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tandem mass spectrometry (nLC-ESI-MS ⁄ MS). ... miss fluctuations occurring over shorter time scales ..... the core transcription complex TFIID (Santos-Rosa.

The Japanese Society of Developmental Biologists

Develop. Growth Differ. (2011) 53, 576–586

doi: 10.1111/j.1440-169X.2011.01271.x

Review Article

Nuclear organization and transcriptional dynamics in Dictyostelium Michelle Stevense, Jonathan R. Chubb* and Tetsuya Muramoto Division of Cell and Developmental Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK

The Dictyostelium model has a set of features uniquely well-suited to developing our understanding of transcriptional control. The complete Dictyostelium discoideum genome sequence has revealed that many of the molecular components regulating transcription in larger eukaryotes are conserved in Dictyostelium, from transcription factors and chromatin components to the enzymes and signals that regulate them. In addition, the system permits visualization of single gene firing events in living cells, which provides a more detailed view of transcription and its relationships to cell and developmental processes. This review will bring together the available knowledge of the structure and dynamics of the Dictyostelium nucleus and discuss recent transcription imaging studies and their implications for stability and accuracy of cell decisions. Key words: chromatin, live-cell imaging, nuclear organization, stochastic gene expression, transcription.

The last few years have a seen a resurgence of interest in gene regulation in Dictyostelium. This new interest has been stimulated by the conservation of nuclear components apparent from the Dictyostelium discoideum genome sequence, the consequent utility of reagents such as histone modification-specific antibodies designed for other organisms, and the development and improvement of methods for imaging nuclear processes in living cells. The purpose of the review is to summarize recent developments in our understanding of Dictyostelium nuclear biology, with a focus on chromatin organization and transcription imaging, and to integrate these developments into broader themes of transcriptional mechanism and cell specification during development. However, it is first appropriate to introduce the context of the biology we will discuss, by outlining what is known of the structure of the Dictyostelium nucleus.

Nuclear organization in Dictyostelium Dictyostelium discoideum amoebae have nuclei of approximately 3 microns in diameter, and contain a haploid genome of 34 Mb (the yeast genome is three *Author to whom all correspondence should be addressed. Email: [email protected] Received 11 January 2011; revised 28 January 2011; accepted 31 January 2011. ª 2011 The Authors Development, Growth & Differentiation ª 2011 Japanese Society of Developmental Biologists

times smaller and human 100 times larger). The nuclear morphology is somewhat round, but heterogeneous, with distortions perhaps caused by the highly dynamic cytoskeleton. The genome is organized on six chromosomes, with the exception of around 100 rDNA-containing minichromosomes of 88 kb (Sucgang et al. 2003). Nuclei undergo a fenestrated mitosis (Moens 1976), where the spindle microtubules operate through a partially disrupted nuclear envelope. The components of the nuclear envelope are sparsely characterized, although they contain conserved components such as the inner nuclear membrane protein, Sun1 (Xiong et al. 2008). Mitosis in Dictyostelium takes around 5 min (Muramoto & Chubb 2008). Nucleoli reside at the periphery of nuclei, and there are usually one to three lobes (Balbo & Bozzaro 2006). Chromosome organization has been revealed by the genome project (Eichinger et al. 2005). The gene density is high, with 62% of the genome predicted to encode protein. Each chromosome carries a cluster of repeats rich in Dictyostelium intermediate repeat sequence (DIRS) transposable elements near one end. It is likely that these tracts contain the centromeres, as they cluster adjacent to the centrosome at the nuclear edge during interphase, while dispersing at mitosis. The repeats are enriched in histone H3 methylated at lysine 9 (Chubb et al. 2006a), and recruit HP1 (Kaller et al. 2006a) and the centromeric histone H3 variant, H3v1 (DdCenH3) (Dubin et al. 2010). No ‘‘magic’’ centromere sequence has been associated with these repeats (Glockner & Heidel 2009), unlike the defined

The Dictyostelium nucleus

sequences of the yeast models. The ends of the chromosomes consist of some rDNA sequence (Eichinger et al. 2005). It is presently unclear if repeats exist more distally. Sequences at the telomeres of the rDNA minichromsomes have been identified, comprising four near perfect 29bp tandem repeats and a more distal CnT repeat (where n is 1-8) (Emery & Weiner 1981). The Dictyostelium genome encodes a telomerase homologue (DDB_G0293918). Nuclear DNA is replicated in a short S-phase (around 40 min per 8 h average cell cycle) and DNA replication begins immediately after completion of mitosis (Muramoto & Chubb 2008). There are distinct phases to DNA replication, with most of the nuclear DNA replicating in the first half of S-phase and the heterochromatin-like sequences (transposons ⁄ centromeres) replicating in the second half. Using the DNA-replication marker, GFP-PCNA (proliferating cell nuclear antigen), the early part of S-phase is characterized by a diffuse labeling overlaid by faint spots (Muramoto & Chubb 2008). These spots may be equivalent to mammalian replication factories (Gillespie & Blow 2010). In late S-phase, the heterochromatin replicates at a single bright fluorescent spot (visualized by GFP-PCNA or BrdU) at the nuclear edge. Late replication of heterochromatin is a feature shared by mammalian nuclei, contrasting the early replication of silent chromatin in budding and fission yeast.

Nucleosomal components and modifications The genome complement of histones in Dictyostelium reveals greater diversity than budding yeast, yet retains enough simplicity for genetic approaches to be very useful. The organism lacks the large repetitive tracts of histone genes found in many animal species but most of the histone subtypes have a number of divergent variants, permitting diversity of function. Histone molecular genetics are sufficiently advanced in Dictyostelium that point mutations can be targeted into endogenous histone loci (Muramoto et al. 2010). The major histone types in the core Dictyostelium nucleosome can be revealed by mass spectrometry of acid extracted nucleosomes (Fig. 1A), and comprise the standard core nucleosomal histones H3, H4, H2A and H2B. In addition, a linker histone, designated histone H1, is encoded by a single gene. H4 is encoded by two genes (at different genomic locations) predicted to encode identical polypeptides. The other histone types have additional variants. The H3 family comprises five genes. Three variants, H3a, H3b and H3c have a high level of conservation with mammalian H3 genes. They are H3.3-like histones, containing substitutions that make them distinct from H3.1 and H3.2

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classes (Elsaesser et al. 2010). H3a has AAIG in the histone core at residues 91–95 (typical of H3.3), H3b has AAIQ and H3c has AAIE, compared to SAVM in H3.1 ⁄ H3.2. H3.3 is capable of replication-independent deposition (Ahmad & Henikoff 2002), unlike H3.1, which is incorporated into chromatin only during DNA replication. An apparent paradox is that H3b mRNA contains a clear SL (stem loop) motif (Davila Lopez & Samuelsson 2008), normally a feature of replicationdependent histones. Unlike replication-independent histones, replication-dependent histone mRNAs are not polyadenylated, and contain a 3¢ SL motif associated with a partially independent RNA processing pathway involving U7 snRNP and the stem loop binding protein SLBP (DDB_G0288225 in Dictyostelium). The H3b and H3c genes are adjacent in the genome. H3c expressed sequence tags (ESTs) cannot be detected in EST databases (Urushihara et al. 2006), and we found no convincing evidence for H3c protein. Two more H3 variants, H3v1 and H3v2 have also been defined in the genome sequence. H3v1 is likely to be a centromeric H3 variant (Dubin et al. 2010). There is also a Dictybase gene model for an additional distant H3 variant (DDB_G0278587). Dictyostelium has five H2A genes. The major nucleosomal variant is H2AX, although peptides encoded by the gene annotated H2AZ can also be identified. Three other divergent variants (H2Av1-3) are encoded in the genome. Dictyostelium has three H2B variants. The major nucleosomal H2B is H2Bv3, and the genome has a hybrid gene, H2Bv1, which consists of a H2B histone domain followed by a divergent H2A sequence. The placement of an H2A-H2B dimer in the same polypeptide may have interesting structural implications. A further variant, H2Bv2, consists of N-terminal H2B sequence, with a long C-terminal domain with no identifiable sequence homologies. Whilst commercial antibodies against modified histone residues react with Dictyostelium histones (Kaller et al. 2006b), small changes in epitopes may render some antibodies ineffective. We therefore surveyed, using mass spectrometry (Martin et al. 2000; Aebersold & Mann 2003; Garcia et al. 2007), the modifications of the major Dictyostelium histone variants from asynchronously growing cells. Post-transcriptional modifications on histones H2AX, H2Bv3, H3a, H3b and H4 in Dictyostelium are shown in Figure 1. We observed patterns of methyl and acetyl marks on histone H3 and H4 with many characteristics of mammalian histones. We detected many modifications usually associated with transcriptional activation on H3 such as methylated K4, K36 and K79 (using standard H3 numbering after alignment with human H3) and acetylated K9, K14, K18, K23, and K27. In addition, we

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Fig. 1. Post-translational modification of core histones in Dictyostelium. (A) Crude nuclei were purified as described (Charlesworth & Parish 1975) with minor modifications. Histone extraction was performed by incubation with 0.4 N sulfuric acid for 1 h on ice and then the sample was precipitated with trichloroacetic acid (TCA). (B) Individual histones were digested with Trypsin, Chymotrypsin, Lys-C, or Arg-C, to cover various amino acid regions. The digested samples were analyzed by nano-HPLC electrospray ionization multistage tandem mass spectrometry (nLC-ESI-MS ⁄ MS). The resulting data were submitted to a MASCOT program (Perkins et al. 1999) for searching against Dictyostelium and histone protein databases. ac, acetylation; me, methylation; P, phosphorylation. Numbers of dots under methylated lysines represent mono-, di-, or tri-methylation.

identified both H3K9Me2 and H3K9Me3, modifications absent from yeast, in agreement with earlier antibody data (Chubb et al. 2006a; Dubin et al. 2010). The mitosis-associated phosphorylation of H3S10 was also detected, although was rare, perhaps because mitosis is around 1% of the cell cycle (Muramoto & Chubb 2008). Although H3K27Me is found in many complex

eukaryotic systems (Kouzarides 2007), we found no evidence of this modification in Dictyostelium. H3K27 methylation is linked to polycomb function in many metazoans, so the absence of H3K27Me in Dictyostelium may coincide with the apparent absence of polycomb complex components in the organism. By preparing the sample in the DNA damaging agents

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bleomycin and cisplatin, we were able to detect phosphorylation of S150 on Dictyostelium H2AX, as previously detected by immunoblot (Hudson et al. 2005). Evidence for modification of H2AZ was not detected, although we identified peptides spanning more than 70% of the protein.

Transcription dynamics It is now straightforward to visualize nascent RNA at single endogenous genes in live Dictyostelium cells. Standard methods to measure transcription such as northern blotting, microarrays, reverse transcription– polymerase chain reaction (RT–PCR) and RNAseq are ensemble measurements of disrupted cells. Although useful, these techniques create a population average and individual cells cannot be followed through time. In many systems, single cell transcriptional activity has been inferred by measuring fluctuations in fluorescent proteins (Elowitz et al. 2002; Ozbudak et al. 2002; Bar-Even et al. 2006; Sigal et al. 2006), or enzymes (Rutter et al. 1995) at the single cell level. Although extremely useful, these techniques are influenced by protein folding as well as RNA and protein turnover, and depending upon these parameters, can potentially miss fluctuations occurring over shorter time scales (Dong & Mcmillen 2008). Single cell and in some cases single molecule analyses of transcription have been possible in fixed cells for a number of years, using RNA fluorescence in situ (A)

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hybridization (FISH) (Femino et al. 1998; Raj et al. 2008). These techniques were instrumental in revealing the noise inherent to transcription (Larson et al. 2009), have illustrated how network architecture can minimize developmental error (Raj et al. 2010), highlighted the lack of transcriptional order in cells over short integration times (Gandhi et al. 2011), and have provided evidence for important models of transcriptional mechanism (Raj et al. 2006; Zenklusen et al. 2008). However, the cells are dead, therefore dynamic information is lost. Live analysis of multicopy transgene expression has been possible in recent years in human tissue culture cells (Janicki et al. 2004; Darzacq et al. 2007), in addition to more indirect methods for looking at transcription, such as the appearance of regulators at heat shock loci of polytene chromosomes (Yao et al. 2006). More recently, single allele transcriptional events were measured in HEK-293 cells using Flp recombinase-integrated reporters (Yunger et al. 2010), and mice bearing a transcriptional reporter in the locus encoding b-actin have also been generated (Lionnet et al. 2011). Detecting transcription in living cells takes advantage of a RNA hairpin from the genome of the RNA bacteriophage MS2 (Fig. 2) (Bertrand et al. 1998). The hairpin has a high affinity, sequence-specific interaction with the MS2 phage coat protein. If GFP is fused to the coat protein, the fluorescence is directed to the RNA in living cells. Dictyostelium allows rapid generation of strains with insertions at endogenous loci, so (C)

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Fig. 2. (A) The MS2 protein (grey) binds with high affinity and specificity to the MS2 RNA stem loop. The MS2 protein is fused to green fluorescent protein (GFP) (green circle). (B) Multiple MS2 repeats (24 repeats; 1.3 kb) are integrated into the 5¢ region of the gene of interest by homologous recombination. A drug resistance cassette is used for selection of recombinants. (C) Upon transcription by RNA polymerase (grey oval), the MS2 repeats are incorporated into the newly synthesized RNA and form stem-loops, creating a binding site for the MS2-GFP fusion protein, which is constitutively expressed in cells. (D) Discontinuous transcription of developmentally induced gene in Dictyostelium cells. An example of single cell transcription during development is shown. Arrows indicate the transcription site in Dictyostelium cells. Timing is in minutes. ª 2011 The Authors Development, Growth & Differentiation ª 2011 Japanese Society of Developmental Biologists

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hairpins can be introduced as tandem arrays into genes of interest. The hairpins are incorporated into nascent RNA at the site of transcription. In the recombinant cells, the MS2-protein-GFP fusion is coexpressed. At the site of transcription, the MS2-GFP binds the hairpins, causing an accumulation of GFP at the site of transcription, which can be revealed, using standard laboratory microscopes, as a fluorescent spot. By minimizing photodamage using imaging conditions of low light together with sensitive cameras, the fluorescent RNA spots were observed to appear and disappear at irregular intervals, a behavior we called pulsing (Fig. 2). Pulsing was first observed for the early developmental gene dscA (Chubb et al. 2006b), but has subsequently been observed in Dictyostelium for two housekeeping genes (act5 and scd) (Muramoto et al. 2010) and a second developmental gene, ecmA which can be induced in the lab by the addition of specific signals (Stevense et al. 2010). Discontinuity of transcription is not something apparent in standard ensemble measures of transcription, although it is perhaps not especially surprising. For dscA, the pulse lengths and intervals were highly variable, with shorter pulses (5 min or less) the most common, but longer pulses, of over 20 min also detected (Chubb et al. 2006b). The dscA gene was observed in several thousand cells at different 30 min time windows during early development, which revealed several features of the pulsing phenomenon. First, cells expressing early during capture, showed a greater tendency to express later in the window than a cell that had not previously expressed. This was interpreted as an observation of a ‘‘transcriptional memory’’, which may relate to earlier observations that dsc genes are expressed in only a subset of cells (Clarke & Gomer 1995). Second, there was variability in the number of cells expressing during development- with a strong surge in expressers during the first half hour, dropping over the next few hours, followed by a strong surge in the number of cells expressing just before aggregation (over 40%). Third, the individual cell responses, measured as pulse length, interval, intensity and frequency, showed only small changes over the whole of early development, evidence of a binary transcriptional response, which we return to later. From other data in the literature, it appears discontinuous transcription is a conserved phenomenon, from bacteria to mammals (Raj & van Oudenaarden 2008; Chubb & Liverpool 2010). Using live cell RNA counting, irregular build-up of transcripts was observed in Escherichia coli (Golding et al. 2005). In yeast, flies and mammalian cells, snapshots of transcriptional activity inferred by single molecule FISH

revealed broad distributions of RNA number per cell, implying significant proportions of the population in active and inactive transcriptional states (Raj et al. 2006; Zenklusen et al. 2008; Pare et al. 2009). Put together, these data have been suggested to imply that transcription is a bursting process, where genes exist in two states, one inactive, and one with a certain probability of transcription, with a slow fluctuation between these states. Bursting is not likely to be a property of all genes, as a study in yeast found strong evidence for a more simple transcription mechanism (Zenklusen et al. 2008). The variance for transcript number was low, suggesting a simple probability describing the likelihood of productive transcription. One potential confusion arising from bursting models is that extrinsic noise could distort RNA number without the need for bursting transcription, for example via inaccuracies in segregation of cellular components at cell division (Huh & Paulsson 2011) or heterogeneity in the cell cycle (Brooks 1981). Does the noise arise from transcriptional mechanism or is it simply channeled through it? The question ‘‘what does pulsing mean for the cell?’’ is perhaps not one with a satisfying answer. How could most genes do otherwise? Protein complexes are dynamic rather than static. Transcriptional complexes, potentially unstable, may fall apart, and transcription would cease until a new complex forms. A nucleosome might hinder an initiating or elongating polymerase, causing a block, and a delay in transcription (Voliotis et al. 2008). The appropriate chromatin environment, and transcription factor concentration may only be found when a locus arrives at a particular nuclear location. The signals that regulate the gene are also unlikely to be continuous in many cases. Pulsing may be advantageous, in situations where flexibility is beneficial. The analogy with the thermostat has been made (Larson et al. 2009), whereby pulsing allows finer and more rapid control over transcriptional responses than a single burst. Noise in gene expression, potentially arising from noisy transcription, provides the source of initial variability in many models of cell fate specification (Losick & Desplan 2008). Lateral inhibition is thought to operate by the amplification of initial differences between cells. This type of amplified noise has also been predicted for changes in ES cell fate (Kalmar et al. 2009). As biology evolved out of noise, we must also remember that just because there is some residual noise left in the system, it is not necessarily important. Noisy transcription may be an obstacle to cells as they struggle to exert control over gene expression (Raser & O’shea 2005). During development, cells are exposed to signaling factors at many different

ª 2011 The Authors Development, Growth & Differentiation ª 2011 Japanese Society of Developmental Biologists

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concentrations. In a number of developmental biology models, cells assess signal strength with precision and respond appropriately, within limited timescales. Cells may be expected to adopt different fates with

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