Biology subjects

Askary, A.

Publications and source records attributed to Askary, A..

6 recordsLinked to original sources

bioRxiv2026

Regenerative base editing enables deep lineage recording

Reconstructing the lineage histories of individual cells can reveal the dynamics of developmental and disease processes. In engineered recording systems, cells stochastically edit synthetic barcode sequences as they proliferate, creating distinct, heritable edit patterns that can be used to reconstruct the lineage trees relating individual cells in a manner analogous to phylogenetic reconstruction. However, recording depth is often limited by the kinetics of the editing process: the rate of editing declines exponentially over time for an array of independently editable targets, leading to most edits occurring in early generations. Here, we introduce the hypercascade, a regenerative molecular recording system that takes advantage of the predictability of A-to-G base editing to progressively create new target sites over time. The hypercascade packs 4 editable target sites in every 20 bp of sequence, enabling high density information storage. More importantly, the hypercascades regenerative logic leads to an approximately constant rate of mutation accumulation over time. This in turn facilitates reconstruction of deep lineage relationships. We demonstrate this by reconstructing trees spanning 23 days of editing and approximately 17 generations after a single polyclonal engineering step. Finally, simulations show that the hypercascade has the potential to record chromatin state transition dynamics across multiple genomic loci in parallel. The hypercascade thus provides a flexible and broadly useful tool for molecular recording.

bioengineering↗

bioRxiv2024

Reconstructing signaling history of single cells with imaging-based molecular recording

The intensity and duration of biological signals encode information that allows a few pathways to regulate a wide array of cellular behaviors. Despite the central importance of signaling in biomedical research, our ability to quantify it in individual cells over time remains limited. Here, we introduce INSCRIBE, an approach for reconstructing signaling history in single cells using endpoint fluorescence images. By regulating a CRISPR base editor, INSCRIBE generates mutations in genomic target sequences, at a rate proportional to signaling activity. The number of edits is then recovered through a novel ratiometric readout strategy, from images of two fluorescence channels. We engineered human cell lines for recording WNT and BMP pathway activity, and demonstrated that INSCRIBE faithfully recovers both the intensity and duration of signaling. Further, we used INSCRIBE to study the variability of cellular response to WNT and BMP stimulation, and test whether the magnitude of response is a stable, heritable trait. We found a persistent memory in the BMP pathway. Progeny of cells with higher BMP response levels are likely to respond more strongly to a second BMP stimulation, up to 3 weeks later. Together, our results establish a scalable platform for genetic recording and in situ readout of signaling history in single cells, advancing quantitative analysis of cell-cell communication during development and disease.

synthetic biology↗

bioRxiv2024

Spatial motifs reveal patterns in cellular architecture of complex tissues

Spatial organization of cells is crucial to both proper physiological function of tissues and pathological conditions like cancer. Recent advances in spatial transcriptomics have enabled joint profiling of gene expression and spatial context of the cells. The outcome is an information rich map of the tissue where individual cells, or small regions, can be labeled based on their gene expression state. While spatial transcriptomics excels in its capacity to profile numerous genes within the same sample, most existing methods for analysis of spatial data only examine distribution of one or two labels at a time. These approaches overlook the potential for identifying higher-order associations between cell types - associations that can play a pivotal role in understanding development and function of complex tissues. In this context, we introduce a novel method for detecting motifs in spatial neighborhood graphs. Each motif represents a spatial arrangement of cell types that occurs in the tissue more frequently than expected by chance. To identify spatial motifs, we developed an algorithm for uniform sampling of paths from neighborhood graphs and combined it with a motif finding algorithm on graphs inspired by previous methods for finding motifs in DNA sequences. Using synthetic data with known ground truth, we show that our method can identify spatial motifs with high accuracy and sensitivity. Applied to spatial maps of mouse retinal bipolar cells and hypothalamic preoptic region, our method reveals previously unrecognized patterns in cell type arrangements. In some cases, cells within these spatial patterns differ in their gene expression from other cells of the same type, providing insights into the functional significance of the spatial motifs. These results suggest that our method can illuminate the substantial complexity of neural tissues, provide novel insight even in well studied models, and generate experimentally testable hypotheses.

bioinformatics↗

bioRxiv2023

Lineage motifs: developmental modules for control of cell type proportions

In multicellular organisms, cell types must be produced and maintained in appropriate proportions. One way this is achieved is through committed progenitor cells that produce specific sets of descendant cell types. However, cell fate commitment is probabilistic in most contexts, making it difficult to infer progenitor states and understand how they establish overall cell type proportions. Here, we introduce Lineage Motif Analysis (LMA), a method that recursively identifies statistically overrepresented patterns of cell fates on lineage trees as potential signatures of committed progenitor states. Applying LMA to published datasets reveals spatial and temporal organization of cell fate commitment in zebrafish and rat retina and early mouse embryo development. Comparative analysis of vertebrate species suggests that lineage motifs facilitate adaptive evolutionary variation of retinal cell type proportions. LMA thus provides insight into complex developmental processes by decomposing them into simpler underlying modules.

developmental biology↗

bioRxiv2020

osr1 couples intermediate mesoderm cell fate with temporal dynamics of vessel progenitor cell differentiation

Transcriptional regulatory networks refine gene expression boundaries throughout embryonic development to define the precise dimensions of organ progenitor territories. Kidney progenitors originate within the intermediate mesoderm (IM), but the pathways that establish the boundary between the IM and its neighboring vessel progenitors are poorly understood. Here, we delineate new roles for the zinc finger transcription factor Osr1 in kidney and vessel progenitor development. Zebrafish osr1 mutants display decreased IM formation and premature emergence of neighboring lateral vessel progenitors (LVPs). These phenotypes contrast with the increased IM and absent LVPs observed with loss of the bHLH transcription factor Hand2, and loss of hand2 partially suppresses the osr1 mutant phenotypes. hand2 and osr1 are both expressed in the posterior lateral mesoderm, but osr1 expression decreases dramatically prior to LVP emergence. Overexpressing osr1 inhibits LVP development while enhancing IM formation. Together, our data demonstrate that osr1 modulates both the extent of IM formation and the temporal dynamics of LVP development, suggesting that a balance between levels of osr1 and hand2 expression is essential to demarcate the dimensions of kidney and vessel progenitor territories. SUMMARY STATEMENTAnalysis of the osr1 mutant phenotype reveals roles in determining the extent of intermediate mesoderm formation while inhibiting premature differentiation of neighboring vessel progenitors.

developmental biology↗

bioRxiv2017

Genome-Wide Analysis of Facial Regionalization in Zebrafish

Patterning of the facial skeleton involves the precise deployment of thousands of genes in distinct regions of the pharyngeal arches. Despite the significance for craniofacial development, how genetic programs drive this regionalization remains incompletely understood. Here we use combinatorial labeling of zebrafish cranial neural crest-derived cells (CNCCs) to define global gene expression along the dorsoventral axis of the developing arches. Intersection of region-specific transcriptomes with expression changes in response to signaling perturbations demonstrates complex roles for Endothelin1 (Edn1) signaling in the intermediate joint-forming region yet a surprisingly minor role in ventral-most regions. Analysis of co-variance across multiple sequencing experiments further reveals clusters of coregulated genes, with in situ hybridization confirming the domain-specific expression of novel genes. We then performed mutational analysis of a number of these genes, which uncovered antagonistic functions of two new Edn1 targets, follistatin a (fsta) and emx2, in regulating cartilaginous joints in the hyoid arch. Our unbiased discovery and functional analysis of genes with regional expression in zebrafish arch CNCCs reveals complex regulation by Ednl and points to novel candidates for craniofacial disorders.\n\nSummary StatementUsing zebrafish to purify distinct groups of embryonic cells, Askary et al. have created a detailed map of how thousands of genes are deployed to shape the developing face.

developmental biology↗