Seq-ing answers: uncovering the unexpected in global gene regulation

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Analysis of molecular pathway activation is the recent instrument that helps to quantize activities of various intracellular signaling, structural, DNA synthesis and repair, and biochemical processes. This may have a deep impact in fundamental research, bioindustry, and medicine. Unlike gene ontology analyses and numerous qualitative methods that can establish whether a pathway is affected in principle, the quantitative approach has the advantage of exactly measuring the extent of a pathway up/downregulation. This results in emergence of a new generation of molecular biomarkers-pathway activation levels, which reflect concentration changes of all measurable pathway components. The input data can be the high-throughput proteomic or transcriptomic profiles, and the output numbers take both positive and negative values and positively reflect overall pathway activation. Due to their nature, the pathway activation levels are more robust biomarkers compared to the individual gene products/protein levels. Here, we review the current knowledge of the quantitative gene expression interrogation methods and their applications for the molecular pathway quantization. We consider enclosed bioinformatic algorithms and their applications for solving real-world problems. Besides a plethora of applications in basic life sciences, the quantitative pathway analysis can improve molecular design and clinical investigations in pharmaceutical industry, can help finding new active biotechnological components and can significantly contribute to the progressive evolution of personalized medicine. In addition to the theoretical principles and concepts, we also propose publicly available software for the use of large-scale protein/RNA expression data to assess the human pathway activation levels.

SUMO is a pervasive regulator of meiosis

Protein modification by SUMO helps orchestrate the elaborate events of meiosis to faithfully produce haploid gametes. To date, only a handful of meiotic SUMO targets have been identified. Here, we delineate a multidimensional SUMO-modified meiotic proteome in budding yeast, identifying 2747 conjugation sites in 775 targets, and defining their relative levels and dynamics. Modified sites cluster in disordered regions and only a minority match consensus motifs. Target identities and modification dynamics imply that SUMOylation regulates all levels of chromosome organization and each step of meiotic prophase I. Execution-point analysis confirms these inferences, revealing functions for SUMO in S-phase, the initiation of recombination, chromosome synapsis and crossing over. K15-linked SUMO chains become prominent as chromosomes synapse and recombine, consistent with roles in these processes. SUMO also modifies ubiquitin, forming hybrid oligomers with potential to modulate ubiquitin signaling. We conclude that SUMO plays diverse and unanticipated roles in regulating meiotic chromosome metabolism.

Most mammalian, yeast and other eukaryote cells have two sets of chromosomes, one from each parent, which contain all the cell’s DNA. Sex cells – like the sperm and egg – however, have half the number of chromosomes and are formed by a specialized type of cell division known as meiosis. At the start of meiosis, each cell replicates its chromosomes so that it has twice the amount of DNA. The cell then undergoes two rounds of division to form sex cells which each contain only one set of chromosomes. Before the cell divides, the two duplicated sets of chromosomes pair up and swap sections of their DNA. This exchange allows each new sex cell to have a unique combination of DNA, resulting in offspring that are genetically distinct from their parents.

This complex series of events is tightly regulated, in part, by a protein called the 'small ubiquitin-like modifier' (or SUMO for short), which attaches itself to other proteins and modifies their behavior. This process, known as SUMOylation, can affect a protein’s stability, where it is located in the cell and how it interacts with other proteins. However, despite SUMO being known as a key regulator of meiosis, only a handful of its protein targets have been identified.

To gain a better understanding of what SUMO does during meiosis, Bhagwat et al. set out to find which proteins are targeted by SUMO in budding yeast and to map the specific sites of modification. The experiments identified 2,747 different sites on 775 different proteins, suggesting that SUMO regulates all aspects of meiosis. Consistently, inactivating SUMOylation at different times revealed SUMO plays a role at every stage of meiosis, including the replication of DNA and the exchanges between chromosomes. In depth analysis of the targeted proteins also revealed that SUMOylation targets different groups of proteins at different stages of meiosis and interacts with other protein modifications, including the ubiquitin system which tags proteins for destruction.

The data gathered by Bhagwat et al. provide a starting point for future research into precisely how SUMO proteins control meiosis in yeast and other organisms. In humans, errors in meiosis are the leading cause of pregnancy loss and congenital diseases. Most of the proteins identified as SUMO targets in budding yeast are also present in humans. So, this research could provide a platform for medical advances in the future. The next step is to study mammalian models, such as mice, to confirm that the regulation of meiosis by SUMO is the same in mammals as in yeast.

Monitoring Bacterial Translation Rates Genome-Wide

Modern DNA sequencing technologies have allowed for the sequencing of tens of thousands of bacterial genomes. While this explosion of information has brought about new insights into the diversity of the prokaryotic world, much less is known of the identity of proteins encoded within these genomes, as well as their rates of production. The advent of ribosome profiling, or the deep sequencing of ribosome-protected footprints, has recently enabled the systematic evaluation of every protein-coding region in a given experimental condition, the rates of protein production for each gene, and the variability in translation rates across each message. Here, I provide an update to the bacterial ribosome profiling approach, with a particular emphasis on a simplified strategy to reduce cloning time.

Rules are made to be broken: a "simple" model organism reveals the complexity of gene regulation

Global methods for assaying translation have greatly improved our understanding of the protein-coding capacity of the genome. In particular, it is now possible to perform genome-wide and condition-specific identification of translation initiation sites through modified ribosome profiling methods that selectively capture initiating ribosomes. Here we discuss our recent study applying such an approach to meiotic and mitotic timepoints in the simple eukaryote, budding yeast, as an example of the surprising diversity of protein products-many of which are non-canonical-that can be revealed by such methods. We also highlight several key challenges in studying non-canonical protein isoforms that have precluded their prior systematic discovery. A growing body of work supports expanded use of empirical protein-coding region identification, which can help relieve some of the limitations and biases inherent to traditional genome annotation approaches. Our study also argues for the adoption of less static views of gene identity and a broader framework for considering the translational capacity of the genome.

Proteomic analysis of meiosis and characterization of novel short open reading frames in the fission yeast Schizosaccharomyces pombe

Meiosis is the process by which haploid gametes are produced from diploid precursor cells. We used stable isotope labeling by amino acids in cell culture (SILAC) to characterize the meiotic proteome in the fission yeast Schizosaccharomyces pombe. We compared relative levels of proteins extracted from cells harvested around meiosis I with those of meiosis II, and proteins from premeiotic S phase with the interval between meiotic divisions, when S phase is absent. Our proteome datasets revealed peptides corresponding to short open reading frames (sORFs) that have been previously identified by ribosome profiling as new translated regions. We verified expression of selected sORFs by Western blotting and analyzed the phenotype of deletion mutants. Our data provide a resource for studying meiosis that may help understand differences between meiosis I and meiosis II and how S phase is suppressed between the two meiotic divisions.

Quantitation of Molecular Pathway Activation Using RNA Sequencing Data

Intracellular molecular pathways (IMPs) control all major events in the living cell. IMPs are considered hotspots in biomedical sciences and thousands of IMPs have been discovered for humans and model organisms. Knowledge of IMPs activation is essential for understanding biological functions and differences between the biological objects at the molecular level. Here we describe the Oncobox system for accurate quantitative scoring activities of up to several thousand molecular pathways based on high throughput molecular data. Although initially designed for gene expression and mainly RNA sequencing data, Oncobox is now also applicable for quantitative proteomics, microRNA and transcription factor binding sites mapping data. The Oncobox system includes modules of gene expression data harmonization, aggregation and comparison and a recursive algorithm for automatic annotation of molecular pathways. The universal rationale of Oncobox enables scoring of signaling, metabolic, cytoskeleton, immunity, DNA repair, and other pathways in a multitude of biological objects. The Oncobox system can be helpful to all those working in the fields of genetics, biochemistry, interactomics, and big data analytics in molecular biomedicine.

Evidence for an Integrated Gene Repression Mechanism Based on mRNA Isoform Toggling in Human Cells

We recently described an unconventional mode of gene regulation in budding yeast by which transcriptional and translational interference collaborate to down-regulate protein expression. Developmentally timed transcriptional interference inhibited production of a well translated mRNA isoform and resulted in the production of an mRNA isoform containing inhibitory upstream open reading frames (uORFs) that prevented translation of the main ORF. Transcriptional interference and uORF-based translational repression are established mechanisms outside of yeast, but whether this type of integrated regulation was conserved was unknown. Here we find that, indeed, a similar type of regulation occurs at the locus for the human oncogene MDM2 We observe evidence of transcriptional interference between the two MDM2 promoters, which produce a poorly translated distal promoter-derived uORF-containing mRNA isoform and a well-translated proximal promoter-derived transcript. Down-regulation of distal promoter activity markedly up-regulates proximal promoter-driven expression and results in local reduction of histone H3K36 trimethylation. Moreover, we observe that this transcript toggling between the two MDM2 isoforms naturally occurs during human embryonic stem cell differentiation programs.

Melatonin Mitigates Mitochondrial Meltdown: Interactions with SIRT3

Melatonin exhibits extraordinary diversity in terms of its functions and distribution. When discovered, it was thought to be uniquely of pineal gland origin. Subsequently, melatonin synthesis was identified in a variety of organs and recently it was shown to be produced in the mitochondria. Since mitochondria exist in every cell, with a few exceptions, it means that every vertebrate, invertebrate, and plant cell produces melatonin. The mitochondrial synthesis of melatonin is not photoperiod-dependent, but it may be inducible under conditions of stress. Mitochondria-produced melatonin is not released into the systemic circulation, but rather is used primarily in its cell of origin. Melatonin's functions in the mitochondria are highly diverse, not unlike those of sirtuin 3 (SIRT3). SIRT3 is an NAD+-dependent deacetylase which regulates, among many functions, the redox state of the mitochondria. Recent data proves that melatonin and SIRT3 post-translationally collaborate in regulating free radical generation and removal from mitochondria. Since melatonin and SIRT3 have cohabitated in the mitochondria for many eons, we predict that these molecules interact in many other ways to control mitochondrial physiology. It is predicted that these mutual functions will be intensely investigated in the next decade and importantly, we assume that the findings will have significant applications for preventing/delaying some age-related diseases and aging itself.

Global Proteome Remodeling during ER Stress Involves Hac1-Driven Expression of Long Undecoded Transcript Isoforms

Cellular stress responses often require transcription-based activation of gene expression to promote cellular adaptation. Whether general mechanisms exist for stress-responsive gene downregulation is less clear. A recently defined mechanism enables both up- and downregulation of protein levels for distinct gene sets by the same transcription factor via coordinated induction of canonical mRNAs and long undecoded transcript isoforms (LUTIs). We analyzed parallel gene expression datasets to determine whether this mechanism contributes to the conserved Hac1-driven branch of the unfolded protein response (UPRER), indeed observing Hac1-dependent protein downregulation accompanying the upregulation of ER-related proteins that typifies UPRER activation. Proteins downregulated by Hac1-driven LUTIs include those with electron transport chain (ETC) function. Abrogated ETC function improves the fitness of UPRER-activated cells, suggesting functional importance to this regulation. We conclude that the UPRER drives large-scale proteome remodeling, including coordinated up- and downregulation of distinct protein classes, which is partly mediated by Hac1-induced LUTIs.