Although naturally occurring catalytic RNA molecules-ribozymes-have attracted a great deal of research interest, very few have been identified in humans. Here, we developed a genome-wide approach to ...discovering self-cleaving ribozymes and identified a naturally occurring ribozyme in humans. The secondary structure and biochemical properties of this ribozyme indicate that it belongs to an unidentified class of small, self-cleaving ribozymes. The sequence of the ribozyme exhibits a clear evolutionary path, from its appearance between ~130 and ~65 million years ago (Ma), to acquiring self-cleavage activity very recently, ~13-10 Ma, in the common ancestors of humans, chimpanzees and gorillas. The ribozyme appears to be functional in vivo and is embedded within a long noncoding RNA belonging to a class of very long intergenic noncoding RNAs. The presence of a catalytic RNA enzyme in lncRNA creates the possibility that these transcripts could function by carrying catalytic RNA domains.
Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model ...alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome‐scale metabolic network for this alga and devised a novel light‐modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light‐driven metabolism and quantitative systems biology.
Synopsis
Algae have garnered significant interest in recent years, especially for their potential application in biofuel production. The hallmark, model eukaryotic microalgae Chlamydomonas reinhardtii has been widely used to study photosynthesis, cell motility and phototaxis, cell wall biogenesis, and other fundamental cellular processes (Harris, 2001). Characterizing algal metabolism is key to engineering production strains and understanding photobiological phenomena. Based on extensive literature on C. reinhardtii metabolism, its genome sequence (Merchant et al, 2007), and gene functional annotation, we have reconstructed and experimentally validated the genome‐scale metabolic network for this alga, iRC1080, the first network to account for detailed photon absorption permitting growth simulations under different light sources. iRC1080 accounts for 1080 genes, associated with 2190 reactions and 1068 unique metabolites and encompasses 83 subsystems distributed across 10 cellular compartments (Figure 1A). Its >32% coverage of estimated metabolic genes is a tremendous expansion over previous algal reconstructions (Boyle and Morgan, 2009; Manichaikul et al, 2009). The lipid metabolic pathways of iRC1080 are considerably expanded relative to existing networks, and chemical properties of all metabolites in these pathways are accounted for explicitly, providing sufficient detail to completely specify all individual molecular species: backbone molecule and stereochemical numbering of acyl‐chain positions; acyl‐chain length; and number, position, and cis–trans stereoisomerism of carbon–carbon double bonds. Such detail in lipid metabolism will be critical for model‐driven metabolic engineering efforts.
We experimentally verified transcripts accounted for in the network under permissive growth conditions, detecting >90% of tested transcript models (Figure 1B) and providing validating evidence for the contents of iRC1080. We also analyzed the extent of transcript verification by specific metabolic subsystems. Some subsystems stood out as more poorly verified, including chloroplast and mitochondrial transport systems and sphingolipid metabolism, all of which exhibited <80% of transcripts detected, reflecting incomplete characterization of compartmental transporters and supporting a hypothesis of latent pathway evolution for ceramide synthesis in C. reinhardtii. Additional lines of evidence from the reconstruction effort similarly support this hypothesis including lack of ceramide synthetase and other annotation gaps downstream in sphingolipid metabolism. A similar hypothesis of latent pathway evolution was established for very long‐chain fatty acids (VLCFAs) and their polyunsaturated analogs (VLCPUFAs) (Figure 1C), owing to the absence of this class of lipids in previous experimental measurements, lack of a candidate VLCFA elongase in the functional annotation, and additional downstream annotation gaps in arachidonic acid metabolism.
The network provides a detailed account of metabolic photon absorption by light‐driven reactions, including photosystems I and II, light‐dependent protochlorophyllide oxidoreductase, provitamin D3 photoconversion to vitamin D3, and rhodopsin photoisomerase; this network accounting permits the precise modeling of light‐dependent metabolism. iRC1080 accounts for effective light spectral ranges through analysis of biochemical activity spectra (Figure 3A), either reaction activity or absorbance at varying light wavelengths. Defining effective spectral ranges associated with each photon‐utilizing reaction enabled our network to model growth under different light sources via stoichiometric representation of the spectral composition of emitted light, termed prism reactions. Coefficients for different photon wavelengths in a prism reaction correspond to the ratios of photon flux in the defined effective spectral ranges to the total emitted photon flux from a given light source (Figure 3B). This approach distinguishes the amount of emitted photons that drive different metabolic reactions. We created prism reactions for most light sources that have been used in published studies for algal and plant growth including solar light, various light bulbs, and LEDs. We also included regulatory effects, resulting from lighting conditions insofar as published studies enabled. Light and dark conditions have been shown to affect metabolic enzyme activity in C. reinhardtii on multiple levels: transcriptional regulation, chloroplast RNA degradation, translational regulation, and thioredoxin‐mediated enzyme regulation. Through application of our light model and prism reactions, we were able to closely recapitulate experimental growth measurements under solar, incandescent, and red LED lights. Through unbiased sampling, we were able to establish the tremendous statistical significance of the accuracy of growth predictions achievable through implementation of prism reactions. Finally, application of the photosynthetic model was demonstrated prospectively to evaluate light utilization efficiency under different light sources. The results suggest that, of the existing light sources, red LEDs provide the greatest efficiency, about three times as efficient as sunlight. Extending this analysis, the model was applied to design a maximally efficient LED spectrum for algal growth. The result was a 677‐nm peak LED spectrum with a total incident photon flux of 360 μE/m2/s, suggesting that for the simple objective of maximizing growth efficiency, LED technology has already reached an effective theoretical optimum.
In summary, the C. reinhardtii metabolic network iRC1080 that we have reconstructed offers insight into the basic biology of this species and may be employed prospectively for genetic engineering design and light source design relevant to algal biotechnology. iRC1080 was used to analyze lipid metabolism and generate novel hypotheses about the evolution of latent pathways. The predictive capacity of metabolic models developed from iRC1080 was demonstrated in simulating mutant phenotypes and in evaluation of light source efficiency. Our network provides a broad knowledgebase of the biochemistry and genomics underlying global metabolism of a photoautotroph, and our modeling approach for light‐driven metabolism exemplifies how integration of largely unvisited data types, such as physicochemical environmental parameters, can expand the diversity of applications of metabolic networks.
The genome‐scale metabolic network of Chlamydomonas reinhardtii (iRC1080) was reconstructed, accounting for >32% of the estimated metabolic genes encoded in the genome, and including extensive details of lipid metabolic pathways.
This is the first metabolic network to explicitly account for stoichiometry and wavelengths of metabolic photon usage, providing a new resource for research of C. reinhardtii metabolism and developments in algal biotechnology.
Metabolic functional annotation and the largest transcript verification of a metabolic network to date was performed, at least partially verifying >90% of the transcripts accounted for in iRC1080. Analysis of the network supports hypotheses concerning the evolution of latent lipid pathways in C. reinhardtii, including very long‐chain polyunsaturated fatty acid and ceramide synthesis pathways.
A novel approach for modeling light‐driven metabolism was developed that accounts for both light source intensity and spectral quality of emitted light. The constructs resulting from this approach, termed prism reactions, were shown to significantly improve the accuracy of model predictions, and their use was demonstrated for evaluation of light source efficiency and design.
Poor prognoses remain the most challenging aspect of hepatocellular carcinoma (HCC) therapy. Consequently, alternative therapeutics are essential to control HCC. This study investigated the ...anticancer effects of safranal against HCC using in vitro, in silico, and network analyses. Cell cycle and immunoblot analyses of key regulators of cell cycle, DNA damage repair and apoptosis demonstrated unique safranal-mediated cell cycle arrest at G2/M phase at 6 and 12 h, and at S-phase at 24 h, and a pronounced effect on DNA damage machinery. Safranal also showed pro-apoptotic effect through activation of both intrinsic and extrinsic initiator caspases; indicating ER stress-mediated apoptosis. Gene set enrichment analysis provided consistent findings where UPR is among the top terms of up-regulated genes in response to safranal treatment. Thus, proteins involved in ER stress were regulated through safranal treatment to induce UPR in HepG2 cells.
Src homology 3 (SH3) domains bind peptides to mediate protein–protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using ...peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two‐hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain‐mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form.
The Caenorhabditis elegans SH3 domain interactome was mapped and compared with the yeast SH3 interactome. Orthologous SH3 domain‐mediated interactions are highly rewired, but the general function of the SH3 domain network is conserved between the two species
Synopsis
The Caenorhabditis elegans SH3 domain interactome was mapped and compared with the yeast SH3 interactome. Orthologous SH3 domain‐mediated interactions are highly rewired, but the general function of the SH3 domain network is conserved between the two species
C. elegans Src homology 3 (SH3) domain interactome was mapped using stringent yeast two‐hybrid, resulting in a total of 1070 interactions among 79 out of 84 worm SH3 domains and 475 proteins.
SH3 domain binding specificities were profiled for 36 worm SH3 domains using peptide phage display.
The yeast and worm SH3 domain interactomes are significantly enriched in endocytosis proteins, but the specific interactions mediated by orthologous SH3 domains are highly rewired.
Using the worm SH3 interactome, we identified new endocytosis proteins in worm and human.
Neuromodulation of arousal states ensures that an animal appropriately responds to its environment and engages in behaviors necessary for survival. However, the molecular and circuit properties ...underlying neuromodulation of arousal states such as sleep and wakefulness remain unclear. To tackle this challenge in a systematic and unbiased manner, we performed a genetic overexpression screen to identify genes that affect larval zebrafish arousal. We found that the neuropeptide neuromedin U (Nmu) promotes hyperactivity and inhibits sleep in zebrafish larvae, whereas nmu mutant animals are hypoactive. We show that Nmu-induced arousal requires Nmu receptor 2 and signaling via corticotropin releasing hormone (Crh) receptor 1. In contrast to previously proposed models, we find that Nmu does not promote arousal via the hypothalamic-pituitary-adrenal axis, but rather probably acts via brainstem crh-expressing neurons. These results reveal an unexpected functional and anatomical interface between the Nmu system and brainstem arousal systems that represents a novel wake-promoting pathway.
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•A zebrafish genetic screen identifies genes that regulate sleep and arousal•Nmu overexpression inhibits sleep whereas nmu mutants are hypoactive•Nmu-induced phenotypes require Nmu receptor 2 but not the glucocorticoid receptor•Nmu-induced arousal activates brainstem Crh neurons and requires Crh signaling
Chiu et al. perform a genetic screen in zebrafish and identify Nmu as a regulator of sleep/wake behaviors. They show that Nmu overexpression activates brainstem Crh neurons and that Nmu-induced arousal requires Crh signaling, thus identifying a novel vertebrate arousal circuit.
Diatoms are a major group of unicellular algae that are rich in lipids and carotenoids. However, sustained research efforts are needed to improve the strain performance for high product yields ...towards commercialization. In this study, we generated a number of mutants of the model diatom
, a cosmopolitan species that has also been found in Nordic region, using the chemical mutagens ethyl methanesulfonate (EMS) and
-methyl-
'-nitro-
-nitrosoguanidine (NTG). We found that both chlorophyll
and neutral lipids had a significant correlation with carotenoid content and these correlations were better during exponential growth than in the stationary growth phase. Then, we studied
common metabolic pathways and analyzed correlated enzymatic reactions between fucoxanthin synthesis and pigmentation or lipid metabolism through a genome-scale metabolic model. The integration of the computational results with liquid chromatography-mass spectrometry data revealed key compounds underlying the correlative metabolic pathways. Approximately 1000 strains were screened using fluorescence-based high-throughput method and five mutants selected had 33% or higher total carotenoids than the wild type, in which four strains remained stable in the long term and the top mutant exhibited an increase of 69.3% in fucoxanthin content compared to the wild type. The platform described in this study may be applied to the screening of other high performing diatom strains for industrial applications.
Sodium (Na
) accumulation in the cytosol will result in ion homeostasis imbalance and toxicity of transpiring leaves. Studies of salinity tolerance in the diploid wheat ancestor
showed that
-like ...gene was a major gene in the QTL for salt tolerance, named
. In the present study, we were interested in investigating the molecular mechanisms underpinning the role of the
gene in salt tolerance in barley (
). A USDA mini-core collection of 2,671 barley lines, part of a field trial was screened for salinity tolerance, and a Genome Wide Association Study (GWAS) was performed. Our results showed important SNPs that are correlated with salt tolerance that mapped to a region where
ion transporter located on chromosome four. Furthermore, sodium (Na
) and potassium (K
) content analysis revealed that tolerant lines accumulate more sodium in roots and leaf sheaths, than in the sensitive ones. In contrast, sodium concentration was reduced in leaf blades of the tolerant lines under salt stress. In the absence of NaCl, the concentration of Na
and K
were the same in the roots, leaf sheaths and leaf blades between the tolerant and the sensitive lines. In order to study the molecular mechanism behind that, alleles of the
gene from five tolerant and five sensitive barley lines were cloned and sequenced. Sequence analysis did not show the presence of any polymorphism that distinguishes between the tolerant and sensitive alleles. Our real-time RT-PCR experiments, showed that the expression of
gene in roots of the tolerant line was significantly induced after challenging the plants with salt stress. In contrast, in leaf sheaths the expression was decreased after salt treatment. In sensitive lines, there was no difference in the expression of
gene in leaf sheath under control and saline conditions, while a slight increase in the expression was observed in roots after salt treatment. These results provide stronger evidence that
gene in barley play a key role in withdrawing Na
from the xylem and therefore reducing its transport to leaves. Given all that, these data support the hypothesis that
gene is responsible for Na
unloading to the xylem and controlling its distribution in the shoots, which provide new insight into the understanding of this QTL for salinity tolerance in barley.
To investigate the phenomic and genomic traits that allow green algae to survive in deserts, we characterized a ubiquitous species,
, which we isolated from multiple locations in the United Arab ...Emirates (UAE). Metabolomic analyses of
indicated that the alga accumulates a broad range of carbon sources, including several desiccation tolerance-promoting sugars and unusually large stores of palmitate. Growth assays revealed capacities to grow in salinities from zero to 60 g/L and to grow heterotrophically on >40 distinct carbon sources. Assembly and annotation of genomic reads yielded a 52.5 Mbp genome with 8153 functionally annotated genes. Comparison with other sequenced green algae revealed unique protein families involved in osmotic stress tolerance and saccharide metabolism that support phenomic studies. Our results reveal the robust and flexible biology utilized by a green alga to successfully inhabit a desert coastline.
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.
Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein ...interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.
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