XMAP215 promotes microtubule catastrophe by disrupting the growing microtubule end

The GTP-tubulin cap is widely accepted to protect microtubules against catastrophe. The GTP-cap size is thought to increase with the microtubule growth rate, presumably endowing fast-growing microtubules with enhanced stability. It is unknown what GTP-cap properties permit frequent microtubule catastrophe despite fast growth. Here, we investigate microtubules growing in the presence and absence of the polymerase XMAP215. Using EB1 as a GTP-cap marker, we find that GTP-cap size increases regardless of whether growth acceleration is achieved by increasing tubulin concentration or by XMAP215. Despite increased mean GTP-cap size, microtubules grown with XMAP215 display increased catastrophe frequency, in contrast to microtubules grown with more tubulin, for which catastrophe is abolished. However, microtubules polymerized with XMAP215 have large fluctuations in growth rate; display tapered and curled ends; and undergo catastrophe at faster growth rates and with higher EB1 end-localization. Our results suggest that structural perturbations induced by XMAP215 override the protective effects of the GTP-cap, ultimately driving microtubule catastrophe.

Cryo-EM structure of amyloid fibrils formed by the entire low complexity domain of TDP-43

Amyotrophic lateral sclerosis and several other neurodegenerative diseases are associated with brain deposits of TDP-43 aggregates. Cryo-EM structure of amyloid formed from the entire TDP-43 low complexity domain reveals single protofilament fibrils containing a large (138-residue), tightly packed core with structural features that differ from those previously found for fibrils formed from short protein fragments. The atomic model provides insight into potential structural perturbations caused by phosphorylation and disease-related mutations.

DReSS: a method to quantitatively describe the influence of structural perturbations on state spaces of genetic regulatory networks

Structures of genetic regulatory networks are not fixed. These structural perturbations can cause changes to the reachability of systems’ state spaces. As system structures are related to genotypes and state spaces are related to phenotypes, it is important to study the relationship between structures and state spaces. However, there is still no method can quantitively describe the reachability differences of two state spaces caused by structural perturbations. Therefore, Difference in Reachability between State Spaces (DReSS) is proposed. DReSS index family can quantitively describe differences of reachability, attractor sets between two state spaces and can help find the key structure in a system, which may influence system’s state space significantly. First, basic properties of DReSS including non-negativity, symmetry and subadditivity are proved. Then, typical examples are shown to explain the meaning of DReSS and the differences between DReSS and traditional graph distance. Finally, differences of DReSS distribution between real biological regulatory networks and random networks are compared. Results show most structural perturbations in biological networks tend to affect reachability inside and between attractor basins rather than to affect attractor set itself when compared with random networks, which illustrates that most genotype differences tend to influence the proportion of different phenotypes and only a few ones can create new phenotypes. DReSS can provide researchers with a new insight to study the relation between genotypes and phenotypes.

Structural Perturbations of Exon Skipping Edits within the Dystrophin D20:24 Region

Exon skipping is a disease modifying therapy that operates at the RNA level. In this strategy, oligonucleotide analog drugs are used to specifically mask specific exons and prevent them from inclusion in the mature mRNA. Of course, this also results in loss of the corresponding region from the cognate protein, which is one possible therapeutic aim. Exon skipping can also be used to restore protein expression in cases where a genetic frameshift mutation has occurred, and this how it is applied to Duchenne muscular dystrophy, DMD. DMD most commonly arises as a result of large exonic deletions that juxtapose flanking exons of incompatible reading frame in the dystrophin gene, creating a frameshift and abolishing protein expression. Loss of dystrophin protein leads to the pathology of the disease, which is severe, causing death generally in the second or third decade of life. Here, the primary aim of exon skipping is the restoration of the reading frame by skipping an exon adjacent to the patient’s original defect. However, the therapeutically expressed protein is of course edited, and missing both the region of the underlying genetic defect, as well as the therapeutically skipped exon. While restoring some protein expression is good, how removing some region from the middle of a protein effects its structure and function is unclear. Complicating this in the case of DMD is the fact that the dystrophin gene is very large, containing 79 exons. Many different underlying deletions are known, and exon skipping can be applied in many ways. It has previously been shown that many exon-skip edits result in structural perturbations of varying degrees. What has been unclear is whether and how exon editing can be done to minimize these perturbations. In this study we examine a systematic and comprehensive panel of possible exon edits in a region of the dystrophin protein, and identify for the first time, exon edits that appear to maintain structural stability similar to wildtype protein. We also identify factors that appear to be correlated with the degree of structural perturbation, such as the number of cooperative protein domains, as well as how the underlying exon structure interacts with the protein domain structure.

DReSS: A difference measurement based on reachability between state spaces of Boolean networks

Researches on dynamical features of biological systems are mostly based on fixed network structure. However, both biological factors and data factors can cause structural perturbations to biological regulatory networks. There are researches focus on the influence of such structural perturbations to the systems’ dynamical features. Reachability is one of the most important dynamical features, which describe whether a state can automatically evolve into another state. However, there is still no method can quantitively describe the reachability differences of two state spaces caused by structural perturbations. DReSS, Difference based on Reachability between State Spaces, is proposed in this research to solve this problem. First, basic properties of DReSS such as non-negativity, symmetry and subadditivity are proved based on the definition. And two more indexes, diagDReSS and iDReSS are proposed based on the definition of DReSS. Second, typical examples like DReSS = 0 or 1 are shown to explain the meaning of DReSS family, and the differences between DReSS and traditional graph distance are shown based on the calculation steps of DReSS. Finally, differences of DReSS distribution between real biological regulatory network and random networks are compared. Multiple interaction positions in real biological regulatory network show significant different DReSS value with those in random networks while none of them show significant different diagDReSS value, which illustrates that the structural perturbations tend to affect reachability inside and between attractor basins rather than to affect attractor set itself.Author summaryBoolean network is a kind of networks which is widely used to model biological regulatory systems. There are structural perturbations in biological systems based on both biological factors and data-related factors. We propose a measurement called DReSS to describe the difference between state spaces of Boolean networks, which can be used to evaluate the influence of specific structural perturbations of a network to its state space quantitively. We can use DReSS to detect the sensitive interactions in a regulatory network, where structural perturbations can influence its state space significantly. We proved properties of DReSS including non-negativity, symmetry and subadditivity, and gave examples to explain the meaning of some special DReSS values. Finally, we present an example of using DReSS to detect sensitive vertexes in yeast cell cycle regulatory network. DReSS can provide a new perspective on how different interactions affect the state space of a specific regulatory network differently.