Extraction of high-quality RNA from mouse pancreatic tumors

Microbial iCLIP2: enhanced mapping of RNA-protein interaction by promoting protein and RNA stability

The entire RNA life cycle, spanning from transcription to decay, is intricately regulated by RNA-binding proteins (RBPs). To understand their precise functions, it is crucial to identify direct targets, pinpoint their exact binding sites, and unravel the underlying specificity in vivo. Individual-nucleotide resolution UV cross-linking and immunoprecipitation 2 (iCLIP2) is a state-of-the-art technique that enables the identification of RBP-binding sites at single-nucleotide resolution. However, in the field of microbiology, optimized iCLIP protocols compared to mammalian systems are lacking. Here, we present the first microbial iCLIP2 approach using the multi-RRM domain protein Rrm4 from the fungus Ustilago maydis as an example. Key challenges, such as inherently high RNase and protease activity in fungi, were addressed by improving mechanical cell disruption and lysis buffer composition. Our modifications increased the yield of cross-link events and improved the identification of Rrm4-binding sites. Thereby, we were able to pinpoint that Rrm4 binds the stop codons of nuclear-encoded mRNAs of mitochondrial respiratory complexes I, III, and V-revealing an intimate link between endosomal mRNA transport and mitochondrial physiology. Thus, our study using U. maydis as an example might serve as a blueprint for optimizing iCLIP2 procedures in other microorganisms with high RNase/protease conditions.

Proteomic Analysis of Rap1A GTPase Signaling-Deficient C57BL/6 Mouse Pancreas and Functional Studies Identify an Essential Role of Rap1A in Pancreas Physiology

Ras-related Rap1A GTPase is implicated in pancreas β-cell insulin secretion and is stimulated by the cAMP sensor Epac2, a guanine exchange factor and activator of Rap1 GTPase. In this study, we examined the differential proteomic profiles of pancreata from C57BL/6 Rap1A-deficient (Null) and control wild-type (WT) mice with nanoLC-ESI-MS/MS to assess targets of Rap1A potentially involved in insulin regulation. We identified 77 overlapping identifier proteins in both groups, with 8 distinct identifier proteins in Null versus 56 distinct identifier proteins in WT mice pancreata. Functional enrichment analysis showed four of the eight Null unique proteins, ERO1-like protein β (Ero1lβ), triosephosphate isomerase (TP1), 14-3-3 protein γ, and kallikrein-1, were exclusively involved in insulin biogenesis, with roles in insulin metabolism. Specifically, the mRNA expression of Ero1lβ and TP1 was significantly (p < 0.05) increased in Null versus WT pancreata. Rap1A deficiency significantly affected glucose tolerance during the first 15-30 min of glucose challenge but showed no impact on insulin sensitivity. Ex vivo glucose-stimulated insulin secretion (GSIS) studies on isolated Null islets showed significantly impaired GSIS. Furthermore, in GSIS-impaired islets, the cAMP-Epac2-Rap1A pathway was significantly compromised compared to the WT. Altogether, these studies underscore an essential role of Rap1A GTPase in pancreas physiological function.

Androgen deprivation triggers a cytokine signaling switch to induce immune suppression and prostate cancer recurrence

Androgen deprivation therapy (ADT) is an effective but not curative treatment for advanced and recurrent prostate cancer (PC). We investigated the mechanisms controlling the response to androgen-deprivation by surgical castration in genetically-engineered mouse models (GEMM) of PC, using high frequency ultrasound imaging to rigorously measure tumor volume. Castration initially causes almost all tumors to shrink in volume, but many tumors subsequently recur within 5-10 weeks. Blockade of tumor necrosis factor (TNF) signaling a few days in advance of castration surgery, using a TNFR2 ligand trap, prevents regression in a PTEN-deficient GEMM. Following tumor regression, a basal stem cell-like population within the tumor increases along with TNF protein levels. Tumor cell lines in culture recapitulate these in vivo observations, suggesting that basal stem cells are the source of TNF. When TNF signaling blockade is administered immediately prior to castration, tumors regress but recurrence is prevented, implying that a late wave of TNF secretion within the tumor, which coincides with the expression of NFkB regulated genes, drives recurrence. The inhibition of signaling downstream of one NFkB-regulated protein, chemokine C-C motif ligand 2 (CCL2), prevents post-castration tumor recurrence, phenocopying post-castration (late) TNF signaling blockade. CCL2 was originally identified as a macrophage chemoattractant and indeed at late times after castration gene sets related to chemotaxis and migration are up-regulated. Importantly, enhanced CCL2 signaling during the tumor recurrence phase coincides with an increase in pro-tumorigenic macrophages and a decrease in CD8 T cells, suggesting that recurrence is driven at least in part by tumor immunosuppression. In summary, we demonstrate that a therapy-induced switch in TNF signaling, a consequence of the increased stem cell-like character of the residual tumor cells surviving ADT, induces an immunosuppressive tumor microenvironment and concomitant tumor recurrence.

Coordinate transcriptional regulation of ErbB2/3 by C-terminal binding protein 2 signals sensitivity to ErbB2 inhibition in pancreatic adenocarcinoma

There is a critical need to identify new therapeutic vulnerabilities in pancreatic ductal adenocarcinoma (PDAC). Transcriptional co-regulators C-terminal binding proteins (CtBP) 1 and 2 are highly overexpressed in human PDAC, and CRISPR-based homozygous deletion of Ctbp2 in a mouse PDAC cell line (CKP) dramatically decreased tumor growth, reduced metastasis, and prolonged survival in orthotopic mouse allografts. Transcriptomic profiling of tumors derived from CKP vs. Ctbp2-deleted CKP cells (CKP/KO) revealed significant downregulation of the EGFR-superfamily receptor Erbb3, the heterodimeric signaling partner for both EGFR and ErbB2. Compared with CKP cells, CKP/KO cells also demonstrated reduced Erbb2 expression and did not activate downstream Akt signaling after stimulation of Erbb3 by its ligand neuregulin-1. ErbB3 expression in human PDAC cell lines was similarly dependent on CtBP2 and depletion of ErbB3 in a human PDAC cell line severely attenuated growth, demonstrating the critical role of ErbB3 signaling in maintaining PDAC cell growth. Sensitivity to the ErbB2-targeted tyrosine kinase inhibitor lapatinib, but not the EGFR-targeted agent erlotinib, varied in proportion to the level of ErbB3 expression in mouse and human PDAC cells, suggesting that an ErBb2 inhibitor can effectively leverage CtBP2-driven transcriptional activation of physiologic ErbB2/3 expression and signaling in PDAC cells for therapeutic benefit.

Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics Analysis

Background: Biological processes are based on complex networks of cells and molecules. Single cell multi-omics is a new tool aiming to provide new incites in the complex network of events controlling the functionality of the cell. Methods: Since single cell technologies provide many sample measurements, they are the ideal environment for the application of Deep Learning and Machine Learning approaches. An autoencoder is composed of an encoder and a decoder sub-model. An autoencoder is a very powerful tool in data compression and noise removal. However, the decoder model remains a black box from which is impossible to depict the contribution of the single input elements. We have recently developed a new class of autoencoders, called Sparsely Connected Autoencoders (SCA), which have the advantage of providing a controlled association among the input layer and the decoder module. This new architecture has the benefit that the decoder model is not a black box anymore and can be used to depict new biologically interesting features from single cell data. Results: Here, we show that SCA hidden layer can grab new information usually hidden in single cell data, like providing clustering on meta-features difficult, i.e. transcription factors expression, or not technically not possible, i.e. miRNA expression, to depict in single cell RNAseq data. Furthermore, SCA representation of cell clusters has the advantage of simulating a conventional bulk RNAseq, which is a data transformation allowing the identification of similarity among independent experiments. Conclusions: In our opinion, SCA represents the bioinformatics version of a universal “Swiss-knife” for the extraction of hidden knowledgeable features from single cell omics data.