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Bioinformatics (Oxford, England) Jun 2024Phenotype-based drug screening emerges as a powerful approach for identifying compounds that actively interact with cells. Transcriptional and proteomic profiling of...
SUMMARY
Phenotype-based drug screening emerges as a powerful approach for identifying compounds that actively interact with cells. Transcriptional and proteomic profiling of cell lines and individual cells provide insights into the cellular state alterations that occur at the molecular level in response to external perturbations, such as drugs or genetic manipulations. In this paper, we propose cycleCDR, a novel deep learning framework to predict cellular response to external perturbations. We leverage the autoencoder to map the unperturbed cellular states to a latent space, in which we postulate the effects of drug perturbations on cellular states follow a linear additive model. Next, we introduce the cycle consistency constraints to ensure that unperturbed cellular state subjected to drug perturbation in the latent space would produces the perturbed cellular state through the decoder. Conversely, removal of perturbations from the perturbed cellular states can restore the unperturbed cellular state. The cycle consistency constraints and linear modeling in the latent space enable to learn transferable representations of external perturbations, so that our model can generalize well to unseen drugs during training stage. We validate our model on four different types of datasets, including bulk transcriptional responses, bulk proteomic responses, and single-cell transcriptional responses to drug/gene perturbations. The experimental results demonstrate that our model consistently outperforms existing state-of-the-art methods, indicating our method is highly versatile and applicable to a wide range of scenarios.
AVAILABILITY AND IMPLEMENTATION
The source code is available at: https://github.com/hliulab/cycleCDR.
Topics: Single-Cell Analysis; Humans; Deep Learning; Computational Biology; Proteomics
PubMed: 38940153
DOI: 10.1093/bioinformatics/btae248 -
Bioinformatics (Oxford, England) Jun 2024Multimodal profiling strategies promise to produce more informative insights into biomedical cohorts via the integration of the information each modality contributes. To...
MOTIVATION
Multimodal profiling strategies promise to produce more informative insights into biomedical cohorts via the integration of the information each modality contributes. To perform this integration, however, the development of novel analytical strategies is needed. Multimodal profiling strategies often come at the expense of lower sample numbers, which can challenge methods to uncover shared signals across a cohort. Thus, factor analysis approaches are commonly used for the analysis of high-dimensional data in molecular biology, however, they typically do not yield representations that are directly interpretable, whereas many research questions often center around the analysis of pathways associated with specific observations.
RESULTS
We develop PathFA, a novel approach for multimodal factor analysis over the space of pathways. PathFA produces integrative and interpretable views across multimodal profiling technologies, which allow for the derivation of concrete hypotheses. PathFA combines a pathway-learning approach with integrative multimodal capability under a Bayesian procedure that is efficient, hyper-parameter free, and able to automatically infer observation noise from the data. We demonstrate strong performance on small sample sizes within our simulation framework and on matched proteomics and transcriptomics profiles from real tumor samples taken from the Swiss Tumor Profiler consortium. On a subcohort of melanoma patients, PathFA recovers pathway activity that has been independently associated with poor outcome. We further demonstrate the ability of this approach to identify pathways associated with the presence of specific cell-types as well as tumor heterogeneity. Our results show that we capture known biology, making it well suited for analyzing multimodal sample cohorts.
AVAILABILITY AND IMPLEMENTATION
The tool is implemented in python and available at https://github.com/ratschlab/path-fa.
Topics: Humans; Bayes Theorem; Proteomics; Factor Analysis, Statistical; Gene Expression Profiling; Melanoma; Algorithms; Computational Biology
PubMed: 38940152
DOI: 10.1093/bioinformatics/btae216 -
Journal of Integrative Neuroscience Jun 2024The effects of heat acclimation (HA) on the hypothalamus after exertional heatstroke (EHS) and the specific mechanism have not been fully elucidated, and this study...
BACKGROUND
The effects of heat acclimation (HA) on the hypothalamus after exertional heatstroke (EHS) and the specific mechanism have not been fully elucidated, and this study aimed to address these questions.
METHODS
In the present study, rats were randomly assigned to the control, EHS, HA, or HA + EHS groups (n = 9). Hematoxylin and eosin (H&E) staining was used to examine pathology. Tandem mass tag (TMT)-based proteomic analysis was utilized to explore the impact of HA on the protein expression profile of the hypothalamus after EHS. Bioinformatics analysis was used to predict the functions of the differentially expressed proteins. The differential proteins were validated by western blotting. An enzyme-linked immunosorbent assay was used to measure the expression levels of inflammatory cytokines in the serum.
RESULTS
The H&E staining (n = 5) results revealed that there were less structural changes in hypothalamus in the HA + EHS group compared with the EHS group. Proteomic analysis (n = 4) revealed that proinflammatory proteins such as argininosuccinate synthetase (ASS1), high mobility group protein B2 (HMGB2) and vimentin were evidently downregulated in the HA + EHS group. The levels of interleukin (IL)-1β, IL-1, and IL-8 were decreased in the serum samples (n = 3) from HA + EHS rats.
CONCLUSIONS
HA may alleviate hypothalamic damage caused by heat attack by inhibiting inflammatory activities, and ASS1, HMGB2 and vimentin could be candidate factors involved in the exact mechanism.
Topics: Animals; Hypothalamus; Heat Stroke; Rats; Proteomics; Male; Rats, Sprague-Dawley; Physical Exertion; Disease Models, Animal
PubMed: 38940089
DOI: 10.31083/j.jin2306116 -
Journal of Extracellular Biology Feb 2024Colon cancer is one of the most commonly occurring tumours among both women and men, and over the past decades the incidence has been on the rise. As such, the need for...
Colon cancer is one of the most commonly occurring tumours among both women and men, and over the past decades the incidence has been on the rise. As such, the need for biomarker identification as well as an understanding of the underlying disease mechanism has never been greater. Extracellular vesicles are integral mediators of cell-to-cell communication and offer a unique opportunity to study the machinery that drives disease progression, and they also function as vectors for potential biomarkers. Tumour tissue and healthy mucosal tissue from the colons of ten patients were used to isolate tissue-resident EVs that were subsequently subjected to global quantitative proteomic analysis through LC-MS/MS. In total, more than 2000 proteins were identified, with most of the common EV markers being among them. Bioinformatics revealed a clear underrepresentation of proteins involved in energy production and cellular adhesion in tumour EVs, while proteins involved in protein biosynthesis were overrepresented. Additionally, 53 membrane proteins were found to be significantly upregulated in tumour EVs. Among them were several proteins with enzymatic functions that degrade the extracellular matrix, and three of these, Fibroblast activating factor (FAP), Cell surface hyaluronidase (CEMIP2), as well as Ephrin receptor B3 (EPHB3), were validated and found to be consistent with the global quantitative results. These stark differences in the proteomes between healthy and cancerous tissue emphasise the importance of the interstitial vesicle secretome as a major player of disease development.
PubMed: 38939898
DOI: 10.1002/jex2.127 -
Frontiers in Pharmacology 2024Mesaconitine (MA), a diester-diterpenoid alkaloid extracted from the medicinal herb , is commonly used to treat various diseases. Previous studies have indicated the...
Mesaconitine (MA), a diester-diterpenoid alkaloid extracted from the medicinal herb , is commonly used to treat various diseases. Previous studies have indicated the potent toxicity of aconitum despite its pharmacological activities, with limited understanding of its effects on the nervous system and the underlying mechanisms. HT22 cells and zebrafish were used to investigate the neurotoxic effects of MA both and , employing multi-omics techniques to explore the potential mechanisms of toxicity. Our results demonstrated that treatment with MA induces neurotoxicity in zebrafish and HT22 cells. Subsequent analysis revealed that MA induced oxidative stress, as well as structural and functional damage to mitochondria in HT22 cells, accompanied by an upregulation of mRNA and protein expression related to autophagic and lysosomal pathways. Furthermore, methylated RNA immunoprecipitation sequencing (MeRIP-seq) showed a correlation between the expression of autophagy-related genes and N6-methyladenosine (m6A) modification following MA treatment. In addition, we identified METTL14 as a potential regulator of m6A methylation in HT22 cells after exposure to MA. Our study has contributed to a thorough mechanistic elucidation of the neurotoxic effects caused by MA, and has provided valuable insights for optimizing the rational utilization of traditional Chinese medicine formulations containing aconitum in clinical practice.
PubMed: 38939838
DOI: 10.3389/fphar.2024.1393717 -
Current Stem Cell Reports Jun 2023The underlying molecular mechanisms that direct stem cell differentiation into fully functional, mature cells remain an area of ongoing investigation. Cell state is the...
PURPOSE OF REVIEW
The underlying molecular mechanisms that direct stem cell differentiation into fully functional, mature cells remain an area of ongoing investigation. Cell state is the product of the combinatorial effect of individual factors operating within a coordinated regulatory network. Here, we discuss the contribution of both gene regulatory and splicing regulatory networks in defining stem cell fate during differentiation and the critical role of protein isoforms in this process.
RECENT FINDINGS
We review recent experimental and computational approaches that characterize gene regulatory networks, splice regulatory networks, and the resulting transcriptome and proteome they mediate during differentiation. Such approaches include long-read RNA sequencing, which has demonstrated high-resolution profiling of mRNA isoforms, and Cas13-based CRISPR, which could make possible high-throughput isoform screening. Collectively, these developments enable systems-level profiling of factors contributing to cell state.
SUMMARY
Overall, gene and splice regulatory networks are important in defining cell state. The emerging high-throughput systems-level approaches will characterize the gene regulatory network components necessary in driving stem cell differentiation.
PubMed: 38939410
DOI: 10.1007/s40778-023-00227-2 -
Journal of Extracellular Biology Dec 2023Extracellular vesicles (EVs) are important mediators of intercellular communication involved in local and long-range signalling of cancer metastasis. The onset of...
Extracellular vesicles (EVs) are important mediators of intercellular communication involved in local and long-range signalling of cancer metastasis. The onset of invasion is the key step of the metastatic cascade, but the secretion of EVs has remained unexplored at that stage due to technical challenges. In this study, we present a platform to track EVs over the course of invasive development of human prostate cancer cell (PC3) tumoroids utilizing in vivo-mimicking extracellular matrix-based 3D cultures. Using this EV production method, combined with proteomic profiling, we show that PC3 tumoroids secrete EVs with previously undefined protein cargo. Intriguingly, an increase in EV amounts and extensive changes in the EV protein composition were detected upon invasive transition of the tumoroids. The changes in EV protein cargo were counteracted by chemical inhibition of invasion. These results reveal the impact of the tumoroids' invasive status on EV secretion and cargo, and highlight the necessity of in vivo-mimicking conditions for uncovering novel cancer-derived EV components.
PubMed: 38938900
DOI: 10.1002/jex2.124 -
Breast Cancer Research : BCR Jun 2024Circular RNAs (circRNAs) are a new group of endogenous RNAs recently found to be involved in the development of various diseases, including their confirmed involvement...
Circular RNAs (circRNAs) are a new group of endogenous RNAs recently found to be involved in the development of various diseases, including their confirmed involvement in the progression of several types of cancers. Unluckily, the abnormal expression and functions of circRNAs in breast cancer shall be further investigated. This work aims to elucidate the action and molecular mechanism of circHSDL2 in the malignant progression of breast cancer. Differential expression profiles of circRNAs in breast cancer tissues relative to normal breast tissues and in the exosomes of breast cancer patients compared to healthy women were analyzed from databases to identify potentially functional circRNAs. CircHSDL2 was selected for further investigation. Cell proliferation, migration and invasion assays were done to assess the effect of circHSDL2 overexpression on breast cancer cells. Bioinformatics test and dual-luciferase reporter experiments were done to explore the interaction between circHSDL2 and miRNA. Downstream target genes were further investigated through proteomics analysis and Western blotting. The influence of circHSDL2 on breast cancer in vivo was evaluated through xenograft experiments in nude mice. Functional analysis demonstrated circHSDL2 overexpression promoted the division, movement, and invasion of breast cancer cells both in vivo and in vitro. Mechanistically, circHSDL2 acted as a sponge for miR-7978 to affect ZNF704 expression and thereby regulate the Hippo pathway in breast cancer cells. In conclusion, circHSDL2 regulates the Hippo pathway through the miR-7978/ZNF704 axis to facilitate the malignancy of breast cancer. This may be a potential biomarker and treatment target.
Topics: Humans; Female; Breast Neoplasms; RNA, Circular; MicroRNAs; Hippo Signaling Pathway; Animals; Mice; Protein Serine-Threonine Kinases; Signal Transduction; Cell Proliferation; Gene Expression Regulation, Neoplastic; Disease Progression; Cell Line, Tumor; Cell Movement; Mice, Nude
PubMed: 38937788
DOI: 10.1186/s13058-024-01864-z -
BMC Cancer Jun 2024Ubiquitin-specific peptidase 10 (USP10), a typical de-ubiquitinase, has been found to play a double-edged role in human cancers. Previously, we reported that the...
OBJECTIVE
Ubiquitin-specific peptidase 10 (USP10), a typical de-ubiquitinase, has been found to play a double-edged role in human cancers. Previously, we reported that the expression of USP10 was negatively correlated with the depth of gastric wall invasion, lymph node metastasis, and prognosis in gastric cancer (GC) patients. However, it remains unclear whether USP10 can regulate the metastasis of GC cells through its de-ubiquitination function.
METHODS
In this study, proteome, ubiquitinome, and transcriptome analyses were conducted to comprehensively identify novel de-ubiquitination targets for USP10 in GC cells. Subsequently, a series of validation experiments, including in vitro cell culture studies, in vivo metastatic tumor models, and clinical sample analyses, were performed to elucidate the regulatory mechanism of USP10 and its de-ubiquitination targets in GC metastasis.
RESULTS
After overexpression of USP10 in GC cells, 146 proteins, 489 ubiquitin sites, and 61 mRNAs exhibited differential expression. By integrating the results of multi-omics, we ultimately screened 9 potential substrates of USP10, including TNFRSF10B, SLC2A3, CD44, CSTF2, RPS27, TPD52, GPS1, RNF185, and MED16. Among them, TNFRSF10B was further verified as a direct de-ubiquitination target for USP10 by Co-IP and protein stabilization assays. The dysregulation of USP10 or TNFRSF10B affected the migration and invasion of GC cells in vitro and in vivo models. Molecular mechanism studies showed that USP10 inhibited the epithelial-mesenchymal transition (EMT) process by increasing the stability of TNFRSF10B protein, thereby regulating the migration and invasion of GC cells. Finally, the retrospective clinical sample studies demonstrated that the downregulation of TNFRSF10B expression was associated with poor survival among 4 of 7 GC cohorts, and the expression of TNFRSF10B protein was significantly negatively correlated with the incidence of distant metastasis, diffuse type, and poorly cohesive carcinoma.
CONCLUSIONS
Our study established a high-throughput strategy for screening de-ubiquitination targets for USP10 and further confirmed that inhibiting the ubiquitination of TNFRSF10B might be a promising therapeutic strategy for GC metastasis.
Topics: Stomach Neoplasms; Humans; Ubiquitin Thiolesterase; Ubiquitination; Mice; Animals; Cell Line, Tumor; Cell Movement; Gene Expression Regulation, Neoplastic; Female; Male; Neoplasm Metastasis; Gene Expression Profiling; Epithelial-Mesenchymal Transition; Prognosis; Multiomics
PubMed: 38937694
DOI: 10.1186/s12885-024-12549-3 -
Scientific Reports Jun 2024The association of postpartum cardiac reverse remodeling (RR) with urinary proteome, particularly in pregnant women with cardiovascular (CV) risk factors who show...
The association of postpartum cardiac reverse remodeling (RR) with urinary proteome, particularly in pregnant women with cardiovascular (CV) risk factors who show long-term increased risk of cardiovascular disease and mortality is unknown. We aim to profile the urinary proteome in pregnant women with/without CV risk factors to identify proteins associated with postpartum RR. Our study included a prospective cohort of 32 healthy and 27 obese and/or hypertensive and/or diabetic pregnant women who underwent transthoracic echocardiography, pulse-wave-velocity, and urine collection at the 3rd trimester and 6 months postpartum. Shotgun HPLC-MS/MS profiled proteins. Generalized linear mixed-effects models were used to identify associations between urinary proteins and left ventricle mass (LVM), a surrogate of RR. An increase in arterial stiffness was documented from 3rd trimester to 6 months after delivery, being significantly elevated in women with CV risk factors. In addition, the presence of at least one CV risk factor was associated with worse LVM RR. We identified 6 and 11 proteins associated with high and low LVM regression, respectively. These proteins were functionally linked with insulin-like growth factor (IGF) transport and uptake regulation by IGF binding-proteins, platelet activation, signaling and aggregation and the immune system's activity. The concentration of IGF-1 in urine samples was associated with low LVM regression after delivery. Urinary proteome showed a predicting potential for identifying pregnant women with incomplete postpartum RR.
Topics: Humans; Female; Pregnancy; Adult; Proteome; Postpartum Period; Ventricular Remodeling; Prospective Studies; Biomarkers; Vascular Stiffness; Echocardiography; Risk Factors
PubMed: 38937573
DOI: 10.1038/s41598-024-65612-1