A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells

Reversing the dysfunctional T cell state that arises in cancer and chronic viral infections is the focus of therapeutic interventions; however, current therapies are effective in only some patients and some tumor types. To gain a deeper molecular understanding of the dysfunctional T cell state, we analyzed population and single-cell RNA profiles of CD8+tumor-infiltrating lymphocytes (TILs) and used genetic perturbations to identify a distinct gene module for T cell dysfunction that can be uncoupled from T cell activation. This distinct dysfunction module is downstream of intracellular metallothioneins that regulate zinc metabolism and can be identified at single-cell resolution. We further identify Gata-3, a zinc-finger transcription factor in the dysfunctional module, as a regulator of dysfunction, and we use CRISPR-Cas9 genome editing to show that it drives a dysfunctional phenotype in CD8+TILs. Our results open novel avenues for targeting dysfunctional T cell states while leaving activation programs intact

A Feature-Based Approach to Modeling Protein–DNA Interactions

Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM), which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs), a novel probabilistic method for modeling TF–DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP) dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/

Proteasome Lid Bridges Mitochondrial Stress with Cdc53/Cullin1 NEDDylation Status

Cycles of Cdc53/Cullin1 rubylation (a.k.a NEDDylation) protect ubiquitin-E3 SCF (Skp1-Cullin1-F-box protein) complexes from self-destruction and play an important role in mediating the ubiquitination of key protein substrates involved in cell cycle progression, development, and survival. Cul1 rubylation is balanced by the COP9 signalosome (CSN), a multi-subunit derubylase that shows 1:1 paralogy to the 26 S proteasome lid. The turnover of SCF substrates and their relevance to various diseases is well studied, yet, the extent by which environmental perturbations influence Cul1 rubylation/derubylation cycles per se is still unclear. In this study, we show that the level of cellular oxidation serves as a molecular switch, determining Cullin1 rubylation/derubylation ratio. We describe a mutant of the proteasome lid subunit, Rpn11 that exhibits accumulated levels of Cullin1-Rub1 conjugates, a characteristic phenotype of csn mutants. By dissecting between distinct phenotypes of rpn11 mutants, proteasome and mitochondria dysfunction, we were able to recognize the high reactive oxygen species (ROS) production during the transition of cells into mitochondrial respiration, as a checkpoint of Cullin1 rubylation in a reversible manner. Thus, the study adds the rubylation cascade to the list of cellular pathways regulated by redox homeostasis

Identification of potential biomarkers to differentially diagnose solid pseudopapillary tumors and pancreatic malignancies via a gene regulatory network

Additional file 1: In-degree distribution for GRN. X-axis represents the in-degree for a certain node. A node of in-degree x means that this node is regulated by a total number of x other nodes. Y-axis represents the total number of network nodes which has an in-degree of x. The red curve was the fitting to the power law distribution. (A): The in-degree distribution for sub-GRN in which only miRNAs are included as regulators and the in-degree for each node (miRNAs and protein coding genes) was calculated in this sub-GRN. The in-degree ranges from 0 to 27. (B): In-degree distribution for sub-GRN in which only TFs are included as regulators

Investigating the complexities of microrna-target interactions in cardiac biology

One in three Australians die of cardiovascular disease and despite advances in treatment it remains the leading cause of death in Australia. MiRNAs play critical roles in the heart and specific miRNAs can promote or prevent cardiac hypertrophy, sparking interest to use miRNAs as therapeutic targets. However, cells can produce both miRNAs and their mRNA targets in multiple processing variants increasing the complexity of miRNA-mediated control. It is therefore critical to elucidate the role of these variants in cardiac disease. The aim of this thesis was to profile miRNA and mRNA 3' UTRs in cardiac hypertrophy and to interrogate this data for evidence of processing variation. We established a murine model of left ventricular hypertrophy using transverse aortic constriction as confirmed using haemodynamic, physiological and biochemical measurements. Cardiomyocyctes were isolated from pre-hypertrophic, hypertrophic and control hearts and RNA extracted for next-generation sequencing of miRNAs and mRNA 3' ends. We identified 17 miRNAs and 776 mRNAs that changed in level during the hypertrophy, with the majority being upregulated. Overall, more mRNAs changed expression in the pre-hypertrophic cardiomyocytes, while the miRNAs were altered mostly in the hypertrophic samples. This is the first study to document the expression of miRNAs and mRNAs simultaneously in purified cardiomyocytes and their change in hypertrophy. Analysing the datasets for processing diversity revealed that nearly all miRNAs in cardiomyocytes showed some degree of processing diversity including expression from both hairpin arms, 5' and 3' isomiRs, or the presence of non-templated additions. There was little directional change in miRNA processing during hypertrophy but two examples were identified where the bias for particular variants changed significantly. This is the first documentation of variable miRNA processing in purified cardiomyocytes. Such variants provide a mechanism to change the mRNA targeting properties of miRNAs from a given locus without changing the genomic sequence. In support of this, in vitro luciferase assays demonstrated that the different 5' isomiRs of the cardiac miR-133a-3p have distinct targeting preferences. Analysis of the 3' end sequencing data demonstrated that mRNAs expressed in cardiomyocytes had on average 2.35 distinct 3' UTRs with an average length of 3.7 kb. The proportion of short versus long 3' UTRs was altered for 424 mRNAs, with 272 3' UTRs getting shorter and 152 getting longer, in the pre-hypertrophic cardiomyocytes. This is the first study to provide an in-depth mapping of mRNA 3' UTR diversity in purified cardiomyocytes and document changes to the proportion of these variants in cardiac hypertrophy. Alterations in the length of 3' UTRs can lead to inclusion of or exclusion of miRNA target sites on mRNAs and thus change their sensitivity to regulation by miRNAs. Overall, the datasets reported here provide global information on expression changes to both miRNA sequence and mRNA 3' UTR lengths forming the basis for an improved systems level understanding of miRNA-regulation during cardiac hypertrophy. The realisation that cardiac miRNAs and their targets exist as currently under-appreciated variants with potentially complex effects on target specificities has important implications for the role of miRNAs in cardiac disease

Methods for high-dimensonal analysis of cells dissociated from cyropreserved synovial tissue

BACKGROUND: Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples. METHODS: Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq. RESULTS: Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 mug/ml of Liberase TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4(+) and CD8(+) T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified. CONCLUSIONS: We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers

Methods for high-dimensonal analysis of cells dissociated from cyropreserved synovial tissue

© 2018 The Author(s). Background: Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples. Methods: Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq. Results: Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4+ and CD8+ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified. Conclusions: We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers