Biology subjects

Deng, L.

Publications and source records attributed to Deng, L..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Real-Time Quantification of Cell Mechanics and Functions by Double Resonator Piezoelectric Cytometry -Theory and Study of Cellular Adhesion of HUVECs

Cell mechanics is closely associated with cellular structure and function. However, the inability to measure both cellular force and viscoelasticity of statistically significant number of cells noninvasively remains a challenge for quantitative characterizations of various cellular functions and practical applications. Here a double resonator piezoelectric cytometry (DRPC), using AT and BT cut quartz crystals of the same frequency and surface morphology is developed to simultaneously quantify the cells-generated forces ({Delta}S) and viscoelastic moduli (G', G'') of a population of isolated single cells or cells with different degrees of cell-cell interactions in a non-invasive and real time manner. DRPC captures the dynamic mechanical parameters {Delta}S and G', G'' during the adhesions of human umbilical vein endothelial cells (HUVECs) under different ligand densities of adhesion molecules fibronectin or Arg-Gly-Asp (RGD) modified on the gold surfaces of 9 MHz AT and BT cut quartz crystals, and different seeding densities of HUVECs. It is found that both the ligand density and cell seeding density affect the magnitudes of {Delta}S and G', G'' and their correlations are revealed for the first time by DRPC. The validity of DRPC is further verified by mechanical changes of the cells in response to treatments with cytoskeleton regulators.

biophysics↗

bioRxiv2023

INKILN is a novel long noncoding RNA promoting vascular smooth muscle inflammation

BackgroundActivation of vascular smooth muscle cells (VSMCs) inflammation is vital to initiate vascular disease. However, the role of human-specific long noncoding RNAs (lncRNAs) in VSMC inflammation is poorly understood. MethodsBulk RNA-seq in differentiated human VSMCs revealed a novel human-specific lncRNA called INflammatory MKL1 Interacting Long Noncoding RNA (INKILN). INKILN expression was assessed in multiple in vitro and ex vivo models of VSMC phenotypic modulation and human atherosclerosis and abdominal aortic aneurysm (AAA) samples. The transcriptional regulation of INKILN was determined through luciferase reporter system and chromatin immunoprecipitation assay. Both loss- and gain-of-function approaches and multiple RNA-protein and protein-protein interaction assays were utilized to uncover the role of INKILN in VSMC proinflammatory gene program and underlying mechanisms. Bacterial Artificial Chromosome (BAC) transgenic (Tg) mice were utilized to study INKLIN expression and function in ligation injury-induced neointimal formation. ResultsINKILN expression is downregulated in contractile VSMCs and induced by human atherosclerosis and abdominal aortic aneurysm. INKILN is transcriptionally activated by the p65 pathway, partially through a predicted NF-{kappa}B site within its proximal promoter. INKILN activates the proinflammatory gene expression in cultured human VSMCs and ex vivo cultured vessels. Mechanistically, INKILN physically interacts with and stabilizes MKL1, a key activator of VSMC inflammation through the p65/NF-{kappa}B pathway. INKILN depletion blocks ILI{beta}-induced nuclear localization of both p65 and MKL1. Knockdown of INKILN abolishes the physical interaction between p65 and MKL1, and the luciferase activity of an NF-{kappa}B reporter. Further, INKILN knockdown enhances MKL1 ubiquitination, likely through the reduced physical interaction with the deubiquitinating enzyme, USP10. INKILN is induced in injured carotid arteries and exacerbates ligation injury-induced neointimal formation in BAC Tg mice. ConclusionsThese findings elucidate an important pathway of VSMC inflammation involving an INKILN/MKL1/USP10 regulatory axis. Human BAC Tg mice offer a novel and physiologically relevant approach for investigating human-specific lncRNAs under vascular disease conditions.

molecular biology↗

bioRxiv2023

Development of Multiomics in situ Pairwise Sequencing (MiP-Seq) for Single-cell Resolution Multidimensional Spatial Omics

Delineating the spatial multiomics landscape will pave the way to understanding the molecular basis of physiology and pathology. However, current spatial omics technology development is still in its infancy. Here, we developed a high-throughput multiomics in situ pairwise sequencing (MiP-Seq) strategy to efficiently decipher multiplexed DNAs, RNAs, proteins, and small biomolecules at subcellular resolution. We delineated dynamic spatial gene profiles in the hypothalamus using MiP-Seq. Moreover, MiP-Seq was unitized to detect tumor gene mutations and allele-specific expression of parental genes and to differentiate sites with and without the m6A RNA modification at specific sites. MiP-Seq was combined with in vivo Ca2+ imaging and Raman imaging to obtain a spatial multiomics atlas correlated to neuronal activity and cellular biochemical fingerprints. Importantly, we proposed a "signal dilution strategy" to resolve the crowded signals that challenge the applicability of in situ sequencing. Together, our method improves spatial multiomics and precision diagnostics and facilitates analyses of cell function in connection with gene profiles.

molecular biology↗

bioRxiv2022

Mutation divergence over space in tumour expansion

Mutation accumulation in tumour evolution is one major cause of intra-tumour heterogeneity (ITH), which often leads to drug resistance during treatment. Previous studies with multi-region sequencing have shown that mutation divergence among samples within the patient is common, and the importance of spatial sampling to obtain a complete picture in tumour measurements. However, quantitative comparisons of the relationship between mutation heterogeneity and tumour expansion modes, sampling distances as well as the sampling methods are still few. Here, we investigate how mutations diverge over space by varying the sampling distance and tumour expansion modes using individual based simulations. We measure ITH by the Jaccard index between samples and quantify how ITH increases with sampling distance, the pattern of which holds in various sampling methods and sizes. We also compare the inferred mutation rates based on the distributions of Variant Allele Frequencies (VAF) under different tumour expansion modes and sampling sizes. In exponentially fast expanding tumours, a mutation rate can always be inferred in any sampling size. However, the accuracy compared to the true value decreases when the sampling size decreases, where small sampling sizes result in a high estimate of the mutation rate. In addition, such an inference becomes unreliable when the tumour expansion is slower such as in surface growth.

cancer biology↗

bioRxiv2022

Performance comparison of TCR-pMHC prediction tools reveals a strong data dependency

The interaction of T-cell receptors with peptide-major histocompatibility complex molecules plays a crucial role in adaptive immune responses. Currently there are various models aiming at predicting TCR-pMHC binding, while a standard dataset and procedure to compare the performance of these approaches is still missing. In this work we provide a general method for data collection, preprocessing, splitting and generation of negative examples, as well as comprehensive datasets to compare TCR-pMHC prediction models. We collected, harmonized, and merged all the major publicly available TCR-pMHC binding data and compared the performance of five state-of-the-art deep learning models (TITAN, NetTCR, ERGO, DLpTCR and ImRex) using this data. Our performance evaluation focuses on two scenarios: 1) different splitting methods for generating training and testing data to assess model generalization and 2) different data versions that vary in size and peptide imbalance to assess model robustness. Our results indicate that the five contemporary models do not generalize to peptides that have not been in the training set. We can also show that model performance is strongly dependent on the data balance and size, which indicates a relatively low model robustness. These results suggest that TCR-pMHC binding prediction remains highly challenging and requires further high quality data and novel algorithmic approaches.

bioinformatics↗

bioRxiv2022

CryoEM reveals unprecedented binding site for NaV1.7 inhibitors enabling rational design of potent hybrid inhibitors

The voltage-gated sodium (NaV) channel NaV1.7 has been identified as a potential novel pain target due to its striking human genetics. However, clinically available drugs (e.g. lidocaine, carbamazepine, etc.) are not selective among the nine NaV channel subtypes, NaV1.1-NaV1.9, and the two currently known classes of NaV1.7 subtype-selective inhibitors (aryl- and acylsulfonamides) have undesirable characteristics that may limit their development. Moreover, understanding of the structure-activity relationships of the acylsulfonamide class of NaV1.7 inhibitors, exemplified by the clinical development candidate GDC-0310, has been based solely on a single co-crystal structure of an arylsulfonamide inhibitor series. To advance inhibitor design targeting the NaV1.7 channel, we established an iterative system to routinely obtain high-resolution ligand-bound NaV1.7 structures using cryogenic electron microscopy (cryo-EM). We report that GDC-0310 engages the NaV1.7 voltage-sensing domain 4 (VSD4) through an unexpected binding mode orthogonal to the arylsulfonamide class binding pose, which identifies a previously unknown ligand binding site in NaV channels. This finding enabled the design of a novel hybrid inhibitor series that bridges the aryl and acylsulfonamide binding pockets and allows for the generation of molecules with substantially differentiated structures and properties. Overall, this study highlights the power of cryo-EM methods to pursue challenging drug targets using iterative and high-resolution structure-guided inhibitor design. It also underscores an important role of the membrane bilayer in the discovery of selective NaV channel modulators.

bioengineering↗

bioRxiv2022

Exploring the genome and protein space of viruses

Recent metagenomic studies have identified a vast number of viruses. However, the systematic assessment of the true genetic diversity of the whole virus community on our planet remains to be investigated. Here, we explored the genome and protein space of viruses by simulating the process of virus discovery in viral metagenomic studies. Among multiple functions, the power function was found to best fit the increasing trends of virus diversity and was therefore used to predict the genetic space of viruses. The estimate suggests that there are at least 8.23e+08 viral Operational Taxonomic Units (vOTUs) and 1.62e+09 viral protein clusters on Earth when assuming the saturation of the virus genetic space, taking into account the balance of costs and the identification of novel viruses. Its noteworthy that less than 3% of the viral genetic diversity has been uncovered thus far, emphasizing the vastness of the unexplored viral landscape. To saturate the genetic space, a total of 3.08e+08 samples would be required. Analysis of viral genetic diversity by ecosystem yielded estimates consistent with those mentioned above. Furthermore, the estimate of the virus genetic space remained robust when accounting for the redundancy of sampling, sampling time, sequencing platform, and parameters used for protein clustering. This study provides a guide for future sequencing efforts in virus discovery and contributes to a better understanding of viral diversity in nature.

microbiology↗

bioRxiv2022

Cell remote mechanics regulates large-spatial matrix modeling with dynamic simulations

Tissues are often isotropic and heterogeneous organizations, which developmental processes are coordinated by cells and extracellular matrix modeling. Cells have the capability of modeling matrix in distance, however, the biophysical mechanism is largely unknown. We investigated underlying mechanism of large collagen I (COL) fibrillary modeling by cell mechanics with designed arrays of cell clusters. By incorporating dynamic contractions, Molecular Dynamics simulations yielded highly matching isotropic outcomes with observed COL clustering in experiments from variable geometrical arrays without spatial limitation. Further designed single polygons from triangles to hexagons resulted in predicted structural assembly which showed maintained spatial balance. Cell cytoskeletal integrity (actin filaments, microtubules), actomyosin contractions, and endoplasmic reticulum calcium channels were essential for remote fiber inductions, while membrane mechanosensitive integrin and Piezo showed coordinative role in regulating the fiber assembly. The study provides new insights on cell mechanics-induced isotropic matrix modeling with dynamic large-spatial scales and the associated cellular mechanism. The assembled biomechanical scaffolds with pre-designs may lead to applications in micro-tissue engineering. This work implicates heterogeneous tissue structures maybe partially derived from isotropic cell mechanics.

biophysics↗

bioRxiv2022

IL-12-expressing highly immunogenic recombinant modified vaccinia virus Ankara reprograms tumor-infiltrating myeloid cells to overcome immune resistance

Resistance to immune checkpoint blockade (ICB) remains a major obstacle in cancer immunotherapy. We rationally engineered a second-generation recombinant Modified Vaccinia virus Ankara (MQ833) by deleting viral immune-evasion genes (E3L, E5R, WR199) and incorporating Flt3L, OX40L, and matrix-anchored IL12. Intratumoral MQ833 elicited robust tumor regressions across multiple models, including ICB-resistant and MHC-I-deficient tumors. Single-cell RNA sequencing revealed extensive remodeling of the tumor microenvironment, characterized by neutrophil and monocyte recruitment and activation, M2 macrophage depletion, M1 polarization, and effector T-cell differentiation and proliferation. Conditional Ifnar1 knockout mice demonstrated that MQ833 efficacy requires type I interferon signaling in neutrophils, macrophages/monocytes, and T cells. Moreover, Nos2 deficiency impaired therapeutic efficacy, confirming iNOS myeloid cells as key effectors. Together, these findings show that MQ833 activates innate-adaptive IFN cross-talk to reprogram myeloid and T cells, defining a rationally designed viral immunotherapy capable of overcoming ICB resistance. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/509429v2_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@496f37org.highwire.dtl.DTLVardef@124bd78org.highwire.dtl.DTLVardef@1134528org.highwire.dtl.DTLVardef@216da6_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

IndepthPathway: an integrated tool for in-depth pathway enrichment analysis based on bulk and single cell sequencing data

Single-cell sequencing (SCS) enables exploring the pathways and processes of cells, and cell populations. However, there is a paucity of pathway enrichment methods designed to tolerate the high noise and low gene coverage of this technology. When gene expression data are noisy and signals are sparse, testing pathway enrichment based on the genes expression may not yield statistically significant results which is particularly problematic when detecting the pathways enriched in less abundant cells that are vulnerable to disturbances. In this project, we developed a Weighted Concept Signature Enrichment Analysis (WCSEA) algorithm specialized for pathway enrichment analysis from single cell transcriptomics (scRNA-seq). WCSEA took a broader approach for assessing the functional relations of pathway gene sets to differentially expressed genes, and leverage the cumulative signature of molecular concepts characteristic of the highly differentially expressed genes, which we termed as the universal concept signature, to tolerate the high noise and low coverage of this technology. We then incorporated WCSEA into a R package called "IndepthPathway" for biologists to broadly leverage this method for pathway analysis based on bulk and single cell sequencing data. Through simulating technical variability and dropouts in gene expression characteristic of scRNA-seq as well as benchmarking on a real dataset of matched single cell and bulk RNAseq data, we demonstrate that IndepthPathway presents outstanding stability and depth in pathway enrichment results under stochasticity of the data, thus will substantially improve the scientific rigor of the pathway analysis for single cell sequencing data. The IndepthPathway package is available through: https://github.com/wangxlab/IndepthPathway.

bioinformatics↗

bioRxiv2022

Replidec - Use naive Bayes classifier to identify virus lifecycle from metagenomics data

MotivationViruses are the most abundant biological entities on earth. The majority of these entities are bacterial viruses or phages which specifically infect bacteria. Phages can use different replication strategies to invade their hosts including lytic, lysogenic, chronic cycle and pseudolysogeny. While the determination of the replication strategy used by phages is important to explore the phage-bacteria relationships in different ecosystems there are not many tools that can predict this in metagenomic data. In addition, most of the tools available can only predict lytic and lysogenic cycles. To address this issue, we have developed a new software called Replidec to identify three most common phage replication cycles (virulent, temperate, chronic) in viral sequences. ResultsReplidec uses Naive Bayes classifier combined with alignment-based methods to improve the prediction accuracy in metagenomic data. We test Replidec on viral genomes with known replication cycle and simulated metagenomic sequences. Replidec perform relatively good both in isolated genomes (F1 score: 92.29% {+/-} 0.81; mcc: 89.14% {+/-} 1.22) and simulated metagenomic sequences(F1 score: 87.55% {+/-} 2.12; mcc: 88.23% {+/-} 2.55). Moreover, Replidec can also accurately predict the replication cycle in small viral fragments([~]3000bp). In conclusion, Replidec can achieve the best performance in simulated metagenomic data compared to most prediction softwares including BACPHLIP.

bioinformatics↗

bioRxiv2022

Pseudouridine-dependent ribosome biogenesis regulates translation of polyglutamine proteins during Drosophila oogenesis

Stem cells in many systems, including Drosophila germline stem cells (GSCs), increase ribosome biogenesis and translation during terminal differentiation. Here, we show that pseudouridylation of ribosomal RNA (rRNA) mediated by the H/ACA box is required for ribosome biogenesis and oocyte specification. Reducing ribosome levels during differentiation decreased the translation of a subset of mRNAs that are enriched for CAG repeats and encode polyglutamine-containing proteins, including differentiation factors such as RNA-binding Fox protein 1. Moreover, ribosomes were enriched at CAG repeats within transcripts during oogenesis. Increasing TOR activity to elevate ribosome levels in H/ACA box-depleted germlines suppressed the GSC differentiation defects, whereas germlines treated with the TOR inhibitor rapamycin had reduced levels of polyglutamine-containing proteins. Thus, ribosome biogenesis and ribosome levels can control stem cell differentiation via selective translation of CAG repeat-containing transcripts.

developmental biology↗

bioRxiv2022

Somatostatin interneurons in auditory cortex regulate cortical representations and contribute to auditory perception

In the mammalian neocortex, somatostatin (SOM)-expressing GABAergic interneurons serve as a critical circuit component, receiving diverse inputs and targeting various types of cortical neurons. However, their role in perception and cognition remains not well understood. In this study, we employed cell-type specific imaging and perturbation during an auditory perceptual decision task to investigate the contribution of SOM interneurons. Two-photon calcium imaging revealed that auditory cortex (ACx) SOM interneurons exhibit not only frequency-selective responses but also selectivity to categorical choices. Simultaneous optogenetic inactivation and two-photon imaging revealed that SOM interneurons refine the frequency discriminability of auditory cortical neurons and contribute to their selectivity to the categorical decision boundary. Moreover, bilateral chemogenetic inactivation of ACx SOM interneurons impaired behavior-level perceptual categorization. Our findings provide a mechanistic understanding on the functional significance of SOM interneurons in auditory cortical processing and perceptual categorization, linking cell-type specific cortical circuit computations with perceptual functions.

neuroscience↗

bioRxiv2022

Altered virome structrue and function characterization in Helicobacter pylori-driven colorectal carcinogenesis and H. pylori eradication

The understanding of gut virome and its role in Helicobacter pylori-driven colorectal cancer (CRC), as well as the long-term impact of H. pylori eradication via antibiotic treatment on it could contribute to better understanding the mechanisms of the disruption of gut bacteriome homeostasis involved in H. pylori-driven colorectal carcinogenesis and antibiotic therapy for H. pylori eradication. In the dynamic analysis of viral genome shotgun metagenomic of samples from lower gastrointestinal tract of the Apc+/1638N and C57BL/6 mice with H. pylori infection and eradication, stable viral abundance and replacement of bursted unique viral contigs in infected and uninfected Apc+/1638N mice were observed. Temperate phages, which encoding comprehensive microbial functional genes and targeting various susceptible hosts, were expanded extremely prior to cancer exacerbation. In addition, short-term antibiotic exposure for H. pylori eradication was able to alter the gut virome and thrive the antibiotic resistance genes (ARGs) in the viral genome for at least 6 months. Collectively, these results point toward a potential role of the altered, but dynamically balanced gut virome, characterized by the expanded temperate phages, in contributing to the H. pylori-driven CRC, and indicate that viral genome may act as ARG reservoir for the antibiotic resistance of bacteria after the antibiotics therapy to H. pylori eradication.

microbiology↗

bioRxiv2022

Mechanical vibration modulates regional cerebral blood flow and biomechanical co-variance network in a frequency-dependent manner

Human brain experiences vibration of certain frequency during various physical activities such as vehicle transportation and machine operation or accidents, which may cause traumatic brain injury or other brain diseases. However, little is known about what happened to brain after vibration stimuli. Here, with a custom-built electromagnetic actuator, vibration was induced in the brain while cerebral blood flow (CBF) and brain stiffness were measured at 20, 30, 40 Hz for 52 healthy volunteers. With increasing frequency, multiple regions of the brain showed increasingly reduced CBF, while the size of such regions also expanded. The vibration-induced CBF reduction regions largely fell inside the brains default mode network (DMN), with about 58 or 46 % overlap at 30 or 40 Hz, respectively. By establishing a biomechanical co-variance network based on tissue stiffness, analysis of small-world properties and modularity showed an increased disruption of the network with increased frequency. These findings demonstrate frequency-dependent features of vibration modulation to brain. Furthermore, the overlap between CBF reduction regions and DMN, and the vibration-induced decrease of biomechanical network connections suggest a interweaved relationship between blood flow, tissue stiffness, and cognitive functions. These may provide critical insights into the mechanical stimulus to brain and vibration-induced brain pathologies.

neuroscience↗

bioRxiv2022

DeepsmirUD: Precise prediction of regulatory effects on miRNA expression mediated by small molecular compounds using competing deep learning frameworks

Aberrant miRNA expression has pervasively been found to relate to a growing number of human diseases. Therefore, targeting miRNAs to regulate their expression levels has become an important therapy against diseases that stem from the dysfunction of oncogenic pathways regulated by the miRNAs. In recent years, small molecule compounds have demonstrated enormous potential as drugs to regulate miRNA expression (i.e., SM-miR). A clear understanding of the mechanism of action of small molecules on down- and up-regulating miRNA expression allows precise diagnosis and treatment of oncogenic pathways. However, outside of a slow and costly process of experimental determination, computational strategies to assist this in an ad hoc manner have still not been enabled. In this work, we develop, to the best of our knowledge, the first prediction tool, DeepsmirUD, to infer small molecule-mediated regulatory effects on miRNA expression. This method is powered by an ensemble of 12 cutting-edged deep learning frameworks and achieves state-of-the-art performance with AUC values of 0.840/0.969 and AUCPR values of 0.866/0.983 on two independent test datasets. With a complementarily constructed network inference approach based on similarity, we report a significantly improved accuracy of 0.813 in determining regulatory effects of nearly 650 SM-miR relations formed with either novel small molecules or novel miRNAs. By further integrating miRNA-cancer relations, we established a database of potentially pharmaceutical drugs to aid in understanding the drug mechanisms of action in diseases and to offer novel insight into drug repositioning. Taken together, our method shows great promise to assist and accelerate the therapeutic development of potential miRNA targets and small molecule drugs. Furthermore, we have employed DeepsmirUD to predict regulatory effects of a large number of high-confidence SM-miR relations curated from Psmir, which are publicly available through https://github.com/2003100127/deepsmirud and https://rujinlong.github.io/deepsmirud/ alongside the DeepsmirUD standalone package.

bioinformatics↗

bioRxiv2022

Tumor-intrinsic PRC2 inactivation drives a context-dependent immune-desert tumor microenvironment and confers resistance to immunotherapy

Immune checkpoint blockade (ICB) has demonstrated clinical success in "inflamed" tumors with significant T-cell infiltrates, but tumors with an immune-desert tumor microenvironment (TME) fail to benefit. The tumor cell-intrinsic molecular mechanisms of the immune-desert phenotype remain poorly understood. Here, we demonstrate that inactivation of the Polycomb-repressive complex 2 (PRC2) core components, EED or SUZ12, a prevalent genetic event in malignant peripheral nerve sheath tumor (MPNST) and sporadically in other cancer types, drives a context-dependent immune-desert TME. PRC2 inactivation reprograms the chromatin landscape that leads to a cell-autonomous shift from primed baseline signaling-dependent cellular responses (e.g., interferon {gamma}) to PRC2-regulated development and cellular differentiation transcriptional programs. Further, PRC2 inactivation reprograms the TME, leads to diminished tumor immune infiltrates and immune evasion through reduced chemokine production and impaired antigen presentation and T-cell priming, and confers ICB primary resistance through blunted T-cell recruitment in vivo. We demonstrate that strategies that enhancing innate immunity via intratumoral delivery of inactivated modified vaccinia virus Ankara (MVA) leads to increased tumor immune infiltrates and sensitizes PRC2-loss tumors to ICB. Our results provide novel molecular mechanisms of context-dependent dysfunctional epigenetic reprogramming that underline the immune-desert phenotype in MPNST and other cancers with PRC2 inactivation. Importantly, our findings highlight genetic-inactivation of PRC2 as a novel context-dependent ICB therapeutic resistance biomarker in cancer, and caution that therapeutic strategies that non-selectively target PRC2 in the host may lead to undesirable context-dependent immune evasion and ICB resistance in tumors. Our studies also point to intratumoral delivery of immunogenic therapeutic viruses as an initial strategy to modulate the immune-desert TME and capitalize on the clinical benefit of ICB.

cancer biology↗

bioRxiv2022

CRISPR-Cas provides limited phage immunity to a prevalent gut bacterium in gnotobiotic mice

Many prokaryotes harbor the adaptive CRISPR-Cas system, which stores small nucleotide fragments from previous invasions of nucleic acids via viruses or plasmids. This molecular archive blocks further invaders carrying identical or similar nucleotide sequences. However, very few of these systems have been experimentally confirmed to be active in gut bacteria. Here, we experimentally demonstrate that the type I-C CRISPR-Cas system of the prevalent gut bacterium Eggerthella lenta can specifically target and cleave foreign DNA in vitro by using a plasmid transformation assay. We also show that the CRISPR-Cas system acquires new immunities (spacers) from the genome of a virulent E. lenta phage using traditional phage-assays in vitro but also in vivo using gnotobiotic (GB) mice. An increased number of spacer acquisition events were observed when E. lenta was exposed to a low multiplicity of infection in vitro, and three phage genes were found to contain protospacer hotspots. Interestingly, much less new spacer acquisitions were detected in vivo than in vitro. Longitudinal analysis of phage-bacteria interactions showed sustained coexistence in the gut of GB mice, with phage abundance being approximately one log higher than the bacteria. Our findings show that while the type I-C CRISPR-Cas system is active in vitro and in vivo, a highly virulent phage in vitro was still able co-exist with its bacterial host in vivo. Taken altogether, our results suggest that the CRISPR-Cas defense system of E. lenta provides only partial immunity in the gut.

microbiology↗