bioRxiv Science⌕ Search

Biology subjects

Li, S.

Publications and source records attributed to Li, S..

At least 523 records · Page 29Linked to original sources

AI-enabled Alkaline-resistant Evolution of Protein to Apply in Mass Production

Artificial intelligence (AI) models have been used to study the compositional regularities of proteins in nature, enabling it to assist in protein design to improve the efficiency of protein engineering and reduce manufacturing cost. However, in industrial settings, proteins are often required to work in extreme environments where they are relatively scarce or even non-existent in nature. Since such proteins are almost absent in the training datasets, it is uncertain whether AI model possesses the capability of evolving the protein to adapt extreme conditions. Antibodies are crucial components of affinity chromatography, and they are hoped to remain active at the extreme environments where most proteins cannot tolerate. In this study, we applied an advanced large language model (LLM), the Pro-PRIME model, to improve the alkali resistance of a representative antibody, a VHH antibody capable of binding to growth hormone. Through two rounds of design, we ensured that the selected mutant has enhanced functionality, including higher thermal stability, extreme pH resistance and stronger affinity, thereby validating the generalized capability of the LLM in meeting specific demands. To the best of our knowledge, this is the first LLM-designed protein product, which is successfully applied in mass production.

bioinformatics↗

Coat protein of TCV suppresses RNA decay via ubiquitination and autophagy pathways to facilitate viral infection

Highlight statementThe findings highlight that TCV manipulates 26S proteasome and autophagy pathways to obstruct antiviral RNA decay defenses and ultimately enhance its ability to infect host cells. RNA decay is a pervasive process in eukaryotic cells. Viruses utilize the host cells intracellular machinery to gain access to essential molecules and subcellular structures required for infection during the pathogenesis process. The study demonstrates that turnip crinkle virus (TCV) infection enhances the expression of Arabidopsis Dcp1 (AtDcp1), which negatively regulates the accumulation of TCV RNA, indicating its involvement in antiviral defense. Nevertheless, TCV circumvents the antiviral defense based on RNA decay, as indicated by the capsid protein (CP) of TCV stabilizing the known nonsense-mediated RNA decay targeted transcripts. In vivo, CP physically interacts with AtDcp1, promoting AtDcp1 degradation via ubiquitination and autophagy pathways. This is evidenced by the observation that the degradation is inhibited by both 26S proteasome and autophagy inhibitors. Furthermore, CP elevates the polyubiquitination of Dcp1-Flag and the quantity of pre-autophagosome or autophagosome structures. These data indicate that CP suppresses RNA decay by interacting with AtDcp1 and mediating its degradation through the 26S proteasome and autophagy pathways, effectively subduing antiviral RNA decay. This study uncovers a previously unidentified virulence strategy in the ongoing conflict between plants and viruses.

pathology↗

Switchable Conformation in Protein Subunits: Unveiling Assembly Dynamics of Icosahedral Viruses

The packaging of genetic material within a protein shell, called the capsid, marks a pivotal step in the life cycle of numerous single-stranded RNA viruses. Understanding how hundreds, or even thousands, of proteins assemble around the genome to form highly symmetrical structures remains an unresolved puzzle. In this paper, we design novel subunits and develop a model that enables us to explore the assembly pathways and genome packaging mechanism of icosahedral viruses, which were previously inaccessible. Using molecular dynamics (MD) simulations, we observe capsid fragments, varying in protein number and morphology, assembling at different locations along the genome. Initially, these fragments create a disordered structure that later merges to form a perfect symmetric capsid. The model demonstrates remarkable strength in addressing numerous unresolved issues surrounding virus assembly. For instance, it enables us to explore the advantages of RNA packaging by capsid proteins over linear polymers. Our MD simulations are in excellent agreement with our experimental findings from small-angle X-ray scattering and cryo-transmission electron microscopy, carefully analyzing the assembly products of viral capsid proteins around RNAs with distinct topologies.

biophysics↗

Effect of fumarate and live yeast on methane emissions, rumen fermentation, blood metabolites, and lactation performance in dairy goats

The objective of this study was to evaluate the effects and combined effects of fumarate (32 g/d) and active dry yeast (ADY) (1.5 g/d) on methane emissions, rumen fermentation, microbial community and function, apparent total tract digestibility, blood metabolites, and lactation performance in 28 lactating goats using a randomized complete block design with a 2 x 2 factorial arrangement. Fumarate supplementation inhibited methane emission rates for 3 h post-feeding, while ADY increased the methane emission rates for 2 h pre-feeding, without combined effects between them. Fumarate increased the rumen pH and reduced total VFA concentration without changing the VFA profiles before feeding. Based on two custom dataset of 4,674 metagenome-assembled genomes and 7,758,615 nonredundant genes, neither fumarate nor live yeast influenced the rumen microbial community and function. The addition of fumarate reduced the concentrations of glucose, serum malondialdehyde (MDA), and ammonia in the serum, as well as the activity of insulin, while increasing the activity of serum malate dehydrogenase (MDH) and the levels of urea in both serum and milk. The addition of live yeast reduced serum glucose levels and increased serum MDA concentrations and MUN levels. There was a negative interaction between fumaric acid and live yeast on the levels of urea nitrogen in serum and milk. ConclusionsThe methane inhibition effect of fumaric acid persists for 3 h post-feeding, reflecting its retention or metabolism time in the rumen. Fumaric acid enhances the TCA cycle and the urea cycle in dairy goats, thereby improving energy utilization efficiency and reducing the risk of ammonia toxicity.

microbiology↗

Association Between Relational Mobility and DNA Methylation in Oxytocin Receptor Gene: A Social Epigenetic Study

DNA methylation is a type of epigenetic modification known to exhibit fluctuations in response to environmental factors. The association of macrosocial factors, such as interpersonal mobility, on methylation has seldom been investigated. This study aimed to examine the association of relational mobility, defined as the extent to which individuals can form and replace social relationships, on the DNA methylation of oxytocin receptor genes. DNA was extracted from the buccal cells of 95 adult participants (50 men and 45 women) and subjected to microarray analysis of DNA methylation using Illumina EPIC v2.0. The findings indicate that the oxytocin receptor genes methylation level was higher in individuals residing in low relational mobility social environments. The CpG site associated with relational mobility is an enhancer region, indicating that social environments with low relational mobility exert a suppressive effect on the transcriptional efficiency of the oxytocin receptor gene. Significance StatementThe association between DNA methylation of the oxytocin receptor gene and relational mobility was examined in 95 adults in their 20s to 60s, and found that those living in social environments with lower levels of relationship mobility had higher rates of DNA methylation of the oxytocin receptor gene. This study is a novel approach to a problem discussed in the social sciences using new analytical techniques in epigenomics.

genetics↗

Fc-independent SARS-CoV-2 infection-enhancing antibodies decouple N-terminal and receptor-binding domains by cross-linking neighboring spikes

Antibody dependent enhancement (ADE) is a serious concern in vaccine development. The canonical ADE pathways are dependent on the fragment crystallizable (Fc) region of the antibody. In SARS-CoV-2 several antibodies have been discovered that inflict ADE in vitro. These antibodies target the N-terminal domain (NTD) of the SARS-CoV-2 spike protein. We previously proposed that these NTD-targeting infection-enhancing antibodies (NIEAs) cross-link neighboring spike proteins via their NTDs, and that this results in a decoupling between the NTD and receptor binding domain (RBD), facilitating the "RBD down" to "up" transition. In this study we present a combination of molecular dynamics simulations and cryogenic electron microscopy data that, together, demonstrate that NIEAs are indeed able to cross-link neighboring SARS-CoV-2 spike proteins, and that this cross-linking results in a decoupling of the NTD and RBD domains. These findings provide support for an Fc region independent ADE pathway that is not only relevant for SARS-CoV-2 but also for other viruses of which the spike proteins undergo a conformational change upon host cell entry.

molecular biology↗

Multi-Modal Large Language Model Enables Protein Function Prediction

Predicting the functions of proteins can greatly accelerate biological discovery and applications, where deep learning methods have recently shown great potential. However, these methods predominantly predict protein functions as discrete categories, which fails to capture the nuanced and complex nature of protein functions. Furthermore, existing methods require the development of separate models for each prediction task, a process that can be both resource-heavy and time-consuming. Here, we present ProteinChat, a versatile, multi-modal large language model that takes a proteins amino acid sequence as input and generates comprehensive narratives describing its function. ProteinChat is trained using over 1,500,000 (protein, prompt, answer) triplets curated from the Swiss-Prot dataset, covering diverse functions. This novel model can universally predict a wide range of protein functions, all within a single, unified framework. Furthermore, ProteinChat supports interactive dialogues with human users, allowing for iterative refinement of predictions and deeper exploration of protein functions. Our experimental results, evaluated through both human expert assessment and automated metrics, demonstrate that ProteinChat outperforms general-purpose LLMs like GPT-4, one of the flagship LLMs, by over ten-fold. In addition, ProteinChat exceeds or matches the performance of task-specific prediction models.

bioinformatics↗

Low-cost and highly efficient generation of near-complete bacterial pathogen genomes by TELL-Seq

Recent evidences suggest that de novo genome assembly can provide additional insights into genomic variation landscape beyond short-read NGS analyses. Despite the advent of longread sequencing technologies, generating high-quality bacterial genome assemblies remains expensive and requires high-quality and large quantities of DNA. TELL-Seq, an emerging linked-read technology, has been reported as a low-cost alternative for producing nearcomplete genome assembly in certain bacterial species. However, a systematic assessment of its performance and characteristics in de novo bacterial genome assembly has not yet been conducted. To address this, we benchmarked TELL-Seq using a set of clinical and standard bacterial pathogens with a wide range of genome size (2.0 6.4 Mbp), GC-content (32% - 68%), genome complexity (mappability from 0.15 to 0.60) and Gram types. Our findings indicate that, with 1/6 cost and 1/15,000 of DNA compared to PacBio HiFi, TELL-Seq could generate as high quality near-complete bacterial genome assemblies. The optimal depth for assembly is around 200x, as increased depth improves contiguity and completeness, though quality plateaus at 250x. In general, genome complexity was significantly correlated with assembly quality, but GC-content was not. Nevertheless, genomes with extreme GC-content may require higher depths for accurate assembly. Our study suggests that TELL-Seq could be a scalable method for large-scale bacterial genomic surveys. The data generated from this study could serve as a benchmark dataset for further algorithm development. Impact StatementAn increasing body of literature have shown that de novo genome assembles could provide additional insights into genomic variation beyond standard short-read technologies. Its particularly useful in clinical and epidemiological studies of bacteria, due to high variable nature of their genomes. Although great advances have been made in long-read sequencing technology, its still expensive with high requirement over sample DNAs quality and quantity, limiting its adoption in large-scale studies or surveys. Linked-read technology is an inexpensive alternative which used single molecule barcoding to mark origin of reads for better scaffolding of contigs assembled from normal short reads. TELL-Seq, as one of these promising technologies, was reported to be able to inexpensively and efficiently generate near-complete bacterial de novo genomic assemblies with low DNA inputs. Theres not yet a systematic benchmarking of this technology in bacterial pathogens. In this study, a set of clinically important bacterial pathogens with a wide spectrum of GC-content, genome size, genome complexity, and Gram Type were used to investigate the performance of TELL-Seq technology in de novo genome assembly. We found that, with about 1/6 of cost and 1/15000 of DNA quantity, it could generate comparable de novo assemblies compared to standard reference genomes or PacBio HiFi assemblies, while beating conventional short-read assemblies. We found several key factors, such as genome complexity, and sequencing depth, which would impact the quality of the assembly. Our study suggests that a sequencing depth of 200x is sufficient to achieve satisfactory results. Our study has revealed characteristics of this technology in bacterial genome assembly and paved the way for its large-scale application in clinical or epidemiological surveys. Data SummaryO_LIRaw sequencing data for all isolates have been deposited to SRA, accessible through these NCBI BioProject PRJNA1133244. C_LIO_LIA full list of SRA BioSample accession numbers are available in Tab S5. C_LIO_LIAssemblies and analyses companion this paper is available at: https://github.com/x-lab/tellseq_bacteria C_LI

bioinformatics↗

SegFinder: an automated tool for identifying RNA virus genome segments through co-occurrence in multiple sequenced samples

Metagenomic sequencing has expanded the RNA virosphere, but many identified viral genomes remain incomplete, especially for segmented viruses. Traditional methods relying on sequence homology struggle to identify highly divergent segments and group them confidently within a single virus species. To address this, we developed a new bioinformatic tool - SegFinder - that identifies virus genome segments based on their common co-occurrence at similar abundance within segmented viruses. SegFinder successfully re-discovered all segments from a test data set of individual mosquito transcriptomes, which was also used to establish parameter thresholds for reliable segment identification. Using these optimal parameters, we applied SegFinder to 858 libraries from eight metagenomic sequencing projects, including vertebrates, invertebrates, plants, and environmental samples. Furthermore, we identified 108 (excluding RdRP) unique viral genome segments, of which 55 were novel and 32 showed no recognizable sequence homology to known sequences but which were verified by the presence of conserved sequences at the genome termini. SegFinder is also able to identify segmented genome structures in viruses previously considered to be predominantly unsegmented, and in doing so expanded the number of known families and orders of segmented RNA viruses, making it a valuable tool in an era of large-scale parallel sequencing.

bioinformatics↗

Insomnia score: predictive ability of insomnia, high-diagnostic and prognostic value for cancer.

ObjectiveThis study utilized bioinformatics methods to investigate the association between insomnia and cancer. MethodsWe identified key insomnia-related genes and constructed an insomnia score (riskScore = {sum} Expressiongene * Coefficient) based on an insomnia dataset using differential analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and Least Absolute Shrinkage and Selection Operator (LASSO) regression. The predictive ability of the insomnia score was validated in the insomnia dataset using Receiver Operating Characteristic (ROC) analysis. Finally, the diagnostic and prognostic value of the insomnia score was assessed in a pan-cancer cohort. ResultsDifferential analysis, WGCNA, and LASSO screening of the insomnia dataset yielded three key insomnia-related genes (PTMA, NLRP8, and CCBE1). An insomnia score was then constructed using the formula: riskScore = -0.8039667 * ExpressionPTMA + - 3.1975230 * ExpressionNLRP8 + -0.4957560 * ExpressionCCBE1. The ROC analysis demonstrated that the insomnia score has excellent predictive ability for insomnia. Furthermore, pan-cancer analysis illustrated the diagnostic and prognostic value of the insomnia score across various cancers. ConclusionWe successfully constructed an insomnia score and demonstrated its diagnostic and prognostic value in multiple cancers.

bioinformatics↗

The Changing Immune Landscape of Innate-like T Cells and Innate Cells Throughout Life

Spectral flow cytometry is an advanced immunological tool that enables comprehensive analysis of the immune system by simultaneously comparing innate and adaptive immune cells. Here, using a 40-colour antibody panel we advance our knowledge of innate and innate-like T cells by investigating chemokine receptors, activation and maturation markers not usually assessed on these populations and examine age-related effects to these immune cell subsets. We characterised phenotypic changes of peripheral blood mononuclear cells (PBMC) in three age groups: newborn (cord blood), adults aged 20-30 years, and adults aged 70-80 years, focusing on innate-like T cells and innate cells, including MAIT cells, NKT cells, {gamma}{delta} T cells, ILCs, and Natural Killer (NK) cells. We identify subsets of double-negative (DN) T cells (CD4- CD8-) and CD161+ T cells that increase in an age-related manner and exhibit a phenotype similar to innate-like T cells, MAIT cells and {gamma}{delta} T cells. Innate-like T cell subsets express similar patterns of the chemokine receptors and maturation markers CCR4, CCR6, CD27, CD38, CD57 and CD45RA, and resemble memory subsets of conventional CD4+ T cells and CD8+ T cells. We could detect ILCs in all age ranges, although the frequency of ILC1, ILC2, and ILC3 subsets decreased with age. Notably, we identify the NK maturation marker, CD57, as a universal marker that defines ageing populations of innate and adaptive immune cells. This study enhances our understanding of the ontogeny of human immune cells, highlighting significant age-related changes in the frequency and phenotype of immune cells.

immunology↗

A genetically engineered therapeutic lectin inhibits human influenza A virus infection and sustains robust virus-specific CD8 T cell expansion

Native banana lectin (BanLec) is antiviral but highly mitogenic, which limits its therapeutic value. In contrast, the genetically engineered H84T BanLec (H84T) is not mitogenic but remains effective against influenza A virus (IAV) infection in mouse models. However, the potency and effect of H84T on human immune cells and IAV-specific immune responses is undetermined. We found that H84T efficiently inhibited IAV replication in human dendritic cells (DCs) from blood and tonsils, which preserved DC viability and allowed acquisition and presentation of viral antigen. Consequently, H84T-treated DCs initiated effective expansion of IAV-specific CD8 T cells. Furthermore, H84T preserved the capacity of IAV-exposed DCs to present a second non-IAV antigen and induce robust CD8 T cell expansion. This supports H84T as a potent antiviral in humans as it effectively inhibits IAV infection without disrupting DC function, and preserves induction of antigen-specific adaptive immune responses against diverse antigens, which likely is clinically beneficial.

immunology↗

VIPER-TACs leverage viral E3 ligases for disease-specific targeted protein degradation

In targeted protein degradation (TPD) a protein of interest is degraded by chemically induced proximity to an E3 ubiquitin ligase. One limitation of using TPD therapeutically is that most E3 ligases have broad tissue expression, which can contribute to toxicity via target degradation in healthy cells. Many pathogenic and oncogenic viruses encode E3 ligases (vE3s), which de facto have strictly limited expression to diseased cells. Here, we provide proof-of-concept for Viral E3 Pan-Essential Removing Targeting Chimeras (VIPER-TACs) that are bi-functional molecules that utilize viral E3 ubiquitin ligases to selectively degrade pan-essential proteins and eliminate diseased cells. We find that the human papillomavirus (HPV) ligase E6 can degrade the SARS1 pan-essential target protein in a model of HPV-positive cervical cancer to selectively kill E6 expressing cancer cells. Thus, VIPER-TACs have the capacity to dramatically increase the therapeutic window, alleviate toxicity concerns, and ultimately expand the potential target space for TPD.

cancer biology↗

Introducing identification probability for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in context of the chemical space being considered, are easily automated, or are transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a reference library or chemical space that match to an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multi-property reference libraries constructed from the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

biochemistry↗

Efficient in situ epitope tagging of rice genes by nuclease-mediated prime editing

In situ epitope tagging is crucial for probing gene expression, protein localization, and the dynamics of protein interactions within their natural cellular context. However, the practical application of this technique in plants presents considerable hurdles. Here, we comprehensively explore the potential of the CRISPR/Cas nuclease-mediated prime editing and different DNA repair pathways in epitope tagging of endogenous rice genes. We find that SpCas9 nuclease/microhomology-mediated end joining (MMEJ)-based prime editing strategy (termed NM-PE) facilitates more straightforward and efficient gene tagging compared to the conventional and other derivative PE method. Furthermore, the PAM-flexible SpRY and ScCas9 nucleases-based prime editors have been engineered and implemented for the tagging of endogenous genes with diverse epitopes, significantly broadening the applicability of NM-PE in rice. Moreover, NM-PE has been successfully adopted in simultaneous tagging of OsMPK1 and OsMPK13 in rice plants with c-Myc and HA tags, respectively. Taken together, our results indicate great potential of the NM-PE toolkit in the targeted gene tagging for Rice Protein Tagging Project, gene function study and genetic improvement.

plant biology↗

Thermophilic Fungus Uses Anthraquinones to Modulate Ferrous Excretion, Sterol-Mediated Endocytosis and Iron Storage in Response to Cold Stress

To date, there is no real physiological mechanisms for iron excretion in eukaryote, and no physiological "actuator" that can control all the three fundamental biologic processes of absorption, storage and excretion. Here we observed that the accumulation of anthraquinones by Thermomyces dupontii under cold stress can achieve this process. Through mutation analysis, we found that mutant {Delta}An deficiency in anthraquinones accumulated ferrous and total free iron due to adopting a rare lifestyle with no endocytosis but accumulation of membrane-derived vesicles. Anthraquinone complement indicated that the vesicles in {Delta}An could coat the extrinsic anthraquinone-induced granules to prevent contact with the fungal interiors. Detailed chemical investigation on {Delta}An led to characterization of a rare oxygen-free ergosterene with unstable nature in air as the major membrane steroid in {Delta}An, suggesting hypoxia inner in {Delta}An cells, consistent with dramatically low oxygen-consuming rates in {Delta}An. A series of physiological and metabolic analysis indicated anthraquinones were involved in exporting ferrous and promoting formation of oxygen-containing metabolites, including ergosterols for endocytosis and iron chelators for iron storage. Moreover, we found that both the anticancer agent mitoxantrone with well know-cardiotoxicity side effect and the major terpenoid-derived polycyclic aromatics from Danshen for treating cardiovascular disease showed potent ferrous transporting capabilities in human cancer cells. Our findings provide a novel insight into the underlying mechanisms of polycyclic aromatics in nature and pharmacology, and offer new strategy for developing potential therapeutics and agents for membrane transport, iron homestasis and anticold. Graphical AbstractUp to now, regulation of iron homeostasis by metabolites have rarely been characterized. Moreover, no excretory mechanisms for iron in fungi have been reported. In this study, we found that Thermomyces dupontii can accumulate a large amount of anthraquinones under cold stress. The anthraquinones can release free ferric ion, reduce ferric to ferrous ions, and export ferrous ions, greatly enhancing thermophilic fungus to survive in the bio-system environment. Furthermore, lack of the anthraquinones can inhibit oxygen-dependent ergosterol mediated endocytosis, leading to an self-imposed isolation via oxygen-free ergosterene-mediated cell membranes. Importantly, the well known anthraquinone compound Mitoxantraquinone for anticancer and the main terpenoid polycyclic aromatic metabolites in traditional Chinese medicine Danshen for the treatment of cardiovascular diseases both exhibit strong ferrous ions transport capabilities. Our findings provided new insights for developing potential therapies and drugs for iron homeostasis and drug delivery. O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/605589v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@114551eorg.highwire.dtl.DTLVardef@1e03589org.highwire.dtl.DTLVardef@dad51borg.highwire.dtl.DTLVardef@dd0601_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

A nuclear RNA degradation code for eukaryotic transcriptome surveillance

The RNA exosome plays critical roles in eukaryotic RNA degradation, but it remains unclear how the exosome specifically recognizes its targets. The PAXT connection is an adaptor that recruits the exosome to polyadenylated RNAs in the nucleus, especially transcripts polyadenylated at intronic poly(A) sites. Here we show that PAXT-mediated RNA degradation is induced by the combination of a 5' splice site and a poly(A) junction, but not by either sequence alone. These sequences are bound by U1 snRNP and cleavage/polyadenylation factors, which in turn cooperatively recruit PAXT. As the 5' splice site-poly(A) junction combination is typically not found on correctly processed full-length RNAs, we propose that it functions as a "nuclear RNA degradation code" (NRDC). Importantly, disease-associated single nucleotide polymorphisms that create novel 5' splice sites in 3' untranslated regions can induce aberrant mRNA degradation via the NRDC mechanism. Together our study identified the first NRDC, revealed its recognition mechanism, and characterized its role in human diseases.

molecular biology↗

Satellite stem cell dysfunction in Duchenne muscular dystrophy

Satellite cells are muscle-resident stem cells that maintain and repair muscle. Increasing evidence supports the contributing role of satellite cells in Duchenne muscular dystrophy (DMD), a lethal degenerative muscle disease caused by loss of dystrophin. However, whether or not satellite cells exhibit dysfunction due to loss of dystrophin remains unresolved. Here, we used single cell RNA-sequencing (scRNA-seq) to determine how dystrophin deficiency impacts the satellite cell transcriptome and cellular composition by comparing satellite cells from mdx and the more severe D2-mdx DMD mouse models. DMD satellite cells were disproportionally found within myogenic progenitor clusters and a previously uncharacterized DMD enriched cluster. Despite exposure to different dystrophic environments, mdx and D2-mdx satellite cells exhibited overlapping dysregulation in gene expression and associated biological pathways. When comparing satellite stem cell versus myogenic progenitor populations, we identified unique dysfunctions between DMD and healthy satellite cells including apoptotic cell death and senescence, respectively. Pseudotime analyses revealed differences in cell fate trajectories indicating that DMD satellite cells are stalled in their differentiation capacity. In vivo regeneration assays confirmed that DMD satellite cells exhibit impaired myogenic gene expression and cell fate dynamics during regenerative myogenesis. These defects in differentiation capacity are accompanied by impaired senescence and autophagy dynamics. Finally, we demonstrate that inducing autophagy can rescue differentiation of DMD progenitors. Our findings provide novel molecular evidence of satellite cell dysfunction in DMD, expanding on our understanding of their role in its pathology and suggesting pathways to target and enhance their regenerative capacity.

cell biology↗