The availability of biologically active nitrogen is a major determinant of agricultural crop growth and yield. While manufactured ammonia fertilizers are heavily used to combat soil infertility in developed countries, they are unfeasible for developing countries and contribute to greenhouse gas production and aquatic eutrophication, amongst other environmental concerns. Diazotrophic bacteria can naturally convert atmospheric nitrogen into ammonium; however, only legume species can establish and benefit from a symbiotic relationship with these microbes. Since current approaches to install large, refactored nitrogen-fixation pathways in eukaryotes or extend root-nodule symbiosis to non-legume crop species have had limited success, this research focuses on a novel solution for the nitrogen problem. Here we aim to convert free-living diazotrophic bacteria into primitive organelles residing within yeast cells. The candidate endosymbiont, Sinorhizobium meliloti, and Saccharomyces cerevisiae will be engineered to be metabolically dependent on one another. Thiamine-deficient S. meliloti will carry a synthetic plasmid expressing three SNARE-like proteins to prevent intracellular degradation by the host as well as a uracil permease that allows for metabolite exchange. The yeast strain will be auxotrophic for uracil and thiamine for the endosymbiont will be available for uptake from the cytosol. Using PEG-mediated cell fusion, S. meliloti will be engulfed by S. cerevisiae and retention of the endosymbionts will be evaluated by survival assays and fluorescence microscopy. Establishing a stable relationship between these two species represents the first step towards engineering a synthetic nitrogen-fixing organelle and ultimately towards the development of self-fertilizing plants.

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Efficient ways to produce single-stranded DNA are of great interest for diverse applications in molecular biology and nanotechnology. The flagship platform to replace the phosphoramidite synthesis process is envisioned to be template-independent catalysis by terminal deoxynucleotidyl transferase, although specific conditions are needed to achieve controllable DNA synthesis. Among template-directed methods, asymmetric PCR (aPCR) is suggested as a means to synthesize long ssDNA products, although several reports indicate that the initial optimization of aPCR is not easy and different ssDNAs cannot be produced using a single protocol. Here, we suggest considering in vitro transcription (IVT) using highly processive T7 RNA polymerase (T7 RNAP) as an alternative approach for isothermal synthesis of ssDNA. To achieve that, we engineered T7 RNA polymerase to incorporate deoxynucleotide triphosphates (dNTPs) so that ssDNA is produced directly by IVT. We performed in vitro evolution employing droplet microfluidics. Briefly, E. coli cells expressing mutant T7 RNAP variants were encapsulated in droplets together with lysis and IVT reagents, as well as dNTPs and a fluorescent reporter. After the in-droplet IVT assay, fluorescence-activated droplet sorting was used to enrich the variants able to produce transcripts utilizing dNTPs. We identified mutations V783M, V783L, V689Q, and G555L as novel T7 RNAP variants leading to relaxed substrate discrimination. Transcribed chimeric oligonucleotides were tested in PCR, and the quality of amplification products as well as fidelity of oligonucleotide synthesis were assessed by NGS. We concluded that enzymatically produced chimeric DNA transcripts contain significantly fewer deletions and insertions compared to chemically synthesized counterparts and can successfully serve as PCR primers, making the evolved enzymes superior for simple and cheap one-pot synthesis of multiple chimeric DNA oligonucleotides in parallel using a plethora of premixed templates.

Scalable information processing platforms, such as those that handle written language or computer code, have sparked technology innovation cycles that develop applications to sit on top of these base layers. While DNA holds promise to become the next major information medium, current workflows for engineering DNA, such as Gibson assembly and Golden Gate assembly, are idiosyncratic, slow, expensive, and difficult to scale. To reduce the operational friction and scale DNA engineering, BacStitch DNA, Inc. has developed a wholly in vivo DNA assembly technology platform that is simpler, more standardized, and more scalable than current technologies. Our platform combines bacterial conjugation, in vivo DNA cutting, and in vivo homologous recombination to seamlessly stitch blocks of DNA together on plasmids in large E. coli arrays or pools. We show that the BacStitch platform is capable of assembling DNA blocks that range from 200bp to 5kb into assemblies of at least 28kb at high throughput and fidelity. The BacStitch platform does not use in vitro annealing, polymerases, or nucleases, and early data indicate that it is relatively insensitive to DNA features that commonly reduce assembly fidelity, such as extreme GC content, homopolymers, and local repeats. Because assembly is stepwise, a growing construct can be “branched” to incorporate many variants at each assembly step. Multiple branching steps can be combined to create directed combinatorial libraries in arrays or pools. DNA blocks in cells are composable, and blocks can be easily reused in new assemblies, thereby creating a low-friction, low-cost programming environment for DNA engineering.

In the rapidly evolving field of synthetic biology, the ability to quickly iterate through Design-Build-Test-Learn (DBTL) cycles is pivotal for the development of novel proteins with enhanced functionalities. Industrial-scale protein engineering and gene editing techniques have simultaneously necessitated and fueled breakthroughs in highly multiplexed molecular biology. However, the growth rate of NGS data output has far-outpaced development of the technologies required to efficiently feed the NGS capacity now available, thus creating a new bottleneck in the DBTL cycle. To demonstrate how a lab can reduce this impediment, we show that starting from bacterial colonies, several thousand plasmids can be sequenced on a single Illumina NextSeq 2000 run and bioinformatic analysis completed by the next day. We leverage a scalable, modular pipeline that includes colony picking, liquid handling, DNA sequencing and bioinformatic analysis. Rolling Circle Amplification (RCA) or direct PCR from colonies is substituted for conventional bacterial culturing and plasmid purification. Integration of an auto-normalizing, one-step library preparation technology provides 6,144 indexes in a convenient 384-well, assay-ready configuration (384 wells x 16 plates). Our benchmarking comparison against other workflows demonstrate that this automated pipeline shortens the typical synthetic biology DBTL cycle from weeks down to hours. These new methods enable the sequencing of thousands of protein variants within 24 hours, providing a massive dataset for AI to learn from and predict promising protein designs with unprecedented speed and accuracy.

The intersection of technology and biology, known as TechBio, is reshaping the landscape of biotechnology. This poster will explore the evolving relationship between TechBio and traditional biotechnology, aiming to elucidate the nuanced connections and divergences that characterize these intertwined domains. As cutting-edge techniques from data-driven technology permeate drug discovery and patient care, the boundaries between TechBio and Biotech become increasingly blurred. Delving into the transformative impact of TechBio on healthcare and emphasizing how data-driven approaches are revolutionizing the industry, the poster will examine the convergence of biological insights with technological advancements, and shed light on the innovative solutions emerging at this dynamic interface.

Natural products are diverse molecules produced by living organisms which have a huge impact on our wellbeing. A vast number of potential therapeutics are available from research on natural products. Only a small fraction of these molecules with therapeutic potential from microbes, plants and marine organisms have been characterized and a lot more work needs to be done to explore the diverse sources and the characterization of new natural product(-like) compounds. A class of natural products are the Ribosomally Synthesized and Post-translationally Modified Peptides (RIPPs), which include lasso peptides among others. RiPPs are important candidates for bioengineering since they are encoded genetically, and their biosynthetic enzymes generally display a wide range of substrate tolerance. The bioengineering of the RiPPs is important because it has the capacity to address mass production issues which is often a major challenge especially in clinical trials. To explore the ability to use RiPP biosynthetic enzymes to make new natural product-like compounds we will develop a platform to ensure the substrate scope of a lasso peptide producing enzyme. To achieve this goal, we utilize a high throughput methodology in which yeast surface display of precursor peptides and deep sequencing are used to broadly examine the ability of the modifying enzyme to modify millions of different precursor peptides. This approach requires development of screening methods to identify if the displayed precursor peptide on the yeast cells is modified or not. This measurement will take advantage of the fact that the leader peptide is removed during lasso peptide modification by looking for the loss of the epitope tag genetically encoded on the peptide. The study will give us an unprecedented view of the scope of substrate tolerance of these enzymes and will guide our library development for use when screening for new biological activities.

1.27 million of global deaths were due to bacterial antimicrobial resistance (AMR) in 2019. The cause of the AMR related deaths include the extensive use of antibiotics in healthcare and livestock farming. For instance, 66% of antibiotics are used in livestock farming, contributing to 63,000 tons of antibiotics being used globally every year. Studies have shown that 40-90% of the ingested antibiotics were excreted and entered the wastewater treatment plants. However, only less than 10% of the antibiotics are degraded by the conventional wastewater treatment plants, not to mention only 8-10% of the wastewater is treated in low income countries with the highest usage of antibiotics for livestock farming.   Here, we propose a next-generation antibiotic contaminated wastewater treatment solution for the bio-circular economy. Antibiotics in wastewater are degraded by synthetic organisms with highly efficient antibiotic degrading enzymes, and the by-products would be converted to regenerate antibiotics or other useful chemicals.

Rising rates of obesity and diabetes have led consumers to desire low-calorie alternatives to common sugars such as sucrose, glucose, and fructose. Current alternative sweeteners lack palatability or are inaccessible due to cost. The naturally occurring but rare sugar allulose, also known as D-psicose, is non-nutritive, highly palatable, and carries the potential for a variety of culinary and therapeutic applications. The current method of production for allulose involves the cell-free enzymatic conversion of common monosaccharides such as glucose and fructose into allulose. Due to a lack of thermodynamic incentive towards allulose, these enzymatic pathways suffer from poor yield and a mixed product that is expensive to purify. In our study, we address these thermodynamic limitations by pairing the conversion of glucose to allulose with thermodynamically favorable phosphorylation/dephosphorylation reactions intrinsically found within living organisms. To accomplish this, we developed a biosynthetic production pathway within the model organism Escherichia coli using only increased expression of native genes and modifications to competing metabolic pathways. Our final strain produced 15.3 g L-1 of allulose, with a productivity of 2 g L-1 h-1 and yield of 62% under test tube conditions. Our ability to produce allulose cheaply, efficiently, and at high yield and purity will allow it to become more accessible to the food and pharmaceutical industries. Greater access will make zero-calorie, delicious foods more affordable for the general public, and will allow researchers to better understand its antihyperglycemic, antihyperlipidemic, antiparasitic, and antioxidant properties being studied today.

Synthetic Biology at the National Institutes of Health Leah Tolosa Croucher, PhD Program Officer, National Institutes of Health, National Center for Advancing Translational Science  The National Institutes of Health (NIH) has released a Notice of Special Interest (NOSI), NOT-EB-23-002, on “Synthetic Biology for Biomedical Applications”. This NOSI was released to encourage new applications to advance research activities relevant to synthetic biology. The overarching goals of this NOSI are to: • Develop tools and technologies to control and reprogram biological systems • Apply synthetic biology approaches for the development of biomedical technologies • Increase the fundamental understanding of synthetic biology concepts as they relate to human health • Gain fundamental biological knowledge through the application of synthetic biology approaches  Multiple NIH institutes and centers are involved in this NOSI including the National Center for Complementary and Integrative Health (NCCIH), the National Cancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI), the National Institute on Aging (NIA), the National Institute of Allergy and Infectious Diseases (NIAID), the National Institute of Biomedical Imaging and Bioengineering (NIBIB), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), and the National Institute of General Medical Sciences (NIGMS) among others. Several Notice of Funding Opportunities (NOFO) are listed in the website with the appropriate due dates.  The NIH Synthetic Biology Consortium is open to input from stakeholders on current needs in the field where the NIH can participate and provide further assistance. Do stop by at the poster presentation for a meet-and-greet.

PyxisTM is a turn-key solution that employs pre-trained large-data machine learning (ML) models to provide rapid, absolute untargeted analyte concentrations directly from raw liquid chromatography mass spectrometry (LC-MS) data. Pyxis thus provides a new capability for applications in synthetic biology and bioengineering, where determining concentrations for a broad set of metabolites and nutrients underlies advanced efforts in metabolic pathway engineering, host and process development, efficiency improvements, and waste minimization. Further, as Pyxis provides absolute concentrations for identified metabolites, it enables quantitative metabolomics (e.g., enzyme kinetics) and data that are inherently comparable across different experiments, sites, laboratories, and process scales.  Unlike conventional metabolomics technologies, Pyxis enables any LC-MS user to: (1) bypass the arduous elements of traditional metabolomics, such as LC method development, peak selection, integration, and per-analyte calibration; and (2) analyze cellular metabolites with sufficient breadth to elucidate biological function. A user with any level of scientific experience can implement a standardized sample preparation protocol and universal LC-MS method. Resultant raw LC-MS data are converted directly to analyte concentration via a cloud-implemented, pretrained ML model and accompanying web application software. No calibration curves, isotopologue reference standards, or even peak analysis and integration are required.  We assess here the absolute concentration accuracy and precision performance of Pyxis across a broad array of untargeted analytes relevant to synthetic biology and microbiome applications. Benchmarking plates, comprising 800 sample wells, more than 336,000 distinct compound-sample pairs, and four representative matrices, were prepared with known underlying analyte concentrations. Benchmarking samples were analyzed on three distinct LC/MS systems over the course of a week (<4 days of acquisition time per instrument). The resulting raw MS files were used to obtain absolute concentration results via the Pyxis cloud-implemented ML model and software. Pyxis accuracy and reproducibility were assessed by comparing the resulting benchmarking sample concentrations to their underlying true values, analyzed by analyte, chemical class, pathway, and sample matrix.

The manufacture of biopharmaceutical products, such as proteins, oligonucleotides, engineered cells, vaccines, and peptides, requires demonstration of process control from raw material inputs through finished product release testing to ensure reproducible, safe products. Typically, hundreds of chemical, biochemical, in vitro and in vivo assays are conducted with a diverse set of analytical techniques, such as HPLC, NMR, mass spectrometry, infrared spectrometry, ELISA, and potency assays, each of which requires extensive development, bespoke reagents, complex sample preparation, high cost capital and highly trained staff. Quantum electrochemical spectroscopy (QES), a practical application of inelastic electron tunnelling spectroscopy, offers broad opportunity to simplify biopharmaceutical testing as well as early detection of process anomalies that may lead to batch failure.  The QES benchtop instrument (~8.5 x 12.8 x 17 cm) measures molecular vibrations, generating a digital fingerprint, a digital twin for each sample for use in real time or years from now to monitor process shifts. Typically, the sample size is a single pipetting of less than 10uL, does not require sample preparation or additional reagents, with results obtained in about an hour. Sample complexity ranges from pure samples in solution to crude cell culture. In this manufacturing application the output is a digital representation of all molecules in the sample at a given point in the process. The QES mathematical model representing the mixture also allows longitudinal process monitoring, with real time classification of the manufacturing run as to it producing a passing or a failing product. Further, using authentic samples, a model is created to quantify selected individual components in the sample, or the structural homogeneity or degradation state of an analyte of interest, for example.  QES has demonstrated broad sensitivity and specificity in differentiating mass isotopes, structural isomers1, disease state, proinflammatory biomarkers and markers of liver toxicity, for example. In this work, we expand the assessment to showcase the differentiation and quantitation of two very similar proteins, long-acting (Toujeo/ glargine) and short-acting (Humalog/ lispro) insulin in a mixture of the two molecules; detect and quantify low-abundance inflammatory proteins (e.g. IL-6) in high complexity samples; detect and quantify short oligonucleotide pharmaceutical products from background impurities and demonstrate the use of QES to predict the sanctioning manufacturing runs generating microbial fermentation products while also qualifying the state of microbial health within the fermentation matrix.   Developing and using bioanalytical assays in bioproduction is an intensive and expensive process. The cost is commonly driven by the extensive validation required by reagent-centric methods (e.g. Immunoassays), the extensive sample preparation required (e.g. LC-MS), the cost of capital and infrastructure, and the need for highly trained staff to run the assays. QES does not require reagents, nor sample preparation; , requires one pipetting step, and approximately 2 linear feet of lab bench space, thereby dramatically reducing the complexity and the cost of method creation and validation. Despite being a simple and straightforward analytical method, QES does not compromise the sensitivity or specificity of the analyte detection, as demonstrated in this work by the very low level of insulin isoforms identified and quantified (fg/mL) in a simpler background matrix. We also demonstrate the ability of QES to quantify a bigger protein in a more complex matrix resembling cell culture supernatants.  In summary, QES has been used to classify complex samples (pass/fail; disease/healthy; toxic/non-toxic) using uL’s of complex samples as-collected (cell culture, human blood); quantify selected analytes in those samples over large dynamic ranges; and differentiate structural homologs of proteins, peptides, and small molecules. Because QES does not require a laboratory infrastructure and many of the sample handling steps of other quantitative analytical methods, systematic errors associated with sample transport, handling and preparation are eliminated. The digital model of the sample resides either on premises or in the cloud, thereby allowing rapid sanctioning of the results against historic trends. Together, QES affords more information in less time at a lower cost and facile technology transfer than many analytical methods used to characterize manufacturing processes.  1) Gupta, Chaitanya, et al. "Quantum tunneling currents in a nanoengineered electrochemical system." The Journal of Physical Chemistry C 121.28 (2017): 15085-15105.

Solubility fusion tags help with protein solubility and increase expression yield. However, they can interfere with binding and protein function, often requiring removal for downstream assays. The eProtein Discovery system automates screening of 24 expression constructs with 8 expression additives to report on soluble yield within 24 hours. Using protease additive, the system performs in situ detagging to evaluate the consequences of solubility tag removal, informing scale-up the next day.

Access to soluble recombinant protein is a bottleneck in drug discovery, taking weeks to months to optimize a construct that produces soluble, active protein. The eProtein Discoveryâ„¢ system bridges the gap, enabling DNA to assay-ready protein in 48 hours. 24 DNA constructs are screened against customized expression conditions to report on purified yield. Scale-up the next day to get ug of proteins for functional assays on Biacoreâ„¢ SPR system.

Indigo, a textile dye with a history spanning 6,000 years, was originally extracted from plants. The present indigo market consists of approximately 50,000 tons, with chemically synthesized indigo predominantly occupying this sector. As concerns over hazardous chemicals in the global textiles industry grow, there is an increasing demand for non-toxic chemicals and eco-friendly processes in production of textile dyestuffs. The emergence of biosynthesized indigo presents a promising solution, providing stable quality products while decreasing the land requirements for traditional indigo plant cultivation. Production of indigo through microbial processes offers a greener alternative to chemical methods, eliminating hazardous intermediates.  Recombinant microbes can produce bio-indigo through enzymatic conversion of L-tryptophan or indole utilizing various oxygenases. In this study, we engineered E. coli expressing distinct oxygenases, including naphthalene dioxygenase, flavin-containing monooxygenase (FMO), and respectively P450, and evaluated the production efficiency of these strains. Remarkably, E. coli strains expressing NDO exhibited a significantly higher titer of bio-indigo, achieving 291 mg/L when supplied with tryptophan as the precursor in a shaking flask, surpassing the titers from strains expressing FMO or P450.  However, the titer of indigo produced by E. coli with NDO still needs to be further improved, so we optimized the fermentation parameters and culture medium formula by Design of Experiment. Subsequent validation of the DOE results conducted using a 5-L fermenter, resulting in significant enhancements with the titer of indigo to 1926 mg/L.

Introduction  Combining piggyBac transposase and Cas-CLOVER targeted nuclease technologies enables optimal rapid stable cell expression across multiple bioprocessing platforms important for SynBio. Here we present diverse methods enabling: 1- HEK293 cells expressing therapeutic candidates for rapid development of novel coronavirus vaccines. 2- Multiple industrial yeast strains stably expressing RNAi based biopesticides. 3- The entire Mevalonate (MVA) biosynthetic pathway of 12 genes stably delivered with a single piggyBac vector to produce high value metabolites such as β-farnesene.   About the gene editing technologies  Cas-CLOVER is a gene editing tool similar to CRISPR/Cas9 but offers unique benefits due to its different components. It utilizes two gRNAs and a dimeric nuclease, Clo051, which executes the DNA cutting, enhancing accuracy and minimizing off-target effects. PiggyBac transposase semi-randomly integrates expression cargo stably into non-coding, open chromosomal sites favoring highly transcribed sites in the genome.   Biotherapeutics  In suspension HEK293 cells, we first employed piggyBac transposase to map and characterize novel genomic sites of interest for expression of an enveloped viral-like particle (eVLP) stable core protein, MLV-GAG. Using the newly identified piggyBac integration sites, Cas-CLOVER was used to independently knock-in viral-like protein cargo (GAG, spike proteins, etc.) at these specific sites. Newly identified sites surpassed protein expression levels at known genomic safe harbor sites, rogi1 and GSH31. As a result, we demonstrate the utility of combining piggyBac and Cas-CLOVER to produce innovative cell platforms consistently producing therapeutic molecules at user-desired expression levels.   Biopesticides  This time we first utilized Cas-CLOVER in yeast to knock out multiple genes that could be used to select for high expressing clones. The resulting edited yeast strain was utilized as the foundation for piggyBac transposase to stably deliver a wide range of RNAi copies at different integration sites. A dynamic range of RNAi expression including far above the transient levels was achieved and confirmed to be stable in industrial fermentation pilot runs. When the engineered yeast is fed to its target pest, mosquitos in this case, selective mortality of >90% was observed, paving the way for global distribution of eco-friendly biopesticides.   Biosynthetic Pathways  One of the properties of piggyBac is its very large DNA integration cargo capacity, with over 300 kb being reported in the literature. We sought to engineer a relatively large metabolic pathway in S. cerevisiae to illustrate its utility in the field of synthetic biology and metabolic engineering. In a single transformation of the piggyBac/MVA cassette, levels β-farnesene were produced at titers reaching over 1.6 g/L, generally seen with multiple rounds of engineering.   Conclusion  This innovative application of Cas-CLOVER and piggyBac transposase showcases the technologies versatility and efficiency in bioengineering across a diverse array of SynBio organisms. The precision and effectiveness of Cas-CLOVER in gene editing, paired with the capacity of piggyBac for large DNA cargo integration and stable expression, underscore the potential of these tools to revolutionize fields from medicine to agriculture and beyond. This enables not only the fast-tracking of therapeutic candidates and biopesticides, but also the optimization of metabolic engineering for sustainable production of proteins and valuable compounds.

Lanthanides, a series of 15 f-block elements, are crucial in modern technology, and their purification by conventional chemical means comes at a significant environmental cost. Synthetic biology offers promising solutions. However, progress in developing synthetic biology approaches is bottlenecked because it is challenging to measure lanthanide binding with current biochemical tools. We introduce LanTERN, a lanthanide-responsive fluorescent protein. LanTERN was designed based on GCaMP, a genetically encoded calcium indicator that couples the ion binding of four EF hand motifs to increased GFP fluorescence. We engineered eight mutations across the parent construct’s four EF hand motifs to switch specificity from calcium to lanthanides. The resulting protein, LanTERN, directly converts the binding of 10 measured lanthanides to 14-fold or greater increased fluorescence. LanTERN development opens new avenues for creating improved lanthanide-binding proteins and biosensing systems.

Self-Powering Skins for devices.  Protein-embedded biomaterials offer the promise of regenerative forms of power for devices.  Current power sources — even renewable technologies — fail to embed themselves within nature’s cycles as they cannot be fully disassembled or recycled; nor are they designed to biodegrade.  We build on research from UMASS university which proposed thin films devices made from nanometre-scale protein nanowires harvested from the microbe *Geobacter sulfurreducens*. These nanowires and can produce a continuous 0.5 volts and 17 microamperes per square centimetre. We propose a material scaffold that harnesses these properties. Electric Skin is a compostable material based on calcium alginate composites with silk fibroin, chitosan and glycerin as a plasticizer. This material is made into flexible sheets on which we drop the protein nanowires using a laboratory pipette.  So far our results have yielded a sporadic 0.7 volts on small cell of 0.5 Sqcm.  Our results demonstrate the potential of a biodegradable (perhaps even compostable) source of energy that could be used to power devices relying simply on ambient humidity. Further research is necessary to scale these results, connect the power cells and explore the range of applications of this biotechnology. Immediate theories include coating for buildings and biomedical devices.  In the future the implications of this research range from the possibility for compostable electronics that bypass the need for heavy metal extraction, biophilic wearable technology, continuous energy harvesting in harsh environments and more.

Synthetic Biology is a rapidly growing multidisciplinary field of biotechnology which utilizes principles of genetic engineering to modify or create genetic material in different organisms to address challenges in areas of agriculture, medicine, and conservation of the environment. Liquid handling systems minimize human errors, reduce hands-on time, and increase throughput and reproducibility. Molecular cloning is one of the many genetic engineering techniques that greatly benefit from these platforms, which are widely used for high-throughput gene assembly for applications such as genetically modified crops, antibody discovery, proteomics, and oligo/gene synthesis.  In this poster we describe an end-to-end automated workflow; starting with cloning using In-Fusion Snap Assembly Kit from Takara, followed by plasmid purification using the CosMCprep and EMnetik PLP Beads from Beckman Coulter Life Sciences, and finally transfection of plasmids into cells for functional assays on the Biomek i7 Dual Hybrid Workstation.  In-Fusion cloning is simple, scalable, directional, and highly efficient (>95%), making it ideal for high-throughput workflows. Furthermore, this automated In-Fusion Snap Assembly protocol showcases the ability of the Biomek i7 Dual Hybrid Workstation to perform 1 μL transfers using the 1,200 μL Multichannel head. To demonstrate a 96-sample plate setup, we assembled a 3.7 kb insert into a 2.6 kb plasmid and tested two reaction volumes: 10 μL and 5 μL for the Takara In-Fusion Snap Assembly Kit. CosMCPrep kit utilizes bead-based purification which makes it flexible and easy scalable for high-throughput screenings. Here we demonstrate data from a 96-sample automated plasmid purification starting with 2mL of culture. The average yield of the 96 samples was 151 ng/µL with A260/280 of 1.87 and A230/280 of 2.38. For the automated dual luciferase functional assay, the cell plating, transfection, and luminescence measurements were carried out on the Biomek i7 workstation with a HEPA filter and an integrated SpectraMax i3 X (Molecular Devices) plate reader to measure luminescence. The DLR setup demonstrated here used a firefly luciferase (FLuc) reporter to detect Nuclear Factor Kappa B (NF-κB) signaling in response to Tumor Necrosis Factor α (TNFα). The control luciferase with constant expression used was NanoLuc (Promega). The automated method performed excellently in both 96-well and 384-well format as compared to manual, allowing miniaturization to increase throughput and reduce reagent cost. TNFα EC50 values were 0.4 and 0.3 ng/mL for the automated and manual workflows, respectively. Finally, we show that the automated method developed here was ready to be adapted for high-throughput screening, as Z’ values ranging from 0.70 to 0.80 were observed.  In summary, we show the ability of the Biomek i7 workstation to perform important workflows in synthetic biology along with downstream application for high-throughput screening, thus increasing reproducibility of the assays and reducing user hands-on time and handling errors.

As BASF Bioservices, we provide end-to-end R&D services to Life Science, Biotechnology, and BASF Group companies. Our best-in-class digital and wet-lab R&D platform includes all capabilities required for biotechnology research services and product development, from discovery and screening to large scale production of microbial fermentation products, biobased chemicals, and biocatalysts.

Erythropoietin (EPO) is the major cytokine hormone which regulates erythropoiesis1. EPO also causes the differentiation of platelet precursors, namely reticulated platelets, which leads to increased platelet count. This platelet generation, and possible subsequent thrombosis, is one of the major off-target effects of the administration of EPO3. Additionally, some studies have shown that EPO can prevent cell death of neurons and other cells in the face of cytotoxic assaults, such as hypoxia, in vitro and in many in vivo models of neurodegeneration3. However, the dose used to generate this protective signaling is generally orders of magnitude higher than the dose necessary for RBC differentiation. At higher doses, the likelihood of platelet production and thrombosis is higher, and in vivo or clinical trial data testing whether EPO is neuroprotective are stymied by off-target effects on platelet generation3. For this reason, there have been efforts towards developing a safer EPO. We hypothesized that EPO receptor (EPOR) binding alone can recruit the co-receptor needed for cellular protection, CD131. Thus, we engineered a fusion protein consisting of an EPOR binding scFv. We show that this engineered fusion protein has many of the functions of WT EPO and can cause short and long-term proliferation of blood cell lines and leads to the phosphorylation of EPOR, CD131 and downstream effector STAT5. We imagine that this engineered protein could be used as a safe, longer-lasting EPO mimetic which would also be easier to manufacture and would not cause the production of auto-antibodies against endogenous EPO.

Liquid-liquid phase separation of intrinsically disordered proteins (IDPs) and nucleic acids has been implicated in infectious and neurodegenerative diseases and condensate-modulating small molecules (CMODs) represent a novel modality for drug discovery. So far, CMODs have been discovered and optimized using high content cell imaging assays. We screened a library of bioactive compounds for modulators of SARS-CoV-2 nucleocapsid (N) protein condensation as a potential route to anti-viral therapeutics using a high content cell imaging assay and found that inhibitors of GSK3 promote N condensation. Our pipeline revealed several drawbacks of high content screening, including limited resolution, inaccuracies in image analysis and logistical costs. We hypothesized that molecular proximity biosensors might report on CMOD activity with higher speed and reliability. To test this, we developed biosensors for N-N interaction in cells using split luciferase (NanoBIT) and nano-bioluminescence resonance energy transfer (NanoBRET) technologies. Both biosensors reported on CMOD activity with dose response curves comparable to high content assays. We also tested applicability of proximity biosensors to several other known phase-separating IDPs including the neurodegenerative disease-associated RNA-binding proteins FUS and TDP43, as well as the extremophile tardigrade cytosolic abundant heat soluble protein 2 (CAHS2). Molecular proximity and high content assays report on condensation at different length scales and provide complementary information on CMOD action. Proximity assays may be useful for large screens and rapid dose-response assays where throughput and reproducibility are more important than information content.

Insults to the developing cerebellum can cause motor, language, and social deficits. Here, we investigate whether developmental insults to different cerebellar neurons constrain the ability to acquire cerebellar-dependent behaviors. We perturb cerebellar cortical or nuclei neuron function by eliminating glutamatergic neurotransmission during development, and then we measure motor and social behaviors in early postnatal and adult mice. Altering cortical and nuclei neurons impacts postnatal motor control and social vocalizations. Normalizing neurotransmission in cortical neurons but not nuclei neurons restores social behaviors while the motor deficits remain impaired in adults. In contrast, manipulating only a subset of nuclei neurons leaves social behaviors intact but leads to early motor deficits that are restored by adulthood. Our data uncover that glutamatergic neurotransmission from cerebellar cortical and nuclei neurons differentially control the acquisition of motor and social behaviors, and that the brain can compensate for some but not all perturbations to the developing cerebellum.

Synthetic biology re-engineers biological components, pathways, and organisms to create bioproducts ranging from therapeutics to sustainable chemicals; however, the field faces significant challenges due to the underlying biological complexity of natural systems. Our Masters of Engineering team at UC Berkeley is working with the Anderson Lab to develop software that automates and enhances the complex design functions required in this field. More specifically, our group is developing a pipeline for mining metabolic reactions from databases, transforming the reactions into a ML predictive algorithm to determine enzyme-substrate specificity, and projecting these predictions onto a whole-cell biochemical model to map mechanistically reachable metabolic pathways. Furthermore, these functions, and other open source tools developed by the Anderson Lab, can all be accessed through a custom middleware that interfaces with a large language model, such as GPT-4. This AI tool allows for easy access and communication between a scientific user and the information provided by the different biological design tools, enhancing efficiency and the breadth of capabilities for synthetic biology.

Salivabactin, a novel antibiotic discovered within Streptococcus salivarius (SAL), possesses a unique chemical scaffold with effective inhibitory activity against Gram-positive bacteria, notably Streptococcus pyogenes (GAS), and is comparable to the efficacy of penicillin. However, scaling up salivabactin production within SAL is hindered by several challenges. To circumvent these issues, Escherichia coli has been engineered for the heterologous production of salivabactin. The successful expression of the sar biosynthetic gene cluster (sarBGC) in E. coli has led to the synthesis of salivabactin. By utilizing plasmids with varying copy numbers, we have optimized the expression of sar genes, enhancing production yields by 1.9-fold. Additionally, the elimination of the sarI gene, which encodes a putative insoluble thioesterase, has further increased the titer by approximately 20%. Enhancements to the salivabactin production were further achieved by manipulating the metabolic precursor 4-hydroxybenzoate (4-HB): increasing its exogenous feed concentration and deleting an endogenous 4-HB exporter effectively elevated intracellular 4-HB levels and production titers to 2.51 mg/L. Moreover, constructing a complete biosynthetic pathway from glucose to 4-HB, coupled with the downstream salivabactin pathway, resulted in the production of 0.104 mg/L of salivabactin. We have also explored alternative starting precursors, leading to the discovery of three salivabactin analogues. Production titers in E. coli surpassed those in the native host by 30-fold, establishing a robust platform for the generation of salivabactin and its derivatives.

A fundamental aspect of bioprocessing is the mass transfer of oxygen and other gas molecules inside the bioreactor, and kLa emerges as a key parameter that describes the efficiency of mass transfer between the gas and the liquid phases. As the majority of biopharmaceuticals are produced in aerobic processes, the correct oxygen mass transfer is crucial and a common challenge in both cell culture and microbial applications. Using Securecell’s process information management software Lucullus®, we developed an automated kLa determination operation based on the static gassing-out method. The operation is compatible with virtually any bioreactor system, making it a powerful and widely applicable tool for bioprocess engineers. With two experiments, we demonstrated the potential of the automated kLa determination compared to the standardly applied manual kLa determination to significantly reduce the time investment, improve reproducibility, and enhance process understanding.

In bioprocesses, amino acids are often critically limiting substances. Monitoring and real-time mea-surements of amino acids and other process parameters require the availability of dedicated on-line analytical equipment. However, state-of-the-art analyzers such as chromatographic systems or metabolic analyzers are often only available off-line and therefore require manual reactor sampling, sample processing, and subsequent data management.  We demonstrate how two different off-line analyzers for amino acids, namely the Thermo Scien¬tificâ„¢ Ultimateâ„¢ 3000 HPLC system and the Roche Cedex® Bio HT Analyzer, can be made available on-line using the automated sampling system Numera® and how the associated data management can be seamlessly orchestrated with the overarching bioprocess software Lucullus® (Figure 1). The measured on-line analyzer data was comparable to the manual off-line data demonstrating the ac¬curacy and reliability of the setup. Limiting amino acids were identified with the on-line analyzers and real-time feedback was successfully implemented based on the on-line measurements.

Acute Respiratory Distress Syndrome (ARDS) is a life-threatening condition characterized by fluid accumulation in the delicate alveoli of the lungs which severely compromises respiration leading to an in-hospital 40% mortality rate. With approximately 200,000 annual cases, constituting 10-15% of all ICU admissions and treatment costs reaching up to $450,000 per patient, ARDS poses a substantial healthcare burden. Moreover, the long-term complications, post hospital discharge, of this syndrome were reported to lead to approximately 39% hospital readmissions within 2 years.  While current pharmacoeconomic research predominantly focuses on the immediate effects and costs of ARDS management, our investigation delves into the long-term physical, psychological, and economic implications to create a comprehensive framework for evaluation of the total costs associated with ARDS. We aim to establish a comprehensive framework for assessing the overall expenses related to ARDS, incorporating current and future treatments. Our analysis will feature MultiStem therapy as a model, a promising cell-based treatment derived from Multipotent Adult Progenitor Cells (MAPCs). MultiStem has a dual action, mitigating acute inflammation in ARDS and promoting the body's regenerative abilities.   Employing a rigorous scientific approach, we analyze the intricate inflammatory pathway associated with ARDS and explore how the anti-inflammatory and regenerative potential of MultiStem can effectively combat the acute and long-term effects of this condition. Additionally, we consider patient-centric measures and pharmaco-economic factors to assess the potential benefits of emerging treatments. This study not only deepens our understanding of ARDS pathophysiology but also paves the way for defining crucial outcome measures that could potentially revolutionize ARDS treatment. By incorporating long-term consequences of ARDS into the efficacy evaluation, we aim to enhance cost-effectiveness for the benefit of patients and the healthcare system.

Establishing bioprocesses to manufacture biologics at scale requires the design, construction and optimisation of host protein expression systems, viable upstream processes and downstream product recovery and purification. Ingenza is changing the game in product development with its innovative inGenius® platform of multiple production hosts and integrated toolbox of enabling technologies. Combined with DoE and tailored fermentation protocols, our inGenius® platform accelerates and de-risks bioprocess development and production. Case studies will illustrate the application of our approach to address development limitations normally associated with the iterative and often empirical process to optimise bio-manufacturing.

Microbial natural products (NPs) are encoded by biosynthetic gene clusters (BGCs) and represent an unparalleled source of clinically significant compounds. Since 1981, nearly two-thirds of clinically approved small molecule drugs for cancer treatment are either NPs, their analogues, or synthetic molecules inspired by NPs. Modern genome sequencing has revolutionized the current paradigms for NP discovery. Emerging bioinformatics tools have enabled rapid and systematic identification of NP producers by mining microbial genomes for BGCs that encode the biosynthesis of the associated NPs. However, experimental characterization cannot match the pace of BGC identification as most BGCs are transcriptionally cryptic under laboratory conditions. Synthetic biology has enabled heterologous BGC expression in model hosts bypassing native regulatory circuits. However, effective replacement of non-native promoters and selective disruption of BGC-specific regulation is challenged by complex NP families such as the enediyne family of anticancer NPs. Enediyne biosynthesis involves intricate regulatory networks and unknown tailoring steps, hindering heterologous expression. This study focuses on tiancimycin production in a model heterologous host, marking the first successful heterologous production of an enediyne, achieved through transcriptomics-guided BGC refactoring and systematic host strain and media evaluation. This work highlights the need for comprehensive synthetic biology workflows to activate heterologous BGCs, advancing the production of targeted NPs.