Front Microbiol. 2024 Mar 5;15:1337368. doi: 10.3389/fmicb.2024.1337368. eCollection 2024.

ABSTRACT

Meta-organisms encompassing the host and resident microbiota play a significant role in combatting diseases and responding to stress. Hence, there is growing traction to build a knowledge base about this ecosystem, particularly to characterize the bidirectional relationship between the host and microbiota. In this context, metabolomics has emerged as the major converging node of this entire ecosystem. Systematic comprehension of this resourceful omics component can elucidate the organism-specific response trajectory and the communication grid across the ecosystem embodying meta-organisms. Translating this knowledge into designing nutraceuticals and next-generation therapy are ongoing. Its major hindrance is a significant knowledge gap about the underlying mechanisms maintaining a delicate balance within this ecosystem. To bridge this knowledge gap, a holistic picture of the available information has been presented with a primary focus on the microbiota-metabolite relationship dynamics. The central theme of this article is the gut-brain axis and the participating microbial metabolites that impact cerebral functions.

PMID:38505556 | PMC:PMC10949987 | DOI:10.3389/fmicb.2024.1337368

MicroPubl Biol. 2024 Mar 4;2024. doi: 10.17912/micropub.biology.001006. eCollection 2024.

ABSTRACT

In the early stage of the nematode Caenorhabditis elegans embryogenesis, the zygote divides asymmetrically into a symmetric fast lineage and an asymmetric slow lineage, producing 16 and 8 cells respectively almost at the same time, followed by the onset of gastrulation. It was recently reported that this cell division pattern is optimal for rapid cell proliferation. In this work, we compare the cell lineages of 9 nematode species, revealing that this pattern is conserved for >60 million years. It further suggests that such lineage design has an important functional role and it might speed up embryonic development in the nematode kingdom, not limited to C. elegans , and independent of the maternal-zygotic transition dynamics.

PMID:38505394 | PMC:PMC10949086 | DOI:10.17912/micropub.biology.001006

Front Immunol. 2024 Mar 5;15:1388453. doi: 10.3389/fimmu.2024.1388453. eCollection 2024.

NO ABSTRACT

PMID:38504992 | PMC:PMC10949890 | DOI:10.3389/fimmu.2024.1388453

Front Plant Sci. 2024 Mar 5;15:1331156. doi: 10.3389/fpls.2024.1331156. eCollection 2024.

ABSTRACT

Trichome patterning in Arabidopsis is regulated by R2R3MYB, bHLH and WDR (MBW) genes. These are considered to form a trimeric MBW protein complex that promotes trichome formation. The MBW proteins are engaged in a regulatory network to select trichome cells among epidermal cells through R3MYB proteins that can move between cells and repress the MBW complex by competitive binding with the R2R3MYB to the bHLHL protein. We use quantitative pull-down assays to determine the relative dissociation constants for the protein-protein interactions of the involved genes. We find similar binding strength between the trichome promoting genes and weaker binding of the R3MYB inhibitors. We used the dissociation constants to calculate the relative percentage of all possible complex combinations and found surprisingly low fractions of those complexes that are typically considered to be relevant for the regulation events. Finally, we predict an increased robustness in patterning as a consequence of higher ordered complexes mediated by GL3 dimerization.

PMID:38504903 | PMC:PMC10948613 | DOI:10.3389/fpls.2024.1331156

Microsc Res Tech. 2024 Mar 19. doi: 10.1002/jemt.24556. Online ahead of print.

ABSTRACT

Estrus detection in buffaloes primarily relies on behavioral and physiological signs. Especially during summer, these signs are less prominent to recognize. Thus, estrus detection is a pronounced challenge within the realm of buffalo husbandry, particularly in the summer. Therefore, a simple and accurate estrus detection method is required for buffalo farmers. The observation of fern-like salivary crystallization patterns is one such simple method to detect estrus in buffaloes, bactrian camels, beagle bitches, and cows. However, the exact mechanism for the formation of typical fern-like is not known. We hypothesized that it might be because of the estrus-specific mucins and salts. To test this hypothesis, we prepared the smears by combining different concentrations of mucin type -2 (MUC2) and -3 (MUC3) with sodium chloride (NaCl). Microscopic examination confirmed that fern-like patterns resulted from a combination of the MUC3 and NaCl produced more realistic fern patterns than that of MUC2 or BSA with salt. To predict possible mucin and salt concentration showing natural fern-like patterns at the estrus stage in buffalo saliva, we constructed a guide tree of artificially generated fern-like patterns using an image analysis online tool. This computation analysis revealed that most of the natural buffalo estrus saliva samples showing typical fern-like patterns clustered in the cluster 2 of the guide tree comprising of 13 clusters. In the cluster 2, MUC3 in combination with the salt concentrations of 100, 150, and 250 mM was commonly found in a close proximity to the natural typical fern-like patterns of saliva smear of buffaloes at estrus. Conclusively, the buffalo saliva at estrus is predicted to have a gel-forming heavily glycosylated protein such as mucin along with at least 100 mM of NaCl. RESEARCH HIGHLIGHTS: Glycoprotein and salts combination replicates fern-like pattern of buffalo saliva at estrus. MUC3 and NaCl salt combination produces more realistic fern-like patterns compared with MUC2 or BSA and salt combination. MUC3 with NaCl at 100, 150, and 250 mM consistently resembled natural estrus saliva fern-like patterns. During estrus, buffalo saliva is expected to contain heavily glycosylated mucin and at least of 100 mM NaCl.

PMID:38504429 | DOI:10.1002/jemt.24556

J Chem Inf Model. 2024 Mar 19. doi: 10.1021/acs.jcim.3c01878. Online ahead of print.

ABSTRACT

Proteolysis-targeting chimeras (PROTACs) that engage two biological targets at once are a promising technology in degrading clinically relevant protein targets. Since factors that influence the biological activities of PROTACs are more complex than those of a small molecule drug, we explored a combination of computational chemistry and deep learning strategies to forecast PROTAC activity and enable automated design. A new method named PROTACable was developed for the de novo design of PROTACs, which includes a robust 3-D modeling workflow to model PROTAC ternary complexes using a library of E3 ligase and linker and an SE(3)-equivariant graph transformer network to predict the activity of newly designed PROTACs. PROTACable is available at https://github.com/giaguaro/PROTACable/.

PMID:38504115 | DOI:10.1021/acs.jcim.3c01878

Nat Methods. 2024 Mar 19. doi: 10.1038/s41592-024-02216-7. Online ahead of print.

ABSTRACT

The ENCODE Consortium's efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE-gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.

PMID:38504114 | DOI:10.1038/s41592-024-02216-7

Nat Med. 2024 Mar 19. doi: 10.1038/s41591-024-02857-3. Online ahead of print.

ABSTRACT

Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks, requiring the objective characterization of histopathological entities from whole-slide images (WSIs). The high resolution of WSIs and the variability of morphological features present significant challenges, complicating the large-scale annotation of data for high-performance applications. To address this challenge, current efforts have proposed the use of pretrained image encoders through transfer learning from natural image datasets or self-supervised learning on publicly available histopathology datasets, but have not been extensively developed and evaluated across diverse tissue types at scale. We introduce UNI, a general-purpose self-supervised model for pathology, pretrained using more than 100 million images from over 100,000 diagnostic H&E-stained WSIs (>77 TB of data) across 20 major tissue types. The model was evaluated on 34 representative CPath tasks of varying diagnostic difficulty. In addition to outperforming previous state-of-the-art models, we demonstrate new modeling capabilities in CPath such as resolution-agnostic tissue classification, slide classification using few-shot class prototypes, and disease subtyping generalization in classifying up to 108 cancer types in the OncoTree classification system. UNI advances unsupervised representation learning at scale in CPath in terms of both pretraining data and downstream evaluation, enabling data-efficient artificial intelligence models that can generalize and transfer to a wide range of diagnostically challenging tasks and clinical workflows in anatomic pathology.

PMID:38504018 | DOI:10.1038/s41591-024-02857-3

Nat Microbiol. 2024 Mar 19. doi: 10.1038/s41564-024-01628-7. Online ahead of print.

ABSTRACT

Microbiota-directed complementary food (MDCF) formulations have been designed to repair the gut communities of malnourished children. A randomized controlled trial demonstrated that one formulation, MDCF-2, improved weight gain in malnourished Bangladeshi children compared to a more calorically dense standard nutritional intervention. Metagenome-assembled genomes from study participants revealed a correlation between ponderal growth and expression of MDCF-2 glycan utilization pathways by Prevotella copri strains. To test this correlation, here we use gnotobiotic mice colonized with defined consortia of age- and ponderal growth-associated gut bacterial strains, with or without P. copri isolates closely matching the metagenome-assembled genomes. Combining gut metagenomics and metatranscriptomics with host single-nucleus RNA sequencing and gut metabolomic analyses, we identify a key role of P. copri in metabolizing MDCF-2 glycans and uncover its interactions with other microbes including Bifidobacterium infantis. P. copri-containing consortia mediated weight gain and modulated energy metabolism within intestinal epithelial cells. Our results reveal structure-function relationships between MDCF-2 and members of the gut microbiota of malnourished children with potential implications for future therapies.

PMID:38503977 | DOI:10.1038/s41564-024-01628-7

Nat Plants. 2024 Mar 19. doi: 10.1038/s41477-024-01652-9. Online ahead of print.

ABSTRACT

The plant DNA damage response (DDR) pathway safeguards genomic integrity by rapid recognition and repair of DNA lesions that, if unrepaired, may cause genome instability. Most frequently, DNA repair goes hand in hand with a transient cell cycle arrest, which allows cells to repair the DNA lesions before engaging in a mitotic event, but consequently also affects plant growth and yield. Through the identification of DDR proteins and cell cycle regulators that react to DNA double-strand breaks or replication defects, it has become clear that these proteins and regulators form highly interconnected networks. These networks operate at both the transcriptional and post-transcriptional levels and include liquid-liquid phase separation and epigenetic mechanisms. Strikingly, whereas the upstream DDR sensors and signalling components are well conserved across eukaryotes, some of the more downstream effectors are diverged in plants, probably to suit unique lifestyle features. Additionally, DDR components display functional diversity across ancient plant species, dicots and monocots. The observed resistance of DDR mutants towards aluminium toxicity, phosphate limitation and seed ageing indicates that gaining knowledge about the plant DDR may offer solutions to combat the effects of climate change and the associated risk for food security.

PMID:38503962 | DOI:10.1038/s41477-024-01652-9

Cell Rep Methods. 2024 Mar 12:100733. doi: 10.1016/j.crmeth.2024.100733. Online ahead of print.

ABSTRACT

Here, we present Anchored-fusion, a highly sensitive fusion gene detection tool. It anchors a gene of interest, which often involves driver fusion events, and recovers non-unique matches of short-read sequences that are typically filtered out by conventional algorithms. In addition, Anchored-fusion contains a module based on a deep learning hierarchical structure that incorporates self-distillation learning (hierarchical view learning and distillation [HVLD]), which effectively filters out false positive chimeric fragments generated during sequencing while maintaining true fusion genes. Anchored-fusion enables highly sensitive detection of fusion genes, thus allowing for application in cases with low sequencing depths. We benchmark Anchored-fusion under various conditions and found it outperformed other tools in detecting fusion events in simulated data, bulk RNA sequencing (bRNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Our results demonstrate that Anchored-fusion can be a useful tool for fusion detection tasks in clinically relevant RNA-seq data and can be applied to investigate intratumor heterogeneity in scRNA-seq data.

PMID:38503288 | DOI:10.1016/j.crmeth.2024.100733

Methods Mol Biol. 2024;2776:305-320. doi: 10.1007/978-1-0716-3726-5_19.

ABSTRACT

ChloroKB ( http://chlorokb.fr ) is a knowledge base providing synoptic representations of the metabolism of the model plant Arabidopsis thaliana and its regulation. Initially focused on plastid metabolism, ChloroKB now accounts for the metabolism throughout the cell. ChloroKB is based on the CellDesigner formalism. CellDesigner supports graphical notation and listing of the corresponding symbols based on the Systems Biology Graphical Notation. Thus, this formalism allows biologists to represent detailed biochemical processes in a way that can be easily understood and shared, facilitating communication between researchers. In this chapter, we will focus on a specificity of ChloroKB, the representation of multilayered regulation of protein activity. Information on regulation of protein activity is indeed central to understanding the plant response to fluctuating environmental conditions. However, the intrinsic diversity of the regulatory modes and the abundance of detail may hamper comprehension of the regulatory processes described in ChloroKB. With this chapter, ChloroKB users will be guided through the representation of these sophisticated biological processes of prime importance to understanding metabolism or for applied purposes. The descriptions provided, which summarize years of work and a broad bibliography in a few pages, can help speed up the integration of regulatory processes in kinetic models of plant metabolism.

PMID:38502513 | DOI:10.1007/978-1-0716-3726-5_19

Methods Mol Biol. 2024;2784:25-44. doi: 10.1007/978-1-0716-3766-1_2.

ABSTRACT

Candida albicans is the most prevalent human fungal pathogen. Its pathogenicity is linked to the ability of C. albicans to reversibly change morphology and to grow as yeast, pseudohyphae, or hyphal cells in response to environmental stimuli. Understanding the molecular regulation controlling those morphological switches remains a challenge that, if solved, could help eradicate C. albicans infections.While numerous studies investigated gene expression changes occurring during C. albicans morphological switches using bulk approaches (e.g., RNA sequencing), here we describe a single-cell and single-molecule RNA imaging and analysis protocol to measure absolute mRNA counts in morphologically intact cells. To detect endogenous mRNAs in single fixed cells, we optimized a single-molecule fluorescent in situ hybridization (smFISH) protocol for C. albicans, which allows one to quantify the differential expression of mRNAs in yeast, pseudohyphae, or hyphal cells. We quantified the expression of two mRNAs, a cell cycle-controlled mRNA (CLB2) and a transcription factor (EFG1), which show expression changes in the different morphological cell types and nutrient conditions. In this protocol, we described in detail the major steps of this approach: growth and fixation, hybridization, imaging, cell segmentation, and mRNA spot analysis. Raw data is provided with the protocol to favor reproducibility. This approach could benefit the molecular characterization of C. albicans and other filamentous fungi, pathogenic or nonpathogenic.

PMID:38502476 | DOI:10.1007/978-1-0716-3766-1_2

J Exp Med. 2024 May 6;221(5):e20231359. doi: 10.1084/jem.20231359. Epub 2024 Mar 19.

ABSTRACT

Metastasis of primary tumors remains a challenge for early diagnosis and prevention. The cellular properties and molecular drivers of metastatically competent clones within primary tumors remain unclear. Here, we generated 10-16 single cell-derived lines from each of three colorectal cancer (CRC) tumors to identify and characterize metastatic seeds. We found that intrinsic factors conferred clones with distinct metastatic potential and cellular communication capabilities, determining organ-specific metastasis. Poorly differentiated or highly metastatic clones, rather than drug-resistant clones, exhibited poor clinical prognostic impact. Personalized genetic alterations, instead of mutation burden, determined the occurrence of metastatic potential during clonal evolution. Additionally, we developed a gene signature for capturing metastatic potential of primary CRC tumors and demonstrated a strategy for identifying metastatic drivers using isogenic clones with distinct metastatic potential in primary tumors. This study provides insight into the origin and mechanisms of metastasis and will help develop potential anti-metastatic therapeutic targets for CRC patients.

PMID:38502057 | DOI:10.1084/jem.20231359

Physiology (Bethesda). 2024 Mar 19. doi: 10.1152/physiol.00024.2023. Online ahead of print.

ABSTRACT

Cystic Fibrosis (CF) is an inherited disorder caused by a deleterious mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Given that the CFTR protein is a chloride channel expressed on a variety of cells throughout the human body, mutations in this gene impact several organs, particularly the lungs. For this very reason, research regarding CF disease and CFTR function has historically focused on the lung airway epithelium. Nevertheless, it has been discovered more than two decades ago that CFTR is also expressed and functional on endothelial cells. Despite the great strides that have been made in understanding the role of CFTR in the airway epithelium, the role of CFTR in the endothelium remains unclear. Considering that the airway epithelium and endothelium work in tandem to allow gas exchange, it becomes very crucial to understand how a defective CFTR protein can impact the pulmonary vasculature and overall lung function. Fortunately, more recent research has been dedicated to elucidating the role of CFTR in the endothelium. As a result, several vascular dysfunctions associated with CF disease have come to light. Here, we summarize the current knowledge on pulmonary vascular dysfunctions in CF and discuss applicable therapies.

PMID:38501963 | DOI:10.1152/physiol.00024.2023

Protein Sci. 2024 Apr;33(4):e4941. doi: 10.1002/pro.4941.

ABSTRACT

Tardigrades are microscopic animals that survive desiccation by inducing biostasis. To survive drying tardigrades rely on intrinsically disordered CAHS proteins, which also function to prevent perturbations induced by drying in vitro and in heterologous systems. CAHS proteins have been shown to form gels both in vitro and in vivo, which has been speculated to be linked to their protective capacity. However, the sequence features and mechanisms underlying gel formation and the necessity of gelation for protection have not been demonstrated. Here we report a mechanism of fibrillization and gelation for CAHS D similar to that of intermediate filament assembly. We show that in vitro, gelation restricts molecular motion, immobilizing and protecting labile material from the harmful effects of drying. In vivo, we observe that CAHS D forms fibrillar networks during osmotic stress. Fibrillar networking of CAHS D improves survival of osmotically shocked cells. We observe two emergent properties associated with fibrillization; (i) prevention of cell volume change and (ii) reduction of metabolic activity during osmotic shock. We find that there is no significant correlation between maintenance of cell volume and survival, while there is a significant correlation between reduced metabolism and survival. Importantly, CAHS D's fibrillar network formation is reversible and metabolic rates return to control levels after CAHS fibers are resolved. This work provides insights into how tardigrades induce reversible biostasis through the self-assembly of labile CAHS gels.

PMID:38501490 | DOI:10.1002/pro.4941

iScience. 2024 Mar 4;27(4):109386. doi: 10.1016/j.isci.2024.109386. eCollection 2024 Apr 19.

ABSTRACT

During cellular processes such as differentiation or response to external stimuli, cells exhibit dynamic changes in their gene expression profiles. Single-cell RNA sequencing (scRNA-seq) can be used to investigate these dynamic changes. To this end, cells are typically ordered along a pseudotemporal trajectory which recapitulates the progression of cells as they transition from one cell state to another. We infer transcriptional dynamics by modeling the gene expression profiles in pseudotemporally ordered cells using a Bayesian inference approach. This enables ordering genes along transcriptional cascades, estimating differences in the timing of gene expression dynamics, and deducing regulatory gene interactions. Here, we apply this approach to scRNA-seq datasets derived from mouse embryonic forebrain and pancreas samples. This analysis demonstrates the utility of the method to derive the ordering of gene dynamics and regulatory relationships critical for proper cellular differentiation and maturation across a variety of developmental contexts.

PMID:38500834 | PMC:PMC10946328 | DOI:10.1016/j.isci.2024.109386

iScience. 2024 Feb 29;27(4):109362. doi: 10.1016/j.isci.2024.109362. eCollection 2024 Apr 19.

ABSTRACT

The manifestation of metabolic deteriorations that accompany overweight and obesity can differ greatly between individuals, giving rise to a highly heterogeneous population. This inter-individual variation can impede both the provision and assessment of nutritional interventions as multiple aspects of metabolic health should be considered at once. Here, we apply the Mixed Meal Model, a physiology-based computational model, to characterize an individual's metabolic health in silico. A population of 342 personalized models were generated using data for individuals with overweight and obesity from three independent intervention studies, demonstrating a strong relationship between the model-derived metric of insulin resistance (ρ = 0.67, p < 0.05) and the gold-standard hyperinsulinemic-euglycemic clamp. The model is also shown to quantify liver fat accumulation and β-cell functionality. Moreover, we show that personalized Mixed Meal Models can be used to evaluate the impact of a dietary intervention on multiple aspects of metabolic health at the individual level.

PMID:38500825 | PMC:PMC10946327 | DOI:10.1016/j.isci.2024.109362

Front Pharmacol. 2024 Mar 4;15:1288584. doi: 10.3389/fphar.2024.1288584. eCollection 2024.

ABSTRACT

Objective: To evaluate the efficacy of the fruits of the medicinal plant Forsythia suspensa (Thunb.) Vahl (FS), in treating inflammation-associated diseases through a meta-analysis of animal models, and also probe deeply into the signaling pathways underlying the progression of inflammation. Materials and methods: All data analyses were performed using Review Manager 5.3 and the results are presented as flow diagrams, risk-of-bias summaries, forest plots, and funnel plots. Summary estimates were calculated using a random- or fixed-effect model, depending on the value of I2. Results: Of the 710 records identified in the initial search, 11 were selected for the final meta-analysis. Each study extracted data from the model and treatment groups for analysis, and the results showed that FS alleviated the inflammatory cytokine levels in serum; oxidant indicator: reactive oxygen species; enzymes of liver function; endotoxin and regulatory cells in blood; and improved the antioxidant enzyme superoxide dismutase. Conclusion: FS effectively reversed the change in acute or chronic inflammation indicators in animal models, and the regulation of multiple channel proteins in inflammatory signaling pathways suggests that FS is a good potential drug for inflammatory disease drug therapy.

PMID:38500762 | PMC:PMC10946063 | DOI:10.3389/fphar.2024.1288584

Clin Transl Med. 2024 Mar;14(3):e1626. doi: 10.1002/ctm2.1626.

ABSTRACT

The interplay between the immune system and the metabolic state of a cell is intricate. In all phases of an immune response, the corresponding metabolic changes shall occur to support its modulation, in addition to the signalling through the cytokine environment and immune receptor stimulation. While autoimmune disorders may develop because of a metabolic imbalance that modulates switching between T-cell phenotypes, the effects that the interaction between T and B cells have on one another's cellular metabolism are yet to be understood in disease context. Here, we propose a perspective which highlights the potential of targeting metabolism to modulate T- and B-cell subtypes populations as well as T-B and B-T cell interactions to successfully treat autoimmune disorders. Specifically, we envision how metabolic changes can tip the balance of immune cells interactions, through definite mechanisms in both health and disease, to explain phenotype switches of B and T cells. Within this scenario, we highlight targeting metabolism that link inflammation, immunometabolism, epigenetics and ageing, is critical to understand inflammatory disorders. The combination of treatments targeting immune cells that cause (T/B) cell phenotype imbalances, and the metabolic pathways involved, may increase the effectiveness of treatment of autoimmune disorders, and/or ameliorate their symptoms to improve patients' quality of life.

PMID:38500390 | DOI:10.1002/ctm2.1626