Biology subjects

Lu, V.

Publications and source records attributed to Lu, V..

5 recordsLinked to original sources

bioRxiv2026

ABC transporters support Drosophila intestinal stem and progenitor cells during cytotoxic challenge

Adult stem cells can survive diverse insults, from ionizing radiation to toxic chemicals. In vertebrates, ABC transporter expression and dye-efflux capacity have been associated with stem-cell protection and multidrug resistance. How compound accumulation differs between adult stem cells and their differentiated daughters within an intact tissue remains poorly understood. Here, we show that adult Drosophila intestinal stem/progenitor cells maintain a distinct low-accumulation state for membrane-permeable compounds and that ABC transporters contribute to this phenotype and to the response to cytotoxic stress. Across nine membrane-permeable probes, stem/progenitor cells accumulated eight at lower levels than differentiated enterocytes. We selected tetramethylrhodamine methyl ester (TMRM), a membrane-permeable fluorescent probe that showed a strong difference in accumulation between stem/progenitor cells and enterocytes, as a quantitative readout for an RNAi screen of all 56 Drosophila ABC-family genes. The screen identified seven candidate transporters whose depletion increased the stem/progenitor-to-enterocyte TMRM fluorescence ratio. Further characterization of one of them, ABCB7, showed that ABCB7-depleted guts contained fewer mitotic cells during cytotoxic drug exposure. These results implicate ABC transporters in lower compound accumulation in Drosophila intestinal stem/progenitor cells and support a role for ABC transporters in their response to cytotoxic challenge.

genetics↗

bioRxiv2024

Label-Free Melanoma Phenotype Classification Using Artificial Intelligence-Based Morphological Profiling

Melanomas are the deadliest skin cancers, in part due to cellular plasticity and heterogeneity. Intratumoral heterogeneity drives varied mutable phenotypes, specifically "melanocytic" and "mesenchymal" cell states, which result in differential functional properties and drug responses. Definitive and rigorous classification of these phenotypic states has been challenging with conventional biomarker-based methods, and high-parameter molecular methods are cell-destructive, labor-intensive, and time-consuming. To overcome these technical and practical limitations, we utilized label-free artificial intelligence-based morphological profiling to classify live melanoma cells into melanocytic and mesenchymal phenotypes based on high resolution imaging of single cells. To predict the phenotypes of single melanoma cells based on morphology alone, we developed the AI-based Melanoma Phenotype Classifier trained with 19 patient-derived cell lines with known melanocytic or mesenchymal transcriptional profiles. To link phenotypic state with high-dimensional morphological profiles, cells were subjected to genetic and chemical perturbations known to shift phenotypic states. The AI classifier successfully predicted phenotypic shifts which were confirmed by single-cell RNA-Seq (scRNA-Seq). These results demonstrate that correlations between melanoma cell phenotypes and morphological changes are detectable by AI. Additionally, the Melanoma Phenotype Classifier was applied to dissociated tumor biopsy samples and characterization of phenotypic heterogeneity was supported by scRNA-Seq transcriptional profiles. This work establishes a link between cell morphology and melanoma phenotypes, laying the groundwork for the use of a label-free morphology-based method for phenotyping live melanoma cells combined with additional analyses.

cancer biology↗

bioRxiv2023

Artificial intelligence-driven morphology-based enrichment of malignant cells from body fluid

Cell morphology is a fundamental feature used to evaluate patient specimens in pathological analysis. However, traditional cytopathology analysis of patient effusion samples is limited by low tumor cell abundance coupled with high background of non-malignant cells, restricting the ability for downstream molecular and functional analyses to identify actionable therapeutic targets. We applied the Deepcell platform that combines microfluidic sorting, brightfield imaging, and real-time deep learning interpretations based on multi-dimensional morphology to enrich carcinoma cells from malignant effusions without cell staining or labels. Carcinoma cell enrichment was validated with whole genome sequencing and targeted mutation analysis, which showed higher sensitivity for detection of tumor fractions and critical somatic variant mutations that were initially at low-levels or undetectable in pre-sort patient samples. Combined, our study demonstrates the feasibility and added value of supplementing traditional morphology-based cytology with deep learning, multi-dimensional morphology analysis, and microfluidic sorting.

pathology↗

bioRxiv2021

A microRNA cluster downstream of the selector gene Fezf2 coordinates fate specification with dendritic branching in cortical neurons

In the cerebral cortex, cortical projection neurons comprise classes of neurons project to distant regions of the central nervous system. These neurons develop from the same progenitor pool, but they acquire strikingly different inputs and outputs to underpin strikingly different functions. The question of how corticospinal projection neurons - involved in motor function and implicated in paralysis - and callosal projection neurons - involved in cognitive function and implicated in autism - develop represents a fundamental and clinically important question in neurodevelopment. A network of transcription factors, including the selector gene Fezf2, is central to specifying cortical projection neuron fates. Gene regulation up- and down-stream of these transcription factors, however, is not well understood, particularly as it relates to the development of the major inputs to cortical projection neurons. Here we show that the miR-193b~365 microRNA cluster downstream of Fezf2 cooperatively represses the signaling molecule Mapk8, and impacts dendritic branching of cortical projection neurons.

developmental biology↗

bioRxiv2020

An evolutionarily acquired microRNA shapes development of mammalian cortical projections

The corticospinal tract is unique to mammals and the corpus callosum is unique to placental mammals (eutherians). The emergence of these structures is thought to underpin the evolutionary acquisition of complex motor and cognitive skills. Corticospinal motor neurons (CSMN) and callosal projection neurons (CPN) are the archetypal projection neurons of the corticospinal tract and corpus callosum, respectively. Although a number of conserved transcriptional regulators of CSMN and CPN development have been identified in vertebrates, none are unique to mammals and most are co-expressed across multiple projection neuron subtypes. Here, we discover seventeen CSMN-enriched microRNAs (miRNAs), fifteen of which map to a single genomic cluster that is exclusive to eutherians. One of these, miR-409-3p, promotes CSMN subtype identity in part via repression of LMO4, a key transcriptional regulator of CPN development. In vivo, miR-409-3p is sufficient to convert deep-layer CPN into CSMN. This is the first demonstration of an evolutionarily acquired miRNA in eutherians that refines cortical projection neuron subtype development. Our findings implicate miRNAs in the eutherians increase in neuronal subtype and projection diversity, the anatomic underpinnings of their complex behavior. Significance StatementThe mammalian central nervous system contains unique projections from the cerebral cortex thought to underpin complex motor and cognitive skills, including the corticospinal tract and corpus callosum. The neurons giving rise to these projections - corticospinal and callosal projection neurons - develop from the same progenitors, but acquire strikingly different fates. The broad evolutionary conservation of known genes controlling cortical projection neuron fates raises the question of how the more narrowly conserved corticospinal and callosal projections evolved. We identify a microRNA cluster selectively expressed by corticospinal projection neurons and exclusive to placental mammals. One of these microRNAs promotes corticospinal fate via regulation of the callosal gene LMO4, suggesting a mechanism whereby microRNA regulation during development promotes evolution of neuronal diversity.

neuroscience↗