High-Density Guide RNA Tiling and Machine Learning for Designing CRISPR Interference in Synechococcus sp. PCC 7002

While CRISPRi was previously established in Synechococcus sp. PCC 7002 (hereafter 7002), the design principles for guide RNA (gRNA) effectiveness remain largely unknown. Here, 76 strains of 7002 were constructed with gRNAs targeting three reporter systems to evaluate features that impact gRNA efficiency. Correlation analysis of the data revealed that important features of gRNA design include the position relative to the start codon, GC content, protospacer adjacent motif (PAM) site, minimum free energy, and targeted DNA strand. Unexpectedly, some gRNAs targeting upstream of the promoter region showed small but significant increases in reporter expression, and gRNAs targeting the terminator region showed greater repression than gRNAs targeting the 3' end of the coding sequence. Machine learning algorithms enabled prediction of gRNA effectiveness, with Random Forest having the best performance across all training sets. This study demonstrates that high-density gRNA data and machine learning can improve gRNA design for tuning gene expression in 7002.

Advances in engineering algae for biofuel production

While algae demonstrate potential as a sustainable fuel source, low productivities limit the economic realization of algal biofuels. High-throughput strain engineering, omics-informed genome-scale modeling, and microbiome engineering are key technologies for enabling algal biofuels. High-throughput strain engineering efforts generate improved traits, including high biomass productivity and lipid content, in diverse algal species. Genome-scale models, constructed with the aid of omics data, provide insight into metabolic limitations and guide rational algal strain engineering efforts. As outdoor cultivation systems introduce exogenous organisms, microbiome engineering seeks to eliminate harmful organisms and introduce beneficial species. Optimizing algal biomass production and lipid content using these technologies may overcome the productivity barrier for the commercialization of algal biofuels.

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high recall or high specificity. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded as additional data is generated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility, and adaptability.

Bacteria and archaea, single-cell organisms collectively known as prokaryotes, live in all imaginable environments and comprise the majority of living organisms on this planet. Prokaryotes play a critical role in the homeostasis of multicellular organisms (such as animals and plants) and ecosystems. In addition, bacteria can be pathogenic and cause a variety of diseases in these same hosts and ecosystems. In short, understanding the biology and molecular functions of bacteria and archaea and devising mechanisms to engineer and optimize their properties are critical scientific endeavors with significant implications in healthcare, agriculture, manufacturing, and climate science among others. One major molecular difference between unicellular and multicellular organisms is the way they express genes–multicellular organisms make individual RNA molecules for each gene while, prokaryotes express operons (i.e., a group of genes coding functionally related proteins) in contiguous polycistronic RNA molecules. Understanding which genes exist within operons is critical for elucidating basic biology and for engineering organisms. In this work, we use a combination of statistical and machine learning-based methods to use next-generation sequencing data to predict operon structure across a range of prokaryotes. Our method provides an easily implemented, robust, accurate, and flexible way to determine operon structure in an organism-agnostic manner using readily available data.

Identification of Metal Stresses in Arabidopsis thaliana Using Hyperspectral Reflectance Imaging

Industrial accidents, such as the Fukushima and Chernobyl disasters, release harmful chemicals into the environment, covering large geographical areas. Natural flora may serve as biological sensors for detecting metal contamination, such as cesium. Spectral detection of plant stresses typically employs a few select wavelengths and often cannot distinguish between different stress phenotypes. In this study, we apply hyperspectral reflectance imaging in the visible and near-infrared along with multivariate curve resolution (MCR) analysis to identify unique spectral signatures of three stresses in Arabidopsis thaliana: salt, copper, and cesium. While all stress conditions result in common stress physiology, hyperspectral reflectance imaging and MCR analysis produced unique spectral signatures that enabled classification of each stress. As the level of potassium was previously shown to affect cesium stress in plants, the response of A. thaliana to cesium stress under variable levels of potassium was also investigated. Increased levels of potassium reduced the spectral response of A. thaliana to cesium and prevented changes to chloroplast cellular organization. While metal stress mechanisms may vary under different environmental conditions, this study demonstrates that hyperspectral reflectance imaging with MCR analysis can distinguish metal stress phenotypes, providing the potential to detect metal contamination across large geographical areas.

Revisiting the Effects of Xenon on Urate Oxidase and Tissue Plasminogen Activator: No Evidence for Inhibition by Noble Gases

Although chemically inert, Xe and other noble gases have been shown to have functional effects on biological systems. For example, Xe is a powerful anesthetic with neuroprotective properties. Recent reports have claimed that Xe inhibits the activity of tissue plasminogen activator (tPA) and urate oxidase (UOX), indicating that the use of Xe as an anesthetic may have undesirable side effects. Here, we revisited the methods used to demonstrate Xe inhibition of UOX and tPA, testing both indirect and direct gas delivery methods with variable bubble sizes and gas flowrates. Our results indicate that Xe or Kr do not affect the activity of UOX or tPA and that the previously reported inhibition is due to protein damage attendant to directly bubbling gases into protein solutions. The lack of evidence to support Xe inhibition of UOX or tPA alleviates concerns regarding possible side effects for the clinical application of Xe as an anesthetic. Furthermore, this study illustrates the importance of using indirect methods of gas dissolution for studying gas-protein interactions in aqueous solution.

Genetic tools for advancement of Synechococcus sp. PCC 7002 as a cyanobacterial chassis

Background

Successful implementation of modified cyanobacteria as hosts for industrial applications requires the development of a cyanobacterial chassis. The cyanobacterium Synechococcus sp. PCC 7002 embodies key attributes for an industrial host, including a fast growth rate and high salt, light, and temperature tolerances. This study addresses key limitations in the advancement of Synechococcus sp. PCC 7002 as an industrial chassis.

Results

Tools for genome integration were developed and characterized, including several putative neutral sites for genome integration. The minimum homology arm length for genome integration in Synechococcus sp. PCC 7002 was determined to be approximately 250 bp. Three fluorescent protein reporters (hGFP, Ypet, and mOrange) were characterized for gene expression, microscopy, and flow cytometry applications in Synechococcus sp. PCC 7002. Of these three proteins, the yellow fluorescent protein (Ypet) had the best optical properties for minimal interference with the native photosynthetic pigments and for detection using standard microscopy and flow cytometry optics. Twenty-five native promoters were characterized as tools for recombinant gene expression in Synechococcus sp. PCC 7002 based on previous RNA-seq results. This characterization included comparisons of protein and mRNA levels as well as expression under both continuous and diurnal light conditions. Promoters A2520 and A2579 were found to have strong expression in Synechococcus sp. PCC 7002 while promoters A1930, A1961, A2531, and A2813 had moderate expression. Promoters A2520 and A2813 showed more than twofold increases in gene expression under light conditions compared to dark, suggesting these promoters may be useful tools for engineering diurnal regulation.

Conclusions

The genome integration, fluorescent protein, and promoter tools developed in this study will help to advance Synechococcus sp. PCC 7002 as a cyanobacterial chassis. The long minimum homology arm length for Synechococcus sp. PCC 7002 genome integration indicates native exonuclease activity or a low efficiency of homologous recombination. Low correlation between transcript and protein levels in Synechococcus sp. PCC 7002 suggests that transcriptomic data are poor selection criteria for promoter tool development. Lastly, the conventional strategy of using promoters from photosynthetic operons as strong promoter tools is debunked, as promoters from hypothetical proteins (A2520 and A2579) were found to have much higher expression levels.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-016-0584-6) contains supplementary material, which is available to authorized users.

Improved Free Fatty Acid Production in Cyanobacteria with Synechococcus sp. PCC 7002 as Host

Microbial free fatty acids (FFAs) have been proposed as a potential feedstock for renewable energy. The ability to directly convert carbon dioxide into FFAs makes cyanobacteria ideal hosts for renewable FFA production. Previous metabolic engineering efforts using the cyanobacterial hosts Synechocystis sp. PCC 6803 and Synechococcus elongatus PCC 7942 have demonstrated this direct conversion of carbon dioxide into FFAs; however, FFA yields in these hosts are limited by the negative impact of FFA production on the host cell physiology. This work investigates the use of Synechococcus sp. PCC 7002 as a cyanobacterial host for FFA production. In comparison to S. elongatus PCC 7942, Synechococcus sp. PCC 7002 strains produced and excreted FFAs at similar concentrations but without the detrimental effects on host physiology. The enhanced tolerance to FFA production with Synechococcus sp. PCC 7002 was found to be temperature-dependent, with physiological effects such as reduced photosynthetic yield and decreased photosynthetic pigments observed at higher temperatures. Additional genetic manipulations were targeted for increased FFA production, including thioesterases and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO). Overexpression of non-native RuBisCO subunits (rbcLS) from a psbAI promoter resulted in more than a threefold increase in FFA production, with excreted FFA concentrations reaching >130 mg/L. This work illustrates the importance of host strain selection for cyanobacterial biofuel production and demonstrates that the FFA tolerance of Synechococcus sp. PCC 7002 can allow for high yields of excreted FFA.

RNA-Seq analysis and targeted mutagenesis for improved free fatty acid production in an engineered cyanobacterium

BACKGROUND

High-energy-density biofuels are typically derived from the fatty acid pathway, thus establishing free fatty acids (FFAs) as important fuel precursors. FFA production using photosynthetic microorganisms like cyanobacteria allows for direct conversion of carbon dioxide into fuel precursors. Recent studies investigating cyanobacterial FFA production have demonstrated the potential of this process, yet FFA production was also shown to have negative physiological effects on the cyanobacterial host, ultimately limiting high yields of FFAs.

RESULTS

Cyanobacterial FFA production was shown to generate reactive oxygen species (ROS) and lead to increased cell membrane permeability. To identify genetic targets that may mitigate these toxic effects, RNA-seq analysis was used to investigate the host response of Synechococcus elongatus PCC 7942. Stress response, nitrogen metabolism, photosynthesis, and protein folding genes were up-regulated during FFA production while genes involved in carbon and hydrogen metabolisms were down-regulated. Select genes were targeted for mutagenesis to confirm their role in mitigating FFA toxicity. Gene knockout of two porins and the overexpression of ROS-degrading proteins and hypothetical proteins reduced the toxic effects of FFA production, allowing for improved growth, physiology, and FFA yields. Comparative transcriptomics, analyzing gene expression changes associated with FFA production and other stress conditions, identified additional key genes involved in cyanobacterial stress response.

CONCLUSIONS

A total of 15 gene targets were identified to reduce the toxic effects of FFA production. While single-gene targeted mutagenesis led to minor increases in FFA production, the combination of these targeted mutations may yield additional improvement, advancing the development of high-energy-density fuels derived from cyanobacteria.

Physiological effects of free fatty acid production in genetically engineered Synechococcus elongatus PCC 7942

The direct conversion of carbon dioxide into biofuels by photosynthetic microorganisms is a promising alternative energy solution. In this study, a model cyanobacterium, Synechococcus elongatus PCC 7942, is engineered to produce free fatty acids (FFA), potential biodiesel precursors, via gene knockout of the FFA-recycling acyl-ACP synthetase and expression of a thioesterase for release of the FFA. Similar to previous efforts, the engineered strains produce and excrete FFA, but the yields are too low for large-scale production. While other efforts have applied additional metabolic engineering strategies in an attempt to boost FFA production, we focus on characterizing the engineered strains to identify the physiological effects that limit cell growth and FFA synthesis. The strains engineered for FFA-production show reduced photosynthetic yields, chlorophyll-a degradation, and changes in the cellular localization of the light-harvesting pigments, phycocyanin and allophycocyanin. Possible causes of these physiological effects are also identified. The addition of exogenous linolenic acid, a polyunsaturated FFA, to cultures of S. elongatus 7942 yielded a physiological response similar to that observed in the FFA-producing strains with only one notable difference. In addition, the lipid constituents of the cell and thylakoid membranes in the FFA-producing strains show changes in both the relative amounts of lipid components and the degree of saturation of the fatty acid side chains. These changes in lipid composition may affect membrane integrity and structure, the binding and diffusion of phycobilisomes, and the activity of membrane-bound enzymes including those involved in photosynthesis. Thus, the toxicity of unsaturated FFA and changes in membrane composition may be responsible for the physiological effects observed in FFA-producing S. elongatus 7942. These issues must be addressed to enable the high yields of FFA synthesis necessary for large-scale biofuel production.

Transcriptome profiling of a curdlan-producing Agrobacterium reveals conserved regulatory mechanisms of exopolysaccharide biosynthesis

Background

The ability to synthesize exopolysaccharides (EPS) is widespread among microorganisms, and microbial EPS play important roles in biofilm formation, pathogen persistence, and applications in the food and medical industries. Although it is well established that EPS synthesis is invariably in response to environmental cues, it remains largely unknown how various environmental signals trigger activation of the biochemical synthesis machinery.

Results

We report here the transcriptome profiling of Agrobacterium sp. ATCC 31749, a microorganism that produces large amounts of a glucose polymer known as curdlan under nitrogen starvation. Transcriptome analysis revealed a nearly 100-fold upregulation of the curdlan synthesis operon upon transition to nitrogen starvation, thus establishing the prominent role that transcriptional regulation plays in the EPS synthesis. In addition to known mechanisms of EPS regulation such as activation by c-di-GMP, we identify novel mechanisms of regulation in ATCC 31749, including RpoN-independent NtrC regulation and intracellular pH regulation by acidocalcisomes. Furthermore, we show evidence that curdlan synthesis is also regulated by conserved cell stress responses, including polyphosphate accumulation and the stringent response. In fact, the stringent response signal, pppGpp, appears to be indispensible for transcriptional activation of curdlan biosynthesis.

Conclusions

This study identifies several mechanisms regulating the synthesis of curdlan, an EPS with numerous applications. These mechanisms are potential metabolic engineering targets for improving the industrial production of curdlan from Agrobacterium sp. ATCC 31749. Furthermore, many of the genes identified in this study are highly conserved across microbial genomes, and we propose that the molecular elements identified in this study may serve as universal regulators of microbial EPS synthesis.

Engineered cyanobacteria: teaching an old bug new tricks

Cyanobacteria have played an important role in the development of the Earth and have long been studied as model organisms for photosynthesis and the circadian rhythm. Recent developments have led to increased interest in the use of engineered cyanobacteria for the production of protein and chemical products. This review highlights the genetic tools and strategies for manipulation of cyanobacteria as well as previous accomplishments in the development of engineered cyanobacteria for applied use. Particular attention is given to the engineering of cyanobacteria for biofuel production, including both hydrocarbon and hydrogen fuels. Genetic engineering efforts to enhance cyanobacterial fitness are reviewed with an emphasis on physiological improvements for large-scale production. Lastly, a future outlook on engineered cyanobacteria is presented, highlighting the future areas of focus and technical challenges in this field. With the uncertainty of future energy security, it is an exciting time in applied cyanobacterial research, but we must take the time to learn from these past accomplishments before we can capitalize on the potential of these photosynthetic microorganisms. 

Metabolic engineering of Agrobacterium sp. strain ATCC 31749 for production of an alpha-Gal epitope

Background

Oligosaccharides containing a terminal Gal-α1,3-Gal moiety are collectively known as α-Gal epitopes. α-Gal epitopes are integral components of several medical treatments under development, including flu and HIV vaccines as well as cancer treatments. The difficulty associated with synthesizing the α-Gal epitope hinders the development and application of these treatments due to the limited availability and high cost of the α-Gal epitope. This work illustrates the development of a whole-cell biocatalyst for synthesizing the α-Gal epitope, Gal-α1,3-Lac.

Results

Agrobacterium sp. ATCC 31749 was engineered to produce Gal-α1,3-Lac by the introduction of a UDP-galactose 4'-epimerase:α1,3-galactosyltransferase fusion enzyme. The engineered Agrobacterium synthesized 0.4 g/L of the α-Gal epitope. Additional metabolic engineering efforts addressed the factors limiting α-Gal epitope production, namely the availability of the two substrates, lactose and UDP-glucose. Through expression of a lactose permease, the intracellular lactose concentration increased by 60 to 110%, subsequently leading to an improvement in Gal-α1,3-Lac production. Knockout of the curdlan synthase gene increased UDP-glucose availability by eliminating the consumption of UDP-glucose for synthesis of the curdlan polysaccharide. With these additional engineering efforts, the final engineered strain synthesized approximately 1 g/L of Gal-α1,3-Lac.

Conclusions

The Agrobacterium biocatalyst developed in this work synthesizes gram-scale quantities of α-Gal epitope and does not require expensive cofactors or permeabilization, making it a useful biocatalyst for industrial production of the α-Gal epitope. Furthermore, the engineered Agrobacterium, with increased lactose uptake and improved UDP-glucose availability, is a promising host for the production of other medically-relevant oligosaccharides.