High-Throughput Characterization and Optimization of Polyamide Hydrolase Activity Using Open Port Sampling Interface Mass Spectrometry

Enzymatic biodegradation of polymers, such as polyamides (PA), has the potential to cost-effectively reduce plastic waste, but enhancements in degradation efficiency are needed. Engineering enzymes through directed evolution is one pathway toward identification of critical domains needed for improving activity. However, screening such enzymatic libraries (100s-to-1000s of samples) is time-consuming. Here we demonstrate the use of robotic autosampler (PAL) and immediate drop on demand technology (I.DOT) liquid handling systems coupled with open-port sampling interface-mass spectrometry (OPSI-MS) to screen for PA6 and PA66 hydrolysis by 6-aminohexanoate-oligomer endo-hydrolase (nylon hydrolase, NylC) in a high-throughput (8-20 s/sample) manner. The OPSI-MS technique required minimal sample preparation and was amenable to 96-well plate formats for automated processing. Enzymatic hydrolysis of PA characteristically produced soluble linear oligomer products that could be identified by OPSI-MS. Incubation temperatures and times were optimized for PA6 (65 °C, 24 h) and PA66 (75 °C, 24 h) over 108 experiments. In addition, the I.DOT/OPSI-MS quantified production of PA6 linear dimer (8.3 ± 1.6 μg/mL) and PA66 linear monomer (13.5 ± 1.5 μg/mL) by NylC with a lower limit of detection of 0.029 and 0.032 μg/mL, respectively. For PA6 and PA66, linear oligomer production corresponded to 0.096 ± 0.018% and 0.204 ± 0.028% conversion of dry pellet mass, respectively. The developed methodology is expected to be utilized to assess enzymatic hydrolysis of engineered enzyme libraries, comprising hundreds to thousands of individual samples.

PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.

Sphingobium lignivorans sp. nov., isolated from river sediment downstream of a paper mill

A bacterial isolate, B1D3A^T, was isolated from river sediment collected from the Hiwassee River near Calhoun, TN, by enrichment culturing with a model 5-5' lignin dimer, dehydrodivanillate, as its sole carbon source. B1D3A^T was also shown to utilize several model lignin-derived monomers and dimers as sole carbon sources in a variety of minimal media. Cells were Gram-stain-negative, aerobic, motile, rod-shaped and formed yellow/cream-coloured colonies on rich agar. Optimal growth occurred at 30 °C, pH 7-8, and in the absence of NaCl. The major fatty acids of B1D3A^T were C_18 : 1 ω7c and C_17 : 1 ω6c. The predominant hydroxy fatty acids were C_14 : 0 2-OH and C_15 : 0 2-OH. The polar lipid profile consisted of a mixture of phosphatidylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, phosphatidyldimethylethanolamine and sphingoglycolipid. B1D3A^T contained spermidine as the only major polyamine. The major isoprenoid quinone was Q-10 with minor amounts of Q-9 and Q-11. The genomic DNA G+C content of B1D3A^T was 65.6 mol%. Phylogenetic analyses based on 16S rRNA gene sequences and coding sequences of 49 core, universal genes defined by Clusters of Orthologous Groups gene families indicated that B1D3A^T was a member of the genus Sphingobium. B1D3A^T was most closely related to Sphingobium sp. SYK-6, with a 100 % 16S rRNA gene sequence similarity. B1D3A^T showed 78.1-89.9 % average nucleotide identity and 19.5-22.2% digital DNA-DNA hybridization identity with other type strains from the genus Sphingobium. On the basis of phenotypic and genotypic properties and phylogenetic inference, strain B1D3A^T should be classified as representing a novel species of the genus Sphingobium, for which the name Sphingobium lignivorans sp. nov. is proposed. The type strain is strain B1D3A^T (ATCC TSD-279^T=DSM 111877^T).

The effect of bacterial growth strategies on plasmid transfer and naphthalene degradation for bioremediation

Mobilizable plasmids are extra-chromosomal, circular DNA that have contributed to the rapid evolution of bacterial genomes and have been used in environmental, biotechnological, and medicinal applications. Degradative plasmids with genetic capabilities to degrade organic contaminants, such as polycyclic aromatic hydrocarbons (PAHs), have the potential to be useful for more environmentally friendly and cost-effective remediation technologies compared to existing physical remediation methods. Genetic bioaugmentation, the addition of catabolic genes into well-adapted communities via plasmid transfer (conjugation), is being explored as a remediation approach that is sustainable and long-lasting. Here, we explored the effect of the ecological growth strategies of plasmid donors and recipients on conjugation and naphthalene degradation of two PAH-degrading plasmids, pNL1 and NAH7. Overall, both pNL1 and NAH7 showed conjugation preferences towards a slow-growing ecological growth strategy, except when NAH7 was in a mixed synthetic community. These conjugation preferences were partially described by a combination of growth strategy, GC content, and phylogenetic relatedness. Further, removal of naphthalene via plasmid-mediated degradation was consistently higher in a community consisting of recipients with a slow-growing ecological growth strategy compared to a mixed community or a community consisting of fast-growing ecological growth strategy. Understanding plasmid conjugation and degradative preferences has the capacity to influence future remediation technology design and has broad implications in biomedical, environmental, and health fields.

Microbial assimilation of lignin-derived aromatic compounds and conversion to value-added products

Lignin is an abundant and sustainable source of aromatic compounds that can be converted to value-added products. However, lignin is underutilized, since depolymerization produces a complex mixture of aromatic compounds that is difficult to convert to a single product. Microbial conversion of mixed aromatic substrates provides a potential solution to this conversion challenge. Recent advances have expanded the range of lignin-derived aromatic substrates that can be assimilated and demonstrated efficient conversion via central metabolism to new potential products. The development of additional non-model microbial hosts and genetic tools for these hosts have accelerated engineering efforts. However, yields with real depolymerized lignin are still low, and additional work will be required to achieve viable conversion processes.

Pseudodesulfovibrio mercurii sp. nov., a mercury-methylating bacterium isolated from sediment

The sulfate-reducing, mercury-methylating strain ND132^T was isolated from the brackish anaerobic bottom sediments of Chesapeake Bay, USA. Capable of high levels of mercury (Hg) methylation, ND132^T has been widely used as a model strain to study the process and to determine the genetic basis of Hg methylation. Originally called Desulfovibrio desulfuricans ND132^T on the basis of an early partial 16S rRNA sequence, the strain has never been formally described. Phylogenetic and physiological traits place this strain within the genus Pseudodesulfovibrio, in the recently reclassified phylum Desulfobacterota (formerly Deltaproteobacteria). ND132^T is most closely related to Pseudodesulfovibrio hydrargyri BerOc1^T and Pseudodesulfovibrio indicus J2^T. Analysis of average nucleotide identity (ANI) of whole-genome sequences showed roughly 88 % ANI between P. hydrargyri BerOc1^T and ND132^T, and 84 % similarity between ND132^T and P. indicus J2^T. These cut-off scores <95 %, along with a multi-gene phylogenetic analysis of members of the family Desulfovibrionacea, and differences in physiology indicate that all three strains represent separate species. The Gram-stain-negative cells are vibrio-shaped, motile and not sporulated. ND132^T is a salt-tolerant mesophile with optimal growth in the laboratory at 32 °C, 2 % salinity, and pH 7.8. The DNA G+C content of the genomic DNA is 65.2 %. It is an incomplete oxidizer of short chain fatty acids, using lactate, pyruvate and fumarate with sulfate or sulfite as the terminal electron acceptors. ND132^T can respire fumarate using pyruvate as an electron donor. The major fatty acids are iso-C_15 : 0, anteiso-C_15 : 0, iso-C_17 : 0, iso-C_17 : 1ω9c and anteiso-C_17 : 0. We propose the classification of strain ND132^T (DSM 110689, ATCC TSD-224) as the type strain Pseudodesulfovibrio mercurii sp. nov.

Complete Genome Sequences of Four Natural Pseudomonas Isolates That Catabolize a Wide Range of Aromatic Compounds Relevant to Lignin Valorization

Many soil microorganisms have evolved catabolic strategies to utilize phenolic compounds arising from depolymerized lignin. We report the complete genome sequences of four Pseudomonas sp. isolates that demonstrated robust growth on a wide range of aromatic monomers and dimers that are relevant to the valorization of lignin into value-added chemicals.

Horizontal transfer of a pathway for coumarate catabolism unexpectedly inhibits purine nucleotide biosynthesis

A microbe's ecological niche and biotechnological utility are determined by its specific set of co-evolved metabolic pathways. The acquisition of new pathways, through horizontal gene transfer or genetic engineering, can have unpredictable consequences. Here we show that two different pathways for coumarate catabolism failed to function when initially transferred into Escherichia coli. Using laboratory evolution, we elucidated the factors limiting activity of the newly acquired pathways and the modifications required to overcome these limitations. Both pathways required host mutations to enable effective growth with coumarate, but the necessary mutations differed. In one case, a pathway intermediate inhibited purine nucleotide biosynthesis, and this inhibition was relieved by single amino acid replacements in IMP dehydrogenase. A strain that natively contains this coumarate catabolism pathway, Acinetobacter baumannii, is resistant to inhibition by the relevant intermediate, suggesting that natural pathway transfers have faced and overcome similar challenges. Molecular dynamics simulation of the wild type and a representative single-residue mutant provide insight into the structural and dynamic changes that relieve inhibition. These results demonstrate how deleterious interactions can limit pathway transfer, that these interactions can be traced to specific molecular interactions between host and pathway, and how evolution or engineering can alleviate these limitations.

Genetic Selection for Small Molecule Production in Competitive Microfluidic Droplets

Biosensors can be used to screen or select for small molecule production in engineered microbes. However, mutations to the biosensor that interfere with accurate signal transduction are common, producing an excess of false positives. Strategies have been developed to avoid this limitation by physically separating the production pathway and biosensor, but these approaches have only been applied to screens, not selections. We have developed a novel biosensor-mediated selection strategy using competition between cocultured bacteria. When applied to the biosynthesis of cis,cis-muconate, we show that this strategy yields a selective advantage to producer strains that outweighs the costs of production. By encapsulating the competitive cocultures into microfluidic droplets, we successfully enriched the muconate-producing strains from a large population of control nonproducers. Facile selections for small molecule production will increase testing throughput for engineered microbes and allow for the rapid optimization of novel metabolic pathways.

Hardwood Tree Genomics: Unlocking Woody Plant Biology

Woody perennial angiosperms (i.e., hardwood trees) are polyphyletic in origin and occur in most angiosperm orders. Despite their independent origins, hardwoods have shared physiological, anatomical, and life history traits distinct from their herbaceous relatives. New high-throughput DNA sequencing platforms have provided access to numerous woody plant genomes beyond the early reference genomes of Populus and Eucalyptus, references that now include willow and oak, with pecan and chestnut soon to follow. Genomic studies within these diverse and undomesticated species have successfully linked genes to ecological, physiological, and developmental traits directly. Moreover, comparative genomic approaches are providing insights into speciation events while large-scale DNA resequencing of native collections is identifying population-level genetic diversity responsible for variation in key woody plant biology across and within species. Current research is focused on developing genomic prediction models for breeding, defining speciation and local adaptation, detecting and characterizing somatic mutations, revealing the mechanisms of gender determination and flowering, and application of systems biology approaches to model complex regulatory networks underlying quantitative traits. Emerging technologies such as single-molecule, long-read sequencing is being employed as additional woody plant species, and genotypes within species, are sequenced, thus enabling a comparative ("evo-devo") approach to understanding the unique biology of large woody plants. Resource availability, current genomic and genetic applications, new discoveries and predicted future developments are illustrated and discussed for poplar, eucalyptus, willow, oak, chestnut, and pecan.

Identification of parallel and divergent optimization solutions for homologous metabolic enzymes

Metabolic pathway assembly typically involves the expression of enzymes from multiple organisms in a single heterologous host. Ensuring that each enzyme functions effectively can be challenging, since many potential factors can disrupt proper pathway flux. Here, we compared the performance of two enzyme homologs in a pathway engineered to allow Escherichia coli to grow on 4-hydroxybenzoate (4-HB), a byproduct of lignocellulosic biomass deconstruction. Single chromosomal copies of the 4-HB 3-monooxygenase genes pobA and praI, from Pseudomonas putida KT2440 and Paenibacillus sp. JJ-1B, respectively, were introduced into a strain able to metabolize protocatechuate (PCA), the oxidation product of 4-HB. Neither enzyme initially supported consistent growth on 4-HB. Experimental evolution was used to identify mutations that improved pathway activity. For both enzymes, silent mRNA mutations were identified that increased enzyme expression. With pobA, duplication of the genes for PCA metabolism allowed growth on 4-HB. However, with praI, growth required a mutation in the 4-HB/PCA transporter pcaK that increased intracellular concentrations of 4-HB, suggesting that flux through PraI was limiting. These findings demonstrate the value of directed evolution strategies to rapidly identify and overcome diverse factors limiting enzyme activity.

Transfer of a Catabolic Pathway for Chloromethane in Methylobacterium Strains Highlights Different Limitations for Growth with Chloromethane or with Dichloromethane

Chloromethane (CM) is an ozone-depleting gas, produced predominantly from natural sources, that provides an important carbon source for microbes capable of consuming it. CM catabolism has been difficult to study owing to the challenging genetics of its native microbial hosts. Since the pathways for CM catabolism show evidence of horizontal gene transfer, we reproduced this transfer process in the laboratory to generate new CM-catabolizing strains in tractable hosts. We demonstrate that six putative accessory genes improve CM catabolism, though heterologous expression of only one of the six is strictly necessary for growth on CM. In contrast to growth of Methylobacterium strains with the closely related compound dichloromethane (DCM), we find that chloride export does not limit growth on CM and, in general that the ability of a strain to grow on DCM is uncorrelated with its ability to grow on CM. This heterologous expression system allows us to investigate the components required for effective CM catabolism and the factors that limit effective catabolism after horizontal transfer.

Controlled Measurement and Comparative Analysis of Cellular Components in E. coli Reveals Broad Regulatory Changes in Response to Glucose Starvation

How do bacteria regulate their cellular physiology in response to starvation? Here, we present a detailed characterization of Escherichia coli growth and starvation over a time-course lasting two weeks. We have measured multiple cellular components, including RNA and proteins at deep genomic coverage, as well as lipid modifications and flux through central metabolism. Our study focuses on the physiological response of E. coli in stationary phase as a result of being starved for glucose, not on the genetic adaptation of E. coli to utilize alternative nutrients. In our analysis, we have taken advantage of the temporal correlations within and among RNA and protein abundances to identify systematic trends in gene regulation. Specifically, we have developed a general computational strategy for classifying expression-profile time courses into distinct categories in an unbiased manner. We have also developed, from dynamic models of gene expression, a framework to characterize protein degradation patterns based on the observed temporal relationships between mRNA and protein abundances. By comparing and contrasting our transcriptomic and proteomic data, we have identified several broad physiological trends in the E. coli starvation response. Strikingly, mRNAs are widely down-regulated in response to glucose starvation, presumably as a strategy for reducing new protein synthesis. By contrast, protein abundances display more varied responses. The abundances of many proteins involved in energy-intensive processes mirror the corresponding mRNA profiles while proteins involved in nutrient metabolism remain abundant even though their corresponding mRNAs are down-regulated.

Bacteria frequently experience starvation conditions in their natural environments. Yet how they modify their physiology in response to these conditions remains poorly understood. Here, we performed a detailed, two-week starvation experiment in E. coli. We exhaustively monitored changes in cellular components, such as RNA and protein abundances, over time. We subsequently compared and contrasted these measurements using novel computational approaches we developed specifically for analyzing gene-expression time-course data. Using these approaches, we could identify systematic trends in the E. coli starvation response. In particular, we found that cells systematically limit mRNA and protein production, degrade proteins involved in energy-intensive processes, and maintain or increase the amount of proteins involved in energy production. Thus, the bacteria assume a cellular state in which their ongoing energy use is limited while they are poised to take advantage of any nutrients that may become available.

Effective use of a horizontally-transferred pathway for dichloromethane catabolism requires post-transfer refinement

When microbes acquire new abilities through horizontal gene transfer, the genes and pathways must function under conditions with which they did not coevolve. If newly-acquired genes burden the host, their utility will depend on further evolutionary refinement of the recombinant strain. We used laboratory evolution to recapitulate this process of transfer and refinement, demonstrating that effective use of an introduced dichloromethane degradation pathway required one of several mutations to the bacterial host that are predicted to increase chloride efflux. We then used this knowledge to identify parallel, beneficial mutations that independently evolved in two natural dichloromethane-degrading strains. Finally, we constructed a synthetic mobile genetic element carrying both the degradation pathway and a chloride exporter, which preempted the adaptive process and directly enabled effective dichloromethane degradation across diverse Methylobacterium environmental isolates. Our results demonstrate the importance of post-transfer refinement in horizontal gene transfer, with potential applications in bioremediation and synthetic biology.

Synthetic RNA switches for yeast metabolic engineering: screening recombinant enzyme libraries

Directed evolution is a powerful technique for increasing the activity of poorly active enzymes, for example when an enzyme is engineered to accept a new substrate or function in a new environment. Since enzyme activity greatly depends on the enzyme environment, screening should be performed under the same conditions as the ultimate application of the enzyme. When an enzyme will be used in live cells, RNA biosensors offer a powerful and flexible method of linking the desired phenotype, production of a small molecule of interest, to an easily measured phenotype, such as fluorescence. Here, we describe methods for screening enzyme libraries using an RNA biosensor, showing examples from the evolution of a P450 monooxygenase.

Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways

Cells are filled with biosensors, molecular systems that measure the state of the cell and respond by regulating host processes. In much the same way that an engineer would monitor a chemical reactor, the cell uses these sensors to monitor changing intracellular environments and produce consistent behavior despite the variable environment. While natural systems derive a clear benefit from pathway regulation, past research efforts in engineering cellular metabolism have focused on introducing new pathways and removing existing pathway regulation. Synthetic biology is a rapidly growing field that focuses on the development of new tools that support the design, construction, and optimization of biological systems. Recent advances have been made in the design of genetically-encoded biosensors and the application of this class of molecular tools for optimizing and regulating heterologous pathways. Biosensors to cellular metabolites can be taken directly from natural systems, engineered from natural sensors, or constructed entirely in vitro. When linked to reporters, such as antibiotic resistance markers, these metabolite sensors can be used to report on pathway productivity, allowing high-throughput screening for pathway optimization. Future directions will focus on the application of biosensors to introduce feedback control into metabolic pathways, providing dynamic control strategies to increase the efficient use of cellular resources and pathway reliability.