How cyanobacteria pose new problems to old methods: challenges in microarray time series analysis

Improved RNA stability estimation indicates that transcriptional interference is frequent in diverse bacteria

We used stochastic simulations and experimental data from E. coli, K. aerogenes, Synechococcus PCC 7002 and Synechocystis PCC 6803 to provide evidence that transcriptional interference via the collision mechanism is likely a prevalent mechanism for bacterial gene regulation. Rifampicin time-series data can be used to globally monitor and quantify collision between sense and antisense transcription-complexes. Our findings also highlight that transcriptional events, such as differential RNA decay, partial termination, and internal transcriptional start sites often deviate from gene annotations. Consequently, within a single gene annotation, there exist transcript segments with varying half-lives and transcriptional properties. To address these complexities, we introduce 'rifi', an R-package that analyzes transcriptomic data from rifampicin time series. 'rifi' employs a dynamic programming-based segmentation approach to identify individual transcripts, enabling accurate assessment of RNA stability and detection of diverse transcriptional events.

Manipulation of topoisomerase expression inhibits cell division but not growth and reveals a distinctive promoter structure in Synechocystis

In cyanobacteria DNA supercoiling varies over the diurnal cycle and is integrated with temporal programs of transcription and replication. We manipulated DNA supercoiling in Synechocystis sp. PCC 6803 by CRISPRi-based knockdown of gyrase subunits and overexpression of topoisomerase I (TopoI). Cell division was blocked but cell growth continued in all strains. The small endogenous plasmids were only transiently relaxed, then became strongly supercoiled in the TopoI overexpression strain. Transcript abundances showed a pronounced 5'/3' gradient along transcription units, incl. the rRNA genes, in the gyrase knockdown strains. These observations are consistent with the basic tenets of the homeostasis and twin-domain models of supercoiling in bacteria. TopoI induction initially led to downregulation of G+C-rich and upregulation of A+T-rich genes. The transcriptional response quickly bifurcated into six groups which overlap with diurnally co-expressed gene groups. Each group shows distinct deviations from a common core promoter structure, where helically phased A-tracts are in phase with the transcription start site. Together, our data show that major co-expression groups (regulons) in Synechocystis all respond differentially to DNA supercoiling, and suggest to re-evaluate the long-standing question of the role of A-tracts in bacterial promoters.

Model-Based Clustering With Data Correction For Removing Artifacts In Gene Expression Data

The NIH Library of Integrated Network-based Cellular Signatures (LINCS) contains gene expression data from over a million experiments, using Luminex Bead technology. Only 500 colors are used to measure the expression levels of the 1,000 landmark genes measured, and the data for the resulting pairs of genes are deconvolved. The raw data are sometimes inadequate for reliable deconvolution, leading to artifacts in the final processed data. These include the expression levels of paired genes being flipped or given the same value, and clusters of values that are not at the true expression level. We propose a new method called model-based clustering with data correction (MCDC) that is able to identify and correct these three kinds of artifacts simultaneously. We show that MCDC improves the resulting gene expression data in terms of agreement with external baselines, as well as improving results from subsequent analysis.

Similarity-Based Segmentation of Multi-Dimensional Signals

The segmentation of time series and genomic data is a common problem in computational biology. With increasingly complex measurement procedures individual data points are often not just numbers or simple vectors in which all components are of the same kind. Analysis methods that capitalize on slopes in a single real-valued data track or that make explicit use of the vectorial nature of the data are not applicable in such scenaria. We develop here a framework for segmentation in arbitrary data domains that only requires a minimal notion of similarity. Using unsupervised clustering of (a sample of) the input yields an approximate segmentation algorithm that is efficient enough for genome-wide applications. As a showcase application we segment a time-series of transcriptome sequencing data from budding yeast, in high temporal resolution over ca. 2.5 cycles of the short-period respiratory oscillation. The algorithm is used with a similarity measure focussing on periodic expression profiles across the metabolic cycle rather than coverage per time point.

Minimal tool set for a prokaryotic circadian clock

BACKGROUND

Circadian clocks are found in organisms of almost all domains including photosynthetic Cyanobacteria, whereby large diversity exists within the protein components involved. In the model cyanobacterium Synechococcus elongatus PCC 7942 circadian rhythms are driven by a unique KaiABC protein clock, which is embedded in a network of input and output factors. Homologous proteins to the KaiABC clock have been observed in Bacteria and Archaea, where evidence for circadian behavior in these domains is accumulating. However, interaction and function of non-cyanobacterial Kai-proteins as well as homologous input and output components remain mainly unclear.

RESULTS

Using a universal BLAST analyses, we identified putative KaiC-based timing systems in organisms outside as well as variations within Cyanobacteria. A systematic analyses of publicly available microarray data elucidated interesting variations in circadian gene expression between different cyanobacterial strains, which might be correlated to the diversity of genome encoded clock components. Based on statistical analyses of co-occurrences of the clock components homologous to Synechococcus elongatus PCC 7942, we propose putative networks of reduced and fully functional clock systems. Further, we studied KaiC sequence conservation to determine functionally important regions of diverged KaiC homologs. Biochemical characterization of exemplary cyanobacterial KaiC proteins as well as homologs from two thermophilic Archaea demonstrated that kinase activity is always present. However, a KaiA-mediated phosphorylation is only detectable in KaiC1 orthologs.

CONCLUSION

Our analysis of 11,264 genomes clearly demonstrates that components of the Synechococcus elongatus PCC 7942 circadian clock are present in Bacteria and Archaea. However, all components are less abundant in other organisms than Cyanobacteria and KaiA, Pex, LdpA, and CdpA are only present in the latter. Thus, only reduced KaiBC-based or even simpler, solely KaiC-based timing systems might exist outside of the cyanobacterial phylum, which might be capable of driving diurnal oscillations.

Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth

Cyanobacteria are an integral part of Earth's biogeochemical cycles and a promising resource for the synthesis of renewable bioproducts from atmospheric CO₂ Growth and metabolism of cyanobacteria are inherently tied to the diurnal rhythm of light availability. As yet, however, insight into the stoichiometric and energetic constraints of cyanobacterial diurnal growth is limited. Here, we develop a computational framework to investigate the optimal allocation of cellular resources during diurnal phototrophic growth using a genome-scale metabolic reconstruction of the cyanobacterium Synechococcus elongatus PCC 7942. We formulate phototrophic growth as an autocatalytic process and solve the resulting time-dependent resource allocation problem using constraint-based analysis. Based on a narrow and well-defined set of parameters, our approach results in an ab initio prediction of growth properties over a full diurnal cycle. The computational model allows us to study the optimality of metabolite partitioning during diurnal growth. The cyclic pattern of glycogen accumulation, an emergent property of the model, has timing characteristics that are in qualitative agreement with experimental findings. The approach presented here provides insight into the time-dependent resource allocation problem of phototrophic diurnal growth and may serve as a general framework to assess the optimality of metabolic strategies that evolved in phototrophic organisms under diurnal conditions.

Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach

Oxygenic photosynthesis dominates global primary productivity ever since its evolution more than three billion years ago. While many aspects of phototrophic growth are well understood, it remains a considerable challenge to elucidate the manifold dependencies and interconnections between the diverse cellular processes that together facilitate the synthesis of new cells. Phototrophic growth involves the coordinated action of several layers of cellular functioning, ranging from the photosynthetic light reactions and the electron transport chain, to carbon-concentrating mechanisms and the assimilation of inorganic carbon. It requires the synthesis of new building blocks by cellular metabolism, protection against excessive light, as well as diurnal regulation by a circadian clock and the orchestration of gene expression and cell division. Computational modeling allows us to quantitatively describe these cellular functions and processes relevant for phototrophic growth. As yet, however, computational models are mostly confined to the inner workings of individual cellular processes, rather than describing the manifold interactions between them in the context of a living cell. Using cyanobacteria as model organisms, this contribution seeks to summarize existing computational models that are relevant to describe phototrophic growth and seeks to outline their interactions and dependencies. Our ultimate aim is to understand cellular functioning and growth as the outcome of a coordinated operation of diverse yet interconnected cellular processes.

Minimal Tool Set for a Prokaryotic Circadian Clock.. [DOI: 10.1101/075291]

Background

Circadian clocks are found in organisms of almost all domains including photosynthetic Cyanobacteria, whereby large diversity exists within the protein components involved. In the model cyanobacteriumSynechococcus elongatusPCC 7942 circadian rhythms are driven by a unique KaiABC protein clock, which is embedded in a network of input and output factors. Homologous proteins to the KaiABC clock have been observed in Bacteria and Archaea, where evidence for circadian behavior in these domains is accumulating. However, interaction and function of non-cyanobacterial Kai-proteins as well as homologous input and output components remain mainly unclear.

Results

Using a universal BLAST analyses, we identified putative KaiC-based timing systems in organisms outside as well as variations within Cyanobacteria. A systematic analyses of publicly available microarray data elucidated interesting variations in circadian gene expression between different cyanobacterial strains, which might be correlated to the diversity of genome encoded clock components. Based on statistical analyses of co-occurrences of the clock components homologous toSynechococcus elongatusPCC 7942, we propose putative networks of reduced and fully functional clock systems. Further, we studied KaiC sequence conservation to determine functionally important regions of diverged KaiC homologs. Biochemical characterization of exemplary cyanobacterial KaiC proteins as well as homologs from two thermophilic Archaea demonstrated that kinase activity is always present. However, a KaiA-mediated phosphorylation is only detectable in KaiC1 orthologs.

Conclusion

Our analysis of 11,264 genomes clearly demonstrates that components of theSynechococcus elongatusPCC 7942 circadian clock are present in Bacteria and Archaea. However, all components are less abundant in other organisms than Cyanobacteria and KaiA, Pex, LdpA, and CdpA are only present in the latter. Thus, only reduced KaiBC-based or even simpler, solely KaiC-based timing systems might exist outside of the cyanobacterial phylum, which might be capable of driving diurnal oscillations.

Elucidating temporal resource allocation and diurnal dynamics in phototrophic metabolism using conditional FBA

The computational analysis of phototrophic growth using constraint-based optimization requires to go beyond current time-invariant implementations of flux-balance analysis (FBA). Phototrophic organisms, such as cyanobacteria, rely on harvesting the sun’s energy for the conversion of atmospheric CO2 into organic carbon, hence their metabolism follows a strongly diurnal lifestyle. We describe the growth of cyanobacteria in a periodic environment using a new method called conditional FBA. Our approach enables us to incorporate the temporal organization and conditional dependencies into a constraint-based description of phototrophic metabolism. Specifically, we take into account that cellular processes require resources that are themselves products of metabolism. Phototrophic growth can therefore be formulated as a time-dependent linear optimization problem, such that optimal growth requires a differential allocation of resources during different times of the day. Conditional FBA then allows us to simulate phototrophic growth of an average cell in an environment with varying light intensity, resulting in dynamic time-courses for all involved reaction fluxes, as well as changes in biomass composition over a diurnal cycle. Our results are in good agreement with several known facts about the temporal organization of phototrophic growth and have implications for further analysis of resource allocation problems in phototrophic metabolism.

Determination of Temporal Order among the Components of an Oscillatory System

Oscillatory systems in biology are tightly regulated process where the individual components (e.g. genes) express in an orderly manner by virtue of their functions. The temporal order among the components of an oscillatory system may potentially be disrupted for various reasons (e.g. environmental factors). As a result some components of the system may go out of order or even cease to participate in the oscillatory process. In this article, we develop a novel framework to evaluate whether the temporal order is unchanged in different populations (or experimental conditions). We also develop methodology to estimate the order among the components with a suitable notion of “confidence.” Using publicly available data on S. pombe, S. cerevisiae and Homo sapiens we discover that the temporal order among the genes cdc18; mik1; hhf1; hta2; fkh2 and klp5 is evolutionarily conserved from yeast to humans.

Coupling of Cellular Processes and Their Coordinated Oscillations under Continuous Light in Cyanothece sp. ATCC 51142, a Diazotrophic Unicellular Cyanobacterium

Unicellular diazotrophic cyanobacteria such as Cyanothece sp. ATCC 51142 (henceforth Cyanothece), temporally separate the oxygen sensitive nitrogen fixation from oxygen evolving photosynthesis not only under diurnal cycles (LD) but also in continuous light (LL). However, recent reports demonstrate that the oscillations in LL occur with a shorter cycle time of ~11 h. We find that indeed, majority of the genes oscillate in LL with this cycle time. Genes that are upregulated at a particular time of day under diurnal cycle also get upregulated at an equivalent metabolic phase under LL suggesting tight coupling of various cellular events with each other and with the cell's metabolic status. A number of metabolic processes get upregulated in a coordinated fashion during the respiratory phase under LL including glycogen degradation, glycolysis, oxidative pentose phosphate pathway, and tricarboxylic acid cycle. These precede nitrogen fixation apparently to ensure sufficient energy and anoxic environment needed for the nitrogenase enzyme. Photosynthetic phase sees upregulation of photosystem II, carbonate transport, carbon concentrating mechanism, RuBisCO, glycogen synthesis and light harvesting antenna pigment biosynthesis. In Synechococcus elongates PCC 7942, a non-nitrogen fixing cyanobacteria, expression of a relatively smaller fraction of genes oscillates under LL condition with the major periodicity being 24 h. In contrast, the entire cellular machinery of Cyanothece orchestrates coordinated oscillation in anticipation of the ensuing metabolic phase in both LD and LL. These results may have important implications in understanding the timing of various cellular events and in engineering cyanobacteria for biofuel production.

Cyanobacterial Oxygenic Photosynthesis is Protected by Flavodiiron Proteins

Flavodiiron proteins (FDPs, also called flavoproteins, Flvs) are modular enzymes widely present in Bacteria and Archaea. The evolution of cyanobacteria and oxygenic photosynthesis occurred in concert with the modulation of typical bacterial FDPs. Present cyanobacterial FDPs are composed of three domains, the β-lactamase-like, flavodoxin-like and flavin-reductase like domains. Cyanobacterial FDPs function as hetero- and homodimers and are involved in the regulation of photosynthetic electron transport. Whilst Flv2 and Flv4 proteins are limited to specific cyanobacterial species (β-cyanobacteria) and function in photoprotection of Photosystem II, Flv1 and Flv3 proteins, functioning in the "Mehler-like" reaction and safeguarding Photosystem I under fluctuating light conditions, occur in nearly all cyanobacteria and additionally in green algae, mosses and lycophytes. Filamentous cyanobacteria have additional FDPs in heterocyst cells, ensuring a microaerobic environment for the function of the nitrogenase enzyme under the light. Here, the evolution, occurrence and functional mechanisms of various FDPs in oxygenic photosynthetic organisms are discussed.

The ω subunit of RNA polymerase is essential for thermal acclimation of the cyanobacterium Synechocystis sp. PCC 6803

The rpoZ gene encodes the small ω subunit of RNA polymerase. A ΔrpoZ strain of the cyanobacterium Synechocystis sp. PCC 6803 grew well in standard conditions (constant illumination at 40 µmol photons m⁻² s⁻¹; 32°C; ambient CO₂) but was heat sensitive and died at 40°C. In the control strain, 71 genes were at least two-fold up-regulated and 91 genes down-regulated after a 24-h treatment at 40°C, while in ΔrpoZ 394 genes responded to heat. Only 62 of these heat-responsive genes were similarly regulated in both strains, and 80% of heat-responsive genes were unique for ΔrpoZ. The RNA polymerase core and the primary σ factor SigA were down-regulated in the control strain at 40°C but not in ΔrpoZ. In accordance with reduced RNA polymerase content, the total RNA content of mild-heat-stress-treated cells was lower in the control strain than in ΔrpoZ. Light-saturated photosynthetic activity decreased more in ΔrpoZ than in the control strain upon mild heat stress. The amounts of photosystem II and rubisco decreased at 40°C in both strains while PSI and the phycobilisome antenna protein allophycocyanin remained at the same level as in standard conditions. The phycobilisome rod proteins, phycocyanins, diminished during the heat treatment in ΔrpoZ but not in the control strain, and the nblA1 and nblA2 genes (encode NblA proteins required for phycobilisome degradation) were up-regulated only in ΔrpoZ. Our results show that the ω subunit of RNAP is essential in heat stress because it is required for heat acclimation of diverse cellular processes.

Time resolved DNA occupancy dynamics during the respiratory oscillation uncover a global reset point in the yeast growth program

The structural dynamics of chromatin have been implicated in the regulation of fundamental eukaryotic processes, such as DNA transcription, replication and repair. Although previous studies have revealed that the chromatin landscape, nucleosome remodeling and histone modification events are intimately tied into cellular energetics and redox state, few studies undertake defined time-resolved measurements of these state variables. Here, we use metabolically synchronous, continuously-grown yeast cultures to measure DNA occupancy and track global patterns with respect to the metabolic state of the culture. Combined with transcriptome analyses and ChIP-qPCR experiments, these paint an intriguing picture where genome-wide nucleosome focusing occurs during the recovery of energy charge, followed by clearance of the promoter regions and global transcriptional slow-down, thus indicating a nucleosome-mediated “reset point” for the cycle. The reset begins at the end of the catabolic and stress-response transcriptional programs and ends prior to the start of the anabolic and cell-growth transcriptional program, and the histones on genes from both the catabolic and anabolic superclusters are deacetylated.

Quantifying periodicity in omics data

Oscillations play a significant role in biological systems, with many examples in the fast, ultradian, circadian, circalunar, and yearly time domains. However, determining periodicity in such data can be problematic. There are a number of computational methods to identify the periodic components in large datasets, such as signal-to-noise based Fourier decomposition, Fisher's g-test and autocorrelation. However, the available methods assume a sinusoidal model and do not attempt to quantify the waveform shape and the presence of multiple periodicities, which provide vital clues in determining the underlying dynamics. Here, we developed a Fourier based measure that generates a de-noised waveform from multiple significant frequencies. This waveform is then correlated with the raw data from the respiratory oscillation found in yeast, to provide oscillation statistics including waveform metrics and multi-periods. The method is compared and contrasted to commonly used statistics. Moreover, we show the utility of the program in the analysis of noisy datasets and other high-throughput analyses, such as metabolomics and flow cytometry, respectively.

The structural code of cyanobacterial genomes

A periodic bias in nucleotide frequency with a period of about 11 bp is characteristic for bacterial genomes. This signal is commonly interpreted to relate to the helical pitch of negatively supercoiled DNA. Functions in supercoiling-dependent RNA transcription or as a 'structural code' for DNA packaging have been suggested. Cyanobacterial genomes showed especially strong periodic signals and, on the other hand, DNA supercoiling and supercoiling-dependent transcription are highly dynamic and underlie circadian rhythms of these phototrophic bacteria. Focusing on this phylum and dinucleotides, we find that a minimal motif of AT-tracts (AT2) yields the strongest signal. Strong genome-wide periodicity is ancestral to a clade of unicellular and polyploid species but lost upon morphological transitions into two baeocyte-forming and a symbiotic species. The signal is intermediate in heterocystous species and weak in monoploid picocyanobacteria. A pronounced 'structural code' may support efficient nucleoid condensation and segregation in polyploid cells. The major source of the AT2 signal are protein-coding regions, where it is encoded preferentially in the first and third codon positions. The signal shows only few relations to supercoiling-dependent and diurnal RNA transcription in Synechocystis sp. PCC 6803. Strong and specific signals in two distinct transposons suggest roles in transposase transcription and transpososome formation.

Daily expression pattern of protein-encoding genes and small noncoding RNAs in synechocystis sp. strain PCC 6803

Many organisms harbor circadian clocks with periods close to 24 h. These cellular clocks allow organisms to anticipate the environmental cycles of day and night by synchronizing circadian rhythms with the rising and setting of the sun. These rhythms originate from the oscillator components of circadian clocks and control global gene expression and various cellular processes. The oscillator of photosynthetic cyanobacteria is composed of three proteins, KaiA, KaiB, and KaiC, linked to a complex regulatory network. Synechocystis sp. strain PCC 6803 possesses the standard cyanobacterial kaiABC gene cluster plus multiple kaiB and kaiC gene copies and antisense RNAs for almost every kai transcript. However, there is no clear evidence of circadian rhythms in Synechocystis sp. PCC 6803 under various experimental conditions. It is also still unknown if and to what extent the multiple kai gene copies and kai antisense RNAs affect circadian timing. Moreover, a large number of small noncoding RNAs whose accumulation dynamics over time have not yet been monitored are known for Synechocystis sp. PCC 6803. Here we performed a 48-h time series transcriptome analysis of Synechocystis sp. PCC 6803, taking into account periodic light-dark phases, continuous light, and continuous darkness. We found that expression of functionally related genes occurred in different phases of day and night. Moreover, we found day-peaking and night-peaking transcripts among the small RNAs; in particular, the amounts of kai antisense RNAs correlated or anticorrelated with those of their respective kai target mRNAs, pointing toward the regulatory relevance of these antisense RNAs. Surprisingly, we observed that the amounts of 16S and 23S rRNAs in this cyanobacterium fluctuated in light-dark periods, showing maximum accumulation in the dark phase. Importantly, the amounts of all transcripts, including small noncoding RNAs, did not show any rhythm under continuous light or darkness, indicating the absence of circadian rhythms in Synechocystis.

Flux balance analysis of cyanobacterial metabolism: the metabolic network of Synechocystis sp. PCC 6803

Cyanobacteria are versatile unicellular phototrophic microorganisms that are highly abundant in many environments. Owing to their capability to utilize solar energy and atmospheric carbon dioxide for growth, cyanobacteria are increasingly recognized as a prolific resource for the synthesis of valuable chemicals and various biofuels. To fully harness the metabolic capabilities of cyanobacteria necessitates an in-depth understanding of the metabolic interconversions taking place during phototrophic growth, as provided by genome-scale reconstructions of microbial organisms. Here we present an extended reconstruction and analysis of the metabolic network of the unicellular cyanobacterium Synechocystis sp. PCC 6803. Building upon several recent reconstructions of cyanobacterial metabolism, unclear reaction steps are experimentally validated and the functional consequences of unknown or dissenting pathway topologies are discussed. The updated model integrates novel results with respect to the cyanobacterial TCA cycle, an alleged glyoxylate shunt, and the role of photorespiration in cellular growth. Going beyond conventional flux-balance analysis, we extend the computational analysis to diurnal light/dark cycles of cyanobacterial metabolism.