Biology subjects

McKenna, A.

Publications and source records attributed to McKenna, A..

At least 19 recordsLinked to original sources

bioRxiv2026

PALINCODE: Recording cell lineage with ternary palindromic CRISPR bits

Reconstructing complete and accurate lineage trees remains a long-standing challenge in biology. Here, we introduce PALINCODE (Palindromic Coding and Decoding), a system that utilizes ternary CRISPR bits (cBits) to stochastically write one of three possible states over time, permanently embedding lineage relationships in the genome. We demonstrate PALINCODEs lineage-recording potential through simulations and establish palindromic CRISPR editing in cell culture models. We show that truncated Cas9 guide sequences yield ternary outcomes at high efficiency when compared to conventional guides. Using PALINCODE, we derived lineage-recording cell lines with a theoretical coding capacity of up to 10^25 bits, enabling the generation of lineage trees 32 cell divisions deep in single-cell sequencing of 293T cells. Furthermore, we applied PALINCODE using an in vivo melanoma model to jointly read out lineage history and gene expression, enabling in vivo reconstruction of clonal evolution within tumor cell clonal populations. PALINCODE circumvents several limitations of prior CRISPR-based systems while increasing the information potential at individual CRISPR sites, creating a lineage-recording platform with higher density than many competing approaches.

genomics↗

bioRxiv2026

Mapping breast cancer lineage in radiation and immunotherapy using the REMAP mouse

We present REMAP (Recording Evolution in Mammary tumors via Active PyMT), a lineage-tracing mouse model that integrates inducible CRISPR recording with the MMTV-PyMT model of hormone receptor-positive (HR+) breast cancer. Inducible Cas9 drives editing of MARC1 homing guide RNAs (hgRNAs), generating heritable lineage marks, and enables reconstruction of clonal relationships. Using REMAP, we profiled tumor evolution and response to radiation combined with anti-PD1 immunotherapy. Treatment reduced tumor burden locally and systemically, and single-cell RNA sequencing revealed remodeling of the tumor microenvironment (TME). We identified metastatic clones present across primary tumors and distant sites, which exhibited elevated epithelial-mesenchymal transition (EMT) programs as a heritable clonal state. Treatment reduced EMT-associated transcriptional programs and reshaped immune composition, with radiation driving clonal expansion of T cells and reduced repertoire diversity. In contrast, cancer-associated fibroblast clones spanned multiple transcriptional states, indicating substantial stromal plasticity. Together, REMAP enables high-resolution coupling of clonal history and cellular state in vivo, revealing that tumor progression, metastasis, and therapeutic response are governed by heritable lineage programs.

cancer biology↗

bioRxiv2025

SCOUT: Ornstein-Uhlenbeck modelling of gene expression evolution on single-cell lineage trees

Understanding the evolutionary dynamics of clonal populations is essential for uncovering the principles of development, disease progression, and therapeutic resistance. Recent advances in single-cell lineage tracing and transcriptomics enable such analyses by combining heritable barcodes with cell-state information. Here, we present SCOUT (single-cell Ornstein-Uhlenbeck trees), a framework that models gene expression dynamics along single-cell lineage trees using Ornstein-Uhlenbeck processes to distinguish neutral drift from selective pressure. Using simulations, we demonstrate that SCOUT accurately classifies genes based on their underlying evolutionary models. We further validate SCOUT in Caenorhabditis elegans development, identifying biological processes under selection across distinct developmental contexts. Finally, we apply SCOUT to a lung adenocarcinoma xenograft model, revealing key regulators of metastatic progression and tumor microenvironmental adaptation. By integrating lineage and transcriptomic data, SCOUT provides a powerful evolutionary lens for dissecting the forces that shape cell fate.

bioinformatics↗

bioRxiv2025

Hierarchical Lineage Tracing Reveals Diverse Pathways of AML Treatment Resistance

Cancer cells adapt to treatment, leading to the emergence of clones that are more aggressive and resistant to anti-cancer therapies. We have a limited understanding of the development of treatment resistance as we lack technologies to map the evolution of cancer under the selective pressure of treatment. To address this, we developed a hierarchical, dynamic lineage tracing method called FLARE (Following Lineage Adaptation and Resistance Evolution). We use this technique to track the progression of acute myeloid leukemia (AML) cell lines through exposure to Cytarabine (AraC), a front-line treatment in AML, in vitro and in vivo. We map distinct cellular lineages in murine and human AML cell lines predisposed to AraC persistence and/or resistance via the upregulation of cell adhesion and motility pathways. Additionally, we highlight the heritable expression of immunoproteasome 11S regulatory cap subunits as a potential mechanism aiding AML cell survival, proliferation, and immune escape in vivo. Finally, we validate the clinical relevance of these signatures in the TARGET-AML cohort, with a bisected response in blood and bone marrow. Our findings reveal a broad spectrum of resistance signatures attributed to significant cell transcriptional changes. To our knowledge, this is the first application of dynamic lineage tracing to unravel treatment response and resistance in cancer, and we expect FLARE to be a valuable tool in dissecting the evolution of resistance in a wide range of tumor types.

cancer biology↗

bioRxiv2024

Leukemia-derived apelin selects endothelial niche clones to promote tumorigenesis

Hematopoietic stem cells are regulated by endothelial and mesenchymal stromal cells in the marrow niche1-3. Leukemogenesis was long believed to be solely driven by genetic perturbations in hematopoietic cells but introduction of genetic mutations in the microenvironment demonstrated the ability of niche cells to drive disease progression4-8. The mechanisms by which the stem cell niche induces leukemia remain poorly understood. Here, using cellular barcoding in zebrafish, we found that clones of niche endothelial and stromal cells are significantly expanded in leukemic marrows. The pro-angiogenic peptide apelin secreted by leukemic cells induced sinusoidal endothelial cell clonal selection and transcriptional reprogramming towards an angiogenic state to promote leukemogenesis in vivo. Overexpression of apelin in normal hematopoietic stem cells led to clonal amplification of the niche endothelial cells and promotes clonal dominance of blood cells. Knock-out of apelin in leukemic zebrafish resulted in a significant reduction in disease progression. Our results demonstrate that leukemic cells remodel the clonal and transcriptional landscape of the marrow niche to promote leukemogenesis and provide a potential therapeutic opportunity for anti-apelin treatment.

cancer biology↗

bioRxiv2024

Hierarchal single-cell lineage tracing reveals differential fate commitment of CD8 T-cell clones in response to acute infection.

Generating balanced populations of CD8 effector and memory T cells is necessary for immediate and durable immunity to infections and cancer. Yet, a definitive understanding of CD8 differentiation remains unclear. We used CARLIN, a processive lineage recording mouse model with single-cell RNA-seq and TCR-seq to track endogenous antigen-specific CD8 T cells during acute viral infection. We identified a diverse repertoire of expanded T-cell clones represented by seven transcriptional states. TCR enrichment analysis revealed differential memory- or effector-fate biases within clonal populations. Shared Vb segments and amino acid motifs were found within biased categories despite high TCR diversity. Using single-cell CARLIN barcode-seq we tracked multi-generational clones and found that unlike unbiased or memory-biased clones, which stably retain their fate profiles, effector-biased clones could adopt memory- or effector-bias within subclones. Collectively, our study demonstrates that a heterogenous T-cell repertoire specific for a shared antigen is composed of clones with distinct TCR-intrinsic fate-biases.

immunology↗

bioRxiv2024

Contrast-enhanced photon-counting micro-CT of tumor xenograft models

Photon-counting micro computed tomography (micro-CT) offers new potential in preclinical imaging, particularly in distinguishing materials. It becomes especially helpful when combined with contrast agents, enabling the differentiation of tumors from surrounding tissues. There are mainly two types of contrast agents in the market for micro-CT: small molecule-based and nanoparticle-based. However, despite their widespread use in liver tumor studies, there is a notable gap in research on the application of these commercially available agents for photon-counting micro-CT in breast and ovarian tumors. Herein, we explored the effectiveness of these agents in differentiating tumor xenografts from various origins (AU565, MDA-MB-231, and SKOV-3) in nude mice, using photon-counting micro-CT. Specifically, ISOVUE-370 (a small molecule-based agent) and Exitrone Nano 12000 (a nanoparticle-based agent) were investigated in this context. To improve tumor visualization, we proposed a novel color visualization method for photon-counting micro-CT, which changes color tones to highlight contrast media distribution, offering a robust alternative to traditional material decomposition methods with less computational demand. Our in vivo experiments confirm its effectiveness, showing distinct enhancement characteristics for each contrast agent. Qualitative and quantitative analyses suggested that Exitrone Nano 12000 provides superior vasculature enhancement and better quantitative consistency across scans, while ISOVUE-370 gives more comprehensive tumor enhancement but with a significant variance between scans due to its short blood half-time. This variability leads to high sensitivity to timing and individual differences among mice. Further, a paired t-test on mean and standard deviation values within tumor volumes showed significant differences between the AU565 and SKOV-3 tumor models with the nanoparticle-based (p-values < 0.02), attributable to their distinct vascularity, as confirmed by immunohistochemistry. These findings underscore the utility of photon-counting micro-CT in non-invasively assessing the morphology and anatomy of different tumor xenografts, which is crucial for tumor characterization and longitudinal monitoring of tumor development and response to treatments.

bioengineering↗

bioRxiv2023

Chromosome-scale genome assembly of the African spiny mouse (Acomys cahirinus)

There is increasing interest in the African spiny mouse (Acomys cahirinus) as a model organism because of its ability for regeneration of tissue after injury in skin, muscle, and internal organs such as the kidneys. A high-quality reference genome is needed to better understand these regenerative properties at the molecular level. Here, we present an improved reference genome for A. cahirinus generated from long Nanopore sequencing reads. We confirm the quality of our annotations using RNA sequencing data from four different tissues. Our genome is of higher contiguity and quality than previously reported genomes from this species and will facilitate ongoing efforts to better understand the regenerative properties of this organism.

genomics↗

bioRxiv2022

Circuit-seq: Circular reconstruction of cut in vitro transposed plasmids using Nanopore sequencing

Recombinant DNA is a fundamental tool in biotechnology and medicine. Validation of the resulting plasmid sequence is a critical and time-consuming step, which has been dominated for the last 35 years by Sanger sequencing. As plasmid sequences grow more complex with new DNA synthesis and cloning techniques, we need new approaches that address the corresponding validation challenges at scale. Here we prototype a high-throughput plasmid sequencing approach using DNA transposition and Oxford Nanopore sequencing. Our method, Circuit-seq, creates robust, full-length, and accurate plasmid assemblies without prior knowledge of the underlying sequence for approximately $1.50 per plasmid. We demonstrate the power of Circuit-seq across a wide range of plasmid sizes and complexities, generating accurate and contiguous plasmid maps. We then leverage our long read-data to characterize epigenetic marks and estimate plasmid contamination levels. Circuit-seq scales to large numbers of samples at a lower cost than commercial Sanger sequencing, accelerating a key step in synthetic biology, with low startup costs make it practical for individual laboratories.

molecular biology↗

bioRxiv2021

Simultaneous Identification of Brain Cell Type and Lineage via Single Cell RNA Sequencing

Acquired mutations are sufficiently frequent such that the genome of a single cell offers a record of its history of cell divisions. Among more common somatic genomic alterations are loss of heterozygosity (LOH). Large LOH events are potentially detectable in single cell RNA sequencing (scRNA-seq) datasets as tracts of monoallelic expression for constitutionally heterozygous single nucleotide variants (SNVs) located among contiguous genes. We identified runs of monoallelic expression, consistent with LOH, uniquely distributed throughout the genome in single cell brain cortex transcriptomes of F1 hybrids involving different inbred mouse strains. We then phylogenetically reconstructed single cell lineages and simultaneously identified cell types by corresponding gene expression patterns. Our results are consistent with progenitor cells giving rise to multiple cortical cell types through stereotyped expansion and distinct waves of neurogenesis. Compared to engineered recording systems, LOH events accumulate throughout the genome and across the lifetime of an organism, affording tremendous capacity for encoding lineage information and increasing resolution for later cell divisions. This approach can conceivably be computationally incorporated into scRNA-seq analysis and may be useful for organisms where genetic engineering is prohibitive, such as humans.

genomics↗

bioRxiv2020

Single-cell lineage and transcriptome reconstruction of metastatic cancer reveals selection of aggressive hybrid EMT states

Metastatic cancer remains largely incurable due to an incomplete understanding of how cancer cells disseminate throughout the body. However, tools for probing metastatic dissemination and associated molecular changes at high resolution are lacking. Here we present multiplexed, activatable, clonal, and subclonal GESTALT (macsGESTALT), an inducible lineage recorder with concurrent single cell readout of transcriptional and phylogenetic information. By integrating multiple copies of combined static barcodes and evolving CRISPR/Cas9 barcodes, macsGESTALT enables clonal tracing and subclonal phylogenetic reconstruction, respectively. High barcode editing and recovery rates produce deep lineage reconstructions, densely annotated with transcriptomic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we reconstruct dissemination of tens-of-thousands of single cancer cells representing 95 clones and over 6,000 unique subclones across multiple distant sites, e.g. liver and lung metastases. Transcriptionally, cells exist along a continuum of epithelial-to-mesenchymal transition (EMT) in vivo with graded changes in associated signaling, metabolic, and regulatory processes. Lineage analysis reveals that from a majority of non-metastatic, highly epithelial clones, a single dominant clone that has progressed along EMT drives the majority of metastasis. Within this dominant clone a parallel process occurs, where a small number of aggressive subclones drive clonal outgrowth. By precisely mapping subclones along the EMT continuum, we find that size and dissemination gradually increase, peaking at late-hybrid EMT states but precipitously falling once subclones are highly mesenchymal. Late-hybrid EMT states are selected from a predominately epithelial ancestral pool, enabling rapid metastasis but also forcing extensive and continuous population bottlenecking. Notably, late-hybrid gene signatures are associated with decreased survival in human pancreatic cancer, while epithelial, early-hybrid, and highly mesenchymal states are not. Our findings illuminate features of metastasis and EMT with the potential for therapeutic exploitation. Ultimately, macsGESTALT provides a powerful, accessible tool for probing cancer and stem cell biology in vivo.

cancer biology↗

bioRxiv2020

Impact of industrial production system parameters on chicken microbiomes: mechanisms to improve performance and reduce Campylobacter

BackgroundThe factors affecting host-pathogen ecology in terms of the microbiome remain poorly studied. Chickens are a key source of protein with gut health heavily dependent on the complex microbiome which has key roles in nutrient assimilation and vitamin and amino acid biosynthesis. The chicken gut microbiome may be influenced by extrinsic production system parameters such as Placement Birds/m2 (stocking density), feed type and additives. Such parameters, in addition to on-farm biosecurity may influence performance and also pathogenic bacterial numbers such as Campylobacter. In this study, three different production systems Normal (N), Higher Welfare (HW) and Omega-3 Higher Welfare (O) were investigated "in a natural environment" at day 7 and day 30 with a range of extrinsic parameters assessing performance in correlation with microbial dynamics and Campylobacter presence. ResultsOur data identified production system N as significantly dissimilar from production systems HW and O when comparing the prevalence of genera. An increase in Placement Birds/m2 density led to a decrease in environmental pressure influencing the microbial community structure. Prevalence of genera such as Eisenbergiella within HW and O, and likewise Alistipes within N were representative. These genera have roles directly relating to energy metabolism, amino acid, nucleotide and short chain fatty acid (SCFA) utilisation. Thus, an association exists between consistent and differentiating parameters of the production systems, that affect feed utilisation, advance our knowledge of mechanistic underpinnings, leading to competitive exclusion of genera based on competition for nutrients and other factors. Campylobacter was identified within specific production system and presence was linked with the increased diversity and increased environmental pressure on microbial community structure. Addition of Omega-3 though did alter prevalence of specific genera, in our analysis did not differentiate itself from HW production system. However, Omega-3 was linked with a positive impact on weight gain. ConclusionsOverall, our results show that microbial communities in different industrial production systems are deterministic in elucidating the underlying biological confounders, and these recommendations are transferable to farm practices and diet manipulation leading to improved performance and better intervention strategies against Campylobacter within the food chain. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/084251v2_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@c43951org.highwire.dtl.DTLVardef@8efa5corg.highwire.dtl.DTLVardef@d6db70org.highwire.dtl.DTLVardef@1e09fb9_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2019

Emergence of neuronal diversity during vertebrate brain development

Neurogenesis in the vertebrate brain comprises many steps ranging from the proliferation of progenitors to the differentiation and maturation of neurons. Although these processes are highly regulated, the landscape of transcriptional changes and progenitor identities underlying brain development are poorly characterized. Here, we describe the first developmental single-cell RNA-seq catalog of more than 200,000 zebrafish brain cells encompassing 12 stages from 12 hours post-fertilization to 15 days post-fertilization. We characterize known and novel gene markers for more than 800 clusters across these timepoints. Our results capture the temporal dynamics of multiple neurogenic waves from embryo to larva that expand neuronal diversity from [~]20 cell types at 12 hpf to [~]100 cell types at 15 dpf. We find that most embryonic neural progenitor states are transient and transcriptionally distinct from long-lasting neural progenitors of post-embryonic stages. Furthermore, we reconstruct cell specification trajectories for the retina and hypothalamus, and identify gene expression cascades and novel markers. Our analysis reveal that late-stage retinal neural progenitors transcriptionally overlap cell states observed in the embryo, while hypothalamic neural progenitors become progressively distinct with developmental time. These data provide the first comprehensive single-cell transcriptomic time course for vertebrate brain development and suggest distinct neurogenic regulatory paradigms between different stages and tissues.

developmental biology↗

bioRxiv2019

Estimation of cell lineage trees by maximum-likelihood phylogenetics

CRISPR technology has enabled large-scale cell lineage tracing for complex multicellular organisms by mutating synthetic genomic barcodes during organismal development. However, these sophisticated biological tools currently use ad-hoc and outmoded computational methods to reconstruct the cell lineage tree from the mutated barcodes. Because these methods are agnostic to the biological mechanism, they are unable to take full advantage of the datas structure. We propose a statistical model for the mutation process and develop a procedure to estimate the tree topology, branch lengths, and mutation parameters by iteratively applying penalized maximum likelihood estimation. In contrast to existing techniques, our method estimates time along each branch, rather than number of mutation events, thus providing a detailed account of tissue-type differentiation. Via simulations, we demonstrate that our method is substantially more accurate than existing approaches. Our reconstructed trees also better recapitulate known aspects of zebrafish development and reproduce similar results across fish replicates.

bioinformatics↗

bioRxiv2018

Massively parallel profiling and predictive modeling of the outcomes of CRISPR/Cas9-mediated double-strand break repair

Non-homologous end-joining (NHEJ) plays an important role in double-strand break (DSB) repair of DNA. Recent studies have shown that the error patterns of NHEJ are strongly biased by sequence context, but these studies were based on relatively few templates. To investigate this more thoroughly, we systematically profiled [~]1.16 million independent mutational events resulting from CRISPR/Cas9-mediated cleavage and NHEJ-mediated DSB repair of 6,872 synthetic target sequences, introduced into a human cell line via lentiviral infection. We find that: 1) insertions are dominated by 1 bp events templated by sequence immediately upstream of the cleavage site, 2) deletions are predominantly associated with microhomology, and 3) targets exhibit variable but reproducible diversity with respect to the number and relative frequency of the mutational outcomes to which they give rise. From these data, we trained a model that uses local sequence context to predict the distribution of mutational outcomes. Exploiting the bias of NHEJ outcomes towards microhomology mediated events, we demonstrate the programming of deletion patterns by introducing microhomology to specific locations in the vicinity of the DSB site. We anticipate that our results will inform investigations of DSB repair mechanisms as well as the design of CRISPR/Cas9 experiments for diverse applications including genome-wide screens, gene therapy, lineage tracing and molecular recording.

genomics↗

bioRxiv2017

Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data

Advances in proteomics reveal that pathway databases fail to capture the majority of cellular signaling activity. Our mass spectrometry study of the dynamic epidermal growth factor (EGF) response demonstrates that over 89% of significantly (de)phosphorylated proteins are excluded from individual EGF signaling maps, and 63% are absent from all annotated pathways. We present a computational method, the Temporal Pathway Synthesizer (TPS), to discover missing pathway elements by modeling temporal phosphoproteomic data. TPS uses constraint solving to exhaustively explore all possible structures for a signaling pathway, eliminating structures that are inconsistent with protein-protein interactions or the observed phosphorylation event timing. Applied to our EGF response data, TPS connects 83% of the responding proteins to receptors and signaling proteins in EGF pathway maps. Inhibiting predicted active kinases supports the TPS pathway model. The TPS algorithm is broadly applicable and also recovers an accurate model of the yeast osmotic stress response.

bioinformatics↗

bioRxiv2017

Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain by scGESTALT

Hundreds of cell types are generated during development, but their lineage relationships are largely elusive. Here we report a technology, scGESTALT, which combines cell type identification by single-cell RNA sequencing with lineage recording by cumulative barcode editing. We sequenced ~60,000 transcriptomes from the juvenile zebrafish brain and identified more than 100 cell types and marker genes. We engineered an inducible system that combines early and late barcode editing and isolated thousands of single-cell transcriptomes and their associated barcodes. The large diversity of edited barcodes and cell types enabled the generation of lineage trees with hundreds of branches. Inspection of lineage trajectories identified restrictions at the level of cell types and brain regions and helped uncover gene expression cascades during differentiation. These results establish scGESTALT as a new and widely applicable tool to simultaneously characterize the molecular identities and lineage histories of thousands of cells during development and disease.

developmental biology↗

bioRxiv2017

FlashFry: a fast and flexible tool for large-scale CRISPR target design

FlashFry is a fast and flexible command-line tool for characterizing large numbers of CRISPR target sequences. While several CRISPR web application exist, genome-wide knockout studies, noncoding deletion scans, and other large-scale studies or methods development projects require a simple and lightweight framework that can quickly discover and score thousands of candidates guides targeting an arbitrary DNA sequence. With FlashFry, users can specify an unconstrained number of mismatches to putative off-targets, richly annotate discovered sites, and tag potential guides with commonly used on target and off-target scoring metrics. FlashFry runs at speeds comparable to widely used genome-wide sequence aligners, and output is provided as an easy-to-manipulate text file.\n\nAvailabilityFlashFry is written in Scala and bundled as a stand-alone Jar file, easily run on any system with an installed Java virtual machine (JVM). The tool is freely licensed under version 3 of the GPL, and code, documentation, and tutorials are available on the GitHub page: http://aaronmck.github.io/FlashFry/

bioinformatics↗