Structural Biochemistry/Cell Signaling Pathways/Noise in Signaling
Noise can be defined as random fluctuations of a signal. Noise caused by stochastic fluctuations in genetic circuits (transcription and translation) is now appreciated as a central aspect of cell function and phenotypic behavior. Noise has also been detected in signaling networks, but the origin of this noise and how it shapes cellular outcomes remain poorly understood. The noise in signaling networks results from the intrinsic promiscuity of protein-protein interactions (PPIs), and that this noise has shaped cellular signal transduction. Features promoted by the presence of this molecular signaling noise include multimerization and clustering of signaling components, pleiotropic effects of gross changes in protein concentration, and a probabilistic rather than a linear view of signal propagation.
Types of Noise
Genetic noise is caused by the random fluctuations of signals during the processes of transcription and translation in DNA replication. The noise can cause genes to express differently. For example, two genetically identical cells can behave differently due to the influence of noise. This random gene expression may allow the cell to suddenly be able to resist a substance that would originally have killed it if the noise did not cause the cell to change.
Noise in signaling is caused by the numerous amount of protein-protein interactions(PPI) due to its promiscuous nature. Since proteins interact with many other types of proteins in a short period of time, many signals are being produced. The promiscuity of PPIs that create signal noise may help the recovery of cell functions through homologous pathways. This signaling noise may also be important for increasing robustness of signaling between cells by dampening incorrect events. Increasing robustness of signals can be due to multimerization, functional selectivity, and also pleiotropic effects. There has been research that shows that noise plays a role in epigenetic memory by affecting the central switches of cell functions. There is also speculation that changes in levels of signaling noise may be related to human diseases. By understanding how signaling noise affects cell function, researchers and scientists can finally get a better idea on its affect on diseases or also on propagation of epigenetic memory.
Noise creates a threshold for signals to cross before a signal can create an effect. This threshold prevents many irrelevant signals due to the promiscuous nature of PPI to cause an effect. A single signal from a receptor cannot overcome the noise threshold by itself. To overcome this threshold, multiple receptors must come together to create a signal large enough to overcome the signal. The process of which multiple receptors come together is called multimerization.
Multimerization is the clustering of multiple receptors which together create a noise which surpasses the background noise in the cells. This is the first method of overcoming the noise threshold so that signals can be sent appropriately and accordingly. When the receptors sending the same signal join together, the signal is then amplified which allows it to be sent. In contrast, when there is just one or a few receptors, the combined noise of their signals will less likely be greater than the threshold, resulting in no signal being sent.
Functional selectivity is another way to allow signals to be sent through a "proof-reading" method. If the components of the signal are all present and in the exact order in which the signal consists of, then the signal will be sent. If there are some but not all of the components of the specific signal, then that signal will not be sent. This method can be referred to as "proof-reading" because the body makes sure that the signal components are all correct in order for the process to proceed. The body will "proof-read" for any mistakes and correct them to allow signals to proceed.
Pleiotropic effect is when the body produces more of one specific molecule that will lead to the surpassing of the noise threshold which results in a signal being sent. This effect does not necessarily mean that the number of receptors will change (like in multimerization). Instead, the concentration of a molecule is what changes in order to increase the chances of sending a signal. The body can also reduce the chance of a sending a harmful signal by reducing the concentration of a molecule related to the harmful signal. This way the noise level of the harmful signal will not surpass the noise threshold and will not be sent.
The human interactome is a large intricate network of thousands of protein-protein interactions (PPIs). It contrasts the classical idea that protein interactions follow a linear signaling pathway. Within the human interactome, proteins not only interact with one other protein, but they interact with many different proteins. This could also be seen as proteins having multiple protein partners to communicate with. The interaction of several proteins is what makes up the promiscuity of these PPI networks. The human interactome is a huge discovery because it allows researchers to search deeper into its relationship with diseases and genetics.
There are three different ways to see whether interactome networks have been established. The first is through a compilation of interactions from published work. There are usually some established literature-based work on the physical or biochemical interactions done by other researchers which can reassure that the interaction network does exist. The second way is through computational predictions which are based on the structural information of a protein, sequence and gene-order, and the existence of genes in genomes that transfer interactions between organisms (via orthology mapping). Though this way might be quick, the lack of experimental proof due to indirect 'orthogonal' information makes this a not so strong approach. The last approach is through systematic mapping strategies applied towards large groups of genomes and proteomes. Because of the advance in technology, researchers and scientists are able to put together interactomes in shorter periods of time (than before).