Biology subjects

Montezano, D.

Publications and source records attributed to Montezano, D..

4 recordsLinked to original sources

bioRxiv2026

COB: a comprehensive database of chloroplast outer envelope beta-barrel proteins

Despite their central role in metabolite exchange, lipid trafficking, and protein import, chloroplast outer envelope beta-barrel proteins lack a dedicated comprehensive sequence database spanning many plant proteomes. Here we present the database COB (chloroplast outer-envelope beta-barrel), consisting of 16,586 beta-barrel sequences organized across ten protein categories and an uncharacterized group. COB was constructed using a machine learning classifier that identifies chloroplast beta-barrels based on features derived from evolutionary protein contact maps. Analysis of COB reveals that Streptophyta have more barrels overall and use a greater variety of solute transporters than Chlorophyta. Furthermore, we find considerable structural diversity across OEP categories, including variation in beta-strand count and a high prevalence of open barrel conformations not observed in bacterial outer membrane proteins. Structure predictions for Arabidopsis thaliana outer envelope proteins identified candidate hybrid barrel assemblies, with TOC159 family members emerging as universal interaction partners. We also report single-chain multi-barrel domain architectures in the chloroplast outer envelope, a topology previously described only in Gram-negative bacteria. Finally, we find chloroplast membrane barrels have more open topologies and shorter strands than bacterial membrane barrels. COB provides a comprehensive sequence resource for chloroplast outer envelope beta-barrels and establishes a foundation for investigating the evolution, structure, and function of this essential protein in chloroplast.

plant biology↗

bioRxiv2026

Counting strands in outer membrane beta-barrels

Beta-barrel structures are critical components of bacterial outer membranes, where they facilitate transport, cell signaling, antibiotic resistance, and structural integrity. A key feature of beta-barrels is their strand count, which influences pore diameter, binding site locations, and functional properties. However, because of breaks in strands and the presence of strands in periplasmic domains and plug domains, manual counting is inefficient and current algorithms do not accurately determine barrel strand count. To address this, we refined our previous beta-barrel structural assessment tool, PolarBearal, to improve strand number identification in large-scale datasets. To enhance the accuracy of barrel strand number labeling, our updated algorithm integrates three structural criteria, namely inter-residue vector angles, hydrogen-bonding distances, and strand connectivity. Using this algorithm, we labeled strand numbers for 571,760 predicted outer membrane beta-barrel structures obtained from the AlphaFold2 database. Our algorithm has 97% accuracy in strand number assignments, and the resulting dataset facilitates assessment of the homogeneity of strand counts for different types of outer membrane proteins. The strand labeling also provides insights on beta-barrel strand distribution and evolutionary patterns, supporting further research in protein structure prediction and design. SignificanceThis work contributes an accurate, automated method for counting beta-barrel strands in bacterial outer membrane proteins. Methodological ImpactThe algorithm achieves 97% accuracy in strand counting, solving a technical problem that has hindered large-scale structural analysis. Previous manual methods were inefficient, and existing algorithms failed to handle the structural complexities of real beta-barrel proteins, including strand breaks and additional domains. Scale of ContributionBy annotating over 571,000 predicted structures from the AlphaFold2 database, this work represents the largest systematic characterization of beta-barrel strand distributions to date. This labeled dataset provides a resource for the structural biology community. Broader ApplicationsThis tool enables researchers understand structure-function relationships in outer membrane proteins, supporting advances in protein design, drug development targeting bacterial membranes.

bioinformatics↗

bioRxiv2022

Is It A Barrel? General Features of Transmembrane Beta Barrels from a Large Database

Large datasets contribute new insights to subjects formerly investigated by exemplars. We used co-evolution data to create a large, high-quality database of transmembrane {beta}-barrels (TMBB). By applying simple feature detection on generated evolutionary contact maps, our method (IsItABarrel) achieves 95.88% balanced accuracy when discriminating among protein classes. Moreover, comparison with IsItABarrel revealed a high rate of false positives in previous TMBB algorithms. In addition to being more accurate than previous datasets, our database (available online) contains 1,894,206 bacterial TMBB proteins from 20 evolutionary classes, respectively 17 and 2.2 times larger than the previous sets TMBB-DB and OMPdb. We anticipate that due to its quality and size the database will serve as a useful resource where high quality TMBB sequence data is required. We found that TMBBs can be divided into 10 types, three of which have not been previously reported. We find tremendous variance in proteome percentage among TMBB-containing organisms with some using 6.79% of their proteome for TMBBs and others using as little as 0.27% of their proteome. The distribution of the lengths of the TMBBs is suggestive of previously hypothesized duplication events. In addition, we find that the C-terminal {beta}-signal varies among different classes of bacteria though it is most commonly HyGHyGY+F. However, this {beta}-signal is only characteristic of prototypical TMBBs. The nine non-prototypical barrel types have other C-terminal motifs and it remains to be determined if these alternative motifs facilitate TMBB insertion or perform any other signaling function. Significance StatementOuter membrane proteins (OMPs) control all interactions between Gram negative bacteria and their environments including uptake and efflux of antibiotics. We created an algorithm that identifies bacterial OMPs from sequence. The quality of our algorithm allows us to identify most OMPs ([~]1.8 million) from prokaryotic genomes including >240,000 unrelated to previously structurally-resolved OMPs. We identify ten types of OMPs in our database. The largest types signal sequence--used for targeting the membrane-insertion machinery--varies by phylogenetic class. All other types of OMPs do not have a related signal sequence, raising new questions of how these proteins fold. Our web-accessible database will allow for further exploration of the varieties of outer membrane proteins to uncover new targets for controlling antibiotic resistance.

bioinformatics↗

bioRxiv2019

Colicin E1 Fragments Potentiate Antibiotics by Plugging TolC

The double membrane architecture of Gram-negative bacteria forms a barrier that is effectively impermeable to extracellular threats. Bacteriocin proteins evolved to exploit the accessible, surface-exposed proteins embedded in the outer membrane to deliver cytotoxic cargo. Colicin E1 is a bacteriocin produced by, and lethal to, Escherichia coli that hijacks the outer membrane proteins TolC and BtuB to enter the cell. Here we capture the colicin E1 translocation domain inside its membrane receptor, TolC, by high-resolution cryoEM, the first reported structure of a bacteriocin bound to TolC. Colicin E1 binds stably to TolC as an open hinge through the TolC pore--an architectural rearrangement from colicin E1s unbound conformation. This binding is stable in live E. coli cells as indicated by single-molecule fluorescence microscopy. Finally, colicin E1 fragments binding to TolC plugs the channel, inhibiting its native efflux function as an antibiotic efflux pump and heightening susceptibility to three antibiotic classes. In addition to demonstrating that these protein fragments are useful starting points for developing novel antibiotic potentiators, this method could be expanded to other colicins to inhibit other outer membrane protein functions.

biophysics↗