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Cancer-associated fibroblasts (CAFs) in the tumor microenvironment contribute to all stages of tumorigenesis and are usually considered to be tumor-promoting cells. CAFs show a remarkable degree of heterogeneity, which is attributed to developmental origin or to local environmental niches, resulting in distinct CAF subsets within individual tumors. While CAF heterogeneity is frequently investigated in late-stage tumors, data on longitudinal CAF development in tumors are lacking. To this end, we used the transgenic polyoma middle T oncogene-induced mouse mammary carcinoma model and performed whole transcriptome analysis in FACS-sorted fibroblasts from early- and late-stage tumors. We observed a shift in fibroblast populations over time towards a subset previously shown to negatively correlate with patient survival, which was confirmed by multispectral immunofluorescence analysis. Moreover, we identified a transcriptomic signature distinguishing CAFs from early- and late-stage tumors. Importantly, the signature of early-stage CAFs correlated well with tumor stage and survival in human mammary carcinoma patients. A random forest analysis suggested predictive value of the complete set of differentially expressed genes between early- and late-stage CAFs on bulk tumor patient samples, supporting the clinical relevance of our findings. In conclusion, our data show transcriptome alterations in CAFs during tumorigenesis in the mammary gland, which suggest that CAFs are educated by the tumor over time to promote tumor development. Moreover, we show that murine CAF gene signatures can harbor predictive value for human cancer.
Targeting self-renewal and tumorigenicity has been proposed as a potential strategy against cancer stem cells (CSCs). Epigenetic proteins are key modulators of gene expression and cancer development contributing to regulation and maintenance of self-renewal and tumorigenicity. Here, we have screened a small-molecule epigenetic inhibitor library using 3D in vitro models in order to determine potential epigenetic targets associated with self-renewal and tumorigenicity in Canine Mammary Cancer (CMC) cells. We identified inhibition of BET proteins as a promising strategy to inhibit CMC colonies and tumorspheres formation. Low doses of (+)-JQ1 were able to downregulate important genes associated to self-renewal pathways such as WNT, NOTCH, Hedgehog, PI3K/AKT/mTOR, EGF receptor and FGF receptor in CMC tumorspheres. In addition, we observed downregulation of ZEB2, a transcription factor important for the maintenance of self-renewal in canine mammary cancer cells. Furthermore, low doses of (+)-JQ1 were not cytotoxic in CMC cells cultured in 2D in vitro models but induced G2/M cell cycle arrest accompanied by upregulation of G2/M checkpoint-associated genes including BTG2 and CCNG2. Our work indicates the BET inhibition as a new strategy for canine mammary cancers by modulating the self-renewal phenotype in tumorigenic cells such as CSCs.
The combination of high-throughput sequencing and in vivo crosslinking approaches leads to the progressive uncovering of the complex interdependence between cellular transcriptome and proteome. Yet, the molecular determinants governing interactions in protein-RNA networks are not well understood. Here we investigated the relationship between the structure of an RNA and its ability to interact with proteins. Analysing in silico, in vitro and in vivo experiments, we find that the amount of double-stranded regions in an RNA correlates with the number of protein contacts. This relationship —which we call structure-driven protein interactivity— allows classification of RNA types, plays a role in gene regulation and could have implications for the formation of phase-separated ribonucleoprotein assemblies. We validate our hypothesis by showing that a highly structured RNA can rearrange the composition of a protein aggregate. We report that the tendency of proteins to phase-separate is reduced by interactions with specific RNAs.
Formation of the anteroposterior and dorsoventral body axis in Caenorhabditis elegans depends on cortical flows and advection of polarity determinants. The role of this patterning mechanism in tissue polarization after formation of cell-cell contacts is not fully understood. Here, we demonstrate that planar asymmetries are established during left-right symmetry breaking: Centripetal cortical flows asymmetrically and differentially advect anterior polarity determinants (aPARs) from contacts to the medial cortex, resulting in their unmixing from apical myosin. Contact localization and advection of PAR-6 requires balanced CDC-42 activation, while asymmetric retention and advection of PAR-3 can occur independently of PAR-6. Concurrent asymmetric retention of PAR-3, E-cadherin/HMR-1 and opposing retention of antagonistic CDC-42 and Wnt pathway components leads to planar asymmetries. The most obvious mark of planar asymmetry, retention of PAR-3 at a single cell-cell contact, is required for proper cytokinetic cell intercalation. Hence, our data uncover how planar polarity is established in a system without the canonical planar cell polarity pathway through planar asymmetric retention of aPARs.
In all eukaryotic cells, the nucleolus is functionally and structurally linked to rRNA synthesis and ribosome biogenesis. This compartment contains as well factors involved in other cellular activities, but the functional interconnection between non-ribosomal activities and the nucleolus (structure and function) still remains an open question. Here, we report a novel mass spectrometry analysis of isolated nucleoli from Arabidopsis thaliana plants using the FANoS (Fluorescence Assisted Nucleolus Sorting) strategy. We identified many ribosome biogenesis factors (RBF) and proteins non-related with ribosome biogenesis, in agreement with the recognized multi-functionality of the nucleolus. Interestingly, we found that 26S proteasome subunits localize in the nucleolus and demonstrated that proteasome activity and nucleolus organization are intimately linked to each other. Proteasome subunits form discrete foci in the disorganized nucleolus of nuc1.2 plants. Nuc1.2 protein extracts display reduced proteasome activity in vitro compared to WT protein extracts. Remarkably, proteasome activity in nuc1.2 is similar to proteasome activity in WT plants treated with proteasome inhibitors (MG132 or ALLN). Finally, we show that MG132 treatment induces disruption of nucleolar structures in WT but not in nuc1.2 plants. Altogether, our data suggest a functional interconnection between nucleolus structure and proteasome activity.
The identification of heat stress (HS)-resilient germplasm is important to ensure food security under less favorable environmental conditions. For that, germplasm with an altered activity of factors regulating the HS response is an important genetic tool for crop improvement. Heat shock binding protein (HSBP) is one of the main negative regulators of HS response, acting as a repressor of the activity of HS transcription factors. We identified a TILLING allele of Solanum lycopersicum (tomato) HSBP1. We examined the effects of the mutation on the functionality of the protein in tomato protoplasts, and compared the thermotolerance capacity of lines carrying the wild-type and mutant alleles of HSBP1. The methionine-to-isoleucine mutation in the central heptad repeats of HSBP1 leads to a partial loss of protein function, thereby reducing the inhibitory effect on Hsf activity. Mutant seedlings show enhanced basal thermotolerance, while mature plants exhibit increased resilience in repeated HS treatments, as shown by several physiological parameters. Importantly, plants that are homozygous for the wild-type or mutant HSBP1 alleles showed no significant differences under non-stressed conditions. Altogether, these results indicate that the identified mutant HSBP1 allele can be used as a genetic tool in breeding, aiming to improve the thermotolerance of tomato varieties.
uORF-tools—workflow for the determination of translation-regulatory upstream open reading frames
(2019)
Ribosome profiling (ribo-seq) provides a means to analyze active translation by determining ribosome occupancy in a transcriptome-wide manner. The vast majority of ribosome protected fragments (RPFs) resides within the protein-coding sequence of mRNAs. However, commonly reads are also found within the transcript leader sequence (TLS) (aka 5’ untranslated region) preceding the main open reading frame (ORF), indicating the translation of regulatory upstream ORFs (uORFs). Here, we present a workflow for the identification of translation-regulatory uORFs. Specifically, uORF-Tools uses Ribo-TISH to identify uORFs within a given dataset and generates a uORF annotation file. In addition, a comprehensive human uORF annotation file, based on 35 ribo-seq files, is provided, which can serve as an alternative input file for the workflow. To assess the translation-regulatory activity of the uORFs, stimulus-induced changes in the ratio of the RPFs residing in the main ORFs relative to those found in the associated uORFs are determined. The resulting output file allows for the easy identification of candidate uORFs, which have translation-inhibitory effects on their associated main ORFs. uORF-Tools is available as a free and open Snakemake workflow at https://github.com/Biochemistry1-FFM/uORF-Tools. It is easily installed and all necessary tools are provided in a version-controlled manner, which also ensures lasting usability. uORF-Tools is designed for intuitive use and requires only limited computing times and resources.
Rpn13 is an intrinsic ubiquitin receptor of the 26S proteasome regulatory subunit that facilitates substrate capture prior to degradation. Here we show that the C-terminal region of Rpn13 binds to the tetratricopeptide repeat (TPR) domain of SGTA, a cytosolic factor implicated in the quality control of mislocalised membrane proteins (MLPs). The overexpression of SGTA results in a substantial increase in steady-state MLP levels, consistent with an effect on proteasomal degradation. However, this effect is strongly dependent upon the interaction of SGTA with the proteasomal component Rpn13. Hence, overexpression of the SGTA-binding region of Rpn13 or point mutations within the SGTA TPR domain both inhibit SGTA binding to the proteasome and substantially reduce MLP levels. These findings suggest that SGTA can regulate the access of MLPs to the proteolytic core of the proteasome, implying that a protein quality control cycle that involves SGTA and the BAG6 complex can operate at the 19S regulatory particle. We speculate that the binding of SGTA to Rpn13 enables specific polypeptides to escape proteasomal degradation and/or selectively modulates substrate degradation.
Live-cell labelling techniques to visualize proteins with minimal disturbance are important; however, the currently available methods are limited in their labelling efficiency, specificity and cell permeability. We describe high-throughput protein labelling facilitated by minimalistic probes delivered to mammalian cells by microfluidic cell squeezing. High-affinity and target-specific tracing of proteins in various subcellular compartments is demonstrated, culminating in photoinduced labelling within live cells. Both the fine-tuned delivery of subnanomolar concentrations and the minimal size of the probe allow for live-cell super-resolution imaging with very low background and nanometre precision. This method is fast in probe delivery (∼1,000,000 cells per second), versatile across cell types and can be readily transferred to a multitude of proteins. Moreover, the technique succeeds in combination with well-established methods to gain multiplexed labelling and has demonstrated potential to precisely trace target proteins, in live mammalian cells, by super-resolution microscopy.
Background: Microarray analysis represents a powerful way to test scientific hypotheses on the functionality of cells. The measurements consider the whole genome, and the large number of generated data requires sophisticated analysis. To date, no gold-standard for the analysis of microarray images has been established. Due to the lack of a standard approach there is a strong need to identify new processing algorithms.
Methods: We propose a novel approach based on hyperbolic partial differential equations (PDEs) for unsupervised spot segmentation. Prior to segmentation, morphological operations were applied for the identification of co-localized groups of spots. A grid alignment was performed to determine the borderlines between rows and columns of spots. PDEs were applied to detect the inflection points within each column and row; vertical and horizontal luminance profiles were evolved respectively. The inflection points of the profiles determined borderlines that confined a spot within adapted rectangular areas. A subsequent k-means clustering determined the pixels of each individual spot and its local background.
Results: We evaluated the approach for a data set of microarray images taken from the Stanford Microarray Database (SMD). The data set is based on two studies on global gene expression profiles of Arabidopsis Thaliana. We computed values for spot intensity, regression ratio, and coefficient of determination. For spots with irregular contours and inner holes, we found intensity values that were significantly different from those determined by the GenePix Pro microarray analysis software. We determined the set of differentially expressed genes from our intensities and identified more activated genes than were predicted by the GenePix software.
Conclusions: Our method represents a worthwhile alternative and complement to standard approaches used in industry and academy. We highlight the importance of our spot segmentation approach, which identified supplementary important genes, to better explains the molecular mechanisms that are activated in a defense responses to virus and pathogen infection.