Paired single-cell host profiling with multiplex-tagged bacterial mutants reveals intracellular virulence-immune networks.

Encounters between host cells and intracellular bacterial pathogens lead to complex phenotypes that determine the outcome of infection. Single-cell RNA sequencing (scRNA-seq) is increasingly used to study the host factors underlying diverse cellular phenotypes but has limited capacity to analyze the role of bacterial factors. Here, we developed scPAIR-seq, a single-cell approach to analyze infection with a pooled library of multiplex-tagged, barcoded bacterial mutants. Infected host cells and barcodes of intracellular bacterial mutants are both captured by scRNA-seq to functionally analyze mutant-dependent changes in host transcriptomes. We applied scPAIR-seq to macrophages infected with a library of Salmonella Typhimurium secretion system effector mutants. We analyzed redundancy between effectors and mutant-specific unique fingerprints and mapped the global virulence network of each individual effector by its impact on host immune pathways. ScPAIR-seq is a powerful tool to untangle bacterial virulence strategies and their complex interplay with host defense strategies that drive infection outcome.

Down-regulation of LATS kinases alters p53 to promote cell migration.

p53 is a pivotal tumor suppressor and a major barrier against cancer. We now report that silencing of the Hippo pathway tumor suppressors LATS1 and LATS2 in nontransformed mammary epithelial cells reduces p53 phosphorylation and increases its association with the p52 NF-κB subunit. Moreover, it partly shifts p53's conformation and transcriptional output toward a state resembling cancer-associated p53 mutants and endows p53 with the ability to promote cell migration. Notably, LATS1 and LATS2 are frequently down-regulated in breast cancer; we propose that such down-regulation might benefit cancer by converting p53 from a tumor suppressor into a tumor facilitator.

mRNA-seq whole transcriptome profiling of fresh frozen versus archived fixed tissues.

BACKGROUND: The main bottleneck for genomic studies of tumors is the limited availability of fresh frozen (FF) samples collected from patients, coupled with comprehensive long-term clinical follow-up. This shortage could be alleviated by using existing large archives of routinely obtained and stored Formalin-Fixed Paraffin-Embedded (FFPE) tissues. However, since these samples are partially degraded, their RNA sequencing is technically challenging. RESULTS: In an effort to establish a reliable and practical procedure, we compared three protocols for RNA sequencing using pairs of FF and FFPE samples, both taken from the same breast tumor. In contrast to previous studies, we compared the expression profiles obtained from the two matched sample types, using the same protocol for both. Three protocols were tested on low initial amounts of RNA, as little as 100 ng, to represent the possibly limited availability of clinical samples. For two of the three protocols tested, poly(A) selection (mRNA-seq) and ribosomal-depletion, the total gene expression profiles of matched FF and FFPE pairs were highly correlated. For both protocols, differential gene expression between two FFPE samples was in agreement with their matched FF samples. Notably, although expression levels of FFPE samples by mRNA-seq were mainly represented by the 3'-end of the transcript, they yielded very similar results to those obtained by ribosomal-depletion protocol, which produces uniform coverage across the transcript. Further, focusing on clinically relevant genes, we showed that the high correlation between expression levels persists at higher resolutions. CONCLUSIONS: Using the poly(A) protocol for FFPE exhibited, unexpectedly, similar efficiency to the ribosomal-depletion protocol, with the latter requiring much higher (2-3 fold) sequencing depth to compensate for the relative low fraction of reads mapped to the transcriptome. The results indicate that standard poly(A)-based RNA sequencing of archived FFPE samples is a reliable and cost-effective alternative for measuring mRNA-seq on FF samples. Expression profiling of FFPE samples by mRNA-seq can facilitate much needed extensive retrospective clinical genomic studies.

An accessible database for mouse and human whole transcriptome qPCR primers.

MOTIVATION: Real time quantitative polymerase chain reaction (qPCR) is an important tool in quantitative studies of DNA and RNA molecules; especially in transcriptome studies, where different primer combinations allow identification of specific transcripts such as splice variants or precursor messenger RNA. Several softwares that implement various rules for optimal primer design are available. Nevertheless, as designing qPCR primers needs to be done manually, the repeated task is tedious, time consuming and prone to errors. RESULTS: We used a set of rules to automatically design all possible exon-exon and intron-exon junctions in the human and mouse transcriptomes. The resulting database is included as a track in the UCSC genome browser, making it widely accessible and easy to use. AVAILABILITY: The database is available from the UCSC genome browser (http://genome.ucsc.edu/), track name 'Whole Transcriptome qPCR Primers' for the hg19 (Human) and mm10 (Mouse) genome versions. Batch query is available in the following: http://www.weizmann.ac.il/complex/compphys/software/Amit/primers/batch_query_qpcr_primers.htm CONTACT: amit.zeisel@weizmann.ac.il or eytan.domany@weizmann.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets.

MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miR's targets is a considerable bioinformatic challenge of great importance for inferring the miR's function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methods--it identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs' function in a specific context.

Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.

Complex interactions between different host immune cell types can determine the outcome of pathogen infections. Advances in single cell RNA-sequencing (scRNA-seq) allow probing of these immune interactions, such as cell-type compositions, which are then interpreted by deconvolution algorithms using bulk RNA-seq measurements. However, not all aspects of immune surveillance are represented by current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we develop a deconvolution algorithm for inferring cell-type specific infection responses from bulk measurements. We apply our dynamic deconvolution algorithm to a cohort of healthy individuals challenged ex vivo with Salmonella, and to three cohorts of tuberculosis patients during different stages of disease. We reveal cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and human infection outcomes.

Tumor Evolution Inferred by Patterns of microRNA Expression through the Course of Disease, Therapy, and Recurrence in Breast Cancer.

PURPOSE: Molecular evolution of tumors during progression, therapy, and metastasis is a major clinical challenge and the main reason for resistance to therapy. We hypothesized that microRNAs (miRNAs) that exhibit similar variation of expression through the course of disease in several patients have a significant function in the tumorigenic process. EXPERIMENTAL DESIGN: Exploration of evolving disease by profiling 800 miRNA expression from serial samples of individual breast cancer patients at several time points: pretreatment, posttreatment, lymph nodes, and recurrence sites when available (58 unique samples from 19 patients). Using a dynamic approach for analysis, we identified expression modulation patterns and classified varying miRNAs into one of the eight possible temporal expression patterns. RESULTS: The various patterns were found to be associated with different tumorigenic pathways. The dominant pattern identified an miRNA set that significantly differentiated between disease stages, and its pattern in each patient was also associated with response to therapy. These miRNAs were related to tumor proliferation and to the cell-cycle pathway, and their mRNA targets showed anticorrelated expression. Interestingly, the level of these miRNAs was lowest in matched recurrent samples from distant metastasis, indicating a gradual increase in proliferative potential through the course of disease. Finally, the average expression level of these miRNAs in the pretreatment biopsy was significantly different comparing patients experiencing recurrence to recurrence-free patients. CONCLUSIONS: Serial tumor sampling combined with analysis of temporal expression patterns enabled to pinpoint significant signatures characterizing breast cancer progression, associated with response to therapy and with risk of recurrence. Clin Cancer Res; 22(14); 3651-62. ©2016 AACR.

The locus of microRNA-10b: a critical target for breast cancer insurgence and dissemination.

Contemporary microRNA research has led to significant advances in our understanding of the process of tumorigenesis. MicroRNAs participate in different events of a cancer cell's life, through their ability to target hundreds of putative transcripts involved in almost every cellular function, including cell cycle, apoptosis, and differentiation. The relevance of these small molecules is even more evident in light of the emerging linkage between their expression and both prognosis and clinical outcome of many types of human cancers. This identifies microRNAs as potential therapeutic modifiers of cancer phenotypes. From this perspective, we overview here the miR-10b locus and its involvement in cancer, focusing on its role in the establishment (miR-10b*) and spreading (miR-10b) of breast cancer. We conclude that targeting the locus of microRNA 10b holds great potential for cancer treatment.

miR-10b*, a master inhibitor of the cell cycle, is down-regulated in human breast tumours.

Deregulated proliferation is a hallmark of cancer cells. Here, we show that microRNA-10b* is a master regulator of breast cancer cell proliferation and is downregulated in tumoural samples versus matched peritumoural counterparts. Two canonical CpG islands (5 kb) upstream from the precursor sequence are hypermethylated in the analysed breast cancer tissues. Ectopic delivery of synthetic microRNA-10b* in breast cancer cell lines or into xenograft mouse breast tumours inhibits cell proliferation and impairs tumour growth in vivo, respectively. We identified and validated in vitro and in vivo three novel target mRNAs of miR-10b* (BUB1, PLK1 and CCNA2), which play a remarkable role in cell cycle regulation and whose high expression in breast cancer patients is associated with reduced disease-free survival, relapse-free survival and metastasis-free survival when compared to patients with low expression. This also suggests that restoration of microRNA-10b* expression might have therapeutic promise.