Cross-species transcriptional network analysis reveals conservation and variation in response to metal stress in cyanobacteria

LAFEM: A Scoring Model to Evaluate Functional Landscape of Lysine Acetylome

Protein lysine acetylation is a critical post-translational modification involved in a wide range of biological processes. To date, about 20,000 acetylation sites of Homo sapiens were identified through mass spectrometry-based proteomic technology, but more than 95% of them have unclear functional annotations because of the lack of existing prioritization strategy to assess the functional importance of the acetylation sites on large scale. Hence, we established a lysine acetylation functional evaluating model (LAFEM) by considering eight critical features surrounding lysine acetylation site to high-throughput estimate the functional importance of given acetylation sites. This was achieved by selecting one of the random forest models with the best performance in 10-fold cross-validation on undersampled training dataset. The global analysis demonstrated that the molecular environment of acetylation sites with high acetylation functional scores (AFSs) mainly had the features of larger solvent-accessible surface area, stronger hydrogen bonding-donating abilities, near motif and domain, higher homology, and disordered degree. Importantly, LAFEM performed well in validation dataset and acetylome, showing good accuracy to screen out fitness directly relevant acetylation sites and assisting to explain the core reason for the difference between biological models from the perspective of acetylome. We further used cellular experiments to confirm that, in nuclear casein kinase and cyclin-dependent kinase substrate 1, acetyl-K35 with higher AFS was more important than acetyl-K9 with lower AFS in the proliferation of A549 cells. LAFEM provides a prioritization strategy to large scale discover the fitness directly relevant acetylation sites, which constitutes an unprecedented resource for better understanding of functional acetylome.

Environment-driven shifts in inter-individual variation and phenotypic integration within subnetworks of the mussel transcriptome and proteome

The environment can alter the magnitude of phenotypic variation among individuals, potentially influencing evolutionary trajectories. However, environmental influences on variation are complex and remain understudied. Populations in heterogeneous environments might exhibit more variation, the amount of variation could differ between benign and stressful conditions, and/or variation might manifest in different ways among stages of the gene‐to‐protein expression cascade or among physiological functions. Here, we explore these three issues by quantifying patterns of inter‐individual variation in both transcript and protein expression levels among California mussels, Mytilus californianus Conrad. Mussels were exposed to five ecologically relevant treatments that varied in the mean and interindividual heterogeneity of body temperature. To target a diverse set of physiological functions, we assessed variation within 19 expression subnetworks, including canonical stress‐response pathways and empirically derived coexpression clusters that represent a diffuse set of cellular processes. Variation in expression was particularly pronounced in the treatments with high mean and heterogeneous body temperatures. However, with few exceptions, environment‐dependent shifts of variation in the transcriptome were not reflected in the proteome. A metric of phenotypic integration provided evidence for a greater degree of constraint on relative expression levels (i.e., stronger correlation) within expression subnetworks in benign, homogeneous environments. Our results suggest that environments that are more stressful on average – and which also tend to be more heterogeneous – can relax these expression constraints and reduce phenotypic integration within biochemical subnetworks. Context‐dependent “unmasking” of functional variation may contribute to interindividual differences in physiological phenotype and performance in stressful environments.

New insights into the function of the proteins IsiC and IsiD from Synechocystis sp. PCC 6803 under iron limitation

Iron is a common cofactor in biological processes such as respiration, photosynthesis, and nitrogen fixation. The genes isiC and isiD encode unknown proteins, and the growth of ΔisiC and ΔisiD mutants is inhibited under iron-deficient conditions. To study the regulatory mechanisms of IsiC and IsiD during iron starvation, we carried out transcriptome and metabolome sequencing. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the photosynthesis, nitrogen metabolism, and ABC transporter pathways play a vital role in regulating iron deficiency. Upon iron repletion, IsiC and IsiD also have a regulatory effect on these pathways. Additionally, KEGG analysis of the differential metabolites of wild type (WT) and mutants showed that they were all enriched in starch and sucrose metabolism after iron limitation. Weighted gene co-expression network analysis (WGCNA) constructed a co-expression network of differentially expressed genes with phenotypes and metabolites, and finally identified five modules. The turquoise module was positively correlated with iron deficiency. In contrast, the WT and blue module exhibited a negative correlation, and the mutants ΔisiC and ΔisiD were positively correlated with the gray and brown modules, respectively. WGCNA also analyzed the relationship between metabolites and phenotypes, and the green module was related to iron starvation. The co-expression network determined the hub genes and metabolites of each module. This study lays a foundation for a better understanding of cyanobacteria in response to iron deficiency. KEY POINTS: • Nitrogen metabolism and ABC transporters are involved in iron regulation. • Starch and sucrose metabolism is related to the regulation of iron deficiency. • WGCNA analyzes the correlation between genes and metabolites.

A Comprehensive Coexpression Network Analysis in Vibrio cholerae

Cholera is a devastating illness that kills tens of thousands of people annually. Vibrio cholerae, the causative agent of cholera, is an important model organism to investigate both bacterial pathogenesis and the impact of horizontal gene transfer on the emergence and dissemination of new virulent strains. Despite the importance of this pathogen, roughly one-third of V. cholerae genes are functionally unannotated, leaving large gaps in our understanding of this microbe. Through coexpression network analysis of existing RNA sequencing data, this work develops an approach to uncover novel gene-gene relationships and contextualize genes with no known function, which will advance our understanding of V. cholerae virulence and evolution.

Research into the evolution and pathogenesis of Vibrio cholerae has benefited greatly from the generation of high-throughput sequencing data to drive molecular analyses. The steady accumulation of these data sets now provides a unique opportunity for in silico hypothesis generation via coexpression analysis. Here, we leverage all published V. cholerae RNA sequencing data, in combination with select data from other platforms, to generate a gene coexpression network that validates known gene interactions and identifies novel genetic partners across the entire V. cholerae genome. This network provides direct insights into genes influencing pathogenicity, metabolism, and transcriptional regulation, further clarifies results from previous sequencing experiments in V. cholerae (e.g., transposon insertion sequencing [Tn-seq] and chromatin immunoprecipitation sequencing [ChIP-seq]), and expands upon microarray-based findings in related Gram-negative bacteria.

IMPORTANCE Cholera is a devastating illness that kills tens of thousands of people annually. Vibrio cholerae, the causative agent of cholera, is an important model organism to investigate both bacterial pathogenesis and the impact of horizontal gene transfer on the emergence and dissemination of new virulent strains. Despite the importance of this pathogen, roughly one-third of V. cholerae genes are functionally unannotated, leaving large gaps in our understanding of this microbe. Through coexpression network analysis of existing RNA sequencing data, this work develops an approach to uncover novel gene-gene relationships and contextualize genes with no known function, which will advance our understanding of V. cholerae virulence and evolution.

Nostoc muscorum and Phormidium foveolarum differentially respond to butachlor and UV-B stress

Present study deals with responses of two cyanobacteria viz. Nostoc muscorum and Phormidium foveolarum against butachlor [2-chloro-2,6-diethyl-N-(butoxymethyl) acetanilide] (low dose; 5 µg mL^-1 and high dose; 10 µg mL^-1) and UV-B (7.2 kJ m^-2) alone, and in combination. Butachlor and UV-B exposure, alone and in combination, suppressed growth of both the cyanobacteria. This was accompanied by inhibitory effect on whole cell oxygen evolution and photosynthetic electron transport activities. Both the stressors induced the oxidative stress as there was significant increase in superoxide radical (O₂ ^·-) and hydrogen peroxide (H₂O₂) contents resulting into increased lipid peroxidation and electrolyte leakage. In N. muscorum, low dose of butachlor and UV-B alone increased the activities of superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD), while activity of all these enzymatic antioxidants declined significantly at treatments with high dose of butachlor alone, and with low and high doses of butachlor and UV-B in combination. In P. foveolarum, enhanced activity of SOD, CAT and POD (except POD at high dose of butachlor and UV-B combination) was noticed. Ascorbate level in N. muscorum declined progressively with increasing intensity of stress while in P. foveolarum varied response was noticed. Proline contents increased progressively under tested stress in both the organisms. Overall results suggest that N. muscorum was more sensitive than P. foveolarum against butachlor and UV-B stresses. Hence, P. foveolarum may be preferred in paddy field for sustainable agriculture.

Improvement of Thermosynechococcus sp. CL-1 performance on biomass productivity and CO2 fixation via growth factors arrangement

The enormous attraction on CO₂ biofixation using photosynthetic microorganisms such as cyanobacteria has been risen due to its promising efficiency and valuable by-products production. In this study, an isolated cyanobacterium from hot spring in Taiwan, Thermosynechococcus sp. CL-1 (TCL-1) was evaluated for its growth factors arrangement effect on the biomass productivity and CO₂ biofixation. The initial biomass concentration, and nutrient supply level variation influenced TCL-1 biomass productivity and CO₂ biofixation rate while the adjusted and controlled pH value gave an insignificant difference on its performance. The initial biomass concentration of 3 g L^-1 gave the best result on biomass productivity and CO₂ fixation which reached 143.4 mg L^-1 h^-1 and 224 mg L^-1 h^-1 respectively. Regarding to the result of this study, controlled pH value by the CO₂ supply inside the reactor, produced an insignificant difference in TCL-1 performance compared to those with the uncontrolled pH value. The variation of nutrient supply level was achieved by the variation of macronutrient and micronutrient supply inside the medium. The G-solution contains metals and other micronutrient elements which are necessary for the growth of TCL-1. The combination between 5-folds MF medium as the macronutrient, and 3-folds G-solution as the micronutrient supply, present the best TCL-1 performance on biomass productivity and CO2 fixation rate.

Revealing shared differential co-expression profiles in rice infected by virus from reoviridae and sequiviridae group

Differential co-expression is a cutting-edge approach to analyze gene expression data and identify both shared and divergent expression patterns. The availability of high-throughput gene expression datasets and efficient computational approaches have unfolded the opportunity to a systems level understanding of functional genomics of different stresses with respect to plants. We performed the meta-analysis of the available microarray data for reoviridae and sequiviridae infection in rice with the aim to identify the shared gene co-expression profile. The microarray data were downloaded from ArrayExpress and analyzed through a modified Weighted Gene Co-expression Network Analysis (WGCNA) protocol. WGCNA clustered the genes based on the expression intensities across the samples followed by identification of modules, eigengenes, principal components, topology overlap, module membership and module preservation. The module preservation analysis identified 4 modules; salmon (638 genes), midnightblue (584 genes), lightcyan (686 genes) and red (562 genes), which are highly preserved in both the cases. The networks in case of reoviridae infection showed neatly packed clusters whereas, in sequiviridae, the clusters were loosely connected which is due to the differences in the correlation values. We also identified 83 common transcription factors targeting the hub genes from all the identified modules. This study provides a coherent view of the comparative aspect of the expression of common genes involved in different virus infections which may aid in the identification of novel targets and development of new intervention strategy against the virus.

Species-specific transcriptomic network inference of interspecies interactions

The advent of high-throughput 'omics approaches coupled with computational analyses to reconstruct individual genomes from metagenomes provides a basis for species-resolved functional studies. Here, a mutual information approach was applied to build a gene association network of a commensal consortium, in which a unicellular cyanobacterium Thermosynechococcus elongatus BP1 supported the heterotrophic growth of Meiothermus ruber strain A. Specifically, we used the context likelihood of relatedness (CLR) algorithm to generate a gene association network from 25 transcriptomic datasets representing distinct growth conditions. The resulting interspecies network revealed a number of linkages between genes in each species. While many of the linkages were supported by the existing knowledge of phototroph-heterotroph interactions and the metabolism of these two species several new interactions were inferred as well. These include linkages between amino acid synthesis and uptake genes, as well as carbohydrate and vitamin metabolism, terpenoid metabolism and cell adhesion genes. Further topological examination and functional analysis of specific gene associations suggested that the interactions are likely to center around the exchange of energetically costly metabolites between T. elongatus and M. ruber. Both the approach and conclusions derived from this work are widely applicable to microbial communities for identification of the interactions between species and characterization of community functioning as a whole.

Crosstalk of two-component signal transduction systems in regulating central carbohydrate and energy metabolism during autotrophic and photomixotrophic growth of Synechocystis sp. PCC 6803

Unicellular model cyanobacterium Synechocystis sp. PCC 6803 has received considerable attention as a sustainable energy resource because of its photosynthetic machinery. However, two-component signal transduction systems (TCSTSs) in regulating central carbohydrate and energy metabolism of cyanobacteria are still poorly understood due to their diversity and functional complication. In this study, by comparing the growth of knockout mutants of 44 response regulators (RRs) of TCSTSs in Synechocystis, several RR mutants demonstrating differential growth patterns were identified under auto- or photomixotrophic conditions. However, in spite of no growth difference observed for the remaining RR mutants, liquid chromatography-mass spectrometry based metabolomic profile analysis showed that a widespread crosstalk of TCSTSs in regulating central carbohydrate and energy metabolism of Synechocystis was identified, while most of them showed diverse patterns during different trophic types or growth stages. Furthermore, an integrative analysis between evolutionary relationships and metabolomic profiles revealed some pairs of paralogous RRs with highly functional convergence, suggesting the possible conserved functions of Synechocystis TCSTSs during evolution. This study laid an important basis for understanding the function of TCSTSs in photosynthetic cyanobacteria.

Small Molecule Chelators Reveal That Iron Starvation Inhibits Late Stages of Bacterial Cytokinesis

Bacterial cell division requires identification of the division site, assembly of the division machinery, and constriction of the cell envelope. These processes are regulated in response to several cellular and environmental signals. Here, we use small molecule iron chelators to characterize the surprising connections between bacterial iron homeostasis and cell division. We demonstrate that iron starvation downregulates the transcription of genes encoding proteins involved in cell division, reduces protein biosynthesis, and prevents correct positioning of the division machinery at the division site. These combined events arrest the constriction of the cell during late stages of cytokinesis in a manner distinct from known mechanisms of inhibiting cell division. Overexpression of genes encoding cell division proteins or iron transporters partially suppresses the biological activity of iron chelators and restores growth and division. We propose a model demonstrating the effect of iron availability on the regulatory mechanisms coordinating division in response to the nutritional state of the cell.

An Integrated Analysis of miRNAs and Methylated Genes Encoding mRNAs and lncRNAs in Sheep Breeds with Different Fecundity

In our previous study, we investigated the regulatory relationship between lncRNAs, miRNA, and mRNAs in an effort to shed light onto the regulatory mechanisms involved in sheep fecundity. As an extension of this study, here, we aimed to identify potential regulators of sheep fecundity using a genome-wide analysis of miRNAs and the methylated genes encoding mRNAs and lncRNAs in the ovaries of Dorset sheep (low fecundity) and Small Tail Han ewes (high fecundity) with the genotype BB (Han BB) and the genotype ++ (Han ++) by performing RNA-Seq and MeDIP-Seq analyses. Methylated coding-non-coding gene co-expression networks for Han and Dorset sheep were constructed using the methylated genes encoding the differentially expressed mRNAs and lncRNAs identified in this study. In the Han BB vs. Dorset comparison, the lncRNAs TTC26 and MYH15 had the largest degree. Similarly, the lncRNA NYAP1 had the largest degree in the Han ++ vs. Dorset comparison. None of the methylated genes encoding lncRNAs were co-expressed with the methylated genes encoding mRNAs in the Han BB vs. Han ++ comparison. The methylated genes encoding lncRNAs identified here may play a vital regulatory role in sheep breeding. Our results suggest that miRNAs might play a key role in sheep prolificacy by regulating target genes related to thyroid hormone synthesis, and methylated genes encoding lncRNAs associated with tight junctions might contribute to the high breeding rate in Han sheep. These findings may contribute to a deeper understanding of sheep prolificacy.

Comparison of gene co-expression networks in Pseudomonas aeruginosa and Staphylococcus aureus reveals conservation in some aspects of virulence

Pseudomonas aeruginosa and Staphylococcus aureus are two evolutionary distant bacterial species that are frequently isolated from persistent infections such as chronic infectious wounds and severe lung infections in cystic fibrosis patients. To the best of our knowledge no comprehensive genome scale co-expression study has been already conducted on these two species and in most cases only the expression of very few genes has been the subject of investigation. In this study, in order to investigate the level of expressional conservation between these two species, using heterogeneous gene expression datasets the weighted gene co-expression network analysis (WGCNA) approach was applied to study both single and cross species genome scale co-expression patterns of these two species. Single species co-expression network analysis revealed that in P. aeruginosa, genes involved in quorum sensing (QS), iron uptake, nitrate respiration and type III secretion systems and in S. aureus, genes associated with the regulation of carbon metabolism, fatty acid-phospholipids metabolism and proteolysis represent considerable co-expression across a variety of experimental conditions. Moreover, the comparison of gene co-expression networks between P. aeruginosa and S. aureus was led to the identification of four co-expressed gene modules in both species totally consisting of 318 genes. Several genes related to two component signal transduction systems, small colony variants (SCVs) morphotype and protein complexes were found in the detected modules. We believe that targeting the key players among the identified co-expressed orthologous genes will be a potential intervention strategy to control refractory co-infections caused by these two bacterial species.

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.

Metabolomic analysis reveals mechanism of antioxidant butylated hydroxyanisole on lipid accumulation in Crypthecodinium cohnii

The heterotrophic dinoflagellate alga Crypthecodinium cohnii is known to accumulate lipids with a high fraction of docosahexaenoic acid (DHA). In this study, we first evaluated two antioxidant compounds, butylated hydroxyanisole (BHA) and propyl gallate (PG), for their effects on lipid accumulation in C. cohnii. The results showed that antioxidant BHA could increase lipid accumulation in C. cohnii by 8.80% at a final concentration of 30 μM, while PG had no obvious effect on lipid accumulation at the tested concentrations. To decipher the molecular mechanism responsible for the increased lipid accumulation by BHA, we employed an integrated GC-MS and LC-MS metabolomic approach to determine the time-series metabolic profiles with or without BHA, and then subjected the metabolomic data to a principal component analysis (PCA) and a weighted gene coexpression network analysis (WGCNA) network analyses to identify the key metabolic modules and metabolites possibly relevant to the increased lipid accumulation. LC-MS analysis showed that several metabolites, including NADPH, could be important for the stimulation role of BHA on lipid accumulation. Meanwhile GC-MS and network analyses allowed identification of eight metabolic modules and nine hub metabolites possibly relevant to the stimulation role of BHA in C. cohnii. The study provided a metabolomics view of the BHA mode of action on lipid accumulation in C. cohnii, and the information could be valuable for a better understanding of antioxidant effects on lipid accumulation in other microalgae as well.

Metabolomic analysis reveals functional overlapping of three signal transduction proteins in regulating ethanol tolerance in cyanobacterium Synechocystis sp. PCC 6803

Low ethanol tolerance is a crucial factor that restricts the feasibility of bioethanol production in renewable cyanobacterial systems. Our previous studies showed that several transcriptional regulators were differentially regulated by exogenous ethanol in Synechocystis. In this study, by constructing knockout mutants of 34 Synechocystis putative transcriptional regulator-encoding genes and analyzing their phenotypes under ethanol stress, we found that three mutants of regulatory gene sll1392, sll1712 and slr1860 grew poorly in the BG11 medium supplemented with ethanol when compared with the wild type in the same medium, suggesting that the genes may be involved in the regulation of ethanol tolerance. To decipher the regulatory mechanism, targeted LC-MS and untargeted GC-MS approaches were employed to determine metabolic profiles of the three mutants and the wild type under both normal and ethanol stress conditions. The results were then subjected to PCA and WGCNA analyses to determine the responsive metabolites and metabolic modules related to ethanol tolerance. Interestingly, the results showed that there was a significant overlapping of the responsive metabolites and metabolic modules between three regulatory proteins, suggesting that a possible crosstalk between various regulatory proteins may be involved in combating against ethanol toxicity in Synechocystis. The study provided new insights into ethanol-tolerance regulation and knowledge important to rational tolerance engineering in Synechocystis.

Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803

Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein–protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

Metabolomic basis of laboratory evolution of butanol tolerance in photosynthetic Synechocystis sp. PCC 6803

BACKGROUND

Recent efforts demonstrated the potential application of cyanobacteria as a "microbial cell factory" to produce butanol directly from CO2. However, cyanobacteria have very low tolerance to the toxic butanol, which limits the economic viability of this renewable system.

RESULTS

Through a long-term experimental evolution process, we achieved a 150% increase of the butanol tolerance in a model cyanobacterium Synechocystis sp. PCC 6803 after a continuous 94 passages for 395 days in BG11 media amended with gradually increased butanol concentration from 0.2% to 0.5% (v/v). To decipher the molecular mechanism responsible for the tolerance increase, we employed an integrated GC-MS and LC-MS approach to determine metabolomic profiles of the butanol-tolerant Synechocystis strains isolated from several stages of the evolution, and then applied PCA and WGCNA network analyses to identify the key metabolites and metabolic modules related to the increased tolerance. The results showed that unstable metabolites of 3-phosphoglyceric acid (3PG), D-fructose 6-phosphate (F6P), D-glucose 6-phosphate (G6P), NADPH, phosphoenolpyruvic acid (PEP), D-ribose 5-phosphate (R5P), and stable metabolites of glycerol, L-serine and stearic acid were differentially regulated during the evolution process, which could be related to tolerance increase to butanol in Synechocystis.

CONCLUSIONS

The study provided the first time-series description of the metabolomic changes related to the gradual increase of butanol tolerance, and revealed a metabolomic basis important for rational tolerance engineering in Synechocystis.

Complementary iTRAQ proteomics and RNA-seq transcriptomics reveal multiple levels of regulation in response to nitrogen starvation in Synechocystis sp. PCC 6803

Sequential adaptation to environmental stress needs complex regulation at different cellular levels in cyanobacteria. To uncover the regulatory mechanism in response to nitrogen starvation, we investigated the genome-wide correlation between protein abundance and gene expression in a model cyanobacterium Synechocystis sp. PCC 6803 using complementary quantitative iTRAQ proteomics and RNA-seq transcriptomics. Consistent with the cell growth inhibition, proteomic analysis indicated phase-dependent down-regulation of proteins related to nitrogen metabolism, ribosome complexes, glycolysis pathway and tricarboxylic acid (TCA) cycles by nitrogen starvation. Transcriptomic analysis also showed that genes related to "Photosynthesis", "Protein synthesis" and "Energy metabolism" were significantly down-regulated by nitrogen starvation. Interestingly, the concordance between protein abundances and their corresponding mRNAs exhibited a functional categories-dependent pattern, with some categories, such as "Protein synthesis" and "Energy metabolism", having a relatively high correlation, while others even with numerous discordant changes in protein-mRNA pairs, indicated divergent regulation of transcriptional and post-transcriptional processes. In particular, an increased abundance of proteins related to "Photosynthesis" upon nitrogen starvation was found to be reversely correlated with the down-regulation of their corresponding mRNAs. In addition, two metabolic modules highly correlated with nitrogen starvation were identified by a co-expression network analysis, and were found to contain mostly photosynthetic proteins and hypothetical proteins, respectively. We further confirmed the involvement of the photosynthetic genes in nitrogen starvation tolerance by constructing and analyzing the psbV gene deletion mutant.

Metabolomic analysis of the salt-sensitive mutants reveals changes in amino acid and fatty acid composition important to long-term salt stress in Synechocystis sp. PCC 6803

Early studies in cyanobacteria have found that few genes induced by short-term salt shock (15-60 min) display a stable induction in the long-term (>1 day) salt-acclimated cells; meanwhile, most of the genes responsive to long-term salt stress were different from those by short-term salt shock, suggesting that different regulatory mechanisms may be involved for short-term and long-term salt stress responses. In our previous work using the model cyanobacterium Synechocystis sp. PCC 6803, sll1734 encoding CO2 uptake-related protein (CupA) and three genes encoding hypothetical proteins (i.e., ssr3402, slr1339, and ssr1853) were found induced significantly after a 3-day salt stress, and the corresponding gene knockout mutants were found salt sensitive. To further decipher the mechanisms that these genes may be involved, in this study, we performed a comparative metabolomic analysis of the wild-type Synechocystis and the four salt-sensitive mutants using a gas chromatography-mass spectrometry (GC-MS) approach. A metabolomic data set that consisted of 60 chemically classified metabolites was then subjected to a weighted correlation network analysis (WGCNA) to identify the metabolic modules and hub metabolites specifically related to each of the salt-stressed mutants. The results showed that two, one, zero, and two metabolic modules were identified specifically associated with the knockout events of sll1734, ssr3402, slr1339, and ssr1853, respectively. The mutant-associated modules included metabolites such as lysine and palmitic acid, suggesting that amino acid and fatty acid metabolisms are among the key protection mechanisms against long-term salt stresses in Synechocystis. The metabolomic results were further confirmed by quantitative reverse-transcription PCR analysis, which showed the upregulation of lysine and fatty acid synthesis-related genes. The study provided new insights on metabolic networks involved in long-term salt stress response in Synechocystis.

Global metabolomic and network analysis of Escherichia coli responses to exogenous biofuels

Although synthetic biology progress has made it possible to produce various biofuels in more user-friendly hosts, such as Escherichia coli, the large-scale biofuel production in these non-native systems is still challenging, mostly due to the very low tolerance of these non-native hosts to the biofuel toxicity. To address the issues, in this study we determined the metabolic responses of E. coli induced by three major biofuel products, ethanol, butanol, and isobutanol, using a gas chromatography-mass spectrometry (GC-MS) approach. A metabolomic data set of 65 metabolites identified in all samples was then subjected to principal component analysis (PCA) to compare their effects and a weighted correlation network analysis (WGCNA) to identify the metabolic modules specifically responsive to each of the biofuel stresses, respectively. The PCA analysis showed that cellular responses caused by the biofuel stress were in general similar to aging cells at stationary phase, inconsistent with early studies showing a high degree of dissimilarity between metabolite responses during growth cessation as induced through stationary phases or through various environmental stress applications. The WGCNA analysis allowed identification of 2, 4, and 2 metabolic modules specifically associated with ethanol, butanol, and isobutanol treatments, respectively. The biofuel-associated modules included amino acids and osmoprotectants, such as isoleucine, valine, glycine, glutamate, and trehalose, suggesting amino acid metabolism and osmoregulation are among the key protection mechanisms against biofuel stresses in E. coli. Interestingly, no module was found associated with all three biofuel products, suggesting differential effects of each biofuel on E. coli. The findings enhanced our understanding of E. coli responses to exogenous biofuels and also demonstrated the effectiveness of the metabolomic and network analysis in identifying key targets for biofuel tolerance.

Integrated proteomic and transcriptomic analysis reveals novel genes and regulatory mechanisms involved in salt stress responses in Synechocystis sp. PCC 6803

Salt stress is a common stress that limits growth and productivity of photosynthetic microbes in natural environments. Although cellular responses of a model cyanobacterium Synechocystis sp. PCC6803 to high and changing salt concentration have been studied, it remains undefined of the gene components and their regulation in the long-term salt acclimation networks. In this study, we performed an integrated study coupling a quantitative iTRAQ-LC-MS/MS proteomics and a next-generation sequencing-based RNA-seq transcriptomics on Synechocystis under salt stress for an extended period of time. Comparative quantification of protein abundances led to the identification of 68 and 108 proteins differentially regulated by salt treatment at 24 and 48 h, respectively. RNA-seq transcriptomic analysis showed that genes involved in energy metabolism and protein synthesis, and genes encoding hypothetical proteins responded to salt stress in a phase-dependent pattern. Notably, a gene encoding CO2-uptake-related protein (CupA) and three genes encoding hypothetical proteins were induced significantly at either transcript or protein level after long-term salt stress. Gene knockout and comparative growth analysis demonstrated that these four genes were involved in salt tolerance in Synechocystis. In addition, a complementary proteome and transcriptome analysis showed that concordance between protein abundances and their corresponding mRNAs varied significantly between various gene-protein pairs, indicating divergent regulation of transcriptional and post-transcriptional processes during salt stress adaptation in Synechocystis. The study provided new insights on genes and regulatory mechanism involved in salt stress response in Synechocystis.