High-precision chemical quantum sensing in flowing monodisperse microdroplets.

A method is presented for high-precision chemical detection that integrates quantum sensing with droplet microfluidics. Using nanodiamonds (ND) with fluorescent nitrogen-vacancy (NV) centers as quantum sensors, rapidly flowing microdroplets containing analyte molecules are analyzed. A noise-suppressed mode of optically detected magnetic resonance is enabled by pairing controllable flow with microwave control of NV electronic spins, to detect analyte-induced signals of a few hundredths of a percent of the ND fluorescence.

Corn stover variability drives differences in bisabolene production by engineered Rhodotorula toruloides.

Unlabelled: Microbial conversion of lignocellulosic biomass represents an alternative route for production of biofuels and bioproducts. While researchers have mostly focused on engineering strains such as Rhodotorula toruloides for better bisabolene production as a sustainable aviation fuel, less is known about the impact of the feedstock heterogeneity on bisabolene production. Critical material attributes like feedstock composition, nutritional content, and inhibitory compounds can all influence bioconversion.

Matching diverse feedstocks to conversion processes for the future bioeconomy.

A wide variety of wasted or underutilized organic feedstocks can be leveraged to build a sustainable bioeconomy, ranging from crop residues to food processor residues and municipal wastes. Leveraging these feedstocks is both high-risk and high-reward. Converting mixed, variable, and/or highly contaminated feedstocks can pose engineering and economic challenges.

Engineering Rhodosporidium toruloides for production of 3-hydroxypropionic acid from lignocellulosic hydrolysate.

Microbial production of valuable bioproducts is a promising route towards green and sustainable manufacturing. The oleaginous yeast, Rhodosporidium toruloides, has emerged as an attractive host for the production of biofuels and bioproducts from lignocellulosic hydrolysates. 3-hydroxypropionic acid (3HP) is an attractive platform molecule that can be used to produce a wide range of commodity chemicals.

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.

Perspectives for self-driving labs in synthetic biology.

Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. While there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single target for affecting the incredibly wide repertoire of biological cell behavior.

Engineering Pseudomonas putida for efficient aromatic conversion to bioproduct using high throughput screening in a bioreactor.

Pseudomonas putida KT2440 is an emerging biomanufacturing host amenable for use with renewable carbon streams including aromatics such as para-coumarate. We used a pooled transposon library disrupting nearly all (4,778) non-essential genes to characterize this microbe under common stirred-tank bioreactor parameters with quantitative fitness assays. Assessing differential fitness values by monitoring changes in mutant strain abundance identified 33 gene mutants with improved fitness across multiple stirred-tank bioreactor formats.

Further engineering of R. toruloides for the production of terpenes from lignocellulosic biomass.

Background: Mitigation of climate change requires that new routes for the production of fuels and chemicals be as oil-independent as possible. The microbial conversion of lignocellulosic feedstocks into terpene-based biofuels and bioproducts represents one such route. This work builds upon previous demonstrations that the single-celled carotenogenic basidiomycete, Rhodosporidium toruloides, is a promising host for the production of terpenes from lignocellulosic hydrolysates.

Machine learning for metabolic engineering: A review.

Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production. We also include practical advice for the practitioner in terms of data management, algorithm libraries, computational resources, and important non-technical issues.

Genome-scale metabolic rewiring improves titers rates and yields of the non-native product indigoidine at scale.

High titer, rate, yield (TRY), and scalability are challenging metrics to achieve due to trade-offs between carbon use for growth and production. To achieve these metrics, we take the minimal cut set (MCS) approach that predicts metabolic reactions for elimination to couple metabolite production strongly with growth. We compute MCS solution-sets for a non-native product indigoidine, a sustainable pigment, in Pseudomonas putida KT2440, an emerging industrial microbe.

Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation.

Background: Despite the latest advancements in metabolic engineering for genome editing and characterization of host performance, the successful development of robust cell factories used for industrial bioprocesses and accurate prediction of the behavior of microbial systems, especially when shifting from laboratory-scale to industrial conditions, remains challenging. To increase the probability of success of a scale-up process, data obtained from thoroughly performed studies mirroring cellular responses to typical large-scale stimuli may be used to derive crucial information to better understand potential implications of large-scale cultivation on strain performance. This study assesses the feasibility to employ a barcoded yeast deletion library to assess genome-wide strain fitness across a simulated industrial fermentation regime and aims to understand the genetic basis of changes in strain physiology during industrial fermentation, and the corresponding roles these genes play in strain performance.

Production of ent-kaurene from lignocellulosic hydrolysate in Rhodosporidium toruloides.

Background: Rhodosporidium toruloides has emerged as a promising host for the production of bioproducts from lignocellulose, in part due to its ability to grow on lignocellulosic feedstocks, tolerate growth inhibitors, and co-utilize sugars and lignin-derived monomers. Ent-kaurene derivatives have a diverse range of potential applications from therapeutics to novel resin-based materials.

Results: The Design, Build, Test, and Learn (DBTL) approach was employed to engineer production of the non-native diterpene ent-kaurene in R.

Correction to: Production efficiency of the bacterial non-ribosomal peptide indigoidine relies on the respiratory metabolic state in S. cerevisiae.

Following publication of the original article [1], the authors have noted that the standard curve in Additional file 1: Figure S7 is incorrect.

Engineering Robust Production Microbes for Large-Scale Cultivation.

Systems biology and synthetic biology are increasingly used to examine and modulate complex biological systems. As such, many issues arising during scaling-up microbial production processes can be addressed using these approaches. We review differences between laboratory-scale cultures and larger-scale processes to provide a perspective on those strain characteristics that are especially important during scaling.

Production efficiency of the bacterial non-ribosomal peptide indigoidine relies on the respiratory metabolic state in S. cerevisiae.

Background: Beyond pathway engineering, the metabolic state of the production host is critical in maintaining the efficiency of cellular production. The biotechnologically important yeast Saccharomyces cerevisiae adjusts its energy metabolism based on the availability of oxygen and carbon sources. This transition between respiratory and non-respiratory metabolic state is accompanied by substantial modifications of central carbon metabolism, which impact the efficiency of metabolic pathways and the corresponding final product titers.

Short-chain ketone production by engineered polyketide synthases in Streptomyces albus.

Microbial production of fuels and commodity chemicals has been performed primarily using natural or slightly modified enzymes, which inherently limits the types of molecules that can be produced. Type I modular polyketide synthases (PKSs) are multi-domain enzymes that can produce unique and diverse molecular structures by combining particular types of catalytic domains in a specific order. This catalytic mechanism offers a wealth of engineering opportunities.

Simultaneous application of predictive model and least cost formulation can substantially benefit biorefineries outside Corn Belt in United States: A case study in Florida.

Previously, a predictive model was developed to identify optimal blends of expensive high-quality and cheaper low-quality feedstocks for a given geographical location that can deliver high sugar yields. In this study, the optimal process conditions were tested for application at commercially-relevant higher biomass loadings. We observed lower sugar yields but 100% conversion to ethanol from a blend that contained only 20% high-quality feedstock.

Xylose induces cellulase production in .

Background: Lignocellulosic biomass is an important resource for renewable production of biofuels and bioproducts. Enzymes that deconstruct this biomass are critical for the viability of biomass-based biofuel production processes. Current commercial enzyme mixtures have limited thermotolerance.

A bacterial pioneer produces cellulase complexes that persist through community succession.

Cultivation of microbial consortia provides low-complexity communities that can serve as tractable models to understand community dynamics. Time-resolved metagenomics demonstrated that an aerobic cellulolytic consortium cultivated from compost exhibited community dynamics consistent with the definition of an endogenous heterotrophic succession. The genome of the proposed pioneer population, 'Candidatus Reconcilibacillus cellulovorans', possessed a gene cluster containing multidomain glycoside hydrolases (GHs).

a new platform organism for conversion of lignocellulose into terpene biofuels and bioproducts.

Background: Economical conversion of lignocellulosic biomass into biofuels and bioproducts is central to the establishment of a robust bioeconomy. This requires a conversion host that is able to both efficiently assimilate the major lignocellulose-derived carbon sources and divert their metabolites toward specific bioproducts.

Results: In this study, the carotenogenic yeast was examined for its ability to convert lignocellulose into two non-native sesquiterpenes with biofuel (bisabolene) and pharmaceutical (amorphadiene) applications.

Predictive modeling to de-risk bio-based manufacturing by adapting to variability in lignocellulosic biomass supply.

Commercial-scale bio-refineries are designed to process 2000tons/day of single lignocellulosic biomass. Several geographical areas in the United States generate diverse feedstocks that, when combined, can be substantial for bio-based manufacturing. Blending multiple feedstocks is a strategy being investigated to expand bio-based manufacturing outside Corn Belt.

Scale-up and process integration of sugar production by acidolysis of municipal solid waste/corn stover blends in ionic liquids.

Background: Lignocellulosic biorefineries have tonnage and throughput requirements that must be met year round and there is no single feedstock available in any given region that is capable of meeting the price and availability demands of the biorefineries scheduled for deployment. Significant attention has been historically given to agriculturally derived feedstocks; however, a diverse range of wastes, including municipal solid wastes (MSW), also have the potential to serve as feedstocks for the production of advanced biofuels and have not been extensively studied. In addition, ionic liquid (IL) pretreatment with certain ILs is receiving great interest as a potential process that enables fractionation of a wide range of feedstocks.

Blending municipal solid waste with corn stover for sugar production using ionic liquid process.

Municipal solid waste (MSW) represents an attractive cellulosic resource for sustainable fuel production. However, its heterogeneity is the major barrier to efficient conversion to biofuels. MSW paper mix was generated and blended with corn stover (CS).

Engineering and two-stage evolution of a lignocellulosic hydrolysate-tolerant Saccharomyces cerevisiae strain for anaerobic fermentation of xylose from AFEX pretreated corn stover.

The inability of the yeast Saccharomyces cerevisiae to ferment xylose effectively under anaerobic conditions is a major barrier to economical production of lignocellulosic biofuels. Although genetic approaches have enabled engineering of S. cerevisiae to convert xylose efficiently into ethanol in defined lab medium, few strains are able to ferment xylose from lignocellulosic hydrolysates in the absence of oxygen.