For decades, molecular biologists have been uncovering the mechanics of
biological systems. Efforts to bring their findings together have led to
the development of multiple databases and information systems that
capture and present pathway information in a computable network format.
Concurrently, the advent of modern omics technologies has empowered
researchers to systematically profile cellular processes across
different modalities. Numerous algorithms, methodologies, and tools have
been developed to use prior knowledge networks in the analysis of omics
datasets. Interestingly, it has been repeatedly demonstrated that the
source of prior knowledge can greatly impact the results of a given
analysis. For these methods to be successful it is paramount that their
selection of prior knowledge networks is amenable to the data type and
the computational task they aim to accomplish. Here we present a
five-level framework that broadly describes network models in terms of
their scope, level of detail, and ability to inform causal predictions.
To contextualize this framework, we review a handful of network-based
omics analysis methods at each level, while also describing the
computational tasks they aim to accomplish.
Proper branching of neuronal dendrites is crucial for healthy brain function. We previously reported that cypin, a guanine deaminase, binds to tubulin heterodimers via its collapsin response mediator protein (CRMP) homology domain (amino acids 350‐403), promoting microtubule assembly in a cell‐free system. This increased microtubule assembly results in increased dendrite number and branching. Here, we ask how cypin alters microtubules in neurons. We found that overexpression of cypin increases the number of and decreases the spacing between microtubules. We also observed that overexpression of cypin increases microtubule polymerization as evidenced by increased movement of end‐binding protein 3 (EB3) comets. To determine whether cypin binds polymerized microtubules in addition to tubulin heterodimers, we performed a series of biochemical and computational experiments. We found that cypin binds to fully formed microtubules but does not prefer microtubule ends or shafts. In addition, preliminary protein‐protein docking strategies suggest that cypin binds to microtubules through several unreported residues near the N‐terminal end of cypin, which form a surface‐exposed loop with several bulky residues. We used structure‐based approaches through docking analyses of “straight” polymerized microtubules and of “curved” soluble tubulin heterodimers and found that cypin binds free heterodimers though its CRMP homology domain along with a small amino acid region near the N‐terminus (residues 43‐63). Molecular dynamics data also suggest that the region of residues 43‐63 is highly flexible and may bind protein partners. Our results suggest that cypin regulates the microtubule cytoskeleton by promoting assembly and stabilizing microtubules.
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