Biology subjects

Liu, Z.

Publications and source records attributed to Liu, Z..

At least 523 records · Page 29Linked to original sources

bioRxiv2024

Engineered minimal type I CRISPR-Cas system for transcriptional activation and base editing in human cells

Type I CRISPR-Cas systems are widespread and have exhibited remarkable versatility and efficiency in genome editing and gene regulation in prokaryotes. However, due to the multi-subunit composition and large size, their application in eukaryotes has not been thoroughly investigated. Here, we demonstrate that the type I-F2 Cascade, the most compact among type I systems and significantly smaller than SpCas9, can be developed into programmable tools for use in human cells. For transcriptional activation, the efficiency of the tool based on the engineered I-F2 system can match or surpass that of dCas9. Besides, narrow editing windows limit the application of base editors. Although the R-loop formed by Cascade is much wider than that by Cas9 or Cas12, the potential of base editing with Cascade has not yet been explored. We successfully created a base editor with the I-F2 Cascade, which induces a considerably wide editing window ([~]30 nt) with a bimodal distribution. The wide editing window can expand the range of targetable sites and can be useful for disrupting functional sequences and genetic screening. The editing efficiency can achieve 50% in human cells. This research underscores the application potential of compact type I systems in eukaryotes and developed a new base editor with an extraordinary wide editing window.

molecular biology↗

bioRxiv2024

Dynamic minimization of proteome reallocation explains metabolic transition in hierarchical utilization of mixed carbon sources

Cells choose between alternative pathways in metabolic networks under diverse environmental conditions, but the principles governing the choice are insufficiently understood, especially in response to dynamically changing conditions. Here we observed that a lactic acid bacterium Bacillus coagulans displayed homolactic fermentation on glucose or trehalose as the sole carbon source, but transitioned from homolactic to heterolactic fermentation during the hierarchical utilization of glucose and trehalose when growing on the mixture. We simulated the observation by dynamic minimization of reallocation of proteome (dMORP) using an enzyme-constrained genome-scale metabolic model of B. coagulans, which coincided with our omics data. Moreover, we evolved strains to co-utilize mixed carbon sources and repress the choice of heterolactic fermentation, and the dynamics after co-utilization of carbon sources could also be captured by dMORP. Altogether, the findings suggest that upon rapid environmental changes bacteria tend to minimize proteome reallocation and accordingly adjust metabolism, and dMORP would be useful in simulating and understanding cellular dynamics.

systems biology↗

bioRxiv2024

Tmc7 deficiency causes acrosome biogenesis defects and male infertility in mice

Transmembrane channel-like (TMC) proteins are a highly conserved ion channel family consisting of eight members (TMC1-TMC8) in mammals. TMC1/2 are components of the mechanotransduction channel in hair cells, and mutations of TMC1/2 cause deafness in humans and mice. However, the physiological roles of other TMC proteins remain largely unknown. Here, we show that Tmc7 is specifically expressed in the testis and that it is required for acrosome biogenesis during spermatogenesis. Tmc7-/- mice exhibited abnormal sperm head, disorganized mitochondrial sheaths, and reduced number of elongating spermatids, similar to human oligo-astheno-teratozoospermia. We further demonstrate that TMC7 is colocalized with GM130 at the cis-Golgi region in round spermatids. TMC7 deficiency leads to aberrant Golgi morphology and impaired fusion of Golgi-derived vesicles to the developing acrosome. Moreover, upon loss of TMC7 intracellular ion homeostasis is impaired and ROS levels are increased, which in turn causes Golgi and endoplasmic reticulum (ER) stress. Taken together, these results suggest that TMC7 is required to maintain pH and ion homeostasis, which is needed for acrosome biogenesis. Our findings unveil a novel role for TMC7 in acrosome biogenesis during spermiogenesis.

developmental biology↗

bioRxiv2024

PbrSYP71 regulates ER accumulation by interacting with actin during pollen tube growth in Pyrus

The uneven distribution of endoplasmic reticulum (ER) underlies the rapid polar growth of pollen tubes. However, the mechanism governing ER distribution remains elusive. In this study, we have identified a pollen tube-specific syntaxin protein, PbrSYP71. Our findings reveal that both overexpression and knocking down of PbrSYP71 inhibited pollen tube growth. Subcellular localization analysis demonstrates that PbrSYP71 anchors to the ER via its transmembrane structure. Overexpression of PbrSYP71 leads to clustered ER distribution in the pollen tube, while knocking down of PbrSYP71 abolishes the uneven ER distribution. Remarkably, transient overexpression of PbrSYP71{Delta}ABD, lacking the actin binding domain (ABD) of PbrSYP71, has no impact on ER distribution or pollen tube growth. Further investigation indicates that ABD is positioned on F-actin in the pollen tube and has a direct interaction with F-actin. PbrSYP71 assists the ER in moving towards the apex of pollen tube, with ABD displaying autonomous mobility. Our study elucidates that PbrSYP71 maintains uneven distribution of the ER by tethering ER to F-actin, facilitating ER movement towards the pollen tube apex for pear pollen tube elongation. These insights shed light on the mechanisms governing ER distribution in polarized cell growth.

cell biology↗

bioRxiv2024

CellDemux: coherent genetic demultiplexing in single-cell and single-nuclei experiments.

Multiplexed single-cell experiment designs are superior in terms of reduced batch effects, increased cost-effectiveness, throughput and statistical power. However, current computational strategies using genetics to demultiplex single-cell (sc) libraries are limited when applied to single-nuclei (sn) sequencing data (e.g., snATAC-seq and snMultiome). Here, we present CellDemux: a computational framework for genetic demultiplexing within and across data modalities, including single-cell, single-nuclei and paired snMultiome measurements. CellDemux uses a consensus approach, leveraging modality-specific tools to robustly identify non-empty oil droplets and singlets, which are subsequently demultiplexed to donors. Notable, CellDemux demonstrates good performance in demultiplexing snMultiome data and is generalizable to single modalities, i.e. snATAC-seq and sc/snRNA-seq libraries. We benchmark CellDemux on 187 genetically multiplexed libraries from 800 samples (scRNA-seq, snATAC-seq, CITE-seq and snMultiome), confidently identifying and assigning cells to 88% of donors. In paired snMultiome libraries, CellDemux achieves consistent demultiplexing across data modalities. Moreover, analysis of 38 snATAC libraries from 149 samples shows that CellDemux retains more genetically demultiplexed nuclei for downstream analyses compared to existing methods. In summary, CellDemux is a modular and robust framework that deconvolves donors from genetically multiplexed single-cell and single-nuclei RNA/ATAC/Multiome libraries.

genomics↗

bioRxiv2024

Expanding the ligandable proteome by paralog hopping with covalent probes

More than half of the [~]20,000 protein-encoding human genes have at least one paralog. Chemical proteomics has uncovered many electrophile-sensitive cysteines that are exclusive to a subset of paralogous proteins. Here, we explore whether such covalent compound-cysteine interactions can be used to discover ligandable pockets in paralogs that lack the cysteine. Leveraging the covalent ligandability of C109 in the cyclin CCNE2, we mutated the corresponding residue in paralog CCNE1 to cysteine (N112C) and found through activity-based protein profiling (ABPP) that this mutant reacts stereoselectively and site-specifically with tryptoline acrylamides. We then converted the tryptoline acrylamide-N112C-CCNE1 interaction into a NanoBRET-ABPP assay capable of identifying compounds that reversibly inhibit both N112C- and WT-CCNE1:CDK2 complexes. X-ray crystallography revealed a cryptic allosteric pocket at the CCNE1:CDK2 interface adjacent to N112 that binds the reversible inhibitors. Our findings thus provide a roadmap for leveraging electrophile-cysteine interactions to extend the ligandability of the proteome beyond covalent chemistry.

biochemistry↗

bioRxiv2024

Genomes of Aegilops umbellulata provide new insights into unique structural variations and genetic diversity in the U-genome for wheat improvement

Aegilops spp. serve as an important reservoir for novel sources of resistance or tolerance to biotic and abiotic stresses. To harness this reservoir, we have generated a high-quality chromosome-level genome assembly of an Ae. umbellulata accession PI 554389 using a combination of PacBio HiFi, Oxford nanopore, and chromosome conformation capture (Hi-C) sequencing technologies and resequenced 20 Ae. umbellulata genomes using Illumina sequencing. We assembled a 4.20 Gb genome spanned over seven chromosomes, rich in repetitive elements ([~]84%), achieving a QV of 59.54 with 98.14% completeness. The phylogenetic analysis places the U-genome with D-lineage, but major and distinct rearrangements were revealed in the U-genome. Unique transposon landscape of diploid U-genome and complex chromosomal rearrangements, most prominently in 4U and 6U chromosomes uncovered a distinct evolutionary trajectory of Ae. umbellulata. Additionally, the resequencing of geographically and morphologically diverse Ae. umbellulata accessions revealed three distinctive evolutionary sub-populations. Resequencing also identified six new haplotypes for Lr9, the first leaf rust resistance gene introgressed and cloned from Ae. umbellulata. These genomics resources along with high levels of resistance in the resequenced accessions against five devastating wheat diseases affirmed the genetic potential of Ae. umbellulata for wheat improvement.

plant biology↗

bioRxiv2024

Coordinated molecular and ecological adaptations underlie a highly successful parasitoid

The success of an organism depends on the molecular and ecological adaptations that promote its beneficial fitness. Parasitoids are valuable biocontrol agents for successfully managing agricultural pests, and they have evolved diversified strategies to adapt to both the physiological condition of hosts and the competition of other parasitoids. Here, we deconstructed the parasitic strategies in a highly successful parasitoid, Trichopria drosophilae, which parasitizes a broad range of Drosophila hosts, including the globally invasive species D. suzukii. We found that T. drosophilae had developed specialized venom proteins that arrest host development to obtain more nutrients via secreting tissue inhibitors of metalloproteinases (TIMPs), as well as a unique type of cell-- teratocytes--that digest host tissues for feeding by releasing trypsin proteins. In addition to the molecular adaptations that optimize nutritional uptake, this pupal parasitoid has evolved ecologically adaptive strategies including the conditional tolerance of intraspecific competition to enhance parasitic success in older hosts and the obligate avoidance of interspecific competition with larval parasitoids. Our study not only demystifies how parasitoids weaponize themselves to colonize formidable hosts but also provided empirical evidence of the intricate coordination between the molecular and ecological adaptations that drive evolutionary success.

ecology↗

bioRxiv2024

Capsaicin acts as a novel NRF2 agonist to suppress ethanol induced gastric mucosa oxidative damage by directly disrupting the KEAP1-NRF2 interaction

Excessive alcohol consumption poses significant health risks and is closely associated with oxidative damage. The KEAP1-NRF2-ARE signaling pathway serves as the primary antioxidant system. However, current small molecule inhibitors are all covalently bound to KEAP1, meaning that once bound, they are not easily dissociated, while continuous inhibition of KEAP1 exhibits severe side effects. In this study, BLI, CETSA, Pull-down, Co-IP and HDX-MS assay analysis were conducted to detect the KEAP1 binding behavior of natural product, capsaicin (CAP), both in vitro and in cells. The ethanol-induced acute gastric mucosal damage rat model was also established to evaluate the therapeutic effect of CAP. Our findings demonstrated that CAP mitigated mitochondrial damage, facilitated the nuclear translocation of NRF2, leading to the up-regulation of downstream antioxidant response elements, HMOX1, TXN, GSS and NQO1 in GES-1 cells. Furthermore, CAP directly bind to KEAP1 and inhibit the interaction between KEAP1 and NRF2. In the KEAP1-knockout 293T cells, CAP failed to activate NRF2 expression. We identified that CAP non-covalently bound to Kelch domain and allosterically regulated three specific regions of KEAP1 : L342-L355, D394-G423 and N482-N495. To improve drug solubility and delivery efficiency, we developed IR-Dye800 modified albumin coated CAP nanoparticles. The nanoparticles significantly reduced the gastric mucosal inflammation and activated NRF2 downstream genes in vivo. Our hypothesis was further verified our hypothesis in Nfe2l2-knockout mice. This study provides new insights that CAP is a safe and novel NRF2 agonist by allosterically regulating KEAP1, which may contribute to the development of lead drugs for oxidative stress-related illness, e.g. aging, cancer, neurodegenerative and cardiovascular diseases.

cell biology↗

bioRxiv2024

Differential endothelial cell cycle status in postnatal retinal vessels revealed using a novel PIP-FUCCI reporter and zonation analysis

Cell cycle regulation is critical to blood vessel formation and function, but how the endothelial cell cycle integrates with vascular regulation is not well-understood, and available dynamic cell cycle reporters do not precisely distinguish all cell cycle stage transitions in vivo. Here we characterized a recently developed improved cell cycle reporter (PIP-FUCCI) that precisely delineates S phase and the S/G2 transition. Live image analysis of primary endothelial cells revealed predicted temporal changes and well-defined stage transitions. A new inducible mouse cell cycle reporter allele was selectively expressed in postnatal retinal endothelial cells upon Cre-mediated activation and predicted endothelial cell cycle status. We developed a semi-automated zonation program to define endothelial cell cycle status in spatially defined and developmentally distinct retinal areas and found predicted cell cycle stage differences in arteries, veins, and remodeled and angiogenic capillaries. Surprisingly, the predicted dearth of proliferative tip cells at the vascular front was accompanied by an unexpected enrichment for endothelial tip cells in G2, suggesting G2 stalling as a contribution to tip-cell arrest. Thus, this improved reporter precisely defines endothelial cell cycle status in vivo and reveals novel G2 regulation that may contribute to unique aspects of blood vessel network expansion.

cell biology↗

bioRxiv2024

Prototype mRNA vaccines imprint broadly neutralizing human serum antibodies after Omicron variant-matched boosting

Immune imprinting is a phenomenon in which an individuals prior antigenic experiences influence responses to subsequent infection or vaccination. Here, using antibody depletion and multiplexed spike-binding assays, we characterized the type-specificity and cross-reactivity of serum antibody responses after mRNA vaccination in mice and human clinical trial participants. In mice, a single priming dose of a preclinical version of mRNA-1273 vaccine encoding Wuhan-1 spike minimally imprinted serum responses elicited by Omicron boosters, enabling a robust generation of type-specific antibodies. However, substantial imprinting was observed in mice receiving an Omicron booster after two priming doses of mRNA-1273, an effect that was mitigated by a second booster dose of Omicron mRNA vaccine. In humans who received two BA.5 or XBB.1.5 Omicron-matched boosters after two or more doses of the prototype mRNA-1273 vaccine, spike-binding and neutralizing serum antibodies cross-reacted with circulating Omicron variants as well as more distantly related sarbecoviruses. Because the serum neutralizing response against Omicron strains and other sarbecoviruses was completely abrogated after pre-clearing with the Wuhan-1 spike protein, antibodies induced by XBB.1.5 boosting in humans focus on conserved epitopes shaped and shared by the antecedent mRNA-1273 primary series. Our depletion analysis also identified cross-reactive neutralizing antibodies that recognize distinct epitopes in the receptor binding domain (RBD) and S2 proteins with differential inhibitory effects on members of the sarbecovirus subgenus. Thus, although the serum antibody response to Omicron-based boosters in humans is dominantly imprinted by prior immunizations with prototype mRNA-1273 vaccines, this outcome can be beneficial as it drives expansion of multiple classes of cross-neutralizing antibodies that inhibit infection of emerging SARS-CoV-2 variants and extend activity to distantly related sarbecoviruses.

immunology↗

bioRxiv2024

Multi-omic characterization of allele-specific regulatory variation in hybrid pigs

Genetic variation in the regulation of gene expression contributes substantially to phenotypic variation. Understanding how variation in DNA sequences and epigentic modifications leads to gene expression variation remains a challenging task. In hybrid animals where cellular environments are homogeneous, differences between the expression of paternal and maternal alleles must be due to cis sequence or epigenic differences. Therefore, hybrid mapping is a powerful approach to efficiently identify and characterize genes under regulation through mechanisms in cis. In this study, using reciprocal crosses of the phenotypically divergent Duroc and Lulai pig breeds, we performed a comprehensive multi-omic characterization of regulatory variation across brain, liver, muscle, and placenta in four developmental stages. We produced one of the largest multi-omic datasets to date in pigs, including 16 whole genome sequenced genomes, 48 whole genome bisulfite sequencing, 168 ATAC-Seq and 168 RNA-Seq samples. We developed a novel read count-based method to reliably assess allele-specific methylation, chromatin accessibility, and RNA expression. We showed that tissue specificity was much stronger than developmental stage specificity in all of DNA methylation, chromatin accessibility, and gene expression. We identified 573 genes showing allele specific expression, including those influenced by parent-of-origin as well as allele genotype effects. By integrating methylation, chromatin accessibility, and gene expression data, many of these allele specific expression can be explained by allele specific methylation and/or chromatin accessibility. This study provides one of the most comprehensive characterizations of regulatory variation across multiple tissues and developmental stages in pigs and offers new opportunity of genetic improvement for this important food animal species.

developmental biology↗

bioRxiv2024

Hunting for peptide binders of specific targets with data-centric generative language models

Bioactive peptides have become strong candidates for a variety of clinical therapies due to their diverse advantages, which promotes the development of deep generative models for peptide design. Considering that existing methods cannot effectively deal with the conformational flexibility of peptides and are difficult to capture accurate residue-to-residue interaction dependencies, we propose a unified weakly order-dependent autoregressive language modeling architecture (PepGenWOA) for bioactive peptide generative design with tolerating out-of-order input as inductive bias. The superiority of PepGenWOA is demonstrated by generating three classes of therapeutic peptides, including antimicrobial peptides, anticancer peptides, and peptide binders. For antimicrobial and anticancer peptide generation, PepGenWOA not only comprehensively outperforms state-of-the-art baseline models, but also exhibits a significant propensity to incorporate specific types of residues that are beneficial for antimicrobial or anticancer bioactivity. For characteristic-guided peptide binder generation, the pretrained PepGenWOA is fine-tuned with Mixture-of-Experts-style plugins with lifelong learning paradigm, thereby achieving the best trade-off between memory stability for world knowledge and learning plasticity for new downstream tasks. The subsequent structure-based virtual screening anchors the 7 most promising candidates from the mega-scale synthetic sequence space, reducing the number of candidates for in vitro experimental validation by 5 orders of magnitude. A target binding rate of 28.6% with binding specificity further confirms the effectiveness of the fine-tuning strategy. Overall, PepGenWOA is a unified architecture for peptide generative design that can be flexibly customized for different task requirements, thereby harnessing generative language models to reach the "dark space" of biological language.

bioinformatics↗

bioRxiv2023

Deconer: A comprehensive and systematic evaluation toolkit for reference-based cell type deconvolution algorithms using gene expression data

In recent years, computational methods for quantifying cell type proportions from transcription data have gained significant attention, particularly those reference-based methods which have demonstrated high accuracy. However, there is currently a lack of comprehensive evaluation and guidance for available reference-based deconvolution methods in cell proportion deconvolution analysis. In this study, we propose a comprehensive evaluation toolkit, called Deconer, specifically designed for reference-based deconvolution methods. Deconer provides various simulated and real gene expression datasets, including both bulk and single-cell sequencing data, and offers multiple visualization interfaces. By utilizing Deconer, we conducted systematic comparisons of 14 reference-based deconvolution methods from different perspectives, including method robustness, accuracy in deconvolving rare components, signature gene selection, and building external reference. We also performed an in-depth analysis of the application scenarios and challenges in cell proportion deconvolution methods. Finally, we provided constructive suggestions for users in selecting and developing cell proportion deconvolution algorithms. This work presents novel insights to researchers, assisting them in choosing appropriate toolkits, applying solutions in clinical contexts, and advancing the development of deconvolution tools tailored to gene expression data.

bioinformatics↗

bioRxiv2023

ConBoTNet: supervised contrastive learning enhances MHC-II peptide binding affinity prediction

Accurate prediction of major histocompatibility complex (MHC)-peptide binding affinity can improve our understanding of cellular immune responses and guide personalized immunotherapies. Nevertheless, the existing deep learning-based approaches for predicting MHC-II peptide interactions fall short of satisfactory performance and offer restricted model interpretability. In this study, we propose a novel deep neural network, termed ConBoTNet, to address the above issues by introducing the designed supervised contrastive learning and bottleneck transformer extractors. Specifically, the supervised contrastive learning pre-training enhances the models representative and generalizable capabilities on MHC-II peptides by pulling positive pairs closer and pushing negative pairs further in the feature space, while the bottleneck transformer module focuses on MHC-II peptide interactions to precisely identify binding cores and anchor positions in an unsupervised manner. Extensive experiments on benchmark datasets under 5-fold cross-validation, leave-one-molecule-out validation, independent testing, and binding core prediction settings highlighted the superiority of our proposed ConBoTNet over current state-of-the-art methods. Data distribution analysis in the latent feature space demonstrated that supervised contrastive learning can aggregate MHC-II-peptide samples with similar affinity labels and learn common features of similar affinity. Additionally, we interpreted the trained neural network by associating the attention weights with peptides and innovatively find both well-established and potential peptide motifs. This work not only introduces an innovative tool for accurately predicting MHC-II peptide affinity, but also provides new insights into a new paradigm for modeling essential biological interactions, advancing data-driven discovery in biomedicine.

bioinformatics↗

bioRxiv2023

Integrative genomics reveals the polygenic basis of seedlessness in grapevine

Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, while the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated four haplotype-resolved telomere-to-telomere (T2T) genomes for two seedless grape cultivars, Thompson Seedless (TS, syn. Sultania) and Black Monukka (BM). Comparative genomics identified a [~]4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, tracing the origin of the seedlessness trait back to Sultania. Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including novel candidate genes, such as three 11S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 groups related to seed development. Machine learning based genomic selection achieved a remarkable 99% precision in predicting grapevine seedlessness. Our findings highlight the polygenic nature of seedless and provide novel candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding.

genetics↗

bioRxiv2023

Adapting Nanopore Sequencing Basecalling Models for Modification Detection via Incremental Learning and Anomaly Detection

We leverage machine learning approaches to adapt nanopore sequencing basecallers for nucleotide modification detection. We first apply the incremental learning technique to improve the basecalling of modification-rich sequences, which are usually of high biological interests. With sequence backbones resolved, we further run anomaly detection on individual nucleotides to determine their modification status. By this means, our pipeline promises the single-molecule, single-nucleotide and sequence context-free detection of modifications. We benchmark the pipeline using control oligos, further apply it in the basecalling of densely-modified yeast tRNAs and E.coli genomic DNAs, the cross-species detection of N6-methyladenosine (m6A) in mammalian mRNAs, and the simultaneous detection of N1-methyladenosine (m1A) and m6A in human mRNAs. Our IL-AD workflow is available at: https://github.com/wangziyuan66/IL-AD.

bioinformatics↗

bioRxiv2023

Mantis: high-throughput 4D imaging and analysis of the molecular and physical architecture of cells

High-throughput dynamic imaging of cells and organelles is essential for understanding complex cellular responses. We report Mantis, a high-throughput 4D microscope that integrates two complementary, gentle, live-cell imaging technologies: remote-refocus label-free microscopy and oblique light-sheet fluorescence microscopy. Additionally, we report shrimPy, an open-source software for high-throughput imaging, deconvolution, and single-cell phenotyping of 4D data. Using Mantis and shrimPy, we achieved high-content correlative imaging of molecular dynamics and the physical architecture of 20 cell lines every 15 minutes over 7.5 hours. This platform also facilitated detailed measurements of the impacts of viral infection on the architecture of host cells and host proteins. The Mantis platform can enable high-throughput profiling of intracellular dynamics, long-term imaging and analysis of cellular responses to perturbations, and live-cell optical screens to dissect gene regulatory networks. Significance StatementUnderstanding the dynamics and interactions of cellular components is crucial for biological research and drug discovery. Current dynamic fluorescence microscopy methods can only image a few fluorescent labels, providing a limited view of these complex processes. We developed Mantis, a high-throughput 3D microscope that maps interactions among components of dynamic cell systems. Mantis combines light-sheet fluorescence imaging of multiple fluorophores with quantitative label-free microscopy and is complemented by shrimPy, our open-source software for high-throughput data acquisition and high-performance analysis. Mantis enabled simultaneous 3D time-lapse imaging of 20 cell lines and quantitative analysis of responses to perturbations like viral infection at single-cell resolution. This approach can accelerate the analysis of cellular dynamics and image-based drug discovery.

cell biology↗