Evidence map›Paper›PMID 36986310›Full record

ArticlePathogens (Basel, Switzerland)2023

Novelty Search Promotes Antigenic Diversity in Microbial Pathogens.

Brandon Ely, Winston Koh, Eamen Ho, Tasmina M Hassan, Anh V Pham, Weigang Qiu

Open access · goldAbstract read
In one paragraph

Article in Pathogens (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 98% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Brandon ElyDepartment of Biology, Graduate Center, City University of New York, New York, NY 10016, USA.ORCID 0000-0002-9554-3424
Winston KohDepartment of Biological Sciences, Hunter College, City University of New York, New York, NY 10065, USA.ORCID 0000-0002-9241-4862
Eamen HoDepartment of Biological Sciences, Hunter College, City University of New York, New York, NY 10065, USA.ORCID 0000-0001-5380-0034
Tasmina M HassanDepartment of Biological Sciences, Hunter College, City University of New York, New York, NY 10065, USA.ORCID 0000-0003-4389-8044
Anh V PhamDepartment of Biological Sciences, Hunter College, City University of New York, New York, NY 10065, USA.
Weigang QiuDepartment of Biology, Graduate Center, City University of New York, New York, NY 10016, USA.ORCID 0000-0003-4585-1872
City University of New York · USThe Graduate Center, CUNY · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Driven by host-pathogen coevolution, cell surface antigens are often the fastest evolving parts of a microbial pathogen. The persistent evolutionary impetus for novel antigen variants suggests the utility of novelty-seeking algorithms in predicting antigen diversification in microbial pathogens. In contrast to traditional genetic algorithms maximizing variant fitness, novelty-seeking algorithms optimize variant novelty. Here, we designed and implemented three evolutionary algorithms (fitness-seeking, novelty-seeking, and hybrid) and evaluated their performances in 10 simulated and 2 empirically derived antigen fitness landscapes. The hybrid walks combining fitness- and novelty-seeking strategies overcame the limitations of each algorithm alone, and consistently reached global fitness peaks. Thus, hybrid walks provide a model for microbial pathogens escaping host immunity without compromising variant fitness. Biological processes facilitating novelty-seeking evolution in natural pathogen populations include hypermutability, recombination, wide dispersal, and immune-compromised hosts. The high efficiency of the hybrid algorithm improves the evolutionary predictability of novel antigen variants. We propose the design of escape-proof vaccines based on high-fitness variants covering a majority of the basins of attraction on the fitness landscape representing all potential variants of a microbial antigen.

Indexed as

antigenic variationevolutionfitness landscapegenetic algorithmlocal optima networksNK modelnovelty searchsurface antigen

Identifiers

PMID36986310
PMCPMC10053453
OpenAlexW4322742387

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.