Biochem Biophys Res Commun. 2024 Oct 26;737:150869. doi: 10.1016/j.bbrc.2024.150869. Online ahead of print.

ABSTRACT

GLABRA1 (GL1), which encodes an R2R3 MYB transcription factor, is a key regulator of trichome patterning in the aerial organs of Arabidopsis (Arabidopsis thaliana). Although it has been generally assumed that GL1 functions exclusively in shoots and is not expressed in roots, reverse transcription polymerase chain reaction (RT-PCR) analysis has revealed that GL1 is indeed expressed in roots. To investigate whether GL1 plays a role in root epidermal patterning, we analyzed the effects of gl1 mutations in sensitized genetic backgrounds. Our findings show that gl1 mutants enhance the root epidermal phenotype of a weak allele of the werewolf (wer) mutant and suppress the phenotype of the caprice (cpc) mutant. We also demonstrate that the GL1 promoter is active in N-position epidermal cells, and that the GFP-GL1 fusion protein is predominantly localized in the nucleus of N-position cells. Furthermore, we provide evidence that GL1 expression is positively regulated by WER, GLABRA3, ENHANCER OF GLABRA3, and TRANSPARENT TESTA GLABRA1, while negatively regulated by CPC, TRIPTYCHON, and GLABRA2 (GL2). Notably, GL2, which is positively regulated by GL1, moderately represses GL1 expression, and both GL1 and GL2 are positively regulated by WER in N-position cells. These findings suggest that a negative feedback regulation of GL1 expression via GL2 contributes to the fine-tuning of non-hair cell fate determination in Arabidopsis root epidermis.

PMID:39489112 | DOI:10.1016/j.bbrc.2024.150869

Clin Imaging. 2024 Oct 21;116:110334. doi: 10.1016/j.clinimag.2024.110334. Online ahead of print.

ABSTRACT

Theranostics is emerging as a critical pillar of oncologic management, as exemplified by the success of Lu-177-PSMA-617 for the treatment of castration-resistant prostate cancer. The emergence of such theranostic agents represents an opportunity to reconsider facets of nuclear medicine practice that will enable its engagement in high-volume radioligand delivery. In this article, we aim to explore simple ethical principles that can guide the development of theranostics programs as radiopharmaceutical agents proliferate and the typical nuclear medicine physician transitions from a primarily diagnostic role to a mixed diagnostic and therapeutic role. Such a mixed role will demand all the attendant competencies of direct patient care. We argue that restructuring nuclear medicine practice to meet this challenge involves developing processes for promoting the principle of fairness in patient selection for theranostic agents and for promoting the principle of responsibility during the administration of theranostic agents. We further specify that this responsibility extends to the patient receiving the therapy, the local community of the patient, and the general community exposed to the population of patients receiving theranostic agents. PRéCIS: The expansion of radioligand therapy requires promoting the ethical principle of fairness in patient selection and the ethical principle of responsibility in the delivery of radioligand therapy.

PMID:39488932 | DOI:10.1016/j.clinimag.2024.110334

STAR Protoc. 2024 Nov 2;5(4):103286. doi: 10.1016/j.xpro.2024.103286. Online ahead of print.

ABSTRACT

Proteins congregate into complexes to perform diverse cellular functions. Protein complexes are remodeled by protein-coding mutations or cellular signaling changes, driving phenotypic outcomes in health and disease. We present an affinity purification-mass spectrometry (AP-MS) proteomics protocol to express affinity-tagged "bait" proteins in mammalian cells, identify and quantify purified protein interactors, and visualize differential protein-protein interaction networks between pairwise conditions. Our protocol possesses general applicability to various cell types and biological areas. For complete details on the use and execution of this protocol, please refer to Bouhaddou et al.1.

PMID:39488835 | DOI:10.1016/j.xpro.2024.103286

Gut Microbes. 2024 Jan-Dec;16(1):2420771. doi: 10.1080/19490976.2024.2420771. Epub 2024 Nov 3.

ABSTRACT

Probiotics hold great potential for treating metabolic diseases such as obesity. Given the complex and multifactorial nature of these diseases, research on probiotic combination with multiple targets has become popular. Here, we choose four obesity-related targets to perform high-throughput screening, including pancreatic lipase activity, bile salt hydrolase activity, glucagon-like peptide-1 secretion and adipocyte differentiation. Then, we obtained 649 multi-strain combinations with the requirement that each must cover all these targets in principle. After in vitro co-culture and in vivo co-colonization experiments, only four (<0.7%) combinations were selected as symbiotic probiotic communities (SPCs). Next, genome-scale metabolic model analysis revealed that these SPCs showed lower metabolic resource overlap and higher metabolic interaction potential involving amino acid metabolism (Ammonium, L-Lysine, etc.) and energy metabolism (Phosphate, etc.). Further animal experiments demonstrated that all SPCs exhibited a good safety profile and excellent effects in improving obesity and associated glucose metabolism disruptions and depression-like behaviors in high-fat-diet-fed mice. This anti-obesity improvement was achieved through reduced cholesterol level, fat accumulation and inhibited adipocyte differentiation. Taken together, our study provides a new perspective for designing multi-strain combinations, which may facilitate greater therapeutic effect on obesity and other complex diseases in the future.

PMID:39488738 | DOI:10.1080/19490976.2024.2420771

Crit Rev Biochem Mol Biol. 2024 Nov 3:1-26. doi: 10.1080/10409238.2024.2418639. Online ahead of print.

ABSTRACT

Space exploration and research are uncovering the potential for terrestrial life to survive in outer space, as well as the environmental factors that affect life during interplanetary transfer. The presence of methane in the Martian atmosphere suggests the possibility of methanogens, either extant or extinct, on Mars. Understanding how methanogens survive and adapt under space-exposed conditions is crucial for understanding the implications of extraterrestrial life. In this article, we discuss methanogens as model organisms for obtaining energy transducers and producing methane in a simulated Martian environment. We also explore the chemical evolution of cellular composition and growth maintenance to support survival in extraterrestrial environments. Neutral selective pressure is imposed on the chemical composition of cellular components to increase cell survival and reduce growth under physiological conditions. Energy limitation is an evolutionary driver of macromolecular polymerization, growth maintenance, and survival fitness of methanogens. Methanogens grown in a Martian environment may exhibit global alterations in their metabolic function and gene expression at the system scale. A space systems biology approach would further elucidate molecular survival mechanisms and adaptation to a drastic outer space environment. Therefore, identifying a genetically stable methanogenic community is essential for biomethane production from waste recycling to achieve sustainable space-life support functions.

PMID:39488737 | DOI:10.1080/10409238.2024.2418639

Eur J Surg Oncol. 2024 Oct 24:108783. doi: 10.1016/j.ejso.2024.108783. Online ahead of print.

ABSTRACT

Endometrial cancer (EC) is increasing incidence among women, and it constitutes a health problem for women globally. An important aspect of EC management involves the use of protein biomarkers for early detection and monitoring. Protein biomarkers allow the identification of high-risk patients, the detection of the disease in its early stages, and the assessment of treatment responses. Mass spectrometry (MS)-based proteomics offers robust analytical techniques and a comprehensive understanding of proteins. Proteomics methods allow scientists to investigate both the quantities and functions of proteins. Thus, it provides valuable insights into how proteins are altered under different conditions. This review summarizes recent advances in MS-based proteomic biomarker discovery for EC, focusing on different sample types and MS-based techniques used in clinical studies. The review emphasized in detail the most commonly used key sources such as blood, urine, vaginal fluids and tissue. Furthermore, MS-based proteomics techniques such as untargeted, targeted, sequential window acquisition of all theoretical mass spectra (SWATH-MS) and mass spectrometry imaging used in the discovery and validation/validation phases were evaluated. This review highlights the importance of biomarker discovery and clinical translation to improve diagnostic and therapeutic outcomes in EC. It aims to provide a comprehensive overview of MS-based proteomics in EC, guiding future research and clinical applications.

PMID:39488491 | DOI:10.1016/j.ejso.2024.108783

Cell Genom. 2024 Oct 24:100691. doi: 10.1016/j.xgen.2024.100691. Online ahead of print.

ABSTRACT

The insufficient availability of comprehensive protein-level perturbation data is impeding the widespread adoption of systems biology. In this perspective, we introduce the rationale, essentiality, and practicality of perturbation proteomics. Biological systems are perturbed with diverse biological, chemical, and/or physical factors, followed by proteomic measurements at various levels, including changes in protein expression and turnover, post-translational modifications, protein interactions, transport, and localization, along with phenotypic data. Computational models, employing traditional machine learning or deep learning, identify or predict perturbation responses, mechanisms of action, and protein functions, aiding in therapy selection, compound design, and efficient experiment design. We propose to outline a generic PMMP (perturbation, measurement, modeling to prediction) pipeline and build foundation models or other suitable mathematical models based on large-scale perturbation proteomic data. Finally, we contrast modeling between artificially and naturally perturbed systems and highlight the importance of perturbation proteomics for advancing our understanding and predictive modeling of biological systems.

PMID:39488205 | DOI:10.1016/j.xgen.2024.100691

Mar Environ Res. 2024 Oct 29;202:106819. doi: 10.1016/j.marenvres.2024.106819. Online ahead of print.

ABSTRACT

Back-reef habitats are important and fragile transition zones acting as nurseries for many coral reef fishes. In this framework, Passive Acoustic Monitoring (PAM) can be an important tool to evaluate the diversity and dynamics of sonic fish community. Here, we investigated the diversity, spatial and diel dynamics of fish sounds in back-reef habitats at Makogai Island in Fiji, South Pacific. Synchronized underwater recorders were deployed in 4 bays collecting data for about 4 days. The abundance of 12 different sub-categories of fish sounds were quantified. Signals were acoustically characterized and the level of discrimination between the sub-categories was evaluated by Discrimination Function Analysis. Generalized Additive Models showed that the abundance of signals was related to the bay and the hour. Moreover, the Shannon Diversity and Equitability Indices were calculated using acoustic and visual census data to describe fish biodiversity of each bay. The two bays with greater biodiversity based on visual census also showed a greater acoustic diversity at dawn and night. Our results highlight the importance of PAM to reveal the diversity of fish community in back-reef habitats, providing a baseline to understand future changes in these crucial environments.

PMID:39488099 | DOI:10.1016/j.marenvres.2024.106819

Microb Biotechnol. 2024 Nov;17(11):e70027. doi: 10.1111/1751-7915.70027.

ABSTRACT

Artificial intelligence (AI) has the potential to transform clinical practice and healthcare. Following impressive advancements in fields such as computer vision and medical imaging, AI is poised to drive changes in microbiome-based healthcare while facing challenges specific to the field. This review describes the state-of-the-art use of AI in microbiome-related healthcare. It points out limitations across topics such as data handling, AI modelling and safeguarding patient privacy. Furthermore, we indicate how these current shortcomings could be overcome in the future and discuss the influence and opportunities of increasingly complex data on microbiome-based healthcare.

PMID:39487766 | DOI:10.1111/1751-7915.70027

Liver Int. 2024 Nov 2. doi: 10.1111/liv.16150. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Glucagon-like peptide-1 receptor (GLP1R) agonists and glucose-dependent insulinotropic polypeptide receptor (GIPR) agonists may help treat metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). However, their definitive effects are still unclear. Our study aims to clarify this uncertainty.

METHODS: We utilised conventional Mendelian randomisation (MR) analysis to explore potential causal links between plasma GLP-1/GIP concentrations and MASLD and its related traits. Next, we conducted drug-target MR analysis using highly expressed tissue data to assess the effects of corresponding drug perturbation on these traits. Finally, mediation analysis was performed to ascertain whether the potential causal effect is direct or mediated by other MASLD-related traits.

RESULTS: Circulating 2-h GLP-1 and GIP concentrations measured during an oral glucose tolerance test showed hepatoprotective effects on MASLD risk (ORGLP-1 = 0.168 [95% CI 0.033-0.839], p = 0.030; ORGIP = 0.331 [95% CI 0.222-0.494], p = 6.31 × 10-8). GLP1R expression in the blood had a minimal causal effect on MASLD risk, whereas GIPR expression significantly affected MASLD risk (OR = 0.671 [95% CI 0.531-0.849], p = 9.07 × 10-4). Expression levels of GLP1R or GIPR in the blood significantly influenced MASLD-related clinical traits. Mediation analysis revealed that GIPR expression protected against MASLD, even after adjusting for type 2 diabetes or body mass index.

CONCLUSIONS: GLP-1/GIP receptor agonists offer promise in lowering MASLD/MASH risk. GIP receptor agonists can exert direct and indirect effects on MASLD mediated by weight reduction or glycemic control improvement.

PMID:39487684 | DOI:10.1111/liv.16150

Sci Rep. 2024 Nov 1;14(1):26328. doi: 10.1038/s41598-024-76773-4.

ABSTRACT

Water scarcity has evolved into a pressing global issue, significantly impacting numerous regions worldwide. The use of treated wastewater stands out as a promising solution to this problem. However, the proliferation of various contaminants, primarily Antimicrobial Resistance Genes (ARGs), poses a significant challenge to its safe and sustainable use. In this study, we assessed the composition and abundance of 373 ARGs, corresponding to 31 different classes of antibiotics, in six wastewater treatment plants (WWTP) in Agadir city of Morocco. Influent and effluent samples were collected during the months of February and July in 2020, in addition to samples from the Atlantic Ocean. In total, 223 ARGs were uncovered, highlighting in particular resistance to aminoglycoside, macrolide lincosamide, beta-lactamase, chloramphenicol, sulfonamide, tetracycline, and other antibiotics. The mechanisms of action of these ARGs were mainly antibiotic inactivation, antibiotic target alteration, efflux pump and cellular protection. Mobile genetic elements (MGEs) were detected at high levels their co-occurrence with ARGs highlights their involvement in the acquisition and transmission of ARGs in microbial communities through horizontal gene transfer. While many wastewater treatment methods effectively reduce a large proportion of gene material and pathogens, a substantial fraction of ARGs and other contaminants persist in treated wastewater. This persistence poses potential risks to both human health and the environment, warranting the need of more effective treatment strategies.

PMID:39487157 | DOI:10.1038/s41598-024-76773-4

Sci Rep. 2024 Nov 1;14(1):26322. doi: 10.1038/s41598-024-75328-x.

ABSTRACT

Establishing a sustainable life-support system for space exploration is a formidable challenge due to the vast distances, high costs, and environmental differences from Earth. Building upon the lessons from the Biosphere 2 experiment, we introduce the novel "Ecosphere" and "Biosealed" systems, self-sustaining ecosystems within customizable, enclosed containers. These systems incorporate terrestrial ecosystems and groundwater layers, offering a potential model for transplanting Earth-like biomes to extraterrestrial environments. Over 4 years, we conducted rigorous experiments and analyses to understand the dynamics of these enclosed ecosystems. We successfully mitigated moisture deficiency, a major obstacle to plant growth, by incorporating groundwater layers. Additionally, we quantified microbial communities proliferating in specific soils, including simulated lunar and Ryugu asteroid regolith, enhance plant cultivation in space environments. Metagenomic analysis of these simulated space soils revealed diverse microbial populations and their crucial role in plant growth and ecosystem stability. Notably, we identified symbiotic relationships between plants and Cyanobacteria, enhancing oxygen production, and demonstrated the potential of LED lighting as an alternative light source for plant cultivation in sun-limited space missions. We also confirmed the survival of fruit flies within these systems, relying on plant-produced oxygen and photosynthetic bacteria. Our research provides a comprehensive framework for developing future space life-support systems. The novelty of our work lies in the unique design of our enclosed ecosystems, incorporating groundwater layers and simulated extraterrestrial soils, and the detailed analysis of microbial communities within these systems. These findings offer valuable insights into the challenges and potential solutions for establishing sustainable human habitats in space, including the importance of microbial management and potential health concerns related to microbial exposure.

PMID:39487149 | DOI:10.1038/s41598-024-75328-x

Nat Commun. 2024 Nov 1;15(1):9432. doi: 10.1038/s41467-024-53628-0.

ABSTRACT

Identifying cell-type-specific 3D chromatin interactions between regulatory elements can help decipher gene regulation and interpret disease-associated non-coding variants. However, achieving this resolution with current 3D genomics technologies is often infeasible given limited input cell numbers. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps, including regulatory interactions, from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility across metacells, and a CTCF motif track as inputs and employs a lightweight architecture to train on standard GPUs. Trained on paired scATAC-seq and Hi-C data in human samples, ChromaFold accurately predicts the 3D contact map and peak-level interactions across diverse human and mouse test cell types. Compared to leading contact map prediction models that use ATAC-seq and CTCF ChIP-seq, ChromaFold achieves state-of-the-art performance using only scATAC-seq. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations.

PMID:39487131 | DOI:10.1038/s41467-024-53628-0

Trends Plant Sci. 2024 Oct 31:S1360-1385(24)00276-0. doi: 10.1016/j.tplants.2024.10.008. Online ahead of print.

ABSTRACT

Understanding molecular dynamics at the single cell level is crucial to understand plant traits. Recently, Liu et al. and Cui et al. reported multiome analysis in the same cell/nucleus to dissect the key plant traits (osmotic stress response and pod development). Their results provide novel insights into pathways and regulatory networks at a single cell resolution.

PMID:39487081 | DOI:10.1016/j.tplants.2024.10.008

Exp Gerontol. 2024 Oct 31:112627. doi: 10.1016/j.exger.2024.112627. Online ahead of print.

NO ABSTRACT

PMID:39487063 | DOI:10.1016/j.exger.2024.112627

Carbohydr Polym. 2025 Jan 1;347:122750. doi: 10.1016/j.carbpol.2024.122750. Epub 2024 Sep 17.

ABSTRACT

Designing materials for wound dressings with superior therapeutic benefits, self-healing and injectable characteristics is important in clinical practice. Herein, a new self-healing injectable hydrogel was prepared via thermal treatment and dynamic Schiff base reaction by mixing oxidized hyaluronic acid (OHA) and hydrazided Salecan (Sal-ADH). The versatility of the wound dressing was confirmed by studying the inherent rheological properties, high swelling rate, sustained-release behavior of the drug, pH/hyaluronidase-dependent biodegradation, in vitro antimicrobial as well as in vivo wound healing performance. The presence of the antimicrobial drug polyhexamethylene biguanide (PHMB) conferred good antimicrobial properties to the Sal-ADH/OHA/PHMB (SOP) hydrogel, which could effectively prevent wound infection (the width of the inhibition circle of SOP-0.20 hydrogel was 4.97 mm, 5.93 mm for Staphylococcus aureus and Escherichia coli, respectively). The findings suggested that SOP hydrogel exhibited remarkable self-healing and injectability properties, as well as excellent hemostasis and biocompatibility. In vivo experiments indicated that the application of SOP hydrogels would obviously accelerate wound healing and attenuate the inflammatory response while increasing collagen deposition and angiogenesis. Altogether, antibacterial SOP hydrogels with moderate mechanical properties, pH-responsive release, excellent injectability, exceptional self-healing ability and anti-inflammatory effects could expand potential applications of injectable hydrogels in the biomedical field.

PMID:39486979 | DOI:10.1016/j.carbpol.2024.122750

Cytometry A. 2024 Nov 1. doi: 10.1002/cyto.a.24901. Online ahead of print.

ABSTRACT

Mass cytometry enables deep profiling of biological samples at single-cell resolution. This technology is more than relevant in cancer research due to high cellular heterogeneity and complexity. Downstream analysis of high-dimensional datasets increasingly relies on machine learning (ML) to extract clinically relevant information, including supervised algorithms for classification and regression purposes. In cancer research, they are used to develop predictive models that will guide clinical decision making. However, the development of supervised algorithms faces major challenges, such as sufficient validation, before being translated into the clinics. In this work, we provide a framework for the analysis of mass cytometry data with a specific focus on supervised algorithms and practical examples of their applications. We also raise awareness on key issues regarding good practices for researchers curious to implement supervised ML on their mass cytometry data. Finally, we discuss the challenges of supervised ML application to cancer research.

PMID:39486897 | DOI:10.1002/cyto.a.24901

Math Biosci. 2024 Oct 30:109330. doi: 10.1016/j.mbs.2024.109330. Online ahead of print.

ABSTRACT

The present work focuses on a non-local integro-differential model reproducing Cancer-on-chip experiments where tumor cells, treated with chemotherapy drugs, secrete chemical signals stimulating the immune response. The reliability of the model in reproducing the phenomenon of interest is investigated through a global sensitivity analysis, rather than a local one, to have global information about the role of parameters, and by examining potential non-linear effects in greater detail. Focusing on a region in the parameter space, the effect of 13 model parameters on the in silico outcome is investigated by considering 11 different target outputs, properly selected to monitor the spatial distribution and the dynamics of immune cells along the period of observation. In order to cope with the large number of model parameters to be investigated and the computational cost of each numerical simulation, a two-step global sensitivity analysis is performed. First, the screening Morris method is applied to rank the effect of the 13 model parameters on each target output and it emerges that all the output targets are mainly affected by the same 6 parameters. The extended Fourier Amplitude Sensitivity Test (eFAST) method is then used to quantify the role of these 6 parameters. As a result, the proposed analysis highlights the feasibility of the considered space of parameters, and indicates that the most relevant parameters are those related to the chemical field and cell-substrate adhesion. In turn, it suggests how to possibly improve the model description as well as the calibration procedure, in order to better capture the observed phenomena and, at the same time, reduce the complexity of the simulation algorithm. On one hand, the model could be simplified by neglecting cell-cell alignment effects unless clear empirical evidences of their importance emerge. On the other hand, the best way to increase the accuracy and reliability of our model predictions would be to have experimental data/information to reduce the uncertainty of the more relevant parameters.

PMID:39486639 | DOI:10.1016/j.mbs.2024.109330

Cancer Cell. 2024 Oct 30:S1535-6108(24)00395-7. doi: 10.1016/j.ccell.2024.10.007. Online ahead of print.

ABSTRACT

Intratumoral TLR9 agonists and anti-PD-1 produce clinical responses and broad immune activation. We conducted a single-arm study of neoadjuvant TLR9 agonist vidutolimod combined with anti-PD-1 nivolumab in high-risk resectable melanoma. In 31 evaluable patients, 55% major pathologic response (MPR) was observed, meeting primary endpoint. MPR was associated with necrosis, and melanophagocytosis with increased CD8+ tumor-infiltrating lymphocytes and plasmacytoid dendritic cells (pDCs) in the tumor microenvironment, and increased frequencies of Ki67+CD8+ T cells peripherally. MPRs had an enriched pre-treatment gene signature of myeloid cells, and response to therapy was associated with gene signatures of immune cells, pDCs, phagocytosis, and macrophage activation. MPRs gut microbiota were enriched for Gram-negative bacteria belonging to the Bacteroidaceae and Enterobacteriaceae families and the small subgroup of Gram-negative Firmicutes. Our findings support that combined vidutolimod and nivolumab stimulates a broad anti-tumor immune response and is associated with distinct baseline myeloid gene signature and gut microbiota. ClinicalTrials.gov identifier: NCT03618641.

PMID:39486411 | DOI:10.1016/j.ccell.2024.10.007

Genetics. 2024 Nov 1:iyae178. doi: 10.1093/genetics/iyae178. Online ahead of print.

ABSTRACT

Cryptococcus neoformans is an opportunistic fungal pathogen with a polysaccharide capsule that becomes greatly enlarged in the mammalian host and during in vitro growth under host-like conditions. To understand how individual environmental signals affect capsule size and gene expression, we grew cells in all combinations of five signals implicated in capsule size and systematically measured cell and capsule sizes. We also sampled these cultures over time and performed RNA-Seq in quadruplicate, yielding 881 RNA-Seq samples. Analysis of the resulting data sets showed that capsule induction in tissue culture medium, typically used to represent host-like conditions, requires the presence of either CO2 or exogenous cyclic AMP (cAMP). Surprisingly, adding either of these pushes overall gene expression in the opposite direction from tissue culture media alone, even though both are required for capsule development. Another unexpected finding was that rich medium blocks capsule growth completely. Statistical analysis further revealed many genes whose expression is associated with capsule thickness; deletion of one of these significantly reduced capsule size. Beyond illuminating capsule induction, our massive, uniformly collected dataset will be a significant resource for the research community.

PMID:39485829 | DOI:10.1093/genetics/iyae178