Gabriel D. Victora’s team engineered mice so competing B cells all began with the same unmutated antibody sequence. They immunized the mice to form germinal centers and then tracked B cells using multiphoton microscopy, laser-based photoactivation and DNA sequencing. The researchers followed thousands of individual B cells across 119 germinal centers and reconstructed family trees of cell lineages.
They also used Deep Mutational Scanning (DMS), a technique that links almost every possible amino-acid change to antibody performance. From DNA sequences the team could infer binding strength and structural stability. At the level of a single germinal center, evolution often seemed almost random: some lineages expanded, others vanished, and promising mutations sometimes failed. Some centers showed clonal bursts while others kept many competing lineages.
Repeated selection across many germinal centers produced consistently stronger antibodies. The system showed a small bias toward beneficial mutations and tended to favor mutations that the cellular machinery makes easily. The researchers say germinal centers are more selective than thought, a result that could guide vaccine design.
Difficult words
- germinal center — area in lymphoid tissue where B cells evolvegerminal centers
- deep mutational scanning — laboratory method testing effects of many protein changesDMS
- lineage — group of cells descended from one original celllineages
- mutation — a change in DNA that can alter proteinsmutations
- antibody — protein made by immune system to bind targetsantibodies
- selection — process where useful cell variants become more common
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Discussion questions
- How could the finding that germinal centers are more selective help scientists design better vaccines?
- Why might some promising mutations fail even if they seem useful? Give one or two possible reasons.
- Have you heard of laboratory methods that test many protein changes? How do you think such methods change medical research?
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