Timothy K. Lu - US grants

DESCRIPTION (Provided by the applicant) Abstract: Amyloids play an integral role in a broad range of human illnesses including prion diseases, neurodegenerative conditions such as Alzheimer's and Parkinson's diseases, systemic amyloidoses, type II diabetes, and bacterial biofilms. Amyloids are aggregates of proteins or peptides with cross-beta structure and fibrillar morphology. Amyloids assemble via a rate-limiting nucleation step followed by fibril propagation in a dynamic environment with monomers, oligomers, and multimers. Effective therapeutics are urgently needed to treat amyloid-associated diseases but few options exist. For example, human prion diseases are rapidly fatal and untreatable. No disease-modifying therapies for Alzheimer's disease are available. No approved therapies directly treat biofilms, which serve to protect bacteria from antimicrobial agents. To create effective anti-amyloid therapeutics, the mechanisms that confer amyloidogenicity and toxicity must be better understood. Here, we propose to use synthetic biology and nanotechnology to understand and treat the pathogenic mechanisms underlying amyloid-associated diseases. Using peptide arrays, oligomer-binding antibodies, and a novel discovery platform for amyloid-toxicity inhibitors, we will identify peptides that modulate amyloid assembly and toxicity. These findings will be used to study the molecular mechanisms which underlie amyloid pathogenesis and to create effective multivalent peptide-displaying nanoparticles as therapeutic candidates. In particular, we shall: i) identify amyloid nucleation domains using peptide arrays and isolate oligomer-binding peptides, ii) produce multivalent peptide-nanoparticles that modulate amyloid assembly and oligomers, and iii) elucidate the conformational species and mechanisms which underlie amyloid toxicity using in vitro characterization, cell toxicity assays, and an innovative synthetic-biology-based platform for screening, selecting, and evolving toxicity inhibitors. This work will shed insights into the mechanisms that link amyloid assembly, oligomers, and toxicity using peptide and nanoparticle modulators. We will test the hypothesis that certain oligomers are pathogenic by altering assembly pathways and oligomer species with engineered peptide-nanoparticles. We shall also explore whether peptide-nanoparticles can decrease mammalian cell toxicity by directing assembly pathways towards non-toxic intermediates and fibrils. Identifying amyloid modulators will reveal the molecular pathways which govern the formation and pathogenesis of toxic species. We will also develop an innovative and broad platform to screen, select, and enrich for inhibitors of mammalian cell toxicity by amyloids. In addition, this system can be applied to discover peptide inhibitors of other diseases, such as viral infections and tauopathies. This high-throughput platform is enabled by our expertise in synthetic biology and bacterial engineering. Public Health Relevance: Amyloids are centrally involved in a broad range of important human illnesses, including prion diseases, neurodegenerative conditions such as Alzheimer's and Parkinson's diseases, systemic amyloidoses, type II diabetes, and bacterial biofilms but few amyloid treatments are available. This proposal aims to identify peptides which modulate amyloid assembly and toxicity using peptide arrays, oligomer-binding antibodies, and a novel discovery platform enabled by synthetic biology. The resulting findings will be used to study the molecular mechanisms which underlie amyloid toxicity and to create effective multivalent peptide-displaying nanoparticles as therapeutic candidates for amyloid-associated diseases.

This project is awarded under the Nanoelectronics for 2020 and Beyond competition, with support by multiple Directorates and Divisions at the National Science Foundation as well as by the Nanoelectronics Research Initiative of the Semiconductor Research Corporation. In the last decade, the scaling of electronics has slowed due to limitations in underlying technologies as nanoscale dimensions are approached, including leakage, power dissipation, lithography, interconnect, and noise. Thus, fundamentally new paradigms for efficient and high-performance computation are needed to enable important applications such as studying complex biological systems. The research objective of this proposal is to breakthrough the scaling limits of conventional electronics with a hybrid analog-digital computational platform that integrates heterogeneous biological and nanoelectronic systems. The hypothesis that will be explored is that heterogeneous integration of electronic computation and biological computation is desirable since the former contributes precision, programmability, and speed while the latter yields highly parallel and efficient processing. These systems will be implemented in bio-inspired subthreshold electronics and living cells using synthetic biology; they shall be integrated with each other via microfluidics and biological nanomaterials.


This research has the potential to have broad impacts on a wide range of fields including computational science, synthetic biology, electrical engineering, nanomaterials research, infectious diseases, and biomedical science. Our experiments with novel forms of biological processing will enhance the breadth of computational platforms and provide insights into how biology achieves robust and efficient computation. Our biological circuits will advance the field of synthetic biology via new devices and architectures for engineering biological systems. By mimicking biological networks with subthreshold electronics, we can discover new high-performance electrical circuit designs. Our research into biologically synthesized and organized nanowires will inform our understanding of how biological systems are self-organized and shall enable new nanoelectronics, sustainable and environmentally friendly nanomaterial synthesis, and self-healing structures in the future. We will validate our computational platform on currently intractable problems in biomedical research, including modeling, simulating, and understanding how emergent properties, such as antibiotic resistance in bacteria and yeast, arise from large-scale networks. This computational platform will enable the unprecedented modeling of large-scale biological systems for hypothesis-driven biomedical research.

This project also aims to advance education and outreach efforts in the highly interdisciplinary disciplines involved in this research. This project shall create a new course, "Molecular Circuits Engineering", to train undergraduates and graduates in both computational and experimental techniques for molecular computation. The team will also supervise students in the International Genetically Engineered Machines (iGEM) competition to provide hands-on experimental training. A key priority is to work with MIT and the MIT Center for Integrative Synthetic Biology to actively recruit under-represented minorities and women into computational, synthetic biology, and bio-inspired electronics research via the Saturday Engineering Enrichment and Discovery Academy, the MIT Summer Research Program, and the Society of Women Engineers.

Biology is full of rich and complex systems where the interplay between past events, present inputs, and genetics determines cellular behavior. For example, stem cells are in a pluripotent "state" in which they can self-renew and also transform into diverse cell types with distinct functions, such as skin, bone, and blood cells, based on the timing and identities of regulatory signals. These properties require cells to store memory and perform computations, similar to modern computers. To understand such systems, the investigator proposes that biological systems can be thought of as state machines, in which the identity and function of a cell as well as transitions between these cell "states" are determined by past events and present inputs. The research team will build synthetic gene circuits that implement artificial biological state machines along with algorithms to guide their design. The research team will experiment on these circuits to quantify and gain insights into their behavior.

BROADER IMPACTS. To ensure broad impacts, the investigator will establish a new course called Biological Circuit Engineering Laboratory (BioCEL) to educate interdisciplinary scientists at the intersection of biology and engineering and will provide these teaching materials openly to the public. Furthermore, the investigator will engage high school, community college, and university students with opportunities for hands-on research. The investigator will create competitive games that teach the concepts used in this research to the general public. Finally, the investigator will establish an online resource to share the algorithms and circuits developed in this project to encourage their use by the broader scientific community. The creation of new design strategies for biological state machines is expected to shed insights into natural biological systems and advance important basic science, biotechnology, and biosensing applications.

Successful computing systems leverage their underlying technologies to solve problems humans simply cannot. Electronic systems harness the power of radio waves and electrons. Mechanical systems use physical force and physical interactions. Biological systems represent a computing paradigm that can harness evolution, adaptation, replication, self-repair, chemistry, and living organisms. Engineered, living biological systems which make decisions, process "data", record events, adapt to their environment, and communicate to one another will deliver exciting new solutions in bio-therapeutics, bio-materials, bio-energy, and bio-remediation. This project will create a quantitative set of freely available design principles, computational tools, mathematical models, physical biological artifacts, educational resources, and outreach activities. Once available, these resources will allow for novel, living biological solutions to be built more quickly, perform better, be more reliable to manufacture, and cost less to produce. This project is unique in that these resources will be explicitly developed to validate key computational concepts to understand how well these concepts can be applied rigorously and repeatedly to biology. This project decomposes these concepts into three areas: Computing Paradigm (digital, analog, memory, and communication), Computing Activity (specification, design, and verification), and Computing Metric (time, space, quality, and complexity). Once complete, this project will provide the most comprehensive, freely available, and computationally relevant set of building blocks to engineer biological systems to date.

By developing the tools, techniques, and materials outlined in this project, this research will fundamentally change the way biological systems are specified, designed, assembled, and tested. Advanced bio-energy, bio-sensing, bio-therapeutics, and bio-materials all will become increasingly viable commercial technologies that can be made better, cheaper, faster, and more safely as a result of this project. The education of an entire new generation of engineers will occur through workshops, coursework, and community engagement activities. This new generation will have access to these approaches which will influence how biological computation is done and how that process is communicated to the community. This project will bring computational questions and methods to the forefront of biotechnology via an interdisciplinary research team focused not on one-off solutions but on foundational computing principles.

Explicitly five unanswered questions will be addressed in this project: (1) What computational models are available to biology, what are their limits, and how do they perform? (2) What communication mechanisms are available to biology, what are their limits, and how do they perform? (3) What are the theoretical and empirical measures of quality, scale, time, and space in biological computing systems? (4) How generalizable are the concepts and "design rules" which can be learned from studying biological systems? (5) How can the results (data and learnings) from biological specification, design, and verification be authoritatively disseminated to the community as design principles and grand challenges? This project addresses these questions with an interdisciplinary team with expertise in theoretical computer science, electronic design automation, bio-physics/chemistry, control theory, and molecular cell biology. For more information visit www.programmingbiology.org.

1511431
Lu, Timothy
Massachusetts Institute of Technology

To counter the current Ebola outbreak one treatment option involves a cocktail of three antibodies called 'ZMapp', which has been shown to cure primates and has been reportedly used in the current outbreak to treat a small number of people. Despite the promise of ZMapp, its use has been highly restricted to just a few patients because of its severely limited availability. This low availability is because ZMapp production is currently carried out in plants, a slow process that is difficult to expand rapidly. Other anti-Ebola antibodies are similarly constrained by production systems that are challenging, time-consuming, and expensive to engineer and scale-up. Thus, there is a tremendous need for generalizable platforms that can be rapidly engineered to produce anti-infectious drugs and then easily scaled-up to create large numbers of doses. In this RAPID proposal yeast strains optimized for rapid production of anti-infectious antibodies will be adapted to express anti-Ebola antibodies. Yeast are promising hosts for manufacturing therapeutic molecules because they can be transported without refrigeration, quickly grown to large scales, and modified to make humanized therapies. It is anticipate that the engineered yeasts will be useful for economical and large-scale manufacturing of anti-Ebola therapies. In addition, this work will provide rapid-response capabilities for tackling future emerging diseases because the yeast platform can be quickly engineered with synthetic biology tools to generate new therapeutic agents. In addition, a distributed biomanufacturing approach will be applied by coupling engineered yeast with a novel micro-bioreactor technology that has the potential to mount rapid responses at the source of disease outbreaks.

The goal of this RAPID proposal is to establish a rapid and flexible biomanufacturing platform in Pichia pastoris for the production of anti-Ebola neutralizing antibodies. ZMapp, a cocktail of 3 neutralizing monoclonal antibodies (mAbs), has been shown to rescue 100% of rhesus macaques when administered up to 5 days post-infection. Zmapp1 is currently produced in the plant Nicotiana benthamiana, a slow process that is difficult to scale. Current efforts to express neutralizing antibodies from other hosts, such as CHO cells, also require substantial time and expensive infrastructure to scale. Moreover, quick delivery and long-term storage of mAb therapies and Ebola vaccines will likely be difficult in the under-developed areas most susceptible to Ebola outbreaks. Finally, viral mutations may necessitate the rapid development of new therapeutic agents. Thus, a rapidly engineerable and deployable platform for the portable and scalable production of multiple anti-infectious therapies would be useful for addressing the current Ebola crisis as well as future infectious outbreaks. In this project P. pastoris strains will be designed to produce anti-Ebola mAbs. P. pastoris can be engineered with human glycosylation pathways, can be lyophilized, and is highly efficient at secreting biologics and mAbs, thus enabling industrial-scale production and simplifying purification. The group has already modified P. pastoris with synthetic-biology tools to achieve rapid and specific engineering of strains that manufacture biologic drugs. Distributed and portable production of anti-Ebola mAbs will be achieved by integrating engineered P. pastoris strains with portable micro-bioreactors. The technology also enables new therapeutic molecules to be rapidly generated and scaled-up for testing and deployment against evolving viruses and emerging infections using synthetic biology tools and a highly adaptable biomanufacturing platform.

? DESCRIPTION (provided by applicant): The objective of this work is to create and validate a platform for engineering phage-based antimicrobials that share a common scaffold and are generalizable to target a broad range of bacterial pathogens, which we call phagebodies. Our phagebody technology will be used to create efficacious, well-defined, and targeted antimicrobials against carbapenem-resistant Enterobacteriaceae (CRE). CRE are resistant to nearly all antibiotics, and thus there is a tremendous unmet clinical need for new anti-CRE treatment strategies. Bacteriophages enact targeted killing of specific bacteria without affecting neighboring bacteria. These narrow-spectrum agents differ significantly from most chemical antibiotics, which exhibit broad-spectrum activity and can therefore generate undesirable side effects such as Clostridium difficile overgrowth and selection for antibiotic resistance. Furthermore, the antibiotic pipeline for pathogens such as CRE is dwindling. However, for narrow-spectrum agents such as phages to be useful in clinical settings, technologies for the extensible and high-throughput creation of targeted phage therapeutics are critically needed. In conventional phage therapy, cocktails of naturally isolated phages are constructed to cover a broad set of a given target bacteria. This approach poses several difficulties for the use of phage therapy in Western clinical settings. Natural phage cocktails are often composed of phages from diverse families, thus posing challenges for characterization and manufacturing under conditions needed for clinical application. In addition, natural phage isolation protocols are reliant on environmental sampling and screening, which can be laborious and challenging to scale to cover a broad range of perpetually evolving bacterial targets. Here, we will create and optimize a novel strategy for engineering well-defined and customizable phagebodies as antimicrobials. In preliminary studies, we have shown that common phage scaffolds can be retargeted against new bacterial hosts by modular tail fiber swapping or mutagenesis of host-recognition domains within tail fiber tips. We will extend these findings to create highly diversified phage banks that will be screened against panels of carbapenem-resistant E. coli and K. pneumoniae to identify efficacious phages that kill these bacteria. These phages shall be validated and optimized within in vitro and in vivo models of infection. This work is significant since it will provide an extensible technological platform to discover effective phage-based antimicrobials that can be further advanced into preclinical and clinical development against urgent threats, such as CRE and other pathogens. This work is innovative since it involves the novel creation of tailored phagebody antimicrobials that overcome prior challenges associated with natural phage therapy.

PROJECT SUMMARY To address the complexity of heterogeneous cancers that are resistant to chemotherapy and frequently recur or metastasize, we propose to develop a set of tools based on multidisciplinary innovations combining Synthetic Biology, Cancer Organoid Technology, and Bioinformatics. These Synthetic Tools to Annotate Reporter Organoids for Cancer Heterogeneity and Recurrence Development (StarOrchard) include: Synthetic Promoter Activated Recombination of Kaleidoscopic Organoids (SPARKO), Combinatorial Genetics En Masse (CombiGEM), and single-cell RNA sequencing panorama (Scanorama). SPARKO can annotate heterogeneous cancer populations in living cells via fluorescent protein expression libraries to make multi- colored tumor organoids. CombiGEM can rapidly identify potential therapeutic targets via large-scale, massively parallel, and unbiased combinatorial genetic screens. Scanorama can integrate the analysis of large datasets of single-cell transcriptomics via sophisticated bioinformatics algorithms. These tools focus on barcoding strategies to enable accurate tracking and analysis of individual tumor cells that harbor distinct genetic aberrations, and substantially expand the utility of the Next Generation Cancer Models (NGCMs) for cancer mechanistic investigations or therapeutic discovery. The StarOrchard tools enable targeted genetic perturbations in annotated heterogeneous tumor phenotypes without destroying cells for sequencing. These tools will be applied to a large number and variety of NGCMs to optimize experimental protocol. To ensure success, we have convened an outstanding team: PI Timothy K. Lu, MD, PhD, has made strikingly original contributions to Synthetic Biology tools that enable high-throughput genetic interrogation of cancer cell drug dependency; PI Ömer Yilmaz, MD, PhD, has extensive expertise in cancers of the gastrointestinal tract and has developed novel technologies to maintain patient-derived colon cancer organoids for in vivo modeling; and PI Bonnie Berger, PhD, will use her expertise in bioinformatics and her Scanorama algorithm to integrate data across all tumor types based on dynamic single cell RNA sequencing (scRNAseq). We are also supported by leading experts in cancer biology and various cancer types at both the basic science and clinical oncology frontiers of cancer research. The collective commitment and multidisciplinary contributions of the entire team ensure the establishment of an openly distributed investigative tool set that accelerates advancements in cancer biology and therapeutic discovery