Biodiversity loss in the present era requires new tools for studying nonmodel organisms. Elephants are both an endangered species and excellent models for studying complex phenotypes including size, social behavior and longevity. Here we report the first derivation of elephant (Elephas maximus) induced pluripotent stem (emiPS) cells. We achieved emiPS cells using two approaches: (1) a two-step process of chemical media induction and colony selection followed by over-expression of elephant transcription factors; and (2) a one-step process with transcription factors and HRAS mutant, HRASG12V. For both protocols, we inhibited TP53 retrogenes, which are hypothesized to confer unique cancer resistance in elephants. To confirm their reprogrammed state, we generated a functional omics catalog of emiPS cells. While these emiPS cells remain transgene-dependent, we inactivated the transgenes and differentiated emiPS cells into all three germ layers via tri-lineage differentiation, embryoid body generation and direct differentiation into putative cell types from all three layers. These methods will open new frontiers for cellular models of nonmodel organisms, including for genetic rescue and conservation.

Pluripotent cells specialize into numerous cell types by receiving external signals, making fate decisions, and executing differentiation functions - a paradigm similar to computer algorithms. While advances in biosensor design have enabled cells to respond to diverse stimuli, the ability to maintain a synthetic memory of the cell's experiences that then informs its behaviors remains elusive. Here, we developed a system for cellular memory-driven behaviors by simulating a "for-loop" that counts to three using recombinase STepwise gene Expression Programs (STEPs). STEPs were genomically integrated into human cells, genotyped through targeted nanopore sequencing, and evaluated for function through changes in fluorescent reporter expression. While all STEPs were capable of heritable memory and sequential gene expression, the STEP design using tyrosine recombinases for successive excisions (TRex) significantly outperformed the others tested. We then used live cell imaging to track TRex cells as they incremented from count zero to three and observed the successive emergence of four cell states from an initially homogeneous population. The STEPs framework provides biological memory and conditional expression capabilities that, coupled with input mechanisms such as biosensors, can start to approach a programming language for biology.

Differentiation of induced pluripotent stem cells (iPSCs) into specialized cell types is essential for uncovering cell-type specific molecular mechanisms and interrogating cellular function. Transcription factor screens have enabled efficient production of a few cell types; however, engineering cell types that require complex transcription factor combinations remains challenging. Here, we report an iterative, high-throughput single-cell transcription factor screening method that enables the identification of transcription factor combinations for specialized cell differentiation, which we validated by differentiating human microglia-like cells. We found that the expression of six transcription factors, SPI1, CEBPA, FLI1, MEF2C, CEBPB, and IRF8, is sufficient to differentiate human iPSC into cells with transcriptional and functional similarity to primary human microglia within 4 days. Through this screening method, we also describe a novel computational method allowing the exploration of single-cell RNA sequencing data derived from transcription factor perturbation assays to construct causal gene regulatory networks for future cell fate engineering.

The creation of induced pluripotent stem cells (iPSCs) has enabled scientists to explore the function, mechanisms, and differentiation processes of many types of cells. One of the fastest and most efficient approaches is transcription factor (TF) over-expression. However, finding the right combination of TFs to over-express to differentiate iPSCs directly into other cell types is a difficult task. Here, we describe a machine-learning (ML) pipeline, called CellCartographer, that uses chromatin accessibility and transcriptomics data to design multiplex TF pooled-screening experiments for cell-type conversions that then may be iteratively refined. We validate this method by differentiating iPSCs into twelve cell types at low efficiency in preliminary screens and iteratively refine our TF combinations to achieve high-efficiency differentiation for six of these cell types in <6 days. Finally, we functionally characterize iPSC-derived cytotoxic T cells (iCytoTs), regulatory T cells (iTregs), type II astrocytes (iAstIIs), and hepatocytes (iHeps) to validate functionally accurate differentiation.

Multicellular organisms originate from a single cell, ultimately giving rise to mature organisms of heterogeneous cell type composition in complex structures. Recent work in the areas of stem cell biology and tissue engineering has laid major groundwork in the ability to convert certain types of cells into other types, but there has been limited progress in the ability to control the morphology of cellular masses as they grow. Contemporary approaches to this problem have included the use of artificial scaffolds, 3D bioprinting, and complex media formulations; however, there are no existing approaches to controlling this process purely through genetics and from a single-cell starting point. Here we describe a computer-aided design approach, called CellArchitect, for designing recombinase-based genetic circuits for controlling the formation of multicellular masses into arbitrary shapes in human cells.

ABSTRACTThe crisis of biodiversity loss in the anthropogenic era requires new tools for studying non-model organisms. Elephants, for example, are both an endangered species and excellent models studying complex phenotypes like size, social behavior, and longevity, but they remain severely understudied. Here we report the first derivation of elephant (Elephas maximus) induced pluripotent stem cells (emiPSCs) achieved via a two-step process of chemical-media induction and colony selection, followed by overexpression of elephant transcription factorsOCT4, SOX2, KLF4, MYC±NANOGandLIN28A, and modulation of theTP53pathway. Since the seminal discovery of reprogramming by Shinya Yamanaka, iPSCs from many species including the functionally extinct northern white rhinocerous have been reported, but emiPSCs have remained elusive. While for multiple species the reprogramming protocol was adopted with little changes compared to model organisms like mouse and human, our emiPSC protocol requires a longer timeline and inhibition ofTP53expansion genes that are hypothesized to confer unique cancer resistance in elephants. iPSCs unlock tremendous potential to explore cell fate determination, cell and tissue development, cell therapies, drug screening, disease modeling, cancer development, gametogenesis and beyond to further our understanding of this iconic megafauna. This study opens new frontiers in advanced non-model organism cellular models for genetic rescue and conservation.

The Biological Weapons Convention (BWC) prohibits the development, production, and stockpiling of biological weapons. Since its creation in the 1970's it has lacked a mechanism to verify compliance of its States Parties. Most of the 1990s was spent trying to develop such a regime. These failed in 2001. The authors consider the scientific and technical feasibility of verifying compliance with the BWC, primarily focussing on on-site verification (activities conducted with physical access to a facility) but also addressing off-site verification (activities that can be conducted from other locations). They review past thinking on what verifying the BTWC was to accomplish, the verification measures identified, and the assessment criteria used. They then examine changes in the life sciences, biotechnology, and biomanufacturing since the last time these issues were considered at the multilateral level in 1993. Using criteria previously developed by the BWC States Parties, the authors assess the impact of current scientific and technical capabilities on verifying compliance with the BWC. They conclude that using a variety of measures in concert, and by compiling numerous sources of information and signatures of unusual behaviour, it might be feasible to identify non-compliance with the BWC. They identify several ways in which advances offer opportunities and challenges to verifying compliance with the BWC. They consider how current trends may affect future work on verification and how that might be integrated into the work of the BWC.

The ability to differentiate stem cells into human cell types is essential to define basic mechanisms and therapeutics, especially for cell types not routinely accessible by biopsies. But while engineered expression of transcription factors (TFs) identified through TF screens has been found to rapidly and efficiently produce some cell types, generation of other cell types that require complex combinations of TFs has been elusive. Here we develop an iterative, pooled single-cell TF screening method that improves the identification of effective TF combinations using the generation of human microglia-like cells as a testbed: Two iterations identified a combination of SPI1, CEBPA, FLI1, MEF2C, CEBPB, and IRF8 as sufficient to differentiate human iPSC into microglia-like cells in 4 days. Characterization of TF-induced microglia demonstrated molecular and functional similarity to primary microglia. We explore the use of single-cell atlas reference datasets to confirm identified TFs and how combining single-cell TF perturbation and gene expression data can enable the construction of causal gene regulatory networks. We describe what will be needed to fashion these methods into a generalized integrated pipeline, further ideas for enhancement, and possible applications.

Targeted delivery of therapeutic proteins toward specific cells and across cell membranes remains major challenges. Here, we develop protein-based delivery systems utilizing detoxified single-chain bacterial toxins such as diphtheria toxin (DT) and botulinum neurotoxin (BoNT)-like toxin, BoNT/X, as carriers. The system can deliver large protein cargoes including Cas13a, CasRx, Cas9, and Cre recombinase into cells in a receptor-dependent manner, although delivery of ribonucleoproteins containing guide RNAs is not successful. Delivery of Cas13a and CasRx, together with guide RNA expression, reduces mRNAs encoding GFP, SARS-CoV-2 fragments, and endogenous proteins PPIB, KRAS, and CXCR4 in multiple cell lines. Delivery of Cre recombinase modifies the reporter loci in cells. Delivery of Cas9, together with guide RNA expression, generates mutations at the targeted genomic sites in cell lines and induced pluripotent stem cell (iPSC)derived human neurons. These findings establish modular delivery systems based on single-chain bacterial toxins for delivery of membrane-impermeable therapeutics into targeted cells.

Interactions between cells are indispensable for signaling and creating structure. The ability to direct precise cell-cell interactions would be powerful for engineering tissues, understanding signaling pathways, and directing immune cell targeting. In humans, intercellular interactions are mediated by cell adhesion molecules (CAMs). However, endogenous CAMs are natively expressed by many cells and tend to have cross-reactivity, making them unsuitable for programming specific interactions. Here, we showcase "helixCAM," a platform for engineering synthetic CAMs by presenting coiled-coil peptides on the cell surface. helixCAMs were able to create specific cell-cell interactions and direct patterned aggregate formation in bacteria and human cells. Based on coiled-coil interaction principles, we built a set of rationally designed helixCAM libraries, which led to the discovery of additional high-performance helixCAM pairs. We applied this helixCAM toolkit for various multicellular engineering applications, such as spherical layering, adherent cell targeting, and surface patterning.

Coronavirus disease 2019 (COVID-19) continues to burden society worldwide. Despite most patients having a mild course, severe presentations have limited treatment options. COVID-19 manifestations extend beyond the lungs and may affect the cardiovascular, nervous, and other organ systems. Current treatments are nonspecific and do not address potential long-term consequences such as pulmonary fibrosis, demyelination, and ischemic organ damage. Cell therapies offer great potential in treating severe COVID-19 presentations due to their customizability and regenerative function. This review summarizes COVID-19 pathogenesis, respective areas where cell therapies have potential, and the ongoing 89 cell therapy trials in COVID-19 as of 1 January 2021.

Biosecurity is a multi-disciplinary topic that covers areas of policy, public health, economics, and science. This chapter focuses on the technical scientific aspects of the current international biosecurity framework. We discuss these technical areas in terms time horizon. We begin this chapter with review of current technology within the international biosecurity framework and discuss weakness and opportunities for further work. We then focus on near-term technical developments and imminent opportunities to strengthen the existing framework. Specifically, we break down the range of issues into biological threat prevention, detection, and response. We discuss how technical tools can assist in policy development and the engineering cycle of Design, Built, and Test. Finally, this chapter describes a ‘futuring’ exercise conducted by the working group that created this chapter to explore broader longer-term issues in the biosecurity space.

Human cell conversion technology has become an important tool for devising new cell transplantation therapies, generating disease models and testing gene therapies. However, while transcription factor over-expression-based methods have shown great promise in generating cell types in vitro, they often endure low conversion efficiency. In this context, great effort has been devoted to increasing the efficiency of current protocols and the development of computational approaches can be of great help in this endeavor. Here we introduce a computer-guided design tool that combines a computational framework for prioritizing more efficient combinations of instructive factors (IFs) of cellular conversions, called IRENE, with a transposon-based genomic integration system for efficient delivery. Particularly, IRENE relies on a stochastic gene regulatory network model that systematically prioritizes more efficient IFs by maximizing the agreement of the transcriptional and epigenetic landscapes between the converted and target cells. Our predictions substantially increased the efficiency of two established iPSC-differentiation protocols (natural killer cells and melanocytes) and established the first protocol for iPSC-derived mammary epithelial cells with high efficiency.

Molecular biologists rely on the use of fluorescent probes to take measurements of their model systems. These fluorophores fall into various classes (e.g. fluorescent dyes, fluorescent proteins, etc.), but they all share some general properties (such as excitation and emission spectra, brightness) and require similar equipment for data acquisition. Selecting an ideal set of fluorophores for a particular measurement technology or vice versa is a multidimensional problem that is difficult to solve with ad hoc methods due to the enormous solution space of possible fluorophore panels. Choosing sub-optimal fluorophore panels can result in unreliable or erroneous measurements of biochemical properties in model systems. Here, we describe a set of algorithms, implemented in an open-source software tool, for solving these problems efficiently to arrive at fluorophore panels optimized for maximal signal and minimal bleed-through.

Understanding the evolutionary stability and possible context dependence of biological containment techniques is critical as engineered microbes are increasingly under consideration for applications beyond biomanufacturing. While synthetic auxotrophy previously prevented Escherichia coli from exhibiting detectable escape from batch cultures, its long-term effectiveness is unknown. Here, we report automated continuous evolution of a synthetic auxotroph while supplying a decreasing concentration of essential biphenylalanine (BipA). After 100 days of evolution, triplicate populations exhibit no observable escape and exhibit normal growth rates at 10-fold lower BipA concentration than the ancestral synthetic auxotroph. Allelic reconstruction reveals the contribution of three genes to increased fitness at low BipA concentrations. Based on its evolutionary stability, we introduce the progenitor strain directly to mammalian cell culture and observe containment of bacteria without detrimental effects on HEK293T cells. Overall, our findings reveal that synthetic auxotrophy is effective on time scales and in contexts that enable diverse applications.

The fast-paced field of synthetic biology is fundamentally changing the global biosecurity framework. Current biosecurity regulations and strategies are based on previous governance paradigms for pathogen-oriented security, recombinant DNA research, and broader concerns related to genetically modified organisms (GMOs). Many scholarly discussions and biosecurity practitioners are therefore concerned that synthetic biology outpaces established biosafety and biosecurity measures to prevent deliberate and malicious or inadvertent and accidental misuse of synthetic biology's processes or products. This commentary proposes three strategies to improve biosecurity: Security must be treated as an investment in the future applicability of the technology; social scientists and policy makers should be engaged early in technology development and forecasting; and coordination among global stakeholders is necessary to ensure acceptable levels of risk.

Human pluripotent stem cells (hPSCs) offer an unprecedented opportunity to model diverse cell types and tissues. To enable systematic exploration of the programming landscape mediated by transcription factors (TFs), we present the Human TFome, a comprehensive library containing 1,564 TF genes and 1,732 TF splice isoforms. By screening the library in three hPSC lines, we discovered 290 TFs, including 241 that were previously unreported, that induce differentiation in 4 days without alteration of external soluble or biomechanical cues. We used four of the hits to program hPSCs into neurons, fibroblasts, oligodendrocytes and vascular endothelial-like cells that have molecular and functional similarity to primary cells. Our cell-autonomous approach enabled parallel programming of hPSCs into multiple cell types simultaneously. We also demonstrated orthogonal programming by including oligodendrocyte-inducible hPSCs with unmodified hPSCs to generate cerebral organoids, which expedited in situ myelination. Large-scale combinatorial screening of the Human TFome will complement other strategies for cell engineering based on developmental biology and computational systems biology. A library of human transcription factor genes is screened for differentiation of human pluripotent stem cells.

Bio-design automation (BDA) is an emerging field focused on computer-aided design, engineering principles, and automated manufacturing of biological systems. Here we discuss some outstanding challenges for bio-design that can be addressed by developing new tools for combinatorial engineering, equipment interfacing, next-generation sequencing, and workflow integration. These four areas, while not an exhaustive list of those that need to be addressed, could yield advances in bio-design, laboratory automation, and biometrology.

Design automation refers to a category of software tools for designing systems that work together in a workflow for designing, building, testing, and analyzing systems with a target behavior. In synthetic biology, these tools are called bio-design automation (BDA) tools. In this review, we discuss the BDA tools areas-specify, design, build, test, and learn-and introduce the existing software tools designed to solve problems in these areas. We then detail the functionality of some of these tools and show how they can be used together to create the desired behavior of two types of modern synthetic genetic regulatory networks.