@SheriHarari @bblarsen1 @LucasKampman @HelenChuMD The final published version of the study is now available at

Finally, we plan to repeat this effort in ~6 months prior to next vaccine strain selection. If you have sera cohorts that you think would be well suited for this type of study and are potentially interesting in collaborating, please feel free to reach out.

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Thanks to @CKikawa & @huddlej for leading study, also Andrea Loes, Sam Turner, Jover Lee, Ian Barr, @bencowling88, Jan Englund, @GreningerLab, Ruth Harvey, Hideki Hasegawa, Faith Ho, Kirsten Lacombe, @nancyleung_hk, Nicola Lewis, Heidi Peck, Shinji Watanabe, Derek Smith, @trvrb

Many more analyses are possible w these data. But we have made all data & code available now at https://t.co/NGLH9zYmUg Reason is to provide near real-time titer data that can be leveraged by scientific community for real-time decisions like vaccine strain selection.

Above visualizations just scratch surface of data: there is tremendous heterogeneity across sera from different individuals not easily summarized by median/mean. Indeed, we previously found this heterogeneity may be important for influenza evolution: https://t.co/zFtxM1jJuO

Working w @huddlej @trvrb, we mapped neutralization titers on interactive Nextstrain trees to visualize neutralization across subclades and natural mutations. See: https://t.co/TDAImxtnxp https://t.co/0afQn7VjBR

We then measured how 188 human sera recently collected at four different sites neutralized all 140 influenza strains in library. Titers are summarized below; can be examined interactively at https://t.co/T1O0eN22KW & https://t.co/X4F6xQ6kZp

In spring of 2025, we designed library of naturally occurring human seasonal influenza strains that represented diversity of available sequences at that time; this library continues to cover most sequenced diversity of H3N2 and H1N1 hemagglutinin today.

To do this, we used sequencing-based neutralization assays that measure many neutralization curves simultaneously ( https://t.co/5DWrewho1P& https://t.co/zFtxM1jJuO) Approach enabled one grad student (@CKikawa) to measure ~26,000 neutralization curves in ~5 months.

But because it takes time to perform experiments, measurement of how current strains are neutralized by human serum antibodies can lag timeline for vaccine strain selection. Our goal was to use new approach to characterize human antibody landscape at scale in near real-time.

As background, seasonal influenza evolves to erode antibody immunity. Viruses w more antibody escape spread in human population & people more likely to be infected by strains their antibodies neutralize less well. Vaccine updated bi-annually to keep pace w viral evolution.

In new study led by @CKikawa, we provide near real-time data on human neutralizing antibody landscape to influenza by measuring ~26,000 titers to >100 recent viral strains. Data can inform vaccine selection & evolutionary/epidemiological modeling. https://t.co/rthJdShpwP

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Data in interactive form at https://t.co/jMEPhHnUWe Thanks to Xiaohui Ju for leading study Thanks to @msdiamondlab for help w this study Also Will Hannon, @CaelanRadford, @bblarsen1, Daved Fremont, Ofer Zimmerman, Tomasz Kaszuba, Chris Nelson, Israel Baltazar-Perez, S Nelson

Overall, these results shed light on how Chikungunya virus naturally infects cells from highly diverse species. Sequence-function information can aid in immunogen engineering, and loss-of-tropism mutants could be useful in vaccines as well.

After using pseudoviruses & reporter particles to show mutations *loss* of function, we engineered into Chikungunya virus: mutants lost ability to infect human or mosquito cells. So we reduced natural tropism for both human & mosquito cells to just one type of cell.

We next used non-replicative single-cycle alphavirus reporter particles (which provide another safe way to study mutations) to validate that mutations identified in deep mutational scanning indeed specifically impaired entry in human or mosquito cells only.

Sites where mutations specifically impair entry in 293T-MXRA8 cells mostly at MXRA8 binding interface. We also find sites where mutations specifically impair entry in C6/36 cells. Although mosquito receptor unknown, we hypothesize these sites at its binding interface.

Most mutations similarly affect entry in all three cells, but some have cell-specific effects. For instance, mutations at E2 site 119 are generally tolerated in C6/36 and 293T-TIM1 cells, but deleterious in 293T-MXRA8 cells. (See https://t.co/FTUKHqLxA6 interactive plot.)

We then measured how mutations affect entry in two other cells: the mosquito cell-line C6/36, and 293T cells expressing TIM1 which enables envelope protein independent cell binding by virion associated phosphatidylserine.