Meister, K. | bioRxiv Science

bioRxiv2026

Computational Redesign of an Antifreeze Protein Using Deep Learning

Antifreeze proteins (AFPs) found in various cold-adapted organisms inhibit ice growth and are of interest for applications in food products, cryopreservation, agriculture, and materials science. Although high-resolution structures are available for several AFPs, the amino acids required for full antifreeze activity remain incompletely defined, and the development of AFP variants with properties such as enhanced solubility, high expression yield, and improved thermostability may further facilitate applications. Here, we used the deep learning model ProteinMPNN to redesign the globular fish antifreeze protein AFPIII, keeping the previously reported ice-binding residues fixed. We readily obtained sequences confidently predicted to adopt AFPIIIs structure and we selected five designed variants for expression, all of which expressed efficiently in E. coli. Circular dichroism spectroscopy showed that two of these variants retained secondary structure elements consistent with AFPIII, whereas the other three exhibited structural differences. One design was predicted and experimentally confirmed to have increased thermostability. All five variants displayed measurable thermal hysteresis activity. However, none reached the activity of wild-type AFPIII, suggesting that maintaining the currently established set of ice-binding residues is not sufficient to fully preserve this AFPs function; other, unidentified residues can also impact its activity. Our findings highlight the value of deep learning-based protein design methods both for generating AFP variants with desirable properties and for uncovering gaps in existing knowledge of well-characterized AFPs.

biophysics↗

bioRxiv2026

Loss of dispersal via ice nucleation activity constrains microbial evolution

The ability to disperse over long distances through the atmosphere is a common trait across the tree of life, facilitating resource access and increasing long-range gene flow. Loss of dispersal mechanisms, viz. flight, can occur in animals found on islands where documented phenotypic changes like loss of wingspan impedes longer distance travel to mate with the metapopulation. Bacteria also experience atmospheric flight and descend via bioprecipitation by catalyzing the freezing of cloud droplets with protein InaZ. InaZ triggers ice nucleation at temperatures near 0{circ}C(1). This ice nucleation activity (INA), a biophysical trait, enhances bacterial deposition through precipitation. The role of InaZ-mediated ice nucleation on bacterial dispersal is well documented, but the impact of loss of INA and thus reduction or loss of atmospheric dispersal on bacterial ecology and evolution has not been described. Here we show that the loss of the ancestral inaZ gene restricts bacterial dispersal and leads to significant genetic and ecological isolation across multiple genera. Through the analysis of available complete genomes, we demonstrate that lineages lacking functional inaZ experience major gene loss events, reduced recombination rates and a marked dependence on human-mediated or insect transmission. These INA-lacking bacteria exhibit an increased ecological signature of isolation that parallels the distribution of geographically isolated animals. Our results establish InaZ as a keystone biophysical trait that defines microbial dispersal strategies. We anticipate these findings will provide a framework for understanding how shifts in biophysical traits drive niche differentiation and changes in dispersal with downstream consequences for Earth system processes. Significance StatementSome microorganisms catalyze freezing of cloud droplets near 0{degrees}C via ice nucleation activity (INA) enhancing their deposition. We determined that loss of the gene encoding the INA protein in Gammaproteobacteria restricts bacterial dispersal. Bacteria that lost this ancestral trait compared to relatives with INA experienced distinct, major gene loss events, altered gene flow and marked dependence on transmission by plant tissues or insects and an increased ecological signature of isolation paralleling the geographically isolated plants and animals. We posit that gene loss for biophysical traits such as INA is a keystone example of the consequences of a biological trait defining microbial dispersal.

evolutionary biology↗