PLoS One. 2024 May 30;19(5):e0300190. doi: 10.1371/journal.pone.0300190. eCollection 2024.

ABSTRACT

Histone variants are paralogs that replace canonical histones in nucleosomes, often imparting novel functions. However, how histone variants arise and evolve is poorly understood. Reconstruction of histone protein evolution is challenging due to large differences in evolutionary rates across gene lineages and sites. Here we used intron position data from 108 nematode genomes in combination with amino acid sequence data to find disparate evolutionary histories of the three H2A variants found in Caenorhabditis elegans: the ancient H2A.ZHTZ-1, the sperm-specific HTAS-1, and HIS-35, which differs from the canonical S-phase H2A by a single glycine-to-alanine C-terminal change. Although the H2A.ZHTZ-1 protein sequence is highly conserved, its gene exhibits recurrent intron gain and loss. This pattern suggests that specific intron sequences or positions may not be important to H2A.Z functionality. For HTAS-1 and HIS-35, we find variant-specific intron positions that are conserved across species. Patterns of intron position conservation indicate that the sperm-specific variant HTAS-1 arose more recently in the ancestor of a subset of Caenorhabditis species, while HIS-35 arose in the ancestor of Caenorhabditis and its sister group, including the genus Diploscapter. HIS-35 exhibits gene retention in some descendent lineages but gene loss in others, suggesting that histone variant use or functionality can be highly flexible. Surprisingly, we find the single amino acid differentiating HIS-35 from core H2A is ancestral and common across canonical Caenorhabditis H2A sequences. Thus, we speculate that the role of HIS-35 lies not in encoding a functionally distinct protein, but instead in enabling H2A expression across the cell cycle or in distinct tissues. This work illustrates how genes encoding such partially-redundant functions may be advantageous yet relatively replaceable over evolutionary timescales, consistent with the patchwork pattern of retention and loss of both genes. Our study shows the utility of intron positions for reconstructing evolutionary histories of gene families, particularly those undergoing idiosyncratic sequence evolution.

PMID:38814971 | DOI:10.1371/journal.pone.0300190

J Med Chem. 2024 May 30. doi: 10.1021/acs.jmedchem.4c00735. Online ahead of print.

ABSTRACT

The spike-protein of SARS-CoV-2 has a distinctive amino-acid sequence (682RRARS686) that forms a cleavage site for the enzyme furin. Strikingly, the structure of the spike-protein loop containing the furin cleavage site bears substantial similarity to neurotoxin peptides found in the venoms of certain snakes and marine cone snails. Leveraging this relationship, we designed and synthesized disulfide-constrained peptides with amino-acid sequences corresponding to the furin cleavage-sites of wild-type (B.1 variant) SARS-CoV-2 or the Alpha, Delta, and Omicron variants. Remarkably, some of these peptides potently inhibited α7 and α9α10 nicotinic acetylcholine receptors (nAChR) with nM affinity and showed SARS-CoV-2 variant and nAChR subtype-dependent potencies. Nuclear magnetic resonance spectroscopy and molecular dynamics were used to rationalize structure-activity relationships between peptides and their cognate receptors. These findings delineate nAChR subtypes that can serve as high-affinity spike-protein targets in tissues central to COVID-19 pathophysiology and identify ligands and target receptors to inform the development of novel SARS-CoV-2 therapeutics.

PMID:38814877 | DOI:10.1021/acs.jmedchem.4c00735

J Comput Biol. 2024 May 29. doi: 10.1089/cmb.2024.0517. Online ahead of print.

ABSTRACT

Single-cell transcriptomic studies of differentiating systems allow meaningful understanding, especially in human embryonic development and cell fate determination. We present an innovative method aimed at modeling these intricate processes by leveraging scRNAseq data from various human developmental stages. Our implemented method identifies pseudo-perturbations, since actual perturbations are unavailable due to ethical and technical constraints. By integrating these pseudo-perturbations with prior knowledge of gene interactions, our framework generates stage-specific Boolean networks (BNs). We apply our method to medium and late trophectoderm developmental stages and identify 20 pseudo-perturbations required to infer BNs. The resulting BN families delineate distinct regulatory mechanisms, enabling the differentiation between these developmental stages. We show that our program outperforms existing pseudo-perturbation identification tool. Our framework contributes to comprehending human developmental processes and holds potential applicability to diverse developmental stages and other research scenarios.

PMID:38814745 | DOI:10.1089/cmb.2024.0517

Elife. 2024 May 30;13:e91533. doi: 10.7554/eLife.91533.

ABSTRACT

To navigate their environment, insects need to keep track of their orientation. Previous work has shown that insects encode their head direction as a sinusoidal activity pattern around a ring of neurons arranged in an eight-column structure. However, it is unclear whether this sinusoidal encoding of head direction is just an evolutionary coincidence or if it offers a particular functional advantage. To address this question, we establish the basic mathematical requirements for direction encoding and show that it can be performed by many circuits, all with different activity patterns. Among these activity patterns, we prove that the sinusoidal one is the most noise-resilient, but only when coupled with a sinusoidal connectivity pattern between the encoding neurons. We compare this predicted optimal connectivity pattern with anatomical data from the head direction circuits of the locust and the fruit fly, finding that our theory agrees with experimental evidence. Furthermore, we demonstrate that our predicted circuit can emerge using Hebbian plasticity, implying that the neural connectivity does not need to be explicitly encoded in the genetic program of the insect but rather can emerge during development. Finally, we illustrate that in our theory, the consistent presence of the eight-column organisation of head direction circuits across multiple insect species is not a chance artefact but instead can be explained by basic evolutionary principles.

PMID:38814703 | DOI:10.7554/eLife.91533

Mol Neurobiol. 2024 May 30. doi: 10.1007/s12035-024-04223-3. Online ahead of print.

ABSTRACT

Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb., two nootropics, are recognized in Indian Ayurvedic texts. Studies have attempted to understand their action as memory enhancers and neuroprotectants, but many molecular aspects remain unknown. We propose that Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb. share common neuroprotective mechanisms. Mass spectrometry-based untargeted metabolomics and network pharmacology approach were used to identify potential protein targets for the metabolites from each extract. Phytochemical analyses and cell culture validation studies were also used to assess apoptosis and ROS activity using aqueous extracts prepared from both herbal powders. Further, docking studies were also performed using the LibDock protocol. Untargeted metabolomics and network pharmacology approach unveiled 2751 shared metabolites and 3439 and 2928 non-redundant metabolites from Bacopa monnieri and Centella asiatica extracts, respectively, suggesting a potential common neuroprotective mechanism among these extracts. Protein-target prediction highlighted 92.4% similarity among the proteins interacting with metabolites for these extracts. Among them, kinases mapped to MAPK, mTOR, and PI3K-AKT signaling pathways represented a predominant population. Our results highlight a significant similarity in the metabolome of Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb., and their potential protein targets may be attributed to their common neuroprotective functions.

PMID:38814535 | DOI:10.1007/s12035-024-04223-3

Biomacromolecules. 2024 May 30. doi: 10.1021/acs.biomac.4c00373. Online ahead of print.

ABSTRACT

The delivery of oligonucleotides across biological barriers is a challenge of unsurpassed significance at the interface of materials science and medicine, with emerging clinical utility in prophylactic and therapeutic vaccinations, immunotherapies, genome editing, and cell rejuvenation. Here, we address the role of readily available branched lipids in the design, synthesis, and evaluation of isoprenoid charge-altering releasable transporters (CARTs), a pH-responsive oligomeric nanoparticle delivery system for RNA. Systematic variation of the lipid block reveals an emergent relationship between the lipid block and the neutralization kinetics of the polycationic block. Unexpectedly, iA21A11, a CART with the smallest lipid side chain, isoamyl-, was identified as the lead isoprenoid CART for the in vitro transfection of immortalized lymphoblastic cell lines. When administered intramuscularly in a murine model, iA21A11-mRNA complexes induce higher protein expression levels than our previous lead CART, ONA. Isoprenoid CARTs represent a new delivery platform for RNA vaccines and other polyanion-based therapeutics.

PMID:38814265 | DOI:10.1021/acs.biomac.4c00373

Epilepsia Open. 2024 May 30. doi: 10.1002/epi4.12982. Online ahead of print.

ABSTRACT

OBJECTIVE: GABAA receptor subunit mutations pose a significant risk for genetic generalized epilepsy; however, there are over 150 identified variants, many with unknown or unvalidated pathogenicity. We aimed to develop in vivo models for testing GABAA receptor variants using the model organism, Caenorhabditis elegans.

METHODS: CRISPR-Cas9 gene editing was used to create a complete deletion of unc-49, a C. elegans GABAA receptor, and to create homozygous epilepsy-associated mutations in the endogenous unc-49 gene. The unc-49 deletion strain was rescued with transgenes for either the C. elegans unc-49B subunit or the α1, β3, and γ2 subunits for the human GABAA receptor. All newly created strains were analyzed for phenotype and compared against existing unc-49 mutations.

RESULTS: Nematodes with a full genetic deletion of the entire unc-49 locus were compared with existing unc-49 mutations in three separate phenotypic assays-coordinated locomotion, shrinker frequency and seizure-like convulsions. The full unc-49 deletion exhibited reduced locomotion and increased shrinker frequency and PTZ-induced convulsions, but were not found to be phenotypically stronger than existing unc-49 mutations. Rescue with the unc-49B subunit or creation of humanized worms for the GABAA receptor both showed partial phenotypic rescue for all three phenotypes investigated. Finally, two epilepsy-associated variants were analyzed and deemed to be loss of function, thus validating their pathogenicity.

SIGNIFICANCE: These findings establish C. elegans as a genetic model to investigate GABAA receptor mutations and delineate a platform for validating associated variants in any epilepsy-associated gene.

PLAIN LANGUAGE SUMMARY: Epilepsy is a complex human disease that can be caused by mutations in specific genes. Many possible mutations have been identified, but it is unknown for most of them whether they cause the disease. We tested the role of mutations in one specific gene using a small microscopic worm as an animal model. Our results establish this worm as a model for epilepsy and confirm that the two unknown mutations are likely to cause the disease.

PMID:38813985 | DOI:10.1002/epi4.12982

Biochem Soc Trans. 2024 May 30:BST20230229. doi: 10.1042/BST20230229. Online ahead of print.

ABSTRACT

Advancements in synthetic biology have facilitated the incorporation of heterologous metabolic pathways into various bacterial chassis, leading to the synthesis of targeted bioproducts. However, total output from heterologous production pathways can suffer from low flux, enzyme promiscuity, formation of toxic intermediates, or intermediate loss to competing reactions, which ultimately hinder their full potential. The self-assembling, easy-to-modify, protein-based bacterial microcompartments (BMCs) offer a sophisticated way to overcome these obstacles by acting as an autonomous catalytic module decoupled from the cell's regulatory and metabolic networks. More than a decade of fundamental research on various types of BMCs, particularly structural studies of shells and their self-assembly, the recruitment of enzymes to BMC shell scaffolds, and the involvement of ancillary proteins such as transporters, regulators, and activating enzymes in the integration of BMCs into the cell's metabolism, has significantly moved the field forward. These advances have enabled bioengineers to design synthetic multi-enzyme BMCs to promote ethanol or hydrogen production, increase cellular polyphosphate levels, and convert glycerol to propanediol or formate to pyruvate. These pioneering efforts demonstrate the enormous potential of synthetic BMCs to encapsulate non-native multi-enzyme biochemical pathways for the synthesis of high-value products.

PMID:38813858 | DOI:10.1042/BST20230229

OMICS. 2024 May 30. doi: 10.1089/omi.2024.0110. Online ahead of print.

ABSTRACT

A quiet quadruple revolution has been in the making in systems science with convergence of (1) artificial intelligence, machine learning, and other digital technologies; (2) multiomics big data integration; (3) growing interest in the "variability science" of precision/personalized medicine that aims to account for patient-to-patient and between-population differences in disease susceptibilities and responses to health interventions such as drugs, nutrition, vaccines, and radiation; and (4) planetary health scholarship that both scales up and integrates biological, clinical, and ecological contexts of health and disease. Against this overarching background, this article presents and highlights some of the salient challenges and prospects of multiomics research, emphasizing the attendant pivotal role of systems medicine and systems biology. In addition, we emphasize the rapidly growing importance of planetary health research for systems medicine, particularly amid climate emergency, ecological degradation, and loss of planetary biodiversity. Looking ahead, we anticipate that the integration and utilization of multiomics big data and artificial intelligence will drive further progress in systems medicine and systems biology, heralding a promising future for both human and planetary health.

PMID:38813661 | DOI:10.1089/omi.2024.0110

EClinicalMedicine. 2024 Apr 26;71:102490. doi: 10.1016/j.eclinm.2024.102490. eCollection 2024 May.

ABSTRACT

BACKGROUND: Urinary tract infections (UTI) affect approximately 250 million people annually worldwide. Patients often experience a cycle of antimicrobial treatment and recurrent UTI (rUTI) that is thought to be facilitated by a gut reservoir of uropathogenic Escherichia coli (UPEC).

METHODS: 125 patients with UTI caused by an antibiotic-resistant organism (ARO) were enrolled from July 2016 to May 2019 in a longitudinal, multi-center cohort study. Multivariate statistical models were used to assess the relationship between uropathogen colonization and recurrent UTI (rUTI), controlling for clinical characteristics. 644 stool samples and 895 UPEC isolates were interrogated for taxonomic composition, antimicrobial resistance genes, and phenotypic resistance. Cohort UTI gut microbiome profiles were compared against published healthy and UTI reference microbiomes, as well as assessed within-cohort for timepoint- and recurrence-specific differences.

FINDINGS: Risk of rUTI was not independently associated with clinical characteristics. The UTI gut microbiome was distinct from healthy reference microbiomes in both taxonomic composition and antimicrobial resistance gene (ARG) burden, with 11 differentially abundant taxa at the genus level. rUTI and non-rUTI gut microbiomes in the cohort did not generally differ, but gut microbiomes from urinary tract colonized patients were elevated in E. coli abundance 7-14 days post-antimicrobial treatment. Corresponding UPEC gut isolates from urinary tract colonizing lineages showed elevated phenotypic resistance against 11 of 23 tested drugs compared to non-colonizing lineages.

INTERPRETATION: The gut microbiome is implicated in UPEC urinary tract colonization during rUTI, serving as an ARG-enriched reservoir for UPEC. UPEC can asymptomatically colonize the gut and urinary tract, and post-antimicrobial blooms of gut E. coli among urinary tract colonized patients suggest that cross-habitat migration of UPEC is an important mechanism of rUTI. Thus, treatment duration and UPEC populations in both the urinary and gastrointestinal tract should be considered in treating rUTI and developing novel therapeutics.

FUNDING: This work was supported in part by awards from the U.S. Centers for Disease Control and Prevention Epicenter Prevention Program (grant U54CK000482; principal investigator, V.J.F.); to J.H.K. from the Longer Life Foundation (an RGA/Washington University partnership), the National Center for Advancing Translational Sciences (grants KL2TR002346 and UL1TR002345), and the National Institute of Allergy and Infectious Diseases (NIAID) (grant K23A1137321) of the National Institutes of Health (NIH); and to G.D. from NIAID (grant R01AI123394) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (grant R01HD092414) of NIH. R.T.'s research was funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation; grant 402733540). REDCap is Supported by Clinical and Translational Science Award (CTSA) Grant UL1 TR002345 and Siteman Comprehensive Cancer Center and NCI Cancer Center Support Grant P30 CA091842. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.

PMID:38813445 | PMC:PMC11133793 | DOI:10.1016/j.eclinm.2024.102490

Front Nutr. 2024 May 15;11:1346483. doi: 10.3389/fnut.2024.1346483. eCollection 2024.

ABSTRACT

Anxiety disorders disproportionally affect females and are frequently comorbid with eating disorders. With the emerging field of nutritional psychiatry, focus has been put on the impact of diet quality in anxiety pathophysiology and gut microbiome underlying mechanisms. While the relationship between diet and anxiety is bidirectional, improving dietary habits could better facilitate the actions of pharmacological and psychological therapies, or prevent their use. A better understanding of how gut bacteria mediate and moderate such relationship could further contribute to develop personalized programs and inform probiotics and prebiotics manufacturing. To date, studies that look simultaneously at diet, the gut microbiome, and anxiety are missing as only pairwise relationships among them have been investigated. Therefore, this study aims at summarizing and integrating the existing knowledge on the dietary effects on anxiety with focus on gut microbiome. Findings on the effects of diet on anxiety are critically summarized and reinterpreted in relation to findings on (i) the effects of diet on the gut microbiome composition, and (ii) the associations between the abundance of certain gut bacteria and anxiety. This novel interpretation suggests a theoretical model where the relationship between diet and anxiety is mediated and/or modulated by the gut microbiome through multiple mechanisms. In parallel, this study critically evaluates methodologies employed in the nutritional field to investigate the effects of diet on anxiety highlighting a lack of systematic operationalization and assessment strategies. Therefore, it ultimately proposes a novel evidence-based approach that can enhance studies validity, reliability, systematicity, and translation to clinical and community settings.

PMID:38812941 | PMC:PMC11133642 | DOI:10.3389/fnut.2024.1346483

iScience. 2024 May 7;27(6):109928. doi: 10.1016/j.isci.2024.109928. eCollection 2024 Jun 21.

ABSTRACT

Interactions within the tumor microenvironment (TME) significantly influence tumor progression and treatment responses. While single-cell RNA sequencing (scRNA-seq) and spatial genomics facilitate TME exploration, many clinical cohorts are assessed at the bulk tissue level. Integrating scRNA-seq and bulk tissue RNA-seq data through computational deconvolution is essential for obtaining clinically relevant insights. Our method, ProM, enables the examination of major and minor cell types. Through evaluation against existing methods using paired single-cell and bulk RNA sequencing of human urothelial cancer (UC) samples, ProM demonstrates superiority. Application to UC cohorts treated with immune checkpoint inhibitors reveals pre-treatment cellular features associated with poor outcomes, such as elevated SPP1 expression in macrophage/monocytes (MM). Our deconvolution method and paired single-cell and bulk tissue RNA-seq dataset contribute novel insights into TME heterogeneity and resistance to immune checkpoint blockade.

PMID:38812546 | PMC:PMC11133924 | DOI:10.1016/j.isci.2024.109928

J Exp Bot. 2024 May 30:erae235. doi: 10.1093/jxb/erae235. Online ahead of print.

ABSTRACT

Plants, being sessile organisms, constantly need to respond to environmental stresses, often leading to the accumulation of reactive oxygen species (ROS). While ROS can be harmful, they also act as messengers guiding plant growth and stress responses. Because chloroplasts are sensitive to environmental changes and are both a source and target of ROS during stress conditions, they are important in conveying environmental changes to the nucleus, where acclimation responses are coordinated to maintain organellar and overall cellular homeostasis. ANAC102 has previously been established as a regulator of β-cyclocitral-mediated chloroplast-to-nucleus signaling, protecting plants against photooxidative stress. However, debates persist about where ANAC102 is located - in chloroplasts or in the nucleus. Our study, utilizing the genomic ANAC102 sequence driven by its native promoter, establishes ANAC102 primarily as a nuclear protein, lacking a complete N-terminal chloroplast-targeting peptide. Moreover, our research reveals the sensitivity of plants overexpressing ANAC102 to severe superoxide-induced chloroplast oxidative stress. Transcriptome analysis unraveled ANAC102's dual role in negatively and positively regulating genome-wide transcriptional responses to chloroplast oxidative stress. Through the integration of published data and our own study, we constructed a comprehensive transcriptional network, which suggests that ANAC102 exerts direct and indirect control over transcriptional responses through downstream transcription factor networks, providing deeper insights into the ANAC102-mediated regulatory landscape during oxidative stress.

PMID:38812358 | DOI:10.1093/jxb/erae235

Environ Microbiome. 2024 May 29;19(1):35. doi: 10.1186/s40793-024-00578-1.

ABSTRACT

BACKGROUND: Extreme weather events induced by climate change, particularly droughts, have detrimental consequences for crop yields and food security. Concurrently, these conditions provoke substantial changes in the soil bacterial microbiota and affect plant health. Early recognition of soil affected by drought enables farmers to implement appropriate agricultural management practices. In this context, interpretable machine learning holds immense potential for drought stress classification of soil based on marker taxa.

RESULTS: This study demonstrates that the 16S rRNA-based metagenomic approach of Differential Abundance Analysis methods and machine learning-based Shapley Additive Explanation values provide similar information. They exhibit their potential as complementary approaches for identifying marker taxa and investigating their enrichment or depletion under drought stress in grass lineages. Additionally, the Random Forest Classifier trained on a diverse range of relative abundance data from the soil bacterial micobiome of various plant species achieves a high accuracy of 92.3 % at the genus rank for drought stress prediction. It demonstrates its generalization capacity for the lineages tested.

CONCLUSIONS: In the detection of drought stress in soil bacterial microbiota, this study emphasizes the potential of an optimized and generalized location-based ML classifier. By identifying marker taxa, this approach holds promising implications for microbe-assisted plant breeding programs and contributes to the development of sustainable agriculture practices. These findings are crucial for preserving global food security in the face of climate change.

PMID:38812054 | DOI:10.1186/s40793-024-00578-1

Respir Res. 2024 May 29;25(1):223. doi: 10.1186/s12931-024-02821-2.

ABSTRACT

BACKGROUND: Community-acquired pneumonia (CAP) is a common and serious condition that can be caused by a variety of pathogens. However, much remains unknown about how these pathogens interact with the lower respiratory commensals, and whether any correlation exists between the dysbiosis of the lower respiratory microbiota and disease severity and prognosis.

METHODS: We conducted a retrospective cohort study to investigate the composition and dynamics of sputum microbiota in patients diagnosed with CAP. In total, 917 sputum specimens were collected consecutively from 350 CAP inpatients enrolled in six hospitals following admission. The V3-V4 region of the 16 S rRNA gene was then sequenced.

RESULTS: The sputum microbiota in 71% of the samples were predominately composed of respiratory commensals. Conversely, 15% of the samples demonstrated dominance by five opportunistic pathogens. Additionally, 5% of the samples exhibited sterility, resembling the composition of negative controls. Compared to non-severe CAP patients, severe cases exhibited a more disrupted sputum microbiota, characterized by the highly dominant presence of potential pathogens, greater deviation from a healthy state, more significant alterations during hospitalization, and sparser bacterial interactions. The sputum microbiota on admission demonstrated a moderate prediction of disease severity (AUC = 0.74). Furthermore, different pathogenic infections were associated with specific microbiota alterations. Acinetobacter and Pseudomonas were more abundant in influenza A infections, with Acinetobacter was also enriched in Klebsiella pneumoniae infections.

CONCLUSION: Collectively, our study demonstrated that pneumonia may not consistently correlate with severe dysbiosis of the respiratory microbiota. Instead, the degree of microbiota dysbiosis was correlated with disease severity in CAP patients.

PMID:38811936 | DOI:10.1186/s12931-024-02821-2

BMC Plant Biol. 2024 May 29;24(1):468. doi: 10.1186/s12870-024-05172-8.

ABSTRACT

BACKGROUND: The cuticular wax serves as a primary barrier that protects plants from environmental stresses. The Eceriferum (CER) gene family is associated with wax production and stress resistance.

RESULTS: In a genome-wide identification study, a total of 52 members of the CER family were discovered in four Gossypium species: G. arboreum, G. barbadense, G. raimondii, and G. hirsutum. There were variations in the physicochemical characteristics of the Gossypium CER (GCER) proteins. Evolutionary analysis classified the identified GCERs into five groups, with purifying selection emerging as the primary evolutionary force. Gene structure analysis revealed that the number of conserved motifs ranged from 1 to 15, and the number of exons varied from 3 to 13. Closely related GCERs exhibited similar conserved motifs and gene structures. Analyses of chromosomal positions, selection pressure, and collinearity revealed numerous fragment duplications in the GCER genes. Additionally, nine putative ghr-miRNAs targeting seven G. hirsutum CER (GhCER) genes were identified. Among them, three miRNAs, including ghr-miR394, ghr-miR414d, and ghr-miR414f, targeted GhCER09A, representing the most targeted gene. The prediction of transcription factors (TFs) and the visualization of the regulatory TF network revealed interactions with GhCER genes involving ERF, MYB, Dof, bHLH, and bZIP. Analysis of cis-regulatory elements suggests potential associations between the CER gene family of cotton and responses to abiotic stress, light, and other biological processes. Enrichment analysis demonstrated a robust correlation between GhCER genes and pathways associated with cutin biosynthesis, fatty acid biosynthesis, wax production, and stress response. Localization analysis showed that most GCER proteins are localized in the plasma membrane. Transcriptome and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) expression assessments demonstrated that several GhCER genes, including GhCER15D, GhCER04A, GhCER06A, and GhCER12D, exhibited elevated expression levels in response to water deficiency stress compared to control conditions. The functional identification through virus-induced gene silencing (VIGS) highlighted the pivotal role of the GhCER04A gene in enhancing drought resistance by promoting increased tissue water retention.

CONCLUSIONS: This investigation not only provides valuable evidence but also offers novel insights that contribute to a deeper understanding of the roles of GhCER genes in cotton, their role in adaptation to drought and other abiotic stress and their potential applications for cotton improvement.

PMID:38811873 | DOI:10.1186/s12870-024-05172-8

Nat Genet. 2024 May 29. doi: 10.1038/s41588-024-01813-8. Online ahead of print.

NO ABSTRACT

PMID:38811845 | DOI:10.1038/s41588-024-01813-8

Nature. 2024 May 29. doi: 10.1038/s41586-024-07593-9. Online ahead of print.

NO ABSTRACT

PMID:38811742 | DOI:10.1038/s41586-024-07593-9

Sci Rep. 2024 May 29;14(1):12316. doi: 10.1038/s41598-024-62741-5.

ABSTRACT

Addressing the significant level of variability exhibited by pancreatic cancer necessitates the adoption of a systems biology approach that integrates molecular data, biological properties of the tumors, medical images, and clinical features of the patients. In this study, a comprehensive multi-omics methodology was employed to examine a distinctive collection of patient dataset containing rapid autopsy tumor and normal tissue samples as well as longitudinal imaging with a focus on pancreatic cancer. By performing a whole exome sequencing analysis on tumor and normal tissues to identify somatic gene variants and a radiomic feature analysis to tumor CT images, the genome-wide association approach established a connection between pancreatic cancer driver genes and relevant radiomic features, enabling a thorough and quantitative assessment of the heterogeneity of pancreatic tumors. The significant association between sets of genes and radiomic features revealed the involvement of genes in shaping tumor morphological heterogeneity. Some results of the association established a connection between the molecular level mechanism and their outcomes at the level of tumor structural heterogeneity. Because tumor structure and tumor structural heterogeneity are related to the patients' overall survival, patients who had pancreatic cancer driver gene mutations with an association to a certain radiomic feature have been observed to experience worse survival rates than cases without these somatic mutations. Furthermore, the association analysis has revealed potential gene mutations and radiomic feature candidates that warrant further investigation in future research endeavors.

PMID:38811597 | DOI:10.1038/s41598-024-62741-5

NPJ Syst Biol Appl. 2024 May 29;10(1):60. doi: 10.1038/s41540-024-00380-2.

ABSTRACT

The amazing complexity of gene regulatory circuits, and biological systems in general, makes mathematical modeling an essential tool to frame and develop our understanding of their properties. Here, we present some fundamental considerations to develop and analyze a model of a gene regulatory circuit of interest, either representing a natural, synthetic, or theoretical system. A mathematical model allows us to effectively evaluate the logical implications of our hypotheses. Using our models to systematically perform in silico experiments, we can then propose specific follow-up assessments of the biological system as well as to reformulate the original assumptions, enriching both our knowledge and our understanding of the system. We want to invite the community working on different aspects of gene regulatory circuits to explore the power and benefits of mathematical modeling in their system.

PMID:38811585 | DOI:10.1038/s41540-024-00380-2