Parallel single B cell transcriptomics to elucidate pig B cell repertoire.

Pork is the most widely consumed meat on the planet, placing swine health as a critical factor for both the world economy and the food industry. Infectious diseases in pigs not only threaten these sectors but also raise zoonotic concerns, as pigs can act as "mixing vessels" for several animals and human viruses and can lead to the emergence of new viruses that are capable of infecting humans. Several efforts are ongoing to develop pig vaccines, albeit with limited success. This has been largely attributed to the complex nature of pig infections and incomplete understanding of the pig immune responses. Additionally, pig has been suggested to be a good experimental model to study viral infections (e.g., human influenza). Despite the significant importance of studying pig immunology for developing infection models, zoonosis, and the crucial need to develop better swine vaccines, there is still very limited information on the response of the swine adaptive immune system to several emerging pathogens. Particularly, very little is known about the pig B cell repertoire upon infection. Understanding the B cell repertoire is especially crucial towards designing better vaccines, predicting zoonosis and can provide insights into developing new diagnostic agents. Here, we developed methods for performing parallel single pig B cell (up to 10,000 B cells) global and immunoglobulin transcriptome sequencing. We then adapted a computational pipeline previously built for human/mouse sequences, to now analyze pig sequences. This allowed us to comprehensively map the B cell repertoire and get paired antibody sequences from pigs in a single parallel sequencing experiment. We believe that these approaches will have significant implications for swine diseases, particularly in the context of swine mediated zoonosis and swine and human vaccine development.

A computationally designed ACE2 decoy has broad efficacy against SARS-CoV-2 omicron variants and related viruses in vitro and in vivo.

SARS-CoV-2, especially B.1.1.529/omicron and its sublineages, continues to mutate to evade monoclonal antibodies and antibodies elicited by vaccination. Affinity-enhanced soluble ACE2 (sACE2) is an alternative strategy that works by binding the SARS-CoV-2 S protein, acting as a 'decoy' to block the interaction between the S and human ACE2. Using a computational design strategy, we designed an affinity-enhanced ACE2 decoy, FLIF, that exhibited tight binding to SARS-CoV-2 delta and omicron variants. Our computationally calculated absolute binding free energies (ABFE) between sACE2:SARS-CoV-2 S proteins and their variants showed excellent agreement to binding experiments. FLIF displayed robust therapeutic utility against a broad range of SARS-CoV-2 variants and sarbecoviruses, and neutralized omicron BA.5 in vitro and in vivo. Furthermore, we directly compared the in vivo therapeutic efficacy of wild-type ACE2 (non-affinity enhanced ACE2) against FLIF. A few wild-type sACE2 decoys have shown to be effective against early circulating variants such as Wuhan in vivo. Our data suggest that moving forward, affinity-enhanced ACE2 decoys like FLIF may be required to combat evolving SARS-CoV-2 variants. The approach described herein emphasizes how computational methods have become sufficiently accurate for the design of therapeutics against viral protein targets. Affinity-enhanced ACE2 decoys remain highly effective at neutralizing omicron subvariants.