Periodic Reporting for period 4 - MANGO (The determinants of cross-seeding of protein aggregation: a Multiple TANGO)
Période du rapport: 2019-12-01 au 2020-05-31
During protein aggregation, proteins stick together in organised clumps in a self-recognizing manner. This process occurs in many seemingly unrelated human pathologies such as diabetes, cataract, cancer and dementia, although each disease is characterised by the protein(s) that aggregate and the tissues where this happens.
Whether aggregates cause the pathology or are just consequences of some other degenerative mechanism is still debated. This is true even in diseases where protein aggregates took centre-stage in the disease mechanism, such as the aggregation of the amyloid beta peptide in Alzheimer disease, because interventions targeting the aggregates have failed to provide benefit to the patients.
Our understanding of the effect of protein aggregates on biological systems, including the human body, is still very limited. We do know that aggregation is part of normal ageing, but we cannot tell the essential differences between functional, desired aggregation and unwanted and uncontrolled aggregation causing disease. Moreover, not all aggregation is pathologic: nature uses amyloids to construct highly stable biomaterials, such as spider silk and insect egg shell or for memory formation in mammalian brain cells.
The prominent role of aggregation-prone regions (APRs) within proteins to induce aggregation of identical proteins is well established. In this project, we tested the hypothesis if unrelated proteins carrying similar APRs in their sequences can seed each other’s aggregation (cross-seeding) or form mixed aggregates (co-aggregation). Such events could lead to co-aggregation cascades that, starting from a seed aggregate, may lead to inactivation of many other proteins.
The objectives of this project included a) mapping aggregation cascades of disease-associated aggregating proteins, b) studying the seeding of model proteins in cell culture as well as in purified form in vitro, c) constructing bio-informatics algorithms to predict co-aggregation cascades, and d) perform comparative proteome-wide analyses to identify mechanisms that limit co-aggregation.
We have drawn the following conclusions from the results: a) co-aggregation likely plays a role in many aspects of amyloid formation in human disease, which makes the prevention of co-aggregation a therapeutic target, b) reductionist synthetic model systems are appropriate to find in vivo inducers of co-aggregation, c) co-aggregation is sequence and structure-specific, and d) inducing co-aggregation has the potential to become a powerful and innovative tool to fight bacterial and viral infections, as well as cancer.
Whether aggregates cause the pathology or are just consequences of some other degenerative mechanism is still debated. This is true even in diseases where protein aggregates took centre-stage in the disease mechanism, such as the aggregation of the amyloid beta peptide in Alzheimer disease, because interventions targeting the aggregates have failed to provide benefit to the patients.
Our understanding of the effect of protein aggregates on biological systems, including the human body, is still very limited. We do know that aggregation is part of normal ageing, but we cannot tell the essential differences between functional, desired aggregation and unwanted and uncontrolled aggregation causing disease. Moreover, not all aggregation is pathologic: nature uses amyloids to construct highly stable biomaterials, such as spider silk and insect egg shell or for memory formation in mammalian brain cells.
The prominent role of aggregation-prone regions (APRs) within proteins to induce aggregation of identical proteins is well established. In this project, we tested the hypothesis if unrelated proteins carrying similar APRs in their sequences can seed each other’s aggregation (cross-seeding) or form mixed aggregates (co-aggregation). Such events could lead to co-aggregation cascades that, starting from a seed aggregate, may lead to inactivation of many other proteins.
The objectives of this project included a) mapping aggregation cascades of disease-associated aggregating proteins, b) studying the seeding of model proteins in cell culture as well as in purified form in vitro, c) constructing bio-informatics algorithms to predict co-aggregation cascades, and d) perform comparative proteome-wide analyses to identify mechanisms that limit co-aggregation.
We have drawn the following conclusions from the results: a) co-aggregation likely plays a role in many aspects of amyloid formation in human disease, which makes the prevention of co-aggregation a therapeutic target, b) reductionist synthetic model systems are appropriate to find in vivo inducers of co-aggregation, c) co-aggregation is sequence and structure-specific, and d) inducing co-aggregation has the potential to become a powerful and innovative tool to fight bacterial and viral infections, as well as cancer.
We have discovered several ways co-aggregation contributes to human disease including cancer and neurodegenerative disease.
We studied the seeding of co-aggregation in several model systems including in vitro experiments with proteins in solution, in bacteria, cultured cancer cells, and in virus-infected mammalian cells, in plants, as well as in mouse models of bacterial infection.
We have constructed several novel bioinformatics algorithms and built computational pipelines for the prediction of co-aggregation interactions and reducing co-aggregation propensity of proteins, as well as updated or built databases of amyloid-forming hexapeptides and protein-chaperone interactions. The databases and computational pipelines are available through websites.
We have identified several proteome-wide mechanisms limiting co-aggregation, including aggregation-gatekeeper residues and chaperone interactions.
The Mango project contributed to seven patent applications of which one has already been licensed. Data from Mango and an ERC Proof of Concept Grant (PeptIn) established the IP portfolio of targeted protein aggregation that led to the creation of Aelin Therapeutics in 2017 (https://aelintx.com/).
Mango yielded 24 articles, two book chapters and four PhD theses. It has contributed to the training of 3 postdoctoral researchers and 9 graduate students. Dissemination efforts included organisation of a workshop, press releases, coverage in non-scientific/non-peer reviewed publications, and a video.
We studied the seeding of co-aggregation in several model systems including in vitro experiments with proteins in solution, in bacteria, cultured cancer cells, and in virus-infected mammalian cells, in plants, as well as in mouse models of bacterial infection.
We have constructed several novel bioinformatics algorithms and built computational pipelines for the prediction of co-aggregation interactions and reducing co-aggregation propensity of proteins, as well as updated or built databases of amyloid-forming hexapeptides and protein-chaperone interactions. The databases and computational pipelines are available through websites.
We have identified several proteome-wide mechanisms limiting co-aggregation, including aggregation-gatekeeper residues and chaperone interactions.
The Mango project contributed to seven patent applications of which one has already been licensed. Data from Mango and an ERC Proof of Concept Grant (PeptIn) established the IP portfolio of targeted protein aggregation that led to the creation of Aelin Therapeutics in 2017 (https://aelintx.com/).
Mango yielded 24 articles, two book chapters and four PhD theses. It has contributed to the training of 3 postdoctoral researchers and 9 graduate students. Dissemination efforts included organisation of a workshop, press releases, coverage in non-scientific/non-peer reviewed publications, and a video.
The Mango project has pushed the boundary of protein aggregation research beyond the state of the art, both technologically and conceptually.
In the technological arena, we have established peptide arrays as a fast screening method of potential interacting peptides.
We developed the Pept-insTM technology, a method of inducing co-aggregation using synthetic amyloid peptides and employed it both for the specific detection of proteins in a complex biological matrix, and for functional knock-down of target proteins. We have demonstrated that Pept-Ins are effective against cancer targets, pathogenic bacteria or viruses. Moreover, their intravenous or intraperitoneal administration can reduce tumour growth or infection, respectively.
We developed a computational pipeline for predicting heterologous amyloidogenic interactions that takes the structure of the aggregation-prone regions in account (https://cordax.switchlab.org/) and another one that reduces the aggregation-propensity of proteins without affecting their stability (https://solubis.switchlab.org/).
Also, we introduced the use of Atomic Force Microscopy coupled with Fourier-Transform Infrared Spectroscopy (AFM-FTIR) for the in situ study of amyloids. We have obtained funding for such an instrument, with an important additional capability, namely the detection of fluorescence emission on the same samples. This will allow identifying amyloid deposits in tissue sections and imaging that area of interest at the nanoscale using AFM-FTIR.
We have made major conceptual breakthroughs, as well. We have shown that synthetic aggregating peptides, homologous to the aggregation-prone regions present in proteins can induce the aggregation and functional inactivation specific proteins. We have shown that such induced amyloid aggregation event is selectively toxic to cells that rely on the function of the aggregating protein.
We also demonstrated that protein aggregation in plants can generate valuable new traits (e.g. increased growth or starch production). Again, we did not observe any toxic side effects from the presence of these aggregates, suggesting the loss of the function of the (co-)aggregating proteins is a strong determinant of the effect of aggregates on their biological environment.
We have shown that by targeting redundant aggregation-prone regions present in several proteins, it is possible to induce a co-aggregation cascade that leads to massive aggregation and eventually to the collapse of the proteome. We have established inducing co-aggregation with synthetic peptides as a potential new therapeutic modality to address bacterial and viral infections.
We coined the concept of critical aggregation prone regions. These are a minority of aggregation prone regions of proteins that reside in structurally unstable regions of the proteins and are most likely to induce aggregation. We showed that carefully designed mutations in these aggregation prone regions can greatly reduce the aggregation propensity of these proteins. This is of special importance for the therapeutic use of proteins (e.g. monoclonal antibodies), where aggregation is a factor that limits production and efficacy in patients.
We have unequivocally proven the importance of co-aggregation cascades in human pathology, e.g. in neurodegenerative disease.
In the technological arena, we have established peptide arrays as a fast screening method of potential interacting peptides.
We developed the Pept-insTM technology, a method of inducing co-aggregation using synthetic amyloid peptides and employed it both for the specific detection of proteins in a complex biological matrix, and for functional knock-down of target proteins. We have demonstrated that Pept-Ins are effective against cancer targets, pathogenic bacteria or viruses. Moreover, their intravenous or intraperitoneal administration can reduce tumour growth or infection, respectively.
We developed a computational pipeline for predicting heterologous amyloidogenic interactions that takes the structure of the aggregation-prone regions in account (https://cordax.switchlab.org/) and another one that reduces the aggregation-propensity of proteins without affecting their stability (https://solubis.switchlab.org/).
Also, we introduced the use of Atomic Force Microscopy coupled with Fourier-Transform Infrared Spectroscopy (AFM-FTIR) for the in situ study of amyloids. We have obtained funding for such an instrument, with an important additional capability, namely the detection of fluorescence emission on the same samples. This will allow identifying amyloid deposits in tissue sections and imaging that area of interest at the nanoscale using AFM-FTIR.
We have made major conceptual breakthroughs, as well. We have shown that synthetic aggregating peptides, homologous to the aggregation-prone regions present in proteins can induce the aggregation and functional inactivation specific proteins. We have shown that such induced amyloid aggregation event is selectively toxic to cells that rely on the function of the aggregating protein.
We also demonstrated that protein aggregation in plants can generate valuable new traits (e.g. increased growth or starch production). Again, we did not observe any toxic side effects from the presence of these aggregates, suggesting the loss of the function of the (co-)aggregating proteins is a strong determinant of the effect of aggregates on their biological environment.
We have shown that by targeting redundant aggregation-prone regions present in several proteins, it is possible to induce a co-aggregation cascade that leads to massive aggregation and eventually to the collapse of the proteome. We have established inducing co-aggregation with synthetic peptides as a potential new therapeutic modality to address bacterial and viral infections.
We coined the concept of critical aggregation prone regions. These are a minority of aggregation prone regions of proteins that reside in structurally unstable regions of the proteins and are most likely to induce aggregation. We showed that carefully designed mutations in these aggregation prone regions can greatly reduce the aggregation propensity of these proteins. This is of special importance for the therapeutic use of proteins (e.g. monoclonal antibodies), where aggregation is a factor that limits production and efficacy in patients.
We have unequivocally proven the importance of co-aggregation cascades in human pathology, e.g. in neurodegenerative disease.