Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.10.11.758377

Predicting cyanobacterial oxic diazotrophy and prioritizing candidate protein families beyond known Nif proteins

Abstract

Diazotrophic cyanobacteria must reconcile oxygenic photosynthesis with the oxygen sensitivity of nitrogenase. Engineering studies have demonstrated nitrogenase activity in a non-diazotrophic cyanobacterium while highlighting the importance of accessory functions and oxygen management. Robust aerobic nitrogen fixation remains challenging, motivating systematic identification of candidate support functions beyond the canonical Nif machinery. We modeled nifHDK-defined diazotrophic potential from protein-family presence or absence in 426 cyanobacterial assemblies. Four classifiers evaluated with genus-blocked cross-validation achieved mean ROC AUCs of 0.853 to 0.893, with purity and genus-breadth filters fitted within training folds. Restricting the panel to 401 assemblies with current NCBI status gave AUCs of 0.806 to 0.881. Family-content logistic regression outperformed a genome-size-only baseline across ten genus partitions. Two inventories describe candidates across the full panel: 981 high-purity families and 473 families with positive residual associations (accompanied by three ubiquitous controls). Model importance orders the residual-association inventory. A separate heuristic score combines inventory membership with proteomics, condensate-driver ranks and genus-based morphotype proxies to prioritize 167 families for experiments. Proteomics annotations tracked detection opportunity; the condensate contrast between inventories attenuated after prevalence adjustment. These annotations help choose experiments but do not independently validate accessory functions. Protein-family content predicts nifHDK-defined diazotrophic potential, with performance sensitive to assembly inclusion, taxonomy, genome size and taxonomic weighting. The two candidate inventories distinguish high carrier purity from residual association, providing complementary resources for prioritizing previously uncharacterized functions associated with cyanobacterial oxic diazotrophy.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Young, J., Aryal, S., Nelson, D., Raya, D., Gnimpieba Z., E. A., Zhou, R.. 2026-10-12. Predicting cyanobacterial oxic diazotrophy and prioritizing candidate protein families beyond known Nif proteins. https://doi.org/10.64898/2026.10.11.758377

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Carrier-Limited Release Risk in Electrospun Nanofibers for Regenerative Endodontics: Constraint Discovery from 25 Formulations

Regenerative endodontics needs an intracanal carrier that keeps disinfecting across a dressing interval that clinicians schedule at one to four weeks, without harming the stem cells that rebuild the pulp. We ask what one completed 25-formulation electrospinning campaign of poly(vinylpyrrolidone) (PVP) fibers carrying metronidazole, ciprofloxacin, minocycline and Ca(OH)2 can decide, and use machine learning for constraint discovery and decision support rather than as a new predictor. After an audit against the source thesis, logistic regression predicts fine-fiber formation at 96% leave-one-out accuracy, but a one-threshold rule does as well, the gain over the 80% majority baseline is not significant (exact McNemar p = 0.125), and accuracy falls to 84% when mixture loading is encoded per component. Diameter models interpolate within formulation families (ridge MAE 193 nm, 95% CI 96 to 317 nm) and fail across them (R^2 < 0). Because the campaign never measured release, we assemble a same-drug, cross-carrier evidence table: 17 bounded metronidazole and ciprofloxacin observations from seven studies, with two-sided censoring. Water-soluble carriers (PVP, PVA) completed release within 80 h (PVP within 8 h); no water-insoluble monolithic carrier reached 90% within its observation window, releasing 1.5 to 50%; both within-study comparisons separate at matched loading; and blend, core-shell and thick-mat architectures released over 3 to 28 days. The PVP mats therefore carry a carrier-limited release risk, not a proven ceiling, and one dissolution experiment can confirm or overturn it. A censoring-aware screen keeps three necessarily and one possibly nondominated formulation, and fixed-budget replays show that uncertainty sampling finds failed formulations sooner, except the one it is confidently wrong about.

bioinformatics↗

CellMethMarker provides an integrated database of human cell- and tissue-type-specific DNA methylation markers

Cell- and tissue-type-specific DNA methylation markers provide epigenetic signatures of cellular identity and are widely used to infer cellular origin from bulk and single-cell methylomes. Existing resources mainly emphasize disease-associated biomarkers, methylome atlases, genomic annotations or RNA-based cell markers, leaving an unmet need for an integrated region-level resource dedicated to such markers. Here we present CellMethMarker (http://gu-zhanglab.hfcas.ac.cn/CellMethMarker), a curated database integrating 347,514 de novo markers derived from uniformly processed whole-genome and reduced-representation bisulfite sequencing datasets, 2,203,507 literature-derived marker records and harmonized metadata for 2,810 samples. CellMethMarker enables cell- and tissue-centered marker retrieval, coordinate-based search, genome-browser visualization, interactive methylation analysis and data download. In an independent single-cell methylome atlas, these markers recover the expected cell-type-associated methylation patterns, and a platform-matched reference built from them lowers the mean deconvolution error from 0.365 to 0.144. CellMethMarker therefore links region-level DNA methylation variation to cellular identity and supports methylome-based cell-type annotation and deconvolution.

bioinformatics↗

IG-28 enables identification and quantification of high-confidence isoforms from large bulk and single-cell full-length cDNA datasets

The technology to sequence full-length transcriptomes from bulk and single-cell samples has rapidly advanced. As a result, full-length cDNA datasets now reach billions of reads in size which is beyond the capability of most established isoform identification tools. Here, we introduce IG-28 which addresses this challenge with its capability to process and analyze large fl-cDNA datasets fast and using minimal computational resources. In contrast to its predecessor Mandalorion, IG-28 is not limited to bulk fl-cDNA but is capable of parsing, processing, and analyzing single-cell fl-cDNA datasets. It does so in a lightweight, flexible manner, integrating seamlessly with established scRNA-seq analysis workflows. We benchmarked IG-28 against a variety of established and new isoform identification tools using several bulk and a complex single-cell fl-cDNA dataset and found that IG-28 consistently outperformed the other tools by identifying high-confidence public isoforms.

bioinformatics↗