Arterioscler Thromb Vasc Biol. 2024 Oct 24. doi: 10.1161/ATVBAHA.124.321865. Online ahead of print.

NO ABSTRACT

PMID:39445423 | DOI:10.1161/ATVBAHA.124.321865

Plant Cell Environ. 2024 Oct 23. doi: 10.1111/pce.15227. Online ahead of print.

ABSTRACT

Drought is one of the most devastating causes of yield losses in crops like maize, and the anticipated increases in severity and duration of drought spells due to climate change pose an imminent threat to agricultural productivity. To understand the drought response, phenotypic and molecular studies are typically performed at a given time point after drought onset, representing a steady-state adaptation response. Because growth is a dynamic process, we monitored the drought response with high temporal resolution and examined cellular and transcriptomic changes after rehydration at 4 and 6 days after leaf four appearance. These data showed that division zone activity is a determinant for full organ growth recovery upon rehydration. Moreover, a prolonged maintenance of cell division by the ectopic expression of PLASTOCHRON1 extends the ability to resume growth after rehydration. The transcriptome analysis indicated that GROWTH-REGULATING FACTORS (GRFs) affect leaf growth by impacting cell division duration, which was confirmed by a prolonged recovery potential of the GRF1-overexpression line after rehydration. Finally, we used a multiplex genome editing approach to evaluate the most promising differentially expressed genes from the transcriptome study and as such narrowed down the gene space from 40 to seven genes for future functional characterization.

PMID:39444139 | DOI:10.1111/pce.15227

Nature. 2024 Oct 23. doi: 10.1038/s41586-024-08008-5. Online ahead of print.

ABSTRACT

Inflammation and tissue fibrosis co-exist and are causally linked to organ dysfunction1,2. However, the molecular mechanisms driving immune-fibroblast cell communication in human cardiac disease remain unexplored and there are at present no approved treatments that directly target cardiac fibrosis3,4. Here we performed multiomic single-cell gene expression, epitope mapping and chromatin accessibility profiling in 45 healthy donor, acutely infarcted and chronically failing human hearts. We identified a disease-associated fibroblast trajectory that diverged into distinct populations reminiscent of myofibroblasts and matrifibrocytes, the latter expressing fibroblast activator protein (FAP) and periostin (POSTN). Genetic lineage tracing of FAP+ fibroblasts in vivo showed that they contribute to the POSTN lineage but not the myofibroblast lineage. We assessed the applicability of experimental systems to model cardiac fibroblasts and demonstrated that three different in vivo mouse models of cardiac injury were superior compared with cultured human heart and dermal fibroblasts in recapitulating the human disease phenotype. Ligand-receptor analysis and spatial transcriptomics predicted that interactions between C-C chemokine receptor type 2 (CCR2) macrophages and fibroblasts mediated by interleukin-1β (IL-1β) signalling drove the emergence of FAP/POSTN fibroblasts within spatially defined niches. In vivo, we deleted the IL-1 receptor on fibroblasts and the IL-1β ligand in CCR2+ monocytes and macrophages, and inhibited IL-1β signalling using a monoclonal antibody, and showed reduced FAP/POSTN fibroblasts, diminished myocardial fibrosis and improved cardiac function. These findings highlight the broader therapeutic potential of targeting inflammation to treat tissue fibrosis and preserve organ function.

PMID:39443792 | DOI:10.1038/s41586-024-08008-5

Mol Syst Biol. 2024 Oct 23. doi: 10.1038/s44320-024-00067-0. Online ahead of print.

ABSTRACT

The genomic revolution has fueled rapid progress in synthetic and systems biology, opening up new possibilities for using live biotherapeutic products (LBP) to treat, attenuate or prevent human diseases. Among LBP, bacteria-based therapies are particularly promising due to their ability to colonize diverse human tissues, modulate the immune system and secrete or deliver complex biological products. These bacterial LBP include engineered pathogenic species designed to target specific diseases, and microbiota species that promote microbial balance and immune system homeostasis, either through local administration or the gut-body axes. This review focuses on recent advancements in preclinical and clinical trials of bacteria-based LBP, highlighting both on-site and long-reaching strategies.

PMID:39443745 | DOI:10.1038/s44320-024-00067-0

Oncogene. 2024 Oct 23. doi: 10.1038/s41388-024-03141-x. Online ahead of print.

ABSTRACT

The contribution of deubiquitylating enzymes (DUBs) to β-Catenin stabilization in intestinal stem cells and colorectal cancer (CRC) is poorly understood. Here, and by using an unbiassed screen, we discovered that the DUB USP10 stabilizes β-Catenin specifically in APC-truncated CRC in vitro and in vivo. Mechanistic studies, including in vitro binding together with computational modelling, revealed that USP10 binding to β-Catenin is mediated via the unstructured N-terminus of USP10 and is outcompeted by intact APC, favouring β-catenin degradation. However, in APC-truncated cancer cells USP10 binds to β-catenin, increasing its stability which is critical for maintaining an undifferentiated tumour identity. Elimination of USP10 reduces the expression of WNT and stem cell signatures and induces the expression of differentiation genes. Remarkably, silencing of USP10 in murine and patient-derived CRC organoids established that it is essential for NOTUM signalling and the APC super competitor-phenotype, reducing tumorigenic properties of APC-truncated CRC. These findings are clinically relevant as patient-derived organoids are highly dependent on USP10, and abundance of USP10 correlates with poorer prognosis of CRC patients. Our findings reveal, therefore, a role for USP10 in CRC cell identity, stemness, and tumorigenic growth by stabilising β-Catenin, leading to aberrant WNT signalling and degradation resistant tumours. Thus, USP10 emerges as a unique therapeutic target in APC truncated CRC.

PMID:39443725 | DOI:10.1038/s41388-024-03141-x

Nat Chem Biol. 2024 Oct 23. doi: 10.1038/s41589-024-01763-6. Online ahead of print.

ABSTRACT

Synthetic glycans (SGs) containing glycosidic linkages and structures not identified in nature offer a means for deliberately altering microbial community properties. Here pools of SG oligosaccharides were generated via polymerization of monosaccharides and screened for their ability to increase saccharolytic Bacteroides in ex vivo cultures of human fecal samples. A lead SG preparation was orally administered to gnotobiotic mice harboring a consortium of 56 cultured, phylogenetically diverse human gut bacteria and fed a Western diet. The abundances of 3 of 15 Bacteroides strains increased, most prominently B. intestinalis. Underlying mechanisms were characterized by analyzing in vivo expression of the carbohydrate utilization machinery, using retrievable microscopic paramagnetic particles with bound SG oligosaccharides and assaying SG degradation by individual purified B. intestinalis glycoside hydrolases. The results reveal that SGs can selectively co-opt carbohydrate utilization machinery in different human gut Bacteroides and demonstrate a means for identifying artificial carbohydrate structures for targeted bacterial manipulation.

PMID:39443715 | DOI:10.1038/s41589-024-01763-6

Nat Cell Biol. 2024 Oct 23. doi: 10.1038/s41556-024-01537-1. Online ahead of print.

ABSTRACT

The high diversity and complexity of the eukaryotic transcriptome make it difficult to effectively detect specific transcripts of interest. Current targeted RNA sequencing methods often require complex pre-sequencing enrichment steps, which can compromise the comprehensive characterization of the entire transcriptome. Here we describe programmable full-length isoform transcriptome sequencing (PROFIT-seq), a method that enriches target transcripts while maintaining unbiased quantification of the whole transcriptome. PROFIT-seq employs combinatorial reverse transcription to capture polyadenylated, non-polyadenylated and circular RNAs, coupled with a programmable control system that selectively enriches target transcripts during sequencing. This approach achieves over 3-fold increase in effective data yield and reduces the time required for detecting specific pathogens or key mutations by 75%. We applied PROFIT-seq to study colorectal polyp development, revealing the intricate relationship between host immune responses and bacterial infection. PROFIT-seq offers a powerful tool for accurate and efficient sequencing of target transcripts while preserving overall transcriptome quantification, with broad applications in clinical diagnostics and targeted enrichment scenarios.

PMID:39443694 | DOI:10.1038/s41556-024-01537-1

Nat Commun. 2024 Oct 23;15(1):9151. doi: 10.1038/s41467-024-53246-w.

ABSTRACT

In this study, we address the persistent challenge of providing adequate oxygen to transplanted cells by introducing a respiratoid biosystem. Central to our strategy is the chloroplast-transit-peptide (CTP), crucial for optimal oxygenation. Through conjugation of CTP with alginate, we achieve stabilization of chloroplast structure. Strategically anchored to the outer chloroplast membrane, CTP not only ensures structural integrity but also upregulates key photosynthesis-associated genes. This biosystem demonstrates exceptional efficacy in spontaneously generating oxygen, particularly under hypoxic conditions (~1% pO2). In an application, pancreatic islets encapsulated within the respiratoid biosystem and intraperitoneally implanted in diabetic mice maintain normal glucose levels effectively. Insulin secretion persists for 100 days post-xenotransplantation without the need for immunosuppressant administration, highlighting the reliance on the respiratoid biosystem's oxygen supply and structural stability. Our study demonstrates the respiratoid biosystem as a platform in tissue engineering, offering a nature-inspired solution to the critical challenge of spontaneous oxygen supply.

PMID:39443443 | DOI:10.1038/s41467-024-53246-w

Yi Chuan. 2024 Oct;46(10):760-778. doi: 10.16288/j.yczz.24-153.

ABSTRACT

Illustrating molecular mechanisms of human embryonic development has always been one of the most significant challenges in biology. The scarcity of human embryo samples, the difficulty in dissecting embryo samples, and the complex structures of human organs are the major obstacles in studying human embryogenesis. In recent years, with the rapid advancement of single-cell technology, humans can systematically analyze the dynamic changes in differentiation at various stages of the central dogma and achieve observation and research with spatial information. This has accelerated the progress in constructing a human developmental cell atlas, ultimately allowing us to depict the cell ontology, fate trajectories, and three-dimensional dynamic changes of human development. In this review, we first introduce the single-cell technologies used to construct the atlas, then summarize the latest progress in human developmental cell atlas, followed by identifying the main problems and challenges in this field so far. Finally, we discuss how to utilize the human developmental cell atlas to address key biological and medical issues. This review provides guidance for the optimal use of single-cell omics technology in constructing and applying a human developmental cell atlas.

PMID:39443307 | DOI:10.16288/j.yczz.24-153

Trends Cell Biol. 2024 Oct 22:S0962-8924(24)00190-9. doi: 10.1016/j.tcb.2024.09.004. Online ahead of print.

ABSTRACT

The majority of the DNA sequence in our genome is noncoding and not intended for synthesizing proteins. Nonetheless, genome-wide mapping of ribosome footprints has revealed widespread translation in annotated noncoding sequences, including long noncoding RNAs (lncRNAs), untranslated regions (UTRs), and introns of mRNAs. How cells suppress the translation of potentially toxic proteins from various noncoding sequences remains poorly understood. This review summarizes mechanisms for the mitigation of noncoding translation, including the BCL2-associated athanogene 6 (BAG6)-mediated proteasomal degradation pathway, which has emerged as a unifying mechanism to suppress the translation of diverse noncoding sequences in metazoan cells.

PMID:39443270 | DOI:10.1016/j.tcb.2024.09.004

Fish Shellfish Immunol. 2024 Oct 21:109978. doi: 10.1016/j.fsi.2024.109978. Online ahead of print.

ABSTRACT

Fish diseases significantly challenge global aquaculture, causing substantial financial losses and impacting sustainability, trade, and socioeconomic conditions. Understanding microbial pathogenesis and virulence at the molecular level is crucial for disease prevention in commercial fish. This review provides genomic insights into fish pathogenic bacteria from a systems biology perspective, aiming to promote sustainable aquaculture. It covers the genomic characteristics of various fish pathogens and their industry impact. The review also explores the systems biology of zebrafish, fish bacterial pathogens, and probiotic bacteria, offering insights into fish production, potential vaccines, and therapeutic drugs. Genome-scale metabolic models aid in studying pathogenic bacteria, contributing to disease management and antimicrobial development. Researchers have also investigated probiotic strains to improve aquaculture health. Additionally, the review highlights bioinformatics resources for fish and fish pathogens, which are essential for researchers. Systems biology approaches enhance understanding of bacterial fish pathogens by revealing virulence factors and host interactions. Despite challenges from the adaptability and pathogenicity of bacterial infections, sustainable alternatives are necessary to meet seafood demand. This review underscores the potential of systems biology in understanding fish pathogen biology, improving production, and promoting sustainable aquaculture.

PMID:39442738 | DOI:10.1016/j.fsi.2024.109978

Brain Res. 2024 Oct 21:149289. doi: 10.1016/j.brainres.2024.149289. Online ahead of print.

ABSTRACT

Neurons in the locus coeruleus (LC) have been traditionally viewed as a homogenous population. Recent studies begin to reveal their heterogeneity at multiple levels, ranging from molecular compositions to projection targets. To further uncover variations of neuronal properties in the LC, we took a genetic-based tagging approach to identify these neurons. Our data revealed diverse spike waveforms among neurons in the LC region, including a considerable fraction of narrow-spiking units. While all wide-spiking units possessed the regular waveform polarity (negative-positive deflection), the narrow units can be further divided based on opposing waveform polarities. Under anesthesia, wide units emitted action potential at a higher rate than the narrow units. Under wakefulness, only one subtype of narrow units exhibited fast-spiking phenotype. These neurons also had long latencies to optogenetic stimulation. In-situ hybridization further supported the existence of a small population of putative GABAergic neurons in the LC core. Together, our data reveal characteristic differences among neurons in the LC region, and suggest that a fraction of electrophysiologically-identified narrow-spiking neurons can be fast-spiking interneurons, and their fast-spiking feature is masked by anesthesia.

PMID:39442646 | DOI:10.1016/j.brainres.2024.149289

Stem Cell Res. 2024 Oct 20;81:103593. doi: 10.1016/j.scr.2024.103593. Online ahead of print.

ABSTRACT

We recruited a healthy 44-year-old female and obtained her skin fibroblasts. Subsequently, the induced pluripotent stem cell line was successfully established using non-integrated reprogramming technology. The cell line had a normal karyotype and has been confirmed to have good pluripotency through the detection of pluripotency markers and detection of teratoma formation. This cell line can serve as an effective control for studying the cellular pathological mechanisms of other specific mutations.

PMID:39442281 | DOI:10.1016/j.scr.2024.103593

J Proteome Res. 2024 Oct 23. doi: 10.1021/acs.jproteome.4c00663. Online ahead of print.

ABSTRACT

Covalent protein adducts formed by drugs or their reactive metabolites are risk factors for adverse reactions, and inactivation of cytochrome P450 (CYP) enzymes. Characterization of drug-protein adducts is limited due to lack of methods identifying and quantifying covalent adducts in complex matrices. This study presents a workflow that combines data-dependent and data-independent acquisition (DDA and DIA) based liquid chromatography with tandem mass spectrometry (LC-MS/MS) to detect very low abundance adducts resulting from CYP mediated drug metabolism in human liver microsomes (HLMs). HLMs were incubated with raloxifene as a model compound and adducts were detected in 78 proteins, including CYP3A and CYP2C family enzymes. Experiments with recombinant CYP3A and CYP2C enzymes confirmed adduct formation in all CYPs tested, including CYPs not subject to time-dependent inhibition by raloxifene. These data suggest adducts can be benign. DIA analysis showed variable adduct abundance in many peptides between livers, but no concomitant decrease of unadducted peptides. This study sets a new standard for adduct detection in complex samples, offering insights into the human adductome resulting from reactive metabolite exposure. The methodology presented will aid mechanistic studies to identify, quantify and differentiate between adducts that result in adverse drug reactions and those that are benign.

PMID:39442081 | DOI:10.1021/acs.jproteome.4c00663

Sci Adv. 2024 Oct 25;10(43):eadp2622. doi: 10.1126/sciadv.adp2622. Epub 2024 Oct 23.

ABSTRACT

Protein activity state, rather than protein or mRNA abundance, is a biologically regulated and relevant input to many processes in signaling, differentiation, development, and diseases such as cancer. While there are numerous methods to detect and quantify mRNA and protein abundance in biological samples, there are no general approaches to detect and quantify endogenous protein activity with single-cell resolution. Here, we report the development of a chemoproteomic platform, single-cell activity-dependent proximity ligation, which uses automated, microfluidics-based single-cell capture and nanoliter volume manipulations to convert the interactions of family-wide chemical activity probes with native protein targets into multiplexed, amplifiable oligonucleotide barcodes. We demonstrate accurate, reproducible, and multiplexed quantitation of a six-enzyme (Ag-6) panel with known ties to cancer cell aggressiveness directly in single cells. We further identified increased Ag-6 enzyme activity across breast cancer cell lines of increasing metastatic potential, as well as in primary patient-derived tumor cells and organoids from patients with breast cancer.

PMID:39441940 | DOI:10.1126/sciadv.adp2622

PLoS Comput Biol. 2024 Oct 23;20(10):e1012546. doi: 10.1371/journal.pcbi.1012546. Online ahead of print.

ABSTRACT

Public gene expression databases are a rapidly expanding resource of organism responses to diverse perturbations, presenting both an opportunity and a challenge for bioinformatics workflows to extract actionable knowledge of transcription regulatory network function. Here, we introduce a five-step computational pipeline, called iModulonMiner, to compile, process, curate, analyze, and characterize the totality of RNA-seq data for a given organism or cell type. This workflow is centered around the data-driven computation of co-regulated gene sets using Independent Component Analysis, called iModulons, which have been shown to have broad applications. As a demonstration, we applied this workflow to generate the iModulon structure of Bacillus subtilis using all high-quality, publicly-available RNA-seq data. Using this structure, we predicted regulatory interactions for multiple transcription factors, identified groups of co-expressed genes that are putatively regulated by undiscovered transcription factors, and predicted properties of a recently discovered single-subunit phage RNA polymerase. We also present a Python package, PyModulon, with functions to characterize, visualize, and explore computed iModulons. The pipeline, available at https://github.com/SBRG/iModulonMiner, can be readily applied to diverse organisms to gain a rapid understanding of their transcriptional regulatory network structure and condition-specific activity.

PMID:39441835 | DOI:10.1371/journal.pcbi.1012546

Proc Natl Acad Sci U S A. 2024 Oct 29;121(44):e2402340121. doi: 10.1073/pnas.2402340121. Epub 2024 Oct 23.

ABSTRACT

As their statistical power grows, genome-wide association studies (GWAS) have identified an increasing number of loci underlying quantitative traits of interest. These loci are scattered throughout the genome and are individually responsible only for small fractions of the total heritable trait variance. The recently proposed omnigenic model provides a conceptual framework to explain these observations by postulating that numerous distant loci contribute to each complex trait via effect propagation through intracellular regulatory networks. We formalize this conceptual framework by proposing the "quantitative omnigenic model" (QOM), a statistical model that combines prior knowledge of the regulatory network topology with genomic data. By applying our model to gene expression traits in yeast, we demonstrate that QOM achieves similar gene expression prediction performance to traditional GWAS with hundreds of times less parameters, while simultaneously extracting candidate causal and quantitative chains of effect propagation through the regulatory network for every individual gene. We estimate the fraction of heritable trait variance in cis- and in trans-, break the latter down by effect propagation order, assess the trans- variance not attributable to transcriptional regulation, and show that QOM correctly accounts for the low-dimensional structure of gene expression covariance. We furthermore demonstrate the relevance of QOM for systems biology, by employing it as a statistical test for the quality of regulatory network reconstructions, and linking it to the propagation of nontranscriptional (including environmental) effects.

PMID:39441639 | DOI:10.1073/pnas.2402340121

Nucleic Acids Res. 2024 Oct 23:gkae920. doi: 10.1093/nar/gkae920. Online ahead of print.

ABSTRACT

The Bio-Analytic Resource for Plant Biology ('the BAR', at https://bar.utoronto.ca) is celebrating its 20th year in operation in 2025. The BAR encompasses and provides visualization tools for large 'omics data sets from plants. The BAR covers data from Arabidopsis, tomato, wheat, barley and 29 other plant species (with data for 2 others to be released soon). These data include nucleotide and protein sequence data, gene expression data, protein-protein and protein-DNA interactions, protein structures, subcellular localizations, and polymorphisms. The data are stored in more than 200 relational databases holding 186 GB of data and are presented to the researchers via web apps. These web apps provide data analysis and visualization tools. Some of the most popular tools are eFP ('electronic fluorescent pictograph') Browsers, ePlants and ThaleMine (an Arabidopsis-specific instance of InterMine). The BAR was designated a Global Core Biodata Resource in 2023. Like other GCBRs, the BAR has excellent operational stability, provides access without login requirement, and provides an API for researchers to be able to access BAR data programmatically. We present in this update a new overarching search tool called Gaia that permits easy access to all BAR data, powered by machine learning and artificial intelligence.

PMID:39441075 | DOI:10.1093/nar/gkae920

Physiother Res Int. 2024 Oct;29(4):e70002. doi: 10.1002/pri.70002.

ABSTRACT

BACKGROUND AND PURPOSE: To our knowledge, there is currently no research on telerehabilitation concerning artists. This study aims to assess the feasibility, acceptability, and effectiveness of utilizing video-based telerehabilitation in physiotherapy among artists during the COVID-19 pandemic.

METHODS: Fifty-one artists who accessed virtual physiotherapy between November 2020 and February 2022 at a healthcare center that provides specialized healthcare services to artists of all disciplines who reside or work in Ontario, Canada were asked to complete a 26-item online questionnaire about their experience with virtual physiotherapy.

RESULTS: The 51 respondents were from a range of artistic disciplines, with the largest portion being musicians (n = 22; 43%). Of the respondents, 86% (n = 44) felt the virtual physiotherapy met their expectations in therapeutic benefits, 78% (n = 40) were confident in performing all the exercises that the physiotherapist demonstrated on the virtual platform, 80% (n = 41) did not run into many technological challenges when booking or attending virtual sessions, and 54% (n = 20) reported similar treatment outcomes between virtual and in-person sessions. Although artists liked the convenience of accessing physiotherapy from home, 53% (n = 17) of respondents rated the lack of physical contact as a major limitation in telerehabilitation.

CONCLUSION: Telerehabilitation for artists during the COVID-19 pandemic has shown potential to be an effective and viable alternative to in-person physiotherapy, as demonstrated by high satisfaction levels and comparable treatment outcomes, especially when public health restrictions were in place. Future research can explore hybrid models (mix of in-person and virtual sessions) in physiotherapy to meet the needs for physical contact during sessions.

PMID:39440918 | DOI:10.1002/pri.70002

Adv Sci (Weinh). 2024 Oct 23:e2409170. doi: 10.1002/advs.202409170. Online ahead of print.

ABSTRACT

Quantifying molecular regulations between genes/molecules causally from observed data is crucial for elucidating the molecular mechanisms underlying biological processes at the network level. Presently, most methods for inferring gene regulatory and biological networks rely on association studies or observational causal-analysis approaches. This study introduces a novel approach that combines intervention operations and diffusion models within a do-calculus framework by deep learning, i.e., Causal Diffusion Do-calculus (CDD) analysis, to infer causal networks between molecules. CDD can extract causal relations from observed data owing to its intervention operations, thereby significantly enhancing the accuracy and generalizability of causal network inference. Computationally, CDD has been applied to both simulated data and real omics data, which demonstrates that CDD outperforms existing methods in accurately inferring gene regulatory networks and identifying causal links from genes to disease phenotypes. Especially, compared with the Mendelian randomization algorithm and other existing methods, the CDD can reliably identify the disease genes or molecules for complex diseases with better performances. In addition, the causal analysis between various diseases and the potential factors in different populations from the UK Biobank database is also conducted, which further validated the effectiveness of CDD.

PMID:39440482 | DOI:10.1002/advs.202409170