Synthesis cost-optimal targeted mutant protein libraries.

Protein variant libraries produced by site-directed mutagenesis are a useful tool utilized by protein engineers to explore variants with potentially improved properties, such as activity and stability. These libraries are commonly built by selecting residue positions and alternative beneficial mutations for each position. All possible combinations are then constructed and screened, by incorporating degenerate codons at mutation sites. These degenerate codons often encode additional unwanted amino acids or even STOP codons. Our study aims to take advantage of annealing based recombination of oligonucleotides during synthesis and utilize multiple degenerate codons per mutation site to produce targeted protein libraries devoid of unwanted variants. Toward this goal we created an algorithm to calculate the minimum number of degenerate codons necessary to specify any given amino acid set, and a dynamic programming method that uses this algorithm to optimally partition a DNA target sequence with degeneracies into overlapping oligonucleotides, such that the total cost of synthesis of the target mutant protein library is minimized. Computational experiments show that, for a modest increase in DNA synthesis costs, beneficial variant yields in produced mutant libraries are increased by orders of magnitude, an effect particularly pronounced in large combinatorial libraries.

Microbial chassis design and engineering for production of gamma-aminobutyric acid.

Gamma-aminobutyric acid (GABA) is a non-protein amino acid which is widely applied in agriculture and pharmaceutical additive industries. GABA is synthesized from glutamate through irreversible α-decarboxylation by glutamate decarboxylase. Recently, microbial synthesis has become an inevitable trend to produce GABA due to its sustainable characteristics. Therefore, reasonable microbial platform design and metabolic engineering strategies for improving production of GABA are arousing a considerable attraction. The strategies concentrate on microbial platform optimization, fermentation process optimization, rational metabolic engineering as key metabolic pathway modification, promoter optimization, site-directed mutagenesis, modular transporter engineering, and dynamic switch systems application. In this review, the microbial producers for GABA were summarized, including lactic acid bacteria, Corynebacterium glutamicum, and Escherichia coli, as well as the efficient strategies for optimizing them to improve the production of GABA.

BioCloneBot: A versatile, low-cost, and open-source automated liquid handler.

Liquid handler systems can provide significant benefits to researchers by automating laboratory work, however, their unaffordable price provides a steep barrier to entry. Therefore, we provide the BioCloneBot, a versatile, low-cost, and open-source automated liquid handler. This system can be easily built with 3D-printed parts and readily available commercial components. The BioCloneBot is highly adaptive to user needs and facilitates various liquid handling tasks in research and diagnostics. Its user-friendly interface and programmable nature make it suitable for a wide range of applications, from small-scale experiments to larger laboratory setups. By utilizing BioCloneBot, researchers and scientists can streamline their liquid handling processes without the financial constraints posed by traditional systems. In this paper, we detail the design, construction, and validation of BioCloneBot, showcasing its precise control, accuracy, and repeatability in various liquid handling tasks. The open-source nature of the system encourages collaboration and customization, enabling researchers to contribute and adapt the technology to specific experimental requirements.

Building the bioeconomy: A targeted assessment approach to identifying biobased technologies, challenges and opportunities.

The authors explore opportunities, challenges, and strategies to translate and responsibly scale innovative biobased technologies to build more sustainable bioeconomies. The pandemic and other recent disruptions increased exposure to issues of resilience and regional imbalance, highlighting a need for production and consumption regimes centred more on local biobased resources and dispersed production. The authors review potential biobased technology strategies and identify promising and feasible options for the United Kingdom. Initial landscape and bibliometric analysis identified 50 potential existing and emerging biobased technologies, which were assessed for their ability to fulfil requirements related to biobased production, national applicability, and economic-, societal-, and environmental-benefits, leading to identification of 18 promising biobased production technologies. Further analysis and focus-group discussion with industrial, governmental, academic, agricultural, and social stakeholders, identified three technology clusters for targeted assessment, drawing on cellulose-, lignin-, and seaweed feedstocks. Case studies were developed for each cluster, addressing conversations around sustainable management, use of biomass feedstocks, and associated environmental-, social-, and economic challenges. Cases are presented with discussion of insights and implications for policy. The approach presented is put forward as a scalable assessment method that can be useful in prompting, informing, and advancing discussion and deliberation on opportunities and challenges for biobased transformations.

Measuring the economic efficiency of laboratory automation in biotechnology.

Laboratory automation with robot-assisted processes enhances synthetic biology, but its economic impact on projects is uncertain. We have proposed an experiment price index (EPI) for a quantitative comparison of factors in time, cost, and sample numbers, helping measure the efficiency of laboratory automation in synthetic biology and biomolecular engineering.

DuBA.flow─A Low-Cost, Long-Read Amplicon Sequencing Workflow for the Validation of Synthetic DNA Constructs.

Modern biological science, especially synthetic biology, relies heavily on the construction of DNA elements, often in the form of plasmids. Plasmids are used for a variety of applications, including the expression of proteins for subsequent purification, the expression of heterologous pathways for the production of valuable compounds, and the study of biological functions and mechanisms. For all applications, a critical step after the construction of a plasmid is its sequence validation. The traditional method for sequence determination is Sanger sequencing, which is limited to approximately 1000 bp per reaction. Here, we present a highly scalable in-house method for rapid validation of amplified DNA sequences using long-read Nanopore sequencing. We developed two-step amplicon and transposase strategies to provide maximum flexibility for dual barcode sequencing. We also provide an automated analysis pipeline to quickly and reliably analyze sequencing results and provide easy-to-interpret results for each sample. The user-friendly DuBA.flow start-to-finish pipeline is widely applicable. Furthermore, we show that construct validation using DuBA.flow can be performed by barcoded colony PCR amplicon sequencing, thus accelerating research.

Efficient design of synthetic gene circuits under cell-to-cell variability.

BACKGROUND: Synthetic biologists use and combine diverse biological parts to build systems such as genetic circuits that perform desirable functions in, for example, biomedical or industrial applications. Computer-aided design methods have been developed to help choose appropriate network structures and biological parts for a given design objective. However, they almost always model the behavior of the network in an average cell, despite pervasive cell-to-cell variability. RESULTS: Here, we present a computational framework and an efficient algorithm to guide the design of synthetic biological circuits while accounting for cell-to-cell variability explicitly. Our design method integrates a Non-linear Mixed-Effects (NLME) framework into a Markov Chain Monte-Carlo (MCMC) algorithm for design based on ordinary differential equation (ODE) models. The analysis of a recently developed transcriptional controller demonstrates first insights into design guidelines when trying to achieve reliable performance under cell-to-cell variability. CONCLUSION: We anticipate that our method not only facilitates the rational design of synthetic networks under cell-to-cell variability, but also enables novel applications by supporting design objectives that specify the desired behavior of cell populations.

A New Role for Yeast Cells in Health and Nutrition: Antioxidant Power Assessment.

As the use of antioxidant compounds in the domains of health, nutrition and well-being is exponentially rising, there is an urgent need to quantify antioxidant power quickly and easily, ideally within living cells. We developed an Anti Oxidant Power in Yeast (AOPY) assay which allows for the quantitative measurement of the Reactive Oxygen Species (ROS) and free-radical scavenging effects of various molecules in a high-throughput compatible format. Key parameters for Saccharomyces cerevisiae were investigated, and the optimal values were determined for each of them. The cell density in the reaction mixture was fixed at 0.6; the concentration of the fluorescent biosensor (TO) was found to be optimal at 64 µM, and the strongest response was observed for exponentially growing cells. Our optimized procedure allows accurate quantification of the antioxidant effect in yeast of well-known antioxidant molecules: resveratrol, epigallocatechin gallate, quercetin and astaxanthin added in the culture medium. Moreover, using a genetically engineered carotenoid-producing yeast strain, we realized the proof of concept of the usefulness of this new assay to measure the amount of ß-carotene directly inside living cells, without the need for cell lysis and purification.

A reaction network scheme for hidden Markov model parameter learning.

With a view towards artificial cells, molecular communication systems, molecular multiagent systems and federated learning, we propose a novel reaction network scheme (termed the Baum-Welch (BW) reaction network) that learns parameters for hidden Markov models (HMMs). All variables including inputs and outputs are encoded by separate species. Each reaction in the scheme changes only one molecule of one species to one molecule of another. The reverse change is also accessible but via a different set of enzymes, in a design reminiscent of futile cycles in biochemical pathways. We show that every positive fixed point of the BW algorithm for HMMs is a fixed point of the reaction network scheme, and vice versa. Furthermore, we prove that the 'expectation' step and the 'maximization' step of the reaction network separately converge exponentially fast and compute the same values as the E-step and the M-step of the BW algorithm. We simulate example sequences, and show that our reaction network learns the same parameters for the HMM as the BW algorithm, and that the log-likelihood increases continuously along the trajectory of the reaction network.

Vibrio natriegens genome-scale modeling reveals insights into halophilic adaptations and resource allocation.

Vibrio natriegens is a Gram-negative bacterium with an exceptional growth rate that has the potential to become a standard biotechnological host for laboratory and industrial bioproduction. Despite this burgeoning interest, the current lack of organism-specific qualitative and quantitative computational tools has hampered the community's ability to rationally engineer this bacterium. In this study, we present the first genome-scale metabolic model (GSMM) of V. natriegens. The GSMM (iLC858) was developed using an automated draft assembly and extensive manual curation and was validated by comparing predicted yields, central metabolic fluxes, viable carbon substrates, and essential genes with empirical data. Mass spectrometry-based proteomics data confirmed the translation of at least 76% of the enzyme-encoding genes predicted to be expressed by the model during aerobic growth in a minimal medium. iLC858 was subsequently used to carry out a metabolic comparison between the model organism Escherichia coli and V. natriegens, leading to an analysis of the model architecture of V. natriegens' respiratory and ATP-generating system and the discovery of a role for a sodium-dependent oxaloacetate decarboxylase pump. The proteomics data were further used to investigate additional halophilic adaptations of V. natriegens. Finally, iLC858 was utilized to create a Resource Balance Analysis model to study the allocation of carbon resources. Taken together, the models presented provide useful computational tools to guide metabolic engineering efforts in V. natriegens.

A hypothetical model of multi-layered cost-effective wastewater treatment plant integrating microbial fuel cell and nanofiltration technology: A comprehensive review on wastewater treatment and sustainable remediation.

Wastewater management has emerged as an uprising concern that demands immediate attention from environmentalists worldwide. Indiscriminate and irrational release of industrial and poultry wastes, sewage, pharmaceuticals, mining, pesticides, fertilizers, dyes and radioactive wastes, contribute immensely to water pollution. This has led to the aggravation of critical health concerns as evident from the uprising trends of antimicrobial resistance, and the presence of xenobiotics and pollutant traces in humans and animals due to the process of biomagnification. Therefore, the development of reliable, affordable and sustainable technologies for the supply of fresh water is the need of the hour. Conventional wastewater treatment often involves physical, chemical, and biological processes to remove solids from the effluent, including colloids, organic matter, nutrients, and soluble pollutants (metals, organics). Synthetic biology has been explored in recent years, incorporating both biological and engineering concepts to refine existing wastewater treatment technologies. In addition to outlining the benefits and drawbacks of the current technologies, this review addresses novel wastewater treatment techniques, especially those using dedicated rational design and engineering of organisms and their constituent parts. Furthermore, the review hypothesizes designing a multi-bedded wastewater treatment plant that is highly cost-efficient, sustainable and requires easy installation and handling. The novel setup envisages removing all the major wastewater pollutants, providing water fit for household, irrigation and storage purposes.

Metabolic Engineering of Escherichia coli for High-Level Production of (R)-Acetoin from Low-Cost Raw Materials.

Acetoin is an important four-carbon platform chemical with versatile applications. Optically pure (R)-acetoin is more valuable than the racemate as it can be applied in the asymmetric synthesis of optically active α-hydroxy ketone derivatives, pharmaceuticals, and liquid crystal composites. As a cytotoxic solvent, acetoin at high concentrations severely limits culture performance and impedes the acetoin yield of cell factories. In this study, putative genes that may improve the resistance to acetoin for Escherichia coli were screened. To obtain a high-producing strain, the identified acetoin-resistance gene was overexpressed, and the synthetic pathway of (R)-acetoin was strengthened by optimizing the copy number of the key genes. The engineered E. coli strain GXASR-49RSF produced 81.62 g/L (R)-acetoin with an enantiomeric purity of 96.5% in the fed-batch fermentation using non-food raw materials in a 3-L fermenter. Combining the systematic approach developed in this study with the use of low-cost feedstock showed great potential for (R)-acetoin production via this cost-effective biotechnological process.

Cell-Free Dot Blot: an Ultra-Low-Cost and Practical Immunoassay Platform for Detection of Anti-SARS-CoV-2 Antibodies in Human and Animal Sera.

Since its emergence in late 2019, the coronavirus disease 2019 (COVID-19) pandemic has caused severe disruption to key aspects of human life globally and highlighted the need for timely, adaptive, and accessible pandemic response strategies. Here, we introduce the cell-free dot blot (CFDB) method, a practical and ultra-low-cost immune diagnostic platform capable of rapid response and mass immunity screening for the current and future pandemics. Similar in mechanism to the widely used enzyme-linked immunosorbent assays (ELISAs), our method is novel and advantageous in that (i) it uses linear DNA to produce the target viral antigen fused to a SpyTag peptide in a cell-free expression system without the need for traditional cloning and antigen purification, (ii) it uses SpyCatcher2-Apex2, an Escherichia coli-produced peroxidase conjugate as a universal secondary detection reagent, obviating the need for commercial or sophisticated enzyme conjugates, and (iii) sera are spotted directly on a nitrocellulose membrane, enabling a simple "dipping" mechanism for downstream incubation and washing steps, as opposed to individual processing of wells in a multiwell plate. To demonstrate the utility of our method, we performed CFDB to detect anti-severe acute respiratory syndrome coronavirus 2 nucleocapsid protein antibodies in precharacterized human sera (23 negative and 36 positive for COVID-19) and hamster sera (16 negative and 36 positive for COVID-19), including independent testing at a collaborating laboratory, and we show assay performance comparable to that of conventional ELISAs. At a similar capacity to 96-well plate ELISA kits, one CFDB assay costs only ~$3 USD. We believe that CFDB can become a valuable pandemic response tool for adaptive and accessible sero-surveillance in human and animal populations. IMPORTANCE The recent COVID-19 pandemic has highlighted the need for diagnostic platforms that are rapidly adaptable, affordable, and accessible globally, especially for low-resource settings. To address this need, we describe the development and functional validation of a novel immunoassay technique termed the cell-free dot blot (CFDB) method. Based on the principles of cell-free synthetic biology and alternative dot blotting procedures, our CFDB immunoassay is designed to provide for timely, practical, and low-cost responses to existing and emerging public health threats, such as the COVID-19 pandemic, at a similar throughput and comparable performance as conventional ELISAs. Notably, the molecular detection reagents used in CFDB can be produced rapidly in-house, using established protocols and basic laboratory infrastructure, minimizing reliance on strained commercial reagents. In addition, the materials and imaging instruments required for CFDB are the same as those used for common Western blotting experiments, further expanding the reach of CFDB in decentralized facilities.

Research Progress in Heterologous Crocin Production.

Crocin is one of the most valuable components of the Chinese medicinal plant Crocus sativus and is widely used in the food, cosmetics, and pharmaceutical industries. Traditional planting of C. sativus is unable to fulfill the increasing demand for crocin in the global market, however, such that researchers have turned their attention to the heterologous production of crocin in a variety of hosts. At present, there are reports of successful heterologous production of crocin in Escherichia coli, Saccharomyces cerevisiae, microalgae, and plants that do not naturally produce crocin. Of these, the microalga Dunaliella salina, which produces high levels of ß-carotene, the substrate for crocin biosynthesis, is worthy of attention. This article describes the biosynthesis of crocin, compares the features of each heterologous host, and clarifies the requirements for efficient production of crocin in microalgae.

Unveiling Curvularia tuberculata-induced leaf anomalies in Rhododendron ferrugineum: implications in cultural-ecological conservation and harnessing microbial intervention in socio-economic advancement.

Introduction: The research focuses on Rhododendron ferrugineum L., Nepal's national flower and Uttarakhand's state tree, thriving in high-altitude mountain ecosystems. Methodology and Result: A study conducted in Himachal Pradesh (Latitude: N 31° 6' 2.0088", Longitude: E 77° 10' 29.9136") identified leaf anomalies resembling rust-like manifestations in R. ferrugineum. These anomalies were traced back to the pathogenic fungus Curvularia tuberculata, marking the first documented case of its impact on R. ferrugineum in India. Discussion: This discovery emphasizes the need for vigilant monitoring, disease management research, and conservation efforts to protect the cultural and ecological significance of this iconic shrub. Beyond its immediate findings, the study introduces a novel dimension to Indian flora by associating C. tuberculata with R. ferrugineum, historically linked to monocotyledonous crops. The research methodology combines traditional microscopic examination with advanced genomic sequencing and phylogenetic analysis, enhancing pathogen identification accuracy. Future prospect: In a broader context, this research aligns with the United Nations Sustainable Development Goals (SDGs) by highlighting the importance of environmental preservation, conservation, and sustainable management. It underscores the intricate interplay between biodiversity, cultural heritage, and the need for holistic solutions. Overall, this study calls for proactive measures to protect R. ferrugineum's cultural and ecological heritage and emphasizes the significance of interdisciplinary approaches in addressing emerging ecological threats.

Halomonas spp., as chassis for low-cost production of chemicals.

Halomonas spp. are the well-studied platform organisms or chassis for next-generation industrial biotechnology (NGIB) due to their contamination-resistant nature combined with their fast growth property. Several Halomonas spp. have been studied regarding their genomic information and molecular engineering approaches. Halomonas spp., especially Halomonas bluephagenesis, have been engineered to produce various biopolyesters such as polyhydroxyalkanoates (PHA), proteins including surfactants and enzymes, small molecular compounds including amino acids and derivates, as well as organic acids. This paper reviews all the progress reported in the last 10 years regarding this robust microbial cell factory. KEY POINTS: • Halomonas spp. are robust chassis for low-cost production of chemicals • Genomic information of some Halomonas spp. has been revealed • Molecular tools and approaches for Halomonas spp. have been developed • Halomonas spp. are becoming more and more important for biotechnology.

A rapid and standardized workflow for functional assessment of bacterial biosensors in fecal samples.

Gut metabolites are pivotal mediators of host-microbiome interactions and provide an important window on human physiology and disease. However, current methods to monitor gut metabolites rely on heavy and expensive technologies such as liquid chromatography-mass spectrometry (LC-MS). In that context, robust, fast, field-deployable, and cost-effective strategies for monitoring fecal metabolites would support large-scale functional studies and routine monitoring of metabolites biomarkers associated with pathological conditions. Living cells are an attractive option to engineer biosensors due to their ability to detect and process many environmental signals and their self-replicating nature. Here we optimized a workflow for feces processing that supports metabolite detection using bacterial biosensors. We show that simple centrifugation and filtration steps remove host microbes and support reproducible preparation of a physiological-derived media retaining important characteristics of human feces, such as matrix effects and endogenous metabolites. We measure the performance of bacterial biosensors for benzoate, lactate, anhydrotetracycline, and bile acids, and find that they are highly sensitive to fecal matrices. However, encapsulating the bacteria in hydrogel helps reduce this inhibitory effect. Sensitivity to matrix effects is biosensor-dependent but also varies between individuals, highlighting the need for case-by-case optimization for biosensors' operation in feces. Finally, by detecting endogenous bile acids, we demonstrate that bacterial biosensors could be used for future metabolite monitoring in feces. This work lays the foundation for the optimization and use of bacterial biosensors for fecal metabolites monitoring. In the future, our method could also allow rapid pre-prototyping of engineered bacteria designed to operate in the gut, with applications to in situ diagnostics and therapeutics.

Recent advances in genetic technology development of oleaginous yeasts.

As important chemical raw materials and potential nutritional supplements, microbial lipids play an important role in ensuring economic development, food security, and energy security. Compared with non-natural hosts, oleaginous yeasts exhibit obvious advantages in lipid yield and productivity and have great potential to be genetically engineered into an oil cell factory. The main bottleneck in the current oleaginous yeasts engineering is the lack of genetic manipulation tools. Fortunately, the rapid development of synthetic biology has provided numerous new approaches, resources, and ideas for the field. Most importantly, gene editing technology mediated by CRISPR/Cas systems has been successfully applied to some oleaginous yeasts, almost completely rewriting the development pattern of genetic manipulation technology applicable. This paper reviews recent progress in genetic technology with regard to oleaginous yeasts, with a special focus on transformation methods and genome editing tools, discussing the effects of some important genetic parts. KEY POINTS: •Contribution of microbiotechnology in food safety and biofuel by oleaginous yeasts. •Advancement of genetic manipulation and transformation for oleaginous yeasts.

Evaluation of existing guidelines for their adequacy for the food and feed risk assessment of microorganisms obtained through synthetic biology.

EFSA was asked by the European Commission to evaluate synthetic biology (SynBio) developments for agri-food use in the near future and to determine whether or not they are expected to constitute potential new hazards/risks. Moreover, EFSA was requested to evaluate the adequacy of existing guidelines for risk assessment of SynBio and if updated guidance is needed. The scope of this Opinion covers food and feed risk assessment, the variety of microorganisms that can be used in the food/feed chain and the whole spectrum of techniques used in SynBio. This Opinion complements a previously adopted Opinion with the evaluation of existing guidelines for the microbial characterisation and environmental risk assessment of microorganisms obtained through SynBio. The present Opinion confirms that microbial SynBio applications for food and feed use, with the exception of xenobionts, could be ready in the European Union in the next decade. New hazards were identified related to the use or production of unusual and/or new-to-nature components. Fifteen cases were selected for evaluating the adequacy of existing guidelines. These were generally adequate for assessing the product, the production process, nutritional and toxicological safety, allergenicity, exposure and post-market monitoring. The comparative approach and a safety assessment per se could be applied depending on the degree of familiarity of the SynBio organism/product with the non-genetically modified counterparts. Updated guidance is recommended for: (i) bacteriophages, protists/microalgae, (ii) exposure to plant protection products and biostimulants, (iii) xenobionts and (iv) feed additives for insects as target species. Development of risk assessment tools is recommended for assessing nutritional value of biomasses, influence of microorganisms on the gut microbiome and the gut function, allergenic potential of new-to-nature proteins, impact of horizontal gene transfer and potential risks of living cell intake. A further development towards a strain-driven risk assessment approach is recommended.

Evaluation of existing guidelines for their adequacy for the food and feed risk assessment of genetically modified plants obtained through synthetic biology.

Synthetic biology (SynBio) is an interdisciplinary field at the interface of molecular engineering and biology aiming to develop new biological systems and impart new functions to living cells, tissues and organisms. EFSA has been asked by the European Commission to evaluate SynBio developments in agri-food with the aim of identifying the adequacy and sufficiency of existing guidelines for risk assessment and determine if updated guidance is needed. In this context, the GMO Panel has previously adopted an Opinion evaluating the SynBio developments in agri-food/feed and the adequacy and sufficiency of existing guidelines for the molecular characterisation and environmental risk assessment of genetically modified plants (GMPs) obtained through SynBio and reaching the market in the next decade. Complementing the above, in this Opinion, the GMO Panel evaluated the adequacy and sufficiency of existing guidelines for the food and feed risk assessment of GMPs obtained through SynBio. Using selected hypothetical case studies, the GMO Panel did not identify novel potential hazards and risks that could be posed by food and feed from GMPs obtained through current and near future SynBio approaches; considers that the existing guidelines are adequate and sufficient in some Synbio applications; in other cases, existing guidelines may be just adequate and hence need updating; areas needing updating include those related to the safety assessment of new proteins and the comparative analysis. The GMO Panel recommends that future guidance documents provide indications on how to integrate the knowledge available from the SynBio design and modelling in the food and feed risk assessment and encourages due consideration to be given to food and feed safety aspects throughout the SynBio design process as a way to facilitate the risk assessment of SynBio GMPs and reduce the amount of data required.