Front Pharmacol. 2023 Jun 13;14:1200164. doi: 10.3389/fphar.2023.1200164. eCollection 2023.

ABSTRACT

Background: Renal fibrosis is one of the most important triggers of chronic kidney disease (CKD), and only a very limited number of therapeutic options are available to stop fibrosis progression. As fibrosis is characterized by inflammation, myofibroblast activation, and extracellular matrix (ECM) deposition, a drug that can address all these processes might be an interesting therapeutic option. Methods: We tested in vivo in an ischemia-reperfusion (I/R) model in C57BL/6 mice and in kidney tubular epithelial cells (TEC) (HK2 cell line and primary cells) whether the natural product oxacyclododecindione (Oxa) reduces fibrosis progression in kidney disease. This was evaluated by Western blot, mRNA expression, and mass spectrometry secretome analyses, as well as by immunohistochemistry. Results: Indeed, Oxa blocked the expression of epithelial-mesenchymal transition marker proteins and reduced renal damage, immune cell infiltration, and collagen expression and deposition, both in vivo and in vitro. Remarkably, the beneficial effects of Oxa were also detected when the natural product was administered at a time point of established fibrotic changes, a situation close to the clinical situation. Initial in vitro experiments demonstrated that a synthetic Oxa derivative possesses similar features. Conclusion: Although open questions such as possible side effects need to be investigated, our results indicate that the combination of anti-inflammatory and anti-fibrotic effects of Oxa make the substance a promising candidate for a new therapeutic approach in fibrosis treatment, and thus in the prevention of kidney disease progression.

PMID:37383717 | PMC:PMC10294233 | DOI:10.3389/fphar.2023.1200164

JAMA Oncol. 2023 Jun 29. doi: 10.1001/jamaoncol.2023.2000. Online ahead of print.

ABSTRACT

IMPORTANCE: Combination therapy with cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i: palbociclib, ribociclib, abemaciclib) and endocrine therapy (ET) has been a major advance for the treatment of hormone receptor-positive (HR+), ERBB2 (formerly HER2)-negative (ERBB2-) advanced or metastatic breast cancer.

OBSERVATIONS: Randomized phase 3 studies demonstrated that the addition of CDK4/6i reduced the hazard risk of disease progression by approximately half compared with hormonal monotherapy (an aromatase inhibitor, tamoxifen, or fulvestrant) in the first-line (1L) and/or second-line (2L) setting. Hence, the US Food and Drug Administration and European Medicines Agency approved 3 CDK4/6i, in both 1L and 2L settings. However, differences among the CDK4/6i regarding mechanisms of action, adverse effect profiles, and overall survival (OS) are emerging. Both abemaciclib and ribociclib have demonstrated efficacy in high-risk HR+ early breast cancer. While ET with or without CDK4/6i is accepted as standard treatment for persons with advanced HR+ ERBB2- metastatic breast cancer, several key issues remain. First, why are there discordances in OS in the metastatic setting and efficacy differences in the adjuvant setting? Additionally, apart from HR status, there are few biomarkers predictive of response to CDK4/6i plus ET, and these are not used routinely. Despite the clear OS advantage noted in the 1L and 2L metastatic setting with some CDK4/6i, a subset of patients with highly endocrine-sensitive disease do well with ET alone. Therefore, an unanswered question is whether some patients can postpone CDK4/6i until the 2L setting, particularly if financial toxicity is a concern. Finally, given the lack of endocrine responsiveness following progression on some CDK4/6i, strategies to optimally sequence treatment are needed.

CONCLUSIONS AND RELEVANCE: Future research should focus on defining the role of each CDK4/6i in HR+ breast cancer and developing a biomarker-directed integration of these agents.

PMID:37382948 | DOI:10.1001/jamaoncol.2023.2000

Bioinformatics. 2023 Jun 29:btad414. doi: 10.1093/bioinformatics/btad414. Online ahead of print.

ABSTRACT

MOTIVATION: Simultaneous profiling of multi-omics single cell data represents exciting technological advancements for understanding cellular states and heterogeneity. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), allowed for parallel quantification of cell-surface protein expression and transcriptome profiling in the same cells; Methylome and transcriptome sequencing from single-cells (scM&T-Seq) allows for analysis of transcriptomic and epigenomic profiling in the same individual cells. However, effective integration method for minning the heterogeneity of cells over the noisy, sparse and complex multi-modal data is in growing need.

RESULTS: In this paper, we propose a multi-modal high-order neighborhood Laplacian matrix optimization framework for integrating the multi-omics single cell data: scHoML. Hierarchical clustering method was presented for analyzing the optimal embedding representation and identifying cell clusters in a robust manner. This novel method by integrating high-order and multi-modal Laplacian matrices would robustly represent the complex data structures and allow for systematic analysis at the multi-omics single cell level, thus promoting further biological discoveries.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37382572 | DOI:10.1093/bioinformatics/btad414

EMBO Rep. 2023 Jun 29:e57638. doi: 10.15252/embr.202357638. Online ahead of print.

ABSTRACT

The EMBO Journal and EMBO Reports join EMBO Molecular Medicine, Molecular Systems Biology and Life Science Alliance as Open Access journals from 2024. Full Open Access at EMBO Press completes another step towards the goal of an integrated Open Science approach for the dissemination of highly selected and curated science.

PMID:37382563 | DOI:10.15252/embr.202357638

Adv Sci (Weinh). 2023 Jun 29:e2302159. doi: 10.1002/advs.202302159. Online ahead of print.

ABSTRACT

DNA methylation plays a crucial role in the survival of bacteriophages (phages), yet the understanding of their genome methylation remains limited. In this study, DNA methylation patterns are analyzed in 8848 metagenome-assembled high-quality phages from 104 fecal samples using single-molecule real-time sequencing. The results demonstrate that 97.60% of gut phages exhibit methylation, with certain factors correlating with methylation densities. Phages with higher methylation densities appear to have potential viability advantages. Strikingly, more than one-third of the phages possess their own DNA methyltransferases (MTases). Increased MTase copies are associated with higher genome methylation densities, specific methylation motifs, and elevated prevalence of certain phage groups. Notably, the majority of these MTases share close homology with those encoded by gut bacteria, suggesting their exchange during phage-bacterium interactions. Furthermore, these MTases can be employed to accurately predict phage-host relationships. Overall, the findings indicate the widespread utilization of DNA methylation by gut DNA phages as an evasion mechanism against host defense systems, with a substantial contribution from phage-encoded MTases.

PMID:37382405 | DOI:10.1002/advs.202302159

Curr Opin Nephrol Hypertens. 2023 May 29. doi: 10.1097/MNH.0000000000000904. Online ahead of print.

ABSTRACT

PURPOSE OF REVIEW: Tissue clearing enables examination of biological structures at subcellular resolution in three dimensions. It uncovered the spatial and temporal plasticity of multicellular kidney structures that occur during homeostatic stress. This article will review the recent development in tissue clearing protocols and how it facilitated the study of renal transport mechanisms and remodelling of the kidney.

RECENT FINDINGS: Tissue clearing methods have evolved from primarily labelling proteins in thin tissue or individual organs to visualizing both RNA and protein simultaneously in whole animals or human organs. The use of small antibody fragments and innovative imaging techniques improved immunolabelling and resolution. These advances opened up new avenues for studying organ crosstalk and diseases that affect multiple parts of the organism. Accumulating evidence suggests that tubule remodelling can occur rapidly in response to homeostatic stress or injury, allowing for adjustments in the quantitative expression of renal transporters. Tissue clearing helped to better understand the development of tubule cystogenesis, renal hypertension and salt wasting syndromes, and revealed potential progenitor cells in the kidney.

SUMMARY: The continued evolution and improvement of tissue clearing methods can help to gain deep biological insights into the structure and function of the kidney, which will have clinical implications.

PMID:37382119 | DOI:10.1097/MNH.0000000000000904

Zhongguo Zhong Yao Za Zhi. 2023 Jun;48(11):2868-2875. doi: 10.19540/j.cnki.cjcmm.20230227.601.

ABSTRACT

With the advances in medicine, people have deeply understood the complex pathogenesis of diseases. Revealing the mechanism of action and therapeutic effect of drugs from an overall perspective has become the top priority of drug design. However, the traditional drug design methods cannot meet the current needs. In recent years, with the rapid development of systems biology, a variety of new technologies including metabolomics, genomics, and proteomics have been used in drug research and development. As a bridge between traditional pharmaceutical theory and modern science, computer-aided drug design(CADD) can shorten the drug development cycle and improve the success rate of drug design. The application of systems biology and CADD provides a methodological basis and direction for revealing the mechanism and action of drugs from an overall perspective. This paper introduces the research and application of systems biology in CADD from different perspectives and proposes the development direction, providing reference for promoting the application.

PMID:37381949 | DOI:10.19540/j.cnki.cjcmm.20230227.601

Cell. 2023 Jun 21:S0092-8674(23)00598-6. doi: 10.1016/j.cell.2023.05.047. Online ahead of print.

ABSTRACT

N7-methylguanosine (m7G) modification, routinely occurring at mRNA 5' cap or within tRNAs/rRNAs, also exists internally in messenger RNAs (mRNAs). Although m7G-cap is essential for pre-mRNA processing and protein synthesis, the exact role of mRNA internal m7G modification remains elusive. Here, we report that mRNA internal m7G is selectively recognized by Quaking proteins (QKIs). By transcriptome-wide profiling/mapping of internal m7G methylome and QKI-binding sites, we identified more than 1,000 high-confidence m7G-modified and QKI-bound mRNA targets with a conserved "GANGAN (N = A/C/U/G)" motif. Strikingly, QKI7 interacts (via C terminus) with the stress granule (SG) core protein G3BP1 and shuttles internal m7G-modified transcripts into SGs to regulate mRNA stability and translation under stress conditions. Specifically, QKI7 attenuates the translation efficiency of essential genes in Hippo signaling pathways to sensitize cancer cells to chemotherapy. Collectively, we characterized QKIs as mRNA internal m7G-binding proteins that modulate target mRNA metabolism and cellular drug resistance.

PMID:37379838 | DOI:10.1016/j.cell.2023.05.047

Adv Med Sci. 2023 Jun 26;68(2):227-237. doi: 10.1016/j.advms.2023.06.001. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to evaluate the role of Translationally Controlled Tumor Protein (TCTP) in breast cancer (BC) and investigate the effects of sertraline, a serotonin selective reuptake inhibitor (SSRI), on BC cells. The objective was to assess the potential of sertraline as a therapeutic agent in BC treatment by examining its ability to inhibit TCTP expression and exert antitumor effects.

MATERIAL AND METHODS: We utilized five different BC cell lines representing the molecular heterogeneity and distinct subtypes of BC, including luminal, normal-like, HER2-positive, and triple-negative BC. These subtypes play a crucial role in determining clinical treatment strategies and prognosis.

RESULTS: The highest levels of TCTP were observed in triple-negative BC cell lines, known for their aggressive behavior. Sertraline treatment reduced TCTP expression in BC cell lines, significantly impacting cell viability, clonogenicity, and migration. Additionally, sertraline sensitized triple-negative BC cell lines to cytotoxic chemotherapeutic drugs (doxorubicin and cisplatin) suggesting its potential as an adjunctive therapy to enhance the chemotherapeutic response. Bioinformatic analysis of TCTP mRNA levels in TCGA BC data revealed a negative correlation between TCTP levels and patient survival, as well as between TCTP/tpt1 and Ki67. These findings contradict our data and previous studies indicating a correlation between TCTP protein levels and aggressiveness and poor prognosis in BC.

CONCLUSIONS: Sertraline shows a promise as a potential therapeutic option for BC, particularly in triple-negative BC. Its ability to inhibit TCTP expression, enhance chemotherapeutic response, highlights its potential clinical utility in BC treatment, specifically in triple-negative BC subtype.

PMID:37379765 | DOI:10.1016/j.advms.2023.06.001

Mol Autism. 2023 Jun 28;14(1):22. doi: 10.1186/s13229-023-00554-5.

ABSTRACT

BACKGROUND: Autism spectrum disorder (ASD) is a set of highly heterogeneous neurodevelopmental diseases whose genetic etiology is not completely understood. Several investigations have relied on transcriptome analysis from peripheral tissues to dissect ASD into homogenous molecular phenotypes. Recently, analysis of changes in gene expression from postmortem brain tissues has identified sets of genes that are involved in pathways previously associated with ASD etiology. In addition to protein-coding transcripts, the human transcriptome is composed by a large set of non-coding RNAs and transposable elements (TEs). Advancements in sequencing technologies have proven that TEs can be transcribed in a regulated fashion, and their dysregulation might have a role in brain diseases.

METHODS: We exploited published datasets comprising RNA-seq data from (1) postmortem brain of ASD subjects, (2) in vitro cell cultures where ten different ASD-relevant genes were knocked out and (3) blood of discordant siblings. We measured the expression levels of evolutionarily young full-length transposable L1 elements and characterized the genomic location of deregulated L1s assessing their potential impact on the transcription of ASD-relevant genes. We analyzed every sample independently, avoiding to pool together the disease subjects to unmask the heterogeneity of the molecular phenotypes.

RESULTS: We detected a strong upregulation of intronic full-length L1s in a subset of postmortem brain samples and in in vitro differentiated neurons from iPSC knocked out for ATRX. L1 upregulation correlated with an high number of deregulated genes and retained introns. In the anterior cingulate cortex of one subject, a small number of significantly upregulated L1s overlapped with ASD-relevant genes that were significantly downregulated, suggesting the possible existence of a negative effect of L1 transcription on host transcripts.

LIMITATIONS: Our analyses must be considered exploratory and will need to be validated in bigger cohorts. The main limitation is given by the small sample size and by the lack of replicates for postmortem brain samples. Measuring the transcription of locus-specific TEs is complicated by the repetitive nature of their sequence, which reduces the accuracy in mapping sequencing reads to the correct genomic locus.

CONCLUSIONS: L1 upregulation in ASD appears to be limited to a subset of subjects that are also characterized by a general deregulation of the expression of canonical genes and an increase in intron retention. In some samples from the anterior cingulate cortex, L1s upregulation seems to directly impair the expression of some ASD-relevant genes by a still unknown mechanism. L1s upregulation may therefore identify a group of ASD subjects with common molecular features and helps stratifying individuals for novel strategies of therapeutic intervention.

PMID:37381037 | DOI:10.1186/s13229-023-00554-5

Nature. 2023 Jun 28. doi: 10.1038/s41586-023-06252-9. Online ahead of print.

ABSTRACT

The adult human breast is comprised of an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue1-3. Although most previous studies have focused on the breast epithelial system4-6, many of the non-epithelial cell types remain understudied. Here we constructed the comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics study profiled 714,331 cells from 126 women, and 117,346 nuclei from 20 women, identifying 12 major cell types and 58 biological cell states. These data reveal abundant perivascular, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Spatial mapping using four different technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide a reference of the adult normal breast tissue for studying mammary biology and diseases such as breast cancer.

PMID:37380767 | DOI:10.1038/s41586-023-06252-9

Nature. 2023 Jun 28. doi: 10.1038/s41586-023-06249-4. Online ahead of print.

ABSTRACT

Caloric restriction that promotes weight loss is an effective strategy for treating non-alcoholic fatty liver disease and improving insulin sensitivity in people with type 2 diabetes1. Despite its effectiveness, in most individuals, weight loss is usually not maintained partly due to physiological adaptations that suppress energy expenditure, a process known as adaptive thermogenesis, the mechanistic underpinnings of which are unclear2,3. Treatment of rodents fed a high-fat diet with recombinant growth differentiating factor 15 (GDF15) reduces obesity and improves glycaemic control through glial-cell-derived neurotrophic factor family receptor α-like (GFRAL)-dependent suppression of food intake4-7. Here we find that, in addition to suppressing appetite, GDF15 counteracts compensatory reductions in energy expenditure, eliciting greater weight loss and reductions in non-alcoholic fatty liver disease (NAFLD) compared to caloric restriction alone. This effect of GDF15 to maintain energy expenditure during calorie restriction requires a GFRAL-β-adrenergic-dependent signalling axis that increases fatty acid oxidation and calcium futile cycling in the skeletal muscle of mice. These data indicate that therapeutic targeting of the GDF15-GFRAL pathway may be useful for maintaining energy expenditure in skeletal muscle during caloric restriction.

PMID:37380764 | DOI:10.1038/s41586-023-06249-4

Nat Biomed Eng. 2023 Jun;7(6):719-742. doi: 10.1038/s41551-023-01056-8. Epub 2023 Jun 28.

ABSTRACT

In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how patients are diagnosed, treated and billed. In this Perspective, we outline fairness in machine learning through the lens of healthcare, and discuss how algorithmic biases (in data acquisition, genetic variation and intra-observer labelling variability, in particular) arise in clinical workflows and the resulting healthcare disparities. We also review emerging technology for mitigating biases via disentanglement, federated learning and model explainability, and their role in the development of AI-based software as a medical device.

PMID:37380750 | DOI:10.1038/s41551-023-01056-8

Sci Data. 2023 Jun 28;10(1):420. doi: 10.1038/s41597-023-02320-x.

NO ABSTRACT

PMID:37380661 | DOI:10.1038/s41597-023-02320-x

Eur Urol. 2023 Jun 27:S0302-2838(23)02830-0. doi: 10.1016/j.eururo.2023.05.023. Online ahead of print.

ABSTRACT

Small cell/neuroendocrine bladder cancers (SCBCs) are rare and highly aggressive tumors that are associated with poor clinical outcomes. We discovered that lineage-specific transcription factors (ASCL1, NEUROD1, and POU2F3) defined three SCBC molecular subtypes that resemble well-characterized subtypes in small cell lung cancer. The subtypes expressed various levels of neuroendocrine (NE) markers and distinct downstream transcriptional targets. Specifically, the ASCL1 and NEUROD1 subtypes had high NE marker expression and were enriched with different downstream regulators of the NE phenotype (FOXA2 and HES6, respectively). ASCL1 was also associated with the expression of delta-like ligands that control oncogenic Notch signaling. POU2F3, a master regulator of the NE low subtype, targeted TRPM5, SOX9, and CHAT. We also observed an inverse association between NE marker expression and immune signatures associated with sensitivity to immune checkpoint blockade, and the ASCL1 subtype had distinct targets for clinically available antibody-drug conjugates. These findings provide new insight into molecular heterogeneity in SCBCs with implications for the development of new treatment regimens. PATIENT SUMMARY: We investigated the levels of different proteins in a specific type of bladder cancer (small cell/neuroendocrine; SCBC). We could identify three distinct subtypes of SCBC with similarity to small cell/neuroendocrine cancers in other tissues. The results may help in identifying new treatment approaches for this type of bladder cancer.

PMID:37380560 | DOI:10.1016/j.eururo.2023.05.023

STAR Protoc. 2023 Jun 27;4(3):102387. doi: 10.1016/j.xpro.2023.102387. Online ahead of print.

ABSTRACT

Here, we present a computational approach for investigating highly variable genes (HVGs) associated with biological pathways of interest, across multiple time points and cell types in single-cell RNA-sequencing (scRNA-seq) data. Using public dengue virus and COVID-19 datasets, we describe steps for using the framework to characterize the dynamic expression levels of HVGs related to common and cell-type-specific biological pathways over multiple immune cell types. For complete details on the use and execution of this protocol, please refer to Arora et al.1.

PMID:37379219 | DOI:10.1016/j.xpro.2023.102387

Biochem J. 2023 Jun 28;480(12):891-908. doi: 10.1042/BCJ20210534.

ABSTRACT

Metabolomics is a powerful research discovery tool with the potential to measure hundreds to low thousands of metabolites. In this review, we discuss the application of GC-MS and LC-MS in discovery-based metabolomics research, we define metabolomics workflows and we highlight considerations that need to be addressed in order to generate robust and reproducible data. We stress that metabolomics is now routinely applied across the biological sciences to study microbiomes from relatively simple microbial systems to their complex interactions within consortia in the host and the environment and highlight this in a range of biological species and mammalian systems including humans. However, challenges do still exist that need to be overcome to maximise the potential for metabolomics to help us understanding biological systems. To demonstrate the potential of the approach we discuss the application of metabolomics in two broad research areas: (1) synthetic biology to increase the production of high-value fine chemicals and reduction in secondary by-products and (2) gut microbial interaction with the human host. While burgeoning in importance, the latter is still in its infancy and will benefit from the development of tools to detangle host-gut-microbial interactions and their impact on human health and diseases.

PMID:37378961 | DOI:10.1042/BCJ20210534

Asian Pac J Cancer Prev. 2023 Jun 1;24(6):1993-2001. doi: 10.31557/APJCP.2023.24.6.1993.

ABSTRACT

OBJECTIVE: This study aimed to find the key genes and miRNAs as potential biomarkers related to the progression of colorectal cancer (CRC) from Crohn's disease (CD).

BACKGROUND: CD is widely accepted as one of the main risk factors leading to CRC. So, Identifying the novel molecular pathways involved in the development of CRC from CD can provide potential solutions for therapeutic interventions.

METHODS: By implementing a systematic approach, we have analyzed mRNA and miRNA datasets containing CRC and CD samples to determine differentially expressed genes (DEGs) and miRNAs (DEmiRNA). Then by selecting common genes involved in the progression from CD to CRC, different downstream analyses including mRNA-miRNA network, functional enrichment analysis, gene set enrichment analysis, and survival analysis were performed. Finally, quantitative real-time PCR (RT-PCR) analysis of tissue samples obtained from Normal/CRC samples was used to confirm the differential expression of selected genes and miRNA.

RESULTS: There were 10 DE miRNA and 181 genes DEGs common between progression from CD to CRC. The genes obtained for each of the 10 miRNAs were considered as the final target for downstream analyzes. In addition, analysis of RT-PCR indicated that miR-195-5p, PHLPP2, and LITAF were downregulated in the cancer group compared to the control group.

CONCLUSION: This study showed that PHLPP2, LITAF, and miR-195-5p may have key roles in the tumorigenesis of CRC and they can be used as therapeutic targets and diagnostic biomarkers after further in-vitro and in-vivo evaluation.

PMID:37378929 | DOI:10.31557/APJCP.2023.24.6.1993

Adv Exp Med Biol. 2023;1412:311-335. doi: 10.1007/978-3-031-28012-2_17.

ABSTRACT

Currently, methods in machine learning have opened a significant number of applications to construct classifiers with capacities to recognize, identify, and interpret patterns hidden in massive amounts of data. This technology has been used to solve a variety of social and health issues against coronavirus disease 2019 (COVID-19). In this chapter, we present some supervised and unsupervised machine learning techniques that have contributed in three aspects to supplying information to health authorities and diminishing the deadly effects of the current worldwide outbreak on the population. First is the identification and construction of powerful classifiers capable of predicting severe, moderate, or asymptomatic responses in COVID-19 patients starting from clinical or high-throughput technologies. Second is the identification of groups of patients with similar physiological responses to improve the triage classification and inform treatments. The final aspect is the combination of machine learning methods and schemes from systems biology to link associative studies with mechanistic frameworks. This chapter aims to discuss some practical applications in the use of machine learning techniques to handle data coming from social behavior and high-throughput technologies, associated with COVID-19 evolution.

PMID:37378775 | DOI:10.1007/978-3-031-28012-2_17

Plant Cell. 2023 Jun 28:koad188. doi: 10.1093/plcell/koad188. Online ahead of print.

ABSTRACT

Protein activities depend heavily on protein complex formation and dynamic post-translational modifications, such as phosphorylation. The dynamic nature of protein complex formation and post-translational modifications is notoriously difficult to monitor in planta at cellular resolution, often requiring extensive optimization. Here, we generated and exploited the SYnthetic Multivalency in PLants (SYMPL)-vector set to assay protein-protein interactions (PPIs) (SPPIER - Separation of Phases-based Protein Interaction Reporter) and kinase activities (SPARK - Separation of Phases-based Activity Reporter of Kinase) in planta, based on phase separation. This technology enabled easy detection of inducible, binary and ternary protein-protein interactions among cytoplasmic and nuclear proteins in plant cells via a robust image-based readout. Moreover, we applied the SYMPL toolbox to develop an in vivo reporter for SNF1-related kinase 1 (SnRK1) activity, allowing us to visualize tissue-specific, dynamic SnRK1 activity in stable transgenic Arabidopsis (Arabidopsis thaliana) plants. The SYMPL cloning toolbox provides a means to explore PPIs, phosphorylation, and other post-translational modifications with unprecedented ease and sensitivity.

PMID:37378595 | DOI:10.1093/plcell/koad188