J Cell Biol. 2024 Oct 7;223(10):e202310022. doi: 10.1083/jcb.202310022. Epub 2024 Jul 1.

ABSTRACT

The diverse roles of the dynein motor in shaping microtubule networks and cargo transport complicate in vivo analysis of its functions significantly. To address this issue, we have generated a series of missense mutations in Drosophila Dynein heavy chain. We show that mutations associated with human neurological disease cause a range of defects, including impaired cargo trafficking in neurons. We also describe a novel microtubule-binding domain mutation that specifically blocks the metaphase-anaphase transition during mitosis in the embryo. This effect is independent from dynein's canonical role in silencing the spindle assembly checkpoint. Optical trapping of purified dynein complexes reveals that this mutation only compromises motor performance under load, a finding rationalized by the results of all-atom molecular dynamics simulations. We propose that dynein has a novel function in anaphase progression that depends on it operating in a specific load regime. More broadly, our work illustrates how in vivo functions of motors can be dissected by manipulating their mechanical properties.

PMID:38949648 | DOI:10.1083/jcb.202310022

Phys Biol. 2024 Jul 1. doi: 10.1088/1478-3975/ad5d6c. Online ahead of print.

ABSTRACT

Complexity in biology is often described using a multi-map hierarchical architecture, where the genotype, representing the encoded information, is mapped to the functional level, known as the phenotype, which is then connected to a latent phenotype we refer to as fitness. This underlying architecture governs the processes driving evolution. Furthermore, natural selection, along with other neutral forces, can, in turn, modify these maps. At each level, variation is observed. Here, I propose the need to establish principles that can aid in understanding the transformation of variation within this multi-map architecture. Specifically, I will introduce three, related to the presence of modulators, constraints, and the modular channeling of variation. By comprehending these design principles in various biological systems, we can gain better insights into the mechanisms underlying these maps and how they ultimately contribute to evolutionary dynamics.

PMID:38949447 | DOI:10.1088/1478-3975/ad5d6c

Analyst. 2024 Jul 1. doi: 10.1039/d4an00762j. Online ahead of print.

ABSTRACT

Axillary malodour is caused by the microbial conversion of human-derived precursors to volatile organic compounds. Thiols strongly contribute to this odour but are hard to detect as they are present at low concentrations. Additionally, thiols are highly volatile and small making sampling and quantification difficult, including by gas chromatography-mass spectrometry. In this study, surface-enhanced Raman scattering (SERS), combined with chemometrics, was utilised to simultaneously quantify four malodourous thiols associated with axillary odour, both in individual and multiplex solutions. Univariate and multivariate methods of partial least squares regression (PLS-R) were used to calculate the limit of detection (LoD) and results compared. Both methods yielded comparable LoD values, with LoDs using PLS-R ranging from 0.0227 ppm to 0.0153 ppm for the thiols studied. These thiols were then examined and quantified simultaneously in 120 mixtures using PLS-R. The resultant models showed high linearity (Q2 values between 0.9712 and 0.9827 for both PLS-1 and PLS-2) and low values of root mean squared error of predictions (0.0359 ppm and 0.0459 ppm for PLS-1 and PLS-2, respectively). To test this approach further, these models were challenged with 15 new blind test samples, collected independently from the initial samples. This test demonstrated that SERS combined with PLS-R could be used to predict the unknown concentrations of these thiols in a mixture. These results display the ability of SERS for the simultaneous multiplex detection and quantification of analytes and its potential for future development for detecting gaseous thiols produced from skin and other body sites.

PMID:38948950 | DOI:10.1039/d4an00762j

F1000Res. 2023 Oct 9;12:1222. doi: 10.12688/f1000research.140456.2. eCollection 2023.

ABSTRACT

Tyrosine-protein kinase SYK, encoded by the SYK gene, is a non-receptor type protein kinase which mediates immune signal transduction through immunoreceptors. Tyrosine-protein kinase SYK expression has been associated with the development of various inflammatory diseases, cancer and neurodegenerative conditions. The reproducibility of tyrosine-protein kinase SYK research would help elucidate the mechanism in which it causes neuroinflammation as well as its potential as a novel target to treat Alzheimer's disease. This would be facilitated with the availability of high-quality tyrosine-protein kinase SYK. In this study, we characterized thirteen tyrosine-protein kinase SYK commercial antibodies for Western Blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. We identified many high-performing antibodies and encourage readers to use this report as a guide to select the most appropriate antibody for their specific needs.

PMID:38948505 | PMC:PMC11214040 | DOI:10.12688/f1000research.140456.2

Heliyon. 2024 Jun 3;10(12):e32304. doi: 10.1016/j.heliyon.2024.e32304. eCollection 2024 Jun 30.

ABSTRACT

BACKGROUND: Several respiratory infections outbreaks have been observed in mainland China after reduction of non-pharmaceutical interventions. Other countries have seen increases in respiratory infections outside typical seasons post-COVID-19, warranting investigation into underlying causes.

METHODS: We established monitoring networks for suspected respiratory infection in 14 tertiary hospitals nationwide. PCR for SARS-CoV-2, influenza A and B were performed on 3708 respiratory specimens and deep sequencing were conducted to identify co-infections or newly emerging microbes in 2023. Viral evolutionary analysis was completed. We retrospectively detected serum antibody level for various respiratory pathogens from 4324 adults without respiratory infections over 7 years to observe its dynamic curves.

FINDINGS: SARS-CoV-2 and influenza A were the main pathogens during outbreaks in 2023, bacterial-virus and bacterial-bacterial co-infections were most detected, but community co-infections didn't significantly increase pneumonia incidence. Different SARS-CoV-2 and influenza variants were present in different outbreaks, and no novel pathogens were found. The epidemiological patterns of influenza A, COVID-19 and etc. were altered, exhibiting characteristics of being "staggered" compared to most global regions, and potentially led to "overlapping prevalence". Binding antibody testing showed regular fluctuation, without significant decrease against common respiratory pathogens in adults. Influenza A antibody stimulation was attenuated during the 2023 outbreak.

CONCLUSIONS: "Misaligned" alteration in seasonal respiratory disease patterns possibly caused combined epidemics, leading to cases spike in China, 2023. In adults, antibody levels didn't show significant decline, but reduced immune response to influenza during 2020-2023 emphasizes the need for consistent vaccination during pandemics.

PMID:38948033 | PMC:PMC11209019 | DOI:10.1016/j.heliyon.2024.e32304

Bioinform Adv. 2024 Jun 26;4(1):vbae090. doi: 10.1093/bioadv/vbae090. eCollection 2024.

ABSTRACT

MOTIVATION: In recent years, applying computational modeling to systems biology has caused a substantial surge in both discovery and practical applications and a significant shift in our understanding of the complexity inherent in biological systems.

RESULTS: In this perspective article, we briefly overview computational modeling in biology, highlighting recent advancements such as multi-scale modeling due to the omics revolution, single-cell technology, and integration of artificial intelligence and machine learning approaches. We also discuss the primary challenges faced: integration, standardization, model complexity, scalability, and interdisciplinary collaboration. Lastly, we highlight the contribution made by the Computational Modeling of Biological Systems (SysMod) Community of Special Interest (COSI) associated with the International Society of Computational Biology (ISCB) in driving progress within this rapidly evolving field through community engagement (via both in person and virtual meetings, social media interactions), webinars, and conferences.

AVAILABILITY AND IMPLEMENTATION: Additional information about SysMod is available at https://sysmod.info.

PMID:38948011 | PMC:PMC11213628 | DOI:10.1093/bioadv/vbae090

iScience. 2024 May 21;27(6):110062. doi: 10.1016/j.isci.2024.110062. eCollection 2024 Jun 21.

ABSTRACT

As a research infrastructure with a mission to provide services for bioinformatics, ELIXIR aims to identify and inform its target audiences. Here, we present a survey on a community of researchers studying the environment with omics approaches in Greece, one of the youngest member countries of ELIXIR. Personal interviews followed by quantitative and qualitative analysis were employed to document interactions and practices of the community and to perform a gap analysis for the transition toward multiomics and systems biology. Environmental omics in Greece mostly concerns production of data, in large majority on microbes and non-model organisms. Our survey highlighted (1) the popularity and suitability of targeted hands-on training events; (2) data quality and management issues as important elements for the transition to multiomics, and (3) lack of knowledge and misconceptions regarding interoperability, metadata standards, and pre-registration. The publicly available collected answers represent a valuable resource in view of future strategic planning.

PMID:38947499 | PMC:PMC11214481 | DOI:10.1016/j.isci.2024.110062

ACS Cent Sci. 2024 Feb 26;10(6):1156-1166. doi: 10.1021/acscentsci.3c01245. eCollection 2024 Jun 26.

ABSTRACT

A systematic strategy to develop dual-warhead inhibitors is introduced to circumvent the limitations of conventional covalent inhibitors such as vulnerability to mutations of the corresponding nucleophilic residue. Currently, all FDA-approved covalent small molecules feature one electrophile, leaving open a facile route to acquired resistance. We conducted a systematic analysis of human proteins in the protein data bank to reveal ∼400 unique targets amendable to dual covalent inhibitors, which we term "molecular bidents". We demonstrated this strategy by targeting two kinases: MKK7 and EGFR. The designed compounds, ZNL-8162 and ZNL-0056, are ATP-competitive inhibitors that form two covalent bonds with cysteines and retain potency against single cysteine mutants. Therefore, molecular bidents represent a new pharmacological modality with the potential for improved selectivity, potency, and drug resistance profile.

PMID:38947214 | PMC:PMC11212140 | DOI:10.1021/acscentsci.3c01245

Plant Biotechnol J. 2024 Jun 30. doi: 10.1111/pbi.14423. Online ahead of print.

NO ABSTRACT

PMID:38946243 | DOI:10.1111/pbi.14423

J Chem Inf Model. 2024 Jun 30. doi: 10.1021/acs.jcim.4c00546. Online ahead of print.

ABSTRACT

Enhancers are a class of noncoding DNA, serving as crucial regulatory elements in governing gene expression by binding to transcription factors. The identification of enhancers holds paramount importance in the field of biology. However, traditional experimental methods for enhancer identification demand substantial human and material resources. Consequently, there is a growing interest in employing computational methods for enhancer prediction. In this study, we propose a two-stage framework based on deep learning, termed CapsEnhancer, for the identification of enhancers and their strengths. CapsEnhancer utilizes chaos game representation to encode DNA sequences into unique images and employs a capsule network to extract local and global features from sequence "images". Experimental results demonstrate that CapsEnhancer achieves state-of-the-art performance in both stages. In the first and second stages, the accuracy surpasses the previous best methods by 8 and 3.5%, reaching accuracies of 94.5 and 95%, respectively. Notably, this study represents the pioneering application of computer vision methods to enhancer identification tasks. Our work not only contributes novel insights to enhancer identification but also provides a fresh perspective for other biological sequence analysis tasks.

PMID:38946113 | DOI:10.1021/acs.jcim.4c00546

J Dairy Sci. 2024 Jun 28:S0022-0302(24)00968-8. doi: 10.3168/jds.2024-24780. Online ahead of print.

ABSTRACT

Widespread genotyping has enabled the identification of putative recessive mutations that affect fertility through early embryonic fetal loss, or compromise neonate or calf viability. The use of artificial insemination in the global dairy population can rapidly spread these harmful mutations, and testing for multiple mutations can become relatively expensive if not all tests are available on the same SNP panel. However, it is possible to provide heifer and cow predicted carrier status to farmers at no additional cost if the animals are genotyped with a standard SNP panel. Additionally, for defects where the causal mutation is unknown, but a haplotype of markers has been associated with the defect, the carrier status can be predicted based on that haplotype. The aims of this study were 3-fold: 1) to determine the accuracy of imputation of putative causal mutations for recessive deleterious conditions in Australian dairy cattle, 2) to impute carrier status for known recessive deleterious conditions in all genotyped Australian Holstein, Jersey and Red breed cows, and 3) to determine the changes in carrier frequencies across time for these recessive deleterious mutations. We used the F1 statistic, combining precision and recall, to assess the accuracy of carrier status prediction. We showed that known deleterious mutations can be accurately imputed in Australian Holstein and Jersey cattle that are not directly genotyped for the causal mutation, with F1 ranging between 0.88 and 0.99. For recessive deleterious conditions not included on the standard Australian SNP panel, carrier status could be predicted using a marker haplotype, with F1 ranging from 0.91 to 0.92. Most putative causals and haplotypes were either stable with a low carrier percentage or had a declining carrier percentage. However, several recessive mutations showed a relatively high or increasing percentage, highlighting the importance of detecting carriers to reduce the number of at risk matings. Furthermore, the high carrier percentage of the recently identified Bovine Lymphocyte Intestinal Retention Defect (BLIRD) mutation emphasizes the importance of detection of novel mutations.

PMID:38945256 | DOI:10.3168/jds.2024-24780

Lancet Healthy Longev. 2024 Jul;5(7):e480-e492. doi: 10.1016/S2666-7568(24)00092-8.

ABSTRACT

BACKGROUND: Together with environmental factors, intrinsic capacity (the composite of all the physical and mental capacities of an individual) has been proposed as a marker of healthy ageing. However, whether intrinsic capacity predicts major clinical outcomes is unclear. We aimed to explore the association of intrinsic capacity with functional decline and mortality in older adults.

METHODS: In this systematic review and meta-analysis, we conducted a systematic search in MEDLINE (via PubMed), Scopus, and Web of Science from database inception to Feb 14, 2024, of observational longitudinal studies conducted in older adults (age ≥60 years) assessing the association of intrinsic capacity with impairment in basic activities of daily living (BADL) or instrumental activities of daily living (IADL) or risk of mortality. Estimates were extracted by two reviewers (JLS-S and W-HL) and were pooled using three-level meta-analytic models. The quality of each study was independently assessed by two authors (JLS-S and PLV) using the Newcastle-Ottawa Scale for longitudinal studies. Heterogeneity was evaluated using the I2 indicator at two levels: within-study (level 2) and between-study (level 3) variation. For associations between intrinsic capacity and IADL and BADL, we transformed data (standardised β coefficients and odds ratios [ORs]) into Pearson product moment correlation coefficients (r) using Pearson and Digby formulas to allow comparability across studies. For associations between intrinsic capacity and risk of mortality, hazard ratios (HRs) with 95% CIs were extracted from survival analyses. This study is registered with PROSPERO, CRD42023460482.

FINDINGS: We included 37 studies (206 693 participants; average age range 65·3-85·9 years) in the systematic review, of which 31 were included in the meta-analysis on the association between intrinsic capacity and outcomes; three studies (2935 participants) were included in the meta-analysis on the association between intrinsic capacity trajectories and longitudinal changes in BADL or IADL. Intrinsic capacity was inversely associated with longitudinal impairments in BADL (Pearson's r -0·12 [95% CI -0·19 to -0·04]) and IADL (-0·24 [-0·35 to -0·13]), as well as with mortality risk (hazard ratio 0·57 [95% CI 0·51 to 0·63]). An association was also found between intrinsic capacity trajectories and impairment in IADL (but not in BADL), with maintained or improved intrinsic capacity over time associated with a lower impairment in IADL (odds ratio 0·37 [95% CI 0·19 to 0·71]). There was no evidence of publication bias (Egger's test p>0·05) and there was low between-study heterogeneity (I2=18·4%), though within-study (I2=63·2%) heterogeneity was substantial.

INTERPRETATION: Intrinsic capacity is inversely associated with functional decline and mortality risk in older adults. These findings could support the use of intrinsic capacity as a marker of healthy ageing, although further research is needed to refine the structure and operationalisation of this construct across settings and populations.

FUNDING: None.

TRANSLATIONS: For the Spanish and French translations of the abstract see Supplementary Materials section.

PMID:38945130 | DOI:10.1016/S2666-7568(24)00092-8

Exp Mol Med. 2024 Jul 1. doi: 10.1038/s12276-024-01277-0. Online ahead of print.

ABSTRACT

The senescence of alveolar type II (AT2) cells impedes self-repair of the lung epithelium and contributes to lung injury in the setting of idiopathic pulmonary fibrosis (IPF). Yes-associated protein 1 (YAP1) is essential for cell growth and organ development; however, the role of YAP1 in AT2 cells during pulmonary fibrosis is still unclear. YAP1 expression was found to be downregulated in the AT2 cells of PF patients. Deletion of YAP1 in AT2 cells resulted in lung injury, exacerbated extracellular matrix (ECM) deposition, and worsened lung function. In contrast, overexpression of YAP1 in AT2 cells promoted alveolar regeneration, mitigated pulmonary fibrosis, and improved lung function. In addition, overexpression of YAP1 alleviated bleomycin (BLM) -induced senescence of alveolar epithelial cells both in vivo and in vitro. Moreover, YAP1 promoted the expression of peroxiredoxin 3 (Prdx3) by directly interacting with TEAD1. Forced expression of Prdx3 inhibited senescence and improved mitochondrial dysfunction in BLM-treated MLE-12 cells, whereas depletion of Prdx3 partially abrogated the protective effect of YAP1. Furthermore, overexpression of Prdx3 facilitated self-repair of the injured lung and reduced ECM deposition, while silencing Prdx3 attenuated the antifibrotic effect of YAP1. In conclusion, this study demonstrated that YAP1 alleviates lung injury and pulmonary fibrosis by regulating Prdx3 expression to improve mitochondrial dysfunction and block senescence in AT2 cells, revealing a potential novel therapeutic strategy for pulmonary fibrosis.

PMID:38945958 | DOI:10.1038/s12276-024-01277-0

Int J Biol Macromol. 2024 Jun 26:133395. doi: 10.1016/j.ijbiomac.2024.133395. Online ahead of print.

ABSTRACT

Probiotics offer numerous beneficial functions for human bodies, while the low survival rate under gastric acid and short retention time in the intestine are the major obstacles to their utilization. To address these issues, we designed a novel dual-network hydrogel microsphere that combines gastric acid resistance with enhanced mucoadhesion, aiming for the targeted delivery of probiotics. Thiolated oxidized guar gum (SOGG) was disulfide-linked to form the first network, and sodium alginate (SA) was cross-linked with Ca2+ to form the second network. Under the protection of the interpenetrating dual network microspheres, a much higher viability of Lactobacillus rhamnosus (LGG) (8.73 log CFU/mL) was achieved in simulated gastric fluid, compared to the zero-survival rate of free LGG. Mucoadhesion tests showed that the adhesion rate of SOGG/SA microspheres to the intestinal mucosa was 1.75 times higher than that of thiol-free microspheres. In vivo studies revealed that LGG-loaded microspheres significantly enhanced intestinal barrier function, remodeled the gut microbiome, and alleviated DSS-induced colitis in mice. Overall, SOGG/SA microspheres provide an effective strategy to the challenges of probiotic reduction in the stomach and rapid expulsion from the intestines, enhancing their health benefits.

PMID:38945718 | DOI:10.1016/j.ijbiomac.2024.133395

Lancet. 2024 Jun 29;403(10446):2779-2780. doi: 10.1016/S0140-6736(24)01082-1.

NO ABSTRACT

PMID:38944517 | DOI:10.1016/S0140-6736(24)01082-1

Comp Biochem Physiol A Mol Integr Physiol. 2024 Jun 27:111688. doi: 10.1016/j.cbpa.2024.111688. Online ahead of print.

ABSTRACT

Respirometry is an important tool for understanding whole-animal energy and water balance in relation to the environment. Consequently, the growing number of studies using respirometry over the last decade warrants reliable reporting and data sharing for effective dissemination and research synthesis. We provide a checklist guideline on five key sections to facilitate the transparency, reproducibility, and replicability of respirometry studies: 1) materials, set up, plumbing, 2) subject conditions/maintenance, 3) measurement conditions, 4) data processing, and 5) data reporting and statistics, each with explanations and example studies. Transparency in reporting and data availability has benefits on multiple fronts. Authors can use this checklist to design and report on their study, and reviewers and editors can use the checklist to assess the reporting quality of the manuscripts they review. Improved standards for reporting will enhance the value of primary studies and will greatly facilitate the ability to carry out higher quality research syntheses to address ecological and evolutionary theories.

PMID:38944270 | DOI:10.1016/j.cbpa.2024.111688

Biotechnol Adv. 2024 Jun 27:108400. doi: 10.1016/j.biotechadv.2024.108400. Online ahead of print.

ABSTRACT

Constraint-based modeling (CBM) has evolved as the core systems biology tool to map the interrelations between genotype, phenotype, and external environment. The recent advancement of high-throughput experimental approaches and multi-omics strategies has generated a plethora of new and precise information from wide-ranging biological domains. On the other hand, the continuously growing field of machine learning (ML) and its specialized branch of deep learning (DL) provide essential computational architectures for decoding complex and heterogeneous biological data. In recent years, both multi-omics and ML have assisted in the escalation of CBM. Condition-specific omics data, such as transcriptomics and proteomics, helped contextualize the model prediction while analyzing a particular phenotypic signature. At the same time, the advanced ML tools have eased the model reconstruction and analysis to increase the accuracy and prediction power. However, the development of these multi-disciplinary methodological frameworks mainly occurs independently, which limits the concatenation of biological knowledge from different domains. Hence, we have reviewed the potential of integrating multi-disciplinary tools and strategies from various fields, such as synthetic biology, CBM, omics, and ML, to explore the biochemical phenomenon beyond the conventional biological dogma. How the integrative knowledge of these intersected domains has improved bioengineering and biomedical applications has also been highlighted. We categorically explained the conventional genome-scale metabolic model (GEM) reconstruction tools and their improvement strategies through ML paradigms. Further, the crucial role of ML and DL in omics data restructuring for GEM development has also been briefly discussed. Finally, the case-study-based assessment of the state-of-the-art method for improving biomedical and metabolic engineering strategies has been elaborated. Therefore, this review demonstrates how integrating experimental and in silico strategies can help map the ever-expanding knowledge of biological systems driven by condition-specific cellular information. This multiview approach will elevate the application of ML-based CBM in the biomedical and bioengineering fields for the betterment of society and the environment.

PMID:38944218 | DOI:10.1016/j.biotechadv.2024.108400

J Biol Chem. 2024 Jun 27:107508. doi: 10.1016/j.jbc.2024.107508. Online ahead of print.

ABSTRACT

In the Neurospora circadian system, the White Collar Complex (WCC) formed by WC-1 and WC-2 drives expression of the frequency (frq) gene whose product FRQ feedbacks to inhibit transcriptional activity of WCC. Phosphorylation of WCC has been extensively studied, but the extent and significance of other post-translational modifications (PTM) has been poorly studied. To this end, we used mass-spectrometry to study alkylation sites on WCC, resulting in discovery of nine acetylation sites. Mutagenesis analysis showed most of the acetylation events individually do not play important roles in period determination. Moreover, mutating all the lysines falling in either half of WC-1 or all the lysine residues in WC-2 to arginines did not abolish circadian rhythms. In addition, we also found nine mono-methylation sites on WC-1, but like acetylation, individual ablation of most of the mono-methylation events did not result in a significant period change. Taken together, the data here suggest that acetylation or mono-methylation on WCC is not a determinant of the pace of the circadian feedback loop. The finding is consistent with a model in which repression of WCC's circadian activity is controlled mainly by phosphorylation. Interestingly, light-induced expression of some light-responsive genes has been modulated in certain wc-1 acetylation mutants, suggesting that WC-1 acetylation events differentially regulate light responses.

PMID:38944116 | DOI:10.1016/j.jbc.2024.107508

Int J Biol Macromol. 2024 Jun 27:133314. doi: 10.1016/j.ijbiomac.2024.133314. Online ahead of print.

ABSTRACT

The tumor suppressor p53 plays important roles in suppressing the development and progression of cancer by responding to various stress signals. In addition, p53 can regulate the metabolic pathways of cancer cells by regulating energy metabolism and oxidative phosphorylation. Here, we present a mechanism for the interaction between p53 and ZNF568. Initially, we used X-ray crystallography to determine the irregular loop structure of the ZNF568 KRAB domain; this loop plays an important role in the interaction between p53 and ZNF568. In addition, Cryo-EM was used to examine how the p53 DBD and ZNF568 KRAB domains bind together. The function of ZNF568 on p53-mediated mitochondrial respiration was confirmed by measuring glucose consumption and lactate production. These findings show that ZNF568 can reduce p53-mediated mitochondrial respiratory activity by binding to p53 and inhibiting the transcription of SCO2. SIGNIFICANCE: ZNF568 can directly bind to the p53 DBD and transcriptionally regulate the SCO2 gene. SCO2 transcriptional regulation by interaction between ZNF568 and p53 may regulate the balance between mitochondrial respiration and glycolysis.

PMID:38944084 | DOI:10.1016/j.ijbiomac.2024.133314

Transl Oncol. 2024 Jun 28;47:102046. doi: 10.1016/j.tranon.2024.102046. Online ahead of print.

ABSTRACT

Tumor derived Extracellular vesicles (EVs) in circulating system may contain tumor-specific markers, and EV detection in body fluids could become an important tool for early tumor diagnosis, prognosis assessment. Meningiomas are the most common benign intracranial tumors, few studies have revealed specific protein markers for meningiomas from patients' body fluids. In this study, using proximity labeling technology and non-tumor patient plasma as a control, we detected protein levels of EVs in plasma samples from meningioma patients before and after surgery. Through bioinformatics analysis, we discovered that the levels of EV count and protein count in meningioma patients were significantly higher than those in healthy controls, and were significantly decreased postoperatively. Among EV proteins in meningioma patients, the levels of MUC1, SIGLEC11, E-Cadherin, KIT, and TASCTD2 were found not only significantly elevated than those in healthy controls, but also significantly decreased after tumor resection. Moreover, using publicly available GEO databases, we verified that the mRNA level of MUC1, SIGLEC11, and CDH1 in meningiomas were significantly higher in comparison with normal dura mater tissues. Additionally, by analyzing human meningioma specimens collected in this study, we validated the protein levels of MUC1 and SIGLEC11 were significantly increased in WHO grade 2 meningiomas and were positively correlated with tumor proliferation levels. This study indicates that meningiomas secret EV proteins into circulating system, which may serve as specific markers for diagnosis, malignancy predicting and tumor recurrent assessment.

PMID:38943923 | DOI:10.1016/j.tranon.2024.102046