Biology subjects

Li, C.

Publications and source records attributed to Li, C..

At least 721 records · Page 40Linked to original sources

bioRxiv2022

The chromosome-scale genome assembly of the yellowtail clownfish Amphiprion clarkii provides insights into melanic pigmentation of anemonefish

Anemonefish are an emerging group of model organisms for studying genetic, ecological, evolutionary, and developmental traits of coral reef fish. The yellowtail clownfish Amphiprion clarkii possesses species-specific characteristics such as inter-species co-habitation, high intra-species color variation, no anemone specificity, and a broad geographic distribution, that can increase our understanding of anemonefish evolutionary history, behavioral strategies, fish-anemone symbiosis, and color pattern evolution. Despite its position as an emerging model species, the genome of A. clarkii is yet to be published. Using PacBio long-read sequencing and Hi-C chromatin capture technology, we generated a high-quality chromosome-scale genome assembly initially comprised of 1,840 contigs with an N50 of 1,203,211 bp. These contigs were successfully anchored into 24 chromosomes of 843,582,782 bp and annotated with 25,050 protein-coding genes encompassing 97.0 % of conserved actinopterygian genes, making the quality and completeness of this genome the highest amongst all published anemonefish genomes to date. Transcriptomic analysis identified tissue-specific gene expression patterns, with the brain and optic lobe having the largest number of expressed genes. Further analyses revealed higher copy numbers of erbb3b (a gene involved in melanophore development) in A. clarkii compared to other anemonefish, thus suggesting a possible link between erbb3b and the natural melanism polymorphism observed in A. clarkii. The publication of this high-quality genome, along with A. clarkiis many unique traits, position this species as an ideal model organism for addressing scientific questions across a range of disciplines.

genomics↗

bioRxiv2022

MINE is a method for detecting spatial density of regulatory chromatin interactions based on a MultI-modal NEtwork

Chromatin interactions play essential roles in chromatin conformation and gene expression. However, few tools exist to analyze the spatial density of regulatory chromatin interactions. Here, we present the MultI-modal NEtwork (MINE) toolkit, including MINE-Loop, MINE-Density, and MINE-Viewer. MINE-Loop network modeling integrates Hi-C, ATAC-seq, and histone ChIP-seq data to enhance the detection of regulatory chromatin interactions (RCIs, i.e., chromatin interactions that are anchoring regulatory elements to chromatin); MINE-Density quantifies the spatial density of regulatory chromatin interactions identified by MINE-Loop within different chromatin conformations; and MINE-Viewer facilitates 3D visualization of the density of chromatin interactions and participating regulatory factors, such as transcription factors. We applied MINE to investigate the relationship between the spatial density of regulatory chromatin interactions (SD-RCI) and chromatin volume change in HeLa cells before and after liquid-liquid phase separation. Changes in SD-RCI before and after treating the HeLa cells with 1,6-hexanediol showed that the change in chromatin volume was related to the degree of activation or repression of genes in chromatin interactions. The MINE toolkit provides a new method for quantitative study of chromatin conformation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=187 HEIGHT=200 SRC="FIGDIR/small/499656v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@1705cc8org.highwire.dtl.DTLVardef@1db89adorg.highwire.dtl.DTLVardef@2be8e4org.highwire.dtl.DTLVardef@c6f1a6_HPS_FORMAT_FIGEXP M_FIG C_FIG In BriefGong et al. provide a toolkit MINE to explore the relationship between spatial density of regulatory chromatin interactions, gene expression and chromatin structure change. HighlightsO_LIMINE toolkit was provided to detect more regulatory chromatin interactions (RCI), count the spatial density of regulatory chromatin interactions and visualize the density of chromatin interactions with transcription factors in three-dimension. C_LIO_LIChromatin regions were divided into developed active hub, developing active hub, developed repressive hub, and developing repressive hub according to the density of active or repressive regulatory chromatin interactions. C_LIO_LIThe change of chromatin structure before and after liquid-liquid phase separation is quantitively described by using the MINE toolkit. C_LI

bioinformatics↗

bioRxiv2022

Pathway-specific inputs to the superior colliculus support flexible triggering of innate behaviors

Behavioral flexibility requires the ability to modify the feedforward transmission of sensory information. The superior colliculus mediates visually guided innate defensive behaviors via cell-type specific projections. However, how brain-wide inputs to the superior colliculus are organized to modulate visual processing and enable flexible behavior remains unknown. To determine these rules, we focused on inhibitory projection (Gad2) neurons. Trans-synaptic tracing and neuronal recordings revealed that Gad2 neurons projecting to the dorsal lateral geniculate nucleus (LGd) and the parabigeminal nucleus (PBG) form two separate anatomical and functional populations, where each circuit received a different set of non-retinal inputs. Inhibiting LGd or PBG projecting Gad2 neurons resulted in opposing effects on behavior; increasing freezing or escape probability to visual looming stimuli, respectively. These data suggest that projection-specific sampling of brain-wide inputs provide a circuit design principle that enables feed-forward transfer of visual threat to be independently adjusted to produce context specific behavior.

neuroscience↗

bioRxiv2022

Modification Mechanism of Phenol-formaldehyde Resin with Crude Bio-oil by Model Compound Method

To clarify the modification mechanism of bio-oil for phenol-formaldehyde resin with crude bio-oil (BPF), the bio-oil compounds were simplified by model compound method according to the component distribution. The phenol-formaldehyde resin with bio-oil model compounds (BMPF) were prepared and their basic performance, bonding strength and aging characteristics were determined. The changes on the microstructure and chemical bonds of BMPF were also analyzed by scanning electron microscope, Fourier transform infrared spectroscopy, and nuclear magnetic resonance analysis. Results showed that the components of bio-oil had different influence on the performance and microstructure of BMPF, especially phenols. Structural analysis indicated that the phenols and ketones of bio-oil had positive effects on the synthesis of BMPF, while the aldehydes and acids had negative effects. But all components of bio-oil could improve the aging resistance of BMPF inordinately. These results could provide a basis for the modification of BPF.

ecology↗

bioRxiv2022

Single-cell multi-omics enabled discovery of alkaloid biosynthetic pathway genes in the medical plant Catharanthus roseus

Advances in omics technologies now permit generation of highly contiguous genome assemblies, detection of transcripts and metabolites at the level of single cells, and high-resolution determination of gene regulatory features including 3-dimensional chromatin interactions. Using a complementary, multi-omics approach, we interrogated the monoterpene indole alkaloid (MIA) biosynthetic pathway in Catharanthus roseus, a source of leading anti-cancer drugs. We identified not only new clusters of genes involved in MIA biosynthesis on the eight C. roseus chromosomes but also rampant gene duplication including paralogs of MIA pathway genes. Clustering was not limited to the linear genome and through chromatin interaction data, MIA pathway genes were shown to be present within the same topologically associated domain, permitting identification of a secologanin transporter. Single cell RNA-sequencing revealed exquisite and sequential cell-type specific partitioning of the leaf MIA biosynthetic pathway that, when coupled with a newly developed single cell metabolomics approach, permitted identification of a reductase that yields the bis-indole alkaloid anhydrovinblastine. Last, we revealed cell-type specific expression in the root MIA pathway that is conferred in part by neo- and sub-functionalization of paralogous MIA pathway genes. This study highlights how a suite of omic approaches, including single cell gene expression and metabolomics, can efficiently link sequence with function in complex, specialized metabolic pathways of plants.

plant biology↗

bioRxiv2022

Nonlinear effect of light intensity on normal axial development of rhesus monkeys

PurposeTo investigate the effects of different indoor lighting intensity (500 lx, 750 lx and 1,000 lx) on normal ocular axial length growth by using juvenal rhesus monkeys. MethodsTwenty-four juvenile monkeys were exposed continuously to normal intensity light (NIL, 500 lx, n=16), medium intensity light (MIL, 750 lx, n=8) and high intensity light (HIL, 1 000 lx, n=8), with a same CCT value (about 3000 K) for 246 days. Axial length, anterior chamber depth, corneal curvature radius were measured at about a monthly interval. ResultsAfter 246 days of light exposure, the growth of axial length of the MIL group (750 lx) were 0.151 {+/-} 0.081 mm and 0.139 {+/-} 0.070 mm in the right and left eyes, respectively, and significantly larger in comparison with the NIL group (500lx, OD: 0.068 {+/-} 0.055 mm, OS: 0.074 {+/-} 0.057 mm) and the HIL group (1000lx,OD:0.063 {+/-} 0.093 mm, OS: 0.084 {+/-} 0.052 mm) monkeys. This effect was stable and robust during the whole experimental period. ConclusionThe effects of different intensity lighting on normal ocular axial development was not linear as most people currently think. We must be cautious when it comes to elevate light intensity in classrooms. Whether this conclusion is correct under lights of other CCT value needs further study.

developmental biology↗

bioRxiv2022

The Intrinsic Hierarchy of Self - Converging Topography and Dynamics

The brain can be characterized by an intrinsic hierarchy in its topography which, as recently shown for the uni-transmodal distinction of core and periphery, converges with its dynamics. Does such intrinsic hierarchical organization in both topography and dynamic also apply to the brains inner core itself and its higher-order cognitive functions like self? Applying multiple fMRI data sets, we show how the recently established three-layer topography of self (internal, external, mental) is already present during the resting state and carried over to task states including both task-specific and -unspecific effects. Moreover, the topographic hierarchy converges with corresponding dynamic changes (measured by power-law exponent, autocorrelation window, median frequency, sample entropy, complexity) during both rest and task states. Finally, analogous to the topographic hierarchy, we also demonstrate hierarchy among the different dynamic measures themselves according to background and foreground. Finally, we show task-specific- and un-specific effects in the hierarchies of both dynamics and topography. Together, we demonstrate the existence of an intrinsic topographic hierarchy of self and its convergence with dynamics.

neuroscience↗

bioRxiv2022

The Optimal Combination of Scanning Speed and Fiber-to-Stone Distance for Effective and Efficient Dusting during Holmium: YAG Laser Lithotripsy

ObjectivesTo investigate mechanistically the effects of fiber scanning speed (vfiber) and fiber tip-to-stone standoff distance (SD) on dusting efficiency during Holmium (Ho): YAG laser lithotripsy (LL) Materials and MethodsPre-soaked BegoStone samples (23 x 23 x 4 mm, W x L x H) were treated in water using a clinical Ho:YAG laser in dusting mode (0.2 J pulse energy delivered at 20 Hz frequency) at three different SDs (0.10, 0.25 and 0.50 mm) with vfiber in the range of 0 to 10 mm/s. Stone damage was quantified by optical coherence tomography, bubble dynamics were captured by high-speed imaging, and associated pressure transients were measured using a needle hydrophone. To compare photothermal ablation vs. cavitation in stone dusting, the experiments were further repeated in air (photothermal ablation only), and in water with the fiber tip advanced at a short (0.25 mm) offset distance (OSD) from a ureteroscope to mitigate the bubble collapse toward the stone surface, thus eliminating cavitation-induced damage. ResultsCompared to the craters produced by a stationary fiber, the damage troughs produced by a scanning fiber after 100 pulses were significantly larger in volume. The optimal vfiber for maximum dusting efficiency was found to be 3.5 mm/s for SD = 0.10 [~] 0.25 mm, resulting in long (17.5 mm), shallow (0.14 - 0.15 mm) and narrow (0.3 - 0.4 mm) troughs. In contrast, the maximum stone damage was produced at an optimal vfiber of 0.5 mm/s for SD = 0.50 mm, which generates much shorter (2.5 mm), yet deeper (0.35 mm) and wider (1.4 mm) troughs. Greater stone damage was produced in water than in air, especially at vfiber = 0 - 3.5 mm/s. With the scope end placed near the fiber tip, stone damage could be significantly reduced in water by 29% - 58% for SD = 0.10 mm, by 51% - 82% for SD = 0.25 mm, and by 66% - 100 % for SD = 0.50 mm, compared to those produced without the scope. Together, these findings suggest that cavitation plays an indispensable role in stone dusting by scanning treatment. Moreover, under clinically relevant vfiber (1 [~] 3 mm/s), dusting at SD = 0.5 mm (i.e., non-contact mode) may leverage higher frequency of the laser (e.g., 40 to 120 Hz) to harvest the full potential of cavitation damage while significantly reducing the procedure time, compared to its counterpart at SD = 0.1 mm (i.e., contact mode) that promotes photothermal ablation. ConclusionDusting efficiency during Ho:YAG LL may be substantially improved by utilizing the optimal combination of vfiber and SD for a given frequency.

bioengineering↗

bioRxiv2022

Tumor-educated monocytes suppress T cells via adenosine and depletion of adenosine in the tumor microenvironment with adenosine deaminase enzyme promotes response to immunotherapy

Although immune checkpoint inhibitor (ICI) therapy has provided robust results in many cancer types such as melanoma and lung cancer, a large percentage of patients remain unresponsive to this therapy. Emerging evidence strongly suggests that one of the contributing factors in ICI resistance is monocytic myeloid derived suppressor cells (M-MDSCs) that accumulate in late-stage cancer patients. These M-MDSCs are a subset of innate immune cells and possess potent immunosuppressive activity against T lymphocytes. Here we provide evidence of a mechanism by which CD73-expressing M-MDSCs in the tumor microenvironment (TME) exhibit superior T cell suppressor function via adenosine. We show that tumor-derived PGE2, a prostaglandin frequently found at high levels in the TME, directly induces CD73 expression in M-MDSCs by initiating a signaling pathway that is mediated by both Stat3 and CREB. The resulting CD73 overexpression induces elevated levels of adenosine, a nucleoside with strong T cell suppressive activity, culminating in the suppression of CD8+ T cell-mediated anti-tumor responses. We also show that depletion of adenosine in the TME by the repurposed drug PEGylated Adenosine Deaminase (PEG-ADA) increases CD8+ T cell anti-tumor activity and enhances response to ICI therapy in preclinical models of cancer. Our results suggest that use of PEG-ADA is a viable therapeutic option to overcome ICI therapeutic resistance in advanced cancer patients.

cell biology↗

bioRxiv2022

Cable-free brain imaging with miniature wireless microscopes

The invention of the miniaturized microscope has enabled neuroscientists to investigate neural mechanisms in freely moving mice. A lot of efforts have been made to optimize performance of the miniaturized microscope. However, the tethered cables limit the ability of mini-microscope systems to record neural activity from multiple mice simultaneously. Here, we present a wireless mini-microscope (wScope) that enables both real-time remote control and data preview during animal behavior; this design also supports simultaneous recording from up to 8 mice. The wScope has a mass of 2.7 g and a maximum frame rate of 25 Hz at 750 m by 450 m field of view with 1.8 m resolution. We validated the wScopes in video-recording of the cerebral blood flow (CBF) and the activity of neurons in the primary visual cortex (V1) of different mice. The wScope provides a powerful tool for brain imaging of free moving animals, including large primates, in their much larger spaces and more naturalistic environments.

neuroscience↗

bioRxiv2022

The domain-separation low-dimensional language network dynamics in the resting-state support the flexible functional segregation and integration during language and speech processing

Modern linguistic theories and network science propose that the language and speech processing is organized into hierarchical, segregated large-scale subnetworks, with a core of dorsal (phonological) stream and ventral (semantic) stream. The two streams are asymmetrically recruited in receptive and expressive language or speech tasks, which showed flexible functional segregation and integration. We hypothesized that the functional segregation of the two streams was supported by the underlying network segregation. A dynamic conditional correlation approach was employed to construct frame-wise time-varying language networks and investigate the temporal reoccurring patterns. We found that the time-varying language networks in the resting-state robustly clustered into four low-dimensional states, which dynamically reconfigured following a domain-separation manner. Spatially, the hub distributions of the first three states highly resembled the neurobiology of primary auditory processing and lexical-phonological processing, motor and speech production processing, and semantic processing, respectively. The fourth state was characterized by the weakest functional connectivity and subserved as a baseline state. Temporally, the first three states appeared exclusively in limited time bins ([~]15%), and most of the time (> 55%), the language network kept inactive in state 4. Machine learning-based dFC-linguistics prediction analyses showed that dFCs of the four states significantly predicted individual linguistic performance. These findings suggest a domain-separation manner of language network dynamics in the resting-state, which forms a dynamic "meta-networking" (network of networks) framework. HighlightsO_LIThe time-varying language network in the resting-state is robustly clustered into four low-dimensional states. C_LIO_LISpatially, the first three dFC states are cognitively meaningful, which highly resemble the neurobiology of primary auditory processing and lexical-phonological representation, speech production processing, and semantic processing, respectively. C_LIO_LITemporally, the first three states appeared exclusively in limited time bins ([~]15%), and most of the time (> 55%), the language network kept inactive in state 4. C_LIO_LIA dynamic "meta-networking" framework of language network in the resting-state is proposed. C_LI

neuroscience↗

bioRxiv2022

A pangenome analysis pipeline (PSVCP) provides insights into rice functional gene identification

BackgroundA pangenome aims to capture the complete genetic diversity within a species and reduce bias in genetic analysis inherent in using a single reference genome. However, the current linear format of most plant pangenomes limits the presentation of position information for novel sequences. Graph pangenomes have been developed to overcome this limitation. However, there is a lack of bioinformatics analysis tools for graph format genomes. ResultsTo overcome this problem, we have developed a novel pangenome construction strategy and a downstream pangenome analysis pipeline that captures position information while maintaining a linearized layout. We applied this strategy to construct a high-quality rice pangenome using 12 representative rice genomes and analyze an international rice panel with 413 diverse accessions using the pangenome reference. Our results provide insights into rice population structure and genomic diversity. Applying the pangenome for PAV-based GWAS analysis can identify causal structural variations for rice grain weight and plant height, while SNP-based GWAS can only identify approximate genomic locations. Additionally, a new locus (qPH8-1) was found to be associated with plant height on chromosome 8 that could not be detected using the SNP-based GWAS. ConclusionsOur results demonstrate that the pangenome constructed by our pipeline combined with PAV-based GWAS can provide additional power for genomic and genetic analysis. The pangenome constructed in this study and associated genome sequence data provide valuable genomic resources for future rice crop improvement.

genetics↗

bioRxiv2022

Macroscale Adipose Tissue from Cellular Aggregates: A Simplified Method of Mass Producing Cell-Cultured Fat for Food Applications

We present a method of producing bulk cell-cultured fat tissue for food applications. Mass transport limitations (nutrients, oxygen, waste diffusion) of macroscale 3D tissue culture are circumvented by initially culturing murine or porcine adipocytes in 2D, after which bulk fat is produced by mechanically harvesting and aggregating the lipid-filled adipocytes into 3D fats using alginate or transglutaminase binders. The 3D fats were visually similar to fat tissue harvested from animals, with matching textures based on uniaxial compression tests. The mechanical properties of cultured fat tissues were based on binder choice and concentration, and changes in the fatty acid compositions of cellular triacylglyceride and phospholipids were observed after lipid supplementation (soybean oil) during in vitro culture. This approach of aggregating individual adipocytes into a bulk 3D tissue provides a scalable and versatile strategy to produce cultured fat tissue for food-related applications, thereby addressing a key obstacle in cultivated meat production. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/495192v3_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@148ac5eorg.highwire.dtl.DTLVardef@2c8f94org.highwire.dtl.DTLVardef@186553aorg.highwire.dtl.DTLVardef@458c09_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2022

Cross-modal Graph Contrastive Learning with Cellular Images

Constructing discriminative representations of molecules lies at the core of a number of domains such as drug discovery, material science, and chemistry. State-of-the-art methods employ graph neural networks (GNNs) and self-supervised learning (SSL) to learn the structural representations from unlabeled data, which can then be fine-tuned for downstream tasks. Albeit powerful, these methods that are pre-trained solely on molecular structures cannot generalize well to the tasks involved in intricate biological processes. To cope with this challenge, we propose using high-content cell microscopy images to assist in learning molecular representation. The fundamental rationale of our method is to leverage the correspondence between molecular topological structures and the caused perturbations at the phenotypic level. By including cross-modal pre-training with different types of contrastive loss functions in a unified framework, our model can efficiently learn generic and informative representations from cellular images, which are complementary to molecular structures. Empirical experiments demonstrated that the model transfers non-trivially to a variety of downstream tasks and is often competitive with the existing SSL baselines, e.g., a 15.4% absolute Hit@10 gains in graph-image retrieval task and a 4.0% absolute AUC improvements in clinical outcome predictions. Further zero-shot case studies show the potential of the approach to be applied to real-world drug discovery.

bioinformatics↗

bioRxiv2022

TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction

Illuminating interactions between proteins and small drug molecules is a longstanding challenge in the field of drug discovery. Despite the importance of understanding these interactions, most previous works are limited by hand-designed scoring functions and insufficient conformation sampling. The recently-proposed graph neural network-based methods provides alternatives to predict protein-ligand complex conformation in a one-shot manner. However, these methods neglect the geometric constraints of the complex structure and weaken the role of local functional regions. As a result, they might produce unreasonable conformations for challenging targets and generalize poorly to novel proteins. In this paper, we propose Trigonometry-Aware Neural networKs for binding structure prediction, TANKBind, that builds trigonometry constraint as a vigorous inductive bias into the model and explicitly attends to all possible binding sites for each protein by segmenting the whole protein into functional blocks. We construct novel contrastive losses with local region negative sampling to jointly optimize the binding interaction and affinity. Extensive experiments show substantial performance gains in comparison to state-of-the-art physics-based and deep learning-based methods on commonly-used benchmark datasets for both binding structure and affinity predictions with variant settings.

biophysics↗

bioRxiv2022

Respiratory mucosal vaccination of peptide-poloxamine-DNA nanoparticles provides complete protection against lethal SARS-CoV-2 challenge

The ongoing SARS-CoV-2 pandemic represents a brutal reminder of the continual threat of mucosal infectious diseases. Mucosal immunity may provide robust protection at the predominant sites of SARS-CoV-2 infection. However, it remains unclear whether respiratory mucosal administration of DNA vaccines could confer protective immune responses against SARS-CoV-2 challenge due to the insurmountable barriers posed by the airway. Here, we applied self-assembled peptide-poloxamine nanoparticles with mucus-penetrating properties for pulmonary inoculation of a COVID-19 DNA vaccine (pSpike/PP-sNp). Not only displays the pSpike/PP-sNp superior gene-transfection and favorable biocompatibility in the mouse airway, but pSpike/PP-sNp promotes a tripartite immunity consisting of systemic, cellular and mucosal immune responses that are characterized by mucosal IgA secretion, high levels of neutralizing antibodies, and resident memory phenotype T-cell responses in the lungs of mice. Most importantly, pSpike/PP-sNp completely eliminates SARS-CoV-2 infection in both upper and lower respiratory tracts and enables 100% survival rate of mice following lethal SARS-CoV-2 challenge. Our findings indicate PP-sNp might be a promising platform in mediating DNA vaccines to elicit all-around mucosal immunity against SARS-CoV-2.

immunology↗

bioRxiv2022

Single-cell perspectives on the function and development of deep-sea mussel bacteriocytes

The authors have withdrawn their manuscript because the authors need to re-organize the data and writing, meanwhile more experimental evidence from more RNA-seq replications, immunofluorescence assay and in vivo knock-down assays will be added to support the viewpoints. In this preprint, only one individual of decolonized mussel was employed for transcriptome sequencing while combined data from single cell transcriptomics with in situ hybridization is not enough convincing to draw some of the conclusion. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

molecular biology↗

bioRxiv2022

MADET: A Manually Curated Knowledgebase for Microbiomic Effects on Efficacy and Toxicity of Anticancer Treatments

A plethora of studies have reported the associations between microbiota and multiple diseases, leading to at least four databases to demonstrate microbiota-disease associations, i.e., gutMDisorder, mBodyMap, GMrepo and Amadis. Moreover, gut microbiota also mediates drug efficacy and toxicity, whereas a comprehensive database to elucidate the microbiota-drug associations is lacking. Here we report an open-access knowledgebase, MADET (Microbiomics of Anticancer Drug Efficacy and Toxicity), which harbors 453 manually annotated microbiota-drug associations from 24 papers. MADET provides user-friendly functions allowing users to freely browse, search, and download the data conveniently from the database. Users can customize their search filters in MADET using different types of keywords, including bacterial name (e.g., Akkermansia muciniphila), anticancer treatment (e.g., anti-PD-1 therapy) or cancer type (e.g., lung cancer) with different types of experimental evidence of microbiota-drug association and causation. We have also enabled user submission to further enrich the data document in MADET. The MADET database is freely available at https://www.madet.info. We anticipate that MADET will serve as a useful resource for a better understanding of the microbiota-drug associations and facilitate the future development of novel biomarkers and live biotherapeutic products for anticancer therapies.

microbiology↗