Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 559 records · Page 31Linked to original sources

bioRxiv2024

Multi-omics Identify Serotonin Transporter as a Promising Therapeutic Target for Essential Tremor

Essential tremor (ET) stands as one of the most prevalent cerebellar movement disorders. However, effective treatment remains elusive, largely due to a limited understanding of its molecular pathology. Harmaline-induced tremor in mouse is a well-established animal model for ET, while with enigmatic mechanism. The aim of this study was to get insight into the molecular intricacies underlying cerebellar dysfunction in harmaline-induced tremor. Combining LC-MS/MS and RNA-Seq analysis, we delved into the variation of the cerebellum between harmaline-induced tremor and the control ones. This comprehensive investigation revealed a profile of this mouse model from mRNA and protein level, highlighting 5194 correlated coding molecules, with 19 proving to be significant. Further KEGG enrichment analysis identified cerebellar serotonin transporter (SERT) as the key molecule in harmaline-induced tremor. The implications of this transcriptomic and proteomic exploration underscore the potential therapeutic value of targeting SERT as a novel treatment approach for ET. In general, our study unveils crucial insights that could pave the way for molecular target identification and effective therapeutic interventions for ET.

neuroscience↗

bioRxiv2024

Scaled and Efficient Derivation of Loss of Function Alleles in Risk Genes for Neurodevelopmental and Psychiatric Disorders in Human iPSC

Translating genetic findings for neurodevelopmental and psychiatric disorders (NPD) into actionable disease biology would benefit from large-scale and unbiased functional studies of NPD genes. Leveraging the cytosine base editing (CBE) system, here we developed a pipeline for clonal loss-of-function (LoF) allele mutagenesis in human induced pluripotent stem cells (hiPSCs) by introducing premature stop-codons (iSTOP) that lead to mRNA nonsense-mediated-decay (NMD) or protein truncation. We tested the pipeline for 23 NPD genes on 3 hiPSC lines and achieved highly reproducible, efficient iSTOP editing in 22 NPD genes. Using RNAseq, we confirmed their pluripotency, absence of chromosomal abnormalities, and NMD. Interestingly, for three schizophrenia risk genes (SETD1A, TRIO, CUL1), despite the high efficiency of base editing, we only obtained heterozygous LoF alleles, suggesting their essential roles for cell growth. We replicated the reported neural phenotypes of SHANK3-haploinsufficiency and found CUL1-LoF reduced neurite branches and synaptic puncta density. This iSTOP pipeline enables a scaled and efficient LoF mutagenesis of NPD genes, yielding an invaluable shareable resource.

genetics↗

bioRxiv2024

A general evolution landscape of language and cognition genes

The polymorphism profiles of language genes (LG) display different patterns across various ancient and modern populations, leading to the speculation that cognition gene (CG) polymorphism profiles may exhibit similar trends. However, the evolutionary processes of language gene polymorphism patterns (LGPP) and cognition gene polymorphism patterns (CGPP) are likely to demonstrate distinct characteristics. In particular, it is intriguing to determine whether there is any overlap in the timing of significant changes in CGPP and LGPP over the large timescales of evolution. The potential existence of such overlap can also be assessed by examining whether the samples carrying significant changes in LGPP and CGPP are the same. This study investigated the genetic differences at 239 SNP loci in 18 language genes (LG) and 223 SNP loci in 18 cognition genes (CG) across 170 whole genomes. Principal component analysis (PCA) was used to cluster the SNP data of the aforementioned samples, and the similarity of SNP patterns between each sample was calculated from three perspectives: LG, CG, and CGLG. The basic conclusions are as follows: (1) If different positions in the PCA analysis results can essentially represent the pattern differences in SNP polymorphisms, then both language gene polymorphism patterns and cognition gene polymorphism patterns have undergone distinct stages of evolution; (2) There were significant differences in the early manifestations of language gene polymorphism patterns and cognition gene polymorphism patterns during human evolution: Language gene polymorphism patterns could not differentiate general animals, primates, and ancient human samples in the early stages of evolution, whereas cognition gene polymorphism patterns seemed to be initially divisible into two patterns, one closely resembling a group of animals and certain ancient human samples, and the other reflected in a different set of animal and primate samples. (3) It appears that samples from all five continents can be observed at every stage of evolution, suggesting that new evolving populations have always had ample time to spread across continents. (4) A quantitative comparison of the SNP profiles of 170 samples revealed that their CG and LG plus CGLG profiles indeed have 2-3 potential significant change points, and the samples carrying these significant change points has 2 common samples, namely ge1 (Georgia) and us2 (North America), implying that the most significant changes in language or cognition gene polymorphism patterns during human evolution may have occurred in some human populations in Europe/ North America.

molecular biology↗

bioRxiv2024

ERNIE-RNA: An RNA Language Model with Structure-enhanced Representations

With large amounts of unlabeled RNA sequences data produced by high-throughput sequencing technologies, pre-trained RNA language models have been developed to estimate semantic space of RNA molecules, which facilities the understanding of grammar of RNA language. However, existing RNA language models overlook the impact of structure when modeling the RNA semantic space, resulting in incomplete feature extraction and suboptimal performance across various downstream tasks. In this study, we developed a RNA pre-trained language model named ERNIE-RNA (Enhanced Representations with base-pairing restriction for RNA modeling) based on a modified BERT (Bidirectional Encoder Representations from Transformers) by incorporating base-pairing restriction with no MSA (Multiple Sequence Alignment) information. We found that the attention maps from ERNIE-RNA with no fine-tuning are able to capture RNA structure in the zero-shot experiment more precisely than conventional methods such as fine-tuned RNAfold and RNAstructure, suggesting that the ERNIE-RNA can provide comprehensive RNA structural representations. Furthermore, ERNIE-RNA achieved SOTA (state-of-the-art) performance after fine-tuning for various downstream tasks, including RNA structural and functional predictions. In summary, our ERNIE-RNA model provides general features which can be widely and effectively applied in various subsequent research tasks. Our results indicate that introducing key knowledge-based prior information in the BERT framework may be a useful strategy to enhance the performance of other language models.

bioinformatics↗

bioRxiv2024

N-acetylation of α-synuclein enhances synaptic vesicle clustering mediated by α-synuclein and lysophosphatidylcholine

Post-translational modifications (PTMs) of -synuclein (-syn) such as acetylation and phosphorylation play important yet distinct roles in regulating -syn conformation, membrane binding, and amyloid aggregation. However, how PTMs regulate -syn function in presynaptic terminals remains unclear. Previously, we reported that -syn clusters synaptic vesicles (SV)1, and neutral phospholipid lysophosphatidylcholine (LPC) can mediate this clustering2. Here, based on our previous findings, we further demonstrate that N-terminal acetylation, which occurs under physiological conditions and is irreversible in mammalian cells, significantly enhances the functional activity of -syn in clustering SVs. Mechanistic studies reveal that this enhancement is caused by the N-acetylation-promoted insertion of -syns N-terminus and increased intermolecular interactions on the LPC-containing membrane. Our work demonstrates that N-acetylation fine-tunes -syn-LPC interaction for mediating -syns function in SV clustering.

biophysics↗

bioRxiv2024

Glioma-associated fibroblasts promote glioblastoma resistance to temozolomide through CCL2-CCR2 paracrine signaling

Complicated tumor microenvironment contributes mostly to chemoresistance in glioblastoma. Glioma-associated fibroblasts (GAFs) were recently identified as non-tumor stromal cells in the glioblastoma microenvironment, whereas their function in glioblastoma chemoresistance is unclear. Herein, we interrogated the correlation between GAFs and chemoresistance of glioblastoma by examining a series of patient-derived GAFs and glioblastoma organoids (GBOs), revealing that GAFs could promote temozolomide resistance in glioblastoma. Mechanistically, C-C motif chemokine ligand 2 (CCL2) secreted by GAFs selectively activated the ERK1/2 signaling in glioblastoma cells to potentiate temozolomide resistance. Pharmacologically disrupting the CCL2-CCR2 axis or MEK1/2-ERK1/2 pathway effectively improved the therapeutic efficacy of temozolomide in GBM cells and patient-derived GBOs, and both decreased phospho-ERK1/2 expression. Collectively, our results identified that targeting the GAF-dominated CCL2-ERK1/2 pathway may be an alternative strategy to alleviate the GAF-mediated chemoresistance of glioblastoma. SignificanceComprehensive interpretation of the mutual support between tumor microenvironment and cancer cells is demanded for glioma with poor response rates to chemotherapy. This study demonstrates that GAFs promote the temozolomide resistance of glioblastoma by secreting cytokine CCL2 to activate ERK1/2 pathway, which may serve as a potential druggable candidate. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/581575v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@167b955org.highwire.dtl.DTLVardef@b892bcorg.highwire.dtl.DTLVardef@1a9b082org.highwire.dtl.DTLVardef@18327a8_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic abstract.C_FLOATNO Schematic illustration for GAFs mediated chemoresistance of GBMs and underlying mechanisms. We demonstrate that Glioma-associated Fibroblasts (GAFs) grow in gliomas by isolating and identifying a panel of patient-derived GAFs. CCL2 secreted by GAFs stimulates CCR2 in GBM cells, which promotes activation of the ERK1/2 expression to potentiate GBM chemoresistance. C_FIG

cancer biology↗

bioRxiv2024

CoupleVAE: coupled variational autoencoders for predicting perturbational single-cell RNA sequencing data

With the rapid advances in single-cell sequencing technology, it is now feasible to conduct in-depth genetic analysis in individual cells. Study on the dynamics of single cells in response to perturbations is of great significance for understanding the functions and behaviours of living organisms. However, the acquisition of post-perturbation cellular states via biological experiments is frequently cost-prohibitive. Predicting the single-cell perturbation responses poses a critical challenge in the field of computational biology. In this work, we propose a novel deep learning method called coupled variational autoencoders (CoupleVAE), devised to predict the post-perturbation single-cell RNA-Seq data. CoupleVAE is composed of two coupled VAEs connected by a coupler, initially extracting latent features for both controlled and perturbed cells via two encoders, subsequently engaging in mutual translation within the latent space through two nonlinear mappings via a coupler, and ultimately generating controlled and perturbed data by two separate decoders to process the encoded and translated features. CoupleVAE facilitates a more intricate state transformation of single cells within the latent space. Experiments in three real datasets on infection, stimulation and cross-species prediction show that CoupleVAE surpasses the existing comparative models in effectively predicting single-cell RNA-seq data for perturbed cells, achieving superior accuracy.

bioinformatics↗

bioRxiv2024

Host 5-HT affects Plasmodium transmission in mosquitoes via modulating mosquito mitochondrial homeostasis

Malaria parasites hijack the metabolism of their mammalian host during the blood-stage cycle. Anopheles mosquitoes depend on mammalian blood to survive and to transmit malaria parasites. However, it remains understudied whether changes in host metabolism affect parasite transmission in mosquitoes. In this study, we discovered that Plasmodium infection significantly decreased the levels of the tryptophan metabolite, 5-hydroxytryptamine (5-HT), in both humans and mice. The reduction led to the decrease of 5-HT in mosquitoes. Oral supplementation of 5-HT to Anopheles stephensi enhanced its resistance to Plasmodium berghei infection by promoting the generation of mitochondrial reactive oxygen species. This effect was due to the accumulation of dysfunctional mitochondria caused by 5-HT-mediated inhibition of mitophagy. Elevating 5-HT levels in mouse serum significantly suppressed parasite infection in mosquitoes. In summary, our data highlight the critical role of metabolites in animal blood in determining the capacity of mosquitoes to control parasite infection.

pathology↗

bioRxiv2024

Polygenic Risk for Alcohol Use Disorder Affects Cellular Responses to Ethanol Exposure in a Human Microglial Cell Model

Polygenic risk scores (PRS) assess genetic susceptibility to Alcohol Use Disorder (AUD), yet their molecular implications remain underexplored. Neuroimmune interactions, particularly in microglia, are recognized as significant contributors to AUD pathophysiology. We investigated the interplay between AUD PRS and ethanol in human microglia derived from iPSCs from individuals with high- or low-PRS (HPRS or LPRS) of AUD. Ethanol exposure induced elevated CD68 expression and morphological changes in microglia, with differential responses between HPRS and LPRS microglial cells. Transcriptomic analysis revealed expression differences in MHCII complex and phagocytosis-related genes following ethanol exposure; HPRS microglial cells displayed enhanced phagocytosis and increased CLEC7A expression, unlike LPRS microglial cells. Synapse numbers in co-cultures of induced neurons with microglia after alcohol exposure were lower in HRPS co-cultures, suggesting possible excess synapse pruning. This study provides insights into the intricate relationship between AUD PRS, ethanol, and microglial function, potentially influencing neuronal functions in developing AUD.

neuroscience↗

bioRxiv2024

D-mannose suppresses macrophage release of extracellular vesicles and ameliorates type 2 diabetes

The monosaccharide D-mannose exists naturally in low abundance in human blood, while an increased plasma mannose level is associated with insulin resistance and the incidence of type 2 diabetes (T2D) in patients. However, whether and how D-mannose may regulate T2D development remains elusive. Here, we show that despite the altered mannose metabolism in T2D, drinking-water supplementation of supraphysiological D-mannose safely ameliorates T2D in genetically obese db/db mice. Interestingly, D-mannose therapy exerts limited effects on the gut microbiome and peripheral blood T cells, whereas D-mannose after administration is enriched in the liver and alleviates hepatic steatosis and insulin resistance. Mechanistically, D-mannose suppresses macrophage release of pathological extracellular vesicles (EVs) for improving hepatocyte function through metabolic control of CD36 expression. Collectively, these findings reveal D-mannose as an effective and potential T2D therapeutic, which add to the current knowledge of sugars regulating EV-based intercellular communication and inspire translational pharmaceutical strategies of T2D. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/580856v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@604ddcorg.highwire.dtl.DTLVardef@97ca9corg.highwire.dtl.DTLVardef@176f741org.highwire.dtl.DTLVardef@1630699_HPS_FORMAT_FIGEXP M_FIG C_FIG Drinking-water supplementation of D-mannose serves as an effective therapeutic of type 2 diabetes, which rescued hepatocyte steatosis through suppressing macrophage release of extracellular vesicles based on metabolic control of CD36 expression.

cell biology↗

bioRxiv2024

MRI economics: Balancing sample size and scan duration in brain wide association studies

A pervasive dilemma in brain-wide association studies (BWAS) is whether to prioritize functional MRI (fMRI) scan time or sample size. We derive a theoretical model showing that individual-level phenotypic prediction accuracy increases with sample size and total scan duration (sample size x scan time per participant). The model explains empirical prediction accuracies extremely well across 76 phenotypes from nine resting-fMRI and task-fMRI datasets (R2 = 0.89), spanning a wide range of scanners, acquisitions, racial groups, disorders and ages. For scans [≤]20 mins, prediction accuracy increases linearly with the logarithm of total scan duration, suggesting interchangeability of sample size and scan time. However, sample size is ultimately more important than scan time in determining prediction accuracy. Nevertheless, when accounting for overhead costs associated with each participant (e.g., recruitment costs), to boost prediction accuracy, longer scans can yield substantial cost savings over larger sample size. To achieve high prediction performance, 10-min scans are highly cost inefficient. In most scenarios, the optimal scan time is [≥]20 mins. On average, 30-min scans are the most cost-effective, yielding 22% cost savings over 10-min scans. Overshooting is cheaper than undershooting the optimal scan time, so we recommend aiming for [≥]30 mins. Compared with resting-state whole-brain BWAS, the most cost-effective scan time is shorter for task-fMRI and longer for subcortical-cortical BWAS. Standard power calculations maximize sample size at the expense of scan time. Our study demonstrates that optimizing both sample size and scan time can boost prediction power while cutting costs. Our empirically informed reference is available for future study planning: WEB_APPLICATION_LINK

neuroscience↗

bioRxiv2024

Fertilization by short-term stored sperm alters DNA methylation patterns in common carp (Cyprinus carpio) embryos at single-base resolution

Short-term storage of sperm in vitro is widely used for artificial fertilization in aquaculture. It has been shown that short-term storage affects sperm motility characteristics, resulting in diminished fertility. However, the detrimental effects of short-term sperm storage on embryos development have remained largely unexplored in single-base methylome resolution. The main aim of the present study was to investigate DNA methylation in the offspring of common carp (Cyprinus carpio) derived from short-term stored sperm. Sperm were stored in artificial seminal plasma on ice (0-2{degrees}C) for 0, 3 and 6 days in vitro, fertilization was performed using oocytes from a single female, and embryos were collected at the mid-blastula stage. Sperm and embryo DNA was extracted, analysed by liquid chromatography with tandem mass spectrometry (LC-MS/MS) and whole genome bisulfite sequencing (WGBS). DNA methylation was then assessed. Sperm storage showed negative effects on motility, viability and DNA integrity, but had no effect on global DNA methylation of spermatozoa and resulting embryos. Results from the WGBS showed that methylation of 3313 genes was affected in the embryos fertilized with the 6-day-stored sperm, and the differentially methylated regions (DMRs) identified were mainly involved in cell adhesion, calcium, mitogen-activated protein kinase and adrenergic signalling, melanogenesis, metabolism and RNA transport. Such results suggest that prolongation of storage time may have certain impacts on embryonic development. These initial results provide valuable information for future consideration of the DNA methylome in embryos generated from short-term stored sperm, which is widely used for genetic management of broodstock in aquaculture.

molecular biology↗

bioRxiv2024

Highly efficient in vivo mutagenesis method based on the endonuclease and exonuclease activity of Bacillus alcalophilus RecJ (BaRecJ)

With the continual advancement of technologies such as microbial cultivation, DNA sequencing, bioinformatics, and genetic engineering, methods for microbial breeding have become increasingly diverse. We identified a RecJ enzyme (BaRecJ) with both endonuclease and exonuclease activities from B. alcalophilus. Differing from traditional physical-chemical mutagenesis approaches and the methods based on perturbation factor. this research established a novel mutagenesis method utilizing the endonuclease and exonuclease activities of BaRecJ. Mutagenesis of E. coli was conducted using the BaRecJ method, followed by screening for rifampicin-resistant mutants, rpoB sequencing results demonstrated a broader, more uniform spectrum of mutations and a higher frequency of substitution mutations with this mutagenesis approach. Furthermore, this mutagenesis method was applied to S cerevisiae, resulting in mutants with enhanced tolerance to acetic acid and ethanol, exhibiting improved fermentation performance and flocculation abilities Genomic resequencing analysis summarized genes possibly associated with the tolerance of mutants. Therefore, this approach not only holds immense potential in microbial mutagenesis breeding and adaptive evolution but also, when coupled with genomic resequencing, allows for the rapid identification of genetic loci associated with specific traits.

bioengineering↗

bioRxiv2024

CoRAL accurately resolves extrachromosomal DNA genomestructures with long-read sequencing

Extrachromosomal DNA (ecDNA) is a central mechanism for focal oncogene amplification in cancer, occurring in approximately 15% of early stage cancers and 30% of late-stage cancers. EcDNAs drive tumor formation, evolution, and drug resistance by dynamically modulating oncogene copy-number and rewiring gene-regulatory networks. Elucidating the genomic architecture of ecDNA amplifications is critical for understanding tumor pathology and developing more effective therapies. Paired-end short-read (Illumina) sequencing and mapping have been utilized to represent ecDNA amplifications using a breakpoint graph, where the inferred architecture of ecDNA is encoded as a cycle in the graph. Traversals of breakpoint graph have been used to successfully predict ecDNA presence in cancer samples. However, short-read technologies are intrinsically limited in the identification of breakpoints, phasing together of complex rearrangements and internal duplications, and deconvolution of cell-to-cell heterogeneity of ecDNA structures. Long-read technologies, such as from Oxford Nanopore Technologies, have the potential to improve inference as the longer reads are better at mapping structural variants and are more likely to span rearranged or duplicated regions. Here, we propose CoRAL (Complete Reconstruction of Amplifications with Long reads), for reconstructing ecDNA architectures using long-read data. CoRAL reconstructs likely cyclic architectures using quadratic programming that simultaneously optimizes parsimony of reconstruction, explained copy number, and consistency of long-read mapping. CoRAL substantially improves reconstructions in extensive simulations and 9 datasets from previously-characterized cell-lines as compared to previous short-read-based tools. As long-read usage becomes wide-spread, we anticipate that CoRAL will be a valuable tool for profiling the landscape and evolution of focal amplifications in tumors.

cancer biology↗

bioRxiv2024

PRS-Net: Interpretable polygenic risk scores via geometric learning

Polygenic risk score (PRS) serves as a valuable tool for predicting the genetic risk of complex human diseases for individuals, playing a pivotal role in advancing precision medicine. Traditional PRS methods, predominantly following a linear structure, often fall short in capturing the intricate relationships between genotype and phenotype. We present PRS-Net, an interpretable deep learning-based framework designed to effectively model the nonlinearity of biological systems for enhanced disease prediction and biological discovery. PRS-Net begins by deconvoluting the genomewide PRS at the single-gene resolution, and then it encapsulates gene-gene interactions for genetic risk prediction leveraging a graph neural network, thereby enabling the characterization of biological nonlinearity underlying complex diseases. An attentive readout module is specifically introduced into the framework to facilitate model interpretation and biological discovery. Through extensive tests across multiple complex diseases, PRS-Net consistently outperforms baseline PRS methods, showcasing its superior performance on disease prediction. Moreover, the interpretability of PRS-Net has been demonstrated by the identification of genes and gene-gene interactions that significantly influence the risk of Alzheimers disease and multiple sclerosis. In summary, PRS-Net provides a potent tool for parallel genetic risk prediction and biological discovery for complex diseases.

genetics↗

bioRxiv2024

Hosts Manipulate Lifestyle Switch and Pathogenicity Heterogeneity of Opportunistic Pathogens in the Single-cell Resolution

Host-microbe interactions are virtually bidirectional, but how the host affects their microbiome is poorly understood. Here, we report that the host is a critical modulator to regulate the lifestyle switch and pathogenicity heterogeneity of the opportunistic pathogens Serratia marcescens utilizing the Drosophila and bacterium model system. First, we find that Drosophila larvae efficiently outcompete S. marcescens and typically drive a bacterial switch from pathogenicity to commensalism toward the fly. Furthermore, Drosophila larvae reshape the transcriptomic and metabolic profiles of S. marcescens characterized by a lifestyle switch. More important, the host alters pathogenicity and heterogeneity of S. marcescens in the single-cell resolution. Finally, we find that larvae-derived AMPs are required to recapitulate the response of S. marcescens to larvae. Altogether, our findings provide an insight into the pivotal roles of the host in harnessing the life history and heterogeneity of symbiotic bacterial cells, advancing knowledge of the reciprocal relationships between the host and pathogen.

microbiology↗

bioRxiv2024

Dynamic Lateralization in Contralateral-Projecting Corticospinal Neurons During Motor Learning

Understanding the adaptability of the motor cortex in response to bilateral motor tasks is crucial for advancing our knowledge of neural plasticity and motor learning. Here we aim to investigate the dynamic lateralization of contralateral-projecting corticospinal neurons (cpCSNs) during such tasks. Utilizing in vivo two-photon calcium imaging, we observe cpCSNs in mice performing a bilateral lever-press task. Our findings reveal a heterogeneous population dynamics in cpCSNs: a marked decrease in activity during ipsilateral motor learning, in contrast to maintained activity during contralateral motor learning. Notably, individual cpCSNs show dynamic shifts in their engagement with ipsilateral and contralateral movements, displaying an evolving pattern of activation over successive days. This suggests a flexible and learning-related reconfiguration in the cpCSN network, parallel to motor learning stages. Our findings suggest a complex reorganization in cpCSN activities, underscoring the dynamic nature of cortical lateralization in motor learning and offering insights for neuromotor rehabilitation.

neuroscience↗

bioRxiv2024

Diversity, Origin and Evolution of the ESCRT Systems

Endosomal Sorting Complexes Required for Transport (ESCRT) play key roles in protein sorting between membrane-bounded compartments of eukaryotic cells. Homologs of many ESCRT components are identifiable in various groups of archaea, especially in Asgardarchaeota, the archaeal phylum that is currently considered to include the closest relatives of eukaryotes, but not in bacteria. We performed a comprehensive search for ESCRT protein homologs in archaea and reconstructed ESCRT evolution using the phylogenetic tree of Vps4 ATPase (ESCRT IV) as a scaffold, using sensitive protein sequence analysis and comparison of structural models to identify previously unknown ESCRT proteins. Several distinct groups of ESCRT systems in archaea outside of Asgard were identified, including proteins structurally similar to ESCRT-I and ESCRT-II, and several other domains involved in protein sorting in eukaryotes, suggesting an early origin of these components. Additionally, distant homologs of CdvA proteins were identified in Thermoproteales which are likely components of the uncharacterized cell division system in these archaea. We propose an evolutionary scenario for the origin of eukaryotic and Asgard ESCRT complexes from ancestral building blocks, namely, the Vps4 ATPase, ESCRT-III components, wH (winged helix-turn-helix fold) and possibly also coiled-coil, and Vps28-like domains. The Last Archaeal Common Ancestor likely encompassed a complex ESCRT system that was involved in protein sorting. Subsequent evolution involved either simplification, as in the TACK superphylum, where ESCRT was co-opted for cell division, or complexification as in Asgardarchaeota. In Asgardarchaeota, the connection between ESCRT and the ubiquitin system that was previously considered a eukaryotic signature was already established. ImportanceAll eukaryotic cells possess complex intracellular membrane organization. ESCRT (Endosomal Sorting Complexes Required for Transport) plays a central role in membrane remodeling which is essential for cellular functionality in eukaryotes. Recently, it has been shown that Asgard archaea, the archaeal phylum that includes the closest known relatives of eukaryotes, encode homologs of many components of the ESCRT systems. We employed protein sequence and structure comparisons to reconstruct the evolution of ESCRT systems in archaea and identified several previously unknown homologs of ESCRT subunits, some of which can be predicted to participate in cell division. The results of this reconstruction indicate that the Last Archaeal Common ancestor already encoded a complex ESCRT system that was involved in protein sorting. In Asgard archaea, ESCRT systems evolved towards greater complexity, and in particular, the connection between ESCRT and the ubiquitin system that was previously considered a eukaryotic signature was established.

evolutionary biology↗