Appl Biochem Biotechnol. 2023 Sep 18. doi: 10.1007/s12010-023-04595-7. Online ahead of print.

ABSTRACT

Globally, lung cancer contributes significantly to the public health burden-associated mortality. As this form of cancer is insidious in nature, there is an inevitable diagnostic delay leading to chronic tumor development. Non-small cell lung cancer (NSCLC) constitutes 80-85% of all lung cancer cases, making this neoplasia form a prevalent subset of lung carcinoma. One of the most vital aspects for proper diagnosis, prognosis, and adequate therapy is the precise classification of non-small cell lung cancer based on biomarker expression profiling. This form of biomarker profiling has provided opportunities for improvements in patient stratification, mechanistic insights, and probable druggable targets. However, numerous patients have exhibited numerous toxic side effects, tumor relapse, and development of therapy-based chemoresistance. As a result of these exacting situations, there is a dire need for efficient and effective new cancer therapeutics. De novo drug development approach is a costly and tedious endeavor, with an increased attrition rate, attributed, in part, to toxicity-related issues. Drug repurposing, on the other hand, when combined with computer-assisted systems biology approach, provides alternatives to the discovery of new, efficacious, and safe drugs. Therefore, in this review, we focus on a comparison of the conventional therapy-based chemoresistance mechanisms with the repurposed anti-cancer drugs from three different classes-anti-parasitic, anti-depressants, and anti-psychotics for cancer treatment with a primary focus on NSCLC therapeutics. Certainly, amalgamating these novel therapeutic approaches with that of the conventional drug regimen in NSCLC-affected patients will possibly complement/synergize the existing therapeutic modalities. This approach has tremendous translational significance, since it can combat drug resistance and cytotoxicity-based side effects and provides a relatively new strategy for possible application in therapy of individuals with NSCLC.

PMID:37721630 | DOI:10.1007/s12010-023-04595-7

Neurooncol Pract. 2023 May 2;10(5):462-471. doi: 10.1093/nop/npad025. eCollection 2023 Oct.

ABSTRACT

BACKGROUND: 5-aminolevulinic acid (5-ALA) fluorescence-guided resection increases the percentage of complete CNS tumor resections and improves the progression-free survival of IDH-wildtype glioblastoma patients. A small subset of IDH-wildtype glioblastoma shows no 5-ALA fluorescence. An explanation for these cases is missing. In this study, we used DNA methylation profiling to further characterize non-fluorescent glioblastomas.

METHODS: Patients with newly diagnosed and recurrent IDH-wildtype glioblastoma that underwent surgery were analyzed. The intensity of intraoperative 5-ALA fluorescence was categorized as non-visible or visible. DNA was extracted from tumors and genome-wide DNA methylation patterns were analyzed using Illumina EPIC (850k) arrays. Furthermore, 5-ALA intensity was measured by flow cytometry on human gliomasphere lines (BT112 and BT145).

RESULTS: Of 74 included patients, 12 (16.2%) patients had a non-fluorescent glioblastoma, which were compared to 62 glioblastomas with 5-ALA fluorescence. Clinical characteristics were equally distributed between both groups. We did not find significant differences between DNA methylation subclasses and 5-ALA fluorescence (P = .24). The distribution of cells of the tumor microenvironment was not significantly different between the non-fluorescent and fluorescent tumors. Copy number variations in EGFR and simultaneous EGFRvIII expression were strongly associated with 5-ALA fluorescence since all non-fluorescent glioblastomas were EGFR-amplified (P < .01). This finding was also demonstrated in recurrent tumors. Similarly, EGFR-amplified glioblastoma cell lines showed no 5-ALA fluorescence after 24 h of incubation.

CONCLUSIONS: Our study demonstrates an association between non-fluorescent IDH-wildtype glioblastomas and EGFR gene amplification which should be taken into consideration for recurrent surgery and future studies investigating EGFR-amplified gliomas.

PMID:37720395 | PMC:PMC10502788 | DOI:10.1093/nop/npad025

Front Bioeng Biotechnol. 2023 Aug 29;11:1217811. doi: 10.3389/fbioe.2023.1217811. eCollection 2023.

ABSTRACT

High-throughput genetic screening is frequently employed to rapidly associate gene with phenotype and establish sequence-function relationships. With the advent of CRISPR technology, and the ability to functionally interrogate previously genetically recalcitrant organisms, non-model organisms can be investigated using pooled guide RNA (gRNA) libraries and sequencing-based assays to quantitatively assess fitness of every targeted locus in parallel. To aid the construction of pooled gRNA assemblies, we have developed an in silico design workflow for gRNA selection using the gRNA Sequence Region Extraction Tool (gRNA-SeqRET). Built upon the previously developed CCTop, gRNA-SeqRET enables automated, scalable design of gRNA libraries that target user-specified regions or whole genomes of any prokaryote or eukaryote. Additionally, gRNA-SeqRET automates the bulk extraction of any regions of sequence relative to genes or other features, aiding in the design of homology arms for insertion or deletion constructs. We also assess in silico the application of a designed gRNA library to other closely related genomes and demonstrate that for very closely related organisms Average Nucleotide Identity (ANI) > 95% a large fraction of the library may be of relevance. The gRNA-SeqRET web application pipeline can be accessed at https://grna.jgi.doe.gov. The source code is comprised of freely available software tools and customized Python scripts, and is available at https://bitbucket.org/berkeleylab/grnadesigner/src/master/ under a modified BSD open-source license (https://bitbucket.org/berkeleylab/grnadesigner).

PMID:37720317 | PMC:PMC10502169 | DOI:10.3389/fbioe.2023.1217811

iScience. 2023 Jul 24;26(10):107463. doi: 10.1016/j.isci.2023.107463. eCollection 2023 Oct 20.

ABSTRACT

Nasopharyngeal carcinoma (NPC) is known for high curability during early stage of the disease, and early diagnosis relies on nasopharyngeal endoscopy and subsequent pathological biopsy. To enhance the early diagnosis rate by aiding physicians in the real-time identification of NPC and directing biopsy site selection during endoscopy, we assembled a dataset comprising 2,429 nasopharyngeal endoscopy video frames from 690 patients across three medical centers. With these data, we developed a deep learning-based NPC detection model using the you only look once (YOLO) network. Our model demonstrated high performance, with precision, recall, mean average precision, and F1-score values of 0.977, 0.943, 0.977, and 0.960, respectively, for internal test set and 0.825, 0.743, 0.814, and 0.780 for external test set at 0.5 intersection over union. Remarkably, our model demonstrated a high inference speed (52.9 FPS), surpassing the average frame rate (25.0 FPS) of endoscopy videos, thus making real-time detection in endoscopy feasible.

PMID:37720094 | PMC:PMC10502364 | DOI:10.1016/j.isci.2023.107463

Cell Genom. 2023 Aug 18;3(9):100382. doi: 10.1016/j.xgen.2023.100382. eCollection 2023 Sep 13.

ABSTRACT

Genetic variants affecting gene expression levels in humans have been mapped in the Genotype-Tissue Expression (GTEx) project. Trans-acting variants impacting many genes simultaneously through a shared transcription factor (TF) are of particular interest. Here, we developed a generalized linear model (GLM) to estimate protein-level TF activity levels in an individual-specific manner from GTEx RNA sequencing (RNA-seq) profiles. It uses observed differential gene expression after TF perturbation as a predictor and, by analyzing differential expression within pairs of neighboring genes, controls for the confounding effect of variation in chromatin state along the genome. We inferred genotype-specific activities for 55 TFs across 49 tissues. Subsequently performing genome-wide association analysis on this virtual trait revealed TF activity quantitative trait loci (aQTLs) that, as a set, are enriched for functional features. Altogether, the set of tools we introduce here highlights the potential of genetic association studies for cellular endophenotypes based on a network-based multi-omics approach. The transparent peer review record is available.

PMID:37719147 | PMC:PMC10504674 | DOI:10.1016/j.xgen.2023.100382

Bio Protoc. 2023 Sep 5;13(17):e4797. doi: 10.21769/BioProtoc.4797. eCollection 2023 Sep 5.

ABSTRACT

Drug biotransformation by the host microbiome can impact the therapeutic success of treatment. In the context of cancer, drug degradation can take place within the microenvironment of the targeted tumor by intratumor bacteria. In pancreatic cancer, increased chemo-resistance against the frontline chemotherapy gemcitabine is thought to arise from drug degradation by the tumor microbiome. This bacterial-drug interaction highlights the need for developing rapid assays for monitoring bacterial gemcitabine breakdown. While chemical approaches such as high-performance liquid chromatography are suitable for this task, they require specialized equipment and expertise and are limited in throughput. Functional cell-based assays represent an alternate approach for performing this task. We developed a functional assay to monitor the rate of bacterial gemcitabine breakdown using a highly sensitive bacterial reporter strain. Our method relies on standard laboratory equipment and can be implemented at high throughput to monitor drug breakdown by hundreds of strains simultaneously. This functional assay can be readily adapted to monitor degradation of other drugs. Key features Quantification of gemcitabine breakdown by incubating bacteria that degrades the drug and subsequently testing the growth of a reporter strain on filtered supernatant. Use of an optimized reporter strain that was genetically engineered to be a non-degrader strain and highly sensitive to gemcitabine. A high-throughput assay performed in microplates that can be adjusted for identifying bacteria with a fast or slow gemcitabine degradation rate. The assay results can be compared to results from a standard curve with known drug concentrations to quantify degradation rate.

PMID:37719072 | PMC:PMC10501921 | DOI:10.21769/BioProtoc.4797

Front Oncol. 2023 Aug 31;13:1230382. doi: 10.3389/fonc.2023.1230382. eCollection 2023.

ABSTRACT

PURPOSE: Chemotherapy is pivotal in the multimodal treatment of pancreatic ductal adenocarcinoma (PDAC). Technical advances unveiled a high degree of inter- and intratumoral heterogeneity. We hypothesized that intratumoral heterogeneity (ITH) impacts response to gemcitabine treatment and demands specific targeting of resistant subclones.

METHODS: Using single cell-derived cell lines (SCDCLs) from the classical cell line BxPC3 and the basal-like cell line Panc-1, we addressed the effect of ITH on response to gemcitabine treatment.

RESULTS: Individual SCDCLs of both parental tumor cell populations showed considerable heterogeneity in response to gemcitabine. Unsupervised PCA including the 1,000 most variably expressed genes showed a clustering of the SCDCLs according to their respective sensitivity to gemcitabine treatment for BxPC3, while this was less clear for Panc-1. In BxPC3 SCDCLs, enriched signaling pathways EMT, TNF signaling via NfKB, and IL2STAT5 signaling correlated with more resistant behavior to gemcitabine. In Panc-1 SCDCLs MYC targets V1 and V2 as well as E2F targets were associated with stronger resistance. We used recursive feature elimination for Feature Selection in order to compute sets of proteins that showed strong association with the response to gemcitabine. The optimal protein set calculated for Panc-1 comprised fewer proteins in comparison to the protein set determined for BxPC3. Based on molecular profiles, we could show that the gemcitabine-resistant SCDCLs of both BxPC3 and Panc-1 are more sensitive to the BET inhibitor JQ1 compared to the respective gemcitabine-sensitive SCDCLs.

CONCLUSION: Our model system of SCDCLs identified gemcitabine-resistant subclones and provides evidence for the critical role of ITH for treatment response in PDAC. We exploited molecular differences as the basis for differential response and used these for more targeted therapy of resistant subclones.

PMID:37719017 | PMC:PMC10502231 | DOI:10.3389/fonc.2023.1230382

Nucleic Acids Res. 2023 Sep 18:gkad758. doi: 10.1093/nar/gkad758. Online ahead of print.

ABSTRACT

Modular cloning has become a benchmark technology in synthetic biology. However, a notable disparity exists between its remarkable development and the need for standardization to facilitate seamless interoperability among systems. The field is thus impeded by an overwhelming proliferation of organism-specific systems that frequently lack compatibility. To overcome these issues, we present Golden Standard (GS), a Type IIS assembly method underpinned by the Standard European Vector Architecture. GS unlocks modular cloning applications for most bacteria, and delivers combinatorial multi-part assembly to create genetic circuits of up to twenty transcription units (TUs). Reliance on MoClo syntax renders GS fully compatible with many existing tools and it sets the path towards efficient reusability of available part libraries and assembled TUs. GS was validated in terms of DNA assembly, portability, interoperability and phenotype engineering in α-, β-, γ- and δ-proteobacteria. Furthermore, we provide a computational pipeline for parts characterization that was used to assess the performance of GS parts. To promote community-driven development of GS, we provide a dedicated web-portal including a repository of parts, vectors, and Wizard and Setup tools that guide users in designing constructs. Overall, GS establishes an open, standardized framework propelling the progress of synthetic biology as a whole.

PMID:37718823 | DOI:10.1093/nar/gkad758

Light Sci Appl. 2023 Sep 18;12(1):221. doi: 10.1038/s41377-023-01237-9.

ABSTRACT

Optical properties of single emitters can be significantly improved through the interaction with plasmonic structures, leading to enhanced sensing and imaging capabilities. In turn, single emitters can act as sensitive probes of the local electromagnetic field surrounding plasmonic structures, furnishing fundamental insights into their physics and guiding the design of novel plasmonic devices. However, the interaction of emitters in the proximity to a plasmonic nanostructure causes distortion, which hinders precise estimation of position and polarization state and is one of the reasons why detection and quantification of molecular processes yet remain fundamentally challenging in this era of super-resolution. Here, we investigate axially defocused images of a single fluorescent emitter near metallic nanostructure, which encode emitter positions and can be acquired in the far-field with high sensitivity, while analyzing the images with pattern matching algorithm to explore emitter-localized surface plasmon interaction and retrieve information regarding emitter positions. Significant distortion in defocused images of fluorescent beads and quantum dots near nanostructure was observed and analyzed by pattern matching and finite-difference time-domain methods, which revealed that the distortion arises from the emitter interaction with nanostructure. Pattern matching algorithm was also adopted to estimate the lateral positions of a dipole that models an emitter utilizing the distorted defocused images and achieved improvement by more than 3 times over conventional diffraction-limited localization methods. The improvement by defocused imaging is expected to provide a way of enhancing reliability when using plasmonic nanostructure and diversifying strategies for various imaging and sensing modalities.

PMID:37718351 | DOI:10.1038/s41377-023-01237-9

Sci Justice. 2023 Sep;63(5):624-634. doi: 10.1016/j.scijus.2023.07.006. Epub 2023 Jul 24.

ABSTRACT

According to criminal botany, the offender unknowingly carries plant samples from the crime scene. Therefore, studying the genetic data of plants native to the crime scene can solve many ambiguities in the criminal files. In this regard, the aim of this study was to investigate the genome of 5 endemic plants in some areas of Iran with high crime rate. Quercus brantii, Curpressus arizonica, Crataegus pentagyna, Ziziphus Spina-chtista, and Buxus hyrcana were assessed using 1 genetic fragment on plastid regions (trnH-psbA) as well as 1 gene on nuclear chromosome called ITS. The alignment of DNA sequences of trnH-psbA and ITS genes was done using BioEdit, Clustal X, and Muscle v4.0 software programs. The phylogenetic analysis was performed on aligned data using Maximum Parsimony (MP) and the Bayesian methods. The Splits Tree v.4.14.4 software program was used for phylogenetic network analysis. Finally, the data combinability test was conducted using the Incongruence Length Difference (ILD) test by PAUP* software program. All data from nrDNA ITS and trnH-psbA sequences were consistent with Information Compatibility Test (ICT) results. Moreover, the nrDNA ITS indicated more resolved relationship than trnH-psbA. The results from MP and Bayesian analyses did not differ significantly between singular and combined forms, except for a slight variance in confidence interval of branches. As the phylogenetic trees provide more thorough and deeper conception of species relations, it is hoped that they would be useful to illuminate some forensic gaps in regions with high crime rates enriched by these plants, not only in Iran, but also in all areas over the world with this vegetation.

PMID:37718009 | DOI:10.1016/j.scijus.2023.07.006

Pharmacol Ther. 2023 Sep 15:108531. doi: 10.1016/j.pharmthera.2023.108531. Online ahead of print.

ABSTRACT

Glucocorticoids (GCs) are a class of steroid hormones that regulate key physiological processes such as metabolism, immune function, and stress responses. The effects of GCs are mediated by the glucocorticoid receptor (GR), a ligand-dependent transcription factor that activates or represses the expression of hundreds to thousands of genes in a tissue- and physiological state-specific manner. The activity of GR is modulated by numerous coregulator proteins that interact with GR in response to different stimuli assembling into a multitude of DNA-protein complexes and facilitate the integration of these signals, helping GR to communicate with basal transcriptional machinery and chromatin. Here, we provide a brief overview of the physiological and molecular functions of GR, and discuss the roles of GR coregulators in the immune system, key metabolic tissues and the central nervous system. We also present an analysis of the GR interactome in different cells and tissues, which suggests tissue-specific utilization of GR coregulators, despite widespread functions shared by some of them.

PMID:37717739 | DOI:10.1016/j.pharmthera.2023.108531

Metab Eng. 2023 Sep 15:S1096-7176(23)00134-9. doi: 10.1016/j.ymben.2023.09.008. Online ahead of print.

ABSTRACT

An overwhelming number of studies have reported the correlation of decreased abundance of butyrate-producing commensals with a wide range of diseases. However, the molecular-level mechanisms whereby gut butyrate causally affects the host mucosal immunity and pathogenesis were poorly understood, hindered by the lack of efficient tools to control intestinal butyrate. Here we engineered a facultative anaerobic commensal bacterium to delivery butyrate at the intestinal mucosal surface, and implemented it to dissect the causal role of gut butyrate in regulating host intestinal homeostasis in a model of murine chronic colitis. Mechanistically, we show that gut butyrate protected against colitis and preserved intestinal mucosal homeostasis through its inhibiting effect on the key pyroptosis executioner gasdermin D (GSDMD) of colonic epithelium, via functioning as an HDAC3 inhibitor. Overall, our work presents a new avenue to build synthetic living delivery bacteria to decode causal molecules at the host-microbe interface with molecular-level insights.

PMID:37717646 | DOI:10.1016/j.ymben.2023.09.008

Mol Plant Microbe Interact. 2023 Sep 17. doi: 10.1094/MPMI-03-23-0029-R. Online ahead of print.

ABSTRACT

We report a public resource for examining the spatiotemporal RNA expression of 54,893 M. truncatula genes during the first 72 hours of response to rhizobial inoculation. Using a methodology that allows synchronous inoculation and growth of over 100 plants in a single media container, we harvested the same segment of each root responding to rhizobia in the initial inoculation over a time course, collected individual tissues from these segments with laser capture microdissection, and created and sequenced RNA libraries generated from these tissues. We demonstrate the utility of the resource by examining the expression patterns of a set of genes induced very early in nodule signaling, as well as two gene families (CLE peptides and nodule specific PLAT-domain proteins) and show that despite similar whole root expression patterns, there are tissue differences in expression between the genes. Using a rhizobial response data set generated from transcriptomics on intact root segments, we also examined differential temporal expression patterns and determined that, after nodule tissue, the epidermis and cortical cells contained the most temporally patterned genes. We circumscribed gene lists for each time and tissue examined and developed an expression pattern visualization tool. Finally, we explored transcriptomic differences between the inner cortical cells that become nodules and those that do not, confirming that the expression of ACC synthases distinguishes inner cortical cells that become nodules and provide and describe potential downstream genes involved in early nodule cell division.

PMID:37717250 | DOI:10.1094/MPMI-03-23-0029-R

J Invest Dermatol. 2023 Sep 14:S0022-202X(23)02575-7. doi: 10.1016/j.jid.2023.08.018. Online ahead of print.

ABSTRACT

Opportunities to improve the clinical management of skin disease are being created by advances in genomic medicine. Large-scale sequencing increasingly challenges notions about single-gene disorders. It is now apparent that monogenic etiologies make appreciable contributions to the population burden of disease and that they are underrecognized in clinical practice. A genetic diagnosis informs on molecular pathology and may direct targeted treatments and tailored prevention strategies for patients and family members. It also generates knowledge about disease pathogenesis and management that is relevant to patients without pathogenic mutations. Inborn Errors of Immunity (IEI) are a large class of monogenic etiologies that have been well studied and contribute to the population burden of inflammatory diseases. To further delineate contributions of IEI to the pathogenesis of skin disease, we performed a set of analyses that identified 316 IEI associated with skin pathologies, including common skin diseases. This data suggests that clinical sequencing is underutilized in dermatology. We next use these data to derive a network that illuminates the molecular relationships of these disorders and suggests an underlying etiological organization to immune-mediated skin disease. Our results motivate the further development of a molecularly derived and data-driven reorganization of clinical diagnoses of skin disease.

PMID:37716649 | DOI:10.1016/j.jid.2023.08.018

Curr Biol. 2023 Sep 6:S0960-9822(23)01141-7. doi: 10.1016/j.cub.2023.08.061. Online ahead of print.

ABSTRACT

The evolution of roots allowed vascular plants to adapt to land environments. Fossil evidence indicates that roots evolved independently in euphyllophytes (ferns and seed plants) and lycophytes, the two lineages of extant vascular plants. Based on a high-quality genome assembly, mRNA sequencing (mRNA-seq) data, and single-cell RNA-seq data for the lycophyte Selaginella kraussiana, we show that the two root origin events in lycophytes and euphyllophytes adopted partially similar molecular modules in the regulation of root apical meristem (RAM) development. In S. kraussiana, the RAM initiates from the rhizophore primordium guided by auxin and duplicates itself by dichotomous branching. The auxin signaling pathway directly upregulates euAINTEGUMENTAb (SkeuANTb), and then SkeuANTb directly promotes the expression of SkeuANTa and the WUSCHEL-RELATED HOMEOBOX13b (SkWOX13b) for RAM maintenance, partially similar to the molecular pathway involving the euANT-branch PLETHORA (AtPLT) genes and AtWOX5 in root initiation in the seed plant Arabidopsis thaliana. Other molecular modules, e.g., SHORT-ROOT and SCARECROW, also have partially similar expression patterns in the RAMs of S. kraussiana and A. thaliana. Overall, our study not only provides genome and transcriptome tools of S. kraussiana but also indicates the employment of some common molecular modules in RAMs during root origins in lycophytes and euphyllophytes.

PMID:37716350 | DOI:10.1016/j.cub.2023.08.061

Plant J. 2023 Sep 16. doi: 10.1111/tpj.16465. Online ahead of print.

ABSTRACT

Tree growth and survival are dependent on their ability to perceive signals, integrate them, and trigger timely and fitted molecular and growth responses. While ectomycorrhizal symbiosis is a predominant tree-microbe interaction in forest ecosystems, little is known about how and to what extent it helps trees cope with environmental changes. We hypothesized that the presence of Laccaria bicolor influences abiotic cue perception by Populus trichocarpa and the ensuing signaling cascade. We submitted ectomycorrhizal or non-ectomycorrhizal P. trichocarpa cuttings to short-term cessation of watering or ozone fumigation to focus on signaling networks before the onset of any physiological damage. Poplar gene expression, metabolite levels, and hormone levels were measured in several organs (roots, leaves, mycorrhizas) and integrated into networks. We discriminated the signal responses modified or maintained by ectomycorrhization. Ectomycorrhizas buffered hormonal changes in response to short-term environmental variations systemically prepared the root system for further fungal colonization and alleviated part of the root abscisic acid (ABA) signaling. The presence of ectomycorrhizas in the roots also modified the leaf multi-omics landscape and ozone responses, most likely through rewiring of the molecular drivers of photosynthesis and the calcium signaling pathway. In conclusion, P. trichocarpa-L. bicolor symbiosis results in a systemic remodeling of the host's signaling networks in response to abiotic changes. In addition, ectomycorrhizal, hormonal, metabolic, and transcriptomic blueprints are maintained in response to abiotic cues, suggesting that ectomycorrhizas are less responsive than non-mycorrhizal roots to abiotic challenges.

PMID:37715981 | DOI:10.1111/tpj.16465

Am J Hum Biol. 2023 Sep 16:e23983. doi: 10.1002/ajhb.23983. Online ahead of print.

ABSTRACT

BACKGROUND: The current knowledge about the molecular mechanisms underlying the health benefits of exercise is still limited, especially in childhood. We set out to investigate the effects of a 20-week exercise intervention on whole-blood transcriptome profile (RNA-seq) in children with overweight/obesity.

METHODS: Twenty-four children (10.21 ± 1.33 years, 46% girls) with overweight/obesity, were randomized to either a 20-week exercise program (intervention group; n = 10), or to a no-exercise control group (n = 14). Whole-blood transcriptome profile was analyzed using RNA-seq by STRT technique with GlobinLock technology.

RESULTS: Following the 20-week exercise intervention program, 161 genes were differentially expressed between the exercise and the control groups among boys, and 121 genes among girls (p-value <0.05), while after multiple correction, no significant difference between exercise and control groups persisted in gene expression profiles (FDR >0.05). Genes enriched in GO processes and molecular pathways showed different immune response in boys (antigen processing and presentation, infections, and T cell receptor complex) and in girls (Fc epsilon RI signaling pathway) (FDR <0.05).

CONCLUSION: These results suggest that 20-week exercise intervention program alters the molecular pathways involved in immune processes in children with overweight/obesity.

PMID:37715654 | DOI:10.1002/ajhb.23983

Biomol Biomed. 2023 Sep 15. doi: 10.17305/bb.2023.9629. Online ahead of print.

ABSTRACT

High mortality and morbidity rates associated with ST-elevation myocardial infarction (STEMI) and post-STEMI heart failure (HF) necessitate proper risk stratification for coronary artery disease (CAD). A prediction model that combines specificity and convenience is highly required. This study aimed to design a monocyte-based gene assay for predicting STEMI and post-STEMI HF. A total of 1,956 monocyte expression profiles and corresponding clinical data were integrated from multiple sources. Meta-results were obtained through the weighted gene co-expression network analysis (WGCNA) and differential analysis to identify characteristic genes for STEMI. Machine learning models based on the decision tree (DT), support vector machine (SVM), and random forest (RF) algorithms were trained and validated. Five genes overlapped and were subjected to the model proposal. The discriminative performance of the DT model outperformed the other two methods. The established four-gene panel (HLA-J, CFP, STX11, and NFYC) could discriminate STEMI and HF with an area under the curve (AUC) of 0.86 or above. In the gene set enrichment analysis (GSEA), several cardiac pathogenesis pathways and cardiovascular disorder signatures showed statistically significant, concordant differences between subjects with high and low expression levels of the four-gene panel, affirming the validity of the established model. In conclusion, we have developed and validated a model that offers the hope for accurately predicting the risk of STEMI and HF, leading to optimal risk stratification and personalized management of CAD, thereby improving individual outcomes.

PMID:37715537 | DOI:10.17305/bb.2023.9629

BMC Bioinformatics. 2023 Sep 15;24(1):344. doi: 10.1186/s12859-023-05416-8.

ABSTRACT

BACKGROUND: Understanding the Mechanism of Action (MoA) of a compound is an often challenging but equally crucial aspect of drug discovery that can help improve both its efficacy and safety. Computational methods to aid MoA elucidation usually either aim to predict direct drug targets, or attempt to understand modulated downstream pathways or signalling proteins. Such methods usually require extensive coding experience and results are often optimised for further computational processing, making them difficult for wet-lab scientists to perform, interpret and draw hypotheses from.

RESULTS: To address this issue, we in this work present MAVEN (Mechanism of Action Visualisation and Enrichment), an R/Shiny app which allows for GUI-based prediction of drug targets based on chemical structure, combined with causal reasoning based on causal protein-protein interactions and transcriptomic perturbation signatures. The app computes a systems-level view of the mechanism of action of the input compound. This is visualised as a sub-network linking predicted or known targets to modulated transcription factors via inferred signalling proteins. The tool includes a selection of MSigDB gene set collections to perform pathway enrichment on the resulting network, and also allows for custom gene sets to be uploaded by the researcher. MAVEN is hence a user-friendly, flexible tool for researchers without extensive bioinformatics or cheminformatics knowledge to generate interpretable hypotheses of compound Mechanism of Action.

CONCLUSIONS: MAVEN is available as a fully open-source tool at https://github.com/laylagerami/MAVEN with options to install in a Docker or Singularity container. Full documentation, including a tutorial on example data, is available at https://laylagerami.github.io/MAVEN .

PMID:37715141 | DOI:10.1186/s12859-023-05416-8

Nat Rev Genet. 2023 Sep 15. doi: 10.1038/s41576-023-00644-3. Online ahead of print.

ABSTRACT

Genomic imprinting refers to the parent-of-origin expression of genes, which originates from epigenetic events in the mammalian germ line. The evolution of imprinting may reflect a conflict over resource allocation early in life, with silencing of paternal genes in offspring soliciting increased maternal provision and silencing of maternal genes limiting demands on the mother. Parental caregiving has been identified as an area of potential conflict, with several imprinted genes serendipitously found to directly influence the quality of maternal care. Recent systems biology approaches, based on single-cell RNA sequencing data, support a more deliberate relationship, which is reinforced by the finding that imprinted genes expressed in the offspring influence the quality of maternal caregiving. These bidirectional, reiterative relationships between parents and their offspring are critical both for short-term survival and for lifelong wellbeing, with clear implications for human health.

PMID:37714957 | DOI:10.1038/s41576-023-00644-3