by their different pathogenic, biochemical, and conformational properties. They have been most thoroughly studied with regard to prion disease, and are referred to as protein strains.
The likelihood that proteinopathy will develop is increased by certain risk factors that promote the self-assembly of a protein. These include destabilizing changes in the primary amino acid sequence of the protein, post-translational modifications (such as hyperphosphorylation), changes in temperature or pH, an increase in production of a protein, or a decrease in its clearance. Advancing age is a strong risk factor, as is traumatic brain injury. In the aging brain, multiple proteopathies can overlap. For example, in addition to tauopathy and Aβ-amyloidosis (which coexist as key pathologic features of Alzheimer's disease), many Alzheimer patients have concomitant synucleinopathy (Lewy bodies) in the brain.
It is hypothesized that chaperones and co-chaperones (proteins that assist protein folding) may antagonize proteotoxicity during aging and in protein misfolding-diseases to maintain proteostasis.
== Seeded induction ==
Some proteins can be induced to form abnormal assemblies by exposure to the same (or similar) protein that has folded into a disease-causing conformation, a process called 'seeding' or 'permissive templating'. In this way, the disease state can be brought about in a susceptible host by the introduction of diseased tissue extract from an affected donor. The best known forms of inducible proteopathy are prion diseases, which can be transmitted by exposure of a host organism to purified prion protein in a disease-causing conformation.
There is now evidence that other proteinopathies can be induced by a similar mechanism, including Aβ amyloidosis, amyloid A (AA) amyloidosis, and apolipoprotein AII amyloidosis, tauopathy, synucleinopathy, and the aggregation of superoxide dismutase-1 (SOD1), polyglutamine, and TAR DNA-binding protein-43 (TDP-43).
In all of these instances, an aberrant form of the protein itself appears to be the pathogenic agent. In some cases, the deposition of one type of protein can be experimentally induced by aggregated assemblies of other proteins that are rich in β-sheet structure, possibly because of structural complementarity of the protein molecules. For example, AA amyloidosis can be stimulated in mice by such diverse macromolecules as silk, the yeast amyloid Sup35, and curli fibrils from the bacterium Escherichia coli. AII amyloid can be induced in mice by a variety of β-sheet rich amyloid fibrils, and cerebral tauopathy can be induced by brain extracts that are rich in aggregated Aβ. There is also experimental evidence for cross-seeding between prion protein and Aβ. In general, such heterologous seeding is less efficient than is seeding by a corrupted form of the same protein.
== List of proteinopathies ==
== Management ==
The development of effective treatments for many proteopathies has been challenging. Because the proteopathies often involve different proteins arising from different sources, treatment strategies must be customized to each disorder; however, general therapeutic approaches include maintaining the function of affected organs, reducing the formation of the disease-causing proteins, preventing the proteins from misfolding and/or aggregating, or promoting their removal. For example, in Alzheimer's disease, researchers are seeking ways to reduce the production of the disease-associated protein Aβ by inhibiting the enzymes that free it from its parent protein. Another strategy is to use antibodies to neutralize specific proteins by active or passive immunization. In some proteopathies, inhibiting the toxic effects of protein oligomers might be beneficial.
For example, Amyloid A (AA) amyloidosis can be reduced by treating the inflammatory state that increases the amount of the protein in the blood (referred to as serum amyloid A, or SAA). In immunoglobulin light chain amyloidosis (AL amyloidosis), chemotherapy can be used to lower the number of the blood cells that make the light chain protein that forms amyloid in various bodily organs. Transthyretin (TTR) amyloidosis (ATTR) results from the deposition of misfolded TTR in multiple organs. Because TTR is mainly produced in the liver, TTR amyloidosis can be slowed in some hereditary cases by liver transplantation. TTR amyloidosis also can be treated by stabilizing the normal assemblies of the protein (called tetramers because they consist of four TTR molecules bound together). Stabilization prevents individual TTR molecules from escaping, misfolding, and aggregating into amyloid.
Several other treatment strategies for proteopathies are being investigated, including small molecules and biologic medicines such as small interfering RNAs, antisense oligonucleotides, peptides, and engineered immune cells. In some cases, multiple therapeutic agents may be combined to improve effectiveness.
== Additional images ==
== See also ==
Amyloidosis
Neurofibrillary tangles
Protein toxicity
Prion
Transmissible spongiform encephalopathy
== References ==
== External links ==
Amyloidosis
Prion-Related Diseases
Protein Misfolding Diseases Book | Wikipedia/Proteinopathy |
Creutzfeldt–Jakob disease (CJD) is an incurable, always fatal neurodegenerative disease belonging to the transmissible spongiform encephalopathy (TSE) group. Early symptoms include memory problems, behavioral changes, poor coordination, visual disturbances and auditory disturbances. Later symptoms include dementia, involuntary movements, blindness, deafness, weakness, and coma. About 70% of sufferers die within a year of diagnosis. The name "Creutzfeldt–Jakob disease" was introduced by Walther Spielmeyer in 1922, after the German neurologists Hans Gerhard Creutzfeldt and Alfons Maria Jakob.
CJD is caused by abnormal folding of a protein known as a prion. Infectious prions are misfolded proteins that can cause normally folded proteins to also become misfolded. About 85% of cases of CJD occur for unknown reasons, while about 7.5% of cases are inherited in an autosomal dominant manner. Exposure to brain or spinal tissue from an infected person may also result in spread. There is no evidence that sporadic CJD can spread among people via normal contact or blood transfusions, although this is possible in variant Creutzfeldt–Jakob disease. Diagnosis involves ruling out other potential causes. An electroencephalogram, spinal tap, or magnetic resonance imaging may support the diagnosis. Another diagnosis technique is the real-time quaking-induced conversion assay which can detect the disease in early stages.
There is no specific treatment for CJD. Opioids may be used to help with pain, while clonazepam or sodium valproate may help with involuntary movements. CJD affects about one person per million people per year. Onset is typically around 60 years of age. The condition was first described in 1920. It is classified as a type of transmissible spongiform encephalopathy. Inherited CJD accounts for about 10% of prion disease cases. Sporadic CJD is different from bovine spongiform encephalopathy (mad cow disease) and variant Creutzfeldt–Jakob disease (vCJD).
== Signs and symptoms ==
The first symptom of CJD is usually rapidly progressive dementia, leading to memory loss, personality changes, and hallucinations. Myoclonus (jerky movements) typically occurs in 90% of cases, but may be absent at initial onset. Other frequently occurring features include anxiety, depression, paranoia, obsessive-compulsive symptoms, and psychosis. This is accompanied by physical problems such as speech impairment, balance and coordination dysfunction (ataxia), changes in gait, and rigid posture. In most people with CJD, these symptoms are accompanied by involuntary movements. Rarely, unusual symptoms like the alien limb phenomenon have been observed. The duration of the disease varies greatly, but sporadic (non-inherited) CJD can be fatal within months or even weeks. Most affected people die six months after initial symptoms appear, often of pneumonia due to impaired coughing reflexes. About 15% of people with CJD survive for two or more years.
The symptoms of CJD are caused by the progressive death of the brain's nerve cells, which are associated with the build-up of abnormal prion proteins forming in the brain. When brain tissue from a person with CJD is examined under a microscope, many tiny holes can be seen where the nerve cells have died. Parts of the brain may resemble a sponge where the prions were infecting the areas of the brain.
== Cause ==
CJD is a type of transmissible spongiform encephalopathy (TSE), which are caused by prions. Prions are misfolded proteins that occur in the neurons of the central nervous system (CNS). Current research suggests that small, oligomeric aggregates of PrP^Sc (rather than large fibrils) are the most neurotoxic species, interacting with cell surfaces to disrupt neuronal function . The binding of prion oligomers to normal prion protein on neurons may trigger toxic signals similar to how oligomeric β-amyloid causes synaptic damage in Alzheimer’s disease . Different conformations of PrP^Sc (often termed prion “strains”) are thought to cause the distinct subtypes of prion disease, explaining variations in clinical features and progression. They are thought to affect signaling processes, damaging neurons and resulting in degeneration that causes the spongiform appearance in the affected brain. Other forms of TSEs that are found in humans are Gerstmann–Sträussler–Scheinker syndrome, fatal familial insomnia, and kuru, as well as the variably protease-sensitive prionopathy and familial spongiform encephalopathy transmissible spongiform encephalopathy. Susceptibility and disease phenotype are influenced by a common polymorphism at codon 129 of the PRNP gene (methionine/valine). Notably, individuals homozygous at codon 129 are over-represented in sporadic CJD cases and tend to have shorter incubation periods.
The CJD prion is dangerous because it promotes refolding of the cellular prion protein into the diseased state. The number of misfolded protein molecules will increase exponentially and the process leads to a large quantity of insoluble protein in affected cells. This mass of misfolded proteins disrupts neuronal cell function and causes cell death. Mutations in the gene for the prion protein can cause a misfolding of the dominantly alpha helical regions into beta pleated sheets. This change in conformation disables the ability of the protein to undergo digestion. Once the prion is transmitted, the defective proteins invade the brain and induce other prion protein molecules to misfold in a self-sustaining feedback loop. These neurodegenerative diseases are commonly called prion diseases.
=== Transmission ===
The defective protein can be transmitted by contaminated harvested human brain products, corneal grafts, dural grafts, or electrode implants and pituitary human growth hormone, which has been replaced by recombinant human growth hormone that poses no such risk.
It can be familial (fCJD) or it may appear without clear risk factors (sporadic form: sCJD). In the familial form, a mutation has occurred in the gene for PrP, PRNP, in that family. All types of CJD are transmissible irrespective of how they occur in the person.
It is thought that humans can contract the variant form of the disease by eating food from animals infected with bovine spongiform encephalopathy (BSE), the bovine form of TSE, also known as mad cow disease. However, it can also cause sCJD in some cases.
Cannibalism has also been implicated as a transmission mechanism for abnormal prions, causing the disease known as kuru, once found primarily among women and children of the Fore people in Papua New Guinea, who previously engaged in funerary cannibalism. While the men of the tribe ate the muscle tissue of the deceased, women and children consumed other parts, such as the brain, and were more likely than men to contract kuru from infected tissue.
Prions, the infectious agent of CJD, may not be inactivated by means of routine surgical instrument sterilization procedures. The World Health Organization and the US Centers for Disease Control and Prevention recommend that instrumentation used in such cases be immediately destroyed after use; short of destruction, it is recommended that heat and chemical decontamination be used in combination to process instruments that come in contact with high-infectivity tissues. Thermal depolymerization also destroys prions in infected organic and inorganic matter, since the process chemically attacks protein at the molecular level, although more effective and practical methods involve destruction by combinations of detergents and enzymes similar to biological washing powders.
=== Genetics ===
People can also develop CJD because they carry a mutation of the gene that codes for the prion protein (PRNP), located on chromosome 202p12-pter. This occurs in only 10–15% of all CJD cases. In sporadic cases, the misfolding of the prion protein is a process that is hypothesized to occur as a result of the effects of aging on cellular machinery, explaining why the disease often appears later in life. An EU study determined that "87% of cases were sporadic, 8% genetic, 5% iatrogenic and less than 1% variant."
== Diagnosis ==
Testing for CJD has historically been problematic, due to nonspecific nature of early symptoms and difficulty in safely obtaining brain tissue for confirmation. The diagnosis may initially be suspected in a person with rapidly progressing dementia, particularly when it is also found with the characteristic medical signs and symptoms such as involuntary muscle jerking, difficulty with coordination/balance and walking, and visual disturbances. Further testing can support the diagnosis and may include:
Electroencephalography – may have characteristic generalized periodic sharp wave pattern. Periodic sharp wave complexes develop in half of the people with sporadic CJD, particularly in the later stages.
Cerebrospinal fluid (CSF) analysis for elevated levels of 14-3-3 protein and tau protein could be supportive in the diagnosis of sCJD. The two proteins are released into the CSF by damaged nerve cells. Increased levels of tau or 14-3-3 proteins are seen in 90% of prion diseases. The markers have a specificity of 95% in clinical symptoms suggestive of CJD, but specificity is 70% in other less characteristic cases. 14-3-3 and tau proteins may also be elevated in the CSF after ischemic strokes, inflammatory brain diseases, or seizures. The protein markers are also less specific in early CJD, genetic CJD or the bovine variant. However, a positive result should not be regarded as sufficient for the diagnosis. The real-time quaking-induced conversion (RT-QuIC) assay, which amplifies misfolded PrP^Sc, now plays a central role in CJD diagnosis. Second-generation RT-QuIC on cerebrospinal fluid has sensitivity in the 90–97% range and ~100% specificity in sporadic CJD, far superior to earlier CSF tests. A positive RT-QuIC (on CSF or other tissues) is now included as a criterion for probable CJD in many national surveillance center. Studies have shown RT-QuIC can also be done on olfactory mucosa swabs obtained via nasal brushing and on skin biopsies, with high diagnostic accuracy (reported sensitivities ~90–100%)
MRI with diffusion weighted inversion (DWI) and fluid-attenuated inversion recovery (FLAIR) shows a high signal intensity in certain parts of the cortex (a cortical ribboning appearance), the basal ganglia, and the thalami. The most common presenting patterns are simultaneous involvement of the cortex and striatum (60% of cases), cortical involvement without the striatum (30%), thalamus (21%), cerebellum (8%) and striatum without cortical involvement (7%). In populations with a rapidly progressive dementia (early in the disease process), MRI has a sensitivity of 91% and specificity of 97% for diagnosing CJD. The MRI changes characteristic of CJD may also be seen in the immediate aftermath (hours after the event) of autoimmune encephalitis or focal seizures.
In recent years, studies have shown that the tumour marker neuron-specific enolase (NSE) is often elevated in CJD cases; however, its diagnostic utility is seen primarily when combined with a test for the 14-3-3 protein. As of 2010, screening tests to identify infected asymptomatic individuals, such as blood donors, are not yet available, though methods have been proposed and evaluated.
=== Imaging ===
Imaging of the brain may be performed during medical evaluation, both to rule out other causes and to obtain supportive evidence for diagnosis. Imaging findings are variable in their appearance, and also variable in sensitivity and specificity. While imaging plays a lesser role in diagnosis of CJD, characteristic findings on brain MRI in some cases may precede onset of clinical manifestations.
Brain MRI is the most useful imaging modality for changes related to CJD. Of the MRI sequences, diffuse-weighted imaging sequences are most sensitive. Characteristic findings are as follows:
Focal or diffuse diffusion-restriction involving the cerebral cortex or basal ganglia. The most characteristic and striking cortical abnormality has been called "cortical ribboning" or "cortical ribbon sign" due to hyperintensities resembling ribbons appearing in the cortex on MRI. The involvement of the thalamus can be found in sCJD, is even stronger and constant in vCJD.
Varying degree of symmetric T2 hyperintense signal changes in the basal ganglia (i.e., caudate and putamen), and to a lesser extent globus pallidus and occipital cortex.
Brain FDG PET-CT tends to be markedly abnormal, and is increasingly used in the investigation of dementias.
Patients with CJD will normally have hypometabolism on FDG PET.
=== Histopathology ===
Testing of tissue remains the most definitive way of confirming the diagnosis of CJD, although even biopsy is not always conclusive.
In one-third of people with sporadic CJD, deposits of "prion protein (scrapie)", PrPSc, can be found in the skeletal muscle or the spleen. Diagnosis of vCJD can be supported by biopsy of the tonsils, which harbor significant amounts of PrPSc; however, biopsy of brain tissue is the definitive diagnostic test for all other forms of prion disease. Due to its invasiveness, biopsy will not be done if clinical suspicion is sufficiently high or low. A negative biopsy does not rule out CJD, since it may predominate in a specific part of the brain.
The classic histologic appearance is spongiform change in the gray matter: the presence of many round vacuoles from one to 50 micrometers in the neuropil, in all six cortical layers in the cerebral cortex or with diffuse involvement of the cerebellar molecular layer. These vacuoles appear glassy or eosinophilic and may coalesce. Neuronal loss and gliosis are also seen. Plaques of amyloid-like material can be seen in the neocortex in some cases of CJD.
However, extra-neuronal vacuolization can also be seen in other disease states. Diffuse cortical vacuolization occurs in Alzheimer's disease, and superficial cortical vacuolization occurs in ischemia and frontotemporal dementia. These vacuoles appear clear and punched-out. Larger vacuoles encircling neurons, vessels, and glia are a possible processing artifact.
=== Classification ===
Types of CJD include:
Sporadic (sCJD), caused by the spontaneous misfolding of prion-protein in an individual. This accounts for 85% of cases of CJD. Sporadic CJD is can be further sub-classified by molecular profile into subtypes (MM1, MV2, etc.), which correlate with certain clinical-pathologic features.
MM1 / MV1 Subtype:
Clinical Features: Accounts for approximately 75% of sCJD cases. Characterized by rapidly progressive dementia, myoclonus, and typical EEG findings.
Neuropathology: Synaptic-type PrP^Sc deposition predominantly in the cerebral cortex. Spongiform changes are widespread, with significant neuronal loss and gliosis.
MM2 Subtype:
MM2C (Cortical): Presents with a more prolonged disease course and prominent cortical involvement. Neuropathology reveals PrP^Sc deposits in the cortex with less spongiform change compared to MM1.
MM2T (Thalamic): Rare; characterized by predominant thalamic involvement, leading to sleep disturbances and autonomic dysfunction. Neuropathology shows significant PrP^Sc deposition and neuronal loss in the thalamus.
VV1 Subtype:
Clinical Features: Rare; presents at a younger age with a slower disease progression.
Neuropathology: Predominant cortical involvement with synaptic-type PrP^Sc deposition.
VV2 Subtype:
Clinical Features: Second most common subtype. Patients often present with ataxia and other cerebellar signs.
Neuropathology: Significant PrP^Sc deposition in the cerebellum and basal ganglia, with prominent spongiform changes and neuronal loss.
Familial (fCJD), caused by an inherited mutation in the prion-protein gene. This accounts for the majority of the other 15% of cases of CJD.
Acquired CJD, caused by contamination with tissue from an infected person, usually as the result of a medical procedure (iatrogenic CJD). Medical procedures that are associated with the spread of this form of CJD include blood transfusion from the infected person, use of human-derived pituitary growth hormones, gonadotropin hormone therapy, and corneal and meningeal transplants. Variant Creutzfeldt–Jakob disease (vCJD) is a type of acquired CJD potentially acquired from bovine spongiform encephalopathy or caused by consuming food contaminated with prions. Sporadic CJD, while transmissible through tissue transplants, may not be transmitted through blood transfusion.
== Treatment ==
As of 2025, there is no cure or effective treatment for CJD. Some of the symptoms like twitching can be managed, but otherwise treatment is palliative care. Psychiatric symptoms like anxiety and depression can be treated with sedatives and antidepressants. Myoclonic jerks can be handled with clonazepam or sodium valproate. Opiates can help in pain. Seizures are very uncommon but can nevertheless be treated with antiepileptic drugs.
In 2022, results of an early-stage trial of PRN100, a monoclonal antibody against PrP, were reported: the drug appeared safe and reached the brain, but treated patients did not show clearly improved survival compared to historical controls. While not curative, this trial demonstrated the feasibility of immunotherapy for prion disease.
== Prognosis ==
Life expectancy is greatly reduced for people with Creutzfeldt–Jakob disease and the average is less than 6 months. As of 1981, no one was known to have lived longer than 2.5 years after the onset of CJD symptoms. One of the world's longest survivors of vCJD was Jonathan Simms, a Northern Irish man who lived for 10 years after his diagnosis and received experimental treatment with pentosan polysulphate. Simms died in 2011.
== Epidemiology ==
The CDC monitors the occurrence of CJD in the United States through periodic reviews of national mortality data. According to the CDC:
CJD occurs worldwide at roughly 1–1.5 cases per million people per year. Recent surveillance reports indicate a slight increase in recorded incidence in many countries over time. For example, a study made in 2020 noted that sporadic CJD incidence in the U.K. rose from 1990 to 2018, and several other countries also reported increases in CJD cases in the 2000s.
On the basis of mortality surveillance from 1979 to 1994, the annual incidence of CJD remained stable at approximately 1 case per million people in the United States.
In the United States, CJD deaths among people younger than 30 years of age are extremely rare (fewer than five deaths per billion per year).
The disease is found most frequently in people 55–65 years of age, but cases can occur in people older than 90 years and younger than 55 years of age.
In more than 85% of cases, the duration of CJD is less than one year (median: four months) after the onset of symptoms.
Further information from the CDC:
Risk of developing CJD increases with age.
CJD incidence was 3.5 cases per million among those over 50 years of age between 1979 and 2017.
Approximately 85% of CJD cases are sporadic and 10–15% of CJD cases are due to inherited mutations of the prion protein gene.
CJD deaths and age-adjusted death rate in the United States indicate an increasing trend in the number of deaths between 1979 and 2017.
Although not fully understood, additional information suggests that CJD rates in nonwhite groups are lower than in whites. While the mean onset is approximately 67 years of age, cases of sCJD have been reported as young as 17 years and over 80 years of age. Mental capabilities rapidly deteriorate and the average amount of time from onset of symptoms to death is 7 to 9 months.
According to a 2020 systematic review on the international epidemiology of CJD:
Surveillance studies from 2005 and later show the estimated global incidence is 1–2 cases per million population per year.
Sporadic CJD (sCJD) incidence increased from the years 1990–2018 in the UK.
Probable or definite sCJD deaths also increased from the years 1996–2018 in twelve additional countries.
CJD incidence is greatest in those over the age of 55 years old, with an average age of 67 years old.
The intensity of CJD surveillance increases the number of reported cases, often in countries where CJD epidemics have occurred in the past and where surveillance resources are greatest. An increase in surveillance and reporting of CJD is most likely in response to BSE and vCJD. Possible factors contributing to an increase of CJD incidence are an aging population, population increase, clinician awareness, and more accurate diagnostic methods. Since CJD symptoms are similar to other neurological conditions, it is also possible that CJD is mistaken for stroke, acute nephropathy, general dementia, and hyperparathyroidism.
== History ==
The disease was first described by German neurologist Hans Gerhard Creutzfeldt in 1920 and shortly afterward by Alfons Maria Jakob, giving it the name Creutzfeldt–Jakob disease. Some of the clinical findings described in their first papers do not match current criteria for Creutzfeldt–Jakob disease, and it has been speculated that at least two of the people in initial studies had a different ailment. An early description of familial CJD stems from the German psychiatrist and neurologist Friedrich Meggendorfer (1880–1953). A study published in 1997 counted more than 100 cases worldwide of transmissible CJD and new cases continued to appear at the time.
The first report of suspected iatrogenic CJD was published in 1974. Animal experiments showed that corneas of infected animals could transmit CJD, and the causative agent spreads along visual pathways. A second case of CJD associated with a corneal transplant was reported without details. In 1977, CJD transmission caused by silver electrodes previously used in the brain of a person with CJD was first reported. Transmission occurred despite the decontamination of the electrodes with ethanol and formaldehyde. Retrospective studies identified four other cases likely of similar cause. The rate of transmission from a single contaminated instrument is unknown, although it is not 100%. In some cases, the exposure occurred weeks after the instruments were used on a person with CJD. In the 1980s it was discovered that Lyodura, a dura mater transplant product, was shown to transmit CJD from the donor to the recipient. This led to the product being banned in Canada but it was used in other countries such as Japan until 1993. A review article published in 1979 indicated that 25 dura mater cases had occurred by that date in Australia, Canada, Germany, Italy, Japan, New Zealand, Spain, the United Kingdom, and the United States.
By 1985, a series of case reports in the United States showed that when injected, cadaver-extracted pituitary human growth hormone could transmit CJD to humans.
In 1992, it was recognized that human gonadotropin administered by injection could also transmit CJD from person to person.
Stanley B. Prusiner of the University of California, San Francisco (UCSF) was awarded the Nobel Prize in Physiology or Medicine in 1997 "for his discovery of Prions—a new biological principle of infection".
Yale University neuropathologist Laura Manuelidis has challenged the prion protein (PrP) explanation for the disease. In January 2007, she and her colleagues reported that they had found a virus-like particle in naturally and experimentally infected animals. "The high infectivity of comparable, isolated virus-like particles that show no intrinsic PrP by antibody labeling, combined with their loss of infectivity when nucleic acid–protein complexes are disrupted, make it likely that these 25-nm particles are the causal TSE virions".
=== Australia ===
Australia has documented 10 cases of healthcare-acquired CJD (iatrogenic or ICJD). Five of the deaths resulted after the patients, who were in treatment either for infertility or short stature, were treated using contaminated pituitary extract hormone but no new cases have been noted since 1991. The other five deaths occurred due to dura grafting procedures that were performed during brain surgery, in which the covering of the brain is repaired. There have been no other ICJD deaths documented in Australia due to transmission during healthcare procedures.
=== New Zealand ===
A case was reported in 1989 in a 25-year-old man from New Zealand, who also received dura mater transplant. Five New Zealanders have been confirmed to have died of the sporadic form of Creutzfeldt–Jakob disease (CJD) in 2012.
=== United States ===
In 1988 there was a confirmed death from CJD of a person from Manchester, New Hampshire. Massachusetts General Hospital believed the person acquired the disease from a surgical instrument at a podiatrist's office. In 2007 Michael Homer, former Vice President of Netscape, had been experiencing consistent memory problems which led to his diagnosis. In August 2013 the British journalist Graham Usher died in New York of CJD.
In September 2013, another person in Manchester was posthumously determined to have died of the disease. The person had undergone brain surgery at Catholic Medical Center three months before his death, and a surgical probe used in the procedure was subsequently reused in other operations. Public health officials identified thirteen people at three hospitals who may have been exposed to the disease through the contaminated probe but said the risk of anyone contracting CJD is "extremely low".
In January 2015, former speaker of the Utah House of Representatives Rebecca D. Lockhart died of the disease within a few weeks of diagnosis. John Carroll, former editor of The Baltimore Sun and Los Angeles Times, died of CJD in Kentucky in June 2015, after having been diagnosed in January. American actress Barbara Tarbuck (General Hospital, American Horror Story) died of the disease on December 26, 2016. José Baselga, clinical oncologist having headed the AstraZeneca oncology division, died in Cerdanya, March 21, 2021, from CJD. In April 2024, a report was published regarding two hunters from the same lodge who, in 2022, were found to be afflicted with sporadic CJD after eating deer meat infected with chronic wasting disease (CWD), suggesting a potential link between CWD and CJD.
== Research ==
=== Diagnosis ===
In 2010, a team from New York described detection of PrPSc in sheep's blood, even when initially present at only one part in one hundred billion (10−11) in sheep's brain tissue. The method combines amplification with a novel technology called surround optical fiber immunoassay (SOFIA) and some specific antibodies against PrPSc. The technique allowed improved detection and testing time for PrPSc.
In 2014, a human study showed a nasal brushing method that can accurately detect PrP in the olfactory epithelial cells of people with CJD.
=== Treatment ===
Pentosan polysulfate (PPS) may slow the progression of the disease, and may have contributed to the longer than expected survival of the seven people studied. The CJD Therapy Advisory Group to the UK Health Departments advises that data are not sufficient to support claims that pentosan polysulfate is an effective treatment and suggests that further research in animal models is appropriate. A 2007 review of the treatment of 26 people with PPS finds no proof of efficacy because of the lack of accepted objective criteria, but it was unclear to the authors whether that was caused by PPS itself. In 2012 it was claimed that the lack of significant benefits has likely been caused because of the drug being administered very late in the disease in many patients.
Use of RNA interference to slow the progression of scrapie has been studied in mice. The RNA blocks production of the protein that the CJD process transforms into prions.
Both amphotericin B and doxorubicin have been investigated as treatments for CJD, but as yet there is no strong evidence that either drug is effective in stopping the disease. Further study has been taken with other medical drugs, but none are effective. However, anticonvulsants and anxiolytic agents, such as valproate or a benzodiazepine, may be administered to relieve associated symptoms.
Quinacrine, a medicine originally created for malaria, has been evaluated as a treatment for CJD. The efficacy of quinacrine was assessed in a rigorous clinical trial in the UK and the results were published in Lancet Neurology, and concluded that quinacrine had no measurable effect on the clinical course of CJD.
Astemizole, a medication approved for human use, has been found to have anti-prion activity and may lead to a treatment for Creutzfeldt–Jakob disease.
A monoclonal antibody (code name PRN100) targeting the prion protein (PrP) was given to six people with Creutzfeldt–Jakob disease in an early-stage clinical trial conducted from 2018 to 2022. The treatment appeared to be well-tolerated and was able to access the brain, where it might have helped to clear PrPC. While the treated patients still showed progressive neurological decline, and while none of them survived longer than expected from the normal course of the disease, the scientists at University College London who conducted the study see these early-stage results as encouraging and suggest to conduct a larger study, ideally at the earliest possible intervention.
== See also ==
Transmissible spongiform encephalopathy
Chronic wasting disease
Kuru
== References ==
== External links == | Wikipedia/Creutzfeldt–Jakob_disease |
Lattice proteins are highly simplified models of protein-like heteropolymer chains on lattice conformational space which are used to investigate protein folding. Simplification in lattice proteins is twofold: each whole residue (amino acid) is modeled as a single "bead" or "point" of a finite set of types (usually only two), and each residue is restricted to be placed on vertices of a (usually cubic) lattice. To guarantee the connectivity of the protein chain, adjacent residues on the backbone must be placed on adjacent vertices of the lattice. Steric constraints are expressed by imposing that no more than one residue can be placed on the same lattice vertex.
Because proteins are such large molecules, there are severe computational limits on the simulated timescales of their behaviour when modeled in all-atom detail. The millisecond regime for all-atom simulations was not reached until 2010, and it is still not possible to fold all real proteins on a computer. Simplification significantly reduces the computational effort in handling the model, although even in this simplified scenario the protein folding problem is NP-complete.
== Overview ==
Different versions of lattice proteins may adopt different types of lattice (typically square and triangular ones), in two or three dimensions, but it has been shown that generic lattices can be used and handled via a uniform approach.
Lattice proteins are made to resemble real proteins by introducing an energy function, a set of conditions which specify the interaction energy between beads occupying adjacent lattice sites. The energy function mimics the interactions between amino acids in real proteins, which include steric, hydrophobic and hydrogen bonding effects. The beads are divided into types, and the energy function specifies the interactions depending on the bead type, just as different types of amino acids interact differently. One of the most popular lattice models, the hydrophobic-polar model (HP model), features just two bead types—hydrophobic (H) and polar (P)—and mimics the hydrophobic effect by specifying a favorable interaction between H beads.
For any sequence in any particular structure, an energy can be rapidly calculated from the energy function. For the simple HP model, this is an enumeration of all the contacts between H residues that are adjacent in the structure but not in the chain. Most researchers consider a lattice protein sequence protein-like only if it possesses a single structure with an energetic state lower than in any other structure, although there are exceptions that consider ensembles of possible folded states. This is the energetic ground state, or native state. The relative positions of the beads in the native state constitute the lattice protein's tertiary structure. Lattice proteins do not have genuine secondary structure; however, some researchers have claimed that they can be extrapolated onto real protein structures which do include secondary structure, by appealing to the same law by which the phase diagrams of different substances can be scaled onto one another (the theorem of corresponding states).
By varying the energy function and the bead sequence of the chain (the primary structure), effects on the native state structure and the kinetics of folding can be explored, and this may provide insights into the folding of real proteins. Some of the examples include study of folding processes in lattice proteins that have been discussed to resemble the two-phase folding kinetics in proteins. Lattice protein was shown to have quickly collapsed into compact state and followed by slow subsequent structure rearrangement into native state. Attempts to resolve Levinthal paradox in protein folding are another efforts made in the field. As an example, study conducted by Fiebig and Dill examined searching method involving constraints in forming residue contacts in lattice protein to provide insights to the question of how a protein finds its native structure without global exhaustive searching. Lattice protein models have also been used to investigate the energy landscapes of proteins, i.e. the variation of their internal free energy as a function of conformation.
== Lattices ==
A lattice is a set of orderly points that are connected by "edges". These points are called vertices and are connected to a certain number other vertices in the lattice by edges. The number of vertices each individual vertex is connected to is called the coordination number of the lattice, and it can be scaled up or down by changing the shape or dimension (2-dimensional to 3-dimensional, for example) of the lattice. This number is important in shaping the characteristics of the lattice protein because it controls the number of other residues allowed to be adjacent to a given residue. It has been shown that for most proteins the coordination number of the lattice used should fall between 3 and 20, although most commonly used lattices have coordination numbers at the lower end of this range.
Lattice shape is an important factor in the accuracy of lattice protein models. Changing lattice shape can dramatically alter the shape of the energetically favorable conformations. It can also add unrealistic constraints to the protein structure such as in the case of the parity problem where in square and cubic lattices residues of the same parity (odd or even numbered) cannot make hydrophobic contact. It has also been reported that triangular lattices yield more accurate structures than other lattice shapes when compared to crystallographic data. To combat the parity problem, several researchers have suggested using triangular lattices when possible, as well as a square matrix with diagonals for theoretical applications where the square matrix may be more appropriate. Hexagonal lattices were introduced to alleviate sharp turns of adjacent residues in triangular lattices. Hexagonal lattices with diagonals have also been suggested as a way to combat the parity problem.
== Hydrophobic-polar model ==
The hydrophobic-polar protein model is the original lattice protein model. It was first proposed by Dill et al. in 1985 as a way to overcome the significant cost and difficulty of predicting protein structure, using only the hydrophobicity of the amino acids in the protein to predict the protein structure. It is considered to be the paradigmatic lattice protein model. The method was able to quickly give an estimate of protein structure by representing proteins as "short chains on a 2D square lattice" and has since become known as the hydrophobic-polar model. It breaks the protein folding problem into three separate problems: modeling the protein conformation, defining the energetic properties of the amino acids as they interact with one another to find said conformation, and developing an efficient algorithm for the prediction of these conformations. It is done by classifying amino acids in the protein as either hydrophobic or polar and assuming that the protein is being folded in an aqueous environment. The lattice statistical model seeks to recreate protein folding by minimizing the free energy of the contacts between hydrophobic amino acids. Hydrophobic amino acid residues are predicted to group around each other, while hydrophilic residues interact with the surrounding water.
Different lattice types and algorithms were used to study protein folding with HP model. Efforts were made to obtain higher approximation ratios using approximation algorithms in 2 dimensional and 3 dimensional, square and triangular lattices. Alternative to approximation algorithms, some genetic algorithms were also exploited with square, triangular, and face-centered-cubic lattices.
== Problems and alternative models ==
The simplicity of the hydrophobic-polar model has caused it to have several problems that people have attempted to correct with alternative lattice protein models. Chief among these problems is the issue of degeneracy, which is when there is more than one minimum energy conformation for the modeled protein, leading to uncertainty about which conformation is the native one. Attempts to address this include the HPNX model which classifies amino acids as hydrophobic (H), positive (P), negative (N), or neutral (X) according to the charge of the amino acid, adding additional parameters to reduce the number of low energy conformations and allowing for more realistic protein simulations. Another model is the Crippen model which uses protein characteristics taken from crystal structures to inform the choice of native conformation.
Another issue with lattice models is that they generally don't take into account the space taken up by amino acid side chains, instead considering only the α-carbon. The side chain model addresses this by adding a side chain to the vertex adjacent to the α-carbon.
== References == | Wikipedia/Lattice_protein |
Putative tyrosine-protein phosphatase auxilin is an enzyme that in humans is encoded by the DNAJC6 gene.
== Function ==
DNAJC6 belongs to the evolutionarily conserved DNAJ/HSP40 family of proteins, which regulate molecular chaperone activity by stimulating ATPase activity. DNAJ proteins may have up to 3 distinct domains: a conserved 70-amino acid J domain, usually at the N terminus, a glycine/phenylalanine (G/F)-rich region, and a cysteine-rich domain containing 4 motifs resembling a zinc-finger domain (Ohtsuka and Hata, 2000).
== Structure ==
The protein tyrosine phosphatase domain and C2 domain pair of auxilin, located near the N-terminus of the polypeptide, constitute a superdomain, a tandem arrangement of two or more nominally unrelated domains that form a single heritable unit. The phosphatase domain belongs to the auxilin subfamily of lipid phosphatases and is predicted to be catalytically inactive.
== References ==
== External links ==
Human DNAJC6 genome location and DNAJC6 gene details page in the UCSC Genome Browser.
== Further reading == | Wikipedia/DNAJC6 |
A potential energy surface (PES) or energy landscape describes the energy of a system, especially a collection of atoms, in terms of certain parameters, normally the positions of the atoms. The surface might define the energy as a function of one or more coordinates; if there is only one coordinate, the surface is called a potential energy curve or energy profile. An example is the Morse/Long-range potential.
It is helpful to use the analogy of a landscape: for a system with two degrees of freedom (e.g. two bond lengths), the value of the energy (analogy: the height of the land) is a function of two bond lengths (analogy: the coordinates of the position on the ground).
The PES concept finds application in fields such as physics, chemistry and biochemistry, especially in the theoretical sub-branches of these subjects. It can be used to theoretically explore properties of structures composed of atoms, for example, finding the minimum energy shape of a molecule or computing the rates of a chemical reaction. It can be used to describe all possible conformations of a molecular entity, or the spatial positions of interacting molecules in a system, or parameters and their corresponding energy levels, typically Gibbs free energy. Geometrically, the energy landscape is the graph of the energy function across the configuration space of the system. The term is also used more generally in geometric perspectives to mathematical optimization, when the domain of the loss function is the parameter space of some system.
== Mathematical definition and computation ==
The geometry of a set of atoms can be described by a vector, r, whose elements represent the atom positions. The vector r could be the set of the Cartesian coordinates of the atoms, or could also be a set of inter-atomic distances and angles.
Given r, the energy as a function of the positions, E(r), is the value of E(r) for all r of interest. Using the landscape analogy from the introduction, E gives the height on the "energy landscape" so that the concept of a potential energy surface arises.
To study a chemical reaction using the PES as a function of atomic positions, it is necessary to calculate the energy for every atomic arrangement of interest. Methods of calculating the energy of a particular atomic arrangement of atoms are well described in the computational chemistry article, and the emphasis here will be on finding approximations of E(r) to yield fine-grained energy-position information.
For very simple chemical systems or when simplifying approximations are made about inter-atomic interactions, it is sometimes possible to use an analytically derived expression for the energy as a function of the atomic positions. An example is the London-Eyring-Polanyi-Sato potential for the system H + H2 as a function of the three H-H distances.
For more complicated systems, calculation of the energy of a particular arrangement of atoms is often too computationally expensive for large scale representations of the surface to be feasible. For these systems a possible approach is to calculate only a reduced set of points on the PES and then use a computationally cheaper interpolation method, for example Shepard interpolation, to fill in the gaps.
== Application ==
A PES is a conceptual tool for aiding the analysis of molecular geometry and chemical reaction dynamics. Once the necessary points are evaluated on a PES, the points can be classified according to the first and second derivatives of the energy with respect to position, which respectively are the gradient and the curvature. Stationary points (or points with a zero gradient) have physical meaning: energy minima correspond to physically stable chemical species and saddle points correspond to transition states, the highest energy point on the reaction coordinate (which is the lowest energy pathway connecting a chemical reactant to a chemical product).
The term is useful when examining protein folding; while a protein can theoretically exist in a nearly infinite number of conformations along its energy landscape, in reality proteins fold (or "relax") into secondary and tertiary structures that possess the lowest possible free energy. The key concept in the energy landscape approach to protein folding is the folding funnel hypothesis.
In catalysis, when designing new catalysts or refining existing ones, energy landscapes are considered to avoid low-energy or high-energy intermediates that could halt the reaction or demand excessive energy to reach the final products.
In glassing models, the local minima of an energy landscape correspond to metastable low temperature states of a thermodynamic system.
In machine learning, artificial neural networks may be analyzed using analogous approaches. For example, a neural network may be able to perfectly fit the training set, corresponding to a global minimum of zero loss, but overfitting the model ("learning the noise" or "memorizing the training set"). Understanding when this happens can be studied using the geometry of the corresponding energy landscape.
== Attractive and repulsive surfaces ==
Potential energy surfaces for chemical reactions can be classified as attractive or repulsive by comparing the extensions of the bond lengths in the activated complex relative to those of the reactants and products. For a reaction of type A + B—C → A—B + C, the bond length extension for the newly formed A—B bond is defined as R*AB = RAB − R0AB, where RAB is the A—B bond length in the transition state and R0AB in the product molecule. Similarly for the bond which is broken in the reaction, R*BC = RBC − R0BC, where R0BC refers to the reactant molecule.
For exothermic reactions, a PES is classified as attractive (or early-downhill) if R*AB > R*BC, so that the transition state is reached while the reactants are approaching each other. After the transition state, the A—B bond length continues to decrease, so that much of the liberated reaction energy is converted into vibrational energy of the A—B bond. An example is the harpoon reaction K + Br2 → K—Br + Br, in which the initial long-range attraction of the reactants leads to an activated complex resembling K+•••Br−•••Br. The vibrationally excited populations of product molecules can be detected by infrared chemiluminescence.
In contrast the PES for the reaction H + Cl2 → HCl + Cl is repulsive (or late-downhill) because R*HCl < R*ClCl and the transition state is reached when the products are separating. For this reaction in which the atom A (here H) is lighter than B and C, the reaction energy is released primarily as translational kinetic energy of the products. For a reaction such as F + H2 → HF + H in which atom A is heavier than B and C, there is mixed energy release, both vibrational and translational, even though the PES is repulsive.
For endothermic reactions, the type of surface determines the type of energy which is most effective in bringing about reaction. Translational energy of the reactants is most effective at inducing reactions with an attractive surface, while vibrational excitation (to higher vibrational quantum number v) is more effective for reactions with a repulsive surface. As an example of the latter case, the reaction F + HCl(v=1) → Cl + HF is about five times faster than F + HCl(v=0) → Cl + HF for the same total energy of HCl.
== History ==
The concept of a potential energy surface for chemical reactions was first suggested by the French physicist René Marcelin in 1913. The first semi-empirical calculation of a potential energy surface was proposed for the H + H2 reaction by Henry Eyring and Michael Polanyi in 1931. Eyring used potential energy surfaces to calculate reaction rate constants in the transition state theory in 1935.
== H + H2 two-dimensional PES ==
Potential energy surfaces are commonly shown as three-dimensional graphs, but they can also be represented by two-dimensional graphs, in which the advancement of the reaction is plotted by the use of isoenergetic lines.
The collinear system H + H2 is a simple reaction that allows a two-dimension PES to be plotted in an easy and understandable way.
In this reaction, a hydrogen atom (H) reacts with a dihydrogen molecule (H2) by forming a new bond with one atom from the molecule, which in turn breaks the bond of the original molecule. This is symbolized as Ha + Hb–Hc → Ha–Hb + Hc. The progression of the reaction from reactants (H+H₂) to products (H-H-H), as well as the energy of the species that take part in the reaction, are well defined in the corresponding potential energy surface.
Energy profiles describe potential energy as a function of geometrical variables (PES in any dimension are independent of time and temperature).
We have different relevant elements in the 2-D PES:
The 2-D plot shows the minima points where we find reactants, the products and the saddle point or transition state.
The transition state is a maximum in the reaction coordinate and a minimum in the coordinate perpendicular to the reaction path.
The advance of time describes a trajectory in every reaction. Depending on the conditions of the reaction the process will show different ways to get to the product formation plotted between the 2 axes.
== See also ==
Computational chemistry
Energy minimization (or geometry optimization)
Energy profile (chemistry)
Potential well
Reaction coordinate
== References ==
== Bibliographie ==
Schön, J. C. (5 August 2024). "Energy landscapes—Past, present, and future: A perspective". Journal of Chemical Physics. 161 (5): 050901. Bibcode:2024JChPh.161e0901S. doi:10.1063/5.0212867. Retrieved 17 December 2024. | Wikipedia/Energy_landscape |
Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design.
Protein structure prediction is one of the most important goals pursued by computational biology and addresses Levinthal's paradox. Accurate structure prediction has important applications in medicine (for example, in drug design) and biotechnology (for example, in novel enzyme design).
Starting in 1994, the performance of current methods is assessed biannually in the Critical Assessment of Structure Prediction (CASP) experiment. A continuous evaluation of protein structure prediction web servers is performed by the community project Continuous Automated Model EvaluatiOn (CAMEO3D).
== Protein structure and terminology ==
Proteins are chains of amino acids joined together by peptide bonds. Many conformations of this chain are possible due to the rotation of the main chain about the two torsion angles φ and ψ at the Cα atom (see figure). This conformational flexibility is responsible for differences in the three-dimensional structure of proteins. The peptide bonds in the chain are polar, i.e. they have separated positive and negative charges (partial charges) in the carbonyl group, which can act as hydrogen bond acceptor and in the NH group, which can act as hydrogen bond donor. These groups can therefore interact in the protein structure. Proteins consist mostly of 20 different types of L-α-amino acids (the proteinogenic amino acids). These can be classified according to the chemistry of the side chain, which also plays an important structural role. Glycine takes on a special position, as it has the smallest side chain, only one hydrogen atom, and therefore can increase the local flexibility in the protein structure. Cysteine in contrast can react with another cysteine residue to form one cystine and thereby form a cross link stabilizing the whole structure.
The protein structure can be considered as a sequence of secondary structure elements, such as α helices and β sheets. In these secondary structures, regular patterns of H-bonds are formed between the main chain NH and CO groups of spatially neighboring amino acids, and the amino acids have similar Φ and ψ
angles.
The formation of these secondary structures efficiently satisfies the hydrogen bonding capacities of the peptide bonds. The secondary structures can be tightly packed in the protein core in a hydrophobic environment, but they can also present at the polar protein surface. Each amino acid side chain has a limited volume to occupy and a limited number of possible interactions with other nearby side chains, a situation that must be taken into account in molecular modeling and alignments.
=== α-helix ===
The α-helix is the most abundant type of secondary structure in proteins. The α-helix has 3.6 amino acids per turn with an H-bond formed between every fourth residue; the average length is 10 amino acids (3 turns) or 10 Å but varies from 5 to 40 (1.5 to 11 turns). The alignment of the H-bonds creates a dipole moment for the helix with a resulting partial positive charge at the amino end of the helix. Because this region has free NH2 groups, it will interact with negatively charged groups such as phosphates. The most common location of α-helices is at the surface of protein cores, where they provide an interface with the aqueous environment. The inner-facing side of the helix tends to have hydrophobic amino acids and the outer-facing side hydrophilic amino acids. Thus, every third of four amino acids along the chain will tend to be hydrophobic, a pattern that can be quite readily detected. In the leucine zipper motif, a repeating pattern of leucines on the facing sides of two adjacent helices is highly predictive of the motif. A helical-wheel plot can be used to show this repeated pattern. Other α-helices buried in the protein core or in cellular membranes have a higher and more regular distribution of hydrophobic amino acids, and are highly predictive of such structures. Helices exposed on the surface have a lower proportion of hydrophobic amino acids. Amino acid content can be predictive of an α-helical region. Regions richer in alanine (A), glutamic acid (E), leucine (L), and methionine (M) and poorer in proline (P), glycine (G), tyrosine (Y), and serine (S) tend to form an α-helix. Proline destabilizes or breaks an α-helix but can be present in longer helices, forming a bend.
=== β-sheet ===
β-sheets are formed by H-bonds between an average of 5–10 consecutive amino acids in one portion of the chain with another 5–10 farther down the chain. The interacting regions may be adjacent, with a short loop in between, or far apart, with other structures in between. Every chain may run in the same direction to form a parallel sheet, every other chain may run in the reverse chemical direction to form an anti parallel sheet, or the chains may be parallel and anti parallel to form a mixed sheet. The pattern of H bonding is different in the parallel and anti parallel configurations. Each amino acid in the interior strands of the sheet forms two H-bonds with neighboring amino acids, whereas each amino acid on the outside strands forms only one bond with an interior strand. Looking across the sheet at right angles to the strands, more distant strands are rotated slightly counterclockwise to form a left-handed twist. The Cα-atoms alternate above and below the sheet in a pleated structure, and the R side groups of the amino acids alternate above and below the pleats. The Φ and Ψ angles of the amino acids in sheets vary considerably in one region of the Ramachandran plot. It is more difficult to predict the location of β-sheets than of α-helices. The situation improves somewhat when the amino acid variation in multiple sequence alignments is taken into account.
=== Deltas ===
Some parts of the protein have fixed three-dimensional structure, but do not form any regular structures. They should not be confused with disordered or unfolded segments of proteins or random coil, an unfolded polypeptide chain lacking any fixed three-dimensional structure. These parts are frequently called "deltas" (Δ) because they connect β-sheets and α-helices. Deltas are usually located at protein surface, and therefore mutations of their residues are more easily tolerated. Having more substitutions, insertions, and deletions in a certain region of a sequence alignment maybe an indication of some delta. The positions of introns in genomic DNA may correlate with the locations of loops in the encoded protein . Deltas also tend to have charged and polar amino acids and are frequently a component of active sites.
== Protein classification ==
Proteins may be classified according to both structural and sequential similarity. For structural classification, the sizes and spatial arrangements of secondary structures described in the above paragraph are compared in known three-dimensional structures. Classification based on sequence similarity was historically the first to be used. Initially, similarity based on alignments of whole sequences was performed. Later, proteins were classified on the basis of the occurrence of conserved amino acid patterns. Databases that classify proteins by one or more of these schemes are available.
In considering protein classification schemes, it is important to keep several observations in mind. First, two entirely different protein sequences from different evolutionary origins may fold into a similar structure. Conversely, the sequence of an ancient gene for a given structure may have diverged considerably in different species while at the same time maintaining the same basic structural features. Recognizing any remaining sequence similarity in such cases may be a very difficult task. Second, two proteins that share a significant degree of sequence similarity either with each other or with a third sequence also share an evolutionary origin and should share some structural features also. However, gene duplication and genetic rearrangements during evolution may give rise to new gene copies, which can then evolve into proteins with new function and structure.
=== Terms used for classifying protein structures and sequences ===
The more commonly used terms for evolutionary and structural relationships among proteins are listed below. Many additional terms are used for various kinds of structural features found in proteins. Descriptions of such terms may be found at the CATH Web site, the Structural Classification of Proteins (SCOP) Web site, and a Glaxo Wellcome tutorial on the Swiss bioinformatics Expasy Web site.
Active site
a localized combination of amino acid side groups within the tertiary (three-dimensional) or quaternary (protein subunit) structure that can interact with a chemically specific substrate and that provides the protein with biological activity. Proteins of very different amino acid sequences may fold into a structure that produces the same active site.
Architecture
is the relative orientations of secondary structures in a three-dimensional structure without regard to whether or not they share a similar loop structure.
Fold (topology)
a type of architecture that also has a conserved loop structure.
Blocks
is a conserved amino acid sequence pattern in a family of proteins. The pattern includes a series of possible matches at each position in the represented sequences, but there are not any inserted or deleted positions in the pattern or in the sequences. By way of contrast, sequence profiles are a type of scoring matrix that represents a similar set of patterns that includes insertions and deletions.
Class
a term used to classify protein domains according to their secondary structural content and organization. Four classes were originally recognized by Levitt and Chothia (1976), and several others have been added in the SCOP database. Three classes are given in the CATH database: mainly-α, mainly-β, and α–β, with the α–β class including both alternating α/β and α+β structures.
Core
the portion of a folded protein molecule that comprises the hydrophobic interior of α-helices and β-sheets. The compact structure brings together side groups of amino acids into close enough proximity so that they can interact. When comparing protein structures, as in the SCOP database, core is the region common to most of the structures that share a common fold or that are in the same superfamily. In structure prediction, core is sometimes defined as the arrangement of secondary structures that is likely to be conserved during evolutionary change.
Domain (sequence context)
a segment of a polypeptide chain that can fold into a three-dimensional structure irrespective of the presence of other segments of the chain. The separate domains of a given protein may interact extensively or may be joined only by a length of polypeptide chain. A protein with several domains may use these domains for functional interactions with different molecules.
Family (sequence context)
a group of proteins of similar biochemical function that are more than 50% identical when aligned. This same cutoff is still used by the Protein Information Resource (PIR). A protein family comprises proteins with the same function in different organisms (orthologous sequences) but may also include proteins in the same organism (paralogous sequences) derived from gene duplication and rearrangements. If a multiple sequence alignment of a protein family reveals a common level of similarity throughout the lengths of the proteins, PIR refers to the family as a homeomorphic family. The aligned region is referred to as a homeomorphic domain, and this region may comprise several smaller homology domains that are shared with other families. Families may be further subdivided into subfamilies or grouped into superfamilies based on respective higher or lower levels of sequence similarity. The SCOP database reports 1296 families and the CATH database (version 1.7 beta), reports 1846 families.
When the sequences of proteins with the same function are examined in greater detail, some are found to share high sequence similarity. They are obviously members of the same family by the above criteria. However, others are found that have very little, or even insignificant, sequence similarity with other family members. In such cases, the family relationship between two distant family members A and C can often be demonstrated by finding an additional family member B that shares significant similarity with both A and C. Thus, B provides a connecting link between A and C. Another approach is to examine distant alignments for highly conserved matches.
At a level of identity of 50%, proteins are likely to have the same three-dimensional structure, and the identical atoms in the sequence alignment will also superimpose within approximately 1 Å in the structural model. Thus, if the structure of one member of a family is known, a reliable prediction may be made for a second member of the family, and the higher the identity level, the more reliable the prediction. Protein structural modeling can be performed by examining how well the amino acid substitutions fit into the core of the three-dimensional structure.
Family (structural context)
as used in the FSSP database (Families of structurally similar proteins) and the DALI/FSSP Web site, two structures that have a significant level of structural similarity but not necessarily significant sequence similarity.
Fold
similar to structural motif, includes a larger combination of secondary structural units in the same configuration. Thus, proteins sharing the same fold have the same combination of secondary structures that are connected by similar loops. An example is the Rossman fold comprising several alternating α helices and parallel β strands. In the SCOP, CATH, and FSSP databases, the known protein structures have been classified into hierarchical levels of structural complexity with the fold as a basic level of classification.
Homologous domain (sequence context)
an extended sequence pattern, generally found by sequence alignment methods, that indicates a common evolutionary origin among the aligned sequences. A homology domain is generally longer than motifs. The domain may include all of a given protein sequence or only a portion of the sequence. Some domains are complex and made up of several smaller homology domains that became joined to form a larger one during evolution. A domain that covers an entire sequence is called the homeomorphic domain by PIR (Protein Information Resource).
Module
a region of conserved amino acid patterns comprising one or more motifs and considered to be a fundamental unit of structure or function. The presence of a module has also been used to classify proteins into families.
Motif (sequence context)
a conserved pattern of amino acids that is found in two or more proteins. In the Prosite catalog, a motif is an amino acid pattern that is found in a group of proteins that have a similar biochemical activity, and that often is near the active site of the protein. Examples of sequence motif databases are the Prosite catalog and the Stanford Motifs Database.
Motif (structural context)
a combination of several secondary structural elements produced by the folding of adjacent sections of the polypeptide chain into a specific three-dimensional configuration. An example is the helix-loop-helix motif. Structural motifs are also referred to as supersecondary structures and folds.
Position-specific scoring matrix (sequence context, also known as weight or scoring matrix)
represents a conserved region in a multiple sequence alignment with no gaps. Each matrix column represents the variation found in one column of the multiple sequence alignment.
Position-specific scoring matrix—3D (structural context)
represents the amino acid variation found in an alignment of proteins that fall into the same structural class. Matrix columns represent the amino acid variation found at one amino acid position in the aligned structures.
Primary structure
the linear amino acid sequence of a protein, which chemically is a polypeptide chain composed of amino acids joined by peptide bonds.
Profile (sequence context)
a scoring matrix that represents a multiple sequence alignment of a protein family. The profile is usually obtained from a well-conserved region in a multiple sequence alignment. The profile is in the form of a matrix with each column representing a position in the alignment and each row one of the amino acids. Matrix values give the likelihood of each amino acid at the corresponding position in the alignment. The profile is moved along the target sequence to locate the best scoring regions by a dynamic programming algorithm. Gaps are allowed during matching and a gap penalty is included in this case as a negative score when no amino acid is matched. A sequence profile may also be represented by a hidden Markov model, referred to as a profile HMM.
Profile (structural context)
a scoring matrix that represents which amino acids should fit well and which should fit poorly at sequential positions in a known protein structure. Profile columns represent sequential positions in the structure, and profile rows represent the 20 amino acids. As with a sequence profile, the structural profile is moved along a target sequence to find the highest possible alignment score by a dynamic programming algorithm. Gaps may be included and receive a penalty. The resulting score provides an indication as to whether or not the target protein might adopt such a structure.
Quaternary structure
the three-dimensional configuration of a protein molecule comprising several independent polypeptide chains.
Secondary structure
the interactions that occur between the C, O, and NH groups on amino acids in a polypeptide chain to form α-helices, β-sheets, turns, loops, and other forms, and that facilitate the folding into a three-dimensional structure.
Superfamily
a group of protein families of the same or different lengths that are related by distant yet detectable sequence similarity. Members of a given superfamily thus have a common evolutionary origin. Originally, Dayhoff defined the cutoff for superfamily status as being the chance that the sequences are not related of 10 6, on the basis of an alignment score (Dayhoff et al. 1978). Proteins with few identities in an alignment of the sequences but with a convincingly common number of structural and functional features are placed in the same superfamily. At the level of three-dimensional structure, superfamily proteins will share common structural features such as a common fold, but there may also be differences in the number and arrangement of secondary structures. The PIR resource uses the term homeomorphic superfamilies to refer to superfamilies that are composed of sequences that can be aligned from end to end, representing a sharing of single sequence homology domain, a region of similarity that extends throughout the alignment. This domain may also comprise smaller homology domains that are shared with other protein families and superfamilies. Although a given protein sequence may contain domains found in several superfamilies, thus indicating a complex evolutionary history, sequences will be assigned to only one homeomorphic superfamily based on the presence of similarity throughout a multiple sequence alignment. The superfamily alignment may also include regions that do not align either within or at the ends of the alignment. In contrast, sequences in the same family align well throughout the alignment.
Supersecondary structure
a term with similar meaning to a structural motif. Tertiary structure is the three-dimensional or globular structure formed by the packing together or folding of secondary structures of a polypeptide chain.
== Secondary structure ==
Secondary structure prediction is a set of techniques in bioinformatics that aim to predict the local secondary structures of proteins based only on knowledge of their amino acid sequence. For proteins, a prediction consists of assigning regions of the amino acid sequence as likely alpha helices, beta strands (often termed extended conformations), or turns. The success of a prediction is determined by comparing it to the results of the DSSP algorithm (or similar e.g. STRIDE) applied to the crystal structure of the protein. Specialized algorithms have been developed for the detection of specific well-defined patterns such as transmembrane helices and coiled coils in proteins.
The best modern methods of secondary structure prediction in proteins were claimed to reach 80% accuracy after using machine learning and sequence alignments; this high accuracy allows the use of the predictions as feature improving fold recognition and ab initio protein structure prediction, classification of structural motifs, and refinement of sequence alignments. The accuracy of current protein secondary structure prediction methods is assessed in weekly benchmarks such as LiveBench and EVA.
=== Background ===
Early methods of secondary structure prediction, introduced in the 1960s and early 1970s, focused on identifying likely alpha helices and were based mainly on helix-coil transition models. Significantly more accurate predictions that included beta sheets were introduced in the 1970s and relied on statistical assessments based on probability parameters derived from known solved structures. These methods, applied to a single sequence, are typically at most about 60–65% accurate, and often underpredict beta sheets. Since the 1980s, artificial neural networks have been applied to the prediction of protein structures.
The evolutionary conservation of secondary structures can be exploited by simultaneously assessing many homologous sequences in a multiple sequence alignment, by calculating the net secondary structure propensity of an aligned column of amino acids. In concert with larger databases of known protein structures and modern machine learning methods such as neural nets and support vector machines, these methods can achieve up to 80% overall accuracy in globular proteins. The theoretical upper limit of accuracy is around 90%, partly due to idiosyncrasies in DSSP assignment near the ends of secondary structures, where local conformations vary under native conditions but may be forced to assume a single conformation in crystals due to packing constraints. Moreover, the typical secondary structure prediction methods do not account for the influence of tertiary structure on formation of secondary structure; for example, a sequence predicted as a likely helix may still be able to adopt a beta-strand conformation if it is located within a beta-sheet region of the protein and its side chains pack well with their neighbors. Dramatic conformational changes related to the protein's function or environment can also alter local secondary structure.
=== Historical perspective ===
To date, over 20 different secondary structure prediction methods have been developed. One of the first algorithms was Chou–Fasman method, which relies predominantly on probability parameters determined from relative frequencies of each amino acid's appearance in each type of secondary structure. The original Chou-Fasman parameters, determined from the small sample of structures solved in the mid-1970s, produce poor results compared to modern methods, though the parameterization has been updated since it was first published. The Chou-Fasman method is roughly 50–60% accurate in predicting secondary structures.
The next notable program was the GOR method is an information theory-based method. It uses the more powerful probabilistic technique of Bayesian inference. The GOR method takes into account not only the probability of each amino acid having a particular secondary structure, but also the conditional probability of the amino acid assuming each structure given the contributions of its neighbors (it does not assume that the neighbors have that same structure). The approach is both more sensitive and more accurate than that of Chou and Fasman because amino acid structural propensities are only strong for a small number of amino acids such as proline and glycine. Weak contributions from each of many neighbors can add up to strong effects overall. The original GOR method was roughly 65% accurate and is dramatically more successful in predicting alpha helices than beta sheets, which it frequently mispredicted as loops or disorganized regions.
Another big step forward, was using machine learning methods. First artificial neural networks methods were used. As a training sets they use solved structures to identify common sequence motifs associated with particular arrangements of secondary structures. These methods are over 70% accurate in their predictions, although beta strands are still often underpredicted due to the lack of three-dimensional structural information that would allow assessment of hydrogen bonding patterns that can promote formation of the extended conformation required for the presence of a complete beta sheet. PSIPRED and JPRED are some of the most known programs based on neural networks for protein secondary structure prediction. Next, support vector machines have proven particularly useful for predicting the locations of turns, which are difficult to identify with statistical methods.
Extensions of machine learning techniques attempt to predict more fine-grained local properties of proteins, such as backbone dihedral angles in unassigned regions. Both SVMs and neural networks have been applied to this problem. More recently, real-value torsion angles can be accurately predicted by SPINE-X and successfully employed for ab initio structure prediction.
=== Other improvements ===
It is reported that in addition to the protein sequence, secondary structure formation depends on other factors. For example, it is reported that secondary structure tendencies depend also on local environment, solvent accessibility of residues, protein structural class, and even the organism from which the proteins are obtained. Based on such observations, some studies have shown that secondary structure prediction can be improved by addition of information about protein structural class, residue accessible surface area and also contact number information.
== Tertiary structure ==
The practical role of protein structure prediction is now more important than ever. Massive amounts of protein sequence data are produced by modern large-scale DNA sequencing efforts such as the Human Genome Project. Despite community-wide efforts in structural genomics, the output of experimentally determined protein structures—typically by time-consuming and relatively expensive X-ray crystallography or NMR spectroscopy—is lagging far behind the output of protein sequences.
The protein structure prediction remains an extremely difficult and unresolved undertaking. The two main problems are the calculation of protein free energy and finding the global minimum of this energy. A protein structure prediction method must explore the space of possible protein structures which is astronomically large. These problems can be partially bypassed in "comparative" or homology modeling and fold recognition methods, in which the search space is pruned by the assumption that the protein in question adopts a structure that is close to the experimentally determined structure of another homologous protein. In contrast, the de novo protein structure prediction methods must explicitly resolve these problems. The progress and challenges in protein structure prediction have been reviewed by Zhang.
=== Before modelling ===
Most tertiary structure modelling methods, such as Rosetta, are optimized for modelling the tertiary structure of single protein domains. A step called domain parsing, or domain boundary prediction, is usually done first to split a protein into potential structural domains. As with the rest of tertiary structure prediction, this can be done comparatively from known structures or ab initio with the sequence only (usually by machine learning, assisted by covariation). The structures for individual domains are docked together in a process called domain assembly to form the final tertiary structure.
=== Ab initio protein modelling ===
==== Energy- and fragment-based methods ====
Ab initio- or de novo- protein modelling methods seek to build three-dimensional protein models "from scratch", i.e., based on physical principles rather than (directly) on previously solved structures. There are many possible procedures that either attempt to mimic protein folding or apply some stochastic method to search possible solutions (i.e., global optimization of a suitable energy function). These procedures tend to require vast computational resources, and have thus only been carried out for tiny proteins. To predict protein structure de novo for larger proteins will require better algorithms and larger computational resources like those afforded by either powerful supercomputers (such as Blue Gene or MDGRAPE-3) or distributed computing (such as Folding@home, the Human Proteome Folding Project and Rosetta@Home). Although these computational barriers are vast, the potential benefits of structural genomics (by predicted or experimental methods) make ab initio structure prediction an active research field.
As of 2009, a 50-residue protein could be simulated atom-by-atom on a supercomputer for 1 millisecond. As of 2012, comparable stable-state sampling could be done on a standard desktop with a new graphics card and more sophisticated algorithms. A much larger simulation timescales can be achieved using coarse-grained modeling.
==== Evolutionary covariation to predict 3D contacts ====
As sequencing became more commonplace in the 1990s several groups used protein sequence alignments to predict correlated mutations and it was hoped that these coevolved residues could be used to predict tertiary structure (using the analogy to distance constraints from experimental procedures such as NMR). The assumption is when single residue mutations are slightly deleterious, compensatory mutations may occur to restabilize residue-residue interactions.
This early work used what are known as local methods to calculate correlated mutations from protein sequences, but suffered from indirect false correlations which result from treating each pair of residues as independent of all other pairs.
In 2011, a different, and this time global statistical approach, demonstrated that predicted coevolved residues were sufficient to predict the 3D fold of a protein, providing there are enough sequences available (>1,000 homologous sequences are needed). The method, EVfold, uses no homology modeling, threading or 3D structure fragments and can be run on a standard personal computer even for proteins with hundreds of residues. The accuracy of the contacts predicted using this and related approaches has now been demonstrated on many known structures and contact maps, including the prediction of experimentally unsolved transmembrane proteins.
=== Comparative protein modeling ===
Comparative protein modeling uses previously solved structures as starting points, or templates. This is effective because it appears that although the number of actual proteins is vast, there is a limited set of tertiary structural motifs to which most proteins belong. It has been suggested that there are only around 2,000 distinct protein folds in nature, though there are many millions of different proteins. The comparative protein modeling can combine with the evolutionary covariation in the structure prediction.
These methods may also be split into two groups:
Homology modeling is based on the reasonable assumption that two homologous proteins will share very similar structures. Because a protein's fold is more evolutionarily conserved than its amino acid sequence, a target sequence can be modeled with reasonable accuracy on a very distantly related template, provided that the relationship between target and template can be discerned through sequence alignment. It has been suggested that the primary bottleneck in comparative modelling arises from difficulties in alignment rather than from errors in structure prediction given a known-good alignment. Unsurprisingly, homology modelling is most accurate when the target and template have similar sequences.
Protein threading scans the amino acid sequence of an unknown structure against a database of solved structures. In each case, a scoring function is used to assess the compatibility of the sequence to the structure, thus yielding possible three-dimensional models. This type of method is also known as 3D-1D fold recognition due to its compatibility analysis between three-dimensional structures and linear protein sequences. This method has also given rise to methods performing an inverse folding search by evaluating the compatibility of a given structure with a large database of sequences, thus predicting which sequences have the potential to produce a given fold.
=== Modeling of side-chain conformations ===
Accurate packing of the amino acid side chains represents a separate problem in protein structure prediction. Methods that specifically address the problem of predicting side-chain geometry include dead-end elimination and the self-consistent mean field methods. The side chain conformations with low energy are usually determined on the rigid polypeptide backbone and using a set of discrete side chain conformations known as "rotamers". The methods attempt to identify the set of rotamers that minimize the model's overall energy.
These methods use rotamer libraries, which are collections of favorable conformations for each residue type in proteins. Rotamer libraries may contain information about the conformation, its frequency, and the standard deviations about mean dihedral angles, which can be used in sampling. Rotamer libraries are derived from structural bioinformatics or other statistical analysis of side-chain conformations in known experimental structures of proteins, such as by clustering the observed conformations for tetrahedral carbons near the staggered (60°, 180°, −60°) values.
Rotamer libraries can be backbone-independent, secondary-structure-dependent, or backbone-dependent. Backbone-independent rotamer libraries make no reference to backbone conformation, and are calculated from all available side chains of a certain type (for instance, the first example of a rotamer library, done by Ponder and Richards at Yale in 1987). Secondary-structure-dependent libraries present different dihedral angles and/or rotamer frequencies for
α
{\displaystyle \alpha }
-helix,
β
{\displaystyle \beta }
-sheet, or coil secondary structures. Backbone-dependent rotamer libraries present conformations and/or frequencies dependent on the local backbone conformation as defined by the backbone dihedral angles
ϕ
{\displaystyle \phi }
and
ψ
{\displaystyle \psi }
, regardless of secondary structure.
The modern versions of these libraries as used in most software are presented as multidimensional distributions of probability or frequency, where the peaks correspond to the dihedral-angle conformations considered as individual rotamers in the lists. Some versions are based on very carefully curated data and are used primarily for structure validation, while others emphasize relative frequencies in much larger data sets and are the form used primarily for structure prediction, such as the Dunbrack rotamer libraries.
Side-chain packing methods are most useful for analyzing the protein's hydrophobic core, where side chains are more closely packed; they have more difficulty addressing the looser constraints and higher flexibility of surface residues, which often occupy multiple rotamer conformations rather than just one.
== Quaternary structure ==
In the case of complexes of two or more proteins, where the structures of the proteins are known or can be predicted with high accuracy, protein–protein docking methods can be used to predict the structure of the complex. Information of the effect of mutations at specific sites on the affinity of the complex helps to understand the complex structure and to guide docking methods.
== Software ==
A great number of software tools for protein structure prediction exist. Approaches include homology modeling, protein threading, ab initio methods, secondary structure prediction, and transmembrane helix and signal peptide prediction. In particular, deep learning based on long short-term memory has been used for this purpose since 2007, when it was successfully applied to protein homology detection and to
predict subcellular localization of proteins.
Some recent successful methods based on the CASP experiments include I-TASSER, HHpred and AlphaFold. In 2021, AlphaFold was reported to perform best.
Knowing the structure of a protein often allows functional prediction as well. For instance, collagen is folded into a long-extended fiber-like chain and it makes it a fibrous protein. Recently, several techniques have been developed to predict protein folding and thus protein structure, for example, Itasser, and AlphaFold.
=== AI methods ===
AlphaFold was one of the first AIs to predict protein structures. It was introduced by Google's DeepMind in the 13th CASP competition, which was held in 2018. AlphaFold relies on a
neural network approach, which directly predicts the 3D coordinates of all non-hydrogen atoms for a given protein using the amino acid sequence and aligned homologous sequences. The AlphaFold network consists of a trunk which processes the inputs through repeated layers, and a structure module which introduces an explicit 3D structure. Earlier neural networks for protein structure prediction used LSTM.
Since AlphaFold outputs protein coordinates directly, AlphaFold produces predictions in graphics processing unit (GPU) minutes to GPU hours, depending on the length of protein sequence.
The European Bioinformatics Institute together with DeepMind have constructed the AlphaFold – EBI database for predicted protein structures.
=== Current AI methods and databases of predicted protein structures ===
AlphaFold2, was introduced in CASP14, and is capable of predicting protein structures to near experimental accuracy. AlphaFold was swiftly followed by RoseTTAFold and later by OmegaFold and the ESM Metagenomic Atlas.
In a study, Sommer et al. 2022 demonstrated the application of protein structure prediction in genome annotation, specifically in identifying functional protein isoforms using computationally predicted structures, available at https://www.isoform.io. This study highlights the promise of protein structure prediction as a genome annotation tool and presents a practical, structure-guided approach that can be used to enhance the annotation of any genome.
In 2024, David Baker and Demis Hassabis were awarded the Nobel Prize in Chemistry for their contributions to computational protein modeling, including the development of AlphaFold2, an AI-based model for protein structure prediction. AlphaFold2's accuracy has been evaluated against experimentally determined protein structures using metrics such as root-mean-square deviation (RMSD). The median RMSD between different experimental structures of the same protein is approximately 0.6 Å, while the median RMSD between AlphaFold2 predictions and experimental structures is around 1 Å. For regions where AlphaFold2 assigns high confidence, the median RMSD is about 0.6 Å, comparable to the variability observed between different experimental structures. However, in low-confidence regions, the RMSD can exceed 2 Å, indicating greater deviations. In proteins with multiple domains connected by flexible linkers, AlphaFold2 predicts individual domain structures accurately but may assign random relative positions to these domains. Additionally, AlphaFold2 does not account for structural constraints such as the membrane plane, sometimes placing protein domains in positions that would physically clash with the membrane.
=== Evaluation of automatic structure prediction servers ===
CASP, which stands for Critical Assessment of Techniques for Protein Structure Prediction, is a community-wide experiment for protein structure prediction taking place every two years since 1994. CASP provides with an opportunity to assess the quality of available human, non-automated methodology (human category) and automatic servers for protein structure prediction (server category, introduced in the CASP7).
The CAMEO3D Continuous Automated Model EvaluatiOn Server evaluates automated protein structure prediction servers on a weekly basis using blind predictions for newly release protein structures. CAMEO publishes the results on its website.
== See also ==
== References ==
=== Further reading ===
== External links ==
Official website, Protein Structure Prediction Center, CASP experiments
ExPASy Proteomics tools – list of prediction tools and servers | Wikipedia/Protein_folding_problem |
DnaJ homolog subfamily C member 5, also known as cysteine string protein or CSP is a protein, that in humans encoded by the DNAJC5 gene. It was first described in 1990.
== Gene ==
In humans, the gene is located on the long arm of chromosome 20 (20q13.33) on the Watson (positive strand). The gene is 40,867 bases in length and the encoded protein has 198 amino acids with a predicted molecular weight of 22.149 kilodaltons (kDa). The weight of the mature protein is 34 kDa.
This gene is highly conserved and found both in invertebrates and vertebrates. In humans, a pseudogene of this gene is located on the short arm of chromosome 8.
== Structure ==
The organisation of the protein is as follows:
an N-terminus phosphorylation site for protein kinase A
a J domain (~70 amino acids)
a linker region
a cysteine motif consisting of 13–15 cysteines within a stretch of 25 amino acids. It is heavily palmitoylated in the cysteine string motif.
a less conserved C-terminal domain
== Tissue distribution ==
This protein is abundant in neural tissue and displays a characteristic localization to synaptic and clathrin coated vesicles. It is also found on secretory vesicles in endocrine, neuroendocrine and exocrine cells. This protein makes up ~1% of the protein content of the synaptic vesicles. DNAJC5 appears to have a role in stimulated exocytosis.
== Function ==
The encoded protein is a member of the J protein family. These proteins function in many cellular processes by regulating the ATPase activity of 70 kDa heat shock proteins (Hsp70). DNAJC5 is a guanine nucleotide exchange factor for Gα proteins. CSPα plays a role in membrane trafficking and protein folding, and has been shown to have anti-neurodegenerative properties. It is known to play a role in cystic fibrosis and Huntington's disease.
This protein has been proposed as a key element of the synaptic molecular machinery devoted to the rescue of synaptic proteins that have been unfolded by activity dependent stress. Syntaxin 1A, a plasma membrane SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) critical for neurotransmission, forms a complex with CSPα, a G protein and an N-type calcium channel. Huntingtin may be able displace both syntaxin 1A and CSPα from N-type channels. CSP interacts with the calcium sensor protein synaptotagmin 9 via its linker domain.
Huntingtin-interacting protein 14, a palmitoyl transferase, is required for exocytosis and targeting of CSP to synaptic vesicles. The palmitoyl residues are transferred to the cysteine residues. If these resides are mutated membrane targeting is reduced or lost. The rat CSP forms a complex with Sgt (SGTA) and Hsc70 (HSPA8) located on the synaptic vesicle surface. This complex functions as an ATP-dependent chaperone that reactivates denatured substrates. Furthermore, the Csp/Sgt/Hsc70 complex appears to be important for maintenance of normal synapses.
Its expression may be increased with the use of lithium. Quercetin promotes formation of stable CSPα-CSPα dimers.
Cysteine-string protein increases the calcium sensitivity of neurotransmitter exocytosis.
== Interactions ==
DNAJC5 has been shown to interact with the cystic fibrosis transmembrane conductance regulator.
== Clinical significance ==
Mutations in this gene may cause neuronal ceroid lipofuscinosis.
== References ==
== Further reading ==
== External links ==
GeneReviews/NCBI/NIH/UW entry on Neuronal Ceroid-Lipofuscinosis | Wikipedia/DNAJC5 |
Binding immunoglobulin protein (BiPS) also known as 78 kDa glucose-regulated protein (GRP-78) or heat shock 70 kDa protein 5 (HSPA5) is a protein that in humans is encoded by the HSPA5 gene.
BiP is a HSP70 molecular chaperone located in the lumen of the endoplasmic reticulum (ER) that binds newly synthesized proteins as they are translocated into the ER, and maintains them in a state competent for subsequent folding and oligomerization. BiP is also an essential component of the translocation machinery and plays a role in retrograde transport across the ER membrane of aberrant proteins destined for degradation by the proteasome. BiP is an abundant protein under all growth conditions, but its synthesis is markedly induced under conditions that lead to the accumulation of unfolded polypeptides in the ER.
== Structure ==
BiP contains two functional domains: a nucleotide-binding domain (NBD) and a substrate-binding domain (SBD). The NBD binds and hydrolyzes ATP, and the SBD binds polypeptides.
The NBD consists of two large globular subdomains (I and II), each further divided into two small subdomains (A and B). The subdomains are separated by a cleft where the nucleotide, one Mg2+, and two K+ ions bind and connect all four domains (IA, IB, IIA, IIB). The SBD is divided into two subdomains: SBDβ and SBDα. SBDβ serves as a binding pocket for client proteins or peptide and SBDα serves as a helical lid to cover the binding pocket. An inter-domain linker connects NBD and SBD, favoring the formation of an NBD–SBD interface.
== Mechanism ==
The activity of BiP is regulated by its allosteric ATPase cycle: when ATP is bound to the NBD, the SBDα lid is open, which leads to the conformation of SBD with low affinity to substrate. Upon ATP hydrolysis, ADP is bound to the NBD and the lid closes on the bound substrate. This creates a low off rate for high-affinity substrate binding and protects the bound substrate from premature folding or aggregation. Exchange of ADP for ATP results in the opening of the SBDα lid and subsequent release of the substrate, which then is free to fold. The ATPase cycle can be synergistically enhanced by protein disulfide isomerase (PDI), and its cochaperones.
== Function ==
When K12 cells are starved of glucose, the synthesis of several proteins, called glucose-regulated proteins (GRPs), is markedly increased. GRP78 (HSPA5), also referred to as 'immunoglobulin heavy chain-binding protein' (BiP), is a member of the heat-shock protein-70 (HSP70) family and involved in the folding and assembly of proteins in the ER. The level of BiP is strongly correlated with the amount of secretory proteins (e.g. IgG) within the ER.
Substrate release and binding by BiP facilitates diverse functions in the ER such as folding and assembly of newly synthesized proteins, binding to misfolded proteins to prevent protein aggregation, translocation of secretory proteins, and initiation of the UPR.
=== Protein folding and holding ===
BiP can actively fold its substrates (acting as a foldase) or simply bind and restrict a substrate from folding or aggregating (acting as a holdase). Intact ATPase activity and peptide binding activity are required to act as a foldase: temperature-sensitive mutants of BiP with defective ATPase activity (called class I mutations) and mutants of BiP with defective peptide binding activity (called class II mutations) both fail to fold carboxypeptidase Y (CPY) at non-permissive temperature.
=== ER translocation ===
As an ER molecular chaperone, BiP is also required to import polypeptide into the ER lumen or ER membrane in an ATP-dependent manner. ATPase mutants of BiP were found to cause a block in translocation of a number of proteins (invertase, carboxypeptidase Y, a-factor) into the lumen of the ER.
=== ER-associated degradation (ERAD) ===
BiP also plays a role in ERAD. The most studied ERAD substrate is CPY*, a constitutively misfolded CPY completely imported into the ER and modified by glycosylation. BiP is the first chaperone that contacts CPY* and is required for CPY* degradation. ATPase mutants (including allosteric mutants) of BiP have been shown to significantly slow down the degradation rate of CPY*.
=== UPR pathway ===
BiP is both a target of the ER stress response, or UPR, and an essential regulator of the UPR pathway. During ER stress, BiP dissociates from the three transducers (IRE1, PERK, and ATF6), effectively activating their respective UPR pathways. As a UPR target gene product, BiP is upregulated when UPR transcription factors associate with the UPR element in BiP's DNA promoter region.
== Interactions ==
BiP's ATPase cycle is facilitated by its co-chaperones, both nucleotide binding factors (NEFs), which facilitate ATP binding upon ADP release, and J proteins, which promote ATP hydrolysis. BiP is also a validated substrate of HYPE (Huntingtin Yeast Interacting Partner E), which can adenylate BiP at multiple residues.
== Conservation of BiP cysteines ==
BiP is highly conserved among eukaryotes, including mammals (Table 1). It is also widely expressed among all tissue types in human. In the human BiP, there are two highly conserved cysteines. These cysteines have been shown to undergo post-translational modifications in both yeast and mammalian cells. In yeast cells, the N-terminus cysteine has been shown to be sulfenylated and glutathionylated upon oxidative stress. Both modifications enhance BiP's ability to prevent protein aggregation. In mice cells, the conserved cysteine pair forms a disulfide bond upon activation of GPx7 (NPGPx). The disulfide bond enhances BiP's binding to denatured proteins.
== Clinical significance ==
=== Autoimmune disease ===
Like many stress and heat shock proteins, BiP has potent immunological activity when released from the internal environment of the cell into the extracellular space. Specifically, it feeds anti-inflammatory and pro-resolutory signals into immune networks, thus helping to resolve inflammation. The mechanisms underlying BiP's immunological activity are incompletely understood. Nonetheless, it has been shown to induce anti-inflammatory cytokine secretion by binding to a receptor on the surface of monocytes, downregulate critical molecules involved in T-lymphocyte activation, and modulate the differentiation pathway of monocytes into dendritic cells.
The potent immunomodulatory activities of BiP/GRP78 have also been demonstrated in animal models of autoimmune disease including collagen-induced arthritis, a murine disease that resembles human rheumatoid arthritis. Prophylactic or therapeutic parenteral delivery of BiP has been shown to ameliorate clinical and histological signs of inflammatory arthritis.
=== Cardiovascular disease ===
Upregulation of BiP has been associated with ER stress-induced cardiac dysfunction and dilated cardiomyopathy. BiP also has been proposed to suppress the development of atherosclerosis through alleviating homocysteine-induced ER stress, preventing apoptosis of vascular endothelial cells, inhibiting the activation of genes responsible for cholesterol/triglyceride biosynthesis, and suppressing tissue factor procoagulant activity, all of which can contribute to the buildup of atherosclerotic plaques.
Some anticancer drugs, such as proteasome inhibitors, have been associated with heart failure complications. In rat neonatal cardiomyocytes, overexpression of BiP attenuates cardiomyocyte death induced by proteasome inhibition.
=== Neurodegenerative disease ===
As an ER chaperone protein, BiP prevents neuronal cell death induced by ER stress by correcting misfolded proteins. Moreover, a chemical inducer of BiP, named BIX, reduced cerebral infarction in cerebral ischemic mice. Conversely, enhanced BiP chaperone function has been strongly implicated in Alzheimer's disease.
=== Metabolic disease ===
BiP heterozygosity is proposed to protect against high fat diet-induced obesity, type 2 diabetes, and pancreatitis by upregulating protective ER stress pathways. BiP is also necessary for adipogenesis and glucose homeostasis in adipose tissues.
=== Infectious disease ===
Prokaryotic BiP orthologs were found to interact with key proteins such as RecA, which is vital to bacterial DNA replication. As a result, these bacterial Hsp70 chaperones represent a promising set of targets for antibiotic development. Notably, the anticancer drug OSU-03012 re-sensitized superbug strains of Neisseria gonorrhoeae to several standard-of-care antibiotics. Meanwhile, a virulent strain of Shiga toxigenic Escherichia coli undermines host cell survival by producing AB5 toxin to inhibit host BiP. In contrast, viruses rely on host BiP to successfully replicate, largely by infecting cells through cell-surface BiP, stimulating BiP expression to chaperone viral proteins, and suppressing the ER stress death response.
== Notes ==
== References ==
== External links ==
HSPA5+protein,+human at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
Human HSPA5 genome location and HSPA5 gene details page in the UCSC Genome Browser.
PDBe-KB provides an overview of all the structure information available in the PDB for Human Endoplasmic reticulum chaperone BiP | Wikipedia/Binding_immunoglobulin_protein |
Heat shock protein HSP 90-alpha is a protein that in humans is encoded by the HSP90AA1 gene.
== Function ==
The gene, HSP90AA1, encodes the human stress-inducible 90-kDa heat shock protein alpha (Hsp90A). Complemented by the constitutively expressed paralog Hsp90B which shares over 85% amino acid sequence identity, Hsp90A expression is initiated when a cell experiences proteotoxic stress. Once expressed Hsp90A dimers operate as molecular chaperones that bind and fold other proteins into their functional 3-dimensional structures. This molecular chaperoning ability of Hsp90A is driven by a cycle of structural rearrangements fueled by ATP hydrolysis. Current research on Hsp90A focuses in its role as a drug target due to its interaction with a large number of tumor promoting proteins and its role in cellular stress adaptation.
== Gene structure ==
Human HSP90AA1 is encoded on the complement strand of Chromosome 14q32.33 and spans over 59 kbp. Several pseudogenes of HSP90AA1 exist throughout the human genome located on Chromosomes 3, 4, 11 and 14. The HSP90AA1 gene encodes for two distinct mRNA transcripts initiated from separate transcription start sites (TSS). No mRNA splice variants of HSP90AA1 have presently been verified. Transcript variant 1 (TV1, NM_001017963.2) encodes the infrequently observed 854 amino acid isoform 1 of Hsp90A (NP_001017963) from a 3,887 bp mRNA transcript containing 12 exons spanning 59, 012 bp. Transcript variant 1 is located directly next to the WDR20 gene, which is encoded on the opposite coding strand. Transcript variant 2 (TV2, NM_005348.3) encodes the well-studied 732 amino acid isoform 2 (NP_005339) from a 3,366 bp mRNA transcript containing 11 exons spanning 6,438 bp. DYNC1H1 encodes the gene product on the other side of HSP90AA1, which coincidentally has been found to interact with Hsp90A. Hsp90A TV1 and TV2 are identical except for an additional 112 amino acids on the N-terminus of isoform 1 encoded by its first 2 exons. The function of the extended N-terminal domain on isoform 1 is currently not understood. This information was gathered from both NCBI Gene and the UCSC Genome Browser.
== Expression ==
Despite sharing similar amino acid sequence, Hsp90A expression is regulated in a different manner than Hsp90B. Hsp90A is the stress inducible isoform while Hsp90B is expressed constitutively. Several heat shock elements (HSE) are located upstream of Hsp90A allowing for its inducible expression. RNA levels measured in cell lines collected from cancer patients as well as normal tissue can be found at The Human Protein Atlas.
== Promoter ==
Transcription of the HSP90AA1 gene is currently understood to be induced by stress through binding of the master transcription factor (TF) HSF1 to the HSP90AA1 promoter. However, several focused studies of the HSP90AA1 promoter along with extensive global analysis of the human genome indicate that various other transcription complexes regulate HSP90AA1 gene expression. Mammalian HSP90AA1 along with HSP90AB1 gene expression was first characterized in transformed mouse cells where it was shown that HSP90AB1 is constitutively expressed 2.5-fold higher than HSP90AA1 under normal conditions. However upon heat shock, HSP90AA1 expression increased 7.0-fold while HSP90AB1 increases only 4.5-fold. Detailed analysis of the HSP90AA1 promoter shows that there are 2 heat shock elements (HSE) within 1200 bp of the transcription start site. The distal HSE is required for heat shock induction and the proximal HSE functions as a permissive enhancer. This model is supported by ChIP-SEQ analysis of cells under normal conditions where HSF1 is found bound to the proximal HSE and not detected at the distal HSE. The proto-oncogene MYC is also found to induce HSP90AA1 gene expression and binds proximally to the TSS as verified by ChIP-SEQ. Depletion of Hsp90A expression indicates that HSP90AA1 is required for MYC-driven transformation. In breast cancer cells the growth hormone prolactin induces HSP90AA1 expression through STAT5. NF-κB or RELA also induces HSP90AA1 expression possibly explaining the pro-survival ability of NF-κB-driven transcription. Conversely, STAT1, the proto-tumor suppressor, is found to inhibit stress induced expression of HSP90AA1. In addition to these findings, ChIP-SEQ analysis of the human genome indicates that at least 85 unique TFs bind to the RNA polymerase II (POLR2A) footprints associated with the promoter regions that drive the expression of both HSP90AA1 transcript variants. This indicates that HSP90AA1 gene expression may be highly regulated and complex.
== Interactome ==
Combined, Hsp90A and Hsp90B are predicted to interact with 10% of the eukaryotic proteome. In humans this represents a network of roughly 2,000 interacting proteins. Presently over 725 interactions have been experimentally documented for both HSP90A and Hsp90B. This connectivity allows Hsp90 to function as a network hub linking diverse protein interaction networks. Within these networks Hsp90 primarily specializes in maintaining and regulating proteins involved in signal transduction or information processing. These include transcription factors that initiate gene expression, kinases that transmit information by post-translationally modifying other proteins and E3-ligases that target proteins for degradation via the proteosome. Indeed, a recent study utilizing the LUMIER method has shown that human Hsp90B interacts with 7% of all transcription factors, 60% of all kinases and 30% of all E3-ligases. Other studies have shown that Hsp90 interacts with various structural proteins, ribosomal components and metabolic enzymes. Hsp90 has also been found to interact with a large number of viral proteins including those from HIV and EBOLA. This is not to mention the numerous co-chaperones that modulate and direct HSP90 activity. Few studies have focused on discerning the unique protein interactions between Hsp90A and HSP90B. Work done in Xenopus eggs and yeast has shown that Hsp90A and Hsp90B differ in co-chaperone and client interactions. However, little is understood concerning the unique functions delegated to each human paralog. The Picard lab has aggregated all available Hsp90 interaction data into the Hsp90Int.DB website. Gene ontology analysis of both Hsp90A and Hsp90B interactomes indicate that each paralogs is associated with unique biological processes, molecular functions and cellular components.
Heat shock protein 90kDa alpha (cytosolic), member A1 has been shown to interact with:
== Post-translational modifications ==
Post-translational modifications have a large impact on Hsp90 regulation. Phosphorylation, acetylation, S-nitrosylation, oxidation and ubiquitination are ways in which Hsp90 is modified in order to modulate its many functions. A summary of these sites can be found at PhosphoSitePlus. Many of these sites are conserved between Hsp90A and Hsp90B. However, there are a few distinctions between the two that allow for specific functions to be performed by Hsp90A.
Phosphorylation of Hsp90 has been shown to have affect its binding to clients, co-chaperones and nucleotide. Specific phosphorylation of Hsp90A residues have been shown to occur. These unique phosphorylation sites signal Hsp90A for functions such as secretion, allow it to locate to regions of DNA damage and interact with specific co-chaperones. Hyperacetylation also occurs with Hsp90A which leading to its secretion and increased cancer invasiveness.
== Clinical significance ==
Expression of Hsp90A also correlates with disease prognosis. Increased levels of Hsp90A are found in leukemia, breast and pancreatic cancers as well as in patients with chronic obstructive pulmonary disease (COPD). In human T-cells, HSP90AA1 expression is increased by the cytokines IL-2, IL-4 and IL-13. HSP90, alongside other conserved chaperones and co-chaperones that interact to safeguard proteostasis, is repressed in aging human brains. This repression was found to be further exacerbated in the brains of patients with age-onset neurodegenerative diseases such as Alzheimer's or Huntington's disease.
=== Cancer ===
Over the last two decades HSP90 has emerged as an intriguing target in the war on cancer. HSP90 interacts and supports numerous proteins that promote oncogenesis, thus distinguishing Hsp90 as a cancer enabler as it is regarded as essential for malignant transformation and progression. Moreover, through their extensive interactomes, both paralogs are associated with each hallmark of cancer. The HSP90AA1 gene however is not altered in a majority of tumors according to The Cancer Genome Atlas (TCGA). Currently bladder cancer is found to have the largest number of alterations followed by pancreatic cancer. This may not come as a surprise since overall Hsp90 expression levels are held at such a high level compared to most all other proteins within the cell, therefore further increasing Hsp90 levels may not provide any benefit to cancer growth. Additionally, whole genome sequencing across all tumor types and cancer cell lines reveals that there are presently 115 different mutations within the HSP90AA1 open reading frame. The effects of these mutations on HSP90A function, however, remain unknown. Remarkably, in a number of tumors the HSP90AA1 gene is homozygously deleted, suggesting that these tumors may have a reduced level of malignancy. This is supported by a comparative genome-wide analysis of 206 gastric cancer patients that reported loss of HSP90AA1 is indeed associated with favorable outcomes after surgery alone. This supports the possibility that the absence of Hsp90A in tumor biopsies may serve as a biomarker for positive clinical outcomes.
Biologically, Hsp90A differs from Hsp90B in that Hsp90A is presently understood to function as a secreted extracellular agent in wound healing and inflammation in addition to its intracellular roles. These two processes are often hijacked by cancer allowing for malignant cell motility, metastasis and extravasion. Current research in prostate cancer indicates that extracellular Hsp90A transduces signals that promote the chronic inflammation of cancer-associated fibroblasts. This reprogramming of the extracellular milieu surrounding malignant adenocarcinoma cells is understood to stimulate prostate cancer progression. Extracellular HSP90A induces inflammation through the activation of the NF-κB (RELA) and STAT3 transcription programs that include the pro-inflammatory cytokines IL-6 and IL-8. Coincidentally NF-κB also induces expression Hsp90A., thus providing a model where newly expressed Hsp90A would also be secreted from the stimulated fibroblast thereby creating positive autocrine and paracrine feedback loops resulting in an inflammatory storm at the site of malignancy. This concept requires further attention as it may explain the correlation of increased levels of Hsp90A in the plasma of patients with advanced stages of malignancy.
=== Hsp90 Inhibitors ===
Hsp90 is exploited by cancer cells to support activated oncoproteins, including many kinases and transcription factors. These clients are often mutated, amplified or translocated in malignancy, and Hsp90 works to buffer these cellular stresses induced by malignant transformation. Inhibition of Hsp90 leads to the degradation or instability of many of its client proteins. Thus, Hsp90 has become an attractive target for cancer therapy.
As with all ATPases, ATP binding and hydrolysis is essential for the chaperoning function of Hsp90 in vivo. Hsp90 inhibitors interfere with this cycle at its early stages by replacing ATP, leading to the regulated ubiquitination and proteasome-mediated degradation of most client proteins. As such, the nucleotide binding pocket remains that most amenable to inhibitor generation. To date, there are 23 active Hsp90 inhibitor oncology trials, and 13 HSP90 inhibitors are currently undergoing clinical evaluation in cancer patients, 10 of which have entered the clinic in the past few years.
While the N-terminal nucleotide-binding pocket of Hsp90 is most widely studied and thus targeted, recent studies have suggested that a second ATP-binding site is located in the Hsp90 C-terminus. Targeting of this region has resulted in specific reduced Hsp90-hormone interactions and has been shown to influence Hsp90 nucleotide binding. Although none of the C-terminal Hsp90 inhibitors have yet to enter the clinic, the use of both N- and C-terminal Hsp90 inhibitors in combination represents an exciting new strategy for chemotherapy.
Although many of the afore-mentioned inhibitors share the same Hsp90 binding site (either N- or C-terminal), it has been shown that some of these drugs preferentially access distinct Hsp90 populations, which are differentiated by the extent of their post-translational modification. Though no published inhibitor has yet to distinguish between Hsp90A and Hsp90B, a recent study has shown that phosphorylation of a particular residue in the Hsp90 N-terminus can provide isoform specificity to inhibitor binding, thus providing an additional level of regulation for optimal Hsp90 targeting.
== Notes ==
== References ==
== Further reading ==
== External links ==
Overview of all the structural information available in the PDB for UniProt: P07900 (Heat shock protein HSP 90-alpha) at the PDBe-KB. | Wikipedia/Heat_shock_protein_90kDa_alpha_(cytosolic),_member_A1 |
Prokaryotic ubiquitin-like protein (Pup) is a functional analog of ubiquitin found in the prokaryote Mycobacterium tuberculosis. Like ubiquitin, Pup serves to direct proteins to the proteasome for degradation in the Pup-proteasome system (PPS). However, the enzymology of ubiquitylation and pupylation is different, owing to their distinct evolutionary origins. In contrast to the three-step reaction of ubiquitylation, pupylation requires only two steps, and thus only two enzymes are involved in pupylation. The enzymes involved in pupylation are descended from glutamine synthetase.
Similar to ubiquitin, Pup is attached to specific lysine residues of substrate proteins by isopeptide bonds; this is called pupylation. It is then recognized by the protein Mycobacterium proteasomal ATPase (Mpa), in a mechanism that induces folding of Pup. Mpa delivers the substrate protein to the proteasome for degradation by coupling of ATP hydrolysis.
The discovery of Pup indicates that like eukaryotes, bacteria may use a small-protein modifier to control protein stability.
The Pup gene encodes a 64–amino acid protein with a molecular size of about 6.9 kDa.
Pup is an intrinsically disordered protein. In 2010, scientists at the Brookhaven National Laboratory determined the X-ray crystal structure of the complex between Pup and its delivery enzyme Mpa 3M9D and found that Pup binding to Mpa induces the folding of a unique alpha-helix.
In 2017, the presence of Pup homologs in bacterial species outside of the group of gram-positive bacteria was reported. The Pup homologs were termed UBact (for Ubiquitin Bacterial), although the distinction has not been proven to be phylogenetically supported by a separate evolutionary origin and is without experimental evidence. UBact is a homolog of Pup, and is found in several phyla of gram-negative bacteria (Pup is found predominantly in the gram-positive bacterial phylum Actinomycetota).
== Ubiquitin bacterial ==
Ubiquitin Bacterial (UBact) is a protein that is homologous to Prokaryotic ubiquitin-like protein (Pup). UBact was recently described by the group of Professor Aaron Ciechanover at the Technion, Israel.
Ubiquitin was named for its ubiquitous presence among eukaryotes, while UBact ('Ubiquitin bacterial') is very limited in occurrence among the vast number of bacterial species. The terms 'Ubiquitin Bacterial' and 'Prokaryotic ubiquitin-like protein' suggest a molecular similarity between ubiquitin and UBact/Pup which is largely absent. While ubiquitin assumes a highly stable three-dimensional structure in solution, Pup has been shown to belong to the group of intrinsically disordered proteins.
The establishment of the term UBact is controversial, since to date there is no experimental evidence presented to justify the distinction of UBact from Pup. The term UBact was denoted because several bacterial species from the phylum Nitrospirae (where UBact was initially identified; e.g., Leptospirillum ferriphilum) contain both the Pup-proteasome system and a novel ORF-proteasome system that needed to be addressed and therefore was denoted UBact. The conjugation-proteasome components neighboring the UBact and Pup loci in these Nitrospirae bacteria show weak similarity and are probably not entirely redundant. Figure 2 illustrates the differences between the UBact and Pup loci in the representative Nitrospirae bacterium Leptospirillum ferrodiazotrophum. Further analyses of the UBact (and not Pup) locus in Leptospirillum ferrodiazotrophum revealed its existence and extreme conservation across several gram-negative bacterial phyla, as illustrated in figure 3.
In spite of the large difference in sequence, UBact is homologous to Pup and shares several characteristics with it: (i) same genomic location within a cluster of genes homologous to Mpa -> Dop -> Pup/UBact -> PrcB -> PrcA -> PafA, (ii) C-terminal sequence that ends exclusively with glutamine or glutamate across bacterial species, (iii) short size (similar to that of ubiquitin) and, (iv) high sequence conservation across tremendous evolutionary distance (a characteristic also in common with ubiquitin). The differences between UBact and Pup are their taxonomic distribution and amino acid sequences. While Pup is predominantly found in the gram-positive phylum Actinomycetota, UBact was identified only in gram-negative bacteria from the following five phyla: Nitrospirota, Verrucomicrobiota, Armatimonadota, Nitrospinota, and Planctomycetota. UBact was also identified in the genomes of several candidatus bacteria, and specifically from the candidate divisions "Acetothermia", "Handelsmanbacteria", "Fraserbacteria", "Terrybacteria", "Poribacteria", "Parcubacteria", and "Yanofskybacteria". With regard to the amino acid sequence, in difference from Pup and Ubiquitin, UBact does not contain a di-glycine motif at its C-terminus. Rather, it usually ends with the sequence R[T/S]G[E/Q] (see figure 3).
It took almost ten years since the discovery of Pup in 2008, to identify UBact. This is probably due to the difference between Pup and UBact amino acids sequences, and because very few bacteria from the five phyla where UBact is found have been sequenced.
Bacteria from the phyla where UBact is found interact with humans, and are found in the human gut microbiota. In marine systems, the most frequently encountered nitrogen-oxidizing bacteria are related to the UBact encoding Nitrospina gracilis From the knowledge accumulated about the Pup-proteasome system and its importance in bacterial durability and disease causing ability, the homologous UBact-proteasome system is expected to have similar impact on the gram-negative bacteria where it is found. In addition to humans, animals such livestock and fish that eat from the ground or swim in water are expected to be constantly exposed to UBact containing bacteria in the soil and water respectively.
From evolutionary perspective, the finding of the UBact-proteasome system in gram-negative bacteria suggests that either the Pup/UBact-proteasome systems evolved in bacteria prior to the split into gram positive and negative clades over 3000 million years ago or, that these systems were acquired by different bacterial lineages through horizontal gene transfer(s) from a third, yet unknown, organism. In support of the second possibility, two UBact loci were found in the genome of an uncultured anaerobic methanotrophic Archaeon (ANME-1;locus CBH38808.1 and locus CBH39258.1). More possibilities exist.
Update: UBact is also found in the gram-negative bacterial phylum Gemmatimonadota (e.g., A0A2E8WA32, A0A2E3J6F7, A0A2E7JSE3) in the candidate phylum "Latescibacteria" (previously known as WS3; e.g., A0A3D2RHP4, A0A3D5FTR6, A0A3D4H075, and A0A3B8MMW3), in the phylum "Abditibacteriota" (previously candidate phylum FBP; e.g., A0A2S8SU03), and in the phylum Candidatus Bipolaricaulota (e.g., H5SEU7 and H5SQ95).
== See also ==
Ubiquitin
SUMO protein
Neddylation
== References ==
== External links ==
PupDB, a database of pupylated proteins and pupylation sites. | Wikipedia/Prokaryotic_ubiquitin-like_protein |
Allergies, also known as allergic diseases, are various conditions caused by hypersensitivity of the immune system to typically harmless substances in the environment. These diseases include hay fever, food allergies, atopic dermatitis, allergic asthma, and anaphylaxis. Symptoms may include red eyes, an itchy rash, sneezing, coughing, a runny nose, shortness of breath, or swelling. Note that food intolerances and food poisoning are separate conditions.
Common allergens include pollen and certain foods. Metals and other substances may also cause such problems. Food, insect stings, and medications are common causes of severe reactions. Their development is due to both genetic and environmental factors. The underlying mechanism involves immunoglobulin E antibodies (IgE), part of the body's immune system, binding to an allergen and then to a receptor on mast cells or basophils where it triggers the release of inflammatory chemicals such as histamine. Diagnosis is typically based on a person's medical history. Further testing of the skin or blood may be useful in certain cases. Positive tests, however, may not necessarily mean there is a significant allergy to the substance in question.
Early exposure of children to potential allergens may be protective. Treatments for allergies include avoidance of known allergens and the use of medications such as steroids and antihistamines. In severe reactions, injectable adrenaline (epinephrine) is recommended. Allergen immunotherapy, which gradually exposes people to larger and larger amounts of allergen, is useful for some types of allergies such as hay fever and reactions to insect bites. Its use in food allergies is unclear.
Allergies are common. In the developed world, about 20% of people are affected by allergic rhinitis, food allergy affects 10% of adults and 8% of children, and about 20% have or have had atopic dermatitis at some point in time. Depending on the country, about 1–18% of people have asthma. Anaphylaxis occurs in between 0.05–2% of people. Rates of many allergic diseases appear to be increasing. The word "allergy" was first used by Clemens von Pirquet in 1906.
== Signs and symptoms ==
Many allergens such as dust or pollen are airborne particles. In these cases, symptoms arise in areas in contact with air, such as the eyes, nose, and lungs. For instance, allergic rhinitis, also known as hay fever, causes irritation of the nose, sneezing, itching, and redness of the eyes. Inhaled allergens can also lead to increased production of mucus in the lungs, shortness of breath, coughing, and wheezing.
Aside from these ambient allergens, allergic reactions can result from foods, insect stings, and reactions to medications like aspirin and antibiotics such as penicillin. Symptoms of food allergy include abdominal pain, bloating, vomiting, diarrhea, itchy skin, and hives. Food allergies rarely cause respiratory (asthmatic) reactions, or rhinitis. Insect stings, food, antibiotics, and certain medicines may produce a systemic allergic response that is also called anaphylaxis; multiple organ systems can be affected, including the digestive system, the respiratory system, and the circulatory system. Depending on the severity, anaphylaxis can include skin reactions, bronchoconstriction, swelling, low blood pressure, coma, and death. This type of reaction can be triggered suddenly, or the onset can be delayed. The nature of anaphylaxis is such that the reaction can seem to be subsiding but may recur throughout a period of time.
=== Skin ===
Substances that come into contact with the skin, such as latex, are also common causes of allergic reactions, known as contact dermatitis or eczema. Skin allergies frequently cause rashes, or swelling and inflammation within the skin, in what is known as a "wheal and flare" reaction characteristic of hives and angioedema.
With insect stings, a large local reaction may occur in the form of an area of skin redness greater than 10 cm in size that can last one to two days. This reaction may also occur after immunotherapy.
The way the body responds to foreign invaders on the molecular level is similar to how allergens are treated even on the skin. The skin forms an effective barrier to the entry of most allergens but this barrier cannot withstand everything that comes at it. A situation such as an insect sting can breach the barrier and inject allergen to the affected spot. When an allergen enters the epidermis or dermis, it triggers a localized allergic reaction which activates the mast cells in the skin resulting in an immediate increase in vascular permeability, leading to fluid leakage and swelling in the affected area. Mast-cell activation also stimulates a skin lesion called the wheal-and-flare reaction. This is when the release of chemicals from local nerve endings by a nerve axon reflex, causes the vasodilatations of surrounding cutaneous blood vessels, which causes redness of the surrounding skin.
As a part of the allergy response, the body has developed a secondary response which in some individuals causes a more widespread and sustained edematous response. This usually occurs about 8 hours after the allergen originally comes in contact with the skin. When an allergen is ingested, a dispersed form of wheal-and-flare reaction, known as urticaria or hives will appear when the allergen enters the bloodstream and eventually reaches the skin. The way the skin reacts to different allergens gives allergists the upper hand and allows them to test for allergies by injecting a very small amount of an allergen into the skin. Even though these injections are very small and local, they still pose the risk of causing systematic anaphylaxis.
== Cause ==
Risk factors for allergies can be placed in two broad categories, namely host and environmental factors. Host factors include heredity, sex, race, and age, with heredity being by far the most significant. However, there has been a recent increase in the incidence of allergic disorders that cannot be explained by genetic factors alone. Four major environmental candidates are alterations in exposure to infectious diseases during early childhood, environmental pollution, allergen levels, and dietary changes.
=== Dust mites ===
Dust mite allergy, also known as house dust allergy, is a sensitization and allergic reaction to the droppings of house dust mites. The allergy is common and can trigger allergic reactions such as asthma, eczema, or itching. The mite's gut contains potent digestive enzymes (notably peptidase 1) that persist in their feces and are major inducers of allergic reactions such as wheezing. The mite's exoskeleton can also contribute to allergic reactions. Unlike scabies mites or skin follicle mites, house dust mites do not burrow under the skin and are not parasitic.
=== Foods ===
A wide variety of foods can cause allergic reactions, but 90% of allergic responses to foods are caused by cow's milk, soy, eggs, wheat, peanuts, tree nuts, fish, and shellfish. Other food allergies, affecting less than 1 person per 10,000 population, may be considered "rare". The most common food allergy in the US population is a sensitivity to crustacea. Although peanut allergies are notorious for their severity, peanut allergies are not the most common food allergy in adults or children. Severe or life-threatening reactions may be triggered by other allergens and are more common when combined with asthma.
Rates of allergies differ between adults and children. Children can sometimes outgrow peanut allergies. Egg allergies affect one to two percent of children but are outgrown by about two-thirds of children by the age of 5. The sensitivity is usually to proteins in the white, rather than the yolk.
Milk-protein allergies—distinct from lactose intolerance—are most common in children. Approximately 60% of milk-protein reactions are immunoglobulin E–mediated, with the remaining usually attributable to inflammation of the colon. Some people are unable to tolerate milk from goats or sheep as well as from cows, and many are also unable to tolerate dairy products such as cheese. Roughly 10% of children with a milk allergy will have a reaction to beef. Lactose intolerance, a common reaction to milk, is not a form of allergy at all, but due to the absence of an enzyme in the digestive tract.
Those with tree nut allergies may be allergic to one or many tree nuts, including pecans, pistachios, and walnuts. In addition, seeds, including sesame seeds and poppy seeds, contain oils in which protein is present, which may elicit an allergic reaction.
Allergens can be transferred from one food to another through genetic engineering; however, genetic modification can also remove allergens. Little research has been done on the natural variation of allergen concentrations in unmodified crops.
=== Latex ===
Latex can trigger an IgE-mediated cutaneous, respiratory, and systemic reaction. The prevalence of latex allergy in the general population is believed to be less than one percent. In a hospital study, 1 in 800 surgical patients (0.125 percent) reported latex sensitivity, although the sensitivity among healthcare workers is higher, between seven and ten percent. Researchers attribute this higher level to the exposure of healthcare workers to areas with significant airborne latex allergens, such as operating rooms, intensive-care units, and dental suites. These latex-rich environments may sensitize healthcare workers who regularly inhale allergenic proteins.
The most prevalent response to latex is an allergic contact dermatitis, a delayed hypersensitive reaction appearing as dry, crusted lesions. This reaction usually lasts 48–96 hours. Sweating or rubbing the area under the glove aggravates the lesions, possibly leading to ulcerations. Anaphylactic reactions occur most often in sensitive patients who have been exposed to a surgeon's latex gloves during abdominal surgery, but other mucosal exposures, such as dental procedures, can also produce systemic reactions.
Latex and banana sensitivity may cross-react. Furthermore, those with latex allergy may also have sensitivities to avocado, kiwifruit, and chestnut. These people often have perioral itching and local urticaria. Only occasionally have these food-induced allergies induced systemic responses. Researchers suspect that the cross-reactivity of latex with banana, avocado, kiwifruit, and chestnut occurs because latex proteins are structurally homologous with some other plant proteins.
=== Medications ===
About 10% of people report that they are allergic to penicillin; however, of that 10%, 90% turn out not to be. Serious allergies only occur in about 0.03%.
=== Insect stings ===
One of the main sources of human allergies is insects. An allergy to insects can be brought on by bites, stings, ingestion, and inhalation.
=== Toxins interacting with proteins ===
Another non-food protein reaction, urushiol-induced contact dermatitis, originates after contact with poison ivy, eastern poison oak, western poison oak, or poison sumac. Urushiol, which is not itself a protein, acts as a hapten and chemically reacts with, binds to, and changes the shape of integral membrane proteins on exposed skin cells. The immune system does not recognize the affected cells as normal parts of the body, causing a T-cell-mediated immune response.
Of these poisonous plants, sumac is the most virulent. The resulting dermatological response to the reaction between urushiol and membrane proteins includes redness, swelling, papules, vesicles, blisters, and streaking.
Estimates vary on the population fraction that will have an immune system response. Approximately 25% of the population will have a strong allergic response to urushiol. In general, approximately 80–90% of adults will develop a rash if they are exposed to 0.0050 mg (7.7×10−5 gr) of purified urushiol, but some people are so sensitive that it takes only a molecular trace on the skin to initiate an allergic reaction.
=== Genetics ===
Allergic diseases are strongly familial; identical twins are likely to have the same allergic diseases about 70% of the time; the same allergy occurs about 40% of the time in non-identical twins. Allergic parents are more likely to have allergic children and those children's allergies are likely to be more severe than those in children of non-allergic parents. Some allergies, however, are not consistent along genealogies; parents who are allergic to peanuts may have children who are allergic to ragweed. The likelihood of developing allergies is inherited and related to an irregularity in the immune system, but the specific allergen is not.
The risk of allergic sensitization and the development of allergies varies with age, with young children most at risk. Several studies have shown that IgE levels are highest in childhood and fall rapidly between the ages of 10 and 30 years. The peak prevalence of hay fever is highest in children and young adults and the incidence of asthma is highest in children under 10.
Ethnicity may play a role in some allergies; however, racial factors have been difficult to separate from environmental influences and changes due to migration. It has been suggested that different genetic loci are responsible for asthma, to be specific, in people of European, Hispanic, Asian, and African origins.
Researchers have worked to characterize genes involved in inflammation and the maintenance of mucosal integrity. The identified genes associated with allergic disease severity, progression, and development primarily function in four areas: regulating inflammatory responses (IFN-α, TLR-1, IL-13, IL-4, IL-5, HLA-G, iNOS), maintaining vascular endothelium and mucosal lining (FLG, PLAUR, CTNNA3, PDCH1, COL29A1), mediating immune cell function (PHF11, H1R, HDC, TSLP, STAT6, RERE, PPP2R3C), and influencing susceptibility to allergic sensitization (e.g., ORMDL3, CHI3L1).
Multiple studies have investigated the genetic profiles of individuals with predispositions to and experiences of allergic diseases, revealing a complex polygenic architecture. Specific genetic loci, such as MIIP, CXCR4, SCML4, CYP1B1, ICOS, and LINC00824, have been directly associated with allergic disorders. Additionally, some loci show pleiotropic effects, linking them to both autoimmune and allergic conditions, including PRDM2, G3BP1, HBS1L, and POU2AF1. These genes engage in shared inflammatory pathways across various epithelial tissues—such as the skin, esophagus, vagina, and lung—highlighting common genetic factors that contribute to the pathogenesis of asthma and other allergic diseases.
In atopic patients, transcriptome studies have identified IL-13-related pathways as key for eosinophilic airway inflammation and remodeling. That causes the body to experience the type of airflow restriction of allergic asthma. Expression of genes was quite variable: genes associated with inflammation were found almost exclusively in superficial airways, while genes related to airway remodeling were mainly present in endobronchial biopsy specimens. This enhanced gene profile was similar across multiple sample sizes – nasal brushing, sputum, endobronchial brushing – demonstrating the importance of eosinophilic inflammation, mast cell degranulation and group 3 innate lymphoid cells in severe adult-onset asthma. IL-13 is an immunoregulatory cytokine that is made mostly by activated T-helper 2 (Th2) cells. It is an important cytokine for many steps in B-cell maturation and differentiation, since it increases CD23 and MHC class II molecules, and aids in B-cell isotype switching to IgE. IL-13 also suppresses macrophage function by reducing the release of pro-inflammatory cytokines and chemokines. The more striking thing is that IL-13 is the prime mover in allergen-induced asthma via pathways that are independent of IgE and eosinophils.
=== Hygiene hypothesis ===
Allergic diseases are caused by inappropriate immunological responses to harmless antigens driven by a TH2-mediated immune response. Many bacteria and viruses elicit a TH1-mediated immune response, which down-regulates TH2 responses. The first proposed mechanism of action of the hygiene hypothesis was that insufficient stimulation of the TH1 arm of the immune system leads to an overactive TH2 arm, which in turn leads to allergic disease. In other words, individuals living in too sterile an environment are not exposed to enough pathogens to keep the immune system busy. Since our bodies evolved to deal with a certain level of such pathogens, when they are not exposed to this level, the immune system will attack harmless antigens, and thus normally benign microbial objects—like pollen—will trigger an immune response.
The hygiene hypothesis was developed to explain the observation that hay fever and eczema, both allergic diseases, were less common in children from larger families, which were, it is presumed, exposed to more infectious agents through their siblings, than in children from families with only one child. It is used to explain the increase in allergic diseases that have been seen since industrialization, and the higher incidence of allergic diseases in more developed countries. The hygiene hypothesis has now expanded to include exposure to symbiotic bacteria and parasites as important modulators of immune system development, along with infectious agents.
Epidemiological data support the hygiene hypothesis. Studies have shown that various immunological and autoimmune diseases are much less common in the developing world than the industrialized world, and that immigrants to the industrialized world from the developing world increasingly develop immunological disorders in relation to the length of time since arrival in the industrialized world. Longitudinal studies in the third world demonstrate an increase in immunological disorders as a country grows more affluent and, it is presumed, cleaner. The use of antibiotics in the first year of life has been linked to asthma and other allergic diseases. The use of antibacterial cleaning products has also been associated with higher incidence of asthma, as has birth by caesarean section rather than vaginal birth.
=== Stress ===
Chronic stress can aggravate allergic conditions. This has been attributed to a T helper 2 (TH2)-predominant response driven by suppression of interleukin 12 by both the autonomic nervous system and the hypothalamic–pituitary–adrenal axis. Stress management in highly susceptible individuals may improve symptoms.
=== Other environmental factors ===
Allergic diseases are more common in industrialized countries than in countries that are more traditional or agricultural, and there is a higher rate of allergic disease in urban populations versus rural populations, although these differences are becoming less defined. Historically, the trees planted in urban areas were predominantly male to prevent litter from seeds and fruits, but the high ratio of male trees causes high pollen counts, a phenomenon that horticulturist Tom Ogren has called "botanical sexism".
Alterations in exposure to microorganisms is another plausible explanation, at present, for the increase in atopic allergy. Endotoxin exposure reduces release of inflammatory cytokines such as TNF-α, IFNγ, interleukin-10, and interleukin-12 from white blood cells (leukocytes) that circulate in the blood. Certain microbe-sensing proteins, known as Toll-like receptors, found on the surface of cells in the body are also thought to be involved in these processes.
Parasitic worms and similar parasites are present in untreated drinking water in developing countries, and were present in the water of developed countries until the routine chlorination and purification of drinking water supplies. Recent research has shown that some common parasites, such as intestinal worms (e.g., hookworms), secrete chemicals into the gut wall (and, hence, the bloodstream) that suppress the immune system and prevent the body from attacking the parasite. This gives rise to a new slant on the hygiene hypothesis theory—that co-evolution of humans and parasites has led to an immune system that functions correctly only in the presence of the parasites. Without them, the immune system becomes unbalanced and oversensitive.
In particular, research suggests that allergies may coincide with the delayed establishment of gut flora in infants. However, the research to support this theory is conflicting, with some studies performed in China and Ethiopia showing an increase in allergy in people infected with intestinal worms. Clinical trials have been initiated to test the effectiveness of certain worms in treating some allergies. It may be that the term 'parasite' could turn out to be inappropriate, and in fact a hitherto unsuspected symbiosis is at work. For more information on this topic, see Helminthic therapy.
== Pathophysiology ==
=== Acute response ===
In the initial stages of allergy, a type I hypersensitivity reaction against an allergen encountered for the first time and presented by a professional antigen-presenting cell causes a response in a type of immune cell called a TH2 lymphocyte, a subset of T cells that produce a cytokine called interleukin-4 (IL-4). These TH2 cells interact with other lymphocytes called B cells, whose role is production of antibodies. Coupled with signals provided by IL-4, this interaction stimulates the B cell to begin production of a large amount of a particular type of antibody known as IgE. Secreted IgE circulates in the blood and binds to an IgE-specific receptor (a kind of Fc receptor called FcεRI) on the surface of other kinds of immune cells called mast cells and basophils, which are both involved in the acute inflammatory response. The IgE-coated cells, at this stage, are sensitized to the allergen.
If later exposure to the same allergen occurs, the allergen can bind to the IgE molecules held on the surface of the mast cells or basophils. Cross-linking of the IgE and Fc receptors occurs when more than one IgE-receptor complex interacts with the same allergenic molecule and activates the sensitized cell. Activated mast cells and basophils undergo a process called degranulation, during which they release histamine and other inflammatory chemical mediators (cytokines, interleukins, leukotrienes, and prostaglandins) from their granules into the surrounding tissue causing several systemic effects, such as vasodilation, mucous secretion, nerve stimulation, and smooth muscle contraction.
This results in rhinorrhea, itchiness, dyspnea, and anaphylaxis. Depending on the individual, allergen, and mode of introduction, the symptoms can be system-wide (classical anaphylaxis) or localized to specific body systems. Asthma is localized to the respiratory system and eczema is localized to the dermis.
=== Late-phase response ===
After the chemical mediators of the acute response subside, late-phase responses can often occur. This is due to the migration of other leukocytes such as neutrophils, lymphocytes, eosinophils, and macrophages to the initial site. The reaction is usually seen 2–24 hours after the original reaction. Cytokines from mast cells may play a role in the persistence of long-term effects. Late-phase responses seen in asthma are slightly different from those seen in other allergic responses, although they are still caused by release of mediators from eosinophils and are still dependent on activity of TH2 cells.
=== Allergic contact dermatitis ===
Although allergic contact dermatitis is termed an "allergic" reaction (which usually refers to type I hypersensitivity), its pathophysiology involves a reaction that more correctly corresponds to a type IV hypersensitivity reaction. In type IV hypersensitivity, there is activation of certain types of T cells (CD8+) that destroy target cells on contact, as well as activated macrophages that produce hydrolytic enzymes.
== Diagnosis ==
Effective management of allergic diseases relies on the ability to make an accurate diagnosis. Allergy testing can help confirm or rule out allergies. Correct diagnosis, counseling, and avoidance advice based on valid allergy test results reduce the incidence of symptoms and need for medications, and improve quality of life. To assess the presence of allergen-specific IgE antibodies, two different methods can be used: a skin prick test, or an allergy blood test. Both methods are recommended, and they have similar diagnostic value.
Skin prick tests and blood tests are equally cost-effective, and health economic evidence shows that both tests were cost-effective compared with no test. Early and more accurate diagnoses save cost due to reduced consultations, referrals to secondary care, misdiagnosis, and emergency admissions.
Allergy undergoes dynamic changes over time. Regular allergy testing of relevant allergens provides information on if and how patient management can be changed to improve health and quality of life. Annual testing is often the practice for determining whether allergy to milk, egg, soy, and wheat have been outgrown, and the testing interval is extended to 2–3 years for allergy to peanut, tree nuts, fish, and crustacean shellfish. Results of follow-up testing can guide decision-making regarding whether and when it is safe to introduce or re-introduce allergenic food into the diet.
=== Skin prick testing ===
Skin testing is also known as "puncture testing" and "prick testing" due to the series of tiny punctures or pricks made into the patient's skin. Tiny amounts of suspected allergens and/or their extracts (e.g., pollen, grass, mite proteins, peanut extract) are introduced to sites on the skin marked with pen or dye (the ink/dye should be carefully selected, lest it cause an allergic response itself). A negative and positive control are also included for comparison (eg, negative is saline or glycerin; positive is histamine). A small plastic or metal device is used to puncture or prick the skin. Sometimes, the allergens are injected "intradermally" into the patient's skin, with a needle and syringe. Common areas for testing include the inside forearm and the back.
If the patient is allergic to the substance, then a visible inflammatory reaction will usually occur within 30 minutes. This response will range from slight reddening of the skin to a full-blown hive (called "wheal and flare") in more sensitive patients similar to a mosquito bite. Interpretation of the results of the skin prick test is normally done by allergists on a scale of severity, with +/− meaning borderline reactivity, and 4+ being a large reaction. Increasingly, allergists are measuring and recording the diameter of the wheal and flare reaction. Interpretation by well-trained allergists is often guided by relevant literature.
In general, a positive response is interpreted when the wheal of an antigen is ≥3mm larger than the wheal of the negative control (eg, saline or glycerin). Some patients may believe they have determined their own allergic sensitivity from observation, but a skin test has been shown to be much better than patient observation to detect allergy.
If a serious life-threatening anaphylactic reaction has brought a patient in for evaluation, some allergists will prefer an initial blood test prior to performing the skin prick test. Skin tests may not be an option if the patient has widespread skin disease or has taken antihistamines in the last several days.
=== Patch testing ===
Patch testing is a method used to determine if a specific substance causes allergic inflammation of the skin. It tests for delayed reactions. It is used to help ascertain the cause of skin contact allergy or contact dermatitis. Adhesive patches, usually treated with several common allergic chemicals or skin sensitizers, are applied to the back. The skin is then examined for possible local reactions at least twice, usually at 48 hours after application of the patch, and again two or three days later.
=== Blood testing ===
An allergy blood test is quick and simple and can be ordered by a licensed health care provider (e.g., an allergy specialist) or general practitioner. Unlike skin-prick testing, a blood test can be performed irrespective of age, skin condition, medication, symptom, disease activity, and pregnancy. Adults and children of any age can get an allergy blood test. For babies and very young children, a single needle stick for allergy blood testing is often gentler than several skin pricks.
An allergy blood test is available through most laboratories. A sample of the patient's blood is sent to a laboratory for analysis, and the results are sent back a few days later. Multiple allergens can be detected with a single blood sample. Allergy blood tests are very safe since the person is not exposed to any allergens during the testing procedure. After the onset of anaphylaxis or a severe allergic reaction, guidelines recommend emergency departments obtain a time-sensitive blood test to determine blood tryptase levels and assess for mast cell activation.
The test measures the concentration of specific IgE antibodies in the blood. Quantitative IgE test results increase the possibility of ranking how different substances may affect symptoms. A rule of thumb is that the higher the IgE antibody value, the greater the likelihood of symptoms. Allergens found at low levels that today do not result in symptoms cannot help predict future symptom development. The quantitative allergy blood result can help determine what a patient is allergic to, help predict and follow the disease development, estimate the risk of a severe reaction, and explain cross-reactivity.
A low total IgE level is not adequate to rule out sensitization to commonly inhaled allergens. Statistical methods, such as ROC curves, predictive value calculations, and likelihood ratios have been used to examine the relationship of various testing methods to each other. These methods have shown that patients with a high total IgE have a high probability of allergic sensitization, but further investigation with allergy tests for specific IgE antibodies for a carefully chosen of allergens is often warranted.
Laboratory methods to measure specific IgE antibodies for allergy testing include enzyme-linked immunosorbent assay (ELISA, or EIA), radioallergosorbent test (RAST), fluorescent enzyme immunoassay (FEIA), and chemiluminescence immunoassay (CLIA).
=== Other testing ===
Challenge testing: Challenge testing is when tiny amounts of a suspected allergen are introduced to the body orally, through inhalation, or via other routes. Except for testing food and medication allergies, challenges are rarely performed. When this type of testing is chosen, it must be closely supervised by an allergist.
Elimination/challenge tests: This testing method is used most often with foods or medicines. A patient with a suspected allergen is instructed to modify his diet to totally avoid that allergen for a set time. If the patient experiences significant improvement, he may then be "challenged" by reintroducing the allergen, to see if symptoms are reproduced.
Unreliable tests: There are other types of allergy testing methods that are unreliable, including applied kinesiology (allergy testing through muscle relaxation), cytotoxicity testing, urine autoinjection, skin titration (Rinkel method), and provocative and neutralization (subcutaneous) testing or sublingual provocation.
=== Differential diagnosis ===
Before a diagnosis of allergic disease can be confirmed, other plausible causes of the presenting symptoms must be considered. Vasomotor rhinitis, for example, is one of many illnesses that share symptoms with allergic rhinitis, underscoring the need for professional differential diagnosis. Once a diagnosis of asthma, rhinitis, anaphylaxis, or other allergic disease has been made, there are several methods for discovering the causative agent of that allergy.
== Prevention ==
Giving peanut products early in childhood may decrease the risk of allergies, and only breastfeeding during at least the first few months of life may decrease the risk of allergic dermatitis. There is little evidence that a mother's diet during pregnancy or breastfeeding affects the risk of allergies, although there has been some research to show that irregular cow's milk exposure might increase the risk of cow's milk allergy. There is some evidence that delayed introduction of certain foods is useful, and that early exposure to potential allergens may actually be protective.
Fish oil supplementation during pregnancy is associated with a lower risk of food sensitivities. Probiotic supplements during pregnancy or infancy may help to prevent atopic dermatitis.
== Management ==
Management of allergies typically involves avoiding the allergy trigger and taking medications to improve the symptoms. Allergen immunotherapy may be useful for some types of allergies.
=== Medication ===
Several medications may be used to block the action of allergic mediators, or to prevent activation of cells and degranulation processes. These include antihistamines, glucocorticoids, epinephrine (adrenaline), mast cell stabilizers, and antileukotriene agents are common treatments of allergic diseases. Anticholinergics, decongestants, and other compounds thought to impair eosinophil chemotaxis are also commonly used. Although rare, the severity of anaphylaxis often requires epinephrine injection, and where medical care is unavailable, a device known as an epinephrine autoinjector may be used.
=== Immunotherapy ===
Allergen immunotherapy is useful for environmental allergies, allergies to insect bites, and asthma. Its benefit for food allergies is unclear and thus not recommended. Immunotherapy involves exposing people to larger and larger amounts of allergen in an effort to change the immune system's response.
Meta-analyses have found that injections of allergens under the skin is effective in the treatment in allergic rhinitis in children and in asthma. The benefits may last for years after treatment is stopped. It is generally safe and effective for allergic rhinitis and conjunctivitis, allergic forms of asthma, and stinging insects.
To a lesser extent, the evidence also supports the use of sublingual immunotherapy for rhinitis and asthma. For seasonal allergies the benefit is small. In this form the allergen is given under the tongue and people often prefer it to injections. Immunotherapy is not recommended as a stand-alone treatment for asthma.
=== Alternative medicine ===
An experimental treatment, enzyme potentiated desensitization (EPD), has been tried for decades but is not generally accepted as effective. EPD uses dilutions of allergen and an enzyme, beta-glucuronidase, to which T-regulatory lymphocytes are supposed to respond by favoring desensitization, or down-regulation, rather than sensitization. EPD has also been tried for the treatment of autoimmune diseases, but evidence does not show effectiveness.
A review found no effectiveness of homeopathic treatments and no difference compared with placebo. The authors concluded that based on rigorous clinical trials of all types of homeopathy for childhood and adolescence ailments, there is no convincing evidence that supports the use of homeopathic treatments.
According to the National Center for Complementary and Integrative Health, U.S., the evidence is relatively strong that saline nasal irrigation and butterbur are effective, when compared to other alternative medicine treatments, for which the scientific evidence is weak, negative, or nonexistent, such as honey, acupuncture, omega 3's, probiotics, astragalus, capsaicin, grape seed extract, Pycnogenol, quercetin, spirulina, stinging nettle, tinospora, or guduchi.
== Epidemiology ==
The allergic diseases—hay fever and asthma—have increased in the Western world over the past 2–3 decades. Increases in allergic asthma and other atopic disorders in industrialized nations, it is estimated, began in the 1960s and 1970s, with further increases occurring during the 1980s and 1990s, although some suggest that a steady rise in sensitization has been occurring since the 1920s. The number of new cases per year of atopy in developing countries has, in general, remained much lower.
=== Changing frequency ===
Although genetic factors govern susceptibility to atopic disease, increases in atopy have occurred within too short a period to be explained by a genetic change in the population, thus pointing to environmental or lifestyle changes. Several hypotheses have been identified to explain this increased rate. Increased exposure to perennial allergens may be due to housing changes and increased time spent indoors, and a decreased activation of a common immune control mechanism may be caused by changes in cleanliness or hygiene, and exacerbated by dietary changes, obesity, and decline in physical exercise. The hygiene hypothesis maintains that high living standards and hygienic conditions exposes children to fewer infections. It is thought that reduced bacterial and viral infections early in life direct the maturing immune system away from TH1 type responses, leading to unrestrained TH2 responses that allow for an increase in allergy.
Changes in rates and types of infection alone, however, have been unable to explain the observed increase in allergic disease, and recent evidence has focused attention on the importance of the gastrointestinal microbial environment. Evidence has shown that exposure to food and fecal-oral pathogens, such as hepatitis A, Toxoplasma gondii, and Helicobacter pylori (which also tend to be more prevalent in developing countries), can reduce the overall risk of atopy by more than 60%, and an increased rate of parasitic infections has been associated with a decreased prevalence of asthma. It is speculated that these infections exert their effect by critically altering TH1/TH2 regulation. Important elements of newer hygiene hypotheses also include exposure to endotoxins, exposure to pets and growing up on a farm.
== History ==
Some symptoms attributable to allergic diseases are mentioned in ancient sources. Particularly, three members of the Roman Julio-Claudian dynasty (Augustus, Claudius and Britannicus) are suspected to have a family history of atopy. The concept of "allergy" was originally introduced in 1906 by the Viennese pediatrician Clemens von Pirquet, after he noticed that patients who had received injections of horse serum or smallpox vaccine usually had quicker, more severe reactions to second injections. Pirquet called this phenomenon "allergy" from the Ancient Greek words ἄλλος allos meaning "other" and ἔργον ergon meaning "work".
All forms of hypersensitivity used to be classified as allergies, and all were thought to be caused by an improper activation of the immune system. Later, it became clear that several different disease mechanisms were implicated, with a common link to a disordered activation of the immune system. In 1963, a new classification scheme was designed by Philip Gell and Robin Coombs that described four types of hypersensitivity reactions, known as Type I to Type IV hypersensitivity.
With this new classification, the word allergy, sometimes clarified as a true allergy, was restricted to type I hypersensitivities (also called immediate hypersensitivity), which are characterized as rapidly developing reactions involving IgE antibodies.
A major breakthrough in understanding the mechanisms of allergy was the discovery of the antibody class labeled immunoglobulin E (IgE). IgE was simultaneously discovered in 1966–67 by two independent groups: Ishizaka's team at the Children's Asthma Research Institute and Hospital in Denver, USA, and by Gunnar Johansson and Hans Bennich in Uppsala, Sweden. Their joint paper was published in April 1969.
=== Diagnosis ===
Radiometric assays include the radioallergosorbent test (RAST test) method, which uses IgE-binding (anti-IgE) antibodies labeled with radioactive isotopes for quantifying the levels of IgE antibody in the blood.
The RAST methodology was invented and marketed in 1974 by Pharmacia Diagnostics AB, Uppsala, Sweden, and the acronym RAST is actually a brand name. In 1989, Pharmacia Diagnostics AB replaced it with a superior test named the ImmunoCAP Specific IgE blood test, which uses the newer fluorescence-labeled technology.
American College of Allergy Asthma and Immunology (ACAAI) and the American Academy of Allergy Asthma and Immunology (AAAAI) issued the Joint Task Force Report "Pearls and pitfalls of allergy diagnostic testing" in 2008, and is firm in its statement that the term RAST is now obsolete:
The term RAST became a colloquialism for all varieties of (in vitro allergy) tests. This is unfortunate because it is well recognized that there are well-performing tests and some that do not perform so well, yet they are all called RASTs, making it difficult to distinguish which is which. For these reasons, it is now recommended that use of RAST as a generic descriptor of these tests be abandoned.
The updated version, the ImmunoCAP Specific IgE blood test, is the only specific IgE assay to receive Food and Drug Administration approval to quantitatively report to its detection limit of 0.1kU/L.
== Medical specialty ==
The medical speciality that studies, diagnoses and treats diseases caused by allergies is called allergology.
An allergist is a physician specially trained to manage and treat allergies, asthma, and the other allergic diseases. In the United States physicians holding certification by the American Board of Allergy and Immunology (ABAI) have successfully completed an accredited educational program and evaluation process, including a proctored examination to demonstrate knowledge, skills, and experience in patient care in allergy and immunology. Becoming an allergist/immunologist requires completion of at least nine years of training.
After completing medical school and graduating with a medical degree, a physician will undergo three years of training in internal medicine (to become an internist) or pediatrics (to become a pediatrician). Once physicians have finished training in one of these specialties, they must pass the exam of either the American Board of Pediatrics (ABP), the American Osteopathic Board of Pediatrics (AOBP), the American Board of Internal Medicine (ABIM), or the American Osteopathic Board of Internal Medicine (AOBIM). Internists or pediatricians wishing to focus on the sub-specialty of allergy-immunology then complete at least an additional two years of study, called a fellowship, in an allergy/immunology training program. Allergist/immunologists listed as ABAI-certified have successfully passed the certifying examination of the ABAI following their fellowship.
In the United Kingdom, allergy is a subspecialty of general medicine or pediatrics. After obtaining postgraduate exams (MRCP or MRCPCH), a doctor works for several years as a specialist registrar before qualifying for the General Medical Council specialist register. Allergy services may also be delivered by immunologists. A 2003 Royal College of Physicians report presented a case for improvement of what were felt to be inadequate allergy services in the UK.
In 2006, the House of Lords convened a subcommittee. It concluded likewise in 2007 that allergy services were insufficient to deal with what the Lords referred to as an "allergy epidemic" and its social cost; it made several recommendations.
== Research ==
Low-allergen foods are being developed, as are improvements in skin prick test predictions; evaluation of the atopy patch test, wasp sting outcomes predictions, a rapidly disintegrating epinephrine tablet, and anti-IL-5 for eosinophilic diseases.
== See also ==
Allergic shiner
GWAS in allergy
Histamine intolerance
List of allergens
Oral allergy syndrome
== References ==
== External links ==
Media related to Allergies at Wikimedia Commons
Allergy travel guide from Wikivoyage
"Allergy". MedlinePlus. U.S. National Library of Medicine. | Wikipedia/Protein_allergy |
In molecular biology, an intrinsically disordered protein (IDP) is a protein that lacks a fixed or ordered three-dimensional structure, typically in the absence of its macromolecular interaction partners, such as other proteins or RNA. IDPs range from fully unstructured to partially structured and include random coil, molten globule-like aggregates, or flexible linkers in large multi-domain proteins. They are sometimes considered as a separate class of proteins along with globular, fibrous and membrane proteins.
IDPs are a very large and functionally important class of proteins. They are most numerous in eukaryotes, with an estimated 30-40% of residues in the eukaryotic proteome located in disordered regions. Disorder is present in around 70% of proteins, either in the form of disordered tails or flexible linkers. Proteins can also be entirely disordered and lack a defined secondary and/or tertiary structure. Their discovery has disproved the idea that three-dimensional structures of proteins must be fixed to accomplish their biological functions. For example, IDPs have been identified to participate in weak multivalent interactions that are highly cooperative and dynamic, lending them importance in DNA regulation and in cell signaling. Many IDPs can also adopt a fixed three-dimensional structure after binding to other macromolecules. Overall, IDPs are different from structured proteins in many ways and tend to have distinctive function, structure, sequence, interactions, evolution and regulation.
== History ==
In the 1930s-1950s, the first protein structures were solved by protein crystallography. These early structures suggested that a fixed three-dimensional structure might be generally required to mediate biological functions of proteins. These publications solidified the central dogma of molecular biology in that the amino acid sequence of a protein determines its structure which, in turn, determines its function. In 1950, Karush wrote about 'Configurational Adaptability' contradicting this assumption. He was convinced that proteins have more than one configuration at the same energy level and can choose one when binding to other substrates. In the 1960s, Levinthal's paradox suggested that the systematic conformational search of a long polypeptide is unlikely to yield a single folded protein structure on biologically relevant timescales (i.e. microseconds to minutes). Curiously, for many (small) proteins or protein domains, relatively rapid and efficient refolding can be observed in vitro. As stated in Anfinsen's Dogma from 1973, the fixed 3D structure of these proteins is uniquely encoded in its primary structure (the amino acid sequence), is kinetically accessible and stable under a range of (near) physiological conditions, and can therefore be considered as the native state of such "ordered" proteins.
During the subsequent decades, however, many large protein regions could not be assigned in x-ray datasets, indicating that they occupy multiple positions, which average out in electron density maps. The lack of fixed, unique positions relative to the crystal lattice suggested that these regions were "disordered". Nuclear magnetic resonance spectroscopy of proteins also demonstrated the presence of large flexible linkers and termini in many solved structural ensembles.
In 2001, Dunker questioned whether the newly found information was ignored for 50 years with more quantitative analyses becoming available in the 2000s. In the 2010s it became clear that IDPs are common among disease-related proteins, such as alpha-synuclein and tau.
== Abundance ==
It is now generally accepted that proteins exist as an ensemble of similar structures with some regions more constrained than others. IDPs occupy the extreme end of this spectrum of flexibility and include proteins of considerable local structure tendency or flexible multidomain assemblies.
Intrinsic disorder is particularly elevated among proteins that regulate chromatin and transcription, and bioinformatic predictions indicate that is more common in genomes and proteomes than in known structures in the protein database. Based on DISOPRED2 prediction, long (>30 residue) disordered segments occur in 2.0% of archaean, 4.2% of eubacterial and 33.0% of eukaryotic proteins, including certain disease-related proteins.
== Biological roles ==
Highly dynamic disordered regions of proteins have been linked to functionally important phenomena such as allosteric regulation and enzyme catalysis. Many disordered proteins have the binding affinity with their receptors regulated by post-translational modification, thus it has been proposed that the flexibility of disordered proteins facilitates the different conformational requirements for binding the modifying enzymes as well as their receptors. Intrinsic disorder is particularly enriched in proteins implicated in cell signaling and transcription, as well as chromatin remodeling functions. Genes that have recently been born de novo tend to have higher disorder. In animals, genes with high disorder are lost at higher rates during evolution.
=== Flexible linkers ===
Disordered regions are often found as flexible linkers or loops connecting domains. Linker sequences vary greatly in length but are typically rich in polar uncharged amino acids. Flexible linkers allow the connecting domains to freely twist and rotate to recruit their binding partners via protein domain dynamics. They also allow their binding partners to induce larger scale conformational changes by long-range allostery. The flexible linker of FBP25 which connects two domains of FKBP25 is important for the binding of FKBP25 with DNA.
=== Linear motifs ===
Linear motifs are short disordered segments of proteins that mediate functional interactions with other proteins or other biomolecules (RNA, DNA, sugars etc.). Many roles of linear motifs are associated with cell regulation, for instance in control of cell shape, subcellular localisation of individual proteins and regulated protein turnover. Often, post-translational modifications such as phosphorylation tune the affinity (not rarely by several orders of magnitude) of individual linear motifs for specific interactions. Relatively rapid evolution and a relatively small number of structural restraints for establishing novel (low-affinity) interfaces make it particularly challenging to detect linear motifs but their widespread biological roles and the fact that many viruses mimick/hijack linear motifs to efficiently recode infected cells underlines the timely urgency of research on this very challenging and exciting topic.
=== Pre-structured motifs ===
Unlike globular proteins, IDPs do not have spatially-disposed active pockets. Fascinatingly, 80% of target-unbound IDPs (~4 dozens) subjected to detailed structural characterization by NMR possess linear motifs termed PresMos (pre-structured motifs) that are transient secondary structural elements primed for target recognition. In several cases it has been demonstrated that these transient structures become full and stable secondary structures, e.g., helices, upon target binding. Hence, PresMos are the putative active sites in IDPs.
=== Coupled folding and binding ===
Many unstructured proteins undergo transitions to more ordered states upon binding to their targets (e.g. molecular recognition features (MoRFs)). The coupled folding and binding may be local, involving only a few interacting residues, or it might involve an entire protein domain. It was recently shown that the coupled folding and binding allows the burial of a large surface area that would be possible only for fully structured proteins if they were much larger. Moreover, certain disordered regions might serve as "molecular switches" in regulating certain biological function by switching to ordered conformation upon molecular recognition like small molecule-binding, DNA/RNA binding, ion interactions etc.
The ability of disordered proteins to bind, and thus to exert a function, shows that stability is not a required condition. Many short functional sites, for example short linear motifs are over-represented in disordered proteins. Disordered proteins and short linear motifs are particularly abundant in many RNA viruses such as Hendra virus, HCV, HIV-1 and human papillomaviruses. This enables such viruses to overcome their informationally limited genomes by facilitating binding, and manipulation of, a large number of host cell proteins.
=== Disorder in the bound state (fuzzy complexes) ===
Intrinsically disordered proteins can retain their conformational freedom even when they bind specifically to other proteins. The structural disorder in bound state can be static or dynamic. In fuzzy complexes structural multiplicity is required for function and the manipulation of the bound disordered region changes activity. The conformational ensemble of the complex is modulated via post-translational modifications or protein interactions. Specificity of DNA binding proteins often depends on the length of fuzzy regions, which is varied by alternative splicing. Some fuzzy complexes may exhibit high binding affinity, although other studies showed different affinity values for the same system in a different concentration regime.
== Structural aspects ==
Intrinsically disordered proteins adapt a dynamic range of rapidly interchanging conformations in vivo according to the cell's conditions, creating a structural or conformational ensemble.
Therefore, their structures are strongly function-related. However, only few proteins are fully disordered in their native state. Disorder is mostly found in intrinsically disordered regions (IDRs) within an otherwise well-structured protein. The term intrinsically disordered protein (IDP) therefore includes proteins that contain IDRs as well as fully disordered proteins.
The existence and kind of protein disorder is encoded in its amino acid sequence. In general, IDPs are characterized by a low content of bulky hydrophobic amino acids and a high proportion of polar and charged amino acids, usually referred to as low hydrophobicity. This property leads to good interactions with water. Furthermore, high net charges promote disorder because of electrostatic repulsion resulting from equally charged residues. Thus disordered sequences cannot sufficiently bury a hydrophobic core to fold into stable globular proteins. In some cases, hydrophobic clusters in disordered sequences provide the clues for identifying the regions that undergo coupled folding and binding (refer to biological roles). Many disordered proteins reveal regions without any regular secondary structure. These regions can be termed as flexible, compared to structured loops. While the latter are rigid and contain only one set of Ramachandran angles, IDPs involve multiple sets of angles. The term flexibility is also used for well-structured proteins, but describes a different phenomenon in the context of disordered proteins. Flexibility in structured proteins is bound to an equilibrium state, while it is not so in IDPs. Many disordered proteins also reveal low complexity sequences, i.e. sequences with over-representation of a few residues. While low complexity sequences are a strong indication of disorder, the reverse is not necessarily true, that is, not all disordered proteins have low complexity sequences. Disordered proteins have a low content of predicted secondary structure.
Due to the disordered nature of these proteins, topological approaches have been developed to search for conformational patterns in their dynamics. For instance, circuit topology has been applied to track the dynamics of disordered protein domains. By employing a topological approach, one can categorize motifs according to their topological buildup and the timescale of their formation.
A common aspect of IDP structural ensembles is the ability or tendency to fold upon an interaction to a binding partner in the cell. Examples of IDP folding in a binding context are binding-coupled folding, and formation of fuzzy complexes. However, it is also possible for proteins to remain entirely disordered in a binding scenario.
== Experimental validation ==
IDPs can be validated in several contexts. Most approaches for experimental validation of IDPs are restricted to extracted or purified proteins while some new experimental strategies aim to explore in vivo conformations and structural variations of IDPs inside intact living cells and systematic comparisons between their dynamics in vivo and in vitro.
=== In vivo approaches ===
The first direct evidence for in vivo persistence of intrinsic disorder has been achieved by in-cell NMR upon electroporation of a purified IDP and recovery of cells to an intact state.
Larger-scale in vivo validation of IDR predictions is now possible using biotin 'painting'.
=== In vitro approaches ===
Intrinsically unfolded proteins, once purified, can be identified by various experimental methods. The primary method to obtain information on disordered regions of a protein is NMR spectroscopy. The lack of electron density in X-ray crystallographic studies may also be a sign of disorder.
Folded proteins have a high density (partial specific volume of 0.72-0.74 mL/g) and commensurately small radius of gyration. Hence, unfolded proteins can be detected by methods that are sensitive to molecular size, density or hydrodynamic drag, such as size exclusion chromatography, analytical ultracentrifugation, small angle X-ray scattering (SAXS), and measurements of the diffusion constant. Unfolded proteins are also characterized by their lack of secondary structure, as assessed by far-UV (170–250 nm) circular dichroism (esp. a pronounced minimum at ~200 nm) or infrared spectroscopy. Unfolded proteins also have exposed backbone peptide groups exposed to solvent, so that they are readily cleaved by proteases, undergo rapid hydrogen-deuterium exchange and exhibit a small dispersion (<1 ppm) in their 1H amide chemical shifts as measured by NMR. (Folded proteins typically show dispersions as large as 5 ppm for the amide protons.) Recently, new methods including fast parallel proteolysis (FASTpp) have been introduced, which allow to determine the fraction folded/disordered without the need for purification. Even subtle differences in the stability of missense mutations, protein partner binding and (self)polymerisation-induced folding of (e.g.) coiled-coils can be detected using FASTpp as recently demonstrated using the tropomyosin-troponin protein interaction. Fully unstructured protein regions can be experimentally validated by their hypersusceptibility to proteolysis using short digestion times and low protease concentrations.
Bulk methods to study IDP structure and dynamics include SAXS for ensemble shape information, NMR for atomistic ensemble refinement, fluorescence for visualising molecular interactions and conformational transitions, x-ray crystallography to highlight more mobile regions in otherwise rigid protein crystals, cryo-EM to reveal less fixed parts of proteins, light scattering to monitor size distributions of IDPs or their aggregation kinetics, NMR chemical shift and circular dichroism to monitor secondary structure of IDPs.
Single-molecule methods to study IDPs include spFRET to study conformational flexibility of IDPs and the kinetics of structural transitions, optical tweezers for high-resolution insights into the ensembles of IDPs and their oligomers or aggregates, nanopores to reveal global shape distributions of IDPs, magnetic tweezers to study structural transitions for long times at low forces, high-speed atomic force microscopy (AFM) to visualise the spatio-temporal flexibility of IDPs directly.
== Disorder annotation ==
Intrinsic disorder can be either annotated from experimental information or predicted with specialized software. Disorder prediction algorithms can predict intrinsic disorder (ID) propensity with high accuracy (approaching around 80%) based on primary sequence composition, similarity to unassigned segments in protein x-ray datasets, flexible regions in NMR studies and physico-chemical properties of amino acids.
=== Disorder databases ===
Databases have been established to annotate protein sequences with intrinsic disorder information. The DisProt database contains a collection of manually curated protein segments which have been experimentally determined to be disordered. MobiDB is a database combining experimentally curated disorder annotations (e.g. from DisProt) with data derived from missing residues in X-ray crystallographic structures and flexible regions in NMR structures.
=== Predicting IDPs by sequence ===
Separating disordered from ordered proteins is essential for disorder prediction. One of the first steps to find a factor that distinguishes IDPs from non-IDPs is to specify biases within the amino acid composition. The following hydrophilic, charged amino acids A, R, G, Q, S, P, E and K have been characterized as disorder-promoting amino acids, while order-promoting amino acids W, C, F, I, Y, V, L, and N are hydrophobic and uncharged. The remaining amino acids H, M, T and D are ambiguous, found in both ordered and unstructured regions. A more recent analysis ranked amino acids by their propensity to form disordered regions as follows (order promoting to disorder promoting): W, F, Y, I, M, L, V, N, C, T, A, G, R, D, H, Q, K, S, E, P. As it can be seen from the list, small, charged, hydrophilic residues often promote disorder, while large and hydrophobic residues promote order.
This information is the basis of most sequence-based predictors. Regions with little to no secondary structure, also known as NORS (no regular secondary structure) regions, and low-complexity regions can easily be detected. However, not all disordered proteins contain such low complexity sequences.
=== Prediction methods ===
Determining disordered regions from biochemical methods is very costly and time-consuming. Due to the variable nature of IDPs, only certain aspects of their structure can be detected, so that a full characterization requires a large number of different methods and experiments. This further increases the expense of IDP determination. In order to overcome this obstacle, computer-based methods are created for predicting protein structure and function. It is one of the main goals of bioinformatics to derive knowledge by prediction. Predictors for IDP function are also being developed, but mainly use structural information such as linear motif sites. There are different approaches for predicting IDP structure, such as neural networks or matrix calculations, based on different structural and/or biophysical properties.
Many computational methods exploit sequence information to predict whether a protein is disordered. Notable examples of such software include IUPRED and Disopred. Different methods may use different definitions of disorder. Meta-predictors show a new concept, combining different primary predictors to create a more competent and exact predictor.
Due to the different approaches of predicting disordered proteins, estimating their relative accuracy is fairly difficult. For example, neural networks are often trained on different datasets. The disorder prediction category is a part of biannual CASP experiment that is designed to test methods according accuracy in finding regions with missing 3D structure (marked in PDB files as REMARK465, missing electron densities in X-ray structures).
== Disorder and disease ==
Intrinsically unstructured proteins have been implicated in a number of diseases. Aggregation of misfolded proteins is the cause of many synucleinopathies and toxicity as those proteins start binding to each other randomly and can lead to cancer or cardiovascular diseases. Thereby, misfolding can happen spontaneously because millions of copies of proteins are made during the lifetime of an organism. The aggregation of the intrinsically unstructured protein α-synuclein is thought to be responsible. The structural flexibility of this protein together with its susceptibility to modification in the cell leads to misfolding and aggregation. Genetics, oxidative and nitrative stress as well as mitochondrial impairment impact the structural flexibility of the unstructured α-synuclein protein and associated disease mechanisms. Many key tumour suppressors have large intrinsically unstructured regions, for example p53 and BRCA1. These regions of the proteins are responsible for mediating many of their interactions. Taking the cell's native defense mechanisms as a model drugs can be developed, trying to block the place of noxious substrates and inhibiting them, and thus counteracting the disease.
== Computer simulations ==
Owing to high structural heterogeneity, NMR/SAXS experimental parameters obtained will be an average over a large number of highly diverse and disordered states (an ensemble of disordered states). Hence, to understand the structural implications of these experimental parameters, there is a necessity for accurate representation of these ensembles by computer simulations. All-atom molecular dynamic simulations can be used for this purpose but their use is limited by the accuracy of current force-fields in representing disordered proteins. Nevertheless, some force-fields have been explicitly developed for studying disordered proteins by optimising force-field parameters using available NMR data for disordered proteins. (examples are CHARMM 22*, CHARMM 32, Amber ff03* etc.)
MD simulations restrained by experimental parameters (restrained-MD) have also been used to characterise disordered proteins. In principle, one can sample the whole conformational space given an MD simulation (with accurate Force-field) is run long enough. Because of very high structural heterogeneity, the time scales that needs to be run for this purpose are very large and are limited by computational power. However, other computational techniques such as accelerated-MD simulations, replica exchange simulations, metadynamics, multicanonical MD simulations, or methods using coarse-grained representation with implicit and explicit solvents have been used to sample broader conformational space in smaller time scales.
Moreover, various protocols and methods of analyzing IDPs, such as studies based on quantitative analysis of GC content in genes and their respective chromosomal bands, have been used to understand functional IDP segments.
== See also ==
IDPbyNMR
DisProt database
MobiDB database
Molten globule
Prion
Random coil
Dark proteome
== References ==
== External links ==
Intrinsically disordered protein at Proteopedia
MobiDB: a comprehensive database of intrinsic protein disorder annotations
IDEAL - Intrinsically Disordered proteins with Extensive Annotations and Literature Archived 2020-05-02 at the Wayback Machine
D2P2 Database of Disordered Protein Predictions
Gallery of images of intrinsically disordered proteins
First IDP journal covering all topics of IDP research
IDP Journal
Database of experimentally validated IDPs
IDP ensemble database Archived 2018-03-10 at the Wayback Machine | Wikipedia/Intrinsically_unstructured_proteins |
Heat shock protein 47, also known as SERPINH1 is a serpin which serves as a human chaperone protein for collagen.
== Function ==
This protein is a member of the serpin superfamily of serine proteinase inhibitors. Its expression is induced by heat shock. HSP47 is expressed in the endoplasmic reticulum. These cells synthesize and secrete type I and type II collagen. The protein localizes to the endoplasmic reticulum lumen and binds collagen; thus it is thought to be a molecular chaperone involved in the maturation of collagen molecules. HSP47 is essential for the correct folding of procollagen. Antibodies directed to this protein have been found in patients with rheumatoid arthritis.
== Structure ==
HSP47 contains 3 beta sheets and 9 alpha helices. After binding with collagen no conformation change is observed.
== Interactions ==
Heat shock protein 47 has been shown to interact with collagens I, II, III, IV and V. It is involved in the secretion of collagen as well as the processing, assembly, and folding of collagen proteins. Hsp 47 binds specifically to procollagen and collagen only. The protein recognizes the triple helix of procollagen, two HSP47 proteins will bind to the leading and trailing strands of procollagen.
== Research on role in preventing deep vein thrombosis ==
Research published in 2023 indicates a potential role of HSP47 regarding deep vein thrombosis. This initial research will be followed by additional studies.
== Role in Fibrosis ==
Fibrosis is the scarring of connective tissue, one attribute is the excess deposition of collagen in the extracellular matrix of tissue. Research has shown that HSPs have a role in fibrotic diseases. HSP47 has been shown to be pro-fibrosis in various fibrotic diseases. During the process of fibrosis, HSP47 is expressed and is involved in the production of collagen. HSP47 could be a potential therapeutic agent for fibrotic disease, a down-regulation of HSP47 leads to decreased fibrotic progression.
== References ==
== Further reading ==
== External links ==
The MEROPS online database for peptidases and their inhibitors: I04.035 Archived 2012-12-23 at archive.today
HSP47+Heat-Shock+Proteins at the U.S. National Library of Medicine Medical Subject Headings (MeSH) | Wikipedia/Heat_shock_protein_47 |
DnaJ homolog subfamily A member 2 is a protein that in humans is encoded by the DNAJA2 gene.
The protein encoded by this gene shares sequence similarity with Hir1p and Hir2p, the two corepressors of histone gene transcription characterized in the yeast, Saccharomyces cerevisiae. The structural features of this protein suggest that it may function as part of a multiprotein complex. Several cDNAs encoding interacting proteins, HIRIPs, have been identified. HIRIP4 was isolated by virtue of its interaction with this protein; however, its exact function is not known. The sequence of HIRIP4 protein is highly homologous to the human DNJ3/CPR3, mouse Dj3 and rat Dj2 gene products.
== References ==
== Further reading ==
== External links ==
DNAJA2 human gene location in the UCSC Genome Browser.
DNAJA2 human gene details in the UCSC Genome Browser. | Wikipedia/DNAJA2 |
In evolutionary biology, sequence space is a way of representing all possible sequences (for a protein, gene or genome). The sequence space has one dimension per amino acid or nucleotide in the sequence leading to highly dimensional spaces.
Most sequences in sequence space have no function, leaving relatively small regions that are populated by naturally occurring genes. Each protein sequence is adjacent to all other sequences that can be reached through a single mutation. It has been estimated that the whole functional protein sequence space has been explored by life on the Earth. Evolution by natural selection can be visualised as the process of sampling nearby sequences in sequence space and moving to any with improved fitness over the current one.
== Representation ==
A sequence space is usually laid out as a grid. For protein sequence spaces, each residue in the protein is represented by a dimension with 20 possible positions along that axis corresponding to the possible amino acids. Hence there are 400 possible dipeptides arranged in a 20x20 space but that expands to 10130 for even a small protein of 100 amino acids arranged in a space with 100 dimensions. Although such overwhelming multidimensionality cannot be visualised or represented diagrammatically, it provides a useful abstract model to think about the range of proteins and evolution from one sequence to another.
These highly multidimensional spaces can be compressed to 2 or 3 dimensions using principal component analysis. A fitness landscape is simply a sequence space with an extra vertical axis of fitness added for each sequence.
== Functional sequences in sequence space ==
Despite the diversity of protein superfamilies, sequence space is extremely sparsely populated by functional proteins. Most random protein sequences have no fold or function. Enzyme superfamilies, therefore, exist as tiny clusters of active proteins in a vast empty space of non-functional sequence.
The density of functional proteins in sequence space, and the proximity of different functions to one another is a key determinant in understanding evolvability. The degree of interpenetration of two neutral networks of different activities in sequence space will determine how easy it is to evolve from one activity to another. The more overlap between different activities in sequence space, the more cryptic variation for promiscuous activity will be.
Protein sequence space has been compared to the Library of Babel, a theoretical library containing all possible books that are 410 pages long. In the Library of Babel, finding any book that made sense was impossible due to the sheer number and lack of order. The same would be true of protein sequences if it were not for natural selection, which has selected out only protein sequences that make sense. Additionally, each protein sequences is surrounded by a set of neighbours (point mutants) that are likely to have at least some function.
On the other hand, the effective "alphabet" of the sequence space may in fact be quite small, reducing the useful number of amino acids from 20 to a much lower number. For example, in an extremely simplified view, all amino acids can be sorted into two classes (hydrophobic/polar) by hydrophobicity and still allow many common structures to show up. Early life on Earth may have only four or five types of amino acids to work with, and researches have shown that functional proteins can be created from wild-type ones by a similar alphabet-reduction process. Reduced alphabets are also useful in bioinformatics, as they provide an easy way of analyzing protein similarity.
== Exploration through directed evolution and rational design ==
A major focus in the field of protein engineering is on creating DNA libraries that sample regions of sequence space, often with the goal of finding mutants of proteins with enhanced functions compared to the wild type. These libraries are created either by using a wild type sequence as a template and applying one or more mutagenesis techniques to make different variants of it, or by creating proteins from scratch using artificial gene synthesis. These libraries are then screened or selected, and ones with improved phenotypes are used for the next round of mutagenesis.
== See also ==
Protein
Sequence space
Directed evolution
Protein engineering
High-dimensional space
== References == | Wikipedia/Protein_sequence_space |
Reinforcement is a process of speciation where natural selection increases the reproductive isolation (further divided to pre-zygotic isolation and post-zygotic isolation) between two populations of species. This occurs as a result of selection acting against the production of hybrid individuals of low fitness. The idea was originally developed by Alfred Russel Wallace and is sometimes referred to as the Wallace effect. The modern concept of reinforcement originates from Theodosius Dobzhansky. He envisioned a species separated allopatrically, where during secondary contact the two populations mate, producing hybrids with lower fitness. Natural selection results from the hybrid's inability to produce viable offspring; thus members of one species who do not mate with members of the other have greater reproductive success. This favors the evolution of greater prezygotic isolation (differences in behavior or biology that inhibit formation of hybrid zygotes). Reinforcement is one of the few cases in which selection can favor an increase in prezygotic isolation, influencing the process of speciation directly. This aspect has been particularly appealing among evolutionary biologists.
The support for reinforcement has fluctuated since its inception, and terminological confusion and differences in usage over history have led to multiple meanings and complications. Various objections have been raised by evolutionary biologists as to the plausibility of its occurrence. Since the 1990s, data from theory, experiments, and nature have overcome many of the past objections, rendering reinforcement widely accepted,: 354 though its prevalence in nature remains unknown.
Numerous models have been developed to understand its operation in nature, most relying on several facets: genetics, population structures, influences of selection, and mating behaviors. Empirical support for reinforcement exists, both in the laboratory and in nature. Documented examples are found in a wide range of organisms: both vertebrates and invertebrates, fungi, and plants. The secondary contact of originally separated incipient species (the initial stage of speciation) is increasing due to human activities such as the introduction of invasive species or the modification of natural habitats. This has implications for measures of biodiversity and may become more relevant in the future.
== History ==
Reinforcement has had a complex history in that its popularity among scholars has changed over time. Jerry Coyne and H. Allen Orr contend that the theory of reinforcement went through three phases of historical development:: 366
plausibility based on unfit hybrids
implausibility based on hybrids having some fitness
plausibility based on empirical studies and biologically complex and realistic models
Sometimes called the Wallace effect, reinforcement was originally proposed by Alfred Russel Wallace in 1889.: 353 His hypothesis differed markedly from the modern conception in that it focused on post-zygotic isolation, strengthened by group selection.: 353 Theodosius Dobzhansky was the first to provide a thorough description of the process in 1937,: 353 though the term itself was not coined until 1955 by W. Frank Blair. In 1930, Ronald Fisher laid out the first genetic description of the process of reinforcement in The Genetical Theory of Natural Selection, and in 1965 and 1970 the first computer simulations were run to test for its plausibility.: 367 Later population genetic and quantitative genetic studies were conducted showing that completely unfit hybrids lead unequivocally to an increase in prezygotic isolation.: 367
Dobzhansky's idea gained significant support; he suggested that it illustrated the final step in speciation, for example after an allopatric population comes into secondary contact.: 353 In the 1980s, many evolutionary biologists began to doubt the plausibility of the idea,: 353 based not on empirical evidence, but largely on the growth of theory that deemed it an unlikely mechanism of reproductive isolation. A number of theoretical objections arose at the time and are addressed in the Arguments against reinforcement section below.
By the early 1990s, reinforcement saw a revival in popularity among evolutionary biologists; due primarily from a sudden increase in data—empirical evidence from studies in labs and largely by examples found in nature.: 354 Further, computer simulations of the genetics and migration patterns of populations found, "something looking like reinforcement".: 372 The most recent theoretical work on speciation has come from several studies (notably from Liou and Price, Kelly and Noor, and Kirkpatrick and Servedio) using highly complex computer simulations; all of which came to similar conclusions: that reinforcement is plausible under several conditions, and in many cases, is easier than previously thought.: 374
=== Terminology ===
Confusion exists around the meaning of the term reinforcement. It was first used to describe the observed mating call differences in Gastrophryne frogs within a secondary contact hybrid zone. The term secondary contact has also been used to describe reinforcement in the context of an allopatrically separated population experiencing contact after the loss of a geographic barrier. The Wallace effect is similar to reinforcement, but is rarely used. Roger Butlin demarcated incomplete post-zygotic isolation from complete isolation, referring to incomplete isolation as reinforcement and completely isolated populations as experiencing reproductive character displacement. Daniel J. Howard considered reproductive character displacement to represent either assortive mating or the divergence of traits for mate recognition (specifically between sympatric populations). Reinforcement, under his definition, included prezygotic divergence and complete post-zygotic isolation. Servedio and Noor include any detected increase in prezygotic isolation as reinforcement, as long as it is a response to selection against mating between two different species. Coyne and Orr contend that, "true reinforcement is restricted to cases in which isolation is enhanced between taxa that can still exchange genes".: 352
== Models ==
One of the strongest forms of reproductive isolation in nature is sexual isolation: traits in organisms involving mating. This pattern has led to the idea that, because selection acts so strongly on mating traits, it may be involved in the process of speciation. This process of speciation influenced by natural selection is reinforcement, and can happen under any mode of speciation: 355 (e.g. geographic modes of speciation or ecological speciation). It necessitates two forces of evolution that act on mate choice: natural selection and gene flow. Selection acts as the main driver of reinforcement as it selects against hybrid genotypes that are of low-fitness, regardless if individual preferences have no effect on survival and reproduction. Gene flow acts as the primary opposing force against reinforcement, as the exchange of genes between individuals leading to hybrids cause the genotypes to homogenize.
Butlin laid out four primary criteria for reinforcement to be detected in natural or laboratory populations:
Gene flow between two taxa exists or can be established to have existed at some point.
There is divergence of mating-associated traits between two taxa.
Patterns of mating are modified, limiting the production of low fitness hybrids.
Other selection pressures leading to divergence of the mate-recognition system have not occurred.
After speciation by reinforcement occurs, changes after complete reproductive isolation (and further isolation thereafter) are a form of reproductive character displacement. A common signature of reinforcement's occurrence in nature is that of reproductive character displacement; characteristics of a population diverge in sympatry but not allopatry. One difficulty in detection is that ecological character displacement can result in the same patterns. Further, gene flow can diminish the isolation found in sympatric populations. Two important factors in the outcome of the process rely on: 1) the specific mechanisms that causes prezygotic isolation, and 2) the number of alleles altered by mutations affecting mate choice.
In instances of peripatric speciation, reinforcement is unlikely to complete speciation in the case that the peripherally isolated population comes into secondary contact with the main population. In sympatric speciation, selection against hybrids is required; therefore reinforcement can play a role, given the evolution of some form of fitness trade-offs. In sympatry, patterns of strong mating discrimination are often observed—being attributed to reinforcement. Reinforcement is thought to be the agent of gametic isolation.
=== Genetics ===
The underlying genetics of reinforcement can be understood by an ideal model of two haploid populations experiencing an increase in linkage disequilibrium. Here, selection rejects low fitness
B
c
{\displaystyle Bc}
or
b
C
{\displaystyle bC}
allele combinations while favoring combinations of
B
C
{\displaystyle BC}
alleles (in the first subpopulation) and
b
c
{\displaystyle bc}
alleles (in the second subpopulation). The third locus
A
{\displaystyle A}
or
a
{\displaystyle a}
(the assortive mating alleles) have an effect on mating pattern but is not under direct selection. If selection at
B
{\displaystyle B}
and
C
{\displaystyle C}
cause changes in the frequency of allele
A
{\displaystyle A}
, assortive mating is promoted, resulting in reinforcement. Both selection and assortive mating are necessary, that is, that matings of
A
×
A
{\displaystyle A\times A}
and
a
×
a
{\displaystyle a\times a}
are more common than matings of
a
×
A
{\displaystyle a\times A}
and
A
×
a
{\displaystyle A\times a}
. A restriction of migration between populations can further increase the chance of reinforcement, as it decreases the probability of the differing genotypes to exchange.
An alternative model exists to address the antagonism of recombination, as it can reduce the association between the alleles that involve fitness and the assortive mating alleles that do not. Genetic models often differ in terms of the number of traits associated with loci; with some relying on one locus per trait and others on polygenic traits.
=== Population structures ===
The structure and migration patterns of a population can affect the process of speciation by reinforcement. It has been shown to occur under an island model, harboring conditions with infrequent migrations occurring in one direction, and in symmetric migration models where species migrate evenly back and forth between populations.
Reinforcement can also occur in single populations, mosaic hybrid zones (patchy distributions of parental forms and subpopulations), and in parapatric populations with narrow contact zones.
Population densities are an important factor in reinforcement, often in conjunction with extinction. It is possible that, when two species come into secondary contact, one population can become extinct—primarily due to low hybrid fitness accompanied by high population growth rates. Extinction is less likely if the hybrids are inviable instead of infertile, as fertile individuals can still survive long enough to reproduce.
=== Selection ===
Speciation by reinforcement relies directly on selection to favor an increase in prezygotic isolation, and the nature of selection's role in reinforcement has been widely discussed, with models applying varying approaches. Selection acting on hybrids can occur in several different ways. All hybrids produced may be equality low-fitness, conferring a broad disadvantage. In other cases, selection may favor multiple and varying phenotypes such as in the case of a mosaic hybrid zone. Natural selection can act on specific alleles both directly or indirectly. In direct selection, the frequency of the selected allele is favored to the extreme. In cases where an allele is indirectly selected, its frequency increases due to a different linked allele experiencing selection (linkage disequilibrium).
The condition of the hybrids under selection can play a role in post-zygotic isolation, as hybrid inviability (a hybrid unable to mature into a fit adult) and sterility (the inability to produce offspring entirely) prohibit gene flow between populations. Selection against the hybrids can even be driven by any failure to obtain a mate, as it is effectively indistinguishable from sterility—each circumstance results in no offspring.
=== Mating and mate preference ===
Some initial divergence in mate preference must be present for reinforcement to occur. Any traits that promote isolation may be subjected to reinforcement such as mating signals (e.g. courtship display), signal responses, the location of breeding grounds, the timing of mating (e.g. seasonal breeding such as in allochronic speciation), or even egg receptivity. Individuals may also discriminate against mates that differ in various traits such as mating call or morphology. Many of these examples are described below.
== Evidence ==
The evidence for reinforcement comes from observations in nature, comparative studies, and laboratory experiments.: 354
=== Nature ===
Reinforcement can be shown to be occurring (or to have occurred in the past) by measuring the strength of prezygotic isolation in a sympatric population in comparison to an allopatric population of the same species.: 357 Comparative studies of this allow for determining large-scale patterns in nature across various taxa.: 362 Mating patterns in hybrid zones can also be used to detect reinforcement. Reproductive character displacement is seen as a result of reinforcement, so many of the cases in nature express this pattern in sympatry. Reinforcement's ubiquity is unknown, but the patterns of reproductive character displacement are found across numerous taxa and is considered to be a common occurrence in nature. Studies of reinforcement in nature often prove difficult, as alternative explanations for the detected patterns can be asserted.: 358 Nevertheless, empirical evidence exists for reinforcement occurring across various taxa and its role in precipitating speciation is conclusive.
=== Comparative studies ===
Assortive mating is expected to increase among sympatric populations experiencing reinforcement. This fact allows for the direct comparison of the strength of prezygotic isolation in sympatry and allopatry between different experiments and studies.: 362 Coyne and Orr surveyed 171 species pairs, collecting data on their geographic mode, genetic distance, and strength of both prezygotic and postzygotic isolation; finding that prezygotic isolation was significantly stronger in sympatric pairs, correlating with the ages of the species.: 362 Additionally, the strength of post-zygotic isolation was not different between sympatric and allopatric pairs. This finding supports the predictions of speciation by reinforcement and correlates well with a later study that found 33 studies expressing patterns of strong prezygotic isolation in sympatry.: 363 A survey of the rates of speciation in fish and their associated hybrid zones found similar patterns in sympatry, supporting the occurrence of reinforcement.
=== Laboratory experiments ===
Laboratory studies that explicitly test for reinforcement are limited,: 357 with many of the experiments having been conducted on Drosophila fruit flies. In general, two types of experiments have been conducted: using artificial selection to mimic natural selection that eliminates the hybrids (often called "destroy-the-hybrids"), and using disruptive selection to select for a trait (regardless of its function in sexual reproduction).: 355–357 Many experiments using the destroy-the-hybrids technique are generally cited as supportive of reinforcement; however, some researchers such as Coyne and Orr and William R. Rice and Ellen E. Hostert contend that they do not truly model reinforcement, as gene flow is completely restricted between two populations.: 356
== Alternative hypotheses ==
Various alternative explanations for the patterns observed in nature have been proposed.: 375 There is no single, overarching signature of reinforcement; however, there are two proposed possibilities:: 379 that of sex asymmetry (where females in sympatric populations are forced to become choosy in the face of two differing males) and that of allelic dominance: any of the alleles experiencing selection for isolation should be dominate. Though this signature does not fully account for fixation probabilities or ecological character displacement.: 380 Coyne and Orr extend the sex asymmetry signature and contend that, regardless of the change seen in females and males in sympatry, isolation is driven more by females.: 380
=== Ecological or ethological influences ===
Ecology can also play a role in the observed patterns—called ecological character displacement. Natural selection may drive the reduction of an overlap of niches between species instead of acting to reduce hybridization: 377 Though one experiment in stickleback fish that explicitly tested this hypotheses found no evidence.
Species interactions can also result in reproductive character displacement (in both mate preference or mating signal). Examples include predation and competition pressures, parasites, deceptive pollination, and mimicry. Because these and other factors can result in reproductive character displacement, Conrad J. Hoskin and Megan Higgie give five criteria for reinforcement to be distinguished between ecological and ethological influences:
(1) mating traits are identified in the focal species; (2) mating traits are affected by a species interaction, such that selection on mating traits is likely; (3) species interactions differ among populations (present vs. absent, or different species interactions affecting mating traits in each population); (4) mating traits (signal and/or preference) differ among populations due to differences in species interactions; (5) speciation requires showing that mating trait divergence results in complete or near complete sexual isolation among populations. Results will be most informative in a well-resolved biogeographic setting where the relationship and history among populations is known.
=== Fusion ===
It is possible that the pattern of enhanced isolation could simply be a temporary outcome of secondary contact where two allopatric species already have a varying range of prezygotic isolation: with some exhibiting more than others. Those that have weaker prezygotic isolation will eventually fuse, losing their distinctiveness. This hypothesis does not explain the fact that individual species in allopatry, experiencing consistent gene flow, would not differ in levels of gene flow upon secondary contact. Furthermore, patterns detected in Drosophila find high levels of prezygotic isolation in sympatry but not in allopatry. The fusion hypothesis predicts that strong isolation should be found in both allopatry and sympatry. This fusion process is thought to occur in nature, but does not fully explain the patterns found with reinforcement.: 376
=== Sympatry ===
It is possible that the process of sympatric speciation itself may result in the observed patterns of reinforcement.: 378 One method of distinguishing between the two is to construct a phylogenetic history of the species, as the strength of prezygotic isolation between a group of related species should differ according to how they speciated in the past. Two other ways to determine if reinforcement occurs (as opposed to sympatric speciation) are:
if two recently speciated taxa do not show signs of post-zygotic isolation of both sympatric and allopatric populations (in sympatric speciation, post-zygotic isolation is not a prerequisite);
if a cline exists between two species over a range of traits (sympatric speciation does not require a cline to exist at all).
=== Sexual selection ===
In a runaway process (not unlike Fisherian runaway selection), selection against the low-fitness hybrids favors assortive mating, increasing mate discrimination rapidly. Additionally, when there is a low cost to female mate preferences, changes in male phenotypes can result, expressing a pattern identical to that of reproductive character displacement. Post-zygotic isolation is not needed, initiated simply by the fact that unfit hybrids cannot get mates.
== Arguments against reinforcement ==
A number of objections were put forth, mainly during the 1980s, arguing that reinforcement is implausible.: 369 Most rely on theoretical work which suggested that the antagonism between the forces of natural selection and gene flow were the largest barriers to its feasibility.: 369–372 These objections have since been largely contradicted by evidence from nature.: 372
=== Gene flow ===
Concerns about hybrid fitness playing a role in reinforcement has led to objections based on the relationship between selection and recombination.: 369 That is, if gene flow is not zero (if hybrids aren't completely unfit), selection cannot drive the fixation of alleles for prezygotic isolation. For example: If population
X
{\displaystyle X}
has the prezygotic isolating allele
A
{\displaystyle A}
and the high fitness, post-zygotic alleles
B
{\displaystyle B}
and
C
{\displaystyle C}
; and population
Y
{\displaystyle Y}
has the prezygotic allele a and the high fitness, post-zygotic alleles
b
{\displaystyle b}
and
c
{\displaystyle c}
, both
A
B
C
{\displaystyle ABC}
and
a
b
c
{\displaystyle abc}
genotypes will experience recombination in the face of gene flow. Somehow, the populations must be maintained.: 369
In addition, specific alleles that have the selective advantage within the overlapped populations are only useful within that population. However, if they are selectively advantageous, gene flow should allow the alleles to spread throughout both populations. To prevent this, the alleles would have to be deleterious or neutral.: 371 This is not without problems, as gene flow from the presumably large allopatric regions could overwhelm the area when two populations overlap.: 371 For reinforcement to work, gene flow must be present, but very limited.
Recent studies suggest reinforcement can occur under a wider range of conditions than previously thought: 372–373 and that the effect of gene flow can be overcome by selection. For example, the two species Drosophila santomea and D. yakuba on the African island São Tomé occasionally hybridize with one another, resulting in fertile female offspring and sterile male offspring. This natural setting was reproduced in the laboratory, directly modeling reinforcement: the removal of some hybrids and the allowance of varying levels of gene flow. The results of the experiment strongly suggested that reinforcement works under a variety of conditions, with the evolution of sexual isolation arising in 5–10 fruit fly generations.
=== Rapid requirements ===
In conjunction with the fusion hypothesis, reinforcement can be thought of as a race against both fusion and extinction. The production of unfit hybrids is effectively the same as a heterozygote disadvantage; whereby a deviation from genetic equilibrium causes the loss of the unfit allele. This effect would result in the extinction of one of the populations. This objection is overcome by when both populations are not subject to the same ecological conditions.: 370 Though, it is still possible for extinction of one population to occur, and has been shown in population simulations. For reinforcement to occur, prezygotic isolation must happen quickly.: 370
== References == | Wikipedia/Reinforcement_(speciation) |
A number of different Markov models of DNA sequence evolution have been proposed. These substitution models differ in terms of the parameters used to describe the rates at which one nucleotide replaces another during evolution. These models are frequently used in molecular phylogenetic analyses. In particular, they are used during the calculation of likelihood of a tree (in Bayesian and maximum likelihood approaches to tree estimation) and they are used to estimate the evolutionary distance between sequences from the observed differences between the sequences.
== Introduction ==
These models are phenomenological descriptions of the evolution of DNA as a string of four discrete states. These Markov models do not explicitly depict the mechanism of mutation nor the action of natural selection. Rather they describe the relative rates of different changes. For example, mutational biases and purifying selection favoring conservative changes are probably both responsible for the relatively high rate of transitions compared to transversions in evolving sequences. However, the Kimura (K80) model described below only attempts to capture the effect of both forces in a parameter that reflects the relative rate of transitions to transversions.
Evolutionary analyses of sequences are conducted on a wide variety of time scales. Thus, it is convenient to express these models in terms of the instantaneous rates of change between different states (the Q matrices below). If we are given a starting (ancestral) state at one position, the model's Q matrix and a branch length expressing the expected number of changes to have occurred since the ancestor, then we can derive the probability of the descendant sequence having each of the four states. The mathematical details of this transformation from rate-matrix to probability matrix are described in the mathematics of substitution models section of the substitution model page. By expressing models in terms of the instantaneous rates of change we can avoid estimating a large numbers of parameters for each branch on a phylogenetic tree (or each comparison if the analysis involves many pairwise sequence comparisons).
The models described on this page describe the evolution of a single site within a set of sequences. They are often used for analyzing the evolution of an entire locus by making the simplifying assumption that different sites evolve independently and are identically distributed. This assumption may be justifiable if the sites can be assumed to be evolving neutrally. If the primary effect of natural selection on the evolution of the sequences is to constrain some sites, then models of among-site rate-heterogeneity can be used. This approach allows one to estimate only one matrix of relative rates of substitution, and another set of parameters describing the variance in the total rate of substitution across sites.
== DNA evolution as a continuous-time Markov chain ==
=== Continuous-time Markov chains ===
Continuous-time Markov chains have the usual transition matrices
which are, in addition, parameterized by time,
t
{\displaystyle t}
. Specifically, if
E
1
,
E
2
,
E
3
,
E
4
{\displaystyle E_{1},E_{2},E_{3},E_{4}}
are the states, then the transition matrix
P
(
t
)
=
(
P
i
j
(
t
)
)
{\displaystyle P(t)={\big (}P_{ij}(t){\big )}}
where each individual entry,
P
i
j
(
t
)
{\displaystyle P_{ij}(t)}
refers to the probability that state
E
i
{\displaystyle E_{i}}
will change to state
E
j
{\displaystyle E_{j}}
in time
t
{\displaystyle t}
.
Example: We would like to model the substitution process in DNA sequences (i.e. Jukes–Cantor, Kimura, etc.) in a continuous-time fashion. The corresponding transition matrices will look like:
P
(
t
)
=
(
p
A
A
(
t
)
p
A
G
(
t
)
p
A
C
(
t
)
p
A
T
(
t
)
p
G
A
(
t
)
p
G
G
(
t
)
p
G
C
(
t
)
p
G
T
(
t
)
p
C
A
(
t
)
p
C
G
(
t
)
p
C
C
(
t
)
p
C
T
(
t
)
p
T
A
(
t
)
p
T
G
(
t
)
p
T
C
(
t
)
p
T
T
(
t
)
)
{\displaystyle P(t)={\begin{pmatrix}p_{\mathrm {AA} }(t)&p_{\mathrm {AG} }(t)&p_{\mathrm {AC} }(t)&p_{\mathrm {AT} }(t)\\p_{\mathrm {GA} }(t)&p_{\mathrm {GG} }(t)&p_{\mathrm {GC} }(t)&p_{\mathrm {GT} }(t)\\p_{\mathrm {CA} }(t)&p_{\mathrm {CG} }(t)&p_{\mathrm {CC} }(t)&p_{\mathrm {CT} }(t)\\p_{\mathrm {TA} }(t)&p_{\mathrm {TG} }(t)&p_{\mathrm {TC} }(t)&p_{\mathrm {TT} }(t)\end{pmatrix}}}
where the top-left and bottom-right 2 × 2 blocks correspond to transition probabilities and the top-right and bottom-left 2 × 2 blocks corresponds to transversion probabilities.
Assumption: If at some time
t
0
{\displaystyle t_{0}}
, the Markov chain is in state
E
i
{\displaystyle E_{i}}
, then the probability that at time
t
0
+
t
{\displaystyle t_{0}+t}
, it will be in state
E
j
{\displaystyle E_{j}}
depends only upon
i
{\displaystyle i}
,
j
{\displaystyle j}
and
t
{\displaystyle t}
. This then allows us to write that probability as
p
i
j
(
t
)
{\displaystyle p_{ij}(t)}
.
Theorem: Continuous-time transition matrices satisfy:
P
(
t
+
τ
)
=
P
(
t
)
P
(
τ
)
{\displaystyle P(t+\tau )=P(t)P(\tau )}
Note: There is here a possible confusion between two meanings of the word transition. (i) In the context of Markov chains, transition is the general term for the change between two states. (ii) In the context of nucleotide changes in DNA sequences, transition is a specific term for the exchange between either the two purines (A ↔ G) or the two pyrimidines (C ↔ T) (for additional details, see the article about transitions in genetics). By contrast, an exchange between one purine and one pyrimidine is called a transversion.
=== Deriving the dynamics of substitution ===
Consider a DNA sequence of fixed length m evolving in time by base replacement. Assume that the processes followed by the m sites are Markovian independent, identically distributed and that the process is constant over time. For a particular site, let
E
=
{
A
,
G
,
C
,
T
}
{\displaystyle {\mathcal {E}}=\{A,\,G,\,C,\,T\}}
be the set of possible states for the site, and
p
(
t
)
=
(
p
A
(
t
)
,
p
G
(
t
)
,
p
C
(
t
)
,
p
T
(
t
)
)
{\displaystyle \mathbf {p} (t)=(p_{A}(t),\,p_{G}(t),\,p_{C}(t),\,p_{T}(t))}
their respective probabilities at time
t
{\displaystyle t}
. For two distinct
x
,
y
∈
E
{\displaystyle x,y\in {\mathcal {E}}}
, let
μ
x
y
{\displaystyle \mu _{xy}\ }
be the transition rate from state
x
{\displaystyle x}
to state
y
{\displaystyle y}
. Similarly, for any
x
{\displaystyle x}
, let the total rate of change from
x
{\displaystyle x}
be
μ
x
=
∑
y
≠
x
μ
x
y
.
{\displaystyle \mu _{x}=\sum _{y\neq x}\mu _{xy}\,.}
The changes in the probability distribution
p
A
(
t
)
{\displaystyle p_{A}(t)}
for small increments of time
Δ
t
{\displaystyle \Delta t}
are given by
p
A
(
t
+
Δ
t
)
=
p
A
(
t
)
−
p
A
(
t
)
μ
A
Δ
t
+
∑
x
≠
A
p
x
(
t
)
μ
x
A
Δ
t
.
{\displaystyle p_{A}(t+\Delta t)=p_{A}(t)-p_{A}(t)\mu _{A}\Delta t+\sum _{x\neq A}p_{x}(t)\mu _{xA}\Delta t\,.}
In other words, (in frequentist language), the frequency of
A
{\displaystyle A}
's at time
t
+
Δ
t
{\displaystyle t+\Delta t}
is equal to the frequency at time
t
{\displaystyle t}
minus the frequency of the lost
A
{\displaystyle A}
's plus the frequency of the newly created
A
{\displaystyle A}
's.
Similarly for the probabilities
p
G
(
t
)
{\displaystyle p_{G}(t)}
,
p
C
(
t
)
{\displaystyle p_{C}(t)}
and
p
T
(
t
)
{\displaystyle p_{T}(t)}
. These equations can be written compactly as
p
(
t
+
Δ
t
)
=
p
(
t
)
+
p
(
t
)
Q
Δ
t
,
{\displaystyle \mathbf {p} (t+\Delta t)=\mathbf {p} (t)+\mathbf {p} (t)Q\Delta t\,,}
where
Q
=
(
−
μ
A
μ
A
G
μ
A
C
μ
A
T
μ
G
A
−
μ
G
μ
G
C
μ
G
T
μ
C
A
μ
C
G
−
μ
C
μ
C
T
μ
T
A
μ
T
G
μ
T
C
−
μ
T
)
{\displaystyle Q={\begin{pmatrix}-\mu _{A}&\mu _{AG}&\mu _{AC}&\mu _{AT}\\\mu _{GA}&-\mu _{G}&\mu _{GC}&\mu _{GT}\\\mu _{CA}&\mu _{CG}&-\mu _{C}&\mu _{CT}\\\mu _{TA}&\mu _{TG}&\mu _{TC}&-\mu _{T}\end{pmatrix}}}
is known as the rate matrix. Note that, by definition, the sum of the entries in each row of
Q
{\displaystyle Q}
is equal to zero. It follows that
p
′
(
t
)
=
p
(
t
)
Q
.
{\displaystyle \mathbf {p} '(t)=\mathbf {p} (t)Q\,.}
For a stationary process, where
Q
{\displaystyle Q}
does not depend on time t, this differential equation can be solved. First,
P
(
t
)
=
exp
(
t
Q
)
,
{\displaystyle P(t)=\exp(tQ),}
where
exp
(
t
Q
)
{\displaystyle \exp(tQ)}
denotes the exponential of the matrix
t
Q
{\displaystyle tQ}
. As a result,
p
(
t
)
=
p
(
0
)
P
(
t
)
=
p
(
0
)
exp
(
t
Q
)
.
{\displaystyle \mathbf {p} (t)=\mathbf {p} (0)P(t)=\mathbf {p} (0)\exp(tQ)\,.}
=== Ergodicity ===
If the Markov chain is irreducible, i.e. if it is always possible to go from a state
x
{\displaystyle x}
to a state
y
{\displaystyle y}
(possibly in several steps), then it is also ergodic. As a result, it has a unique stationary distribution
π
=
{
π
x
,
x
∈
E
}
{\displaystyle {\boldsymbol {\pi }}=\{\pi _{x},\,x\in {\mathcal {E}}\}}
, where
π
x
{\displaystyle \pi _{x}}
corresponds to the proportion of time spent in state
x
{\displaystyle x}
after the Markov chain has run for an infinite amount of time. In DNA evolution, under the assumption of a common process for each site, the stationary frequencies
π
A
,
π
G
,
π
C
,
π
T
{\displaystyle \pi _{A},\,\pi _{G},\,\pi _{C},\,\pi _{T}}
correspond to equilibrium base compositions. Indeed, note that since the stationary distribution
π
{\displaystyle {\boldsymbol {\pi }}}
satisfies
π
Q
=
0
{\displaystyle {\boldsymbol {\pi }}Q=0}
, we see that when the current distribution
p
(
t
)
{\displaystyle \mathbf {p} (t)}
is the stationary distribution
π
{\displaystyle {\boldsymbol {\pi }}}
we have
p
′
(
t
)
=
p
(
t
)
Q
=
π
Q
=
0
.
{\displaystyle {\mathbf {p} '(t)=\mathbf {p} (t)Q={\boldsymbol {\pi }}}Q=0\,.}
In other words, the frequencies of
p
A
(
t
)
,
p
G
(
t
)
,
p
C
(
t
)
,
p
T
(
t
)
{\displaystyle p_{A}(t),\,p_{G}(t),\,p_{C}(t),\,p_{T}(t)}
do not change.
=== Time reversibility ===
Definition: A stationary Markov process is time reversible if (in the steady state) the amount of change from state
x
{\displaystyle x\ }
to
y
{\displaystyle y\ }
is equal to the amount of change from
y
{\displaystyle y\ }
to
x
{\displaystyle x\ }
, (although the two states may occur with different frequencies). This means that:
π
x
μ
x
y
=
π
y
μ
y
x
{\displaystyle \pi _{x}\mu _{xy}=\pi _{y}\mu _{yx}\ }
Not all stationary processes are reversible, however, most commonly used DNA evolution models assume time reversibility, which is considered to be a reasonable assumption.
Under the time reversibility assumption, let
s
x
y
=
μ
x
y
/
π
y
{\displaystyle s_{xy}=\mu _{xy}/\pi _{y}\ }
, then it is easy to see that:
s
x
y
=
s
y
x
{\displaystyle s_{xy}=s_{yx}\ }
Definition The symmetric term
s
x
y
{\displaystyle s_{xy}\ }
is called the exchangeability between states
x
{\displaystyle x\ }
and
y
{\displaystyle y\ }
. In other words,
s
x
y
{\displaystyle s_{xy}\ }
is the fraction of the frequency of state
x
{\displaystyle x\ }
that is the result of transitions from state
y
{\displaystyle y\ }
to state
x
{\displaystyle x\ }
.
Corollary The 12 off-diagonal entries of the rate matrix,
Q
{\displaystyle Q\ }
(note the off-diagonal entries determine the diagonal entries, since the rows of
Q
{\displaystyle Q\ }
sum to zero) can be completely determined by 9 numbers; these are: 6 exchangeability terms and 3 stationary frequencies
π
x
{\displaystyle \pi _{x}\ }
, (since the stationary frequencies sum to 1).
=== Scaling of branch lengths ===
By comparing extant sequences, one can determine the amount of sequence divergence. This raw measurement of divergence provides information about the number of changes that have occurred along the path separating the sequences. The simple count of differences (the Hamming distance) between sequences will often underestimate the number of substitution because of multiple hits (see homoplasy). Trying to estimate the exact number of changes that have occurred is difficult, and usually not necessary. Instead, branch lengths (and path lengths) in phylogenetic analyses are usually expressed in the expected number of changes per site. The path length is the product of the duration of the path in time and the mean rate of substitutions. While their product can be estimated, the rate and time are not identifiable from sequence divergence.
The descriptions of rate matrices on this page accurately reflect the relative magnitude of different substitutions, but these rate matrices are not scaled such that a branch length of 1 yields one expected change. This scaling can be accomplished by multiplying every element of the matrix by the same factor, or simply by scaling the branch lengths. If we use the β to denote the scaling factor, and ν to denote the branch length measured in the expected number of substitutions per site then βν is used in the transition probability formulae below in place of μt. Note that ν is a parameter to be estimated from data, and is referred to as the branch length, while β is simply a number that can be calculated from the rate matrix (it is not a separate free parameter).
The value of β can be found by forcing the expected rate of flux of states to 1. The diagonal entries of the rate-matrix (the Q matrix) represent -1 times the rate of leaving each state. For time-reversible models, we know the equilibrium state frequencies (these are simply the πi parameter value for state i). Thus we can find the expected rate of change by calculating the sum of flux out of each state weighted by the proportion of sites that are expected to be in that class. Setting β to be the reciprocal of this sum will guarantee that scaled process has an expected flux of 1:
β
=
1
/
(
−
∑
i
π
i
μ
i
i
)
{\displaystyle \beta =1/\left(-\sum _{i}\pi _{i}\mu _{ii}\right)}
For example, in the Jukes–Cantor, the scaling factor would be 4/(3μ) because the rate of leaving each state is 3μ/4.
== Most common models of DNA evolution ==
=== JC69 model (Jukes and Cantor 1969) ===
JC69, the Jukes and Cantor 1969 model, is the simplest substitution model. There are several assumptions. It assumes equal base frequencies
(
π
A
=
π
G
=
π
C
=
π
T
=
1
4
)
{\displaystyle \left(\pi _{A}=\pi _{G}=\pi _{C}=\pi _{T}={1 \over 4}\right)}
and equal mutation rates. The only parameter of this model is therefore
μ
{\displaystyle \mu }
, the overall substitution rate. As previously mentioned, this variable becomes a constant when we normalize the mean-rate to 1.
Q
=
(
∗
μ
4
μ
4
μ
4
μ
4
∗
μ
4
μ
4
μ
4
μ
4
∗
μ
4
μ
4
μ
4
μ
4
∗
)
{\displaystyle Q={\begin{pmatrix}{*}&{\mu \over 4}&{\mu \over 4}&{\mu \over 4}\\{\mu \over 4}&{*}&{\mu \over 4}&{\mu \over 4}\\{\mu \over 4}&{\mu \over 4}&{*}&{\mu \over 4}\\{\mu \over 4}&{\mu \over 4}&{\mu \over 4}&{*}\end{pmatrix}}}
P
=
(
1
4
+
3
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
+
3
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
+
3
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
−
1
4
e
−
t
μ
1
4
+
3
4
e
−
t
μ
)
{\displaystyle P={\begin{pmatrix}{{1 \over 4}+{3 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}\\\\{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}+{3 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}\\\\{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}+{3 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}\\\\{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}-{1 \over 4}e^{-t\mu }}&{{1 \over 4}+{3 \over 4}e^{-t\mu }}\end{pmatrix}}}
When branch length,
ν
{\displaystyle \nu }
, is measured in the expected number of changes per site then:
P
i
j
(
ν
)
=
{
1
4
+
3
4
e
−
4
ν
/
3
if
i
=
j
1
4
−
1
4
e
−
4
ν
/
3
if
i
≠
j
{\displaystyle P_{ij}(\nu )=\left\{{\begin{array}{cc}{1 \over 4}+{3 \over 4}e^{-4\nu /3}&{\mbox{ if }}i=j\\{1 \over 4}-{1 \over 4}e^{-4\nu /3}&{\mbox{ if }}i\neq j\end{array}}\right.}
It is worth noticing that
ν
=
3
4
t
μ
=
(
μ
4
+
μ
4
+
μ
4
)
t
{\displaystyle \nu ={3 \over 4}t\mu =({\mu \over 4}+{\mu \over 4}+{\mu \over 4})t}
what stands for sum of any column (or row) of matrix
Q
{\displaystyle Q}
multiplied by time and thus means expected number of substitutions in time
t
{\displaystyle t}
(branch duration) for each particular site (per site) when the rate of substitution equals
μ
{\displaystyle \mu }
.
Given the proportion
p
{\displaystyle p}
of sites that differ between the two sequences the Jukes–Cantor estimate of the evolutionary distance (in terms of the expected number of changes) between two sequences is given by
d
^
=
−
3
4
ln
(
1
−
4
3
p
)
=
ν
^
{\displaystyle {\hat {d}}=-{3 \over 4}\ln({1-{4 \over 3}p})={\hat {\nu }}}
The
p
{\displaystyle p}
in this formula is frequently referred to as the
p
{\displaystyle p}
-distance. It is a sufficient statistic for calculating the Jukes–Cantor distance correction, but is not sufficient for the calculation of the evolutionary distance under the more complex models that follow (also note that
p
{\displaystyle p}
used in subsequent formulae is not identical to the "
p
{\displaystyle p}
-distance").
=== K80 model (Kimura 1980) ===
K80, the Kimura 1980 model, often referred to as Kimura's two parameter model (or the K2P model), distinguishes between transitions (
A
↔
G
{\displaystyle A\leftrightarrow G}
, i.e. from purine to purine, or
C
↔
T
{\displaystyle C\leftrightarrow T}
, i.e. from pyrimidine to pyrimidine) and transversions (from purine to pyrimidine or vice versa). In Kimura's original description of the model the α and β were used to denote the rates of these types of substitutions, but it is now more common to set the rate of transversions to 1 and use κ to denote the transition/transversion rate ratio (as is done below). The K80 model assumes that all of the bases are equally frequent (
π
A
=
π
G
=
π
C
=
π
T
=
1
4
{\displaystyle \pi _{A}=\pi _{G}=\pi _{C}=\pi _{T}={1 \over 4}}
).
Rate matrix
Q
=
(
∗
κ
1
1
κ
∗
1
1
1
1
∗
κ
1
1
κ
∗
)
{\displaystyle Q={\begin{pmatrix}{*}&{\kappa }&{1}&{1}\\{\kappa }&{*}&{1}&{1}\\{1}&{1}&{*}&{\kappa }\\{1}&{1}&{\kappa }&{*}\end{pmatrix}}}
with columns corresponding to
A
{\displaystyle A}
,
G
{\displaystyle G}
,
C
{\displaystyle C}
, and
T
{\displaystyle T}
, respectively.
The Kimura two-parameter distance is given by:
K
=
−
1
2
ln
(
(
1
−
2
p
−
q
)
1
−
2
q
)
{\displaystyle K=-{1 \over 2}\ln((1-2p-q){\sqrt {1-2q}})}
where p is the proportion of sites that show transitional differences and
q is the proportion of sites that show transversional differences.
=== K81 model (Kimura 1981) ===
K81, the Kimura 1981 model, often called Kimura's three parameter model (K3P model) or the Kimura three substitution type (K3ST) model, has distinct rates for transitions and two distinct types of transversions. The two transversion types are those that conserve the weak/strong properties of the nucleotides (i.e.,
A
↔
T
{\displaystyle A\leftrightarrow T}
and
C
↔
G
{\displaystyle C\leftrightarrow G}
, denoted by symbol
γ
{\displaystyle \gamma }
) and those that conserve the amino/keto properties of the nucleotides (i.e.,
A
↔
C
{\displaystyle A\leftrightarrow C}
and
G
↔
T
{\displaystyle G\leftrightarrow T}
, denoted by symbol
β
{\displaystyle \beta }
). The K81 model assumes that all equilibrium base frequencies are equal (i.e.,
π
A
=
π
G
=
π
C
=
π
T
=
0.25
{\displaystyle \pi _{A}=\pi _{G}=\pi _{C}=\pi _{T}=0.25}
).
Rate matrix
Q
=
(
∗
α
β
γ
α
∗
γ
β
β
γ
∗
α
γ
β
α
∗
)
{\displaystyle Q={\begin{pmatrix}{*}&{\alpha }&{\beta }&{\gamma }\\{\alpha }&{*}&{\gamma }&{\beta }\\{\beta }&{\gamma }&{*}&{\alpha }\\{\gamma }&{\beta }&{\alpha }&{*}\end{pmatrix}}}
with columns corresponding to
A
{\displaystyle A}
,
G
{\displaystyle G}
,
C
{\displaystyle C}
, and
T
{\displaystyle T}
, respectively.
The K81 model is used much less often than the K80 (K2P) model for distance estimation and it is seldom the best-fitting model in maximum likelihood phylogenetics. Despite these facts, the K81 model has continued to be studied in the context of mathematical phylogenetics. One important property is the ability to perform a Hadamard transform assuming the site patterns were generated on a tree with nucleotides evolving under the K81 model.
When used in the context of phylogenetics the Hadamard transform provides an elegant and fully invertible means to calculate expected site pattern frequencies given a set of branch lengths (or vice versa). Unlike many maximum likelihood calculations, the relative values for
α
{\displaystyle \alpha }
,
β
{\displaystyle \beta }
, and
γ
{\displaystyle \gamma }
can vary across branches and the Hadamard transform can even provide evidence that the data do not fit a tree. The Hadamard transform can also be combined with a wide variety of methods to accommodate among-sites rate heterogeneity, using continuous distributions rather than the discrete approximations typically used in maximum likelihood phylogenetics (although one must sacrifice the invertibility of the Hadamard transform to use certain among-sites rate heterogeneity distributions).
=== F81 model (Felsenstein 1981) ===
F81, the Felsenstein's 1981 model, is an extension of the JC69 model in which base frequencies are allowed to vary from 0.25 (
π
A
≠
π
G
≠
π
C
≠
π
T
{\displaystyle \pi _{A}\neq \pi _{G}\neq \pi _{C}\neq \pi _{T}}
)
Rate matrix:
Q
=
(
∗
π
G
π
C
π
T
π
A
∗
π
C
π
T
π
A
π
G
∗
π
T
π
A
π
G
π
C
∗
)
{\displaystyle Q={\begin{pmatrix}{*}&{\pi _{G}}&{\pi _{C}}&{\pi _{T}}\\{\pi _{A}}&{*}&{\pi _{C}}&{\pi _{T}}\\{\pi _{A}}&{\pi _{G}}&{*}&{\pi _{T}}\\{\pi _{A}}&{\pi _{G}}&{\pi _{C}}&{*}\end{pmatrix}}}
When branch length, ν, is measured in the expected number of changes per site then:
β
=
1
/
(
1
−
π
A
2
−
π
C
2
−
π
G
2
−
π
T
2
)
{\displaystyle \beta =1/(1-\pi _{A}^{2}-\pi _{C}^{2}-\pi _{G}^{2}-\pi _{T}^{2})}
P
i
j
(
ν
)
=
{
e
−
β
ν
+
π
j
(
1
−
e
−
β
ν
)
if
i
=
j
π
j
(
1
−
e
−
β
ν
)
if
i
≠
j
{\displaystyle P_{ij}(\nu )=\left\{{\begin{array}{cc}e^{-\beta \nu }+\pi _{j}\left(1-e^{-\beta \nu }\right)&{\mbox{ if }}i=j\\\pi _{j}\left(1-e^{-\beta \nu }\right)&{\mbox{ if }}i\neq j\end{array}}\right.}
=== HKY85 model (Hasegawa, Kishino and Yano 1985) ===
HKY85, the Hasegawa, Kishino and Yano 1985 model, can be thought of as combining the extensions made in the Kimura80 and Felsenstein81 models. Namely, it distinguishes between the rate of transitions and transversions (using the κ parameter), and it allows unequal base frequencies (
π
A
≠
π
G
≠
π
C
≠
π
T
{\displaystyle \pi _{A}\neq \pi _{G}\neq \pi _{C}\neq \pi _{T}}
). [ Felsenstein described a similar (but not equivalent) model in 1984 using a different parameterization; that latter model is referred to as the F84 model. ]
Rate matrix
Q
=
(
∗
κ
π
G
π
C
π
T
κ
π
A
∗
π
C
π
T
π
A
π
G
∗
κ
π
T
π
A
π
G
κ
π
C
∗
)
{\displaystyle Q={\begin{pmatrix}{*}&{\kappa \pi _{G}}&{\pi _{C}}&{\pi _{T}}\\{\kappa \pi _{A}}&{*}&{\pi _{C}}&{\pi _{T}}\\{\pi _{A}}&{\pi _{G}}&{*}&{\kappa \pi _{T}}\\{\pi _{A}}&{\pi _{G}}&{\kappa \pi _{C}}&{*}\end{pmatrix}}}
If we express the branch length, ν in terms of the expected number of changes per site then:
β
=
1
2
(
π
A
+
π
G
)
(
π
C
+
π
T
)
+
2
κ
[
(
π
A
π
G
)
+
(
π
C
π
T
)
]
{\displaystyle \beta ={\frac {1}{2(\pi _{A}+\pi _{G})(\pi _{C}+\pi _{T})+2\kappa [(\pi _{A}\pi _{G})+(\pi _{C}\pi _{T})]}}}
P
A
A
(
ν
,
κ
,
π
)
=
[
π
A
(
π
A
+
π
G
+
(
π
C
+
π
T
)
e
−
β
ν
)
+
π
G
e
−
(
1
+
(
π
A
+
π
G
)
(
κ
−
1.0
)
)
β
ν
]
/
(
π
A
+
π
G
)
{\displaystyle P_{AA}(\nu ,\kappa ,\pi )=\left[\pi _{A}\left(\pi _{A}+\pi _{G}+(\pi _{C}+\pi _{T})e^{-\beta \nu }\right)+\pi _{G}e^{-(1+(\pi _{A}+\pi _{G})(\kappa -1.0))\beta \nu }\right]/(\pi _{A}+\pi _{G})}
P
A
C
(
ν
,
κ
,
π
)
=
π
C
(
1.0
−
e
−
β
ν
)
{\displaystyle P_{AC}(\nu ,\kappa ,\pi )=\pi _{C}\left(1.0-e^{-\beta \nu }\right)}
P
A
G
(
ν
,
κ
,
π
)
=
[
π
G
(
π
A
+
π
G
+
(
π
C
+
π
T
)
e
−
β
ν
)
−
π
G
e
−
(
1
+
(
π
A
+
π
G
)
(
κ
−
1.0
)
)
β
ν
]
/
(
π
A
+
π
G
)
{\displaystyle P_{AG}(\nu ,\kappa ,\pi )=\left[\pi _{G}\left(\pi _{A}+\pi _{G}+(\pi _{C}+\pi _{T})e^{-\beta \nu }\right)-\pi _{G}e^{-(1+(\pi _{A}+\pi _{G})(\kappa -1.0))\beta \nu }\right]/\left(\pi _{A}+\pi _{G}\right)}
P
A
T
(
ν
,
κ
,
π
)
=
π
T
(
1.0
−
e
−
β
ν
)
{\displaystyle P_{AT}(\nu ,\kappa ,\pi )=\pi _{T}\left(1.0-e^{-\beta \nu }\right)}
and formula for the other combinations of states can be obtained by substituting in the appropriate base frequencies.
=== T92 model (Tamura 1992) ===
T92, the Tamura 1992 model, is a mathematical method developed to estimate the number of nucleotide substitutions per site between two DNA sequences, by extending Kimura's (1980) two-parameter method to the case where a G+C content bias exists. This method will be useful when there are strong transition-transversion and G+C-content biases, as in the case of Drosophila mitochondrial DNA.
T92 involves a single, compound base frequency parameter
θ
∈
(
0
,
1
)
{\displaystyle \theta \in (0,1)}
(also noted
π
G
C
{\displaystyle \pi _{GC}}
)
=
π
G
+
π
C
=
1
−
(
π
A
+
π
T
)
{\displaystyle =\pi _{G}+\pi _{C}=1-(\pi _{A}+\pi _{T})}
As T92 echoes the Chargaff's second parity rule — pairing nucleotides do have the same frequency on a single DNA strand, G and C on the one hand, and A and T on the other hand — it follows that the four base frequences can be expressed as a function of
π
G
C
{\displaystyle \pi _{GC}}
π
G
=
π
C
=
π
G
C
2
{\displaystyle \pi _{G}=\pi _{C}={\pi _{GC} \over 2}}
and
π
A
=
π
T
=
(
1
−
π
G
C
)
2
{\displaystyle \pi _{A}=\pi _{T}={(1-\pi _{GC}) \over 2}}
Rate matrix
Q
=
(
∗
κ
π
G
C
/
2
π
G
C
/
2
(
1
−
π
G
C
)
/
2
κ
(
1
−
π
G
C
)
/
2
∗
π
G
C
/
2
(
1
−
π
G
C
)
/
2
(
1
−
π
G
C
)
/
2
π
G
C
/
2
∗
κ
(
1
−
π
G
C
)
/
2
(
1
−
π
G
C
)
/
2
π
G
C
/
2
κ
π
G
C
/
2
∗
)
{\displaystyle Q={\begin{pmatrix}{*}&{\kappa \pi _{GC}/2}&{\pi _{GC}/2}&{(1-\pi _{GC})/2}\\{\kappa (1-\pi _{GC})/2}&{*}&{\pi _{GC}/2}&{(1-\pi _{GC})/2}\\{(1-\pi _{GC})/2}&{\pi _{GC}/2}&{*}&{\kappa (1-\pi _{GC})/2}\\{(1-\pi _{GC})/2}&{\pi _{GC}/2}&{\kappa \pi _{GC}/2}&{*}\end{pmatrix}}}
The evolutionary distance between two DNA sequences according to this model is given by
d
=
−
h
ln
(
1
−
p
h
−
q
)
−
1
2
(
1
−
h
)
ln
(
1
−
2
q
)
{\displaystyle d=-h\ln(1-{p \over h}-q)-{1 \over 2}(1-h)\ln(1-2q)}
where
h
=
2
θ
(
1
−
θ
)
{\displaystyle h=2\theta (1-\theta )}
and
θ
{\displaystyle \theta }
is the G+C content (
π
G
C
=
π
G
+
π
C
{\displaystyle \pi _{GC}=\pi _{G}+\pi _{C}}
).
=== TN93 model (Tamura and Nei 1993) ===
TN93, the Tamura and Nei 1993 model, distinguishes between the two different types of transition; i.e. (
A
↔
G
{\displaystyle A\leftrightarrow G}
) is allowed to have a different rate to (
C
↔
T
{\displaystyle C\leftrightarrow T}
). Transversions are all assumed to occur at the same rate, but that rate is allowed to be different from both of the rates for transitions.
TN93 also allows unequal base frequencies (
π
A
≠
π
G
≠
π
C
≠
π
T
{\displaystyle \pi _{A}\neq \pi _{G}\neq \pi _{C}\neq \pi _{T}}
).
Rate matrix
Q
=
(
∗
κ
1
π
G
π
C
π
T
κ
1
π
A
∗
π
C
π
T
π
A
π
G
∗
κ
2
π
T
π
A
π
G
κ
2
π
C
∗
)
{\displaystyle Q={\begin{pmatrix}{*}&{\kappa _{1}\pi _{G}}&{\pi _{C}}&{\pi _{T}}\\{\kappa _{1}\pi _{A}}&{*}&{\pi _{C}}&{\pi _{T}}\\{\pi _{A}}&{\pi _{G}}&{*}&{\kappa _{2}\pi _{T}}\\{\pi _{A}}&{\pi _{G}}&{\kappa _{2}\pi _{C}}&{*}\end{pmatrix}}}
=== GTR model (Tavaré 1986) ===
GTR, the Generalised time-reversible model of Tavaré 1986, is the most general neutral, independent, finite-sites, time-reversible model possible. It was first described in a general form by Simon Tavaré in 1986.
GTR parameters consist of an equilibrium base frequency vector,
Π
=
(
π
A
,
π
G
,
π
C
,
π
T
)
{\displaystyle \Pi =(\pi _{A},\pi _{G},\pi _{C},\pi _{T})}
, giving the frequency at which each base occurs at each site, and the rate matrix
Q
=
(
−
(
α
π
G
+
β
π
C
+
γ
π
T
)
α
π
G
β
π
C
γ
π
T
α
π
A
−
(
α
π
A
+
δ
π
C
+
ϵ
π
T
)
δ
π
C
ϵ
π
T
β
π
A
δ
π
G
−
(
β
π
A
+
δ
π
G
+
η
π
T
)
η
π
T
γ
π
A
ϵ
π
G
η
π
C
−
(
γ
π
A
+
ϵ
π
G
+
η
π
C
)
)
{\displaystyle Q={\begin{pmatrix}{-(\alpha \pi _{G}+\beta \pi _{C}+\gamma \pi _{T})}&{\alpha \pi _{G}}&{\beta \pi _{C}}&{\gamma \pi _{T}}\\{\alpha \pi _{A}}&{-(\alpha \pi _{A}+\delta \pi _{C}+\epsilon \pi _{T})}&{\delta \pi _{C}}&{\epsilon \pi _{T}}\\{\beta \pi _{A}}&{\delta \pi _{G}}&{-(\beta \pi _{A}+\delta \pi _{G}+\eta \pi _{T})}&{\eta \pi _{T}}\\{\gamma \pi _{A}}&{\epsilon \pi _{G}}&{\eta \pi _{C}}&{-(\gamma \pi _{A}+\epsilon \pi _{G}+\eta \pi _{C})}\end{pmatrix}}}
Where
α
=
r
(
A
→
G
)
=
r
(
G
→
A
)
β
=
r
(
A
→
C
)
=
r
(
C
→
A
)
γ
=
r
(
A
→
T
)
=
r
(
T
→
A
)
δ
=
r
(
G
→
C
)
=
r
(
C
→
G
)
ϵ
=
r
(
G
→
T
)
=
r
(
T
→
G
)
η
=
r
(
C
→
T
)
=
r
(
T
→
C
)
{\displaystyle {\begin{aligned}\alpha =r(A\rightarrow G)=r(G\rightarrow A)\\\beta =r(A\rightarrow C)=r(C\rightarrow A)\\\gamma =r(A\rightarrow T)=r(T\rightarrow A)\\\delta =r(G\rightarrow C)=r(C\rightarrow G)\\\epsilon =r(G\rightarrow T)=r(T\rightarrow G)\\\eta =r(C\rightarrow T)=r(T\rightarrow C)\end{aligned}}}
are the transition rate parameters.
Therefore, GTR (for four characters, as is often the case in phylogenetics) requires 6 substitution rate parameters, as well as 4 equilibrium base frequency parameters. However, this is usually eliminated down to 9 parameters plus
μ
{\displaystyle \mu }
, the overall number of substitutions per unit time. When measuring time in substitutions (
μ
{\displaystyle \mu }
=1) only 8 free parameters remain.
In general, to compute the number of parameters, one must count the number of entries above the diagonal in the matrix, i.e. for n trait values per site
n
2
−
n
2
{\displaystyle {{n^{2}-n} \over 2}}
, and then add n for the equilibrium base frequencies, and subtract 1 because
μ
{\displaystyle \mu }
is fixed. One gets
n
2
−
n
2
+
n
−
1
=
1
2
n
2
+
1
2
n
−
1.
{\displaystyle {{n^{2}-n} \over 2}+n-1={1 \over 2}n^{2}+{1 \over 2}n-1.}
For example, for an amino acid sequence (there are 20 "standard" amino acids that make up proteins), one would find there are 209 parameters. However, when studying coding regions of the genome, it is more common to work with a codon substitution model (a codon is three bases and codes for one amino acid in a protein). There are
4
3
=
64
{\displaystyle 4^{3}=64}
codons, but the rates for transitions between codons which differ by more than one base is assumed to be zero. Hence, there are
20
×
19
×
3
2
+
64
−
1
=
633
{\displaystyle {{20\times 19\times 3} \over 2}+64-1=633}
parameters.
== Two-state substitution models ==
An alternative way to analyze DNA sequence data is to recode the nucleotides as purines (R) and pyrimidines (Y); this practice is often called RY-coding. Insertions and deletions in multiple sequence alignments can also be encoded as binary data and analyzed in using a two-state model.
The simplest two-state model of sequence evolution is called the Cavender-Farris model or the Cavender-Farris-Neyman (CFN) model; the name of this model reflects the fact that it was described independently in several different publications. The CFN model is identical to the Jukes-Cantor model adapted to two states and it has even been implemented as the "JC2" model in the popular IQ-TREE software package (using this model in IQ-TREE requires coding the data as 0 and 1 rather than R and Y; the popular PAUP* software package can interpret a data matrix comprising only R and Y as data to be analyzed using the CFN model). It is also straightforward to analyze binary data using the phylogenetic Hadamard transform. The alternative two-state model allows the equilibrium frequency parameters of R and Y (or 0 and 1) to take on values other than 0.5 by adding single free parameter; this model is variously called CFu or GTR2 (in IQ-TREE).
Other recoding methods are WS (weak-strong) and MK (amino-keto).
== Lie Markov models ==
Lie Markov models are, from a mathematical point of view, Markov models that form a Lie algebra. For the mathematician, this makes them closed under matrix multiplication. From a phylogeneticist's point of view, these models have the benefit of being able to add or remove taxa without affecting the site patterns that the model can generate over the remaining taxa. There is also a natural hierarchy of models based on how many parameters can be changed. Some exsiting models such as JC and F81 are already Lie Markov models, while GTR is not. Lie Markov models (with RY, WS, or MK) are available in IQ-TREE.
== See also ==
Molecular evolution
Molecular clock
UPGMA
== References ==
=== Further reading ===
== External links ==
DAWG: DNA Assembly With Gaps — free software for simulating sequence evolution | Wikipedia/Models_of_DNA_evolution |
Mouse models of colorectal cancer and intestinal cancer are experimental systems in which mice are genetically manipulated, fed a modified diet, or challenged with chemicals to develop malignancies in the gastrointestinal tract. These models enable researchers to study the onset, progression of the disease, and understand in depth the molecular events that contribute to the development and spread of colorectal cancer. They also provide a valuable biological system, to simulate human physiological conditions, suitable for testing therapeutics.
== Colorectal and intestinal cancer ==
=== Familial Adenomatous Polyposis ===
Familial Adenomatous Polyposis (FAP) is a hereditary disease that is characterized with development of numerous colon polyps. A genetic analysis of some FAP kindreds revealed that a common feature of the disease is a deletion of the APC gene. Further analysis of the APC gene revealed the existence of various mutations in cancer sufferers that also play a role in the onset of the sporadic form of colorectal cancer.
==== APC mutant mice ====
The first mouse mutant in the Apc gene came from a colony of randomly mutagenized mice. This mouse model is called Min (multiple intestinal neoplasia) mouse. It was found to carry a truncation mutation at codon 850 of the Apc gene. The Min mouse can develop up to 100 polyps in the small intestine in addition to colon tumors. Later, new knock-out mutants of the Apc gene were engineered. A truncating mutation at codon 716 (ApcΔ716) results in a mouse that develops more than 300 polyps in the small intestine, while truncation at codon 1638 (Apc1638N) results in the formation of about only 3 polyps in the same region of the gastrointestinal tract. More recently a new mutant Apc mouse model was constructed in which multiple polyps form in the distal colon. In this model mutation in the Cdx2 gene in the ApcΔ716 mouse model shifted the formation of the polyps from the intestine to the colon, resembling the human FAP. The Apc mutant mice are characterized by early lethality. There are genes modifying the cancer susceptibility of these mouse models. The most well-established is the modifier of Min locus (Mom1). With combination of Min and Mom1 mutations the lifespan of FAP mouse models of colorectal cancer is increased.
APC was found to associate with catenins. Today we know that the beta-catenin protein (part of the Wnt signaling pathway) is implicated in colorectal carcinogenesis and its stability in the cell is regulated by APC. A mouse model with deregulation of beta-catenin levels was created. The conditional stabilizing mutation in the beta-catenin gene caused formation of up to 3000 polyps in the small intestine of this mouse model.
A mouse model carrying mutations in ApcΔ716 and Smad4 (mothers against decapentaplegic homolog 4) is characterized with development of invasive adenocarcinomas.
=== Hereditary nonpolyposis colorectal cancer ===
The most frequent mutations in Hereditary nonpolyposis colorectal cancer (HNPCC) are mutations in the MSH2 and MLH1 genes. These genes play an important role in repairing incorrectly positioned nucleotides. Another gene involved in DNA mismatch repair is Msh6. Both the Msh6 and Msh2 mutant mice develop gastrointestinal cancer but the tumours differ in their microsatellite instability (MI) status. While MSH2 deficiency promotes MI-high tumours, MSH6 deficiency results in MI-low tumours. Another component of the DNA repair machinery in the cell is the protein MLH1. Ablation of MLH1 in mice causes development of gastrointestinal tumours in the small intestine – adenomas and invasive carcinomas. The combination of MLH1 deficiency with the Apc1638N mutant mouse results in strong reduction of viability and increased tumour burden. The tumours were classified as adenomas, invasive adenocarcinomas and late stage carcinomas. Similarly, mice deficient for Msh2 combined with Apc Min demonstrate accelerated rate of tumorigenesis. Another similar mouse model of HNPCC is the combination of PMS2 mutant mouse with the Min Apc allele resulting in increased number of tumours in the gastrointestinal tract compared to Min. Yet these adenocarcinomas do not metastasize and their histopathology is similar to that of the right side colon cancer in human with frequent mutation of the type II receptor for TGF-β.
=== Mutations in other genes ===
Mice with mutations in transforming growth factor-β1 gene introduced into 129/Sv Rag2 mutant mouse accelerates adenocarcinomas with strong local invasion suggesting a role for genetic background in tumor development. Colon-specific expression of activated mutant of K-ras (protein)
(K-rasG12D) results in development of single or multiple lesions. Oncogenic K-rasG12D allele activated in colon epithelium induces expression of procarcinogenic protein kinase C-βII (PKCβII) and increases cell proliferation of epithelial cells, while in the distal colon the mutant form of K-ras has the opposite effects on PKCβII expression and cell proliferation. Treatment of this mouse model with the procarcinogen azoxymethane (AOM) leads to formation of dysplastic microadenomas in the proximal but not in the distal colon. Thus the K-rasG12D mutant is a valuable mouse model of proximal colon carcinogenesis. Mutation in the Muc2 gene causes adenomas and adenocarcinomas in the intestine of mice.
=== Inflammation related colon cancer ===
Human inflammatory bowel disease is a group of inflammatory conditions in the large and small intestine. It is well known that chronic inflammation in the colon can lead to cancer. There are genetic mouse models for inflammatory bowel disease associated colon cancer. Interleukin 10 knock out mice develop invasive adenocarcinoma in the colon. Mutant mice for interleukin 2 and beta microglobulin genes also produce ulcerative colitis-like phenotype and develop adenocarcinomas in the colon. A mouse mutant for N-cadherin suffers inflammatory bowel disease conditions and adenomas but does not develop carcinomas.
== Diet-related model ==
Humans with high levels of the diet-related bile acid deoxycholate (DOC) in their colons are at a substantially increased risk of developing colon cancer (see Bile acids and colon cancer). A diet-related mouse model of colon cancer was devised. In this model, wild type mice are fed a standard diet plus DOC to give a level of DOC in mouse colon comparable to that in the colons of humans on a high fat diet. After 8–10 months, 45% to 56% of the mice developed colonic adenocarcinomas, and no mice had cancers of the small intestine.
On the basis of histopathology and by expression of specific markers, the colonic tumors in the mice were virtually identical to those in humans. In humans, characteristic aberrant changes in molecular markers are detected both in field defects surrounding cancers (from which the cancers arise) and within cancers. In the colonic tissues of mice fed diet plus DOC similar changes in biomarkers occurred. Thus, 8-OH-dG was increased, DNA repair protein ERCC1 was decreased, autophagy protein beclin-1 was increased and, in the stem cell region at the base of crypts, there was substantial nuclear localization of beta-catenin as well as increased cytoplasmic beta-catenin. However, in mice fed diet plus DOC plus the antioxidant chlorogenic acid, the frequency of colon cancer was reduced. Furthermore, when evaluated for ERCC1, beclin-1, and beta-catenin in the stem cell region of crypts, the colonic tissues of chlorogenic acid-fed mice showed amelioration of the molecular aberrancies, suggesting that chlorogenic acid is protective at the molecular level against colon cancer. This is the first diet-related model of colon cancer that closely parallels human progression to colon cancer, both at the histopathology level as well as in its molecular profile.
== Chemically-induced colorectal cancer ==
Azoxymethane (AOM) is a genotoxic colonic carcinogen and is routinely used to induce colon tumours in mice. The AOM-induced tumours form in the last three centimeters of the distal colon but a p21 knock out mouse treated with AOM shows tumour distribution throughout the colon. AOM-induced tumours are characterized with mutations in the Apc gene.
A novel inflammation-related mouse model of colorectal carcinogenesis combines AOM and dextran sodium sulphate (DSS) to induce colon lesions, positive for beta-catenin, COX-2 and inducible nitric oxide synthase.
== See also ==
Mouse models of breast cancer metastasis
== References == | Wikipedia/Mouse_model_of_colorectal_and_intestinal_cancer |
Model organism databases (MODs) are biological databases, or knowledgebases, dedicated to the provision of in-depth biological data for intensively studied model organisms. MODs allow researchers to easily find background information on large sets of genes, efficiently plan experiments, integrate their data with existing knowledge, and formulate new hypotheses . They allow users to analyse results and interpret datasets, and the data they generate are increasingly used to describe less well studied species. Where possible, MODs share common approaches to collect and represent biological information. For example, all MODs use the Gene Ontology (GO) to describe functions, processes and cellular locations of specific gene products. Projects also exist to enable software sharing for curation, visualization and querying between different MODs. Organismal diversity and varying user requirements however mean that MODs are often required to customize capture, display, and provision of data.
== Types of data and services ==
Model organism databases generate, source and collate species-specific information integratively by combining expert knowledge with literature curation and bioinformatics.
Services provided to biological research communities include:
Genome sequence annotations
Location of genes and regulatory regions in the genome
Functional curation of gene products
Discern functions fulfilled by the gene product by looking at a variety of data including Gene Ontology (GO) annotations, phenotypes, gene expression, pathway information
Protein/RNA sequence annotations
Anatomical information
Stock centres
Orthology
== List of model organism databases ==
== References == | Wikipedia/Model_organism_databases |
Junk DNA (non-functional DNA) is a DNA sequence that has no known biological function. Most organisms have some junk DNA in their genomes—mostly pseudogenes and fragments of transposons and viruses—but it is possible that some organisms have substantial amounts of junk DNA.
All protein-coding regions are generally considered to be functional elements in genomes. Additionally, non-protein coding regions such as genes for ribosomal RNA and transfer RNA, regulatory sequences, origins of replication, centromeres, telomeres, and scaffold attachment regions are considered as functional elements. (See Non-coding DNA for more information.)
It is difficult to determine whether other regions of the genome are functional or nonfunctional. There is considerable controversy over which criteria should be used to identify function. Many scientists have an evolutionary view of the genome and they prefer criteria based on whether DNA sequences are preserved by natural selection. Other scientists dispute this view or have different interpretations of the data.
== History ==
The idea that only a fraction of the human genome could be functional dates back to the late 1940s. The estimated mutation rate in humans suggested that if a large fraction of those mutations were deleterious then the human species could not survive such a mutation load (genetic load). This led to predictions in the late 1940s by one of the founders of population genetics, J.B.S. Haldane, and by Nobel laureate Hermann Muller, that only a small percentage of the human genome contains functional DNA elements (genes) that can be destroyed by mutation. (see Genetic load for more information)
In 1966 Muller reviewed these predictions and concluded that the human genome could only contain about 30,000 genes based on the number of deleterious mutations that the species could tolerate. Similar predictions were made by other leading experts in molecular evolution who concluded that the human genome could not contain more than 40,000 genes and that less than 10% of the genome was functional.
The size of genomes in various species was known to vary considerably and there did not seem to be a correlation between genome size and the complexity of the species. Even closely related species could have very different genome sizes. This observation led to what came to be known as the C-value paradox. The paradox was resolved with the discovery of repetitive DNA and the observation that most of the differences in genome size could be attributed to repetitive DNA. Some scientists thought that most of the repetitive DNA was involved in regulating gene expression but many scientists thought that the excess repetitive DNA was nonfunctional.
At about the same time (late 1960s) the newly developed technique of C0t analysis was refined to include RNA:DNA hybridization leading to the discovery that considerably less than 10% of the human genome was complementary to mRNA and this DNA was in the unique (non-repetitive) fraction. This confirmed the predictions made from genetic load arguments and was consistent with the idea that much of the repetitive DNA is nonfunctional.
The idea that large amounts of eukaryotic genomes could be nonfunctional conflicted with the prevailing view of evolution in 1968 since it seemed likely that nonfunctional DNA would be eliminated by natural selection. The development of the neutral theory and the nearly neutral theory provided a way out of this problem since it allowed for the preservation of slightly deleterious nonfunctional DNA in accordance with fundamental principles of population genetics.
The term "junk DNA" began to be used in the late 1950s but Susumu Ohno popularized the term in a 1972 paper titled "So much 'junk' DNA in our genome" where he summarized the current evidence that had accumulated by then. In a second paper that same year, he concluded that 90% of mammalian genomes consisted of nonfunctional DNA. The case for junk DNA was summarized in a lengthy paper by David Comings in 1972 where he listed four reasons for proposing junk DNA:
some organisms have a lot more DNA than they seem to require (C-value paradox),
current estimates of the number of genes (in 1972) are much less than the number that can be accommodated,
the mutation load would be too large if all the DNA were functional, and
some junk DNA clearly exists.
The discovery of introns in the 1970s seemed to confirm the views of junk DNA proponents because it meant that genes were very large and even huge genomes could not accommodate large numbers of genes. The proponents of junk DNA tended to dismiss intron sequences as mostly nonfunctional DNA (junk) but junk DNA opponents advanced a number of hypotheses attributing functions of various sort to intron sequences.
By 1980 it was apparent that most of the repetitive DNA in the human genome was related to transposons. This prompted a series of papers and letters describing transposons as selfish DNA that acted as a parasite in genomes and produced no fitness advantage for the organism.
Opponents of junk DNA interpreted these results as evidence that most of the genome is functional and they developed several hypotheses advocating that transposon sequences could benefit the organism or the species. The most important opponent of junk DNA at this time was Thomas Cavalier-Smith who argued that the extra DNA was required to increase the volume of the nucleus in order to promote more efficient transport across the nuclear membrane.
The positions of the two sides of the controversy hardened with one side believing that evolution was consistent with large amounts of junk DNA and the other side believing that natural selection should eliminate junk DNA. These differing views of evolution were highlighted in a letter from Thomas Jukes, a proponent of junk DNA, to Francis Crick on December 20, 1979:
"Dear Francis, I am sure that you realize how frightfully angry a lot of people will be if you say that much of the DNA is junk. The geneticists will be angry because they think that DNA is sacred. The Darwinian evolutionists will be outraged because they believe every change in DNA that is accepted in evolution is necessarily an adaptive change. To suggest anything else is an insult to the sacred memory of Darwin."
The other point of view was expressed by Roy John Britten and Kohne in their seminal paper on repetitive DNA.
"A concept that is repugnant to us is that about half of the DNA of higher organisms is trivial or permanently inert (on an evolutionary timescale)."
== Junk DNA and non-coding DNA ==
There is considerable confusion in the popular press and in the scientific literature about the distinction between non-coding DNA and junk DNA.
According to an article published in 2021 in American Scientist:
Close to 99 percent of our genome has been historically classified as noncoding, useless "junk" DNA. Consequently, these sequences were rarely studied.
A book published in 2020 states:
When it was first discovered, the nongenic DNA was sometimes called—somewhat derisively by people who did not know better—"junk DNA" because it had no obvious utility, and they foolishly assumed that if it was not carrying coding information it must be useless trash.
The common theme is that the original proponents of junk DNA thought that all non-coding DNA was junk. This claim has been attributed to a paper by David Comings in 1972 where he is reported to have said that junk DNA refers to all non-coding DNA. But Comings never said that. In that paper he discusses non-coding genes for ribosomal RNA and tRNAs and non-coding regulatory DNA and he proposes several possible functions for the bulk of non-coding DNA. In another publication from the same year Comings again discusses the term junk DNA with the clear understanding that it does not include non-coding regulatory sequences.
The idea that all non-coding DNA was thought to be junk has been criticized by numerous authors for distorting the history of junk DNA; for example:
It is simply not true that noncoding DNA has long been dismissed as worthless junk and that functional hypotheses have only recently been proposed - despite the frequency with which this cliché is repeated in media reports and in the introduction of far too many scientific studies.
Some of the criticisms have been strong:
Revisionist claims that equate noncoding DNA with junk merely reveal that people who are allowed to exhibit their logorrhea in Nature and other glam journals are as ignorant as the worst young-earth creationists.
== Functional vs non-functional ==
The main challenge of identifying junk DNA is to distinguish between "functional" and "non-functional" sequences. This is non-trivial, but there is some good evidence for both categories.
=== Functional ===
Protein-coding sequences are the most obvious functional sequences in genomes. However, they make up only 1-2% of most vertebrate genomes. However, there are also functional but non-coding DNA sequences such as regulatory sequences, origins of replication, and centromeres. These sequences are usually conserved in evolution and make up another 3-8% of the human genome.
The Encyclopedia of DNA Elements (ENCODE) project reported that detectable biochemical activity was observed in regions covering at least 80% of the human genome, with biochemical activity defined primarily as being transcribed. While these findings were announced as the demise of junk DNA it is important to point out that transcription does not mean a sequence is "functional", analogous to some meaningless text that can be transcribed or copied without having any meaning.
=== Non-functional ===
Non-functional DNA is rare in bacterial genomes which typically have an extremely high gene density, with only a few percent being not protein-coding.
However, in most animal or plant genomes, a large fraction of DNA is non-functional, given that there is no obvious selective pressure on these sequences. More importantly, there is strong evidence that these sequences are not functional in other ways (using the human genome as example):
(1) Repetitive elements, especially mobile elements make up a large fraction of the human genome, such as LTR retrotransposons (8.3% of total genome), SINEs (13.1% of total genome) including Alu elements, LINEs (20.4% of total genome), SVAs (SINE-VNTR-Alu) and Class II DNA transposons (2.9% of total genome). Many of these sequences are the descendents of ancient virus infections and are thus "non-functional" in terms of human genome function.
(2) Many sequences can be deleted as shown by comparing genomes. For instance, an analysis of 14,623 individuals identified 42,765 structural variants in the human genome of which 23.4% affected multiple genes (by deleting them or part of them). This study also found 47 deletions of >1 MB, showing that large chunks of the human genome can get deleted without obvious consequences.
(3) Only a small fraction of the human genome is conserved, indicating that there is no strong (functional) selection pressure on these sequences, so they can rather freely mutate. About 11% or less of the human genome is conserved and about 7% is under purifying selection.
Opponents of junk DNA argue that biochemical activity detects functional regions of the genome that are not identified by sequence conservation or purifying selection. According to some scientists, until a region in question has been shown to have additional features, beyond what is expected of the null hypothesis, it should provisionally be labelled as non-functional.
== See also ==
ENCODE Project
Human genome
Comparative genomics
Non-coding DNA
Non-coding RNA
== References == | Wikipedia/Junk_DNA |
An autoimmune disease is a condition that results from an anomalous response of the adaptive immune system, wherein it mistakenly targets and attacks healthy, functioning parts of the body as if they were foreign organisms. It is estimated that there are more than 80 recognized autoimmune diseases, with recent scientific evidence suggesting the existence of potentially more than 100 distinct conditions. Nearly any body part can be involved.
Autoimmune diseases are a separate class from autoinflammatory diseases. Both are characterized by an immune system malfunction which may cause similar symptoms, such as rash, swelling, or fatigue, but the cardinal cause or mechanism of the diseases is different. A key difference is a malfunction of the innate immune system in autoinflammatory diseases, whereas in autoimmune diseases there is a malfunction of the adaptive immune system.
Symptoms of autoimmune diseases can significantly vary, primarily based on the specific type of the disease and the body part that it affects. Symptoms are often diverse and can be fleeting, fluctuating from mild to severe, and typically comprise low-grade fever, fatigue, and general malaise. However, some autoimmune diseases may present with more specific symptoms such as joint pain, skin rashes (e.g., urticaria), or neurological symptoms.
The exact causes of autoimmune diseases remain unclear and are likely multifactorial, involving both genetic and environmental influences. While some diseases like lupus exhibit familial aggregation, suggesting a genetic predisposition, other cases have been associated with infectious triggers or exposure to environmental factors, implying a complex interplay between genes and environment in their etiology.
Some of the most common diseases that are generally categorized as autoimmune include coeliac disease, type 1 diabetes, Graves' disease, inflammatory bowel diseases (such as Crohn's disease and ulcerative colitis), multiple sclerosis, alopecia areata, Addison's disease, pernicious anemia, psoriasis, rheumatoid arthritis, and systemic lupus erythematosus. Diagnosing autoimmune diseases can be challenging due to their diverse presentations and the transient nature of many symptoms.
Treatment modalities for autoimmune diseases vary based on the type of disease and its severity. Therapeutic approaches primarily aim to manage symptoms, reduce immune system activity, and maintain the body's ability to fight diseases. Nonsteroidal anti-inflammatory drugs (NSAIDs) and immunosuppressants are commonly used to reduce inflammation and control the overactive immune response. In certain cases, intravenous immunoglobulin may be administered to regulate the immune system. Despite these treatments often leading to symptom improvement, they usually do not offer a cure and long-term management is often required.
In terms of prevalence, a UK study found that 10% of the population were affected by an autoimmune disease. Women are more commonly affected than men. Autoimmune diseases predominantly begin in adulthood, although they can start at any age. The initial recognition of autoimmune diseases dates back to the early 1900s, and since then, advancements in understanding and management of these conditions have been substantial, though much more is needed to fully unravel their complex etiology and pathophysiology.
== Signs and symptoms ==
Autoimmune diseases represent a vast and diverse category of disorders that, despite their differences, share some common symptomatic threads. These shared symptoms occur as a result of the body's immune system mistakenly attacking its own cells and tissues, causing inflammation and damage. However, due to the broad range of autoimmune diseases, the specific presentation of symptoms can significantly vary based on the type of disease, the organ systems affected, and individual factors such as age, sex, hormonal status, and environmental influences.
An individual may simultaneously have more than one autoimmune disease (known as polyautoimmunity), further complicating the symptomatology.
=== Common symptoms ===
Symptoms that are commonly associated with autoimmune diseases include:
fatigue. This is the most common complaint of people with autoimmune disease. A 2015 US survey found that 98% of people with autoimmune diseases experienced fatigue, 89% said it was a "major issue", 68% said "fatigue is anything but normal. It is profound and prevents [them] from doing the simplest everyday tasks." and 59% said it was "probably the most debilitating symptom of having an [autoimmune disease]."
low-grade fever
malaise (a general feeling of discomfort or unease)
muscle aches
joint pain
skin rashes
Autoimmune diseases can present a diverse array of symptoms. For instance, some people may experience dry mouth or dry eyes, tingling or numbness in various body parts, unexpected changes in weight, and diarrhea.
=== Patterns of symptom occurrence ===
These symptoms often reflect the body's systemic inflammatory response. However, their occurrence and intensity can fluctuate over time, leading to periods of heightened disease activity, referred to as flare-ups, and periods of relative inactivity, known as remissions.
The specific presentation of symptoms largely depends on the location and type of autoimmune response. For instance, in rheumatoid arthritis, an autoimmune disease primarily affecting the joints, symptoms typically include joint pain, swelling, and stiffness. On the other hand, type 1 diabetes, which results from an autoimmune attack on the insulin-producing cells of the pancreas, primarily presents with symptoms related to high blood sugar, such as increased thirst, frequent urination, and unexplained weight loss.
=== Commonly affected body areas ===
Commonly affected areas in autoimmune diseases include blood vessels, connective tissues, joints, muscles, red blood cells, skin, and endocrine glands such as the thyroid gland (in diseases like Hashimoto's thyroiditis and Graves' disease) and the pancreas (in type 1 diabetes). The impacts of these diseases can range from localized damage to certain tissues, alteration in organ growth and function, to more systemic effects when multiple tissues throughout the body are affected.
=== Value of tracking symptom occurrence ===
The appearance of these signs and symptoms can not only provide clues for the diagnosis of an autoimmune condition, often in conjunction with tests for specific biological markers, but also help monitor disease progression and response to treatment. Ultimately, due to the diverse nature of autoimmune diseases, a multidimensional approach is often needed for the management of these conditions, taking into consideration the variety of symptoms and their impacts on individuals' lives.
== Types ==
While it is estimated that over 80 recognized types of autoimmune diseases exist, this section provides an overview of some of the most common and well-studied forms.
=== Coeliac disease ===
Coeliac disease is an immune reaction to eating gluten, a protein found in wheat, barley, and rye. For those with the disease, eating gluten triggers an immune response in the small intestine, leading to damage on the villi, small fingerlike projections that line the small intestine and promote nutrient absorption. This explains the increased risk of gastrointestinal cancers, as the gastrointestinal tract includes the esophagus, stomach, small intestine, large intestine, rectum, and anus, all areas that the ingested gluten would traverse in digestion. The incidence of gastrointestinal cancer can be partially reduced or eliminated if a patient removes gluten from their diet. Additionally, coeliac disease is correlated with lymphoproliferative disorders.
=== Graves' disease ===
Graves' disease is a condition characterized by development of autoantibodies to thyroid-stimulating hormone receptors. The binding of the autoantibodies to the receptors results in unregulated production and release of thyroid hormone, which can lead to stimulatory effects such as rapid heart rate, weight loss, nervousness, and irritability. Other symptoms more specific to Graves' disease include bulging eyes and swelling of the lower legs.
=== Inflammatory bowel disease ===
Inflammatory bowel disease encompasses conditions characterized by chronic inflammation of the digestive tract, including Crohn's disease and ulcerative colitis. In both cases, individuals lose immune tolerance for normal bacteria present in the gut microbiome. Symptoms include severe diarrhea, abdominal pain, fatigue, and weight loss. Inflammatory bowel disease is associated with cancers of the gastrointestinal tract and some lymphoproliferative cancers.
=== Multiple sclerosis ===
Multiple sclerosis (MS) is a neurodegenerative disease in which the immune system attacks myelin, a protective covering of nerve fibers in the central nervous system, causing communication problems between the brain and the rest of the body. Symptoms can include fatigue, difficulty walking, numbness or tingling, muscle weakness, and problems with coordination and balance. MS is associated with an increased risk of central nervous system cancer, primarily in the brain.
=== Rheumatoid arthritis ===
Rheumatoid arthritis (RA) primarily targets the joints, causing persistent inflammation that results in joint damage and pain. It is often symmetrical, meaning that if one hand or knee has it, the other one does too. RA can also affect the heart, lungs, and eyes. Additionally, the chronic inflammation and over-activation of the immune system creates an environment that favors further malignant transformation of other cells, perhaps explaining the associations with cancer of the lungs and skin as well as the increased risk of other hematologic cancers, none of which are directly affected by the inflammation of joints.
=== Psoriasis and psoriatic arthritis ===
Psoriasis is a skin condition characterized by the rapid buildup of skin cells, leading to scaling on the skin's surface. Inflammation and redness around the scales is common. Some individuals with psoriasis also develop psoriatic arthritis, which causes joint pain, stiffness, and swelling.
=== Sjögren's syndrome ===
Sjögren syndrome is a long-term autoimmune disease that affects the body's moisture-producing glands (lacrimal and salivary), and often seriously affects other organ systems, such as the lungs, kidneys, and nervous system.
=== Systemic lupus erythematosus ===
Systemic lupus erythematosus, referred to simply as lupus, is a systemic autoimmune disease that affects multiple organs, including the skin, joints, kidneys, and the nervous system. It is characterized by a widespread loss of immune tolerance. The disease is characterized by periods of flares and remissions, and symptoms range from mild to severe. Women, especially those of childbearing age, are disproportionately affected.
=== Type 1 diabetes ===
Type 1 diabetes is a condition resulting from the immune system attacking insulin-producing beta cells in the pancreas, leading to high blood sugar levels. Symptoms include increased thirst, frequent urination, and unexplained weight loss. It is most commonly diagnosed in children and young adults.
=== Undifferentiated connective tissue disease ===
Undifferentiated connective tissue disease occurs when people have features of connective tissue disease, such as blood test results and external characteristics, but do not fulfill the diagnostic criteria established for any one connective tissue disease. Some 30–40% transition to a specific connective tissue disease over time.
== Causes ==
The exact causes of autoimmune diseases remain largely unknown; however, research has suggested that a combination of genetic, environmental, and hormonal factors, as well as certain infections, may contribute to the development of these disorders.
The human immune system is equipped with several mechanisms to maintain a delicate balance between defending against foreign invaders and protecting its own cells. To achieve this, it generates both T cells and B cells, which are capable of reacting with self-proteins. However, in a healthy immune response, self-reactive cells are generally either eliminated before they become active, rendered inert via a process called anergy, or their activities are suppressed by regulatory cells.
=== Genetics ===
A familial tendency to develop autoimmune diseases suggests a genetic component. Some conditions, like lupus and multiple sclerosis, often occur in several members of the same family, indicating a potential hereditary link. Additionally, certain genes have been identified that increase the risk of developing specific autoimmune diseases.
==== Genetic predisposition ====
Evidence suggests a strong genetic component in the development of autoimmune diseases. For instance, conditions such as lupus and multiple sclerosis frequently appear in multiple members of the same family, signifying a potential hereditary link. Furthermore, certain genes have been identified that augment the risk of developing specific autoimmune diseases.
Experimental methods like genome-wide association studies have proven instrumental in pinpointing genetic risk variants potentially responsible for autoimmune diseases. For example, these studies have been used to identify risk variants for diseases such as type 1 diabetes and rheumatoid arthritis.
In twin studies, autoimmune diseases consistently demonstrate a higher concordance rate among identical twins compared with fraternal twins. For instance, the rate in multiple sclerosis is 35% in identical twins compared to 6% in fraternal twins.
==== Balancing infection and autoimmunity ====
There is increasing evidence that certain genes selected during evolution offer a balance between susceptibility to infection and the capacity to avoid autoimmune diseases. For example, variants in the ERAP2 gene provide some resistance to infection even though they increase the risk of autoimmunity (positive selection). In contrast, variants in the TYK2 gene protect against autoimmune diseases but increase the risk of infection (negative selection). This suggests the benefits of infection resistance may outweigh the risks of autoimmune diseases, particularly given the historically high risk of infection.
Several experimental methods such as the genome-wide association studies have been used to identify genetic risk variants that may be responsible for diseases such as type 1 diabetes and rheumatoid arthritis.
=== Environmental factors ===
A significant number of environmental factors have been implicated in the development and progression of various autoimmune diseases, either directly or as catalysts. Current research suggests that up to seventy percent of autoimmune diseases could be attributed to environmental influences, which encompass an array of elements such as chemicals, infectious agents, dietary habits, and gut dysbiosis. However, a unifying theory that definitively explains the onset of autoimmune diseases remains elusive, emphasizing the complexity and multifaceted nature of these conditions.
Various environmental triggers are identified, some of which include:
Impaired oral tolerance
Gut dysbiosis
Increased gut permeability
Heightened immune reactivity
Chemicals, which are either a part of the immediate environment or found in drugs, are key players in this context. Examples of such chemicals include hydrazines, hair dyes, trichloroethylene, tartrazines, hazardous wastes, and industrial emissions.
Ultraviolet radiation has been implicated as a potential causative factor in the development of autoimmune diseases, such as dermatomyositis. Furthermore, exposure to pesticides has been linked with an increased risk of developing rheumatoid arthritis. Vitamin D, on the other hand, appears to play a protective role, particularly in older populations, by preventing immune dysfunctions.
Infectious agents are also being increasingly recognized for their role as T cell activators — a crucial step in triggering autoimmune diseases. The exact mechanisms by which they contribute to disease onset remain to be fully understood. For instance, certain autoimmune conditions like Guillain-Barre syndrome and rheumatic fever are thought to be triggered by infections. Furthermore, analysis of large-scale data has revealed a significant link between SARS-CoV-2 infection (the causative agent of COVID-19) and an increased risk of developing a wide range of new-onset autoimmune diseases.
=== Gender ===
Women typically make up some 80% of autoimmune disease patients. Whilst many proposals have been made for the cause of this high weighting, no clear explanation is available. A possible role for hormonal factors has been suggested. For example, some autoimmune diseases tend to flare during pregnancy (possibly as an evolutionary mechanism to increase health protection for the child), when hormone levels are high, and improve after menopause, when hormone levels decrease. Women may also naturally have autoimmune disease trigger events in puberty and pregnancy. Under-reporting by men may also be a factor, as men may interact less with the health system than women.
=== Infections ===
Certain viral and bacterial infections have been linked to autoimmune diseases. For instance, research suggests that the bacterium that causes strep throat, Streptococcus pyogenes, might trigger rheumatic fever, an autoimmune response affecting the heart. Similarly, some studies propose a link between the Epstein–Barr virus, responsible for mononucleosis, and the subsequent development of multiple sclerosis or lupus.
=== Dysregulated immune response ===
Another area of interest is the immune system's ability to distinguish between self and non-self, a function that is compromised in autoimmune diseases. In healthy individuals, immune tolerance prevents the immune system from attacking the body's own cells. When this process fails, the immune system may produce antibodies against its own tissues, leading to an autoimmune response.
=== Negative selection and the role of the thymus ===
The elimination of self-reactive T cells occurs primarily through a mechanism known as "negative selection" within the thymus, an organ responsible for the maturation of T cells. This process serves as a key line of defense against autoimmunity. If these protective mechanisms fail, a pool of self-reactive cells can become functional within the immune system, contributing to the development of autoimmune diseases.
=== Molecular mimicry ===
Some infectious agents, like Campylobacter jejuni, bear antigens that resemble, but are not identical to, the body's self-molecules. This phenomenon, known as molecular mimicry, can lead to cross-reactivity, where the immune response to such infections inadvertently results in the production of antibodies that also react with self-antigens. An example of this is Guillain–Barré syndrome, in which antibodies generated in response to a C. jejuni infection also react with the gangliosides in the myelin sheath of peripheral nerve axons.
== Diagnosis ==
Diagnosing autoimmune disorders can be complex due to the wide range of diseases within this category and their often overlapping symptoms. Accurate diagnosis is crucial for determining appropriate treatment strategies. Generally, the diagnostic process involves a combination of medical history evaluation, physical examination, laboratory tests, and, in some cases, imaging or biopsies.
=== Medical history and examination ===
The first step in diagnosing autoimmune disorders typically involves a thorough evaluation of the patient's medical history and a comprehensive physical examination. Clinicians often pay close attention to the patient's symptoms, family history of autoimmune diseases, and any exposure to environmental factors that might trigger an autoimmune response. The physical examination can reveal signs of inflammation or organ damage, which are common features of autoimmune disorders.
=== Laboratory tests ===
Laboratory testing plays a pivotal role in the diagnosis of autoimmune diseases. These tests can identify the presence of certain autoantibodies or other immune markers that indicate a self-directed immune response.
Autoantibody testing: Many autoimmune diseases are characterized by the presence of autoantibodies. Blood tests can identify these antibodies, which are directed against the body's own tissues. For example, antinuclear antibody (ANA) testing is commonly used in the diagnosis of systemic lupus erythematosus and other autoimmune diseases.
Complete Blood Count: Blood counts can provide valuable information about the number and characteristics of different blood cells, which can be affected in some autoimmune diseases.
C-Reactive Protein and Erythrocyte Sedimentation Rate: These tests measure the levels of inflammation in the body, which is often elevated in autoimmune disorders.
Organ-specific tests: Certain autoimmune diseases target specific organs, so tests to evaluate the function of these organs can aid in diagnosis. For example, thyroid function tests are used in diagnosing autoimmune thyroid disorders, while a biopsy can diagnose coeliac disease by identifying damage to the small intestine.
=== Imaging studies ===
In some cases, imaging studies may be used to assess the extent of organ involvement and damage. For example, chest x-rays or CT scans can identify lung involvement in diseases like rheumatoid arthritis or systemic lupus erythematosus, while an MRI can reveal inflammation or damage in the brain and spinal cord in multiple sclerosis.
=== Differential diagnosis ===
Given the variety and nonspecific nature of symptoms that can be associated with autoimmune diseases, differential diagnosis—determining which of several diseases with similar symptoms is causing a patient's illness—is an important part of the diagnostic process. This often involves ruling out other potential causes of symptoms, such as infections, malignancies, or genetic disorders.
=== Multidisciplinary approach ===
Given the systemic nature of many autoimmune disorders, a multidisciplinary approach may be necessary for their diagnosis and management. This can involve rheumatologists, endocrinologists, gastroenterologists, neurologists, dermatologists, and other specialists, depending on the organs or systems affected by the disease.
In summary, the diagnosis of autoimmune disorders is a complex process that requires a thorough evaluation of clinical, laboratory, and imaging data. Due to the diverse nature of these diseases, an individualized approach, often involving multiple specialists, is crucial for an accurate diagnosis.
== Treatment ==
Treatment depends on the type and severity of the condition. The majority of the autoimmune diseases are chronic and there is no definitive cure, but symptoms can be alleviated and controlled with treatment.
Standard treatment methods include:
Vitamin or hormone supplements for what the body is lacking due to the disease (insulin, vitamin B12, thyroid hormone, etc.)
Blood transfusions if the disease is blood related
Physical therapy if the disease impacts bones, joints, or muscles
Pharmaceutical treatment options include immunosuppressant drugs to reduce the immune response against the body's own tissues, such as:
Non-steroidal anti-inflammatory drugs (NSAIDs) to reduce inflammation
Glucocorticoids to reduce inflammation
Disease-modifying anti-rheumatic drugs (DMARDs) to decrease the damaging tissue and organ effects of the inflammatory autoimmune response
Because immunosuppressants weaken the overall immune response, relief of symptoms must be balanced with preserving the patient's ability to combat infections, which could potentially be life-threatening.
Non-traditional treatments are being researched, developed, and used, especially when traditional treatments fail. These methods aim to either block the activation of pathogenic cells in the body, or alter the pathway that suppresses these cells naturally. These treatments aim to be less toxic to the patient and have more specific targets. Such options include:
Monoclonal antibodies that can be used to block pro-inflammatory cytokines
Antigen-specific immunotherapy which allows immune cells to specifically target the abnormal cells that cause autoimmune disease
Co-stimulatory blockade that works to block the pathway that leads to the autoimmune response
Regulatory T cell therapy that utilizes this special type of T cell to suppress the autoimmune response
Thymoquinone, a compound found in the flower Nigella sativa, has been studied for potential in treating several autoimmune diseases due to its effects on inflammation.
== Epidemiology ==
The first estimate of US prevalence for autoimmune diseases as a group was published in 1997 by Jacobson, et al. They reported US prevalence to be around 9 million, applying prevalence estimates for 24 diseases to a US population of 279 million. Jacobson's work was updated by Hayter & Cook in 2012. This study used Witebsky's postulates, as revised by Rose & Bona, to extend the list to 81 diseases and estimated overall cumulative US prevalence for the 81 autoimmune diseases at 5.0%, with 3.0% for males and 7.1% for females.
The estimated community prevalence, which takes into account the observation that many people have more than one autoimmune disease, was 4.5% overall, with 2.7% for males and 6.4% for females.
A 2024 estimate was that 1 in 15 people in the U.S. had at least one autoimmune disease.
== Research ==
In both autoimmune and inflammatory diseases, the condition arises through aberrant reactions of the human adaptive or innate immune systems. In autoimmunity, the patient's immune system is activated against the body's own proteins. In chronic inflammatory diseases, neutrophils and other leukocytes are constitutively recruited by cytokines and chemokines, resulting in tissue damage.
Mitigation of inflammation by activation of anti-inflammatory genes and the suppression of inflammatory genes in immune cells is a promising therapeutic approach. There is a body of evidence that once the production of autoantibodies has been initialized, autoantibodies have the capacity to maintain their own production.
=== Stem-cell therapy ===
Stem cell transplantation is being studied and has shown promising results in certain cases.
Medical trials to replace the pancreatic β cells that are destroyed in type 1 diabetes are in progress.
=== Altered glycan theory ===
According to this theory, the effector function of the immune response is mediated by the glycans (polysaccharides) displayed by the cells and humoral components of the immune system. Individuals with autoimmunity have alterations in their glycosylation profile such that a proinflammatory immune response is favored. It is further hypothesized that individual autoimmune diseases will have unique glycan signatures.
=== Hygiene hypothesis ===
According to the hygiene hypothesis, high levels of cleanliness expose children to fewer antigens than in the past, causing their immune systems to become overactive and more likely to misidentify own tissues as foreign, resulting in autoimmune or allergic conditions such as asthma.
=== Vitamin D influence on immune response ===
Vitamin D is known as an immune regulator that assists in the adaptive and innate immune response. A deficiency in vitamin D, from hereditary or environmental influence, can lead to a more inefficient and weaker immune response and seen as a contributing factor to the development of autoimmune diseases. With vitamin D present, vitamin D response elements are encoded and expressed via pattern recognition receptors responses and the genes associated with those responses. The specific DNA target sequence expressed is known as 1,25-(OH)2D3. The expression of 1,25-(OH)2D3 can be induced by macrophages, dendritic cells, T-cells, and B-cells. In the presence of 1,25-(OH)2D3, the immune system's production of inflammatory cytokines are suppressed and more tolerogenic regulatory T-cells are expressed. This is due to vitamin D's influence on cell maturation, specifically T-cells, and their phenotype expression. Lack of 1,25-(OH)2D3 expression can lead to less tolerant regulatory T-cells, larger presentation of antigens to less tolerant T-cells, and increased inflammatory response.
== See also ==
Epigenetics of autoimmune disorders
List of autoimmune diseases
Immune dysregulation
== References ==
== Further reading ==
== External links ==
Media related to Autoimmune diseases and disorders at Wikimedia Commons | Wikipedia/Autoimmune_diseases |
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