Toward a systems-level understanding of gene regulatory, protein interaction, and metabolic networks in cyanobacteria

Gene Regulatory Identification Based on the Novel Hybrid Time-Delayed Method

Gene regulatory network (GRN) inference with biology data is a difficult and serious issue in the field of system biology. In order to detect the direct associations of GRN more accurately, a novel two-step GRN inference technique based on the time-delayed correlation coefficient (TDCC) and time-delayed complex-valued S-system model (TDCVSS) is proposed. First, a TDCC algorithm is utilized to construct an initial network. Second, a TDCVSS model is utilized to prune the network topology in order to delete false-positive regulatory relationships for each target gene. The complex-valued restricted additive tree and complex-valued differential evolution are proposed to approximate the optimal TDCVSS model. Finally, the overall network could be inferred by integrating the regulations of all target genes. Two real gene expression datasets from E. coli and S. cerevisiae gene networks are utilized to evaluate the performances of our proposed two-step GRN inference algorithm. The results demonstrated that the proposed algorithm could infer GRN more correct than classical methods and time-delayed methods.

Atlas: automatic modeling of regulation of bacterial gene expression and metabolism using rule-based languages

MOTIVATION

Cells are complex systems composed of hundreds of genes whose products interact to produce elaborated behaviors. To control such behaviors, cells rely on transcription factors to regulate gene expression, and gene regulatory networks (GRNs) are employed to describe and understand such behavior. However, GRNs are static models, and dynamic models are difficult to obtain due to their size, complexity, stochastic dynamics and interactions with other cell processes.

RESULTS

We developed Atlas, a Python software that converts genome graphs and gene regulatory, interaction and metabolic networks into dynamic models. The software employs these biological networks to write rule-based models for the PySB framework. The underlying method is a divide-and-conquer strategy to obtain sub-models and combine them later into an ensemble model. To exemplify the utility of Atlas, we used networks of varying size and complexity of Escherichia coli and evaluated in silico modifications, such as gene knockouts and the insertion of promoters and terminators. Moreover, the methodology could be applied to the dynamic modeling of natural and synthetic networks of any bacteria.

AVAILABILITY AND IMPLEMENTATION

Code, models and tutorials are available online (https://github.com/networkbiolab/atlas).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genetic, Genomics, and Responses to Stresses in Cyanobacteria: Biotechnological Implications

Cyanobacteria are widely-diverse, environmentally crucial photosynthetic prokaryotes of great interests for basic and applied science. Work to date has focused mostly on the three non-nitrogen fixing unicellular species Synechocystis PCC 6803, Synechococcus PCC 7942, and Synechococcus PCC 7002, which have been selected for their genetic and physiological interests summarized in this review. Extensive "omics" data sets have been generated, and genome-scale models (GSM) have been developed for the rational engineering of these cyanobacteria for biotechnological purposes. We presently discuss what should be done to improve our understanding of the genotype-phenotype relationships of these models and generate robust and predictive models of their metabolism. Furthermore, we also emphasize that because Synechocystis PCC 6803, Synechococcus PCC 7942, and Synechococcus PCC 7002 represent only a limited part of the wide biodiversity of cyanobacteria, other species distantly related to these three models, should be studied. Finally, we highlight the need to strengthen the communication between academic researchers, who know well cyanobacteria and can engineer them for biotechnological purposes, but have a limited access to large photobioreactors, and industrial partners who attempt to use natural or engineered cyanobacteria to produce interesting chemicals at reasonable costs, but may lack knowledge on cyanobacterial physiology and metabolism.

Understanding the preferences of water users in a context of cyanobacterial blooms in Quebec

Algal blooms, whether they are harmful or more akin to a nuisance, do pose negative impacts on human well-being. In the province of Quebec, excessive phosphorus that contributes to the problem of cyanobacterial blooms comes mainly from non-point sources. Limited regulation on the management of this nutrient leads to its strong accumulation in soils and, combined to climate change effects, contributes to increasing the magnitude of the effects of algal blooms on humans and the environment. The presence of cyanobacteria in water has impacts on its colour, texture and odour, in addition to posing threats to the health of recreationists, as some cyanobacteria are known to release toxins during blooms. This research focuses on studying the impacts of algal bloom events on recreationists and people living close to affected waterbodies. More specifically, we explore the preferences of individuals for different ecosystem services (ES), mainly cultural ES, provided by waterbodies (i.e., recreational activities, aesthetic aspects, and ecological health). We also estimate the average willingness to pay, financed through an increase in municipal taxation, for mechanisms that would allow the resolution of this issue. To achieve these objectives, we use a choice experiment approach, enclosed in a questionnaire that was carried out in person to 252 people. Conditional logit with and without interactions, and a random parameter logit (mixed logit) are alternatively used. Results show that individuals value first their ability to perform recreational activities, followed by the ecological health of waterbodies, and the aesthetic aspects (i.e., odour and visual aspects). Interestingly, the fact that people reported taking part in fishing activities influenced the way they prioritized ES in the choice modelling exercises. Based on the most robust model, we estimate the average willingness to pay at CA$353/household per year to fund a suite of solutions aimed at improving overall water quality.

Proteomic De-Regulation in Cyanobacteria in Response to Abiotic Stresses

Cyanobacteria are oxygenic photoautotrophs, exhibiting a cosmopolitan distribution in almost all possible environments and are significantly responsible for half of the global net primary productivity. They are well adapted to the diverse environments including harsh conditions by evolving a range of fascinating repertoires of unique biomolecules and secondary metabolites to support their growth and survival. These phototrophs are proved as excellent models for unraveling the mysteries of basic biochemical and physiological processes taking place in higher plants. Several known species of cyanobacteria have tremendous biotechnological applications in diverse fields such as biofuels, biopolymers, secondary metabolites and much more. Due to their potential biotechnological and commercial applications in various fields, there is an imperative need to engineer robust cyanobacteria in such a way that they can tolerate and acclimatize to ever-changing environmental conditions. Adaptations to stress are mainly governed by a precise gene regulation pathways resulting in the expression of novel protein/enzymes and metabolites. Despite the demand, till date few proteins/enzymes have been identified which play a potential role in improving tolerance against abiotic stresses. Therefore, it is utmost important to study environmental stress responses related to post-genomic investigations, including proteomic changes employing advanced proteomics, synthetic and structural biology workflows. In this respect, the study of stress proteomics offers exclusive advantages to scientists working on these aspects. Advancements on these fields could be helpful in dissecting, characterization and manipulation of physiological and metabolic systems of cyanobacteria to understand the stress induced proteomic responses. Till date, it remains ambiguous how cyanobacteria perceive changes in the ambient environment that lead to the stress-induced proteins thus metabolic deregulation. This review briefly describes the current major findings in the fields of proteome research on the cyanobacteria under various abiotic stresses. These findings may improve and advance the information on the role of different class of proteins associated with the mechanism(s) of stress mitigation in cyanobacteria under harsh environmental conditions.

Phosphatidylglycerol is implicated in divisome formation and metabolic processes of cyanobacteria

Phosphatidylglycerol is an essential phospholipid for photosynthesis and other cellular processes. We investigated the role of phosphatidylglycerol in cell division and metabolism in a phophatidylglycerol-auxotrophic strain of Synechococcus PCC7942. Here we show that phosphatidylglycerol is essential for the photosynthetic electron transfer and for the oligomerisation of the photosynthetic complexes, notably, we revealed that this lipid is important for non-linear electron transport. Furthermore, we demonstrate that phosphatidylglycerol starvation elevated the expressions of proteins of nitrogen and carbon metabolism. Moreover, we show that phosphatidylglycerol-deficient cells changed the morphology, became elongated, the FtsZ ring did not assemble correctly, and subsequently the division was hindered. However, supplementation with phosphatidylglycerol restored the ring-like structure at the mid-cell region and the normal cell size, demonstrating the phosphatidylglycerol is needed for normal septum formation. Taken together, central roles of phosphatidylglycerol were revealed; it is implicated in the photosynthetic activity, the metabolism and the fission of bacteria.

Photosynthetic functions of Synechococcus in the ocean microbiomes of diverse salinity and seasons

Synechococcus is an important photosynthetic picoplankton in the temperate to tropical oceans. As a photosynthetic bacterium, Synechococcus has an efficient mechanism to adapt to the changes in salinity and light intensity. The analysis of the distributions and functions of such microorganisms in the ever changing river mouth environment, where freshwater and seawater mix, should help better understand their roles in the ecosystem. Toward this objective, we have collected and sequenced the ocean microbiome in the river mouth of Kwangyang Bay, Korea, as a function of salinity and temperature. In conjunction with comparative genomics approaches using the sequenced genomes of a wide phylogeny of Synechococcus, the ocean microbiome was analyzed in terms of their composition and clade-specific functions. The results showed significant differences in the compositions of Synechococcus sampled in different seasons. The photosynthetic functions in such enhanced Synechococcus strains were also observed in the microbiomes in summer, which is significantly different from those in other seasons.

The primary transcriptome of the fast-growing cyanobacterium Synechococcus elongatus UTEX 2973

BACKGROUND

Cyanobacteria have shown promising potential for the production of various biofuels and chemical feedstocks. Synechococcus elongatus UTEX 2973 is a fast-growing strain with pronounced tolerance to high temperatures and illumination. Hence, this strain appears to be ideal for the development of photosynthetic biotechnology. However, molecular insights on how this strain can rapidly accumulate biomass and carbohydrates under high-light and high-temperature conditions are lacking.

RESULTS

Differential RNA-Sequencing (dRNA-Seq) enabled the genome-wide identification of 4808 transcription start sites (TSSs) in S. elongatus UTEX 2973 using a background reduction algorithm. High light promoted the transcription of genes associated with central metabolic pathways, whereas the highly induced small RNA (sRNA) PsrR1 likely contributed to the repression of phycobilisome genes and the accelerated glycogen accumulation rates measured under this condition. Darkness caused transcriptome remodeling with a decline in the expression of genes for carbon fixation and other major metabolic pathways and an increase in the expression of genes for glycogen catabolism and Calvin cycle inhibitor CP12. Two of the identified TSSs drive the transcription of highly abundant sRNAs in darkness. One of them is widely conserved throughout the cyanobacterial phylum. Its gene is fused to a protein-coding gene in some species, illustrating the evolutionary origin of sRNAs from an mRNA 3'-end.

CONCLUSIONS

Our comprehensive set of genome-wide mapped TSSs, sRNAs and promoter activities will be valuable for projects requiring precise information about the control of transcription aimed at metabolic engineering and the elucidation of stress acclimation mechanisms in this promising strain.

Algal Cell Factories: Approaches, Applications, and Potentials

With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive “cell factories”: the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO₂, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.

Diurnal Regulation of Cellular Processes in the Cyanobacterium Synechocystis sp. Strain PCC 6803: Insights from Transcriptomic, Fluxomic, and Physiological Analyses

Synechocystis sp. strain PCC 6803 is the most widely studied model cyanobacterium, with a well-developed omics level knowledgebase. Like the lifestyles of other cyanobacteria, that of Synechocystis PCC 6803 is tuned to diurnal changes in light intensity. In this study, we analyzed the expression patterns of all of the genes of this cyanobacterium over two consecutive diurnal periods. Using stringent criteria, we determined that the transcript levels of nearly 40% of the genes in Synechocystis PCC 6803 show robust diurnal oscillating behavior, with a majority of the transcripts being upregulated during the early light period. Such transcripts corresponded to a wide array of cellular processes, such as light harvesting, photosynthetic light and dark reactions, and central carbon metabolism. In contrast, transcripts of membrane transporters for transition metals involved in the photosynthetic electron transport chain (e.g., iron, manganese, and copper) were significantly upregulated during the late dark period. Thus, the pattern of global gene expression led to the development of two distinct transcriptional networks of coregulated oscillatory genes. These networks help describe how Synechocystis PCC 6803 regulates its metabolism toward the end of the dark period in anticipation of efficient photosynthesis during the early light period. Furthermore, in silico flux prediction of important cellular processes and experimental measurements of cellular ATP, NADP(H), and glycogen levels showed how this diurnal behavior influences its metabolic characteristics. In particular, NADPH/NADP(+) showed a strong correlation with the majority of the genes whose expression peaks in the light. We conclude that this ratio is a key endogenous determinant of the diurnal behavior of this cyanobacterium.

IMPORTANCE

Cyanobacteria are photosynthetic microbes that use energy from sunlight and CO2 as feedstock. Certain cyanobacterial strains are amenable to facile genetic manipulation, thus enabling synthetic biology and metabolic engineering applications. Such strains are being developed as a chassis for the sustainable production of food, feed, and fuel. To this end, a holistic knowledge of cyanobacterial physiology and its correlation with gene expression patterns under the diurnal cycle is warranted. In this report, a genomewide transcriptional analysis of Synechocystis PCC 6803, the most widely studied model cyanobacterium, sheds light on the global coordination of cellular processes during diurnal periods. Furthermore, we found that, in addition to light, the redox level of NADP(H) is an important endogenous regulator of diurnal entrainment of Synechocystis PCC 6803.

The Transcriptional Landscape of the Photosynthetic Model Cyanobacterium Synechocystis sp. PCC6803

Cyanobacteria exhibit a great capacity to adapt to different environmental conditions through changes in gene expression. Although this plasticity has been extensively studied in the model cyanobacterium Synechocystis sp. PCC 6803, a detailed analysis of the coordinated transcriptional adaption across varying conditions is lacking. Here, we report a meta-analysis of 756 individual microarray measurements conducted in 37 independent studies-the most comprehensive study of the Synechocystis transcriptome to date. Using stringent statistical evaluation, we characterized the coordinated adaptation of Synechocystis' gene expression on systems level. Evaluation of the data revealed that the photosynthetic apparatus is subjected to greater changes in expression than other cellular components. Nevertheless, network analyses indicated a significant degree of transcriptional coordination of photosynthesis and various metabolic processes, and revealed the tight co-regulation of components of photosystems I, II and phycobilisomes. Detailed inspection of the integrated data led to the discovery a variety of regulatory patterns and novel putative photosynthetic genes. Intriguingly, global clustering analyses suggested contrasting transcriptional response of metabolic and regulatory genes stress to conditions. The integrated Synechocystis transcriptome can be accessed and interactively analyzed via the CyanoEXpress website (http://cyanoexpress.sysbiolab.eu).

Cyanobacterial KnowledgeBase (CKB), a Compendium of Cyanobacterial Genomes and Proteomes

Cyanobacterial KnowledgeBase (CKB) is a free access database that contains the genomic and proteomic information of 74 fully sequenced cyanobacterial genomes belonging to seven orders. The database also contains tools for sequence analysis. The Species report and the gene report provide details about each species and gene (including sequence features and gene ontology annotations) respectively. The database also includes cyanoBLAST, an advanced tool that facilitates comparative analysis, among cyanobacterial genomes and genomes of E. coli (prokaryote) and Arabidopsis (eukaryote). The database is developed and maintained by the Sub-Distributed Informatics Centre (sponsored by the Department of Biotechnology, Govt. of India) of the National Facility for Marine Cyanobacteria, a facility dedicated to marine cyanobacterial research. CKB is freely available at http://nfmc.res.in/ckb/index.html.

Integrated in silico Analyses of Regulatory and Metabolic Networks of Synechococcus sp. PCC 7002 Reveal Relationships between Gene Centrality and Essentiality

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as "topologically important." Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termed as "functionally important" genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.

Cyanobacteria as photosynthetic biocatalysts: a systems biology perspective

A review of cyanobacterial biocatalysts highlighting their metabolic features that argues for the need for systems-level metabolic engineering.