Biology subjects

Mazutis, L.

Publications and source records attributed to Mazutis, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Cell-in-drop genotyping detects megabase-scale loss of heterozygosity as a quantitative marker for CRISPR-Cas9 on-target toxicity

Targeted DNA double strand breaks catalyzed by CRISPR-Cas9 have been demonstrated to cause megabase-scale segmental deletions and whole chromosome losses in a wide variety of mouse and human cell lines. This raises safety concerns for CRISPR-Cas9 based therapeutics and highlights the need for scalable methods to assess its on-target genotoxicity in clinical contexts. In this report, we present cell-in-drop genotyping, as a high throughput approach that combines single cell encapsulation with droplet-based PCR genotyping of endogenous polymorphisms to detect loss of heterozygosity (LOH) at a targeted chromosome without any genome manipulation. With this approach, we detected megabase scale LOH induced by Cas9 DSBs, mostly frequently by segmental loss. This approach also detected LOH from loss of a critical DNA repair factor, BLM helicase, and LOH induced by other genotoxic conditions, in particular, the chemotherapeutic drugs Paclitaxel and Mitomycin C, which were demonstrated to induce LOH by different mechanisms. A modified version of the assay also captured rare local short range LOH arising from DSB-induced interhomologue recombination. Because it requires no genome manipulation, cell-in-drop genotyping offers a practical, scalable tool for evaluating genotoxic risk of CRISPR-Cas9 and other agents in research and clinical development.

bioengineering↗

bioRxiv2026

Hierarchical classification of immune cell transcriptomes at population-scale

Accurate immune cell classification is essential for interpreting single-cell RNA sequencing (scRNA-seq) data. However, progress in automating cell type annotation is constrained by the lack of independent, high-resolution benchmarks, as routine data integration introduces statistical dependencies that inflate model generalizability. Here, we present the single-cell universal classification omnibus (Suco), a resource of independent, uniform expert annotations, and Compocyte, a modular hierarchical classifier. Together, they establish a framework that substantially outperforms existing classifiers while facilitating expert review of ambiguous annotations. Applying Compocyte across 50 studies, including three newly generated datasets, we classified 15.6 million leukocytes from 3,965 patients. Within this cohort, we identified a new tumor-associated resorptive macrophage phenotype, a non-canonical monocyte subtype in subclinical cytokine release syndrome, and the programmatic erosion of T cell memory stemness across metastatic sites. Suco and Compocyte thus provide a generalizable framework to uncover the principles governing human immunity at population scale. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/728980v2_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@13a6e4borg.highwire.dtl.DTLVardef@11f1626org.highwire.dtl.DTLVardef@1e72bd4org.highwire.dtl.DTLVardef@1ee799b_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefThe single-cell universal classification omnibus and the modular hierarchical classifier Compocyte enable annotating single cell RNA sequencing data from 3,965 patients, revealing novel resorptive macrophage and vaccination-associated monocyte states, alongside the erosion of T cell memory stemness as a hallmark of solid tumor metastases. HighlightsO_LISuco, a benchmark enabling novel single cell artificial intelligence models C_LIO_LICompocyte, a hierarchical cell type classifier outperforming current architectures C_LIO_LIMacrophages adopt osteoclast-like gene expression states across cancer types C_LIO_LIStem-like programs erode in metastasis-infiltrating T memory cells across tumors C_LI

bioinformatics↗

bioRxiv2025

Direct, high-throughput linking of single cell imaging and gene expression

Understanding sequence-phenotype relationships in biology requires large-scale datasets that provide one-to-one mapping of sequence to phenotype. Here, we address this challenge by introducing multimodal droplet barcoding, enabling individual microfluidic droplets to be tracked across both optical and sequencing measurements. We demonstrate the power of this approach through multimodal single-cell analysis. We pair imaging with gene expression profiling of individual cells, identifying genes that correlate with phenotypic features.

genomics↗

bioRxiv2025

Scalable single-cell metagenomic analysis with Bascet and Zorn

Single-cell metagenomic sequencing (scMetaG) can provide maximum-resolution insights into complex microbial communities. However, existing bioinformatic tools are not equipped to handle the massive amounts of data generated by novel high-throughput scMetaG methods. Here, we present a bioinformatic toolkit for complete, end-to-end scMetaG analysis: (i) Bascet, a command-line suite designed to scale to massive scMetaG datasets ([≥]1 million cells); (ii) Zorn, an R package/workflow manager that enables reproducible scMetaG data analysis, exploration, and visualization (http://zorn.henlab.org/). Enabled by recent advances in droplet microfluidics, we use Bascet and Zorn to develop and optimize a high-throughput scMetaG method on a ten-species mock community. To showcase their utility on a real-world sample, we use Bascet and Zorn to characterize a human saliva sample, generating single-amplified genomes (SAGs) from >10k prokaryotic cells. Overall, Bascet and Zorn enable reproducible scMetaG analysis, allowing users to query microbiomes at unprecedented resolution and scale.

microbiology↗

bioRxiv2025

High-throughput single cell -omics using semi-permeable capsules

Biological systems are inherently complex and heterogeneous. Deciphering this complexity increasingly relies on high-throughput analytical methods and tools that efficiently probe the cellular phenotype and genotype. While recent advancements have enabled various single-cell -omics assays, their broader applications are inherently limited by the challenge of efficiently conducting multi-step biochemical assays while retaining various biological analytes. Extending on our previous work (1) here we present a versatile technology based on semi-permeable capsules (SPCs), tailored for a variety of high-throughput nucleic acid assays, including digital PCR, genome sequencing, single-cell RNA-sequencing (scRNA-Seq) and FACS-based isolation of individual transcriptomes based on nucleic acid marker of interest. Being biocompatible, the SPCs support single-cell cultivation and clonal expansion over long periods of time - a fundamental limitation of droplet microfluidics systems. Using SPCs we perform scRNA-Seq on white blood cells from patients with hematopoietic disorders and demonstrate that capsule-based sequencing approach (CapSeq) offers superior transcript capture, even for the most challenging cell types. By applying CapSeq on acute myeloid leukemia (AML) samples, we uncover notable changes in transcriptomes of mature granulocytes and monocytes associated with blast and progenitor cell phenotypes. Accurate representation of the entirety of the cellular heterogeneity of clinical samples, driving new insights into the malfunctioning of the innate immune system, and ability to clonally expand individual cells over long periods of time, positions SPC technology as customizable, highly sensitive and broadly applicable tool for easy-to-use, scalable single-cell -omics applications.

genomics↗

bioRxiv2025

Transcriptomic plasticity is a hallmark of metastatic pancreatic cancer

Metastasis is the leading cause of cancer deaths; nonetheless, how tumor cells adapt to vastly different organ contexts is largely unknown. To investigate this question, we generated a transcriptomic atlas of primary tumor and diverse metastatic samples from a patient with pancreatic ductal adenocarcinoma who underwent rapid autopsy. Unsupervised archetype analysis identified both shared and site-specific gene programs, including lipid metabolism and gastrointestinal programs prevalent in peritoneum and stomach wall lesions, respectively. We developed a probabilistic approach for inferring clonal phylogeny from single-cell and matched whole-exome data. Distantly related genetic clones in the peritoneum express the lipid metabolism program, likely due to signaling by the adipocyte-rich peritoneum environment, and cells in most clones express multiple programs, suggesting that transcriptomic plasticity is a prevalent feature of metastatic cells. These deeply annotated analyses using a patient-centric platform provide a model for investigating metastatic mechanisms and plasticity in advanced cancer.

bioinformatics↗

bioRxiv2024

Single Cell Analysis of Treatment-Resistant Prostate Cancer: Implications of Cell State Changes for Cell Surface Antigen Targeted Therapies

Targeting cell surface molecules using radioligand and antibody-based therapies has yielded considerable success across cancers. However, it remains unclear how the expression of putative lineage markers, particularly cell surface molecules, varies in the process of lineage plasticity, wherein tumor cells alter their identity and acquire new oncogenic properties. A notable example of lineage plasticity is the transformation of prostate adenocarcinoma (PRAD) to neuroendocrine prostate cancer (NEPC)--a growing resistance mechanism that results in the loss of responsiveness to androgen blockade and portends dismal patient survival. To understand how lineage markers vary across the evolution of lineage plasticity in prostate cancer, we applied single cell analyses to 21 human prostate tumor biopsies and two genetically engineered mouse models, together with tissue microarray analysis (TMA) on 131 tumor samples. Not only did we observe a higher degree of phenotypic heterogeneity in castrate-resistant PRAD and NEPC than previously anticipated, but also found that the expression of molecules targeted therapeutically, namely PSMA, STEAP1, STEAP2, TROP2, CEACAM5, and DLL3, varied within a subset of gene-regulatory networks (GRNs). We also noted that NEPC and small cell lung cancer (SCLC) subtypes shared a set of GRNs, indicative of conserved biologic pathways that may be exploited therapeutically across tumor types. While this extreme level of transcriptional heterogeneity, particularly in cell surface marker expression, may mitigate the durability of clinical responses to novel antigen-directed therapies, its delineation may yield signatures for patient selection in clinical trials, potentially across distinct cancer types. SIGNIFICANCE STATEMENTTreatment of prostate cancer is rapidly evolving with several promising new drugs targeting different cell surface antigens. Selection of patients most likely to benefit from these therapies requires an understanding of how expression of these cell surface antigens varies across patients and how they change during disease progression, particularly in tumors that undergo lineage plasticity. Using immunohistochemistry and single cell mRNA sequencing, we reveal heterogeneity of cell states across a cohort of advanced disease prostate cancer patients; this heterogeneity is not captured by conventional histology-based designations of adenocarcinoma and neuroendocrine prostate cancer. We show these cell states can be identified by gene regulatory networks that could provide additional diagnostic precision based on their correlation with clinically relevant cell surface antigen expression.

cancer biology↗

bioRxiv2023

Deep generative model deciphers derailed trajectories in acute myeloid leukemia

Biological insights often depend on comparing conditions such as disease and health, yet we lack effective computational tools for integrating single-cell genomics data across conditions or characterizing transitions from normal to deviant cell states. Here, we present Decipher, a deep generative model that characterizes derailed cell-state trajectories. Decipher jointly models and visualizes gene expression and cell state from normal and perturbed single-cell RNA-seq data, revealing shared and disrupted dynamics. We demonstrate its superior performance across diverse contexts, including in pancreatitis with oncogene mutation, acute myeloid leukemia, and gastric cancer.

bioinformatics↗

bioRxiv2023

inDrops-2: a flexible, versatile and cost-efficient droplet microfluidics approach for high-throughput scRNA-seq of fresh and preserved clinical samples

The development of a large variety of single-cell analytical techniques has empowered researchers to explore diverse biological questions at the level of individual cells. Among these, droplet-based single-cell RNA sequencing (scRNA-seq) methods have been particularly prevalent owing to their high-throughput capabilities and reduced reaction volumes. While commercial systems have contributed to the widespread adoption of droplet-based scRNA-seq, the relatively high cost impose limitations for profiling large numbers of samples. Moreover, as the scope and scale of single cell sequencing methods keeps expanding, the possibility to accommodate diverse molecular biology workflows and inexpensively profile multiple biospecimens simultaneously becomes highly relevant. Herein, we present inDrops-2: an open-source scRNA-seq platform designed to profile fresh or preserved clinical samples with a sensitivity matching that of state-of-the-art commercial systems, yet at a few folds lower cost. Using inDrops-2, we conducted a comparative analysis of two prominent scRNA-seq protocols - those based on exponential and linear amplification of cDNA - and provide useful insights about the pros and cons inherited to each approach. We showcase the utility of inDrops-2 by simultaneously profiling 18 human lung carcinoma samples, all in one run, following cell preservation, long-term storage and multiplexing, to obtain a multiregional cellular profile of tumor microenvironment. The scalability, experimental flexibility and cost-efficiency offered by inDrops-2 should make it appealing for various single-cell transcriptomic studies.

molecular biology↗

bioRxiv2023

Progressive plasticity during colorectal cancer metastasis

Metastasis is the principal cause of cancer death, yet we lack an understanding of metastatic cell states, their relationship to primary tumor states, and the mechanisms by which they transition. In a cohort of biospecimen trios from same-patient normal colon, primary and metastatic colorectal cancer, we show that while primary tumors largely adopt LGR5+ intestinal stem-like states, metastases display progressive plasticity. Loss of intestinal cell states is accompanied by reprogramming into a highly conserved fetal progenitor state, followed by non-canonical differentiation into divergent squamous and neuroendocrine-like states, which is exacerbated by chemotherapy and associated with poor patient survival. Using matched patient-derived organoids, we demonstrate that metastatic cancer cells exhibit greater cell-autonomous multilineage differentiation potential in response to microenvironment cues than their intestinal lineage-restricted primary tumor counterparts. We identify PROX1 as a stabilizer of intestinal lineage in the fetal progenitor state, whose downregulation licenses non-canonical reprogramming.

cancer biology↗

bioRxiv2023

Single-cell transcriptional profiling of clear cell renal cell carcinoma reveals an invasive tumor vasculature phenotype

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of renal cancer, accounting for over 75% of cases. The asymptomatic nature of the disease contributes to late-stage diagnoses and poor survival. Highly vascularized and immune infiltrated microenvironment are prominent features of ccRCC, yet the interplay between vasculature and immune cells, disease progression and response to therapy remains poorly understood. Using droplet-based single-cell RNA sequencing we profiled 50,236 transcriptomes from paired tumor and healthy adjacent kidney tissues. Our analysis revealed significant heterogeneity and inter-patient variability of the tumor microenvironment. Notably, we discovered a previously uncharacterized vasculature subpopulation associated with epithelial-mesenchymal transition. The cell-cell communication analysis revealed multiple modes of immunosuppressive interactions within the tumor microenvironment, including clinically relevant interactions between tumor vasculature and stromal cells with immune cells. The upregulation of the genes involved in these interactions was associated with worse survival in the TCGA KIRC cohort. Our findings demonstrate the role of tumor vasculature and stromal cell populations in shaping the ccRCC microenvironment and uncover a subpopulation of cells within the tumor vasculature that is associated with an invasive phenotype.

cancer biology↗

bioRxiv2022

RNA cytometry of single-cells using semi-permeable microcapsules

Analytical tools for gene expression profiling of individual cells are critical for studying complex biological systems. However, the techniques enabling rapid measurements of gene expression on thousands of single-cells are lacking. Here, we report a high-throughput RNA cytometry for digital profiling of single-cells isolated in liquid droplets enveloped by a thin semi-permeable membrane (microcapsules). Due to selective permeability of the membrane, the desirable enzymes and reagents can be loaded, or replaced, in the microcapsule at any given step by simply changing the reaction buffer in which the microcapsules are dispersed. Therefore, complex molecular biology workflows can be readily adapted to conduct nucleic acid analysis on encapsulated mammalian cells, bacteria, or other biological species. The microcapsules support sequential multi-step enzymatic reactions, and remain intact under different biochemical conditions, freezing, thawing and thermocycling. Combining microcapsules with conventional FACS provides a high-throughput approach for conducting RNA cytometry of individual cells based on their digital gene expression signature.

molecular biology↗

bioRxiv2022

Epigenetic plasticity cooperates with emergent cell-cell interactions to drive neoplastic tissue remodeling in the pancreas

The response to tumor-initiating inflammatory and genetic insults can vary amongst morphologically indistinguishable cells, suggesting yet uncharacterized roles for epigenetic plasticity during early neoplasia. To investigate the origins and impact of such plasticity, we perform single-cell analyses on normal, inflamed, pre-malignant and malignant tissues in autochthonous models of pancreatic cancer. We reproducibly identify heterogeneous cell-states that are primed for diverse late-emerging neoplastic fates and link these to chromatin remodeling at cell-cell communication loci. Using a new inference approach, we reveal signaling gene modules and tissue-level crosstalk, including a neoplasia-driving feedback loop between discrete epithelial and immune cell populations that we validate by genetic perturbation in mice. Our results uncover a neoplasia-specific tissue remodeling program that may be exploited for pancreas cancer interception. One-Sentence SummarySingle-cell analysis reveals that enhanced epigenetic plasticity drives pro-neoplastic crosstalk in early pancreatic cancer.

cancer biology↗

bioRxiv2021

Multilineage plasticity in prostate cancer through expansion of stem-like luminal epithelial cells with elevated inflammatory signaling

Lineage plasticity is a well-established mechanism of resistance to targeted therapies in lung and prostate cancer, where tumors transition from adenocarcinoma to small-cell or neuroendocrine carcinoma. Through single-cell analysis of a cohort of heavily-treated castration-resistant human prostate cancers (CRPC), we report a greater degree of plasticity than previously appreciated, with multiple distinct neuroendocrine (NEPC), mesenchymal (EMT-like), and other subpopulations detected within single biopsies. To explore the steps leading to this plasticity, we turned to two genetically engineered mouse models of prostate cancer that recapitulate progression from adenocarcinoma to neuroendocrine disease. Time course studies reveal expansion of stem-like luminal epithelial cells (Sca1+, Psca+, called L2) that, based on trajectories, gave rise to at least 4 distinct subpopulations, NEPC (Ascl1+), POU2F3 (Pou2f3+), TFF3 (Tff3+) and EMT-like (Vim+, Ncam1+)--these populations are also seen in human prostate and small cell lung cancers. Transformed L2-like cells express stem-like and gastrointestinal endoderm-like transcriptional programs, indicative of reemerging developmental plasticity programs, as well as elevated Jak/Stat and interferon pathway signaling. In sum, while the magnitude of multilineage heterogeneity, both within and across patients, raises considerable treatment challenges, the identification of highly plastic luminal cells as the likely source of this heterogeneity provides a target for more focused therapeutic intervention. One Sentence SummaryMultilineage plasticity results from expansion of stem-like luminal cells with JAK/STAT activation, serving as a therapeutic target.

cancer biology↗

bioRxiv2021

Reversal of lineage plasticity in RB1/TP53-deleted prostate cancer through FGFR and Janus kinase inhibition

The inherent plasticity of tumor cells provides a mechanism of resistance to many molecularly targeted therapies, exemplified by adeno-to-neuroendocrine lineage transitions seen in prostate and lung cancer. Here we investigate the root cause of this lineage plasticity in a primary murine prostate organoid model that mirrors the lineage transition seen in patients. These cells lose luminal identity within weeks following deletion of Trp53 and Rb1, ultimately acquiring an Ar-negative, Syp+ phenotype after orthotopic in vivo transplantation. Single-cell transcriptomic analysis revealed progressive mixing of luminal-basal lineage features after tumor suppressor gene deletion, accompanied by activation of Jak/Stat and Fgfr pathway signaling and interferon-a and -g gene expression programs prior to any morphologic changes. Genetic or pharmacologic inhibition of Jak1/2 in combination with FGFR blockade restored luminal differentiation and sensitivity to antiandrogen therapy in models with residual AR expression. Collectively, we show lineage plasticity initiates quickly as a largely cell-autonomous process and, through newly developed computational approaches, identify a pharmacological strategy that restores lineage identity using clinical grade inhibitors.

cancer biology↗

bioRxiv2020

Single cell profiling reveals novel tumor and myeloid subpopulations in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively), which are associated with distinct therapeutic vulnerabilities. To define the heterogeneity of tumors and their associated microenvironments across subtypes, we sequenced 54,523 cellular transcriptomes from 21 human biospecimens. Our single-cell SCLC atlas reveals tumor diversity exceeding lung adenocarcinoma, driven by canonical, intermediate, and admixed subtypes. We discovered a PLCG2-high tumor cell population with stem-like, pro-metastatic features that recurs across subtypes and predicts worse overall survival, and manipulation of PLCG2 expression in cells confirms correlation with key metastatic markers. Treatment and subtype are associated with substantial phenotypic changes in the SCLC immune microenvironment, with greater T-cell dysfunction in SCLC-N than SCLC-A. Moreover, the recurrent, PLCG2-high subclone is associated with exhausted CD8+ T-cells and a pro-fibrotic, immunosuppressive monocyte/macrophage population, suggesting possible tumor-immune coordination to promote metastasis.

cancer biology↗

bioRxiv2020

Single cell transcriptional profiling reveals helper, effector, and regulatory MAIT cell populations enriched during homeostasis and activation

Mucosal-associated invariant T (MAIT) cells are innate-like lymphocytes that recognize microbial vitamin B metabolites and have emerging roles in infectious disease, autoimmunity, and cancer. Although MAIT cells are identified by a semi-invariant T cell receptor, their phenotypic and functional heterogeneity is not well understood. Here we present an integrated single cell transcriptomic analysis of over 76,000 human MAIT cells during acute and chronic antigen-specific activation with the MR1 ligand 5-OP-RU and non-specific TCR stimulation. We show that MAIT cells span a broad range of homeostatic, effector, helper, tissue-infiltrating, regulatory, and exhausted phenotypes, with distinct gene expression programs associated with CD4+ or CD8+ co-expression. During acute activation, MAIT cells rapidly adopt a cytotoxic phenotype characterized by high expression of GZMB, IFNG and TNF. In contrast, chronic stimulation induces heterogeneous states defined by proliferation, cytotoxicity, immune modulation, and exhaustion. These scRNAseq-defined MAIT cell subtypes were also detected in individuals recently exposed to Mycobacterium tuberculosis infection, confirming their presence during human infection. Our study provides the first comprehensive atlas of human MAIT cells in activation conditions and defines substantial functional heterogeneity, suggesting complex roles in health and disease.

immunology↗

bioRxiv2020

A unified atlas of CD8 T cell dysfunctional states in cancer and infection

CD8 T cells play an essential role in defense against viral and bacterial infections and in tumor immunity. Deciphering T cell loss of functionality is complicated by the conspicuous heterogeneity of CD8 T cell states described across different experimental and clinical settings. By carrying out a unified analysis of over 300 ATAC-seq and RNA-seq experiments from twelve independent studies of CD8 T cell dysfunction in cancer and infection we defined a shared differentiation trajectory towards terminal dysfunction and its underlying transcriptional drivers and revealed a universal early bifurcation of functional and dysfunctional T cell activation states across models. Experimental dissection of acute and chronic viral infection using scATAC-seq and allele-specific scRNA-seq identified state-specific transcription factors and captured the early emergence of highly similar TCF1+ progenitor-like populations at an early branch point, at which epigenetic features of functional and dysfunctional T cells diverge. Our atlas of CD8 T cell states will facilitate mechanistic studies of T cell immunity and translational efforts.

genomics↗