Synthetic Biology Applications in Industrial Microbiology

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With the ability to perform a multitude of unique and complex chemical transformations, microorganisms have long been the “workhorses” of many industrial processes. However, in addition to exploiting the utility of naturally evolved phenotypes, the principles, strategies, and tools of

With the ability to perform a multitude of unique and complex chemical transformations, microorganisms have long been the “workhorses” of many industrial processes. However, in addition to exploiting the utility of naturally evolved phenotypes, the principles, strategies, and tools of synthetic biology are now being applied to facilitate the engineering of tailor-made microbes capable of tackling some of society's most important and toughest challenges. Fueled in part by exponentially increasing reservoirs of bioinformatic data and coupled with more robust and powerful tools for its processing, research in the past decade has brought about new and broadened perspectives of fundamental biological phenomena. The application of said insight is now beginning to unlock the unprecedented potential of synthetic biology in biotechnology, as well as its considerable promise for addressing previously unsolved global challenges. For example, within the realm of industrial microbiology, progress in the field of synthetic biology has enabled the development of new biosynthetic pathways for the production of renewable fuels and chemicals, programmable logic controls to regulate and optimize complex cellular functions, and robust microbes for the destruction of harmful environmental contaminants. In this Research Topic, a collection of articles—including original research, reviews, and mini-reviews—from leading investigators in the synthetic biology community are presented to capture the current state, recent progress, and over-arching challenges associated with integrating synthetic biology with industrial microbiology and biotechnology.

Date Created
2014-08-26
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Integrated Metagenomic and Metatranscriptomic Analyses of Microbial Communities in the Meso- and Bathypelagic Realm of North Pacific Ocean

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Although emerging evidence indicates that deep-sea water contains an untapped reservoir of high metabolic and genetic diversity, this realm has not been studied well compared with surface sea water. The study provided the first integrated meta-genomic and -transcriptomic analysis of

Although emerging evidence indicates that deep-sea water contains an untapped reservoir of high metabolic and genetic diversity, this realm has not been studied well compared with surface sea water. The study provided the first integrated meta-genomic and -transcriptomic analysis of the microbial communities in deep-sea water of North Pacific Ocean. DNA/RNA amplifications and simultaneous metagenomic and metatranscriptomic analyses were employed to discover information concerning deep-sea microbial communities from four different deep-sea sites ranging from the mesopelagic to pelagic ocean. Within the prokaryotic community, bacteria is absolutely dominant (~90%) over archaea in both metagenomic and metatranscriptomic data pools. The emergence of archaeal phyla Crenarchaeota, Euryarchaeota, Thaumarchaeota, bacterial phyla Actinobacteria, Firmicutes, sub-phyla Betaproteobacteria, Deltaproteobacteria, and Gammaproteobacteria, and the decrease of bacterial phyla Bacteroidetes and Alphaproteobacteria are the main composition changes of prokaryotic communities in the deep-sea water, when compared with the reference Global Ocean Sampling Expedition (GOS) surface water. Photosynthetic Cyanobacteria exist in all four metagenomic libraries and two metatranscriptomic libraries. In Eukaryota community, decreased abundance of fungi and algae in deep sea was observed. RNA/DNA ratio was employed as an index to show metabolic activity strength of microbes in deep sea. Functional analysis indicated that deep-sea microbes are leading a defensive lifestyle.

Date Created
2013-10-11
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Single-Cell Analysis Reveals Early Manifestation of Cancerous Phenotype in Pre-Malignant Esophageal Cells

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Cellular heterogeneity plays a pivotal role in a variety of functional processes in vivo including carcinogenesis. However, our knowledge about cell-to-cell diversity and how differences in individual cells manifest in alterations at the population level remains very limited mainly due

Cellular heterogeneity plays a pivotal role in a variety of functional processes in vivo including carcinogenesis. However, our knowledge about cell-to-cell diversity and how differences in individual cells manifest in alterations at the population level remains very limited mainly due to the lack of appropriate tools enabling studies at the single-cell level. We present a study on changes in cellular heterogeneity in the context of pre-malignant progression in response to hypoxic stress. Utilizing pre-malignant progression of Barrett’s esophagus (BE) as a disease model system we studied molecular mechanisms underlying the progression from metaplastic to dysplastic (pre-cancerous) stage. We used newly developed methods enabling measurements of cell-to-cell differences in copy numbers of mitochondrial DNA, expression levels of a set of mitochondrial and nuclear genes involved in hypoxia response pathways, and mitochondrial membrane potential. In contrast to bulk cell studies reported earlier, our study shows significant differences between metaplastic and dysplastic BE cells in both average values and single-cell parameter distributions of mtDNA copy numbers, mitochondrial function, and mRNA expression levels of studied genes. Based on single-cell data analysis, we propose that mitochondria may be one of the key factors in pre-malignant progression in BE.

Date Created
2013-10-08
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Microbe Observation and Cultivation Array (MOCA) for Cultivating and Analyzing Environmental Microbiota

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Background: The use of culture-independent nucleic acid techniques, such as ribosomal RNA gene cloning library analysis, has unveiled the tremendous microbial diversity that exists in natural environments. In sharp contrast to this great achievement is the current difficulty in cultivating the

Background: The use of culture-independent nucleic acid techniques, such as ribosomal RNA gene cloning library analysis, has unveiled the tremendous microbial diversity that exists in natural environments. In sharp contrast to this great achievement is the current difficulty in cultivating the majority of bacterial species or phylotypes revealed by molecular approaches. Although recent new technologies such as metagenomics and metatranscriptomics can provide more functionality information about the microbial communities, it is still important to develop the capacity to isolate and cultivate individual microbial species or strains in order to gain a better understanding of microbial physiology and to apply isolates for various biotechnological applications.

Results: We have developed a new system to cultivate bacteria in an array of droplets. The key component of the system is the microbe observation and cultivation array (MOCA), which consists of a Petri dish that contains an array of droplets as cultivation chambers. MOCA exploits the dominance of surface tension in small amounts of liquid to spontaneously trap cells in well-defined droplets on hydrophilic patterns. During cultivation, the growth of the bacterial cells across the droplet array can be monitored using an automated microscope, which can produce a real-time record of the growth. When bacterial cells grow to a visible microcolony level in the system, they can be transferred using a micropipette for further cultivation or analysis.

Conclusions: MOCA is a flexible system that is easy to set up, and provides the sensitivity to monitor growth of single bacterial cells. It is a cost-efficient technical platform for bioassay screening and for cultivation and isolation of bacteria from natural environments.

Date Created
2013-01-09
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Comparative Genomic and Transcriptomic Analysis Revealed Genetic Characteristics Related to Solvent Formation and Xylose Utilization in Clostridium Acetobutylicum EA 2018

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Background: Clostridium acetobutylicum, a gram-positive and spore-forming anaerobe, is a major strain for the fermentative production of acetone, butanol and ethanol. But a previously isolated hyper-butanol producing strain C. acetobutylicum EA 2018 does not produce spores and has greater capability of

Background: Clostridium acetobutylicum, a gram-positive and spore-forming anaerobe, is a major strain for the fermentative production of acetone, butanol and ethanol. But a previously isolated hyper-butanol producing strain C. acetobutylicum EA 2018 does not produce spores and has greater capability of solvent production, especially for butanol, than the type strain C. acetobutylicum ATCC 824.

Results: Complete genome of C. acetobutylicum EA 2018 was sequenced using Roche 454 pyrosequencing. Genomic comparison with ATCC 824 identified many variations which may contribute to the hyper-butanol producing characteristics in the EA 2018 strain, including a total of 46 deletion sites and 26 insertion sites. In addition, transcriptomic profiling of gene expression in EA 2018 relative to that of ATCC824 revealed expression-level changes of several key genes related to solvent formation. For example, spo0A and adhEII have higher expression level, and most of the acid formation related genes have lower expression level in EA 2018. Interestingly, the results also showed that the variation in CEA_G2622 (CAC2613 in ATCC 824), a putative transcriptional regulator involved in xylose utilization, might accelerate utilization of substrate xylose.

Conclusions: Comparative analysis of C. acetobutylicum hyper-butanol producing strain EA 2018 and type strain ATCC 824 at both genomic and transcriptomic levels, for the first time, provides molecular-level understanding of non-sporulation, higher solvent production and enhanced xylose utilization in the mutant EA 2018. The information could be valuable for further genetic modification of C. acetobutylicum for more effective butanol production.

Date Created
2011-02-02
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Transcriptome and metabolic profiling of premalignant progression in Barrett's esophagus

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Cell-cell interactions in a microenvironment under stress conditions play a critical role in pathogenesis and pre-malignant progression. Hypoxia is a central factor in carcinogenesis, which induces selective pressure in this process. Understanding the role of intercellular communications and cellular adaptation

Cell-cell interactions in a microenvironment under stress conditions play a critical role in pathogenesis and pre-malignant progression. Hypoxia is a central factor in carcinogenesis, which induces selective pressure in this process. Understanding the role of intercellular communications and cellular adaptation to hypoxia can help discover new cancer biosignatures and more effective diagnostic and therapeutic strategies. This dissertation presents a study on transcriptomic and metabolic profiling of pre-malignant progression of Barrett's esophagus. It encompasses two methodology developments and experimental findings of two related studies. To integrate phenotype and genotype measurements, a minimally invasive method was developed for selectively retrieving single adherent cells from cell cultures. Selected single cells can be harvested by a combination of mechanical force and biochemical treatment after phenotype measurements and used for end-point assays. Furthermore, a method was developed for analyzing expression levels of ten genes in individual mammalian cells with high sensitivity and reproducibility without the need of pre-amplifying cDNA. It is inexpensive and compatible with most of commercially available RT-qPCR systems, which warrants a wide applicability of the method to gene expression analysis in single cells. In the first study, the effect of intercellular interactions was investigated between normal esophageal epithelial and dysplastic Barrett's esophagus cells on gene expression levels and cellular functions. As a result, gene expression levels in dysplastic cells were found to be affected to a significantly larger extent than in the normal esophageal epithelial cells. These differentially expressed genes are enriched in cellular movement, TGFβ and EGF signaling networks. Heterotypic interactions between normal and dysplastic cells can change cellular motility and inhibit proliferation in both normal and dysplastic cells. In the second study, alterations in gene transcription levels and metabolic phenotypes between hypoxia-adapted cells and age-matched normoxic controls representing four different stages of pre-malignant progression in Barrett's esophagus were investigated. Through differential gene expression analysis and mitochondrial membrane potential measurements, evidence of clonal evolution induced by hypoxia selection pressure in metaplastic and high-grade dysplastic cells was found. These discoveries on cell-cell interactions and hypoxia adaptations provide a deeper insight into the dynamic evolutionary process in pre-malignant progression of Barrett's esophagus.
Date Created
2014
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Engineering cyanobacteria to convert carbon dioxide to building blocks for renewable plastics

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The production of monomer compounds for synthesizing plastics has to date been largely restricted to the petroleum-based chemical industry and sugar-based microbial fermentation, limiting its sustainability and economic feasibility. Cyanobacteria have, however, become attractive microbial factories to produce renewable fuels

The production of monomer compounds for synthesizing plastics has to date been largely restricted to the petroleum-based chemical industry and sugar-based microbial fermentation, limiting its sustainability and economic feasibility. Cyanobacteria have, however, become attractive microbial factories to produce renewable fuels and chemicals directly from sunlight and CO2. To explore the feasibility of photosynthetic production of (S)- and (R)-3-hydroxybutyrate (3HB), building-block monomers for synthesizing the biodegradable plastics polyhydroxyalkanoates and precursors to fine chemicals, synthetic metabolic pathways have been constructed, characterized and optimized in the cyanobacterium Synechocystis sp. PCC 6803 (hereafter Synechocystis 6803). Both types of 3HB molecules were produced and readily secreted from Synechocystis cells without over-expression of transporters. Additional inactivation of the competing PHB biosynthesis pathway further promoted the 3HB production. Analysis of the intracellular acetyl-CoA and anion concentrations in the culture media indicated that the phosphate consumption during the photoautotrophic growth and the concomitant elevated acetyl-CoA pool acted as a key driving force for 3HB biosynthesis in Synechocystis. Fine-tuning of the gene expression levels via strategies, including tuning gene copy numbers, promoter engineering and ribosome binding site optimization, proved critical to mitigating metabolic bottlenecks and thus improving the 3HB production. One of the engineered Synechocystis strains, namely R168, was able to produce (R)-3HB to a cumulative titer of ~1600 mg/L, with a peak daily productivity of ~200 mg/L, using light and CO2 as the sole energy and carbon sources, respectively. Additionally, in order to establish a high-efficiency transformation protocol in cyanobacterium Synechocystis 6803, methyltransferase-encoding genes were cloned and expressed to pre-methylate the exogenous DNA before Synechocystis transformation. Eventually, the transformation efficiency was increased by two orders of magnitude in Synechocystis. This research has demonstrated the use of cyanobacteria as cell factories to produce 3HB directly from light and CO2, and developed new synthetic biology tools for cyanobacteria.
Date Created
2014
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Integrated -omics study of deep-sea microbial community and new Pseudoalteromonas isolate

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This thesis research focuses on phylogenetic and functional studies of microbial communities in deep-sea water, an untapped reservoir of high metabolic and genetic diversity of microorganisms. The presence of photosynthetic cyanobacteria and diatoms is an interesting and unexpected discovery during

This thesis research focuses on phylogenetic and functional studies of microbial communities in deep-sea water, an untapped reservoir of high metabolic and genetic diversity of microorganisms. The presence of photosynthetic cyanobacteria and diatoms is an interesting and unexpected discovery during a 16S ribosomal rRNA-based community structure analyses for microbial communities in the deep-sea water of the Pacific Ocean. Both RT-PCR and qRT-PCR approaches were employed to detect expression of the genes involved in photosynthesis of photoautotrophic organisms. Positive results were obtained and further proved the functional activity of these detected photosynthetic microbes in the deep-sea. Metagenomic and metatranscriptomic data was obtained, integrated, and analyzed from deep-sea microbial communities, including both prokaryotes and eukaryotes, from four different deep-sea sites ranging from the mesopelagic to the pelagic ocean. The RNA/DNA ratio was employed as an index to show the strength of metabolic activity of deep-sea microbes. These taxonomic and functional analyses of deep-sea microbial communities revealed a `defensive' life style of microbial communities living in the deep-sea water. Pseudoalteromonas sp.WG07 was subjected to transcriptomic analysis by application of RNA-Seq technology through the transcriptomic annotation using the genomes of closely related surface-water strain Pseudoalteromonas haloplanktis TAC125 and sediment strain Pseudoalteromonas sp. SM9913. The transcriptome survey and related functional analysis of WG07 revealed unique features different from TAC125 and SM9913 and provided clues as to how it adapted to its environmental niche. Also, a comparative transcriptomic analysis of WG07 revealed transcriptome changes between its exponential and stationary growing phases.
Date Created
2013
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Single cell RT-qPCR based ocean environmental sensing device development

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This thesis research focuses on developing a single-cell gene expression analysis method for marine diatom Thalassiosira pseudonana and constructing a chip level tool to realize the single cell RT-qPCR analysis. This chip will serve as a conceptual foundation for future

This thesis research focuses on developing a single-cell gene expression analysis method for marine diatom Thalassiosira pseudonana and constructing a chip level tool to realize the single cell RT-qPCR analysis. This chip will serve as a conceptual foundation for future deployable ocean monitoring systems. T. pseudonana, which is a common surface water microorganism, was detected in the deep ocean as confirmed by phylogenetic and microbial community functional studies. Six-fold copy number differences between 23S rRNA and 23S rDNA were observed by RT-qPCR, demonstrating the moderate functional activity of detected photosynthetic microbes in the deep ocean including T. pseudonana. Because of the ubiquity of T. pseudonana, it is a good candidate for an early warning system for ocean environmental perturbation monitoring. This early warning system will depend on identifying outlier gene expression at the single-cell level. An early warning system based on single-cell analysis is expected to detect environmental perturbations earlier than population level analysis which can only be observed after a whole community has reacted. Preliminary work using tube-based, two-step RT-qPCR revealed for the first time, gene expression heterogeneity of T. pseudonana under different nutrient conditions. Heterogeneity was revealed by different gene expression activity for individual cells under the same conditions. This single cell analysis showed a skewed, lognormal distribution and helped to find outlier cells. The results indicate that the geometric average becomes more important and representative of the whole population than the arithmetic average. This is in contrast with population level analysis which is limited to arithmetic averages only and highlights the value of single cell analysis. In order to develop a deployable sensor in the ocean, a chip level device was constructed. The chip contains surface-adhering droplets, defined by hydrophilic patterning, that serve as real-time PCR reaction chambers when they are immersed in oil. The chip had demonstrated sensitivities at the single cell level for both DNA and RNA. The successful rate of these chip-based reactions was around 85%. The sensitivity of the chip was equivalent to published microfluidic devices with complicated designs and protocols, but the production process of the chip was simple and the materials were all easily accessible in conventional environmental and/or biology laboratories. On-chip tests provided heterogeneity information about the whole population and were validated by comparing with conventional tube based methods and by p-values analysis. The power of chip-based single-cell analyses were mainly between 65-90% which were acceptable and can be further increased by higher throughput devices. With this chip and single-cell analysis approaches, a new paradigm for robust early warning systems of ocean environmental perturbation is possible.
Date Created
2013
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Integrative analyses of diverse biological data sources

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The technology expansion seen in the last decade for genomics research has permitted the generation of large-scale data sources pertaining to molecular biological assays, genomics, proteomics, transcriptomics and other modern omics catalogs. New methods to analyze, integrate and visualize these

The technology expansion seen in the last decade for genomics research has permitted the generation of large-scale data sources pertaining to molecular biological assays, genomics, proteomics, transcriptomics and other modern omics catalogs. New methods to analyze, integrate and visualize these data types are essential to unveil relevant disease mechanisms. Towards these objectives, this research focuses on data integration within two scenarios: (1) transcriptomic, proteomic and functional information and (2) real-time sensor-based measurements motivated by single-cell technology. To assess relationships between protein abundance, transcriptomic and functional data, a nonlinear model was explored at static and temporal levels. The successful integration of these heterogeneous data sources through the stochastic gradient boosted tree approach and its improved predictability are some highlights of this work. Through the development of an innovative validation subroutine based on a permutation approach and the use of external information (i.e., operons), lack of a priori knowledge for undetected proteins was overcome. The integrative methodologies allowed for the identification of undetected proteins for Desulfovibrio vulgaris and Shewanella oneidensis for further biological exploration in laboratories towards finding functional relationships. In an effort to better understand diseases such as cancer at different developmental stages, the Microscale Life Science Center headquartered at the Arizona State University is pursuing single-cell studies by developing novel technologies. This research arranged and applied a statistical framework that tackled the following challenges: random noise, heterogeneous dynamic systems with multiple states, and understanding cell behavior within and across different Barrett's esophageal epithelial cell lines using oxygen consumption curves. These curves were characterized with good empirical fit using nonlinear models with simple structures which allowed extraction of a large number of features. Application of a supervised classification model to these features and the integration of experimental factors allowed for identification of subtle patterns among different cell types visualized through multidimensional scaling. Motivated by the challenges of analyzing real-time measurements, we further explored a unique two-dimensional representation of multiple time series using a wavelet approach which showcased promising results towards less complex approximations. Also, the benefits of external information were explored to improve the image representation.
Date Created
2011
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