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Typical multiomics studies employ separate methods for DNA, RNA, and protein sample preparation, which is labor intensive, costly, and prone to sampling bias. We describe a method for preparing high-quality, sequencing-ready DNA and RNA, and either intact proteins or mass-spectrometry-ready peptides for whole proteome analysis from a single sample. This method utilizes a reversible protein tagging scheme to covalently link all proteins in a lysate to a bead-based matrix and nucleic acid precipitation and selective solubilization to yield separate pools of protein and nucleic acids. We demonstrate the utility of this method to compare the genomes, transcriptomes, and proteomes of four triple-negative breast cancer cell lines with different degrees of malignancy. These data show the involvement of both RNA and associated proteins, and protein-only dependent pathways that distinguish these cell lines. We also demonstrate the utility of this multiomics workflow for tissue analysis using mouse brain, liver, and lung tissue.

 

As transposon sequencing (TnSeq) assays have become prolific in the microbiology field, it is of interest to scrutinize their potential drawbacks. TnSeq data consist of millions of nucleotide sequence reads that are generated by PCR amplification of transposon-genomic junctions. Reads mapping to the junctions are enumerated thus providing information on the number of transposon insertion mutations in each individual gene. Here we explore the possibility that PCR amplification of transposon insertions in a TnSeq library skews the results by introducing bias into the detection and/or enumeration of insertions. We compared the detection and frequency of mapped insertions when altering the number of PCR cycles, and when including a nested PCR, in the enrichment step. Additionally, we present nCATRAs - a novel, amplification-free TnSeq method where the insertions are enriched via CRISPR/Cas9-targeted transposon cleavage and subsequent Oxford Nanopore MinION sequencing. nCATRAs achieved 54 and 23% enrichment of the transposons and transposon-genomic junctions, respectively, over background genomic DNA. These PCR-based and PCR-free experiments demonstrate that, overall, PCR amplification does not significantly bias the results of TnSeq insofar as insertions in the majority of genes represented in our library were similarly detected regardless of PCR cycle number and whether or not PCR amplification was employed. However, the detection of a small subset of genes which had been previously described as essential is sensitive to the number of PCR cycles. We conclude that PCR-based enrichment of transposon insertions in a TnSeq assay is reliable, but researchers interested in profiling putative essential genes should carefully weigh the number of amplification cycles employed in their library preparation protocols. In addition, nCATRAs is comparable to traditional PCR-based methods (Kendall’s correlation=0.896–0.897) although the latter remain superior owing to their accessibility and high sequencing depth. 

ABSTRACT Mutation of purR was previously shown to enhance the virulence of Staphylococcus aureus in a murine sepsis model, and this cannot be fully explained by increased expression of genes within the purine biosynthesis pathway. Rather, the increased production of specific S. aureus virulence factors, including alpha toxin and the fibronectin-binding proteins, was shown to play an important role. Mutation of purR was also shown previously to result in increased abundance of SarA. Here, we demonstrate by transposon sequencing that mutation of purR in the USA300 strain LAC increases fitness in a biofilm while mutation of sarA has the opposite effect. Therefore, we assessed the impact of sarA on reported purR -associated phenotypes by characterizing isogenic purR , sarA , and sarA/purR mutants. The results confirmed that mutation of purR results in increased abundance of alpha toxin, protein A, the fibronectin-binding proteins, and SarA, decreased production of extracellular proteases, an increased capacity to form a biofilm, and increased virulence in an osteomyelitis model. Mutation of sarA had the opposite effects on all of these phenotypes and, other than bacterial burdens in the bone, all of the phenotypes of sarA / purR mutants were comparable to those of sarA mutants. Limiting the production of extracellular proteases reversed all of the phenotypes of sarA mutants and most of those of sarA/purR mutants. We conclude that a critical component defining the virulence of a purR mutant is the enhanced production of SarA, which limits protease production to an extent that promotes the accumulation of critical S. aureus virulence factors. 

Triple negative breast cancer (TNBC) is an aggressive type of breast cancer with very little treatment options. TNBC is very heterogeneous with large alterations in the genomic, transcriptomic, and proteomic landscapes leading to various subtypes with differing responses to therapeutic treatments. We applied a multi-omics data integration method to evaluate the correlation of important regulatory features in TNBC BRCA1 wild-type MDA-MB-231 and TNBC BRCA1 5382insC mutated HCC1937 cells compared with non-tumorigenic epithelial breast MCF10A cells. The data includes DNA methylation, RNAseq, protein, phosphoproteomics, and histone post-translational modification. Data integration methods identified regulatory features from each omics method that had greater than 80% positive correlation within each TNBC subtype. Key regulatory features at each omics level were identified distinguishing the three cell lines and were involved in important cancer related pathways such as TGFβ signaling, PI3K/AKT/mTOR, and Wnt/beta-catenin signaling. We observed overexpression of PTEN, which antagonizes the PI3K/AKT/mTOR pathway, and MYC, which downregulates the same pathway in the HCC1937 cells relative to the MDA-MB-231 cells. The PI3K/AKT/mTOR and Wnt/beta-catenin pathways are both downregulated in HCC1937 cells relative to MDA-MB-231 cells, which likely explains the divergent sensitivities of these cell lines to inhibitors of downstream signaling pathways. The DNA methylation and RNAseq data is freely available via GEO GSE171958 and the proteomics data is available via the ProteomeXchange PXD025238.