Biology subjects

Bashir, U.

Publications and source records attributed to Bashir, U..

4 recordsLinked to original sources

bioRxiv2026

Biosynthetic glycan modeling reveals metabolic shifts in disease

Glycans are biosynthesized by partly overlapping cascades of enzymatic reactions that can be conceptualized as biosynthetic networks. These networks latently contain reaction rates, substrate specificities, and metabolic states of the underlying cells. Yet extracting this information, across tissues, species, and hundreds of datasets, is challenging with existing methods. Here, we present a new structure-aware algorithm for glycan biosynthetic network construction that is easily scalable to any number of glycomics datasets and results in more interpretable networks. We further show how these networks then can be used to elucidate substrate preferences of enzymes, quantify metabolic shifts in conditions, such as cancer, and provide hypotheses for not yet elucidated structures via physiological network extension. We also show that tumorigenesis shifts glycome regulation from a carrier-expression-dominated regime toward being governed by biosynthetic network structure, which generalizes across six independent cancer cohorts. We envision that these improvements to glycan biosynthetic modeling will aid in understanding glycan regulation and observed glycomic shifts in health and disease.

bioinformatics↗

bioRxiv2025

Extended nuclear glycosylation is a common post-translational modification

In eukaryotes, glycans modify proteins in the secretory pathway and the extracellular space. Aside from nucleocytoplasmic O-GlcNAc, glycosylation is not considered a relevant post-translational modification in other cellular compartments. Here, we challenge this long-standing paradigm by showing that extended O-glycans are commonly found on intranuclear proteins. Through comprehensive genetic and biochemical analyses, we conclusively demonstrate that these O-glycans stem from the secretory pathway, yet are found on nuclear proteins across mammalian cell lines and primary cells. Using knock-out cell lines, we show mechanistically that nuclear glycans are shuttled to the nucleus via active vesicular transport. We identify several of these intranuclear glycoproteins as RNA-binding proteins, including KHSRP/FUBP2, RBM12, and RPP30. Lastly, we show that site-specific glycosylation of RPP30 is crucial for effective tRNA processing. Overall, our findings suggest a much broader role for glycosylation in regulating cellular functions and open up investigation into the role of glycans in more biological processes.

molecular biology↗

bioRxiv2020

Novel Chlamydiae and Amoebophilus endosymbionts are prevalent in wild isolates of the model social amoebae Dictyostelium discoideum

Amoebae interact with bacteria in diverse and multifaceted ways. Amoeba predation can serve as a selective pressure for the development of bacterial virulence traits. Bacteria may also adapt to life inside amoebae, resulting in symbiotic relationships (pathogenic or mutualistic). Indeed, particular lineages of obligate bacterial endosymbionts have been found in different amoebae. Here, we screened an extensive collection of Dictyostelium discoideum wild isolates for the presence of such bacterial symbionts using PCR primers that identify these endosymbionts. This is the first report of obligate symbionts in this highly-studied amoeba species. They are surprisingly common, identified in 42% of screened isolates (N=730). Members of the Chlamydiae phylum are particularly prevalent, occurring in 27% of the host strains. They are novel and phylogenetically distinct. We also found Amoebophilus symbionts in 8% of screened isolates (N=730). Antibiotic-cured amoebae behave similarly to their endosymbiont-infected counterparts, suggesting that endosymbionts do not significantly impact host fitness, at least in the laboratory. We found several natural isolates were co-infected with multiple endosymbionts, with no obvious fitness effects of co-infection under laboratory conditions. The high prevalence and novelty of amoeba endosymbiont clades in the model organism D. discoideum opens the door to future research on the significance and mechanisms of amoeba-symbiont interactions.

microbiology↗

bioRxiv2020

A Novel Machine Learning Approach Uncovers New and Distinctive Inhibitors for Cyclin-Dependent Kinase 9

We present a novel combination of generative and predictive machine learning models for discovering unique protein inhibitors. The new method is assessed on its ability to generate unique inhibitors for the cancer associated protein kinase, CDK9. We validate our method by performing biochemical assays, attaining a hit rate of more than 10%, demonstrating the method to be a notable improvement upon a more standard, and somewhat naive approach. Moreover, we imposed the additional challenge of finding inhibitors that are readily synthesized. Importantly, two new inhibitors are found, with one being distinct from reported CDK9 inhibitors. We discuss the results in the context of modern machine learning principles and the desire expressed by the rational drug design community to secure molecules that are structurally different, yet with high binding affinities, to structurally determined protein targets.

bioinformatics↗