A Bayesian network model of proteins' association with promyelocytic leukemia (PML) nuclear bodies

Dynamic label-free analysis of SARS-CoV-2 infection reveals virus-induced subcellular remodeling

Assessing the impact of SARS-CoV-2 on organelle dynamics allows a better understanding of the mechanisms of viral replication. We combine label-free holotomographic microscopy with Artificial Intelligence to visualize and quantify the subcellular changes triggered by SARS-CoV-2 infection. We study the dynamics of shape, position and dry mass of nucleoli, nuclei, lipid droplets and mitochondria within hundreds of single cells from early infection to syncytia formation and death. SARS-CoV-2 infection enlarges nucleoli, perturbs lipid droplets, changes mitochondrial shape and dry mass, and separates lipid droplets from mitochondria. We then used Bayesian network modeling on organelle dry mass states to define organelle cross-regulation networks and report modifications of organelle cross-regulation that are triggered by infection and syncytia formation. Our work highlights the subcellular remodeling induced by SARS-CoV-2 infection and provides an Artificial Intelligence-enhanced, label-free methodology to study in real-time the dynamics of cell populations and their content.

PML isoform expression and DNA break location relative to PML nuclear bodies impacts the efficiency of homologous recombination

Promyelocytic leukemia nuclear bodies (PML NBs) are nuclear subdomains that respond to genotoxic stress by increasing in number via changes in chromatin structure. However, the role of the PML protein and PML NBs in specific mechanisms of DNA repair has not been fully characterized. Here, we have directly examined the role of PML in homologous recombination (HR) using I-SceI extrachromosomal and chromosome-based homology-directed repair (HDR) assays, and in HDR by CRISPR/Cas9-mediated gene editing. We determined that PML loss can inhibit HR in an extrachromosomal HDR assay but had less of an effect on CRISPR/Cas9-mediated chromosomal HDR. Overexpression of PML also inhibited both CRISPR HDR and I-SceI-induced HDR using a chromosomal reporter, and in an isoform-specific manner. However, the impact of PML overexpression on the chromosomal HDR reporter was dependent on the intranuclear chromosomal positioning of the reporter. Specifically, HDR at the TAP1 gene locus, which is associated with PML NBs, was reduced compared with a locus not associated with a PML NB; yet, HDR could be reduced at the non-PML NB-associated locus by PML overexpression. Thus, both loss and overexpression of PML isoforms can inhibit HDR, and proximity of a chromosomal break to a PML NB can impact HDR efficiency.

Predicting the dynamics of protein abundance

Protein synthesis is finely regulated across all organisms, from bacteria to humans, and its integrity underpins many important processes. Emerging evidence suggests that the dynamic range of protein abundance is greater than that observed at the transcript level. Technological breakthroughs now mean that sequencing-based measurement of mRNA levels is routine, but protocols for measuring protein abundance remain both complex and expensive. This paper introduces a Bayesian network that integrates transcriptomic and proteomic data to predict protein abundance and to model the effects of its determinants. We aim to use this model to follow a molecular response over time, from condition-specific data, in order to understand adaptation during processes such as the cell cycle. With microarray data now available for many conditions, the general utility of a protein abundance predictor is broad. Whereas most quantitative proteomics studies have focused on higher organisms, we developed a predictive model of protein abundance for both Saccharomyces cerevisiae and Schizosaccharomyces pombe to explore the latitude at the protein level. Our predictor primarily relies on mRNA level, mRNA-protein interaction, mRNA folding energy and half-life, and tRNA adaptation. The combination of key features, allowing for the low certainty and uneven coverage of experimental observations, gives comparatively minor but robust prediction accuracy. The model substantially improved the analysis of protein regulation during the cell cycle: predicted protein abundance identified twice as many cell-cycle-associated proteins as experimental mRNA levels. Predicted protein abundance was more dynamic than observed mRNA expression, agreeing with experimental protein abundance from a human cell line. We illustrate how the same model can be used to predict the folding energy of mRNA when protein abundance is available, lending credence to the emerging view that mRNA folding affects translation efficiency. The software and data used in this research are available at http://bioinf.scmb.uq.edu.au/proteinabundance/.

Sorting the nuclear proteome

Motivation: Quantitative experimental analyses of the nuclear interior reveal a morphologically structured yet dynamic mix of membraneless compartments. Major nuclear events depend on the functional integrity and timely assembly of these intra-nuclear compartments. Yet, unknown drivers of protein mobility ensure that they are in the right place at the time when they are needed.

Results: This study investigates determinants of associations between eight intra-nuclear compartments and their proteins in heterogeneous genome-wide data. We develop a model based on a range of candidate determinants, capable of mapping the intra-nuclear organization of proteins. The model integrates protein interactions, protein domains, post-translational modification sites and protein sequence data. The predictions of our model are accurate with a mean AUC (over all compartments) of 0.71.

We present a complete map of the association of 3567 mouse nuclear proteins with intra-nuclear compartments. Each decision is explained in terms of essential interactions and domains, and qualified with a false discovery assessment. Using this resource, we uncover the collective role of transcription factors in each of the compartments. We create diagrams illustrating the outcomes of a Gene Ontology enrichment analysis. Associated with an extensive range of transcription factors, the analysis suggests that PML bodies coordinate regulatory immune responses.

Contact:m.boden@uq.edu.au

Supplementary information:Supplementary data are available at Bioinformatics online.

DNA mismatch repair proteins are required for efficient herpes simplex virus 1 replication

Herpes simplex virus 1 (HSV-1) is a double-stranded DNA virus that replicates in the nucleus of its human host cell and is known to interact with many cellular DNA repair proteins. In this study, we examined the role of cellular mismatch repair (MMR) proteins in the virus life cycle. Both MSH2 and MLH1 are required for efficient replication of HSV-1 in normal human cells and are localized to viral replication compartments. In addition, a previously reported interaction between MSH6 and ICP8 was confirmed by coimmunoprecipitation and extended to show that UL12 is also present in this complex. We also report for the first time that MLH1 associates with ND10 nuclear bodies and that like other ND10 proteins, MLH1 is recruited to the incoming genome. Knockdown of MLH1 inhibits immediate-early viral gene expression. MSH2, on the other hand, which is generally thought to play a role in mismatch repair at a step prior to that of MLH1, is not recruited to incoming genomes and appears to act at a later step in the viral life cycle. Silencing of MSH2 appears to inhibit early gene expression. Thus, both MLH1 and MSH2 are required but appear to participate in distinct events in the virus life cycle. The observation that MLH1 plays an earlier role in HSV-1 infection than does MSH2 is surprising and may indicate a novel function for MLH1 distinct from its known MSH2-dependent role in mismatch repair.