Biology subjects

Collado, L.

Publications and source records attributed to Collado, L..

2 recordsLinked to original sources

bioRxiv2025

The tubulin poly-glutamylase complex, TPGC, is required for phosphatidyl inositol homeostasis and cilium assembly and maintenance

The tubulin poly-glutamylase complex (TPGC) is comprised of TTLL1 and at least five associated proteins that promote the addition of glutamate residues to tubulin tails of microtubules. Despite its discovery two decades ago, the enzyme has been refractory to characterization owing to its complex multimeric nature and the inability to detect poly-glutamylase activity after assembling the six-subunit complex. We now show that TPGC is the key enzyme driving centriolar and ciliary poly-glutamylation. We identified two novel TPGC subunits, TBC1D19 and KIAA1841, and showed that both components play an essential role in the assembly of the eight-subunit holo-enzyme. Remarkably, we were able to reconstitute the activity of TPGC with all eight subunits. TBC1D19 and KIAA1841 were essential for assembly and activity, and loss of TBC1D19 strongly compromised multiple tubulin modifications, including axonemal poly-glutamylation. TBC1D19 loss abolished transport of Arl13b and other ciliary membrane proteins, abrogating primary cilium assembly. Structural modeling revealed an essential role for TBC1D19 and KIAA1841 in complex assembly, microtubule binding, and preferential poly-glutamylation of -tubulin. We found that TBC1D19 loss abrogated the ciliary localization of phosphatidyl inositol phosphatase, INPP5E, triggering cilium instability. Ciliogenesis in TBC1D19 null cells could be restored through inhibition of a specific phosphatidyl inositol phosphate (PIP) kinase, PIP5K1c, suggesting that TBC1D19 is required to instigate and maintain PIP homeostasis during ciliogenesis. Collectively, our data show that TPGC is a multi-functional enzyme essential for cilium assembly and maintenance.

cell biology↗

bioRxiv2024

Estimating and correcting index hopping misassignments in single-cell RNA-seq data

BackgroundIndex hopping causes read assignment errors in data from multiplexed sequencing libraries. This issue has become more prevalent with the widespread use of high-capacity sequencers and highly multiplexed single-cell RNA sequencing (scRNA- seq). ResultsWe conducted deep, plate-based scRNA-seq on a mixed population of mouse skin cells. Analysis of transcriptomes from 1152 cells identified four distinct cell types. To estimate the error rate in sample assignment due to index hopping, we employed differential expression analysis to identify signature genes that were highly and specifically expressed in each cell type. We quantified the proportion of misassigned reads by examining the detection rates of signature genes in other cell types. Remarkably, regardless of gene expression levels, we estimated that 0.65% of reads per gene were assigned to incorrect cell across our data. To computationally compensate for index hopping, we developed a simple correction method wherein, for each gene, 0.65% of the librarys average expression level was subtracted from the expression in each cell. This correction had notable effects on transcriptome analyses, including increased cell-cell clustering distance and alterations in intermediate state assignments of cell differentiation. ConclusionsIndex hopping misassignments are measurable and can impact the experimental interpretation of sequencing results. We devised a straightforward method to estimate and correct for the index hopping rate by quantifying misassigned genes in distinct cell types within an scRNA-seq library. This approach can be applied to any barcoded, multiplexed scRNA-seq library containing cells with distinct expression profiles, allowing for correction of the expression matrix before conducting biological analysis.

genomics↗