As a well-known phenomenon, total mRNAs poorly correlate to proteins in their abundances as reported. Recent findings calculated with bivariate models suggested even poorer such correlation, whereas focusing on the translating mRNAs (ribosome nascent-chain complex-bound mRNAs, RNC-mRNAs) subset. In this study, we analysed the relative abundances of mRNAs, RNC-mRNAs and proteins on genome-wide scale, comparing human lung cancer A549 and H1299 cells with normal human bronchial epithelial (HBE) cells, respectively. As discovered, a strong correlation between RNC-mRNAs and proteins in their relative abundances could be established through a multivariate linear model by integrating the mRNA length as a key factor. The R2 reached 0.94 and 0.97 in A549 versus HBE and H1299 versus HBE comparisons, respectively. This correlation highlighted that the mRNA length significantly contributes to the translational modulation, especially to the translational initiation, favoured by its correlation with the mRNA translation ratio (TR) as observed. We found TR is highly phenotype specific, which was substantiated by both pathway analysis and biased TRs of the splice variants of BDP1 gene, which is a key transcription factor of transfer RNAs. These findings revealed, for the first time, the intrinsic and genome-wide translation modulations at translatomic level in human cells at steady-state, which are tightly correlated to the protein abundance and functionally relevant to cellular phenotypes.

To fully exploit the microbial genome resources, a high-throughput experimental platform is needed to associate genes with phenotypes at the genome level. We present here a novel method that enables investigation of the cellular consequences of repressing individual transcripts based on the CRISPR interference (CRISPRi) pooled screening in bacteria. We identify rules for guide RNA library design to handle the unique structure of prokaryotic genomes by tiling screening and construct an E. coli genome-scale guide RNA library (~60,000 members) accordingly. We show that CRISPRi outperforms transposon sequencing, the benchmark method in the microbial functional genomics field, when similar library sizes are used or gene length is short. This tool is also effective for mapping phenotypes to non-coding RNAs (ncRNAs), as elucidated by a comprehensive tRNA-fitness map constructed here. Our results establish CRISPRi pooled screening as a powerful tool for mapping complex prokaryotic genetic networks in a precise and high-throughput manner.

Chromosome-centric human proteome project (C-HPP) aims at differentiating chromosome-based and tissue-specific protein compositions in terms of protein expression, quantification, and modification. We previously found that the analysis of translating mRNA (mRNA attached to ribosome-nascent chain complex, RNC-mRNA) can explain over 94% of mRNA-protein abundance. Therefore, we propose here to use full-length RNC-mRNA information to illustrate protein expression both qualitatively and quantitatively. We performed RNA-seq on RNC-mRNA (RNC-seq) and detected 12,758 and 14,113 translating genes in human normal bronchial epithelial (HBE) cells and human colorectal adenocarcinoma Caco-2 cells, respectively. We found that most of these genes were mapped with >80% of coding sequence coverage. In Caco-2 cells, we provided translating evidence on 4180 significant single-nucleotide variations. While using RNC-mRNA data as a standard for proteomic data integration, both translating and protein evidence of 7876 genes can be acquired from four interlaboratory data sets with different MS platforms. In addition, we detected 1397 noncoding mRNAs that were attached to ribosomes, suggesting a potential source of new protein explorations. By comparing the two cell lines, a total of 677 differentially translated genes were found to be nonevenly distributed across chromosomes. In addition, 2105 genes in Caco-2 and 750 genes in HBE cells are expressed in a cell-specific manner. These genes are significantly and specifically clustered on multiple chromosomes, such as chromosome 19. We conclude that HPP/C-HPP investigations can be considerably improved by integrating RNC-mRNA analysis with MS, bioinformatics, and antibody-based verifications.

CRISPR/Cas9 is a promising tool in prokaryotic genome engineering, but its success is limited by the widely varying on-target activity of single guide RNAs (sgRNAs). Based on the association of CRISPR/Cas9-induced DNA cleavage with cellular lethality, we systematically profiled sgRNA activity by co-expressing a genome-scale library (∼70 000 sgRNAs) with Cas9 or its specificity-improved mutant in Escherichia coli. Based on this large-scale dataset, we constructed a comprehensive and high-density sgRNA activity map, which enables selecting highly active sgRNAs for any locus across the genome in this model organism. We also identified ‘resistant’ genomic loci with respect to CRISPR/Cas9 activity, notwithstanding the highly accessible DNA in bacterial cells. Moreover, we found that previous sgRNA activity prediction models that were trained on mammalian cell datasets were inadequate when coping with our results, highlighting the key limitations and biases of previous models. We hence developed an integrated algorithm to accurately predict highly effective sgRNAs, aiming to facilitate CRISPR/Cas9-based genome engineering, screenings and antimicrobials design in bacteria. We also isolated the important sgRNA features that contribute to DNA cleavage and characterized their key differences among wild type Cas9 and its mutant, shedding light on the biophysical mechanisms of the CRISPR/Cas9 system.

The exosome is a key initiator of pre-metastatic niche in numerous cancers, where macrophages serve as primary inducers of tumor microenvironment. However, the proteome that can be exosomally transported from cancer cells to macrophages has not been sufficiently characterized so far. Here, we used colorectal cancer (CRC) exosomes to educate tumor-favorable macrophages. With a SILAC-based mass spectrometry strategy, we successfully traced the proteome transported from CRC exosomes to macrophages. Such a proteome primarily focused on promoting cytoskeleton rearrangement, which was biologically validated with multiple cell lines. We reproduced the exosomal transportation of functional vimentin as a proof-of-concept example. In addition, we found that some CRC exosomes could be recognized by macrophages via Fc receptors. Therefore, we revealed the active and necessary role of exosomes secreted from CRC cells to transform cancer-favorable macrophages, with the cytoskeleton-centric proteins serving as the top functional unit.