High-throughput, combinatorial approaches have revolutionized small molecule drug discovery. Here we describe our work on the combinatorial development of biomaterials for medical devices ranging from nanoparticulate delivery systems to macroscopic devices.
One focus of our work is on nanoparticulate, intracellular delivery systems for RNA therapy and gene editing. Libraries of degradable polymers and lipid-like materials have been synthesized, formulated and screened for their ability to delivery macromolecular payloads inside of cells. These nanoformulations facilitate in vivo delivery, enabling gene suppression with siRNA, gene expression with mRNA, or permanent genetic editing using the CRISPR/Cas9 system, providing therapeutic application for the treatment of disease in both rodent and primate models.
A second focus of our work is on developing biomaterials that can avoid the fibrotic response common to implanted medical devices. Using combinatorial chemistry, we have developed new materials capable of avoiding fibrosis and scar tissue formation. These show particular promise as vehicles for the immune-isolation of transplanted cells, for the treatment of diabetes. When formulated into microcapsules these materials enable functional, long-term islet transplantation in immune competent, diabetic rodents, as well as normal non-human primates.
"Mammoth Biosciences is a biotechnology company in San Francisco leveraging technologies developed in Jennifer Doudna’s lab at UC Berkeley. We are harnessing the natural diversity of CRISPR for a new purpose: a programmable diagnostics platform, called DETECTR, that works by employing CRISPR nucleases that are programmed to find a defined genetic sequence. Upon finding the target DNA or RNA sequence, the CRISPR enzyme cleaves a reporter molecule, which confirms the presence of the target sequence.
Mammoth’s DETECTR technology offers several key advantages over existing PCR-based technology: (1) isothermal signal amplification for rapid target detection obviating the need for thermocycling (2) compatibility with multiple sample matrices, (3) single nucleotide target specificity, (4) multiplexing capability and broad coverage of targets via guide pooling, (5) quick development cycle, and (6) integration with portable, inexpensive formats such as lateral flow strips. Together, these features combine the precision of nucleic acid-based detection with the low cost and accessibility of antibody-based tests.
To help disrupt the chain of transmission of the novel coronavirus COVID-19 outbreak, Mammoth has reconfigured our DETECTR platform to rapidly and accurately detect the SARS-CoV-2 virus and visualized on a lateral flow strip (Broughton et al., Nature Biotech 2020). Mammoth’s SARS-CoV-2 DETECTR assay utilizes RT-LAMP reagents to amplify both viral RNA and a human RNase P, as a sample control. Following pre-amplification at 60°C for 30 minutes, the reaction is incubated with Cas12 reagents for 10 minutes at 37°C. Cas12 rapidly initiates cleavage of a reporter molecule only when its target, as programmed by its gRNA, is present. Finally, a lateral flow strip is added to the reaction and a visual readout of the presence or absence of SARS-CoV-2 is visualized within 2 minutes.
Our SARS-CoV-2 DETECTR assay is highly specific to SARS-CoV-2 and does not detect SARS-CoV (~76% identity) or the closely related bat-SL-CoV strain (~96% identity). In collaboration with Dr. Charles Chiu and colleagues at UCSF, we tested the system on clinical samples from 36 patients with COVID-19 and 42 with other respiratory illnesses. The test achieved a 95% positive predictive agreement and 100% negative predictive agreement when compared to the CDC SARS-CoV-2 qRT-PCR test. Overall, we have designed our SARS-CoV-2 DETECTR assay to leverage commercially available reagents, lateral flow strips, and enzymes to facilitate rapid scale up of the test."
Synthetic biology is bringing together engineers, physicists and biologists to model, design and construct biological circuits out of proteins, genes and other bits of DNA, and to use these circuits to rewire and reprogram organisms. These re-engineered organisms are going to change our lives in the coming years, leading to cheaper drugs, rapid diagnostic tests, and synthetic probiotics to treat infections and a range of complex diseases. In this talk, we highlight recent efforts to create synthetic gene networks and programmable cells, and discuss a variety of synthetic biology applications in biotechnology and biomedicine.
We are in the middle of the COVID-19 pandemic, a time that has both impacted our ability to conduct research and keep labs open, but also one that has required translational scientists to direct energies towards identifying therapeutic opportunities for patients. I will describe the assay development and drug repurposing screening response at NCATS, and the OpenData COVID-19 portal for openly sharing repurposing HTS data with the scientific community as rapidly as possible. I will also describe work in my group to develop a proximity assay for the SARS-CoV-2 Spike protein and its host receptor target ACE2, from asssay development to repurposing screening.
The COVID-19 pandemic has created unprecedented stresses for therapeutic development. With hundreds of thousands perishing in only a few months, there is great interest in discovering pharmacological treatments active against the SARS-CoV-2 virus; however, extant preclinical systems to study the virus and disease have a high risk of failure in human translation, with most in vitro work being done in an immortalized African green monkey cell line (Vero E6) and few-to-no in vivo models in the early phase of the pandemic.
In this talk I will describe the work done at Recursion to discover therapeutics for COVID-19. Recursion applied deep learning-based image AI to rapidly develop a human-cell-based assay for SARS-CoV-2 infection, applying phenotypic screening to deliver value even with the paucity of knowledge regarding virus-host interaction biology and targets. We subsequently deployed this assay to screen thousands of approved and clinical compounds for therapeutic benefit with minimal staff in only a few weeks. The utility of the platform willbe demonstrated with recent results from our screening work.
The immune system consists of complex gene regulatory networks that allow a rapid transition of different cellular states during an immune response. Cell-surface marker analysis using flow cytometry and single cell RNA-seq have allowed characterization of immune cell complexity, however protein-only or RNA-only analysis can greatly limit the understanding of cellular heterogeneity and regulatory networks during complex responses. Protein profiling methods using oligonucleotide conjugated antibodies, such as BD AbSeq on the Rhapsody platform, address this by allowing simultaneous analysis of mRNA and high-plex protein panels from tens of thousands of single cells with a single readout. While detecting new molecules from single cells can open up a new avenues of research, it can be costly to sequence deeply enough to obtain reliable data, and much of the cost can go towards sequencing a few highly abundant targets.
To address this issue we tested three approaches to reduce sequencing requirements and more efficiently distribute sequencing reads without sacrificing assay sensitivity in AbSeq experiments. Using T cell activation as an experimental system to probe transcriptional and post-transcriptional regulatory networks, we compared up-front T cell enrichment, removal of high expressors, and signal dampening by mixing unconjugated antibodies with high expressors as potential methods to reduce sequencing requirements. Here we demonstrated that all approaches reduce sequencing cost by up to 60% for the protein panel while still successfully characterizing gene regulatory networks during an immune response. Furthermore these approaches more efficiently distribute sequencing reads, leading to improved detection of low-abundance proteins and helping to identify rare cell populations. Using these methods researchers can better harness new multiomic methods for biological discovery while controlling experimental cost.
Reprogramming immune cell behavior is at the forefront of cellular therapies for cancer, but significant hurdles remain to achieving a safe, durable, and controlled response by engineered T cells, especially when treating solid tumors. The creation of a cellular product from a patient’s own T cells that target a tumor antigen must be robust enough to work across multiple patients (due to person-to-person variation in immune cell function) while also being adaptable enough to respond to the contextual cues of each patient’s tumor microenvironment.
At ArsenalBio, we are building a new class of therapeutics by reprogramming T cells through genome engineering, allowing them to recognize and kill tumor cells; overcome suppressive signals; and persist in the patient’s body. Our approach is centered around designing synthetic receptors, encoding them in genetic circuits, and testing whether they impart the desired cellular behaviors in response to external signals.
High-throughput screening for cancer drugs has traditionally entailed large cellular screens with small-molecule libraries. We will describe our approach to bringing large-scale, integrated automation into the cell therapy space. By combining synthetic biology and genome engineering with complex cellular assays and multimodal readouts-- and doing so at scale-- we are building a discovery engine for cellular therapies.
Coronavirus infection spreads in clusters, and early identification of these clusters is critical for slowing down the spread of the virus. Here, we propose that daily population-wide surveys that assess the development of symptoms caused by the virus could serve as a strategic and valuable tool for identifying such clusters and informing epidemiologists, public-health officials and policymakers.
We show preliminary results from an Israeli survey of a cumulative number of over 1.5 million responses, demonstrating that such data enabled faster detection of spreading zones and patients; acquisition of a current snapshot of the number of people in each area who have developed symptoms; prediction of future spreading zones several days before an outbreak occurs; and evaluation of the effectiveness of the various social-distancing measures taken and their contribution to reducing the number of symptomatic people.
This information could provide a valuable tool for decision-makers in those areas in which strengthening of social-distancing measures is needed and those in which such measures can be relieved. We found that following severe lockdown measures imposed in Israel, there was a sharp decline in every individual symptom, including our most common symptoms of cough and rhinorrhea or nasal congestion, which decreased from 14.5% and 13.8% of the survey responders, respectively, to 2.4% and 2.5%. We also observed reduction in symptoms separately in the vast majority of cities in Israel.
Overall, these results demonstrate a profound decrease in a variety of clinical symptoms following the implementation of a lockdown in Israel. As our survey symptoms are not specific to COVID-19 infection, this effect likely represents an overall nationwide reduction in the prevalence of infectious diseases, including COVID-19. This quantification may be of major interest for COVID-19 pandemic, as many countries consider implementation of lockdown strategies.
Targeting disease-associated DNA sequences with CRISPR/Cas9-mediated genome editing offers the potential to cure human genetic disorders. A critical step in the development of such potentially curative therapeutics requires the selection of a guide RNA (gRNA) to edit a disease-causing sequence in the genome.
Next-generation sequencing (NGS) is a sensitive, accurate, and efficient method for the identification of successful gRNA directed genome editing events; however, general multiplexed NGS protocols require many tedious and time-consuming user preparation activities like sample transfer (pipetting), purification, tracking, quantification, and normalization calculations. These manual efforts significantly limit the accuracy and precision of sequencing results, total sequencing throughput, and ultimately the selection of the most active and specific gRNAs. Therefore, consistent NGS library preparation workflows are desired to ensure proper on-target genome editing with high gene editing sensitivity, assay reproducibility, and scalability in throughput.
In this presentation, we will discuss how a fully automated NGS preparation platform has enabled the identification of on-target genome editing events and the selection of highly active gRNAs for subsequent functional in vitro, in vivo, and off-target assays. The fully automated system contains numerous integrated devices and has enabled routine NGS library preparation for over 800,000 samples for gRNA selection. Also, the current fully automated system has reduced manual preparation time by 6X and increased throughput by ~2.4X with the possibility of doubling throughput by overnight operation.
This robust automated platform supports ontarget gRNA validation and NGS screens at Intellia, while various subsequent functional assays are also enabled using automated workflows involving cell culture and liquid handling robotics. Altogether, these automation platforms at Intellia provide core functions to help discover lead gRNAs that drive main therapeutic programs like NTLA-2001 and deliver curative therapeutic treatments for patients by harnessing the modularity of CRISPR/Cas9 genome editing.
Proteins are informative biomarkers, as they are often directly related to the disease etiology. Historically, ELISA has been the gold standard for protein assays in the clinical environment. We have developed an ultrasensitive protein detection technology that converts ELISAs into digital measurements. The digital ELISA technology enables proteins to be measured that have never been previously detected in clinical samples. We have used the technology to develop assays for SARS-CoV-2 that provides new diagnostics capabilities as well as insight into fundamental aspects of disease progression.