iScience. 2024 Apr 22;27(5):109795. doi: 10.1016/j.isci.2024.109795. eCollection 2024 May 17.

ABSTRACT

Despite the promising outcomes of immune checkpoint inhibitors (ICIs), resistance to ICI presents a new challenge. Therefore, selecting patients for specific ICI applications is crucial for maximizing therapeutic efficacy. Herein, we curated 69 human esophageal squamous cell cancer (ESCC) patients' tumor microenvironment (TME) single-cell transcriptomic datasets to subtype ESCC. Integrative analyses of the cellular network and transcriptional signatures of T cells and myeloid cells define distinct ESCC subtypes characterized by T cell exhaustion, and interleukin (IL) and interferon (IFN) signaling. Furthermore, this approach classifies ESCC patients into ICI responders and non-responders, as validated by whole tumor transcriptomes and liquid biopsy-based single-cell transcriptomes of anti-PD-1 ICI responders and non-responders. Our study stratifies ESCC patients based on TME transcriptional network, providing novel insights into tumor niche remodeling and potentially predicting ICI responses in ESCC patients.

PMID:38741711 | PMC:PMC11089351 | DOI:10.1016/j.isci.2024.109795

iScience. 2024 Apr 23;27(5):109800. doi: 10.1016/j.isci.2024.109800. eCollection 2024 May 17.

ABSTRACT

Hepatocellular carcinoma (HCC) currently lacks effective therapies, leaving a critical need for new treatment options. A previous study identified the anaplastic lymphoma kinase (ALK) amplification in HCC patients, raising the question of whether ALK inhibitors could be a viable treatment. Here, we showed that both ALK inhibitors and ALK knockout effectively halted HCC growth in cell cultures. Lorlatinib, a potent ALK inhibitor, suppressed HCC tumor growth and metastasis across various mouse models. Additionally, in an advanced immunocompetent humanized mouse model, when combined with an anti-PD-1 antibody, lorlatinib more potently suppressed HCC tumor growth, surpassing individual drug efficacy. Lorlatinib induced apoptosis and senescence in HCC cells, and the senolytic agent ABT-263 enhanced the efficacy of lorlatinib. Additional studies identified that the apoptosis-inducing effect of lorlatinib was mediated via GGN and NRG4. These findings establish ALK inhibitors as promising HCC treatments, either alone or in combination with immunotherapies or senolytic agents.

PMID:38741708 | PMC:PMC11089374 | DOI:10.1016/j.isci.2024.109800

Bioinformatics. 2024 May 13:btae316. doi: 10.1093/bioinformatics/btae316. Online ahead of print.

ABSTRACT

MOTIVATION: Multi-omics data provide a comprehensive view of gene regulation at multiple levels, which is helpful in achieving accurate diagnosis of complex diseases like cancer. However, conventional integration methods rarely utilize prior biological knowledge and lack interpretability.

RESULTS: To integrate various multi-omics data of tissue and liquid biopsies for disease diagnosis and prognosis, we developed a biological pathway informed Transformer, Pathformer. It embeds multi-omics input with a compacted multi-modal vector and a pathway-based sparse neural network. Pathformer also leverages criss-cross attention mechanism to capture the crosstalk between different pathways and modalities. We first benchmarked Pathformer with 18 comparable methods on multiple cancer datasets, where Pathformer outperformed all the other methods, with an average improvement of 6.3%-14.7% in F1 score for cancer survival prediction, 5.1%-12% for cancer stage prediction, and 8.1%-13.6% for cancer drug response prediction. Subsequently, for cancer prognosis prediction based on tissue multi-omics data, we used a case study to demonstrate the biological interpretability of Pathformer by identifying key pathways and their biological crosstalk. Then, for cancer early diagnosis based on liquid biopsy data, we used plasma and platelet datasets to demonstrate Pathformer's potential of clinical applications in cancer screening. Moreover, we revealed deregulation of interesting pathways (e.g., scavenger receptor pathway) and their crosstalk in cancer patients' blood, providing potential candidate targets for cancer microenvironment study.

AVAILABILITY: Pathformer is implemented and freely available at https://github.com/lulab/Pathformer.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:38741230 | DOI:10.1093/bioinformatics/btae316

Bioinformatics. 2024 May 13:btae312. doi: 10.1093/bioinformatics/btae312. Online ahead of print.

ABSTRACT

MOTIVATION: Systems biology aims to better understand living systems through mathematical modelling of experimental and clinical data. A pervasive challenge in quantitative dynamical modelling is the integration of time series measurements, which often have high variability and low sampling resolution. Approaches are required to utilise such information while consistently handling uncertainties.

RESULTS: We present BayModTS (Bayesian Modelling of Time Series data), a new FAIR (Findable, Accessible, Interoperable and Reusable) workflow for processing and analysing sparse and highly variable time series data. BayModTS consistently transfers uncertainties from data to model predictions, including process knowledge via parameterised models. Further, credible differences in the dynamics of different conditions can be identified by filtering noise. To demonstrate the power and versatility of BayModTS, we applied it to three hepatic datasets gathered from three different species and with different measurement techniques: (i) blood perfusion measurements by magnetic resonance imaging in rat livers after portal vein ligation, (ii) pharmacokinetic time series of different drugs in normal and steatotic mice, and (iii) CT-based volumetric assessment of human liver remnants after clinical liver resection.

AVAILABILITY AND IMPLEMENTATION: The BayModTS codebase is available on GitHub at https://github.com/Systems-Theory-in-Systems-Biology/BayModTS. The repository contains a Python script for the executable BayModTS workflow and a widely applicable SBML (Systems Biology Markup Language) model for retarded transient functions. In addition, all examples from the paper are included in the repository. Data and code of the application examples are stored on DaRUS https://doi.org/10.18419/darus-3876. The raw MRI ROI voxel data were uploaded to DaRUS https://doi.org/10.18419/darus-3878. The steatosis metabolite data are published on FairdomHub 10.15490/fairdomhub.1.study.1070.1.

PMID:38741151 | DOI:10.1093/bioinformatics/btae312

Life Sci. 2024 May 11:122715. doi: 10.1016/j.lfs.2024.122715. Online ahead of print.

ABSTRACT

Chronic obstructive pulmonary disease (COPD), a chronic airway disorder, which is mostly brought on by cigarette smoke extract (CSE), is a leading cause of death which has a high frequency. In COPD patients, smoking cigarette could also trigger the epithelial-mesenchymal transition (EMT) of airway remodeling. One of the most significant elements of environmental contaminants that is linked to pulmonary damage is fine particulate matter PM2.5. However, the basic processes of lung injury brought on by environmental contaminants and cigarette smoke are poorly understood, particularly the molecular pathways involved in inflammation. For the clinical management of COPD, investigating the molecular process and identifying workable biomarkers will be important. According to newly available research, circular RNAs (circRNAs) are aberrantly produced and serve as important regulators in the pathological processes of COPD. This class of non-coding RNAs (ncRNAs) functions as microRNA (miRNA) sponges to control the levels of gene expression, changing cellular phenotypes and advancing disease. These findings led us to concentrate our attention in this review on new studies about the regulatory mechanism and potential roles of circRNA-associated ceRNA networks (circCeNETs) in COPD.

PMID:38740326 | DOI:10.1016/j.lfs.2024.122715

Int J Infect Dis. 2024 May 11:107085. doi: 10.1016/j.ijid.2024.107085. Online ahead of print.

ABSTRACT

OBJECTIVES: Predicting progression of nontuberculous mycobacterial lung disease (NTM-LD) remains challenging. This study evaluated whether sputum bacterial microbiome diversity can be the biomarker and provide novel insights into related phenotypes and treatment timing.

METHODS: We analyzed 126 sputum microbiomes of 126 patients with newly diagnosed NTM-LD due to Mycobacterium avium complex, M. abscessus complex, and M. kansasii between May 2020 and December 2021. Patients were followed for 2 years to determine their disease progression status. We identified consistently representative genera that differentiated the progressor and nonprogressor by using six methodologies. These genera were used to construct a prediction model using random forest with 5-fold cross validation.

RESULTS: Disease progression occurred in 49 (38.6%) patients. Compared with nonprogressors, α-diversity was lower in the progressors. Significant compositional differences existed in the β-diversity between groups (p=0.001). The prediction model for NTM-LD progression constructed using seven genera (Burkholderia, Pseudomonas, Sphingomonas, Candidatus Saccharibacteria, Phocaeicola, Pelomonas, and Phascolarctobacterium) with significantly differential abundance achieved an area under curve of 0.871.

CONCLUSIONS: Identification of the composition of sputum bacterial microbiome facilitates prediction of the course of NTM-LD, and maybe used to develop precision treatment involving modulating the respiratory microbiome composition to ameliorate NTM-LD.

PMID:38740280 | DOI:10.1016/j.ijid.2024.107085

BMC Neurosci. 2024 May 13;25(1):24. doi: 10.1186/s12868-024-00867-y.

ABSTRACT

BACKGROUND: Alzheimer's disease (AD) is a devastating neurodegenerative disorder affecting 44 million people worldwide, leading to cognitive decline, memory loss, and significant impairment in daily functioning. The recent single-cell sequencing technology has revolutionized genetic and genomic resolution by enabling scientists to explore the diversity of gene expression patterns at the finest resolution. Most existing studies have solely focused on molecular perturbations within each cell, but cells live in microenvironments rather than in isolated entities. Here, we leveraged the large-scale and publicly available single-nucleus RNA sequencing in the human prefrontal cortex to investigate cell-to-cell communication in healthy brains and their perturbations in AD. We uniformly processed the snRNA-seq with strict QCs and labeled canonical cell types consistent with the definitions from the BRAIN Initiative Cell Census Network. From ligand and receptor gene expression, we built a high-confidence cell-to-cell communication network to investigate signaling differences between AD and healthy brains.

RESULTS: Specifically, we first performed broad communication pattern analyses to highlight that biologically related cell types in normal brains rely on largely overlapping signaling networks and that the AD brain exhibits the irregular inter-mixing of cell types and signaling pathways. Secondly, we performed a more focused cell-type-centric analysis and found that excitatory neurons in AD have significantly increased their communications to inhibitory neurons, while inhibitory neurons and other non-neuronal cells globally decreased theirs to all cells. Then, we delved deeper with a signaling-centric view, showing that canonical signaling pathways CSF, TGFβ, and CX3C are significantly dysregulated in their signaling to the cell type microglia/PVM and from endothelial to neuronal cells for the WNT pathway. Finally, after extracting 23 known AD risk genes, our intracellular communication analysis revealed a strong connection of extracellular ligand genes APP, APOE, and PSEN1 to intracellular AD risk genes TREM2, ABCA1, and APP in the communication from astrocytes and microglia to neurons.

CONCLUSIONS: In summary, with the novel advances in single-cell sequencing technologies, we show that cellular signaling is regulated in a cell-type-specific manner and that improper regulation of extracellular signaling genes is linked to intracellular risk genes, giving the mechanistic intra- and inter-cellular picture of AD.

PMID:38741048 | DOI:10.1186/s12868-024-00867-y

Nat Commun. 2024 May 13;15(1):4014. doi: 10.1038/s41467-024-48370-6.

ABSTRACT

SARS-CoV-2 can re-structure chromatin organization and alter the epigenomic landscape of the host genome, but the mechanisms that produce such changes remain unclear. Here, we use polymer physics to investigate how the chromatin of the host genome is re-organized upon infection with SARS-CoV-2. We show that re-structuring of A/B compartments can be explained by a re-modulation of intra-compartment homo-typic affinities, which leads to the weakening of A-A interactions and the enhancement of A-B mixing. At the TAD level, re-arrangements are physically described by a reduction in the loop extrusion activity coupled with an alteration of chromatin phase-separation properties, resulting in more intermingling between different TADs and a spread in space of the TADs themselves. In addition, the architecture of loci relevant to the antiviral interferon response, such as DDX58 or IFIT, becomes more variable within the 3D single-molecule population of the infected model, suggesting that viral infection leads to a loss of chromatin structural specificity. Analysing the time trajectories of pairwise gene-enhancer and higher-order contacts reveals that this variability derives from increased fluctuations in the chromatin dynamics of infected cells. This suggests that SARS-CoV-2 alters gene regulation by impacting the stability of the contact network in time.

PMID:38740770 | DOI:10.1038/s41467-024-48370-6

Proc Natl Acad Sci U S A. 2024 May 21;121(21):e2322428121. doi: 10.1073/pnas.2322428121. Epub 2024 May 13.

ABSTRACT

Protein evolution is guided by structural, functional, and dynamical constraints ensuring organismal viability. Pseudogenes are genomic sequences identified in many eukaryotes that lack translational activity due to sequence degradation and thus over time have undergone "devolution." Previously pseudogenized genes sometimes regain their protein-coding function, suggesting they may still encode robust folding energy landscapes despite multiple mutations. We study both the physical folding landscapes of protein sequences corresponding to human pseudogenes using the Associative Memory, Water Mediated, Structure and Energy Model, and the evolutionary energy landscapes obtained using direct coupling analysis (DCA) on their parent protein families. We found that generally mutations that have occurred in pseudogene sequences have disrupted their native global network of stabilizing residue interactions, making it harder for them to fold if they were translated. In some cases, however, energetic frustration has apparently decreased when the functional constraints were removed. We analyzed this unexpected situation for Cyclophilin A, Profilin-1, and Small Ubiquitin-like Modifier 2 Protein. Our analysis reveals that when such mutations in the pseudogene ultimately stabilize folding, at the same time, they likely alter the pseudogenes' former biological activity, as estimated by DCA. We localize most of these stabilizing mutations generally to normally frustrated regions required for binding to other partners.

PMID:38739795 | DOI:10.1073/pnas.2322428121

Brief Bioinform. 2024 Mar 27;25(3):bbae253. doi: 10.1093/bib/bbae253.

NO ABSTRACT

PMID:38739760 | DOI:10.1093/bib/bbae253

Brief Bioinform. 2024 Mar 27;25(3):bbae230. doi: 10.1093/bib/bbae230.

ABSTRACT

The complicated process of neuronal development is initiated early in life, with the genetic mechanisms governing this process yet to be fully elucidated. Single-cell RNA sequencing (scRNA-seq) is a potent instrument for pinpointing biomarkers that exhibit differential expression across various cell types and developmental stages. By employing scRNA-seq on human embryonic stem cells, we aim to identify differentially expressed genes (DEGs) crucial for early-stage neuronal development. Our focus extends beyond simply identifying DEGs. We strive to investigate the functional roles of these genes through enrichment analysis and construct gene regulatory networks to understand their interactions. Ultimately, this comprehensive approach aspires to illuminate the molecular mechanisms and transcriptional dynamics governing early human brain development. By uncovering potential links between these DEGs and intelligence, mental disorders, and neurodevelopmental disorders, we hope to shed light on human neurological health and disease. In this study, we have used scRNA-seq to identify DEGs involved in early-stage neuronal development in hESCs. The scRNA-seq data, collected on days 26 (D26) and 54 (D54), of the in vitro differentiation of hESCs to neurons were analyzed. Our analysis identified 539 DEGs between D26 and D54. Functional enrichment of those DEG biomarkers indicated that the up-regulated DEGs participated in neurogenesis, while the down-regulated DEGs were linked to synapse regulation. The Reactome pathway analysis revealed that down-regulated DEGs were involved in the interactions between proteins located in synapse pathways. We also discovered interactions between DEGs and miRNA, transcriptional factors (TFs) and DEGs, and between TF and miRNA. Our study identified 20 significant transcription factors, shedding light on early brain development genetics. The identified DEGs and gene regulatory networks are valuable resources for future research into human brain development and neurodevelopmental disorders.

PMID:38739758 | DOI:10.1093/bib/bbae230

PLoS Comput Biol. 2024 May 13;20(5):e1012043. doi: 10.1371/journal.pcbi.1012043. Online ahead of print.

ABSTRACT

Sensory neurons reconstruct the world from action potentials (spikes) impinging on them. To effectively transfer information about the stimulus to the next processing level, a neuron needs to be able to adapt its working range to the properties of the stimulus. Here, we focus on the intrinsic neural properties that influence information transfer in cortical neurons and how tightly their properties need to be tuned to the stimulus statistics for them to be effective. We start by measuring the intrinsic information encoding properties of putative excitatory and inhibitory neurons in L2/3 of the mouse barrel cortex. Excitatory neurons show high thresholds and strong adaptation, making them fire sparsely and resulting in a strong compression of information, whereas inhibitory neurons that favour fast spiking transfer more information. Next, we turn to computational modelling and ask how two properties influence information transfer: 1) spike-frequency adaptation and 2) the shape of the IV-curve. We find that a subthreshold (but not threshold) adaptation, the 'h-current', and a properly tuned leak conductance can increase the information transfer of a neuron, whereas threshold adaptation can increase its working range. Finally, we verify the effect of the IV-curve slope in our experimental recordings and show that excitatory neurons form a more heterogeneous population than inhibitory neurons. These relationships between intrinsic neural features and neural coding that had not been quantified before will aid computational, theoretical and systems neuroscientists in understanding how neuronal populations can alter their coding properties, such as through the impact of neuromodulators. Why the variability of intrinsic properties of excitatory neurons is larger than that of inhibitory ones is an exciting question, for which future research is needed.

PMID:38739640 | DOI:10.1371/journal.pcbi.1012043

Elife. 2024 May 13;13:RP94800. doi: 10.7554/eLife.94800.

ABSTRACT

A comprehensive census of McrBC systems, among the most common forms of prokaryotic Type IV restriction systems, followed by phylogenetic analysis, reveals their enormous abundance in diverse prokaryotes and a plethora of genomic associations. We focus on a previously uncharacterized branch, which we denote coiled-coil nuclease tandems (CoCoNuTs) for their salient features: the presence of extensive coiled-coil structures and tandem nucleases. The CoCoNuTs alone show extraordinary variety, with three distinct types and multiple subtypes. All CoCoNuTs contain domains predicted to interact with translation system components, such as OB-folds resembling the SmpB protein that binds bacterial transfer-messenger RNA (tmRNA), YTH-like domains that might recognize methylated tmRNA, tRNA, or rRNA, and RNA-binding Hsp70 chaperone homologs, along with RNases, such as HEPN domains, all suggesting that the CoCoNuTs target RNA. Many CoCoNuTs might additionally target DNA, via McrC nuclease homologs. Additional restriction systems, such as Type I RM, BREX, and Druantia Type III, are frequently encoded in the same predicted superoperons. In many of these superoperons, CoCoNuTs are likely regulated by cyclic nucleotides, possibly, RNA fragments with cyclic termini, that bind associated CARF (CRISPR-Associated Rossmann Fold) domains. We hypothesize that the CoCoNuTs, together with the ancillary restriction factors, employ an echeloned defense strategy analogous to that of Type III CRISPR-Cas systems, in which an immune response eliminating virus DNA and/or RNA is launched first, but then, if it fails, an abortive infection response leading to PCD/dormancy via host RNA cleavage takes over.

PMID:38739430 | DOI:10.7554/eLife.94800

Anal Bioanal Chem. 2024 May 13. doi: 10.1007/s00216-024-05317-6. Online ahead of print.

ABSTRACT

Nanozymes are nanomaterials with mimetic enzyme properties and the related research has attracted much attention. It is of great value to develop methods to construct nanozymes and to study their application in bioanalysis. Herein, the metal-ligand cross-linking strategy was developed to fabricate superstructure nanozymes. This strategy takes advantage of being easy to operate, adjustable, cheap, and universal. The fabricated superstructure nanozymes possess efficient peroxidase-like catalytic activity. The enzyme reaction kinetic tests demonstrated that for TMB and H2O2, the Km is 0.229 and 1.308 mM, respectively. Furthermore, these superstructure nanozymes are applied to highly efficient and sensitive detection of glucose. The linear range for detecting glucose is 20-2000 μM, and the limit of detection is 17.5 μM. Furthermore, mechanistic research illustrated that this integrated system oxidizes glucose to produce hydrogen peroxide and further catalyzes the production of ·OH and O2·-, which results in a chromogenic reaction of oxidized TMB for the detection of glucose. This work could not only contribute to the development of efficient nanozymes but also inspire research in the highly sensitive detection of other biomarkers.

PMID:38739158 | DOI:10.1007/s00216-024-05317-6

Acta Naturae. 2024 Jan-Mar;16(1):77-85. doi: 10.32607/actanaturae.27362.

ABSTRACT

The standardization of DNA fragment assembly methods for many tasks of synthetic biology is crucial. This is necessary for synthesizing a wider repertoire of sequences, as well as for further automation and miniaturization of such reactions. In this work, we proposed conditions for the assembly of DNA fragments from chemically synthesized oligonucleotides and we identified the errors occurring in the sequence under these conditions. Additionally, we proposed conditions for further combining synthetic fragments into larger DNA fragments. We showed that the optimized conditions are suitable for the assembly of a wide range of sequences.

PMID:38738632 | PMC:PMC11062099 | DOI:10.32607/actanaturae.27362

Allergy. 2024 May 13. doi: 10.1111/all.16156. Online ahead of print.

NO ABSTRACT

PMID:38738468 | DOI:10.1111/all.16156

Access Microbiol. 2024 Apr 19;6(4):000770.v3. doi: 10.1099/acmi.0.000770.v3. eCollection 2024.

ABSTRACT

Streptomyces sp. DSM 41014, DSM 41527, and DSM 41981 are three strains from the DSMZ strain collection. Here, we present the draft genome sequences of DSM 41014, DSM 41527, and DSM 41981 with a size of 9.09 Mb, 8.45 Mb, and 9.23 Mb, respectively.

PMID:38737806 | PMC:PMC11083389 | DOI:10.1099/acmi.0.000770.v3

Front Plant Sci. 2024 Apr 24;15:1384496. doi: 10.3389/fpls.2024.1384496. eCollection 2024.

ABSTRACT

Arbuscular mycorrhizal fungi (AMF) are obligate symbionts that interact with the roots of most land plants. The genome of the AMF model species Rhizophagus irregularis contains hundreds of predicted small effector proteins that are secreted extracellularly but also into the plant cells to suppress plant immunity and modify plant physiology to establish a niche for growth. Here, we investigated the role of four nuclear-localized putative effectors, i.e., GLOIN707, GLOIN781, GLOIN261, and RiSP749, in mycorrhization and plant growth. We initially intended to execute the functional studies in Solanum lycopersicum, a host plant of economic interest not previously used for AMF effector biology, but extended our studies to the model host Medicago truncatula as well as the non-host Arabidopsis thaliana because of the technical advantages of working with these models. Furthermore, for three effectors, the implementation of reverse genetic tools, yeast two-hybrid screening and whole-genome transcriptome analysis revealed potential host plant nuclear targets and the downstream triggered transcriptional responses. We identified and validated a host protein interactors participating in mycorrhization in the host.S. lycopersicum and demonstrated by transcriptomics the effectors possible involvement in different molecular processes, i.e., the regulation of DNA replication, methylglyoxal detoxification, and RNA splicing. We conclude that R. irregularis nuclear-localized effector proteins may act on different pathways to modulate symbiosis and plant physiology and discuss the pros and cons of the tools used.

PMID:38736443 | PMC:PMC11085264 | DOI:10.3389/fpls.2024.1384496

Glob Chang Biol. 2024 May;30(5):e17312. doi: 10.1111/gcb.17312.

ABSTRACT

Biological invasions pose a rapidly expanding threat to the persistence, functioning and service provisioning of ecosystems globally, and to socio-economic interests. The stages of successful invasions are driven by the same mechanism that underlies adaptive changes across species in general-via natural selection on intraspecific variation in traits that influence survival and reproductive performance (i.e., fitness). Surprisingly, however, the rapid progress in the field of invasion science has resulted in a predominance of species-level approaches (such as deny lists), often irrespective of natural selection theory, local adaptation and other population-level processes that govern successful invasions. To address these issues, we analyse non-native species dynamics at the population level by employing a database of European freshwater macroinvertebrate time series, to investigate spreading speed, abundance dynamics and impact assessments among populations. Our findings reveal substantial variability in spreading speed and abundance trends within and between macroinvertebrate species across biogeographic regions, indicating that levels of invasiveness and impact differ markedly. Discrepancies and inconsistencies among species-level risk screenings and real population-level data were also identified, highlighting the inherent challenges in accurately assessing population-level effects through species-level assessments. In recognition of the importance of population-level assessments, we urge a shift in invasive species management frameworks, which should account for the dynamics of different populations and their environmental context. Adopting an adaptive, region-specific and population-focused approach is imperative, considering the diverse ecological contexts and varying degrees of susceptibility. Such an approach could improve and refine risk assessments while promoting mechanistic understandings of risks and impacts, thereby enabling the development of more effective conservation and management strategies.

PMID:38736133 | DOI:10.1111/gcb.17312

Biochimie. 2024 May 10:S0300-9084(24)00103-2. doi: 10.1016/j.biochi.2024.05.010. Online ahead of print.

ABSTRACT

Extrinsic and intrinsic pathological stimuli in vascular disorders induce DNA methylation based epigenetic reprogramming in endothelial cells, leads to perturbed gene expression and subsequently results in endothelial dysfunction (ED). ED is also characterized by release of exosomes with altered proteome leading to paracrine interactions in vasculature and subsequently contributing to manifestation, progression and severity of vascular complications. However, epigenetic regulation of exosome proteome is not known. Hence, our present study aimed to understand influence of DNA methylation on exosome proteome composition and their influence on endothelial cell (EC) function. DNMT isoforms (DNMT1, DNMT3A, and DNMT3B) were overexpressed using lentivirus in ECs. Exosomes were isolated from all groups, as well as from ECs and C57BL/6 mice treated with 5-aza-2'-deoxycytidine. 3D spheroid assay was performed to understand the influence of exosomes derived from cells overexpressing DNMTs on EC functions. Further, the exosomes were subjected to TMT labelled proteomics analysis followed by validation.3D spheroid assay showed increase in the pro-angiogenic activity in response to exosomes derived from overexpressing cells which was impeded by inclusion of 5-aza-2'-deoxycytidine. Our results showed that exosome proteome and PTMs are significantly modulated and are associated with dysregulation of vascular homeostasis, metabolism, inflammation and endothelial cell functions. In vitro and in vivo validation showed elevated DNMT1 and TGF-β1 exosome proteins due to DNMT1 and DNMT3A overexpression, not DNMT3B which was mitigated by 5-aza-2'-deoxycytidine indicating epigenetic regulation. Further, exosomes induced ED as evidenced by reduced expression of phospho-eNOSser1177. Our study unveils epigenetically regulated exosome proteins, aiding management of vascular complications.

PMID:38735570 | DOI:10.1016/j.biochi.2024.05.010