Project description:Grad-seq in Clostridium difficile 630. Cell lysate is analyzed in a gradient and fractionated into 21 fractions which are analysed for proteins by MS and for transcripts by RNA-sequencing.
Project description:Proteomic data of ScSUGAR-seq samples: 1)TMT experiment to confirm changes in glycosylation due to Swainsonine 2)LFQ biotin pull down experiment to assess lectin binding partners 3)LFQ of MGAT1 cell lines assessing glycopeptide and glycoproteome level changes
Project description:Estrogen Receptor alpha (ERα) is a key driver of most breast cancers, and it is the target of endocrine therapies used in the clinic to treat women with ERα positive (ER+) breast cancer. The two methods ChIP-seq (chromatin immunoprecipitation coupled with deep sequencing) and RIME (Rapid Immunoprecipitation of Endogenous Proteins) have greatly improved our understanding of ERα function during breast cancer progression and in response to anti-estrogens. A critical component of both ChIP-seq and RIME protocols is the antibody that is used to pull down the bait protein. To date, most of the ChIP-seq and RIME experiments for the study of ERα have been performed using the sc-543 antibody from Santa Cruz Biotechnology. However, this antibody has been discontinued, thereby severely impacting the study of ERα in normal physiology as well as diseases such as breast cancer and ovarian cancer. Here, we compare the sc-543 antibody with other commercially available antibodies, and we show that 06-935 (EMD Millipore) and ab3575 (Abcam) antibodies can successfully replace the sc-543 antibody for ChIP-seq and RIME experiments.
Project description:Here we analyzed the full ensemble of cellular RNAs and co-fractionating proteins using gradient profiling by sequencing (Grad-seq) in Synechocystis 6803, a cyanobacterium rich in internal membrane systems.
Project description:Energy metabolism and extracellular matrix function are closely connected to orchestrate and maintain tissue organization, but the crosstalk is poorly understood. Here, we used scRNA-seq analysis to uncover the importance of respiration for extracellular matrix homeostasis in mature cartilage. Genetic inhibition of respiration in cartilage results in the expansion of a central area of 1-month-old mouse femur head cartilage showing disorganized chondrocytes and increased deposition of extracellular matrix material. scRNA-seq analysis identified a cluster-specific decrease in mitochondrial DNA-encoded respiratory chain genes and a unique regulation of extracellular matrix-related genes in nonarticular chondrocyte clusters. These changes were associated with alterations in extracellular matrix composition, a shift in the collagen/non-collagen protein content and an increase of collagen crosslinking and ECM stiffness. The results demonstrate, based on findings of the scRNA-seq analysis, that respiration is a key factor contributing to ECM integrity and mechanostability in cartilage and presumably also in many other tissues.
Project description:Quantitative analysis of the sequence determinants of transcription and translation regulation is of special relevance for systems and synthetic biology applications. Here, we developed a novel generic approach for the fast and efficient analysis of these determinants in vivo. ELM-seq (expression level monitoring by DNA methylation) uses Dam coupled to high-throughput sequencing) as a reporter that can be detected by DNA-seq. We used the genome-reduced bacterium Mycoplasma pneumoniae to show that it is a quantitative reporter. We showed that the methylase activity correlates with protein expression, does not affect cell viability, and has a large dynamic range (~10,000-fold). We applied ELM-seq to randomized libraries of promoters or 5’ untranslated regions. We found that transcription is greatly influenced by the bases around the +1 of the transcript and the Pribnow box, and we also identified several epistatic interactions (including the +1 and the “extended Pribnow”). Regarding translation initiation, we confirmed that the Shine-Dalgarno motif is not relevant, but instead, that RNA secondary structure is the main governing factor. With this in hand, we developed a predictor to help tailor gene expression in M. pneumoniae. The simple ELM-seq methodology will allow identifying and optimizing key sequence determinants for promoter strength and translation. The ELM-seq methodology allows both researchers and companies to identify and optimize in an easy and comprehensive manner, key sequence determinants for promoter strength and translation.
Project description:mRNAs are generally assumed to be loaded instantly with ribosomes upon entry into the cytoplasm. To measure ribosome density on nascent mRNA, we developed nascent Ribo-Seq (nRibo-Seq) by combining Ribo-Seq with progressive 4-thiouridine labelling. In mouse macrophages, we experimentally determined, for the first time, the lag between the appearance of nascent RNA and its association with ribosomes, which was calculated to be 20 - 22 min for bulk mRNA, and approximated the time it takes for mRNAs to be fully loaded with ribosomes to be 41 - 44 min. Notably, ribosomal loading time is adapted to gene function as rapid loading was observed with highly regulated genes. The lag and ribosomal loading time correlate positively with ORF size and mRNA half-life, and negatively with tRNA adaptation index. Similar results were obtained in mouse embryonic stem cells, where the lag in ribosome loading was even more pronounced with 35 - 38 min. We validated our measurements after stimulation of macrophages with lipopolysaccharide, where the lag between cytoplasmic and translated mRNA leads to uncoupling between input and ribosome-protected fragments. Uncoupling is stronger for mRNAs with long ORFs or half-lives, a finding we also confirmed at the level of protein production by nascent chain proteomics. As a consequence of the lag in ribosome loading, ribosome density measurements are distorted when performed under conditions where mRNA levels are far from steady state expression, and transcriptional changes affect ribosome density in a passive way. This study uncovers an unexpected and considerable lag in ribosome loading, and provides guidelines for the interpretation of Ribo-Seq data taking passive effects on ribosome density into account.