Near-real time mapping of the human neutralizing antibody landscape to influenza to inform vaccine selection

 

Jesse Bloom

Fred Hutch Cancer Center / HHMI

Options for Control of Influenza Meeting

August 30, 2026

 

These slides: https://slides.com/jbloom/options2026

Year

HA amino-acid mutations

Hemagglutinin (HA) of human influenza evolves rapidly

HA of human H3N2 influenza has accumulated >45 mutations over last 18 years. x indicates vaccine strains.

HA evolution fixes mutations in regions targeted by neutralizing antibodies

Due to influenza evolution, vaccine updated ~9 months before it will be used each year

In February strains chosen for Northern Hemisphere vaccine administered ~October that year.

In September, strains chosen for Southern Hemisphere vaccine administered the next ~May.

Separate update decisions for H3N2, H1N1, and B strains; not every component changed each time.

Antigenically charactering influenza strains in near real-time to inform vaccine choice

1) Sequencing-based neutralization assays to rapidly measure how human serum antibodies neutralize many viral strains.

 

2) Proof-of-principle: human serology helps explain real-world viral evolution.

 

3) Near real-time data on the current human neutralizing antibody landscape.

Sequencing-based neutralization assays

Traditional neutralization assays are low throughput (each row measures one serum vs one virus)

fraction infectivity

Sequencing-based neutralization assays measure titers to many strains at once

Loes et al (2024); Kikawa et al (2026)

Loes et al (2024); Kikawa et al (2026)

Sequencing-based neutralization assays measure titers to many strains at once

Loes et al (2024); Kikawa et al (2026)

Sequencing-based neutralization assays measure titers to many strains at once

different recent H3N2 viral strains

Measure titers to many strains for each serum

child has low titers to these strains

Kikawa et al (2026)

Kikawa et al (2026)

different recent H3N2 viral strains

Strain-specific titers differ among people

child has low titers to these strains

adult has low titers to these strains

Proof-of-principle: human serology helps explain real-world viral evolution

Measured neutralization for large set of sera against many strains

sera from 95 individuals of different ages

Measured neutralization by each individual serum

Kikawa et al (2026)

sera from 95 individuals of different ages

Measured neutralization by each individual serum

Measured neutralization by pool of all sera

Measured neutralization by the same set of sera as a pool

Kikawa et al (2026)

Estimated actual growth rates of different strains in human population

Kikawa et al (2026)

Multinomial logistic regression fits to estimate strain growth

Growth rates of influenza strains correlate with fraction of sera with titer below cutoff

Kikawa et al (2026)

But viral growth rates do not correlate with titers of a pool of all serum

Kikawa et al (2026)

A strain's antigenic success depends on fraction of humans with low titers to it

See also Kim, ..., Cobey (2024)

Near real-time data on the current human neutralizing antibody landscape

Near real-time measurement of titers to recent strains to inform vaccine choice

All data openly shared as it is collected, so anyone can analyze it to inform vaccine-strain selection and advance public health.

 

Currently generating data for A/H3N2 and A/H1N1; hope to expand to influenza B.

 

Data shared so far:

Near real-time measurement of titers to recent strains to inform vaccine choice

All data openly shared as it is collected, so anyone can analyze it to inform vaccine-strain selection and advance public health.

 

Currently generating data for A/H3N2 and A/H1N1; hope to expand to influenza B.

 

Data shared so far:

I will discuss latest data, much of which was generated in last two weeks and is still incompletely analyzed (so examine yourself too!)

In May, we chose set of recent seasonal strains

Most recently sequenced human influenza within one HA1 mutation of strain in our set

Most recently sequenced human influenza within one HA1 mutation of strain in our set

Measured neutralization of 78 H3N2 and 62 H1N1 strains by >200 human sera

Human sera assayed (all collected between April and June of 2026):

  • Seattle Children's Hospital: 40 convenience samples
  • University of Washington Medical Center: 88 convenience samples
  • Creative Testing Solutions / UCSF: 32 samples from blood donors
  • Victorian Infectious Diseases Lab (Australia): 58 pre- or post-vaccine samples

[Numbers as of Aug-28-2026, more sera still being assayed]

H3N2 results

Low titers to some emerging subclade K variants

Lowest titers are to subclade K variants with mutation at sites 222 or 223.

 

See also:

Sites 222 and 223 are in region of HA not mutated in original subclade K

Mutations at these sites likely erode residual antibodies not already escaped by earlier subclade K mutations; see Liu et al (2026).

V223I is recurrently spreading in subclade K

H1N1 results

Low titers to D.3.1.1, especially with G155E

Most D.3.1.1 strains have lower titers than current D.3.1 vaccine.

 

Titers lowest to strains with G155E.

 

See also:

G155E most affects potent sera from 15-25 yr olds

D.3.1.1 has several mutations relative to D.3.1, with G155E an additional change

D.3.1.1 now dominates, G155E spreading

Conclusions

 

Sequencing-based neutralization assays can measure the neutralization of recent strains by current human antibodies in near real time.

 

These titer measurements are informative about influenza evolution.

 

We are generating and sharing large datasets twice per year.

 

Current data suggests:

  • H3N2 subclade K variants with mutations in antigenic region D (eg, V223I)
  • H1N1 subclade D.3.1.1 has advanced over D.3.1, watch G155E variant

Thanks

These slides: https://slides.com/jbloom/options2026

Most recent data: https://github.com/jbloomlab/flu-seqneut-2026

Fred Hutch / Seattle Childrens: Trevor Bedford, Janet Englund, Kirsten Lacombe

University of Washington: Alex Greninger

Penn: Scott Hensley, Jiaojiao Liu, Sydney Gang, Elizabeth Drapeau, Tachianna Griffiths

Cambridge: Sam Turner, Derek Smith

Basel: Richard Neher

EPI-HK: Ben Cowling, Nancy Leung, Faith Ho

NIID Japan: Shinji Watanabe, Hideki Hasegawa

CTS / UCSF: Michael Busch, Marion Lanteri, Mars Stone, Bryan Spencer