Cancers (Basel). 2023 Nov 3;15(21):5284. doi: 10.3390/cancers15215284.

ABSTRACT

PURPOSE: Cell migration is a critical driver of metastatic tumor spread, contributing significantly to cancer-related mortality. Yet, our understanding of the underlying mechanisms remains incomplete.

METHODS: In this study, a wound healing assay was employed to investigate cancer cell migratory behavior, with the aim of utilizing migration as a biomarker for invasiveness. To gain a comprehensive understanding of this complex system, we developed a computational model based on cellular automata (CA) and rigorously calibrated and validated it using in vitro data, including both tumoral and non-tumoral cell lines. Harnessing this CA-based framework, extensive numerical experiments were conducted and supported by local and global sensitivity analyses in order to identify the key biological parameters governing this process.

RESULTS: Our analyses led to the formulation of a power law equation derived from just a few input parameters that accurately describes the governing mechanism of wound healing. This groundbreaking research provides a powerful tool for the pharmaceutical industry. In fact, this approach proves invaluable for the discovery of novel compounds aimed at disrupting cell migration, assessing the efficacy of prospective drugs designed to impede cancer invasion, and evaluating the immune system's responses.

PMID:37958456 | DOI:10.3390/cancers15215284

Plant Genome. 2023 Nov 13:e20402. doi: 10.1002/tpg2.20402. Online ahead of print.

ABSTRACT

Temperatures below or above optimal growth conditions are among the major stressors affecting productivity, end-use quality, and distribution of key staple crops including rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays L.). Among temperature stresses, cold stress induces cellular changes that cause oxidative stress and slowdown metabolism, limit growth, and ultimately reduce crop productivity. Perception of cold stress by plant cells leads to the activation of cold-responsive transcription factors and downstream genes, which ultimately impart cold tolerance. The response triggered in crops to cold stress includes gene expression/suppression, the accumulation of sugars upon chilling, and signaling molecules, among others. Much of the information on the effects of cold stress on perception, signal transduction, gene expression, and plant metabolism are available in the model plant Arabidopsis but somewhat lacking in major crops. Hence, a complete understanding of the molecular mechanisms by which staple crops respond to cold stress remain largely unknown. Here, we make an effort to elaborate on the molecular mechanisms employed in response to low-temperature stress. We summarize the effects of cold stress on the growth and development of these crops, the mechanism of cold perception, and the role of various sensors and transducers in cold signaling. We discuss the progress in cold tolerance research at the genome, transcriptome, proteome, and metabolome levels and highlight how these findings provide opportunities for designing cold-tolerant crops for the future.

PMID:37957947 | DOI:10.1002/tpg2.20402

Biol Sex Differ. 2023 Nov 13;14(1):82. doi: 10.1186/s13293-023-00568-x.

NO ABSTRACT

PMID:37957715 | DOI:10.1186/s13293-023-00568-x

BMC Genomics. 2023 Nov 13;24(1):681. doi: 10.1186/s12864-023-09764-w.

ABSTRACT

BACKGROUND: Microbial community played an essential role in ecosystem processes, be it mangrove wetland or other intertidal ecologies. Several enzymatic activities like hydrolases are effective ecological indicators of soil microbial function. So far, little is known on halophilic bacterial contribution and function on a genomic viewpoint of Indian Sundarban Wetland. Considering the above mentioned issues, the aims of this study was to understand the life style, metabolic functionalities and genomic features of the isolated bacterium, Salinicoccus roseus strain RF1H. A comparative genome-based study of S. roseus has not been reported yet. Henceforth, we have considered the inclusion of the intra-species genome comparison of S. roseus to gain insight into the high degree of variation in the genome of strain RF1H among others.

RESULTS: Salinicoccus roseus strain RF1H is a pink-red pigmented, Gram-positive and non-motile cocci. The bacterium exhibited high salt tolerance (up to 15% NaCl), antibiotic resistance, biofilm formation and secretion of extracellular hydrolytic enzymes. The circular genome was approximately 2.62978 Mb in size, encoding 574 predicted genes with GC content 49.5%. Presence of genomic elements (prophages, transposable elements, CRISPR-Cas system) represented bacterial virulence and multidrug-resistance. Furthermore, genes associated with salt tolerance, temperature adaptation and DNA repair system were distributed in 17 genomic islands. Genes related to hydrocarbon degradation manifested metabolic capability of the bacterium for potential biotechnological applications. A comparative pangenome analysis revealed two-component response regulator, modified C4-dicarboxylate transport system and osmotic stress regulated ATP-binding proteins. Presence of genes encoding arginine decarboxylase (ADC) enzyme being involved in biofilm formation was reported from the genome. In silico study revealed the protein is thermostable and made up with ~ 415 amino acids, and hydrophilic in nature. Three motifs appeared to be evolutionary conserved in all Salinicoccus sequences.

CONCLUSION: The first report of whole genome analysis of Salinicoccus roseus strain RF1H provided information of metabolic functionalities, biofilm formation, resistance mechanism and adaptation strategies to thrive in climate-change induced vulnerable spot like Sundarban. Comparative genome analysis highlighted the unique genome content that contributed the strain's adaptability. The biomolecules produced during metabolism are important sources of compounds with potential beneficial applications in pharmaceuticals.

PMID:37957573 | DOI:10.1186/s12864-023-09764-w

Nature. 2023 Nov 13. doi: 10.1038/s41586-023-06832-9. Online ahead of print.

ABSTRACT

AlphaFold2 (AF2) 1 has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein's biological function often depends on multiple conformational substates2, and disease-causing point mutations often cause population changes within these substates3,4. We demonstrate that clustering a multiple sequence alignment (MSA) by sequence similarity enables AF2 to sample alternate states of known metamorphic proteins with high confidence. Using this method, AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protein KaiB5, and found that predictions of both conformations were distributed in clusters across the KaiB-family. We used nuclear magnetic resonance (NMR) spectroscopy to confirm a surprising AF-Cluster prediction: a cyanobacteria KaiB variant is stabilized in the opposite state than the more widely-studied variant. To test AF-Cluster's sensitivity to point mutations, we designed and experimentally verified a set of 3 mutations predicted to flip KaiB from Rhodobacter sphaeroides from the ground to the fold-switched state. Finally, screening for alternate states in protein families without known fold-switching identified a putative alternate state for the oxidoreductase Mpt53 in M. tuberculosis. Further development of such bioinformatic methods in tandem with experiments will likely have profound impact on predicting protein energy landscapes, essential for illuminating biological function.

PMID:37956700 | DOI:10.1038/s41586-023-06832-9

Proc Natl Acad Sci U S A. 2023 Nov 28;120(48):e2310347120. doi: 10.1073/pnas.2310347120. Epub 2023 Nov 13.

ABSTRACT

Many animal and plant species synthesize toxic compounds as deterrent; thus, detection of these compounds is of vital importance to avoid their ingestion. Often, such compounds are recognized by taste 2 receptors that mediate bitter taste in humans. Until now, bitter taste receptors have only been found in bony vertebrates, where they occur as a large family already in coelacanth, a "living fossil" and the earliest-diverging extant lobe-finned fish. Here, we have revisited the evolutionary origin of taste 2 receptors (T2Rs) making use of a multitude of recently available cartilaginous fish genomes. We have identified a singular T2R in 12 cartilaginous fish species (9 sharks, 1 sawfish, and 2 skates), which represents a sister clade to all bony fish T2Rs. We have examined its ligands for two shark species, a catshark and a bamboo shark. The ligand repertoire of bamboo shark represents a subset of that of the catshark, with roughly similar thresholds. Amarogentin, one of the most bitter natural substances for humans, also elicited the highest signal amplitudes with both shark receptors. Other subsets of ligands are shared with basal bony fish T2Rs indicating an astonishing degree of functional conservation over nearly 500 mya of separate evolution. Both shark receptors respond to endogenous steroids as well as xenobiotic compounds, whereas separate receptors exist for xenobiotics both in early- and late-derived bony vertebrates (coelacanth, zebrafish, and human), consistent with the shark T2R reflecting the original ligand repertoire of the ancestral bitter taste receptor at the evolutionary origin of this family.

PMID:37956436 | DOI:10.1073/pnas.2310347120

J Cell Biol. 2023 Dec 4;222(12):e202111151. doi: 10.1083/jcb.202111151. Epub 2023 Nov 13.

ABSTRACT

Current models posit that nuclear speckles (NSs) serve as reservoirs of splicing factors and facilitate posttranscriptional mRNA processing. Here, we discovered that ribotoxic stress induces a profound reorganization of NSs with enhanced recruitment of factors required for splice-site recognition, including the RNA-binding protein TIAR, U1 snRNP proteins and U2-associated factor 65, as well as serine 2 phosphorylated RNA polymerase II. NS reorganization relies on the stress-activated p38 mitogen-activated protein kinase (MAPK) pathway and coincides with splicing activation of both pre-existing and newly synthesized pre-mRNAs. In particular, ribotoxic stress causes targeted excision of retained introns from pre-mRNAs of immediate early genes (IEGs), whose transcription is induced during the stress response. Importantly, enhanced splicing of the IEGs ZFP36 and FOS is accompanied by relocalization of the corresponding nuclear mRNA foci to NSs. Our study reveals NSs as a dynamic compartment that is remodeled under stress conditions, whereby NSs appear to become sites of IEG transcription and efficient cotranscriptional splicing.

PMID:37956386 | DOI:10.1083/jcb.202111151

OMICS. 2023 Nov 14. doi: 10.1089/omi.2023.0122. Online ahead of print.

ABSTRACT

A One Health lens is increasingly significant to address the intertwined challenges in planetary health concerned with the health of humans, nonhuman animals, plants, and ecosystems. A One Health approach can benefit the public health systems in Africa that are overburdened by noncommunicable, infectious, and environmental diseases. Notably, the COVID-19 pandemic revealed the previously overlooked two-fold importance of pharmacogenetics (PGx), for individually tailored treatment of noncommunicable diseases and environmental pathogens. For example, dyslipidemia, a common cardiometabolic risk factor, has been identified as an independent COVID-19 severity risk factor. Observational data suggest that patients with COVID-19 infection receiving lipid-lowering therapy may have better outcomes. However, among African patients, the response to these drugs varies from patient to patient, pointing to the possible contribution of genetic variation in important pharmacogenes. The PGx of lipid-lowering therapies may underlie differences in treatment responses observed among dyslipidemia patients as well as patients comorbid with COVID-19 and dyslipidemia. Genetic variations in APOE, ABCB1, CETP, CYP2C9, CYP3A4, CYP3A5, HMGCR, LDLR, NPC1L1, and SLCO1B1 genes affect the pharmacogenomics of statins, and they have individually been linked to differential responses to dyslipidemia and COVID-19 treatment. African populations are underrepresented in PGx research. This leads to poor accounting of additional diverse genetic variants that could be important in understanding interindividual and between-population variations in therapeutic responses to dyslipidemia and COVID-19. This expert review examines and synthesizes the salient and priority PGx variations, as seen through a One Health lens in Africa, to improve and inform personalized medicine in both dyslipidemia and COVID-19.

PMID:37956269 | DOI:10.1089/omi.2023.0122

PLoS One. 2023 Nov 13;18(11):e0291151. doi: 10.1371/journal.pone.0291151. eCollection 2023.

ABSTRACT

Stochastic population models are widely used to model phenomena in different areas such as cyber-physical systems, chemical kinetics, collective animal behaviour, and beyond. Quantitative analysis of stochastic population models easily becomes challenging due to the combinatorial number of possible states of the population. Moreover, while the modeller easily hypothesises the mechanistic aspects of the model, the quantitative parameters associated to these mechanistic transitions are difficult or impossible to measure directly. In this paper, we investigate how formal verification methods can aid parameter inference for population discrete-time Markov chains in a scenario where only a limited sample of population-level data measurements-sample distributions among terminal states-are available. We first discuss the parameter identifiability and uncertainty quantification in this setup, as well as how the existing techniques of formal parameter synthesis and Bayesian inference apply. Then, we propose and implement four different methods, three of which incorporate formal parameter synthesis as a pre-computation step. We empirically evaluate the performance of the proposed methods over four representative case studies. We find that our proposed methods incorporating formal parameter synthesis as a pre-computation step allow us to significantly enhance the accuracy, precision, and scalability of inference. Specifically, in the case of unidentifiable parameters, we accurately capture the subspace of parameters which is data-compliant at a desired confidence level.

PMID:37956126 | DOI:10.1371/journal.pone.0291151

Adv Anat Embryol Cell Biol. 2023;236:21-55. doi: 10.1007/978-3-031-38215-4_2.

ABSTRACT

The ability to assess various cellular events consequent to perturbations, such as genetic mutations, disease states and therapies, has been recently revolutionized by technological advances in multiple "omics" fields. The resulting deluge of information has enabled and necessitated the development of tools required to both process and interpret the data. While of tremendous value to basic researchers, the amount and complexity of the data has made it extremely difficult to manually draw inference and identify factors key to the study objectives. The challenges of data reduction and interpretation are being met by the development of increasingly complex tools that integrate disparate knowledge bases and synthesize coherent models based on current biological understanding. This chapter presents an example of how genomics data can be integrated with biological network analyses to gain further insight into the developmental consequences of genetic perturbations. State of the art methods for conducting similar studies are discussed along with modern methods used to analyze and interpret the data.

PMID:37955770 | DOI:10.1007/978-3-031-38215-4_2

Elife. 2023 Nov 13;12:e85449. doi: 10.7554/eLife.85449.

ABSTRACT

As a major class of biomolecules, carbohydrates play indispensable roles in various biological processes. However, it remains largely unknown how carbohydrates directly modulate important drug targets, such as G-protein coupled receptors (GPCRs). Here, we employed P2Y purinoceptor 14 (P2Y14), a drug target for inflammation and immune responses, to uncover the sugar nucleotide activation of GPCRs. Integrating molecular dynamics simulation with functional study, we identified the uridine diphosphate (UDP)-sugar-binding site on P2Y14, and revealed that a UDP-glucose might activate the receptor by bridging the transmembrane (TM) helices 2 and 7. Between TM2 and TM7 of P2Y14, a conserved salt bridging chain (K2.60-D2.64-K7.35-E7.36 [KDKE]) was identified to distinguish different UDP-sugars, including UDP-glucose, UDP-galactose, UDP-glucuronic acid, and UDP-N-acetylglucosamine. We identified the KDKE chain as a conserved functional motif of sugar binding for both P2Y14 and P2Y purinoceptor 12 (P2Y12), and then designed three sugar nucleotides as agonists of P2Y12. These results not only expand our understanding for activation of purinergic receptors but also provide insights for the carbohydrate drug development for GPCRs.

PMID:37955640 | DOI:10.7554/eLife.85449

J Am Chem Soc. 2023 Nov 13. doi: 10.1021/jacs.3c07861. Online ahead of print.

ABSTRACT

Amino compounds are widely present in complex mixtures in chemistry, biology, medicine, food, and environmental sciences involving drug impurities and metabolisms of proteins, biogenic amines, neurotransmitters, and pyrimidine in biological systems. Nuclear magnetic resonance (NMR) spectroscopy is an excellent tool for simultaneously identifying and quantifying these in-mixture compounds but has a limit-of-detection (LOD) over several micromolarities (>5 μM). To break such a sensitivity barrier, we developed a sensitive and rapid method by combining the probe-induced sensitivity enhancement and nonuniform-sampling-based 1H-13C HSQC 2D-NMR (PRISE-NUS-HSQC). We introduced two 13CH3 tags for each analyte to respectively increase the 1H and 13C abundances for up to 6 and 200 fold. This enabled high-resolution detection of 0.4-0.8 μM analytes in mixtures in 5 mm tubes with a 5 min acquisition on 600 MHz spectrometers. The method is much more sensitive and faster than traditional 1H-13C HSQC methods (∼50 μM, >10 h). Using sulfanilic acid as a single reference, furthermore, we established a database covering chemical shifts and relative-response factors for >100 compounds, enabling reliable identification and quantification. The method showed good quantitation linearity, accuracy, precision, and applicability in multiple biological matrices, offering a rapid and sensitive approach for quantitative analysis of large cohorts of chemical, medicinal, metabolomic, food, and other mixtures.

PMID:37955622 | DOI:10.1021/jacs.3c07861

J Chem Phys. 2023 Nov 14;159(18):185101. doi: 10.1063/5.0176668.

ABSTRACT

Gastropods forage with their radula, a thin chitinous membrane with embedded teeth, which scratch across the substrate to lose food particles. During this interaction, the risk of loosening particles is obvious without having a specialized mechanism holding them on the tooth surface. As mucus secretions are essential in molluscan life cycles and the locomotion and attachment gels are known to have an instant high adhesion, we have hypothesized that the saliva could support particle retention during feeding. As adhesion of snail saliva was not studied before, we present here an experimental setup to test its particle-binding capacity using a large land snail (Lissachatina fulica, Stylommatophora, Heterobranchia). This experiment was also applied to the gels produced by the snail foot for comparison and can be potentially applied to various fluids present at a small volume in the future. We found, that the saliva has high particle retention capacity that is comparable to the foot glue of the snail. To gain some insight into the properties of the saliva, we additionally studied it in the scanning electron microscope, estimated its viscosity in a de-wetting experiment, and investigated its elemental composition using energy dispersive X-ray spectroscopy reveling higher contents of Ca, Zn and other potential cross-linkers similar to those found in the glue.

PMID:37955324 | DOI:10.1063/5.0176668

Front Pharmacol. 2023 Oct 25;14:1239197. doi: 10.3389/fphar.2023.1239197. eCollection 2023.

ABSTRACT

Background: Cynomorium songaricum Rupr. has long been used as an anti-inflammatory, antidepressant, and anti-aging agent in traditional Chinese medicine in Asia. Its ethyl acetate extract (ECS) has been identified as the main antioxidant component with neuroprotective and estrogen-like effects. However, the potential of ECS in treating depression has not been explored yet. Methods: We identified the primary metabolites in ECS in this study using liquid chromatography-electrospray tandem mass spectrometry (LC-MS/MS). Network analysis was used to find the potential targets and pathways associated with the anti-neuroinflammatory depression action of the ECS. In addition, we established a corticosterone (CORT)-induced depression mouse model to assess ECS's antidepressant effects by monitoring various behavioral changes (e.g., sucrose preference, forced swimming, tail suspension, and open field tests) and biochemical indices of the hippocampus, and validating the network analysis results. Significant pathways underwent verification through western blotting based on network analysis prediction. Results: Our study demonstrates that ECS possesses significant antidepressant activity. The LC-MS/MS analysis of ECS identified 30 main metabolites, including phloridzin, phlorizin, ursolic acid, and naringenin, as well as other flavonoids, terpenoids, and phenolic acids. These metabolites were found to be associated with 64 candidate target proteins related to neuroinflammatory depression from the database, and ten hub proteins were identified through filtration: CXCL8, ICAM1, NOS2, SELP, TNF, IL6, APP, ACHE, MAOA and ADA. Functional enrichment analyses of the candidate targets revealed their primary roles in regulating cytokine production, inflammatory response, cytokine activity, and tumor necrosis factor receptor binding. In vivo, ECS improved hippocampal neuroinflammation in the mouse model. Specifically, ECS reduced the expression of inflammatory factors in the hippocampus, inhibited M1 microglial cell polarization, and alleviated depression through the regulation of the NF-κB-NLRP3 inflammation pathway. Conclusion: Based on experimental and network analysis, this study revealed for the first time that ECS exerted antidepression effect via anti-neuroinflammation. Our research provides valuable information on the use of ECS as an alternative therapeutic approach for depression.

PMID:37954847 | PMC:PMC10634308 | DOI:10.3389/fphar.2023.1239197

NAR Genom Bioinform. 2023 Nov 6;5(4):lqad099. doi: 10.1093/nargab/lqad099. eCollection 2023 Dec.

ABSTRACT

A major challenge in mass spectrometry-based phosphoproteomics lies in identifying the substrates of kinases, as currently only a small fraction of substrates identified can be confidently linked with a known kinase. Machine learning techniques are promising approaches for leveraging large-scale phosphoproteomics data to computationally predict substrates of kinases. However, the small number of experimentally validated kinase substrates (true positive) and the high data noise in many phosphoproteomics datasets together limit their applicability and utility. Here, we aim to develop advanced kinase-substrate prediction methods to address these challenges. Using a collection of seven large phosphoproteomics datasets, and both traditional and deep learning models, we first demonstrate that a 'pseudo-positive' learning strategy for alleviating small sample size is effective at improving model predictive performance. We next show that a data resampling-based ensemble learning strategy is useful for improving model stability while further enhancing prediction. Lastly, we introduce an ensemble deep learning model ('SnapKin') by incorporating the above two learning strategies into a 'snapshot' ensemble learning algorithm. We propose SnapKin, an ensemble deep learning method, for predicting substrates of kinases from large-scale phosphoproteomics data. We demonstrate that SnapKin consistently outperforms existing methods in kinase-substrate prediction. SnapKin is freely available at https://github.com/PYangLab/SnapKin.

PMID:37954574 | PMC:PMC10632189 | DOI:10.1093/nargab/lqad099

Case Rep Womens Health. 2023 Jun 19;39:e00521. doi: 10.1016/j.crwh.2023.e00521. eCollection 2023 Sep.

NO ABSTRACT

PMID:37954226 | PMC:PMC10636260 | DOI:10.1016/j.crwh.2023.e00521

iScience. 2023 Oct 13;26(11):108209. doi: 10.1016/j.isci.2023.108209. eCollection 2023 Nov 17.

ABSTRACT

Type I interferons (IFN-I) are important mediators of antiviral immunity and autoimmune diseases. Female plasmacytoid dendritic cells (pDCs) exert an elevated capacity to produce IFN-I upon toll-like receptor 7 (TLR7) activation compared to male pDCs, and both sex hormones and X-encoded genes have been implicated in these sex-specific differences. Using longitudinal samples from a trans men cohort receiving gender-affirming hormone therapy (GAHT), the impact of testosterone injections on TLR7-mediated IFN-I production by pDCs was assessed. Single-cell RNA analyses of pDCs showed downregulation of IFN-I-related gene expression signatures but also revealed transcriptional inter-donor heterogeneity. Longitudinal quantification showed continuous reduction of IFN-I protein production by pDCs and reduced expression of IFN-I-stimulated genes in peripheral blood mononuclear cells (PBMCs). These studies in trans men demonstrate that testosterone administration reduces IFN-I production by pDCs over time and provide insights into the immune-modulatory role of testosterone in sex-specific IFN-I-mediated immune responses.

PMID:37953956 | PMC:PMC10637924 | DOI:10.1016/j.isci.2023.108209

iScience. 2023 Oct 13;26(11):108181. doi: 10.1016/j.isci.2023.108181. eCollection 2023 Nov 17.

ABSTRACT

Latent factor models, like principal component analysis (PCA), provide a statistical framework to infer low-rank representation in various biological contexts. However, feature selection is challenging when this low-rank structure manifests from a sparse subspace. We introduce SuSiE PCA, a scalable sparse latent factor approach that evaluates uncertainty in contributing variables through posterior inclusion probabilities. We validate our model in extensive simulations and demonstrate that SuSiE PCA outperforms other approaches in signal detection and model robustness. We apply SuSiE PCA to multi-tissue expression quantitative trait loci (eQTLs) data from GTEx v8 and identify tissue-specific factors and their contributing eGenes. We further investigate its performance on the large-scale perturbation data and find that SuSiE PCA identifies modules with a higher enrichment of ribosome-related genes than sparse PCA (false discovery rate [FDR] =9.2×10-82 vs. 1.4×10-33), while being ∼ 18x faster. Overall, SuSiE PCA provides an efficient tool to identify relevant features in high-dimensional biological data.

PMID:37953948 | PMC:PMC10638022 | DOI:10.1016/j.isci.2023.108181

PeerJ. 2023 Nov 8;11:e16351. doi: 10.7717/peerj.16351. eCollection 2023.

ABSTRACT

Many tools and algorithms are available for analyzing transcriptomics data. These include algorithms for performing sequence alignment, data normalization and imputation, clustering, identifying differentially expressed genes, and performing gene set enrichment analysis. To make the best choice about which tools to use, objective benchmarks can be developed to compare the quality of different algorithms to extract biological knowledge maximally and accurately from these data. The Dexamethasone Benchmark (Dex-Benchmark) resource aims to fill this need by providing the community with datasets and code templates for benchmarking different gene expression analysis tools and algorithms. The resource provides access to a collection of curated RNA-seq, L1000, and ChIP-seq data from dexamethasone treatment as well as genetic perturbations of its known targets. In addition, the website provides Jupyter Notebooks that use these pre-processed curated datasets to demonstrate how to benchmark the different steps in gene expression analysis. By comparing two independent data sources and data types with some expected concordance, we can assess which tools and algorithms best recover such associations. To demonstrate the usefulness of the resource for discovering novel drug targets, we applied it to optimize data processing strategies for the chemical perturbations and CRISPR single gene knockouts from the L1000 transcriptomics data from the Library of Integrated Network Cellular Signatures (LINCS) program, with a focus on understudied proteins from the Illuminating the Druggable Genome (IDG) program. Overall, the Dex-Benchmark resource can be utilized to assess the quality of transcriptomics and other related bioinformatics data analysis workflows. The resource is available from: https://maayanlab.github.io/dex-benchmark.

PMID:37953774 | PMC:PMC10638921 | DOI:10.7717/peerj.16351

Autophagy. 2023 Nov 12:1-2. doi: 10.1080/15548627.2023.2277583. Online ahead of print.

ABSTRACT

Mycobacterium tuberculosis (Mtb) employs a multifaceted arsenal to elude host defense mechanisms, including those associated with autophagy and lysosome function. Within the realm of host-pathogen interactions, NCOR1, a well-recognized transcriptional co-repressor, is known to associate with a multitude of protein complexes to effect the repression of a diverse spectrum of genes. However, its role in regulating macroautophagy/autophagy, lysosome biogenesis, and, by extension, Mtb pathogenesis remains unexplored. The depletion of NCOR1 assumes a pivotal role in the control of the AMPK-MTOR-TFEB signaling axis, thereby fine-tuning cellular ATP homeostasis. This finely orchestrated adjustment further alters the profile of proteins involved in autophagy and lysosomal biogenesis through its master regulator, TFEB, culminating in the increased Mtb survival within the host milieu. Furthermore, the treatment of NCOR1-depleted cells with either rapamycin, antimycin A, or metformin demonstrates a capacity to restore the TFEB activity and LC3-II levels, consequently restoring the capacity of host cells to clear Mtb. Additionally, exogenous NCOR1 expression rescues the AMPK-MTOR-TFEB signaling axis and essentially the autophagic induction machinery. Overall, these findings demonstrate a crucial role of NCOR1 in regulating Mtb pathogenesis within myeloid cells and sheds light toward its involvement in the development of novel host-directed therapies.

PMID:37953605 | DOI:10.1080/15548627.2023.2277583