Uncovering the universality of self-replication in protein aggregation and its link to disease

Fibrillar protein aggregates are a hallmark of a range of human disorders, from prion diseases to dementias, but are also encountered in several functional contexts. Yet, the fundamental links between protein assembly mechanisms and their functional or pathological roles have remained elusive. Here, we analyze the aggregation kinetics of a large set of proteins that self-assemble by a nucleated-growth mechanism, from those associated with disease, over those whose aggregates fulfill functional roles in biology, to those that aggregate only under artificial conditions. We find that, essentially, all such systems, regardless of their biological role, are capable of self-replication. However, for aggregates that have evolved to fulfill a structural role, the rate of self-replication is too low to be significant on the biologically relevant time scale. By contrast, all disease-related proteins are able to self-replicate quickly compared to the time scale of the associated disease. Our findings establish the ubiquity of self-replication and point to its potential importance across aggregation-related disorders.


Aggregation mechanisms
In the past, we have developed a range of integrated rate laws for variations on the mechanism of aggregation, for example due to differing reaction orders and saturation of particular processes.
Details on these mechanisms can be found in Meisl et al. (7). The majority of proteins in this work, including all for which only one concentration was available, were analysed with a model including primary nucleation, single step secondary nucleation and elongation. The proteins analysed with a different model are Aβ and α-synuclein.

Proteins
Here we briefly discuss each protein studied, including the biological role of aggregation and where the data were obtained. For most proteins, the data have not been previously analysed by fitting of integrated rate laws to obtain reaction rates. In those cases, i.e. when data was analysed for the first time in this work, the fits are shown in Figs. S1 to S22. For datasets which had been previously analysed (Aβ and some tau and IAPP datasets) please refer to the cited works for the details of the fits.

a-Synuclein
a-Synuclein in its amyloid fibril form is the major protein component of the Lewy bodies and neurites that are one of the hallmarks of Parkinson's disease (55). Gaspar et al. investigated the aggregation of full-length wild type a-synuclein (25). Data analysed in our study are those shown in figure 2c of that paper. The biologically relevant timescale is the length of Parkinson's disease. S2

Ab
Aggregation of both isoforms of the Ab peptide, Ab 40 and Ab 42 , is associated with Alzheimer's disease (AD) (16,24). The point mutations E22G, E22Q, and D23N are all associated with familial AD. The rate constants for Ab 40 are from Meisl et al. (24). The Ab 42 values, including all familial AD-associated mutants and the data and fits shown in Fig. 1 of the main text are from Yang et al. (54) (data and fits shown in figure 5 of that paper). The seeded data shown in Fig. 1 are from Weiffert et al. (52). The V18S+A21S Ab 42 is an artificial variant which was designed to try to abolish secondary nucleation, rate constants for this are determined in Thacker et al. (28). For Aβ42, while the aggregation at µM concentrations, under physiological slat concentrations, is dominated by secondary nucleation with a reaction order of 2, there appears to also be fragmentation of fibrils that proceeds at a much lower rate than secondary nucleation, as shown in Meisl et al. (56). However, when κ is calculated at low concentrations, one has to take into account the contribution from fragmentation as this process is expected to dominate over seocndary nucleation at sufficiently low concentrations, due to the fact that the fragmentation rate does not scale with monomer, unlike the secondary nucleation rate. We thus also evaluate κ due to fragmentation, and use this to construct the plots in Fig. 3. The relevant rate constants are given in table 3 under "Ab42 (fragmentation)". The biologically relevant timescale is the length of Alzheimer's disease (specifically average time from Braak stage 3 to Braak stage 6).

Actin
Actin is one of the major components of the eukaryotic cytoskeleton, and its conversion between monomeric (G-actin) and filamentous (F-actin) states facilitates the regulation of a multitude of cellular functions and properties, including cell shape and motility (57). Actin polymerisation is a distinct process from amyloid aggregation, with F-actin lacking the canonical cross-b structure S3 (58,59). Pure actin is only able to form polymers, and requires actin binding proteins (ABPs) to nucleate new F-actin fibres from existing F-actin surfaces, which we can equate to amyloid self-replication processes (60). Higgs et al. investigated the kinetics of actin polymerisation in the absence and presence of ABPs. The ABPs under study were the Arp2/3 complex, a weak cellular nucleating factor, and WA, which stimulates the Arp2/3 nucleation ability and consists of the C-terminal regions of Wiskott-Aldrich syndrome protein, N-WASP, and three isoforms of Scar, collectively termed the WASp/Scar protein family (40). Data analysed in our study were extracted from figure 9 (40). In the tables, aggregation under these conditions is referred to as "Actin + WAsp". The biologically relevant timescale is the length of cytoskeleton formation / rearrangement.

Apomyoglobin
The aggregation of apomyoglobin is not related to any human diseases, nor does it seem to play a role in vivo. The ability of apomyoglobin to form amyloid fibrils is therefore used as a model system and proof of the apparent universality of amyloid aggregation. Tryptophan residues at positions 7 and 14 were found to play an important role in the folding of apomyoglobin (61), and the double apomyoglobin mutant W7F/W14F (W7FW14F) was furthermore found to increase the aggregation propensity of the protein (62). Unlike the WT protein, the W7FW14F readily aggregates at physiological pH and temperature; Vilasi et al. therefore used this construct in their study (63). Data analysed in our study were extracted from figure 3 (63).
The curli fibrils are the major protein component of the extracellular matrix and thus play a key role in biofilm structuring. Andreasen et al. investigated the aggregation of the recombinantly S4 expressed mature form (residues 22-151) of CsgA (53). The data shown here, including the data and fits shown in Fig.1 of the main text, are from Andreasen et al. (53) (data and fits shown in figure 3a of that paper). The seeded data shown in Fig. 1 have not been published previously.
The biologically relevant timescale is the timescale of biofilm formation.

FapC
FapC is produced by Pseudomonas strains and, in its amyloid form, contributes to biofilm structuring and strengthening (44). The data shown here are from Andreasen et al. (53) (data and fits shown in figure 3b of that paper). The biologically relevant timescale is the timescale of biofilm formation.

Gadm1 (b-Parvalbumin)
b-Parvalbumin fibrils do not play a known functional or pathological role (65). Amyloid fibrils of b-parvalbumin are of interest because there is evidence suggesting that they are responsible for food allergies (65). The aggregation of Atlantic cod b-parvalbumin, Gadm1, was studied by Castellanos et al. (66). In this study, the aggregation behaviour of wild-type and two variants (I12C and C19S) of Gadm1 were investigated. These mutations were chosen, since residues I12 and C19 may play a role in amyloid assembly and calcium ion binding properties (66). Data analysed in our study were extracted from figure 3A (66).

Gelsolin
The aggregation of mutant gelsolin, with the D187N/Y mutation being the most common, is associated with gelsolin amyloid disease, or familial amyloidosis of Finnish type (FAF). Gelsolin is cleaved into several fragments, including 5 kDa and 8 kDa fragments, both containing the D187N/Y mutation. Both fragments are amyloidogenic, with the 8 kDa fragment comprising the majority of FAF-associated fibrils. Solomon et al. characterised the aggregation of these S5 two fragments with the D187N mutation (51). Data analysed in our study were extracted from figure 1D of that paper, where aggregation was performed at pH 7.4. The biologically relevant timescale is the length of Finnish gelsolin amyloidosis.

Huntingtin and polyQ peptides
Ectended CAG repeat sequences in trinucleotide (CAG) repeat expansion disorders result in the production of proteins with extended polyglutamine (polyQ) tracts, whose aggregation is characteristic of such diseases (67). Kakkar (67). Data analysed in our study were extracted from figures 1A and S1B-C (67). Kar et al. explored the effects of polyQ tract length on aggregation kinetics; we analysed their data on the N-terminal region of the protein ataxin-7 with a 30Q tract, and on SFQ 37 P 10 K 2 , a fragment of the Huntingtin N-terminal peptide (68). Data analysed in our study were extracted from figures 1C and 3B (68). The biologically relevant timescale is the length of Huntington's disease.

Islet amyloid polypetide precursor
The aggregation of islet amyloid polypeptide precursor (IAPP) is associated with Type II diabetes, in which aggregates of IAPP are found in the extracellular space of the islets of Langerhans (69). Pilkington et al. investigated the aggregation of the 37-residue peptide KCNTAT-CATQRLANFLVHSSNNFGAILSSTNVGSNTY with a disulphide bridge between residues 2 and 7 (69). Data analysed in our study were extracted from figure 1A (69). Additionally, both rates and reaction orders for IAPP aggregation were obtained by Rodriguez-Camargo et al. (26), also included here. The biologically relevant timescale is the timescale of Type 2 diabetes onset.

Insulin
The aggregation of insulin serves neither a functional purpose nor is it associated with pathology. Nielsen et al. studied the aggregation of bovine insulin induced by low pH (70). Data analysed in our study were extracted from figures 2A-B and 6 (70).

LacY
The aggregation of the membrane protein LacY serves neither a functional purpose nor is it associated with pathology. Stroobants et al. monitored the aggregation of the wild type LacY protein (71). Data analysed in our study were extracted from figure 3A (71).

Lysozyme
The aggregation of hen egg white lysozyme (hewL) serves neither a functional purpose nor is it associated with pathology, instead being used as a model system by which to study aggregation.
Hasecke et al. monitored the aggregation of wild-type hewL (72). Data analysed in our study were extracted from figure 2C (72).

Monellin
The aggregation of the plant protein monellin serves neither a functional purpose nor is it associated with pathology (73). Konno et al. studied the aggregation of the wild-type protein (73).
Data analysed in our study were extracted from figure 5A (73).

MSP2
Merozoite surface protein 2 (MSP2) is a 30 kDa protein found on the surface of the malariacausing Plasmodium falciparum (74,75). The structure of MSP2 in this physiological has not yet been fully established, however, some evidence suggests the presence of amyloid-S7 like oligomers, and the ability of MSP2 to form fibrils may play a role in immune recognition (74,76). Adda et al. studied the aggregation kinetics of MSP2 from the FC27 strain with a C-terminal hexa-His tag (76). Data analysed in our study were extracted from figure 5 (76).

Orb2
Aggregation of Orb2 into amyloid fibrils is important for its function in long-term memory formation in Drosophila melanogaster, and its analogues play similar roles in Aplysia californica and mice (77)(78)(79). In Drosophila melanogaster, Orb2 is present in two isoforms, the 551residue Orb2A and the predominant 704-residue Orb2B, which differ only at their N-termini.
investigated the aggregation of the first 87 residues of Orb2A (Orb2A87), whose metal binding properties may play a role in regulating aggregation (80). Data analysed in our study were extracted from figure 6A (80).

Phenol soluble modulins
Phenol soluble modulins (PSMs) are a family of peptides produced by Staphylococcus aureus with a range of functions, behaving as toxins, pro-inflammatory agents, or structural entities in biofilms (81). There are two classes of PSMs, aand b (82). PSMs of type b have been found to be consistently less cytotoxic than the a-type peptides, and are likely to play a key role in biofilm structuring (82)(83)(84)(85). PSMa1 fibrils have also been found to promote biofilm stability, whereas fibrillation of PSMa3 increases its toxicity, suggesting that its main role may be as a toxin against human cells (86)(87)(88). Data analysed in our study are those shown in Fig. 1 of Zaman et al. (89). The biologically relevant timescale is the timescale of biofilm formation.

Prion protein
Aggregation of prion protein (Prp) is responsible for prion disease and transmission. In vitro rate constants used here are from Sang et al. (20). The biologically relevant timescale is the length of prion disease. Prp is one of two systems for which we have determined the self-replication rate also in vivo (38): this was measured in 4 mouse lines which express different concentrations of Prp (resulting in different self-replication rates) and also have different survival times. This variation of self-replication rate, along with the relevant timescale, reflected in the diagonal region marked for "Prions in mice" in Fig. 3 of the main text.

Semenogelin
The deposition of aggregated semenogelin-1 (Sg1) protein in seminal vesicles is associated with

Sup35
The Saccharomyces cerevisiae Sup35 protein (Sup35p), in its soluble form, is a translation termination factor (105). Sup35p also exists in a transmissable amyloid form, wherein it functions as a yeast prion, being responsible for the [PSI + ] phenotype, increasing the phenotypic S10 diversity and thus conferring a survival advantage in changeable environments (106,107). The [PSI + ] phenotype can arise spontaneously and can be propagated to daughter cells via the cytoplasm, dependent on the presence of aggregated Sup35p seeds; self-replication of seeds is therefore crucial for its function (107)

Tau
The aggregation of tau is associated with a range of disorders, of which Alzheimer's disease is the most prevalent. The in vitro rates of tau(304-380) are from Rodriguez-Camargo et al. (27), the tau WT rates are from Kundel et al. (19). The tau datasets from Kundel et al. (19) use heparin to artificially induce primary nucleation, hence the primary rate constants and reaction orders observed in that experiment are not used here. As this means lambda is difficult to estimate, we show these tau data only in Fig. 3 (which is independent of lambda) and not Fig.   2 (this only contains the other tau dataset from Rodriguez-Camargo et al. (27)). While we can't estimate lambda for full length tau, the fact that no aggregation of full length tau is seen in the absence of an inducer of primary nucleation confirms that indeed secondary processes dominate over primary ones also in the full length system. Tau is one of two systems for which we have determined the self-replication rate also in vivo, see Meisl et al. (39): this was measured in humans with Alzheimer's disease. The relevant timescale is the length of Alzheimer's disease S11 (specifically average time from Braak stage 3 to Braak stage 6).

Ure2p
The Ure2 protein (Ure2p) is a yeast prion, which behaves similarly to Sup35p (107,110). Ure2p is responsible for the [URE3] phenotype in its prion form. In its soluble form, Ure2 is a regu-                           Table S3: Proteins shown in the main text, where a reaction order could be determined. When experiments were seeded or self-replication processes were too slow to be detected this is denoted by †. In those cases, upper bounds for λ or κ, were used instead, calculated as outlined in the Methods section. "Aβ42 (fragmentation)" simply records the estimate of the rate of fragmentation Aβ42 (see section on Aβ). The tau datasets from Kundel et al. (19) use heparin to artificially induce primary nucleation, hence the primary rate constants and reaction orders observed in that experiment are not used here (see section on tau). Some datasets had to be analysed with a model including saturation of secondary nucleation or elongation, the respective values for the saturation constants, K M and K E , respectively, are given in the "comments" column. For details on the models please refer to the cited papers as well as Meisl et al. (7).

Investigation of structure-mechanism correlation
In order to investigate whether any specific structural features could be identified that correlate with the propensity for self-replication to dominate over de novo formation, we used a recently developed method to identify sequence patterns, see Fig. S23. This analysis yields 36 different types of patterning score, for each of which we then computed the Pearson correlation coefficient, and its associated p-value for non-correlation, with our measure for dominance of self-replication, log(κ/λ). A weak correlation of log(κ/λ) with some patterning scores is observed, however, when the Bonferroni correction is applied to account for the fact that there are 36 different scores to correlate to, none of these correlations remain significant (p> 0.05).
While there are likely specific structural features that promote or prevent self-replication, our current dataset is likely not extensive enough to provide statistically significant insights and considerable additional work will be needed to elucidate these features. Figure S23: Z-scores from NARDINI analysis (45). Each column is a different protein (when data from multiple forms of the protein were available, the WT was chosen), each row a different patterning parameter, the colour denotes the z-score, which quantifies how much each patterning score differs from a random sequence, with blue and red indicating more and less uniform dispersion, respectively, than would be expected in a scrambled sequence. The data are ordered by increasing κ/λ ratio from left to right, i.e. proteins for which de novo formation dominates are on the left, those for which self-replication dominates are on the right.