Biology subjects

Sanchez, M. B.

Publications and source records attributed to Sanchez, M. B..

3 recordsLinked to original sources

bioRxiv2024

Regulated mRNA recruitment in dinoflagellates is reflected in hyper-variable mRNA spliced leaders and novel eIF4Es

Dinoflagellates are eukaryotic algae with large genomes that rely heavily on post-transcriptional control for the regulation of gene expression. Dinoflagellate mRNAs are trans-spliced with a conserved 22 base spliced leader sequence (SL) that includes the 5-cap to which the translation initiation factor 4E (eIF4E) binds to facilitate ribosomal recruitment. The binding of an eIF4E to a specific mRNA SL is a potential regulatory point in controlling dinoflagellate gene expression. Here we show that m7G is the 5-cap base of the 65 bp SL RNA with additional methylations throughout the SL to give a mixture of novel multi-methylated sequences in Amphidinium carterae (CCMP1314). There is also sequence variability in all four bases seen at the first position followed by a variety of polymorphisms. Three novel clades of eIF4E have been shown in dinoflagellates that are distinct from the three metazoan classes of eIF4E. Members of each clade differ significantly from each other, but all bear the distinctive features of a cap-binding protein. Here we show large differences in expression and activity in six of the eight eIF4E family members from A. carterae. Transcripts of each are expressed throughout the diel cycle, but only eIF4E-1 family members and eIF4E-2a show discernable expression at the level of protein. Recombinant eIF4E-1 family members and eIF4E-3a, but not eIF4E-2a, are able to bind to m7GTP substrates in vitro. Overall, eIF4E-1a emerges with characteristics consistent with the role of a prototypical initiation factor; eIF4E-1a is the most conserved and highly expressed eIF4E family member, has the highest affinity for m7GpppG and m7GpppC by surface plasmon resonance, and is able to complement a yeast strain conditionally deficient in eIF4E. The large number of eIF4E family members along with the sequence and methylation state variability in the mRNA SLs underscore the unique nature of the translational machinery in the dinoflagellate lineage and suggest a wide range of possibilities for differential recruitment of mRNAs to the translation machinery. Impact StatementIn the dinoflagellate, A. carterae, hyper-variable mRNA spliced leaders and novel eIF4Es reflect the reliance of dinoflagellates on variable mRNA recruitment for the regulation of gene expression.

molecular biology↗

bioRxiv2020

miRNome profiling of clonal stem cells in Ph+ CML

Chronic myeloid leukemia (CML) is a myeloid stem cell neoplasm characterized by an expansion of myeloid progenitor cells and the presence of BCR-ABL1 oncoprotein. Since the introduction of specific BCR-ABL1 tyrosine kinase inhibitors (TKI), overall survival has improved significantly. However, under long-term therapy patients may have residual disease that originates from TKI-resistant leukemic stem cells (LSC). In this work, we analyzed the miRNome of CML LSC, normal hematopoietic stem cells (HSC) obtained from the same CML patients, and stem and progenitor cells obtained from healthy donors (HD) by next-generation sequencing. We detected a global decrease of microRNA levels in LSC and HSC from CML patients, and decreased levels of microRNAs and snoRNAs from a genomic cluster in chromosome 14, suggesting a mechanism of silencing of multiple non-coding RNAs. Surprisingly, HSC from CML patients, despite the absence of BCR-ABL1 expression, showed an altered miRNome. In silico analysis revealed an association between validated microRNAs and multiple metabolic pathways, suggesting that these molecules may be mediators of the previously reported dysregulation of LSC metabolism. This is the first report of the LSC miRNome that distinguishes between BCR-ABL1+ LSC and their BCR-ABL1- counterparts, providing valuable data for future studies.

cancer biology↗

bioRxiv2018

Can machine learning assess trunk alignment directly from raw video?

BackgroundThe Segmental Assessment of Trunk Control (SATCo) evaluates sitting control at seven separate trunk segments, making a judgement based on their position in space relative to a defined, aligned posture. SATCo is in regular clinical and research use and is a Recommended Instrument for Cerebral Palsy and Spinal Cord Injury-Paediatric by The National Institute of Neurological Disorders and Stroke (US). However, SATCo remains a subjective assessment.\n\nResearch questionThis study tests the feasibility of providing an objective, automated identification of frames containing the aligned, reference trunk posture using deep convolutional neural network (DCNN) analysis of raw high definition and depth (HD+D) images.\n\nMethodsA SATCo was conducted on sixteen healthy male adults and recorded using a Kinect V2. For each of seven segments tested, two different trials were collected (control and no-control) to simulate a range of alignment configurations. For all images, classification of alignment obtained from a trained and validated DCNN was compared to expert clinicians labelling.\n\nResultsUsing leave-one-out testing, at the optimal operating threshold, the DCNN correctly classified individual images (alignment v misaligned) with average precision 92.7{+/-}16% (mean{+/-}SD).\n\nSignificanceThese results show for the first time, automation of a key component of the SATCo test, namely identification of aligned trunk posture directly from raw images (HD+D). This demonstrates the potential of machine learning to provide a fully automated, objective SATCo test to enhance assessment of trunk control in children and adults for research and treatment of various conditions including neurodisability and stroke.

bioengineering↗