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December 4, 2019 - May 22, 2020
Network analysis provides a more nuanced exploration of the underlying regulatory mechanisms associated with the differential activity of gene regulatory programs.
Changes such as the appearance or disappearance of edges or groups of edges can help define differences between disease phenotypes.
An overview of all PTMs linked to disease would require a full encyclopedia that would need updating on an almost daily basis. The importance of novel PTMs is indeed a recurring theme in the present biomedical literature.
Life is all about information processing. At length scales varying over 9 orders of magnitude, from the full organism to the individual (macro)molecule over the intermediate scales of organs and cells, we integrate signals from the exterior world and process them to yield a specific action.
Allostery and PTMs are major mechanisms in which a protein can modify its form and function as a consequence of a given signal, engage in novel interactions with other biomolecules, and, thereby, pass the information to different compartments of the cell.
Here we define allostery as a conformational change stabilized or induced by ligand binding, leading to altered function of the resulting complex at a site different from the allosteric ligand binding site. Better or worse binding to a third partner ...
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A second important example in which ligand binding at one site modifies the structure at a different site, but for which information has to be transmitted from outside to inside the cell, is that involving the large family of G-protein–coupled receptors (GPCRs).
Seeking an equivalent in computer science, the transistor provides the same function as regulated amplification.
To what level of detail we will need to understand the individual components and/or the modules to make meaningful predictions about cellular outcome is still unclear, but we argue that both a quantitative view of the PTMs and introduction of a spatial and temporal picture of the different determinants and mediators will probably be required to understand signal transduction in terms of cellular, organ, and patient outcomes.
At the histopathological level, the disease is characterized by the presence of two types of abnormal protein deposits: amyloid plaques and neurofibrillary tangles.
The amyloid cascade hypothesis states that the accumulation of amyloid β (Aβ), a peptide derived from the amyloid precursor protein (APP), would initiate AD and start the pathogenesis (Selkoe 1991) and has structured research in the disease over the past 20 years, with the ultimate goal being efficient disease-modifying treatments.
However, the toxicity of Aβ alone is not sufficient to explain the clinically observed neuronal loss, for which reason Tau is believed to be a crucial partner for relaying this toxicity.
After age, the second most important risk factor for AD is genetic in nature, and it concerns the polymorphism of apolipoprotein E
An important bottleneck in the development of a disease-modifying treatment for AD is the extremely slow evolution of the disease—which might range from 10 to 20 years—and the absence of clear biomarkers in the earliest stage of the disease that would indicate that a person is at risk.
Whereas the concentration of Aβ typically decreases as the disease progresses from the early mild cognitive impairment stage to its more severe forms, concentrations of Tau and phospho-Tau typically increase
Recent work has suggested that Tau has multiple functions (Morris and Maeda 2011), with possibly distinct functions at different places in the neuron, and that it should be seen in terms of an integrated system whereby Tau and its interaction partners are anchored spatially together (Hashiguchi and Hashiguchi 2013) or even considered as parts of one single molecular machine composed of a finite number of biomolecules (Juhàsz et al. 2011).
Tau, the tubulin-associated unit, was initially discovered as a protein that stabilizes tubulin assembly into microtubules (Weingarten et al. 1975) and as such is a key regulator of neuronal morphogenesis (Drubin et al., 1985) and neurite polarity (Caceres and Kosik, 1990). Through assembling and stabilizing the microtubules in the axons, Tau is a key player in the axonal transport that connects the neuron cell body with the synapses.
Tau can regulate axonal transport not only through the stabilization of microtubules, but also by directly interfering with the cytoplasmic motor proteins, kinesin and dynein.
Not only is the isoform distribution of Tau developmentally regulated, but also is its phosphorylation pattern, which brings us to the heart of the present topic.
The realization that Tau is the main component of the neurofibrillary tangles that characterize neurons in the brains of patients with AD evidently established a link between microtubule stability and AD.
This observation suggests some parallel between the disease and a normal developmental stage
As in the proposed histone code (Strahl and Allis 2000), the Tau field is faced with a combinatorial pattern of possible modifications that we currently cannot interpret.
In the absence of mechanistic insights in the Tau-tubulin interaction, however, a deeper understanding of how phosphorylation translates to altered function remains challenging.
More recently (Tai et al., 2012), the simultaneous presence of phosphorylated and ubiquitinated Tau oligomers at the synaptic densities derived from AD brains suggested that a defective ubiquitin–proteasome system also plays a role in the synaptic aspects of the disease.
Tau acetylation also follows this trend, and acetylation has been identified as a factor that hinders its degradation and thereby positively contributes to the tauopathy
Tau acetylation is found at every pathological stage of AD and correlates specifically with insoluble Tau aggregates.
The cis–trans conformation of the prolines following a phosphorylated Ser or Thr residue has, indeed, been proposed as a second level of regulation beyond the actual phosphorylation itself
Detecting the phosphorylation status of the 80 possible phosphorylatable residues in a protein such as Tau as isolated from a brain section, indeed, has been and remains a formidable technical challenge.
Defining at a second level possible patterns that consist of two or more simultaneous (or exclusive) phosphorylation events has become feasible only recently with novel sophisticated mass spectrometry (MS) approaches that combine measurements on the intact proteins (top-down MS) and on its trypsin-digested peptides (bottom-up MS) with known reference standards
Our “digital world feeling” has indeed led us to reductionist, linear statements such as “under this condition, protein X becomes phosphorylated at site Y.” This leads to a simple schematic drawing, but does not consider that different copies of protein X may or may not carry the phosphate moiety at this position. We tend to write (and think) digitally, but our language might not be in line with our own physical reality that is profoundly analog. We moreover have a tendency to believe that there is only one mod-form, usually the maximally phosphorylated one, when, in reality, there is a
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Tau contains 80 potential phosphorylation sites, it is clear that all these combinatorial phospho-patterns cannot co-exist, but it is equally difficult to imagine that all molecules at a given moment will be in exactly the same state.
Trigger, and switch are, again, engineering terms that might not recognize the fuzziness of the real situation and are probably less sharply defined in the biological context of a neuron than an electrical engineer might conceive (Pauwels 2013).
Combinations of two kinases have been studied and were shown to lead to novel patterns whereby one kinase incorporates a phosphate at a given position, rendering a neighboring site a suitable substrate for the second kinase
Recently, we showed that NMR spectroscopy could, in a single experiment, yield similar information, allowing us to map the phospho-pattern generated by different kinases or combinations of them
Because of their relatively easy use and high sensitivity, antibodies are not only the historical alternatives to biophysical methods but also remain the tool of choice for most studies. Combined with modern imaging techniques, they allow for a site-specific evaluation of the epitope against which they were raised. Nevertheless, a number of fundamental issues hinder their use for obtaining a view of the distribution of possible PTMs.
However, when we consider that Tau is capable of integrating the information content of the tubulin network, the many kinases and phosphatases that cluster around it, glucose homeostasis, etc., into a given pattern of PTMs, its central role as a hub protein translates this information functionally.
Tau also does this through its effect on transport, its anchoring of other components such as the Fyn kinase, etc., and leads to its playing a central network role in the functioning of the neuron both in the axonal and synaptic compartments.
We expect that Tau as a substrate for Gsk3β and its many other modifying enzymes plays a similar central role, and, as such, actively coordinates the information flow.
The genes currently discovered by different genome-wide association studies can influence both the depth and spread of the potential wells or the barrier that separates them, thereby increasing or decreasing the probability that a neuron evolves from one well into another.
The initial seeds of Tau pathology would start early in life in some selected neurons of the locus ceruleus, and spread from these neurons via their long projecting axons toward the entorhinal cortex
An accurate and quantitative reading of the PTM mod-form of Tau at all levels of the neuron and the brain will be required to understand whether this is a cause or a consequence of AD.
Epigenetic regulation is under the control of a variety of genomic elements, including, but probably not limited to single-nucleotide polymorphisms (SNPs), microRNAs, and a variety of noncoding RNAs.
With regard to epigenetics, the noncoding RNAs of greatest importance for epigenetics are likely long noncoding RNAs (lncRNAs).
LncRNAs are associated with chromatin-modifying complexes and histone methyltransferases and play a central role in controlling gene expression.
The realm of epigenetic variation includes microRNA. These small RNAs can influence gene expression in the absence of changes to genetic sequence variation.
Touted as an “archive” of the cumulative environment of exposures, the advantage of studying DNA methylation is, in part, borne out by the biological stability of this epigenetic mark.
For example, human aging has been associated with significant changes in the methylome.
However, one of the challenges in constructing epigenetic networks is to be able to model the plasticity, epigene–epigene interactions, and the informative role of the environment.
One important consideration of epigenetic networks and the plasticity of epigenetic marks is that they may represent, more than other network facets, the potential of a network to be perturbed toward disease and then returned to a state that trends toward health.
The metabolome is the entire complement of low-molecular-weight molecules (molecular weight <2000 amu) in a biological sample or organism.
