Virus World

Researchers create virus-resistant, safely restrained E. coli for medical and industrial applications.  Engineering bacterial genomes with beneficial traits is the goal of many synthetic biology researchers. Now, work from the lab of George Church, PhD, at Harvard Medical School (HMS), reports the construction of an Escherichia coli strain that is not only immune to viral infections but has reduced potential of escaping into the wild. The work may reduce the threat of viral contamination when harnessing bacteria to produce medicines such as insulin as well as other useful substances, such as biofuels. Currently, viruses that infect vats of bacteria can halt production, compromise drug safety, and cost millions of dollars.

Dyno Therapeutics announces a publication in Science demonstrating the power of a comprehensive machine-guided approach to improve adeno-associated virus (AAV) capsids for gene therapies. Working to surpass the few naturally occurring AAV capsids currently in use, the authors synthesized large libraries of capsids and discovered changes that improve key properties preventing current AAVs from optimal therapeutic function. Dyno is a biotechnology company pioneering the use of artificial intelligence in gene therapy.

AAV capsids are presently the most commonly used vector for gene therapy because of their established ability to deliver genetic material to patient organs with a proven safety profile. However, there are only a few naturally occurring AAV capsids, and they are deficient in essential properties for optimal gene therapy, such as targeted delivery, evasion of the immune system, higher levels of viral production, and greater transduction efficiency. Starting at Harvard in 2015, the authors set out to overcome the limitations of current capsids by developing new machine-guided technologies to rapidly and systematically engineer a suite of new, improved capsids for widespread therapeutic use.

In the research published in Science, the authors demonstrate the advance of their unique machine-guided approach to AAV engineering. Previous approaches have been limited by the difficulty of altering a complex capsid protein without breaking its function and by the general lack of knowledge regarding how AAV capsids interact with the body. Historically, rather than addressing this challenge directly, the most popular approaches to capsid engineering have taken a roundabout solution: generating libraries of new capsids by making random changes to the protein. However, since most random changes to the capsid actually result in decreased function, such random libraries contain few viable capsids, much less improved ones. Recognizing the limitation of conventionally generated capsid libraries, the authors implemented a machine-guided approach that gathered a vast amount of data using new high-throughput measurement technologies to teach them how to build better libraries and, ultimately, lead to synthetic capsids with optimized delivery properties. Focusing on the AAV2 capsid, the authors generated a complete landscape of all single codon substitutions, insertions and deletions, then measured the functional properties important for in vivo delivery. They then used a machine-guided approach, leveraging these data to efficiently generate diverse libraries of AAV capsids with multiple changes that targeted the mouse liver and that outperformed AAVs generated by conventional random mutagenesis approaches. In the process, the authors' systematic efforts unexpectedly revealed the existence of a previously-unrecognized protein encoded within the sequence of all the most popular AAV capsids, which they termed membrane-associated accessory protein (MAAP). The authors believe that the protein plays a role in the natural life cycle of AAV.

"This is just the beginning of machine-guided engineering of AAV capsids to transform gene therapy," underscores co-author Sam Sinai, Ph.D., Lead Machine Learning Scientist and co-founder of Dyno Therapeutics. "The success of the simple linear models used in this study has led us to pursue more data and higher capacity machine learning models, where the potential for improvement in capsid designs feels boundless." 

"The results in the Science publication demonstrate, for the first time, the power of linking a comprehensive set of advanced techniques - large scale DNA synthesis, pooled in vitro and in vivo screens, next-generation sequencing readouts, and iterative machine-guided capsid design - to generate optimized synthetic AAV capsids," explains co-first and co-corresponding author Eric D. Kelsic, Ph.D., CEO and co-founder of Dyno Therapeutics. "At Dyno, our team is committed to advancing these technologies to identify capsids that meet the urgent needs of patients who can benefit from gene therapies."....

Published in Science (29 November, 2019):

https://doi.org/10.1126/science.aaw2900

Preliminary findings suggest that B.1.1.7, a SARS-CoV-2 variant first identified in the United Kingdom, might be more transmissible because it spends more time inside its host than earlier variants do. Previous studies have estimated that B.1.1.7, which is now spreading rapidly in a number of countries, is roughly 50% more contagious than earlier coronavirus variants are. Yonatan Grad at the Harvard T.H. Chan School of Public Health in Boston, Massachusetts, and his colleagues examined the results of daily SARS-CoV-2 tests on 65 people infected with SARS-CoV-2, including 7 infected with B.1.1.7 (S. M. Kissler et al. Preprint at https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37366884; 2021).

The team looked at how long the virus persisted, and the amount of virus present at each time point. In people infected with B.1.1.7, infections lasted an average of 13.3 days, compared with 8.2 days in people with other variants. There was little difference in the peak concentrations of the virus between the two groups. These findings hint that B.1.1.7 is more easily transmitted than other variants are because people who catch it are infected for a relatively long time, and can therefore infect a larger number of contacts. This suggests that longer quarantine periods might be warranted for individuals infected with this variant. The findings have not yet been peer reviewed.

Preprint available at:

https://dash.harvard.edu/handle/1/37366884