Biology subjects

Guan, L.

Publications and source records attributed to Guan, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Phage CRISPR-like regulatory RNAs silence bacterial adaptive and innate immunity

CRISPR RNAs (crRNAs) encoded by CRISPR arrays direct Cas nucleases against viruses. Some CRISPR-Cas loci also contain mini-arrays encoding crRNA-like RNAs (crlRNAs), which modulate transcription of cas or associated toxin genes that safeguard CRISPR-Cas activity. Here, we report that phages hijack these host crlRNA regulatory circuits to suppress bacterial immunity. Viral crlRNAs compete with host crRNAs for Cas protein binding and reprogram Cas proteins to silence their own expression or suppress transcription of CRISPR-safeguarding toxins. These anti-defense crlRNAs are found across diverse phages and plasmids, frequently organized into multiplexed transcriptional units resembling CRISPR arrays, and often synergize with co-encoded anti-CRISPR proteins to disable hierarchical host immune responses. Furthermore, we demonstrate that these compact viral crlRNA architectures can be harnessed for efficient mammalian genome editing. Our findings uncover widespread viral hijacking of host Cas proteins via crlRNAs, highlighting the recurrent exaptation of CRISPR-Cas regulatory functions to counter multilayered bacterial immune defenses.

microbiology↗

bioRxiv2024

Partially characterized topology guides reliable anchor-free scRNA integration

Single-cell RNA sequencing (scRNA-seq) is an important technique for obtaining biological insights at cellular resolution, with scRNA-seq batch integration a key step before downstream statistical analysis. Despite the plethora of methods proposed, achieving reliable batch correction while preserving the heterogeneity of biological signals that define cell type continues to pose a challenge, with existing methods performance varying significantly across different scenarios and datasets. To address this, we propose scCRAFT, an autoencoder model designed to segregate cell-type-related biological signals from batch effects for reliable multi-batch scRNA-seq integration. scCRAFT comprises three key loss components: a reconstruction loss that targets observation reconstruction, a multi-domain adaptation loss aimed at eliminating batch effects, and an innovative dual-resolution triplet loss for preserving topology within each batch, which is introduced as an effective mechanism to counteract the over-correction effect of domain adaptation loss amid heterogeneous cell distributions across batches. We show that scCRAFT effectively manages unbalanced batches, rare cell types, and batch-specific cell phenotypes in simulations, and surpasses state-of-the-art methods in a diverse set of real datasets.

bioinformatics↗

bioRxiv2024

Building a literature knowledge base towards transparent biomedical AI

As artificial intelligence (AI) continues to advance and scale up in biomedical research, concerns about AIs trustworthiness and transparency have grown. There is a critical need to systematically bring accurate and relevant biomedical knowledge into AI applications for transparency and provenance. Knowledge graphs have emerged as a powerful tool that integrates heterogeneous knowledge by explicitly describing biomedical knowledge as entities and relationships between entities. However, PubMed, the largest and most comprehensive repository of biomedical knowledge, exists primarily as unstructured text and is under utilized for advanced machine learning tasks. To address the challenge, we developed LiteralGraph, a computational framework to extract biomedical terms and relationships from PubMed literature into a unified knowledge graph. Using this framework, we established the Genomic Literature Knowledge Base (GLKB), which consolidates 14,634,427 biomedical relationships between 3,276,336 biomedical terms from over 33 million PubMed abstracts and nine well-established biomedical repositories. The database is coupled with RESTful APIs and a user-friendly web interface that makes it accessible to researchers for various usages. We demonstrated the broad utility of GLKB towards transparent AI in three distinct application scenarios. In the LLM grounding scenario, we developed a Retrieval Augmented Generation (RAG) agent to reduce LLM hallucination in biomedical question answering. In the hypothesis generation scenario, we elucidated the potential functions of RFX6 in type 2 diabetes (T2D) using the vast evidence from PubMed articles. In the machine learning scenario, we utilized GLKB to provide semantic knowledge in predictive tasks and scientific fact-checking.

bioinformatics↗

bioRxiv2024

PSMA-specific CAR-engineered macrophages for therapy of prostate cancer

Chimeric antigen receptor (CAR)-modified macrophages (CAR-Ms) are a promising approach for the treatment of solid tumors due to its high infiltration and immune-regulation activity. Prostate cancer is a typical solid tumor associated with highly immunosuppressive microenvironment. To date, the potential application of CAR-M cell therapy in prostate cancer has been infrequently explored. The prostate-specific membrane antigen (PSMA) functions as a specific biomarker for prostate cancer. In this study, we assessed the antitumor efficacy of PSMA-targeted CAR-Ms in preclinical models. CAR-Ms were engineered to express a PSMA-specific single-chain variable fragment (scFv) and co-stimulatory domains. In vitro data demonstrated specific cytotoxicity of CAR-Ms against PSMA-expressing prostate cancer cells, which was further supported by transcriptome analysis demonstrating the pro-inflammatory phenotypes of CAR-Ms. In vivo studies using xenograft mouse models confirmed significant tumor regression after administration of PSMA-targeted CAR-Ms compared to controls. Histopathological analysis showed infiltration of CAR-Ms into tumor tissues without off-target toxicity. These results highlight the strong antitumor activity and safety of PSMA-targeted CAR-Ms, supporting their potential as a new immunotherapy for prostate cancer.

bioengineering↗

bioRxiv2024

Putting computational models of immunity to the test - an invited challenge to predict B. pertussis vaccination outcomes

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting B. pertussis booster responses and generate experimental data for the explicit purpose of model evaluation. We here describe our second computational prediction challenge using this resource, where we benchmarked 49 algorithms from 53 scientists. We found that the most successful models stood out in their handling of nonlinearities, reducing large feature sets to representative subsets, and advanced data preprocessing. In contrast, we found that models adopted from literature that were developed to predict vaccine antibody responses in other settings performed poorly, reinforcing the need for purpose-built models. Overall, this demonstrates the value of purpose-generated datasets for rigorous and open model evaluations to identify features that improve the reliability and applicability of computational models in vaccine response prediction.

immunology↗

bioRxiv2024

Atomic-Level Free Energy Landscape Reveals Cooperative Symport Mechanism of Melibiose Transporter

The Major Facilitator Superfamily (MFS) transporters are an essential class of secondary active transporters involved in various physiological and pathological processes. The melibiose permease (MelB), which catalyzes the stoichiometric symport of the disaccharide melibiose and monovalent cations (e.g., Na+, H+, or Li+), is a key model for understanding the cation-coupled symport mechanisms. Extensive experimental data has established that positive cooperativity between the cargo melibiose and the coupling cation is central to the symport mechanism. However, the structural and energetic origins of this cooperativity remain unclear at the atomistic level for MelB and most other coupled transporters. Here, leveraging recently resolved structures in inward- and outward-facing conformations, we employed the string method and replica-exchange umbrella sampling simulation techniques to comprehensively map the all-atom free energy landscapes of the Na+-coupled melibiose translocation across the MelB in Salmonella enterica serovar Typhimurium (MelBSt), in comparison with the facilitated melibiose transport in a uniporter mutant. The simulation results unravel asymmetrical free energy profiles of melibiose translocation, which is tightly coupled to protein conformational changes in both the N- and C-terminal domains. Notably, the cytoplasmic release of the melibiose induces the simultaneous opening of an inner gate, resulting in a high-energy state of the system. Periplasmic sugar binding and cytoplasmic melibiose released are dynamically coupled with changes in the internal gating elements along the translocation pathway. The outward-facing sugar-bound state is thermodynamically most stable, while the occluded state is a transient state. The binding of Na+ facilitates melibiose translocation by increasing the melibiose-binding affinity and decreasing the overall free energy barrier and change. The cooperative binding of the two substrates results from the allosteric coupling between their binding sites instead of direct electrostatic interaction. These findings add substantial new atomic-level details into how Na+ binding facilitates melibiose translocation and deepen the fundamental understanding of the molecular basis underlying the symport mechanism of cation-coupled transporters.

biophysics↗

bioRxiv2024

Gut metagenomes of Asian octogenarians reveal metabolic potential expansion and distinct microbial species associated with aging phenotypes

While rapid demographic changes in Asia are driving the incidence of chronic diseases related to aging, the limited availability of high-quality in vivo data hampers our ability to understand complex multi-factorial contributions, including gut microbial, to healthy aging. Leveraging the availability of a well-phenotyped cohort of community-living octogenarians in Singapore, we used deep shotgun metagenomic sequencing to do high-resolution taxonomic and functional characterization of their gut microbiomes (n=234). Joint species-level analysis with other Asian cohorts identified a distinct age-associated shift in Asian gut metagenomes, characterized by a reduction in microbial richness, and enrichment of specific Alistipes and Bacteroides species (e.g. Alistipes shahii and Bacteroides xylanisolvens). Functional pathway analysis confirmed that these changes correspond to a metabolic potential expansion in aging towards alternate pathways that synthesize and utilize amino-acid precursors, relative to the dominant microbial guilds that typically produce butyrate in the gut from pyruvate (e.g. Faecalibacterium prausnitzii, Roseburia inulinivorans). Extending these observations to key clinical markers helped identify >10 robust gut microbial associations to inflammation, cardiometabolic and liver health, including potential probiotic species such as Parabacteroides goldsteinii and pathobionts such as Klebsiella pneumoniae, highlighting the role of the microbiome as biomarkers and potential intervention targets for promoting healthy aging.

genomics↗

bioRxiv2024

RUNX1 Isoforms Regulate RUNX1 and Target-Genes Differentially in Platelets-Megakaryocytes: Association with Clinical Cardiovascular Events

BackgroundHematopoietic transcription factor RUNX1 is expressed from proximal P2 and distal P1 promoter to yield isoforms RUNX1 B and C, respectively. The roles of these isoforms in RUNX1 autoregulation and downstream-gene regulation in megakaryocytes and platelets are unknown. ObjectivesTo understand the regulation of RUNX1 and its target genes by RUNX1 isoforms. MethodsWe performed studies on RUNX1 isoforms in megakaryocytic HEL cells and HeLa cells (lack endogenous RUNX1), in platelets from 85 healthy volunteers administered aspirin or ticagrelor, and on the association of RUNX1 target genes with acute events in 587 patients with cardiovascular disease (CVD). ResultsIn chromatin immunoprecipitation and luciferase promoter assays, RUNX1 isoforms B and C bound and regulated P1 and P2 promoters. In HeLa cells RUNX1B decreased and RUNX1C increased P1 and P2 activities, respectively. In HEL cells, RUNX1B overexpression decreased RUNX1C and RUNX1A expression; RUNX1C increased RUNX1B and RUNX1A. RUNX1B and RUNX1C regulated target genes (MYL9, F13A1, PCTP, PDE5A and others) differentially in HEL cells. In platelets RUNX1B transcripts (by RNAseq) correlated negatively with RUNX1C and RUNX1A; RUNX1C correlated positively with RUNX1A. RUNX1B correlated positively with F13A1, PCTP, PDE5A, RAB1B, and others, and negatively with MYL9. In our previous studies, RUNX1C transcripts in whole blood were protective against acute events in CVD patients. We found that higher expression of RUNX1 targets F13A1 and RAB31 associated with acute events. ConclusionsRUNX1 isoforms B and C autoregulate RUNX1 and regulate downstream genes in a differential manner and this associates with acute events in CVD. Scientific categoryPlatelets EssentialsO_LIRUNX1 is expressed from 2 promoters (P1 and P2) to yield isoforms RUNX1C and RUNX1B. C_LIO_LIRUNX1B and RUNX1C regulate RUNX1 and target genes differentially in megakaryocytes/platelets. C_LIO_LIIn platelets RUNX1B and RUNX1C expression is inversely related and ticagrelor increases RUNX1C C_LIO_LIRUNX1 target gene (F13A1, RAB31) expression in blood is associated with death or MI in cardiac disease. C_LI

cell biology↗

bioRxiv2024

FLIGHTED: Inferring Fitness Landscapes from Noisy High-Throughput Experimental Data

Machine learning (ML) for protein design requires large protein fitness datasets generated by high-throughput experiments for training, fine-tuning, and benchmarking models. However, most models do not account for experimental noise inherent in these datasets, harming model performance and changing model rankings in benchmarking studies. Here we develop FLIGHTED, a Bayesian method of accounting for uncertainty by generating probabilistic fitness landscapes from noisy high-throughput experiments. We demonstrate how FLIGHTED can improve model performance on two categories of experiments: single-step selection assays, such as phage display and SELEX, and a novel high-throughput assay called DHARMA that ties activity to base editing. We then compare the performance of standard machine-learning models on fitness landscapes generated with and without FLIGHTED. Accounting for noise significantly improves model performance, especially of CNN architectures, and changes relative rankings on numerous common benchmarks. Based on our new benchmarking with FLIGHTED, data size, not model scale, currently appears to be limiting the performance of protein fitness models, and the choice of top model architecture matters more than the protein language model embedding. Collectively, our results indicate that FLIGHTED can be applied to any high-throughput assay and any machine learning model, making it straightforward for protein designers to account for experimental noise when modeling protein fitness.

bioinformatics↗

bioRxiv2024

Distinct roles of the major binding residues in the cation-binding pocket of MelB

Salmonella enterica serovar Typhimurium melibiose permease (MelBSt) is a prototype of the major facilitator superfamily (MFS) transporters, which play important roles in human health and diseases. MelBSt catalyzed the symport of galactosides with either H+, Li+, or Na+, but prefers the coupling with Na+. Previously, we determined the structures of the inward- and outward-facing conformation of MelBSt, as well as the molecular recognition for galactoside and Na+. However, the molecular mechanisms for H+- and Na+-coupled symport still remain poorly understood. We have solved two x-ray crystal structures of MelBSt cation-binding site mutants D59C at an unliganded apo-state and D55C at a ligand-bound state, and both structures display the outward-facing conformations virtually identical as published previously. We determined the energetic contributions of three major Na+-binding residues in cation selectivity for Na+ and H+ by the free energy simulations. The D55C mutant converted MelBSt to a solely H+-coupled symporter, and together with the free-energy perturbation calculation, Asp59 is affirmed to be the sole protonation site of MelBSt. Unexpectedly, the H+-coupled melibiose transport with poor activities at higher {Delta}pH and better activities at reversal {Delta}pH was observed, supporting that the membrane potential is the primary driving force for the H+-coupled symport mediated by MelBSt. This integrated study of crystal structure, bioenergetics, and free energy simulations, demonstrated the distinct roles of the major binding residues in the cation-binding pocket.

biophysics↗

bioRxiv2023

A genome-wide association study of neonatal metabolites

The hereditary component significantly influences the concentration of metabolites in adults. Nevertheless, the precise influence of genetic factors on neonatal metabolites remains uncertain. To bridge this gap, we employed genotype imputation techniques on large-scale low-pass genome data obtained from non-invasive prenatal testing. Subsequently, we conducted association studies on a total of 75 metabolic components in neonates. The study identified a total 17 previous reported associations and 13 novel discovered associations between single nucleotide polymorphisms and metabolic components. These associations were initially found in the discovery cohort (8,744 participants) and subsequently confirmed in a replication cohort (19,041 participants). The average heritability of metabolic components was calculated to be 76.2%, with a range of 69-78.8%. The aforementioned findings offer valuable insights pertaining to the genetic architecture of neonatal metabolism. In BriefLarge-scale genomes of maternal non-invasive prenatal testing provide insights into the genetic contribution to neonatal metabolism. HighlightsGWAS of 27,785 low-pass genomes revealed 13 novel associations of neonatal metabolic components. Estimated an average of 76.2% heritability of neonatal metabolic components and showed the individual concentration can be accurately predicted from polygenic risk scores. A total of 17 established relationships have been observed, providing evidence that maternal genomes can be utilized in neonatal metabolite GWAS.

genetics↗

bioRxiv2023

Leveraging genetic correlations and multiple populations to improve genetic risk prediction for non-European populations

Genetic prediction accuracy for non-European populations is hindered by the limited sample size of Genome-wide association studies (GWAS) data in these populations. Additionally, it is challenging to tune model parameters with a small tuning dataset for methods that require tuning data, which is often the case for non-European samples. To address these challenges, we propose JointPRS, a novel, data-adaptive framework that simultaneously models multiple populations using GWAS summary statistics. JointPRS incorporates genetic correlation structures into the prediction framework, enabling accurate performance even without individual-level tuning data. Additionally, it uniquely employs a data-adaptive approach, providing a robust solution when only a small tuning dataset is available. Through extensive simulations and real data applications to 22 quantitative traits and four binary traits in five continental populations (European (EUR); East Asian (EAS); African (AFR); South Asian (SAS); and Admixed American (AMR)) evaluated using the UK Biobank (UKBB) and All of Us (AoU), we demonstrate that JointPRS outperforms six other state-of-art methods across three different data scenarios (no tuning data, tuning and testing data from the same cohort, and tuning and testing data from different cohorts) for most traits in non-European populations, while maintaining model simplicity and computational efficiency.

genetics↗

bioRxiv2023

Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with [≥]2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

genomics↗

bioRxiv2023

De novo generation of antibody CDRH3 with a pre-trained generative large language model

Artificial Intelligence (AI) techniques have made great advances in assisting antibody design. However, antibody design still heavily relies on isolating antigen-specific antibodies from serum, which is a resource-intensive and time-consuming process. To address this issue, we propose a Pre-trained Antibody generative large Language Model (PALM) for the de novo generation of artificial antibodies heavy chain complementarity-determining region 3 (CDRH3) with desired antigen-binding specificity, reducing the reliance on natural antibodies. We also build a high-precision model antigen-antibody binder (A2binder) that pairs antigen epitope sequences with antibody sequences to predict binding specificity and affinity. PALM-generated antibodies exhibit binding ability to SARS-CoV-2 antigens, including the emerging XBB variant, as confirmed through in-silico analysis and in-vitro assays. The in-vitro assays validated that PALM-generated antibodies achieve high binding affinity and potent neutralization capability against both wild-type and XBB spike proteins of SARS-CoV-2. Meanwhile, A2binder demonstrated exceptional predictive performance on binding specificity for various epitopes and variants. Furthermore, by incorporating the attention mechanism into the PALM model, we have improved its interpretability, providing crucial insights into the fundamental principles of antibody design.

bioinformatics↗

bioRxiv2023

Spatial transcriptomics of peach and nectarine elucidates the mechanism underlying fruit trichome development

Peach (Prunus persica) is an economically significant fruit-bearing tree. The trichomes of peach fruits are essential for their growth and development by playing a protective role against abiotic stresses, such as intense ultraviolet (UV) light, high temperature, cold-induced stress, and biotic stresses, such as pests and disease infestation. However, the mechanism underlying trichome development in peach fruits is unknown. Therefore, spatial transcriptome sequencing technology was used to compare the transcriptomic information seven days after flowering (DAF) of peach and nectarine fruits at an ultra-high resolution. The results revealed significant variations in how fruits at the early development stage responded to stress exposure. Comparatively, nectarine response to stress was significantly magnified than peach. Notably, a novel trichome-related marker gene, Prupe.7G196500, was identified in peach, which showed a robust function in response to jasmonic acid and wounding. Further, the Prupe.7G196500pro::GUS construct was found to specifically expressed in the trichomes of the true leaves of 10-day-old Arabidopsis thaliana (Arabidopsis) seedlings and induced by drought treatment. Finally, gain-of-function analysis showed that Prupe.7G196500 promoted trichomes development. In conclusion, this study identified the cell types and novel marker genes associated with peach fruit. The role of Prupe.7G196500 in positively regulating trichome development was also characterized, thereby laying the foundation for analyzing the mechanism involved in trichome development in peach fruits.

developmental biology↗

bioRxiv2023

Mimicking the regulatory state of a major facilitator superfamily sugar transporter

While many 3D structures of cation-coupled transporters have been determined, the mechanistic details governing the obligatory coupling and functional regulations still remain elusive. The bacterial melibiose transporter (MelB) is a prototype of the Na+-coupled major facilitator superfamily transporters. With a conformational nanobody (Nb), we determined a low-sugar affinity inward-facing Na+-bound cryoEM structure. Collectively with the available outward-facing sugar-bound structures, both the outer and inner barriers were localized. The N-and C-terminal residues of the inner barrier contribute to the sugar selectivity pocket. When the inner barrier is broken as shown in the inward-open conformation, the sugar selectivity pocket is also broken. The binding assays by isothermal titration calorimetry revealed that this inward-facing conformation trapped by the conformation-selective Nb exhibited a greatly decreased sugar-binding affinity, suggesting the mechanisms for the substrate intracellular release and accumulation. While the inner/outer barrier shift directly regulates the sugar-binding affinity, it has little or no effect on the cation binding, which is also supported by molecular dynamics simulations. Furthermore, the use of this Nb in combination with the hydron/deuterium exchange mass spectrometry allowed us to identify dynamic regions; some regions are involved in the functionally important inner barrier-specific salt-bridge network, which indicates their critical roles in the barrier switching mechanisms for transport. These complementary results provided structural and dynamic insights into the mobile barrier mechanism for cation-coupled symport.

molecular biology↗

bioRxiv2023

A systems vaccinology resource to develop and test computational models of immunity

Computational models that predict an individuals response to a vaccine offer the potential for mechanistic insights and personalized vaccination strategies. These models are increasingly derived from systems vaccinology studies that generate immune profiles from human cohorts pre- and post-vaccination. Most of these studies involve relatively small cohorts and profile the response to a single vaccine. The ability to assess the performance of the resulting models would be improved by comparing their performance on independent datasets, as has been done with great success in other areas of biology such as protein structure predictions. To transfer this approach to system vaccinology studies, we established a prototype platform that focuses on the evaluation of Computational Models of Immunity to Pertussis Booster vaccinations (CMI-PB). A community resource, CMI-PB generates experimental data for the explicit purpose of model evaluation, which is performed through a series of annual data releases and associated contests. We here report on our experience with the first such dry run for a contest where the goal was to predict individual immune responses based on pre-vaccination multi-omic profiles. Over 30 models adopted from the literature were tested, but only one was predictive, and was based on age alone. The performance of new models built using CMI-PB training data was much better, but varied significantly based on the choice of pre-vaccination features used and the model building strategy. This suggests that previously published models developed for other vaccines do not generalize well to Pertussis Booster vaccination. Overall, these results reinforced the need for comparative analysis across models and datasets that CMI-PB aims to achieve. We are seeking wider community engagement for our first public prediction contest, which will open in early 2024.

systems biology↗

bioRxiv2023

Therapeutic effect of dietary interventions on senescence in animals and humans: A systematic review

BackgroundCellular senescence is a permanent state of cell cycle arrest and has been regarded as a therapeutic target for ageing and age-related diseases. Several senotherapeutic agents have been proposed, including compounds derived from natural products which hold the translational potential to promote healthy ageing. It is largely unclear whether cellular senescence could be targeted by dietary interventions. This systematic review examined diets and dietary ingredients and their association with cellular senescence load in animal models and humans, with an intent to identify dietary interventions with senotherapeutic potential. MethodsThe databases PubMed and Embase were systematically searched for key terms related to cellular senescence, senescence markers, diets, nutrients and bioactive compounds. Intervention and observational studies on human and animal models investigating the effects of diets or dietary ingredients via oral administration on cellular senescence load were included. The studies were screened using the Covidence systematic review software. Study design, methods and results were extracted. Biomaterials used for senescence detection were categorized into physiological systems. The SYRCLEs risk of bias tool and Cochrane risk of bias tool v2.0 were used to assess the risk of bias for animal and human studies respectively. ResultsOut of 5707 identified articles, 82 articles consisting of 78 animal studies and 4 human studies aimed to reduce cellular senescence load using dietary interventions. In animal studies, the most-frequently used senescence model was normal ageing (26 studies), followed by D- galactose-induced models (17 studies). Resveratrol (8 studies), vitamin E (4 studies) and soy protein isolate (3 studies) showed positive effects on reducing the level of senescence markers such as p53, p21, p16 and senescence-associated {beta}-galactosidase in various tissues of physiological systems. In three out of four human studies, ginsenoside Rg1 had no positive effect on reducing senescence in muscle tissues after exercise. The risk of bias for both animal and human studies was largely unclear. ConclusionResveratrol, vitamin E and soy protein isolate are promising senotherapeutics studied in animal models. Studies testing dietary interventions with senotherapeutic potential in humans are limited and translation is highly warranted.

cell biology↗