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Biology subjects

Batu, T.

Publications and source records attributed to Batu, T..

2 recordsLinked to original sources

microRNAs bidirectionally regulate FUT1 to modulate α-1,2-fucosylation and cancer-associated biology

The -1,2-fucosyltransferase, FUT1, plays a central role in blood type determination, the establishment of the gut microbiota, and cancer progression. Using high-throughput analysis, we mapped the miRNA regulatory landscape of FUT1 and found that miRNAs bidirectionally regulate this enzyme. Validation of miRFluR assay results across multiple cell lines confirmed that both upregulatory and downregulatory miRNA interactions affect endogenous FUT1 and its enzymatic product, -1,2-fucosylation. Inhibitors of endogenous miRNA impacted both enzyme and glycan levels, underscoring the biological impact of bidirectional miRNA regulation. Upregulatory binding sites (miR-200c-5p and miR-361-3p) and the downregulatory binding site (miR-29c-5p) identified in this work both displayed non-canonical binding. Notably, miRNAs upregulating FUT1 are depleted in various cancers, aligning with observations that loss of -1,2-fucosylation is a hallmark of esophageal cancer, melanoma biogenesis, and metastasis. Furthermore, integration of our previous work with the current results indicates that the loss of miR-200c family has a strong correlation with the loss of -1,2-fucosylation during epithelial-to-mesenchymal transition. Together, these results identify miRNAs as key regulators of FUT1 and demonstrate that bidirectional miRNA control of glycosyltransferases can reshape cell-surface glycosylation with important implications for cancer biology.

molecular biology↗

GenCore: Genomic distance estimation using Locally Consistent Parsing

In the era of exponential data generation, a fast, consistent, and efficient string processing technique is necessary to represent extensive genomic data. One of the earliest string processing techniques, predating MinHash and minimizer-based sketching, is Locally Consistent Parsing (LCP). This technique partitions an input string and identifies short, exactly occurring substrings called cores, which collectively cover the input string while maintaining Partition and Labeling Consistency. The iterative application of LCP yields progressively longer cores in a compressed format, thereby substantially enhancing the efficiency of genomic sequence representation and subsequent downstream analysis. We have previously developed Lcptools as the first iterative implementation of LCP for the DNA alphabet and demonstrated its effectiveness in identifying cores with minimal collisions. Here, we introduce GO_SCPLOWENC_SCPLOWCO_SCPLOWOREC_SCPLOW, a computational method that leverages LCP cores for the first time to sketch and estimate genomic distances for closely related large genomes, and successfully reconstruct simulated progression trees. GO_SCPLOWENC_SCPLOWCO_SCPLOWOREC_SCPLOW also successfully recapitulates primate phylogeny using both telomere-totelomere (T2T) assemblies and the PacBio HiFi reads for assembly-free comparisons. AvailabilityGO_SCPLOWENC_SCPLOWCO_SCPLOWOREC_SCPLOW is available at https://github.com/BilkentCompGen/gencore

bioinformatics↗