Protein condensation diseases

The condensed state of protein condensation contributes to an astonishing range of physiological processes. The failures in the regulation of condensed states, however, may lead to dysfunctional protein assemblies that could be involved in a range of pathological processes. Pathological mechanisms, caused by the perturbations of the condensed states of proteins are just beginning to be discovered. While several human diseases have already been linked with aberrant protein condensation, our analysis indicates that genes encoding condensate-forming proteins can be associated with a much broader range of disorders. Within the framework of the generic nature of the condensed state of proteins, we performed a systematic discovery of the human diseases, where aberrant condensation has a causative nature. We identified over 5000 human diseases associated with aberrant condensation, including 2170 multisystem orphan disorders classified as protein condensation diseases, i.e. conditions caused by the disruption of the normal behaviour of the condensed states of proteins.

Formation of Lewy bodies through maturation of
a-synuclein liquid droplets

Misfolded a-synuclein is a major component of Lewy bodies, which are a hallmark of Parkinson’s disease (PD). We have investigated whether Lewy bodies can be formed through the condensation pathway via maturation α-synuclein condensates. We showed, both in vitro and in a Caenorhabditis elegans model of PD, that α-synuclein undergoes liquid–liquid phase separation by forming a liquid droplet state, which converts into an amyloid-rich hydrogel with Lewy-body-like properties. This maturation process towards the amyloid state is delayed in the presence of model synaptic vesicles in vitro. Thus, formation of Lewy bodies may be linked to the arrested maturation of α -synuclein condensates in the presence of lipids and other cellular components.

Hardenberg MC, Sinnige T, Casford S, Dada S, Poudel C, Robinson EA, Fuxreiter M, Kaminksi C, Kaminski-Schierle GS, Nollen EAA, Dobson CM, Vendruscolo M. (2021) Observation of an α-synuclein liquid droplet state and its maturation into Lewy body-like assemblies. J. Mol Cell Biol  13, 282-294.

Droplet landscapes

Proteins change interaction behaviors according to the cellular context. Thus, motifs, which drive formation of the droplet state through disordered interactions, can also sample more ordered binding modes. Those residues, which have a strong preference for multimodal binding, can induce conversion of liquid-like droplets into solid-like aggregates. This can be illustrated by droplet landscapes. The x axis display the preference for the droplet-state (pDP), whereas the y axis shows the binding mode variability (Sbind). Residues, with high pDP values and low Sbind values tend to maintain disordered interactions. Residues, in the droplet regime with lower pDP  and high Sbind values are aggregation hot-spots and readily convert to amyloid-like aggregates. Although the majority of the TDP-43 low complexity domain samples disordered interactions and forms a liquid-like droplet, residues forming the transient helix also tend to sample more ordered interaction modes and drive aggregation of the protein with the droplets.

M. Vendruscolo and M Fuxreiter (2021) Sequence determinants of the aggregation of proteins within condensates generated by liquid-liquid phase separation. J Mol Biol 434, 167201.

Disease-associated mutations driving aggregation of proteins within liquid droplets

Familial mutations may induce aggregation within liquid-like condensates. Intriguingly, these mutations often do not change aggregation properties or droplet-forming probabilities significantly. Our analysis on ALS-associated mutations with experimental evidence for aggregation in vitro shows that these mutants exhibit increased binding mode promiscuity. In other words, these mutations increase sampling of ordered interaction modes, while the region remains dominantly in disordered binding. Within the droplet landscape framework, we have developed a prediction method to identify aggregation hot-spots from sequence. The method can distinguish ALS-associated mutations and non-ALS mutations, for example indicate that FUS G156E will drive aggregation, while G154E will not impact the liquid state.

M. Vendruscolo and M Fuxreiter (2021) Sequence determinants of the aggregation of proteins within condensates generated by liquid-liquid phase separation. J Mol Biol 434, 167201

M. Fuxreiter (2021) Spot in a drop: mutations in aberrant condensates. Nat. Rev. Mol. Cell Biol 22, 162-163