A system for programmable export of RNA molecules from living cells would enable both non-destructive monitoring of cell dynamics and engineering of cells capable of delivering executable RNA programs to other cells. We developed genetically encoded cellular RNA exporters, inspired by viruses, that efficiently and selectively package and secrete target RNA molecules from mammalian cells within protective nanoparticles. Exporting and sequencing RNA barcodes enabled non-destructive monitoring of cell population dynamics with clonal resolution. Further, by incorporating fusogens into the nanoparticles, we demonstrated delivery, expression, and functional activity of exported mRNA in recipient cells. We term these systems COURIER . COURIER enables measurement of cell dynamics and establishes a foundation for hybrid cell and gene therapies based on cell-to-cell delivery of RNA.  The development of synthetic extracellular vesicles, based on designed protein nanocages, for the programmable and efficient export, cell-to-cell delivery, and expression of mRNA. As a central information carrier in the cell, RNA provides a powerful interface for reading and writing cell behaviors. Sequencing RNA enables readout of cell states. In parallel, expression of RNA controls cell states. However, RNA is typically confined within the cell that produced it, limiting its utility for molecular analysis and intercellular communication. By contrast, the ability to programmably export RNA molecules from cells could unlock ways to both analyze and control living cells.4. However, physically accessing RNA for analysis generally requires lysis or fixation of cells, preventing one from tracking the dynamic behavior of individual living cells over time. Cell-free RNA is naturally secreted by cells in extracellular vesicles or upon cell death, and sequencing this RNA can non-destructively reveal biomarkers of health and disease7. However, the low rates of natural RNA secretion9 limit the sensitivity and information content of cell-free RNA assays. As an alternative approach, engineering cells to efficiently export RNA molecules that encode information about cell populations and states, then collecting and sequencing this exported RNA could enable non-destructive measurement of cell dynamics with enhanced sensitivity and information content compared to natural cell-free RNA assays  or Moloney murine leukemia virus (MMLV), which exhibit only modest binding specificity for viral RNA, as they readily bind other RNA20, posing challenges for specific loading of cargo RNA. VLPs22 and EVs25 have been engineered to improve the selectivity of cargo RNA loading, including by fusing RNA binding proteins to capsids or proteins incorporated into EVs, and tagging cargo RNA with cognate interacting sequences. These approaches have allowed RNA delivery, including in vivo in mice26, but require further development, as they have been limited by inefficient cargo loading and secretion25; restricted cargo capacity and poor cargo expression after delivery23; or capsid modifications that impair VLP assembly28 and likely hinder secretion21.Virus-like particles (VLPs) and extracellular vesicles (EVs) are attractive platforms for export and delivery of RNA. Viral structural proteins  and their natural interactions with RNA packaging signals have been used to package and transfer RNA between cells in VLPsAn ideal RNA export system would overcome these limitations and provide several key features. First, it would export RNA from mammalian cells efficiently, thereby allowing sensitive measurement and potent delivery. Second, it would permit selective export of target RNAs, such as engineered barcodes or cargos. Third, it would protect the exported RNA from degradation by extracellular RNases. Fourth, it would enable delivery and expression of cargo RNA in recipient cells. Finally, expression of export system components would be minimally perturbing to the expressing cells. An RNA export system having these features could be used to create versatile RNA-based reporter and delivery platforms.Here, we report the development of RNA export systems having these features, and the application of these systems for non-destructive monitoring of cell population dynamics and cell-to-cell delivery of mRNA. We designed a set of RNA exporters that combine three types of modular protein components: (i) RNA binding proteins to capture specific RNA molecules, (ii) self-assembling capsids or vesicles to package and secrete those RNAs, and (iii) fusogens to deliver secreted RNA to target cells. We engineered several generations of RNA exporters, starting from VLPs and culminating in extracellular vesicles based on protein nanocages, which efficiently packaged and secreted RNA from cells and exhibited progressive improvements in selectivity for target RNA. We then combined RNA export with genetic barcoding and sequencing to non-destructively monitor cell population dynamics. Finally, by incorporating fusogens into the secreted nanoparticles, we demonstrated delivery and functional activity of cargo RNA in target cells, including mRNA encoding Cre recombinase and fluorescent proteins. We term these systems COURIER, for Controlled Output and Uptake of RNA for Interrogation, Expression, and Regulation. These results establish COURIER as a flexible and extensible paradigm for non-destructive measurement of cell dynamics and intercellular transfer of RNA.29. Retroviruses package their genomes into viral particles via interactions between capsid proteins and RNA structures that serve as packaging signals30.Because RNA viruses are naturally efficient RNA exporters, we initially sought to engineer RNA exporters based on viral components. We focused on retroviral capsid proteins, which self-assemble to form secreted VLPs when expressed in mammalian cells30. We transiently expressed the capsid protein (Gag) from MMLV with cargo RNA that was tagged in its 3’ untranslated region (3’ UTR) with the MMLV packaging signal (PS) in human embryonic kidney (HEK293T) cells  cells . These cT) cells  and dynaT) cells . SimilarT) cells .19, a property shared by other retroviral capsid proteins20. Thus, retroviral components export RNA efficiently, but possess only partial specificity for tagged cargo RNA.To quantify RNA export, we measured the abundance of cargo RNA in cell culture supernatant using reverse transcription and quantitative polymerase chain reaction (RT-qPCR). We collected supernatant, clarified it by centrifugation and filtered it to remove cells and large debris, extracted RNA, treated with DNase, and finally performed RT-qPCR for the target RNA . The cle31. To facilitate engineering, we replaced the MMLV Gag capsid with the HIV Gag capsid, which has better annotated functional domains32 and tolerates protein fusions without compromising VLP assembly and release33. We fused MCP to HIV Gag, forming Gag-MCP, and tagged cargo RNA with twelve tandem MS2 hairpins in its 3’ UTR , which binds to a cognate RNA hairpin aptamers 3’ UTR . Althoug34. This Gag-MCP system efficiently exported MS2-tagged cargo RNA, which was enriched 850-fold in supernatant in the presence compared to the absence of Gag-MCP  molecules per cell per hour . This ra20. We reasoned that ablating its RNA binding activity could reduce non-specific RNA packaging, while preserving the sequence-specific targeting conferred by MCP. However, the RNA binding activity of Gag is essential for nucleating viral particle assembly28. Indeed, deleting the critical zinc finger RNA binding motif (ZF2) from Gag-MCP, forming GagΔZF2-MCP, strongly reduced export activity to background levels  binds diverse RNA sequencesd levels , consist35. To test whether a similar design could rescue GagΔZF2-MCP particle assembly and enable specific RNA export, we substituted a leucine zipper for the nucleocapsid domain in Gag-MCP, to form a new construct, denoted GagZip-MCP  . No degr32, as highlighted by the dual role of nucleocapsid domains in RNA binding and particle assembly in diverse retroviruses38. In addition, fusing proteins to viral capsids can disrupt VLP assembly in an unpredictable manner39. Finally, viral proteins interact extensively with host proteins41, including stimulating innate antiviral sensing pathways46. To overcome these limitations, we sought to engineer synthetic RNA exporters based on designed proteins, which are inherently modular, should tolerate fusion to other proteins47, and are not expected to stimulate antiviral sensors46.Despite functioning well, the viral exporter designs described so far had limited potential for further engineering. Rational design of viral proteins is difficult because their architectures are not modular47. Addition of a membrane binding domain and a secretion signal (the p6 peptide from HIV) enables their secretion from mammalian cells within extracellular vesicles, which average ~110 nm in diameter and each contain ~20 nanocage assemblies48. Further, EPN protomers with diverse domain components and orderings have been secreted from cells48. While the ability of EPNs to package and export RNA has not been reported, their design includes cavities large enough to accommodate RNA binding proteins (Enveloped protein nanocages (EPNs) represent a spectacular achievement of protein design and provide an ideal foundation for RNA export. EPNs are composed of designed protomers that self-assemble into 60-subunit dodecahedral “nanocages”proteins . Both thTo test whether EPNs can export RNA, we designed 9 nanocage variants, based on 3 distinct EPN protomer architectures, which possess different membrane binding domains, with MCP fused at 3 different positions within each architecture . When exAmong these variants, EPN24-MCP exhibited the highest export efficiency. The rate of export by EPN24-MCP was similar to that of Gag-MCP, as indicated by accumulation of RNA over time after transfection . As withEPN24-MCP packaged RNA in extracellular vesicles. Cells expressing EPN24-MCP secreted vesicles with ~120 nm diameter, as revealed by electron microscopy  and dynaRNA encapsulated by EPN24-MCP was protected from degradation in cell culture supernatant and blood. 36% of the RNA exported by EPN24-MCP remained intact after incubation in culture supernatant at 37 C for 6 days . No degr48. To test whether export rates are ESCRT-dependent and whether they could be further enhanced, we selected a panel of six modulators of virus or exosome secretion51, of which two, NEDD4L and CIT, were previously shown to enhance HIV budding by promoting recruitment of ESCRT-I to HIV p6 domains50. We co-expressed each candidate modulator together with EPN24-MCP and target RNA, and assayed export by RT-qPCR  pathway RT-qPCR . NEDD4L  RT-qPCR . This end export . These rFinally, we asked whether the RNA targeting domain could be swapped by replacing MCP with an alternative sequence-specific RNA binding domain, the PP7 bacteriophage coat protein. The PP7-based design exported PP7-tagged cargo RNA, demonstrating modular engineering of RNA targeting specificity .Taken together, these results demonstrate that engineered nanocages enable efficient, specific, and programmable export of RNA.We next characterized the composition of exported RNA at genome scale using RNA sequencing. We expressed RNA exporters and target RNA by transfecting cells with expression plasmids, clarified and filtered culture supernatant, and sequenced total RNA . Using sExport specificity improved with each generation of exporter engineering. Target RNA represented only 4% of supernatant RNA reads with the MMLV Gag exporter, but 81% of supernatant RNA reads with the EPN24-MCP exporter . Improve54. By contrast, few genes were enriched in exported RNA compared to the cellular transcriptome. Gene ontology (GO) analysis of these enriched genes showed no consistent and significant pathway enrichment  and T cells (Jurkat). Gag-MCP, EPN11-MCP, and EPN24-MCP each exported cargo RNA efficiently from K562 cells, with EPN24-MCP achieving the highest efficiency . By contIn addition, the ability to export RNA from non-human cells would enable reporting and delivery applications in animal models. Therefore, we tested RNA export in mouse fibroblasts (C3H/10T1/2) and hamster ovary cells (CHO-K1). Both cell lines efficiently exported RNA with export rates similar to those of HEK293 after accounting for transfection efficiency . Togethe58, viral pathogenesis59, tumor growth60, and other biological processes. However, existing technologies require either destructive sampling of the analyzed cells, which prevents longitudinal analysis of individual cells, or optical transparency, which is not available in most organisms. As an alternative approach, recovering RNA exported from cells at different timepoints could enable non-destructive tracking of cell populations without optical access. More specifically, if different clones export RNA bearing distinguishable barcodes, then the abundances of these exported barcodes, sampled from cell supernatant, could serve as a proxy for clone abundances to non-destructively resolve their population dynamics (Cell populations expand and contract over time. Technologies to track cell population dynamics have advanced our understanding of immune responsesdynamics .6 distinct barcodes (4 cells with <0.2% collision (coincidence) rate  rate .To demonstrate monitoring of cell population dynamics, we tracked populations cultured in the presence or absence of growth-inhibiting drugs to which they were either sensitive or resistant . More spWe first verified that this system accurately and reproducibly reported clone abundances. The majority (63%) of barcodes were detected in both cellular and exported RNA. These barcodes showed strong correlation in their abundances over a >100-fold dynamic range (Pearson r = 0.53) . ImperfeWe also characterized the sensitivity of this reporter system, defined by the minimum number of cells of a given clone that can be reliably detected. In a separate experiment, we sorted 10 cells exporting distinct clone barcodes into a single well containing a carrier population of ~30,000 unlabeled HEK293 cells and cultured them for 24 hours to allow accumulation of exported RNA, while limiting cell proliferation to at most a single cell division . SequencMonitoring exported RNA barcodes revealed the dynamics of cell populations responding to drug selection. Drug-resistant populations grew exponentially, while sensitive populations declined precipitously . Within Tracking individual clone barcodes revealed the dynamics of thousands of clones . ExamineTaken together, these results show that RNA export enables non-destructive monitoring of mammalian cell population dynamics with clonal resolution and high accuracy, reproducibility, and sensitivity.48. However, it is unknown whether mRNA can be transferred by EPN-based exporters, such as EPN24-MCP, and expressed in receiver cells at levels sufficient to achieve functional effects.A major challenge in gene and cell therapies is delivery of nucleic acids to specific cell types within an organism. In principle, RNA export could allow engineered sender cells to transfer RNA cargo to non-engineered receiver cells. EPNs have been pseudotyped with viral fusogens, which enable vesicle-cell fusion, to deliver proteins to cellsTo test whether pseudotyping enables RNA delivery by EPN24-MCP, we transiently co-expressed a fusogen – the glycoprotein G of vesicular stomatitis virus (VSV-G) – together with the RNA exporter EPN24-MCP and MS2-tagged cargo mRNA in HEK293T cells , culture61. Between these extremes, a 20:1 molar ratio of VSV-G expression plasmid to EPN24 expression plasmid optimized delivery efficiency and specificity.RNA delivery efficiency and specificity depended on the expression level of the fusogen . At low Cellular factors that enhanced RNA export  also enhTo characterize the dynamics of mRNA delivery and resulting protein expression, we monitored mCherry fluorescence over time in receiver cells. Expression was detected as early as 3 hours after transferring supernatant from sender cells to receiver cells . The majThe ability to simultaneously deliver multiple distinct RNA cargos would facilitate transfer of complex genetic programs. We therefore tested delivery of two fluorescent protein mRNA cargos from a single sender cell population . The optFinally, we tested whether the EPN24-MCP system is capable of delivering RNA directly from cell to cell in a co-culture setting. Sender cells were transfected with expression plasmids encoding the EPN24-MCP delivery system and a Cre recombinase cargo mRNA. As receiver cells, we used RFP-activating Cre reporter cells . These sThe ability to export RNA enables monitoring and manipulation of cell behaviors. Because performance in both applications depends on the number of RNA molecules available for detection or expression, export efficiency and specificity are crucial. Through systematic engineering, this study establishes a set of RNA exporters that efficiently and specifically package and secrete target RNA molecules from mammalian cells within protective nanoparticles. For viral capsid-based exporters, we factorized the activities of self-assembly and RNA binding, allowing independent optimization of efficiency and specificity . For EPN63 could tune functional properties, such as cargo capacity and stability. Unlike viral proteins46, nanocage parts are not expected to stimulate antiviral sensing pathways, potentially reducing their propensity for innate immune activation compared to viral capsids, although this remains to be tested experimentally. Importantly for cell-based therapeutic RNA delivery systems, the ability of EPN24-MCP to package target RNA with high specificity reduces risks of toxicity or undesired effects due to transfer of non-target RNA.Protein nanocages provide an ideal foundation for next-generation RNA exporters. Their modularity facilitates engineering, as demonstrated by their robustness to domain permutations and replacements . AlternaRNA export enables molecular information to be obtained non-destructively from living cells. The system described here allows clonally resolved non-destructive monitoring of cell population trajectories with single-cell sensitivity and daily time resolution in complex samples . Efficie64, and exporters protect RNA from degradation in whole blood .Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Michael B. Elowitz  and is publicly available as of the date of publication. DOIs are listed in the All original code has been deposited at Github , human lymphoblastoid cells (K562), human T cells (Jurkat), mouse fibroblasts (C3H/10T1/2), and chinese hamster ovary cells (CHO-K1) were cultured in tissue culture-treated plastic plates or flasks at 37 C in humidified chambers with 5% CO2. For HEK293, HEK293T, and HEK293FT cells, growth media consisted of Dulbecco’s Modified Eagle Medium (ThemoFisher), 10% fetal bovine serum (ThermoFisher), 100 units/mL penicillin, 100 μM streptomycin, 2 mM L-glutamine (ThermoFisher), 1 mM sodium pyruvate (ThermoFisher), and 1X Minimal Essential Medium Non-Essential Amino Acids (ThermoFisher). For K562 and Jurkat cells, growth media consisted of Roswell Park Memorial Institute (RPMI) 1640 Medium with GlutaMAX supplement (ThermoFisher), 10% fetal bovine serum (ThermoFisher), 100 units/mL penicillin, 100 μM streptomycin, and 1 mM sodium pyruvate (ThermoFisher). For C3H/10T1/2 cells, growth media consisted of Dulbecco’s Modified Eagle Medium (ThemoFisher), 10% fetal bovine serum (ThermoFisher), 100 units/mL penicillin, and 100 μM streptomycin. For CHO-K1 cells, growth media consisted of Alpha Minimum Essential Medium (Irvine Scientific), 10% fetal bovine serum (ThermoFisher), 100 units/mL penicillin, 100 μM streptomycin, and 2 mM L-glutamine (ThermoFisher). Cells were lifted from plates using 0.05% Trypsin-EDTA (ThermoFisher). Cells were routinely tested with MycoStrip (Invivogen) and confirmed to be negative for mycoplasma.Constructs used in this study are listed in the 48 (PDB 5KP9) and an X-ray crystal structure of MS2 coat protein77 (PDB 1MSC). Models were displayed and protein geometries were evaluated using PyMol molecular graphics system (2.5.3) (Schrödinger).To evaluate structural constraints on design of RNA exporters based on protein nanocages, we examined the design model of the I3–01 protein nanocage3.HEK293T cells were plated on 10 cm dishes with 6,000,000 cells per dish, and co-transfected the following day with 10 ug of RNA exporter plasmid and 10 ug of reporter plasmid using calcium phosphate. Media was harvested 48 hours after transfection. Exporter particles were purified and concentrated approximately 500-fold by ultracentrifugation in a cushion of 20% (w/v) sucrose in phosphate buffered saline (PBS). Particles from all export systems pelleted below the 20% sucrose, indicating that they have buoyant densities < 1.08 g/cm79 and Digital Micrograph software.For electron microscopy, as shown in For dynamic light scattering (DLS), as shown in We used an RT-qPCR assay to measure the abundance of specific RNA molecules in exported or cellular RNA. For exported RNA, RNA was extracted from 140 μL of supernatant using the Viral RNA Mini kit (Qiagen) according to manufacturer’s instructions with inclusion of carrier RNA. For cellular RNA, RNA was extracted from cells using the RNeasy Mini kit (Qiagen) according to manufacturer’s instructions with inclusion of 2-mercaptoethanol. RNA was treated with Turbo DNase (ThermoFisher) at 37 C for 30 min according to manufacturer’s instructions, including the use of inactivation and cation removal reagents. RNA was then reverse transcribed using iScript Reverse Transcription Supermix (Bio-Rad) at 25 C for 5 minutes, 46 C for 20 minutes, and 95 C for 1 minute. Typically, 10 μL of RNA was used as input . Quantitative polymerase chain reaction (qPCR) was performed on the CFX96 Touch system (Biorad) using iQ SYBR Green Supermix (Biorad) with 1 μL of reverse transcription product as input, final concentration of 300 nM per primer, and thermal cycling profile consisting of 95 C for 3 minutes, followed by 40 cycles of 95 C for 10 seconds and 67 C for 30 seconds. Primer sequences are listed in in vitro transcribed mCherry mRNA standard. The production of this RNA is described below. RNA was quantified using the Qubit RNA HS Assay kit (Fisher) and full-length product was confirmed using the RNA 6000 Pico kit with the Bioanalyzer instrument (Agilent). For determining efficiency, RNA was added to nuclease-free water and its abundance was measured using the full RT-qPCR protocol described above (starting with RNA extraction). Based on the measured abundance and the independently measured amount of input RNA (based on Qubit), we calculated the overall detection efficiency of the protocol to be 5.96 × 10−3 and this value was used to determine RNA abundance in input samples.To determine the overall efficiency of this protocol, we used an in vitro transcription as follows. Linear DNA for in vitro transcription was generated using PCR, simultaneously adding a 5’ T7 RNA polymerase promoter followed by AG dinucleotide and a 3’ 120-nucleotide poly-adenosine tract. The PCR product was purified using the DNA Clean and Concentrator-5 kit (Zymo). mRNA synthesis was carried out using the HiScribe T7 High Yield RNA Synthesis kit (NEB) with 500 ng of linear DNA template, 5 mM each of ATP, GTP, CTP, and N1-Methyl-Pseudouridine-5’-Triphosphate (TriLink), and 4 mM CleanCap (TriLink). The reaction was incubated at 37 C for 2 hours, followed by 15 minute DNase treatment, and finally RNA was purified using the RNA Clean and Concentrator-5 kit (Zymo). RNA was further treated with Turbo DNase (ThermoFisher) and purified again using the RNA Clean and Concentrator-5 kit (Zymo).We used mRNA standards to determine the efficiency of the RT-qPCR protocol; determine the relative abundance of clone barcode RNA by normalization to spike-in standards; and validate the RNase protection assay. These mRNA standards were produced by To determine the loss of RNA due to the cleanup steps of clarification and filtration, as shown in To measure the efficiency and specificity of RNA export by viral RNA exporters, as shown in To measure the efficiency and specificity of RNA export by protein nanocage-based RNA exporters, as shown in To measure the rate of RNA export, as shown in To characterize how the RNA export rate of Gag-MCP depends on the copy number of the MS2 export tag, as shown in To characterize how the RNA export rate of Gag-MCP depends on the expression levels of the exporter and reporter RNA, as shown in To test RNA export using expression of components from stable genomically integrated transgenes, as shown in in vitro transcribed mCherry mRNA, which was not packaged and therefore not expected to be protected from RNase activity, was diluted in H2O and used as input in place of media. Protection from RNase degradation was determined using samples lacking RNase and detergent as a reference.To characterize protection from RNase challenge, as shown in To characterize the stability of RNA encapsulated by Gag-MCP or EPN24-MCP during incubation in cell culture supernatant, as shown in in vitro transcribed mCherry mRNA, which was not packaged and therefore not expected to be protected from degradation, was diluted in H2O and used as input. Stability was determined using the samples extracted immediately  as a reference. Note that variability in the yield of RNA purification likely explains the apparent recovery of >100% of RNA after incubation.To characterize the stability of RNA encapsulated by Gag-MCP or EPN24-MCP during incubation in whole blood, as shown in To compare the rate of RNA export by EPN24-MCP to that of Gag-MCP, as shown in To estimate the cargo capacity of EPN24-MCP, we measured the dependence of export efficiency on cargo RNA length. We designed and expressed transcripts of increasing length by introducing non-coding sequences into the 3’ UTR of a cargo mRNA encoding the Cre recombinase. The abundances of cargo RNA within exporting cells  and in cMore specifically, to characterize how export rates depend on the length of RNA cargo, as shown in 53, in place of MCP, forming EPN24-PCP. HEK293T cells were transfected in 12-well plates with 375 ng of RNA exporter EPN24-MCP or EPN24-PCP plasmid and 1250 ng of mCherry reporter plasmid with either MS2 or PP7 aptamer export tags or no export tag, then RT-qPCR was used to measure reporter RNA abundance in supernatant at 48 hours after transfection. These EPN24-PCP constructs exported target RNA containing the PP7 aptamer export tag with efficiency comparable to that with which EPN24-MCP exported MS2-containing transcripts, albeit lower specificity  and UGCG (Uniprot Q16739) that also enhance release of HIV particles51. We used isoforms of STEAP3 (DNASU HsCD00081929) and SDC4 (DNASU HsCD00074146) that enhance production of exosomes24. For the gap junction protein Cx43 (DNASU HsCD00434989), we used a constitutively active mutant (S368A) that enhances transfer of exosomal contents to receiver cells24. HEK293T cells were transfected in 12-well plates with 375 ng of RNA exporter EPN24-MCP, 1250 ng of mCherry reporter plasmid, and 1250 ng of candidate export modulator expression plasmid, then RT-qPCR was used to measure reporter RNA abundance in supernatant at 48 hours after transfection.For testing whether overexpression of cellular factors can enhance RNA export, as shown in To test whether overexpression of a dominant negative inhibitor of the ESCRT pathway affects RNA export, as shown in In principle, target RNA could compete with non-target RNA for export. We therefore examined the dependence of non-target RNA export on the presence and abundance of target RNA. We focused on a representative non-target mRNA, GAPDH, which is highly expressed in HEK293T cells. The abundance of exported GAPDH mRNA, as measured by RT-qPCR, reflected the specificity of RNA export systems, as measured by genome-scale RNA sequencing. In the supernatant of cells expressing MMLV Gag, but not its target RNA, GAPDH mRNA was present at elevated abundance  compared with cells expressing MMLV Gag together with its target RNA mCherry-Psi   . SimilarTo test export of non-target GAPDH mRNA by MMLV Gag, as shown in To test export of RNA from human blood cell lines, as shown in To test export of RNA from rodent cell lines, as shown in To characterize RNA export by sequencing, as shown in To sequence exported RNA, External RNA Controls Consortium (ERCC) synthetic spike-in RNAs (ThermoFisher) were diluted 1:200 in nuclease-free water and 1 μL was added per 560 μL of Buffer AVL (Qiagen). RNA was extracted using the Viral RNA Mini kit (Qiagen) according to manufacturer’s instructions with 280 μL of supernatant as input. RNA was treated with Turbo DNase (ThermoFisher) and purified using the RNA Clean and Concentrator-5 kit (Zymo). Sequencing libraries was prepared using the SMARTer Stranded Total RNA-Seq v2 Pico Input kit (Takara) with 3–15 ng of RNA input (fixed volume of 7 μL of input RNA), no fragmentation step, and 16 cycles of amplification by PCR. Libraries were sequenced by Novogene using the NovaSeq 6000 platform (Illumina) with 20–30M paired-end 150 bp reads per sample.To sequence cellular RNA, after media collection, cells were harvested by adding 350 μL of ice-cold Buffer RLT (Qiagen) containing 2-mercaptoethanol directly to the well, scraping the well with a pipette tip, and storing the solution at −80 C. RNA was extracted using the RNeasy Mini kit (Qiagen), treated with TurboDNase (ThermoFisher), and purified using RNA Clean and Concentrator-5 kit (Zymo). mRNA sequencing libraries were prepared by NovoGene. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads, then libraries were prepared using the NEBNext Ultra II RNA kit for Illumina (NEB), which uses random hexamer priming, and sequenced using the NovaSeq 6000 platform (Illumina) with 20–30M paired-end 150 bp reads per sample.80 with the ENCODE standard options except “--outFilterScoreMinOverLread 0.3 --outFilterMatchNminOverLread 0.3 –outFilterMismatchNmax 20 --outFilterMismatchNoverLmax 0.3 --alignSJoverhangMin 5 --alignSJDBoverhangMin 3”. This reference consisted of the human genome GRCh38.103 with ERCCs  and EGFP, mCherry, and mTagBFP2 coding sequences. Uniquely mapped reads that overlap with genes were counted using HTSeq-count (0.13.5)81 with default settings except “-m intersection-strict”. To normalize for differences in sequencing depth across samples, we rescaled gene counts to counts per million (CPM).Reads from both exported and cellular RNA sequencing were aligned to a custom reference genome using STAR (2.7.8a)To normalize the abundance of extracellular RNA across supernatant samples using the ERCC spike-in standards, we used the mock transfected sample as a reference. For each ERCC transcript , we calculated the ratio of its abundance in each sample to its abundance in the reference sample. We then calculated the geometric mean of this ratio across the 63 transcripts having mean abundance >10 CPM. We normalized gene abundances by dividing all counts in each sample by this ratio (in CPM space), achieving equivalent mean abundance of these ERCCs across all samples. We refer to this normalized abundance as counts per million of standard (CPMS).Abundance and enrichment of endogenous transcripts in supernatant, as shown in 82 was used to analyze pathway enrichment among transcripts overrepresented in supernatant compared with cells (defined as having expression levels exceeding 9 CPM in cells and enrichment of at least 16-fold in supernatant versus cells). Overrepresentations of GO terms among these enriched genes were only marginally significant and inconsistent across exporters. For example, the most significant overrepresentations were miRNA-mediated gene silencing , macromolecule metabolic process (FDR = 0.046), and trans-Golgi network transport vesicle (FDR = 0.023) for MMLV Gag, Gag-MCP, and EPN24-MCP, respectively. Similar results were obtained with varying expression level and enrichment cutoffs.PANTHER55. By contrast, engineered viral and nanocage-based exporters, which were more specific for their target RNA, yielded lower detection rates of cellular transcripts, as expected  includes RNA from endogenous extracellular vesicles (EVs), as well as lysed cells and other natural sources of export. In control samples lacking exporters, cell-free RNA was detected in supernatant, which reflects the contribution of these endogenous export sources. In samples where RNA exporters were expressed, reporter transcripts were detected at much higher abundance in comparison with the control samples, indicating that export via engineered RNA export systems occurs at much higher rates than via endogenous pathways. We quantified off-target export by comparing samples having exporter versus negative control samples lacking exporter. Because both of these types of samples include endogenous EVs, any differences detected in this comparison cannot be explained by endogenous EVs, unless these EVs were induced by the engineered RNA export system itself.83 in R (4.0.5) comparing raw gene counts in cells transfected with and without RNA exporters.To characterize alterations to the cellular transcriptome due to RNA exporter expression, as shown in 84.To image cells transiently expressing RNA exporters, as shown in 84.To image cells stably expressing RNA exporters, as shown in d was calculated using the equation Td = Δt / log2(N2/N1), where Δt is the time difference between the timepoints (24 hours), N1 is the cell count at 24 hours, and N2 is the cell count at 48 hours. Three replicate wells were counted for each sample at each timepoint and their variance was propagated to the estimate of Td. Cells remained sub-confluent at 48 hours after transfection and exhibited stable expression of transfected plasmids based on fluorescent protein markers at both 24 and 48 hour timepoints.For determining the doubling time of cells expressing RNA exporters, as shown in For flow cytometry analysis of cellular toxicity of RNA exporter expression via transfection of expression plasmids, as shown in For flow cytometry analysis of cellular toxicity of RNA exporter expression from stable genomically integrated transgenes, as shown in In both cases, cells were stained using DRAQ7 (ThermoFisher) at 3 μM for 10 minutes on ice. Cells were passed through a 35 μm filter and analyzed by flow cytometry on a CytoFLEX S instrument (Beckman Coulter). Data were analyzed using FlowJo software (10.8.1). Because dead cells could exhibit different forward and side scattering characteristics from live cells, we avoided potential undercounting of dead cells by analyzing DRAQ7+ events among all events without gating on forward or side scatter. As a positive control for detection of toxicity, cells were heat killed by incubation at 65 C for 5 minutes, then placed on ice for 5 minutes before staining.84, then spots were detected by applying a Laplacian of Gaussian filter followed by local maximum spot detection, as implemented in the detect_spots function of Big-FISH (0.6.2)85.To determine the relative abundances of secreted particles with different exporter and cargo configurations, HEK293T cells were plated in 48-well plates and transfected with 75 ng of EPN24-MCP-T2A-GFP plasmid and 250 ng of mCherry reporter plasmid . As a control, the reporter plasmid was omitted. Media was replaced with 1 mL of fresh media at 8 hours after transfection. Media was harvested at 48 hours after transfection, clarified by centrifugation at 3000 g for 5 minutes, passed through a cellulose acetate filter with 0.45 μm pore size (VWR), and stored on ice at 4 C for 12 hours. 20 μL of media was deposited in a well of a 24-well glass-bottom plate (MatTek), dried by incubation at 37 C, rehydrated with 50 μL of DPBS. Imaging was performed using a Nikon Ti Eclipse inverted confocal microscope equipped with a 50 μm pinhole spinning disk (Yokagawa), 60x Plan/Apo Ph3 DM oil objective , and Andor Zyla 4.2 sCMOS camera. To count particles, images were passed through a white tophat filter with a disk-shaped footprint with a radius of 5 pixels using scikit-image (0.19.3)The relative abundance of particles across conditions was normalized using the particle count of media from cells transfected with the EPN24-MCP and mCherry-MS2×12 expression plasmids as the reference, as shown in Stable cell lines used in this study are listed in the To create stable drug-resistant cell lines, as shown in To create stable reporter cell lines, as shown in To create stable cell lines expressing the Gag-MCP exporter and mCherry-MS2×8 reporter RNA (denoted cFH38), as shown in To genetically label clones with exportable RNA barcodes, we created diverse lentiviral barcode libraries. We cloned a gene fragment consisting of the EF1 promoter, an mCherry fluorescent protein marker, eight tandem repeats of the MS2 stem loop aptamer (denoted MS2×8), woodchuck hepatitis virus post-transcriptional regulatory element (WPRE), and a barcode cloning region (containing restriction enzyme digestion sites used for the cloning procedure described below) into the pCDH lentivirus backbone vector (System Biosciences). After cloning to insert the diverse barcode, the barcode region contained a 5 bp viral index barcode, which is shared by members of a barcode library , and a 27 bp clone barcode, which consists of random bases alternating between A/T and G/C to ensure balanced GC-content .To clone the diverse barcode library, we first generated a diverse pool of barcode inserts. We synthesized a 60 bp DNA oligo containing hand-mixed random bases and flanking primer binding and restriction digestion sites (IDT) . We performed primer extension using this DNA fragment and a complementary primer (oFH180), each at 10 uM, with KAPA Hifi Ready Mix (Roche) and the following thermal profile: 95 C for 3 minutes, 98 C for 20 seconds, 50 C for 15 seconds, and 72 C for 1 minute. We purified the products using the DNA Clean and Concentrate-5 kit (Zymo), digested them using KpnI and NotI (ThermoFisher), and purified the products again using the DNA Clean and Concentrate-5 kit (Zymo). We digested the vector using KpnI and NotI (ThermoFisher), dephosphorylated it using shrimp alkaline phosphatase (ThermoFisher), and purified it using the DNA Clean and Concentrate-5 kit (Zymo). We ligated the barcode insert and vector at a molar ratio of 10:1 (insert:vector) using Ligation Mighty Mix (Takara) by incubating at 16 C for 12 hours, then purified the products using the DNA Clean and Concentrate-5 kit (Zymo). To remove residual uncut vector backbone, we digested this product using SmiI (ThermoFisher), purified the products using the DNA Clean and Concentrate-5 kit (Zymo), and eluted in nuclease-free water. We transformed this DNA into Endura cells (Lucigen) by electroporation using the Gene Pulser Xcell system (Biorad) with a 1 mm cuvette at 10 uF, 600 ohms, and 1800 V following manufacturer’s instructions. We recovered the transformation products by adding 975 μL of recovery media, incubated at 37 C rotating at 250 rpm for 1 hour, plated the liquid on LB Lennox agar (Sigma) bioassay plates, and incubated the plates at 30 C for 16 hours. We scraped all colonies off the plates and extracted plasmid DNA using the ZymoPure II Maxiprep kit (Zymo) according to manufacturer’s instructions, except with elution buffer prewarmed to 50 C and elution performed on column for 10 minutes and including EndoZero treatment. The final plasmid sequence was verified using nanopore sequencing (Primordium).To prepare lentivirus, HEK293T cells were plated on 10 cm dishes with 6,000,000 cells per dish. Cells were co-transfected the following day with 10 ug of lentiviral transfer plasmid, 10 ug of psPAX2, and 10 ug of pMD2.G packaging plasmids using calcium phosphate. Media was harvested at 48 hours after transfection and stored at −80 C until further use.To characterize the diversity of the barcode libraries, as shown in 78 based on barcodes observed in replicate resamplings at varying depths, as shown in To identify barcode sequences within each read, we found the sequences that flank the barcode region (GCGGCGCGCC and GCGGCCGCAA). We extracted the barcode sequence as the sequence located between those flanking sequences. Most reads (>90%) matched the expected barcode length of 32 bp and the remainder were predominantly accounted for by uncut vector backbone lacking a barcode insert. Total barcode diversity was estimated using the Chao1 capture-recapture estimatorFor monitoring population dynamics, as shown in in vitro transcription as described above.We used a synthetic RNA spike-in standard to normalize clone barcode abundance across samples. This standard RNA was identical to the exported clone barcode RNA, including having identical GC content, except that it contained a fixed 32 bp barcode sequence in place of the random sequence. RNA was synthesized by We devised a simple PCR-based library preparation method for reading out exported RNA barcode abundances from supernatant, as shown in For characterizing the accuracy of barcode abundances measured in exported RNA, as shown in 86 with parameters “--maximum-overlap=75 --max-mismatch-density=0.5”. Barcodes were extracted from the merged reads as the sequence located between the barcode-flanking sequences (5’-GCGGCCGC and 5’-GGCGCGCC), confirmed to match the designed 32 bp sequence (NNNNNWSWSWSWSWSWSWSWSWSWSWSWSWSW), and separated into the 5 bp viral index barcode and the 27 bp clone barcode. Viral indexes were assigned to references, requiring perfect identity to a reference sequence (discarding reads lacking perfect identity). Within each population marked by a distinct viral index, clone barcodes were clustered to correct PCR and sequencing errors at a Levenshtein distance of one using Starcode (1.4)87 with parameters “--dist 1 --threads 16”.To identify and count clone barcode sequences, paired-end reads were merged using FLASH (1.2.11)88). The knee point threshold was set to 1% of the 99th percentile of read abundance among the top N = 5,000 barcodes, where N is the expected maximum number of barcodes . Barcodes were further filtered to exclude those with fewer than 10 reads. To enhance overall detection sensitivity for clone barcodes having changing abundance (e.g. barcodes that went extinct), filtering was performed separately for each timepoint, then resulting calls for each barcode were propagated across timepoints, such that a barcode was excluded if and only if the filter excluded it at all timepoints .We developed an algorithm to distinguish clone barcodes from erroneous sequences based on the distribution of read counts. Erroneous sequences can arise from residual PCR and sequencing errors that were not corrected by Starcode, resulting in sequences that are represented by few reads . To remove these sequences in an unbiased manner, we used a knee point filter similar to that used in 10X Genomics CellRanger 2.2  . Finally, a normalized barcode abundance matrix was formed with each clone barcode represented by a row and each timepoint represented by a column.Total abundance of each drug-resistant or -sensitive population was determined by summing the abundance of all clones belonging to that population (in CPMS space) and plotted at each timepoint, as shown in f(t) = Aekt to each clone abundance trajectory, where f(t) is clone abundance (in units of CPMS) and t is time (days), using non-linear least squares with initial parameter guesses of A = 10,000 and k = 0, as implemented in the curve_fit function of scipy (1.4.1). To conservatively estimate growth rates, f(t) was set equal to the detection limit in samples in which a clone was not detected, thus providing a detection-limited estimate of the growth rate. Examples of fits are shown in 2) < 0.9, which predominantly removed clones that were detected at only one or two timepoints. Distributions of fitted growth rates k are shown in To determine clone growth rates, we fit an exponential growth model Rarefaction analysis was performed to ensure that sequencing depth was sufficient to saturate clone discovery. We sampled 1, 2, 5, 10, 20, 50, 100, 200, 500, 1,000, 2,000, 5,000, 10,000, 20,000, 50,000, 100,000, 200,000, 500,000, 1,000,000, 2,000,000, 5,000,000, or the totality of reads per library with replacement. The number of unique barcode sequences was determined and plotted as a function of the number of reads sampled, as shown in For characterizing the reproducibility of the reporter system, as shown in For characterizing the accuracy of the reporter system, as shown in To determine the sensitivity of detecting exported RNA originating from single cells, we prepared, barcoded, and sorted cell populations as described above, except we sorted only 10 barcode-labeled zeocin-resistant cells into a single well of a 48-well plate (with eight replicate wells) together with a carrier population of 29,990 HEK293T cells. Media was harvested 24 hours after sorting. We confirmed by microscopy that most labeled cells remained solitary at this time (data not shown), suggesting that they had not divided and represented single-cell clones, as expected based on the ~24-hour doubling time of HEK293 cells. Sequencing libraries were prepared from exported RNA as described above. Reads were preprocessed as described above through the step of barcode clustering using Starcode. Then clone barcode detection by knee point threshold was performed as described above, except using N = 10 (because a maximum of N = 10 cells are expected based on cell sorting). The results of this clone barcode detection procedure are shown in To determine the rate at which cells survived single-cell sorting, we sorted one HEK293T cell per well of three 96-well plates, with sorting performed as described above. We cultured the cells for 7 days, then counted the number of wells having surviving cells by microscopy. Out of 288 total wells, 185 wells contained surviving cells, providing an estimated survival rate of 64 ± 6% .Because cell survival rates can depend on the number of cells sorted into a well, which could in turn affect estimates of reporter sensitivity, estimates of cell survival were refined by analyzing results from bulk sorting of 10,000 barcoded cells per well. More specifically, in the population dynamics experiments performed in the absence of drug selection, we sorted 10,000 cells together into each well, then recovered 3,956 ± 264 (mean ± s.d. of 2 experiments) clone barcodes from each population after 6 days of culture, corresponding to a survival rate of 40 ± 3%. Thus, the cell survival rate of 64 ± 6% estimated from single-cell sorting does not underestimate the survival rates obtained when sorting larger populations.These results also demonstrate sensitive detection of exported reporter transcripts with both exporter and reporter genes stably integrated in the genome, and the reporter gene present at single copy.To characterize RNA exporter expression dynamics during the population dynamics experiment, as shown in To test delivery of Cre-encoding mRNA by EPN24-MCP or Gag-MCP, as shown in Effects of fusogen plasmid dosage, as shown in To measure the dynamics of delivery and expression of mCherry fluorescent protein by the EPN24-MCP system, HEK293T cells were plated on 12-well plates with 300,000 cells per well. Cells were co-transfected the following day with 375 ng of EPN24-MCP exporter plasmid, 50 ng of VSV-G fusogen plasmid, 500 ng of mCherry-MS2×8 cargo plasmid, and 625 ng each of CIT and NEDD4LΔC2 export enhancer plasmids. Exporter plasmid was omitted as a control. Media was replaced with 1 mL of fresh media at 8 hours after transfection. At 24 hours after transfection, HEK293 cells were plated on 24-well plates with 50,000 cells per well to serve as receiver cells. At 48 hours after transfection, the conditioned media was harvested from sender cells, clarified by centrifugation at 3000 g for 5 minutes, and passed through a cellulose acetate filter with 0.45 μm pore size (VWR). Media was then removed from the receiver cells and replaced with 1 mL of conditioned media. Receiver cells were incubated for 0, 3, 6, 12, 24, 32, or 48 hours after media transfer, lifted from the plate, passed through a 35 μm filter, and analyzed on a CytoFLEX S flow cytometer (Beckman Coulter). Data were analyzed by using FlowJo software (10.8.1) to gate for live single cells based on forward and side scatter, then for mCherry-expressing cells, and fraction of cells expressing RFP was calculated.Delivery of two cargo RNAs, as shown in 84. Mean pixel intensity in the RFP channel was calculated in circular shells of varying radii, as shown in To test delivery of mRNA in a co-culture context, as shown in Quantification and statistical analysis was performed using Python version 3.7.7. Details of statistical tests, including statistical tests used, exact number of samples, and dispersion and precision measures, are indicated in the appropriate figure legend.http://rnaexport.org.Detailed protocols and troubleshooting information for RNA export experiments are available at 1Figure S1. Design and characterization of engineered viral RNA exporters, Related toZip indicates that MCP is fused to the C-terminus of Zip). The “∆pol” variant lacks a slippery frameshift-inducing sequence within the HIV Gag coding sequence. (K) Engineered viral RNA exporters secreted target RNA bearing export tags into culture supernatant with varying degrees of efficiency and specificity. Wild-type HIV Gag was not evaluated for RNA export because the HIV packaging signal sequence has not been unambiguously defined. MSx12 indicates twelve MS2 hairpins in a tandem array. (L) Expression levels of cargo RNA molecules cannot account for differences in RNA export efficiency. (M and N) Stability of RNA packaged and secreted by Gag-MCP or in vitro transcribed mRNA (not packaged by an RNA exporter) during incubation in cell culture supernatant (M) or whole mouse blood (N) at 37 C. Data for (M) and (N) are mean and standard deviation of 3 technical replicates. In (C), (F), (G), (H), (I), (K), and (L), each dot represents one technical replicate. In (C), (F), (G), (H), and (I), line indicates the mean of replicates. In (K) and (L), bar indicates the mean of replicates. In (D), (E), (G), (H), (I), and (K), dashed line indicates lower limit of quantification.Figure S2. Design and characterization of protein nanocage-based RNA exporters, Related toin vitro transcribed mRNA (not packaged by an RNA exporter) during incubation in cell culture supernatant (E) or whole mouse blood (F) at 37 C. Data for (D), (E), (F) are mean and standard deviation of 3 technical replicates.  To evaluate the cargo capacity of the EPN24-MCP system, we measured the expression level in exporting cells (G) and abundance in supernatant (H) of cargo RNAs of increasing length. (I) Export efficiency was, within 3-fold, insensitive to cargo RNA length up to 9.8 kb, as revealed by computing the ratios of RNA abundances in supernatant and cells, which is a metric of efficiency that accounts for the availability of cargo RNA. Data for (G), (H), and (I) are mean and standard deviation of 3 biological replicates. (J) To test enhancement of RNA export by modulators of cellular secretion pathways, we co-expressed the EPN24-MCP RNA export system with a panel of 6 candidate modulators. (K) Two activators of the ESCRT pathway, NEDD4L and CIT, enhanced RNA export rates. p-values were calculated using Student’s two-sided t-test. (L) Co-expressing an inhibitor of ESCRT-dependent secretion, VPS-E228Q, reduced RNA export rates. (M) To test modular design of RNA targeting, we fused the sequence-specific RNA binding protein PP7 coat protein (PCP) to EPN24, yielding EPN24-PCP. This system demonstrated efficient export of cognate cargo RNA tagged with the PP7 stem-loop aptamer, albeit with lower specificity than EPN24-MCP. MS2 and PP7 export tags each consisted of 12 tandem repeats of the corresponding stem-loop aptamer (denoted MS2 or PP7). In (A), (B), (K), (L), and (M), each dot represents one technical replicate. In (A), (K), (L), and (M), bar indicates the mean of replicates. In (B), line indicates the mean of replicates and dashed line indicates lower limit of quantification.Figure S3. Additional genome-scale characterization of RNA export efficiency and specificity, Related toFigure S4. RNA exporters are non-toxic and do not perturb cellular morphology, growth, or transcriptome, Related toFigure S5. Barcode libraries, workflow, and performance of RNA-export based population dynamics reporter system, Related to78. (B) Barcode abundance distributions were nearly uniform. (C) Labeling capacity of each library was estimated by using simulations to determine the probability of barcode collisions (coincidence) within labeled cell populations of varying sizes. Data for (C) are the mean and standard deviation of 100 replicate simulations (resamplings). Note range of the y-axis scale. (D) Workflow for counting exported RNA barcodes using sequencing. (E) Flow cytometry revealed spontaneous silencing of RNA exporter expression in a subpopulation of cells during the experiment. Data for (E) are mean and standard deviation of 2 biological replicates per time point. (F) To measure reporter sensitivity, as defined by the minimum number of cells of a given clone that can be reliably detected, we sorted 10 uniquely labeled cells into a single well, cultured them for 24 hours to allow their RNA barcodes to be exported, then collected and sequenced the barcodes from culture supernatant. We estimated the sensitivity as the number of unique barcodes detected per well. (G) Barcodes were detected from 5.2 ± 3.2 cells per well (mean ± s.d. of 10 replicate wells) out of a possible maximum of 10 cells. Because only 64 ± 6%  of cells survived sorting in control experiments, these results suggest a lower bound of 81% on detection sensitivity for RNA barcodes exported by a single cell at daily time resolution. Plots show the read counts for unique barcodes detected in each well. Dashed line indicates the minimum read count cutoff used to discriminate genuine cell detection events from erroneous barcodes, which was determined using an unbiased knee point detection algorithm (lgorithm . Note thFigure S6. Additional characterization of monitoring population dynamics using RNA export and sequencing, Related toFigure S7. Optimizing and characterizing cell-to-cell delivery of RNA, Related to


Recent global events have drawn into focus the diversity of options for combatting disease across a spectrum of prophylactic and therapeutic approaches. The recent success of the mRNA-based COVID-19 vaccines has paved the way for RNA-based treatments to revolutionize the pharmaceutical industry. However, historical treatment options are continuously updated and reimagined in the context of novel technical developments, such as those facilitated through the application of synthetic biology. When it comes to the development of genetic forms of therapies and vaccines, synthetic biology offers diverse tools and approaches to influence the content, dosage, and breadth of treatment with the prospect of economic advantage provided in time and cost benefits. This can be achieved by utilizing the broad tools within this discipline to enhance the functionality and efficacy of pharmaceutical agent sequences. This review will describe how synthetic biology principles can augment RNA-based treatments through optimizing not only the vaccine antigen, therapeutic construct, therapeutic activity, and delivery vector. The enhancement of RNA vaccine technology through implementing synthetic biology has the potential to shape the next generation of vaccines and therapeutics. However, they often fall short when addressing complex diseases or diseases with genetic roots. Additionally, the cost and extended development timelines associated with these approaches have the potential to limit their application to emergent diseases such as SARS-CoV-2. Synthetic biology, a field that has already had a significant impact on the agricultural, environmental, and renewable biofuel industries2, has emerged as an attractive alternative drug development approach.The pharmaceutical industry has long depended on synthetic chemistry approaches to develop novel therapeutics. These approaches, which have led to numerous breakthroughs in drug development, have typically relied on screening compound libraries populated by a range of molecules derived from a set of known and robust chemistry reactions in order to achieve improved efficacy, safety, and pharmacokinetic properties3. These scientific breakthroughs allowed scientists to manipulate DNA in unprecedented ways and opened the door for a wave of innovation in genetic engineering, such as the invention of polymerase chain reaction in 19834, which allowed researchers to amplify DNA sequences for use in genetic manipulation. Not long after, in the 1990s genomics emerged as a field that involved sequencing entire genomes and provided researchers with complete maps of genomes5, punctuated by the completion of the human genome project in 20036. These technological advancements have since led to the creation of a vast and ever-growing catalog of cellular components and their interactions which, in-turn, has enabled a bottom-up approach to designing regulatory networks and circuits that can be used for the biosynthesis of various biochemical products 7. Moreover, the modular components within this catalog can be assembled and tested to identify combinations that yield further advantages beyond each individually. One such modular component, a genetic toggle switch, was engineered into Escherichia coli in the early 2000’s8, which resulted in the creation of the first synthetic biological system8. This breakthrough paved the way for further advances such as bacteria that produce biofuels or cells programmed to target cancer cells.Synthetic biology is a scientific field that involves the rewiring of organisms or biomolecular parts for new and desired abilities. This encompasses diverse applications, from engineering new or improved activities in enzymes, heterologous production of commodity chemicals, assembly of genetic parts in a synthetic manner and developing cellular therapies. Although synthetic biology itself is a relatively new field that emerged in the early 2000’s, the tools required to engineer living systems were under development for decades before the field of synthetic biology was officially founded and its roots can be traced all the way back to the discovery and development of genetic engineering techniques in the 1970s9, gene regulatory networks10, and even entire genomes12, enabling scientists to study complex biological processes and even create synthetic organisms13. However, with the rise of RNA therapeutics, there has been a growing interest in developing synthetic systems exploiting the unique attributes of RNA molecules. RNA is more than just a messenger—it has a direct role in regulating cellular behavior and, in the past few years, large libraries of RNA parts affecting almost every step of biological control have become available14. RNA-based systems constructed using these libraries are safer than those constructed from DNA as they do not integrate into the host genome, making them suitable for therapeutic applications with higher safety standards15. Unlike DNA-based systems, RNA-based systems, built from RNA devices and circuits, are fast-acting as they do not require transcription16. Using diverse libraries of RNA components, researchers have begun to generate RNA-based systems that couple environmental sensing with functional outputs for therapeutic synthetic biology applications18.In the past, synthetic biologists have primarily used DNA as the molecule of choice for designing synthetic systems. As a result, synthetic DNA had been instrumental in the development of artificial genesThe recent success of mRNA COVID-19 vaccines has sparked a surge in interest in RNA therapeutic technology and how the field of synthetic biology can be employed. Particularly, there are some challenges associated with RNA technology which can be addressed using synthetic biology. For example, base modifications and mRNA circularization have been employed to reduce mRNA immunogenicity and improve mRNA’s lifespan respectively. Each of these represents the combination of various biomolecular features in novel and synthetic ways to enhance the native function of this malleable nature of RNA. As this technology advances, scientists are discovering new opportunities for combining an RNA platform with synthetic biology in creating novel therapeutics that could revolutionize the pharmaceutical and healthcare industries. This could even include combining various types of RNA to increase its specificity and enable it to become dynamically responsive. In this review, we will explore how synthetic biology can be employed in the context of RNA technology to create powerful therapies and treatments as researchers seek to combine the two disciplines in novel ways. Specific focus will be given to how synthetic biology principles can be used to advance RNA vaccines.19, ribozymes21, and RNA switches22), can serve as sensors, regulators, or signal molecules. When undergoing the application of synthetic biology, these devices can either be improved through the incorporation of new parts or used in combination with other devices. When combined in a network-like structure, RNA devices can form synthetic circuits that can perform even more complex functions such as gene expression regulation23, signal amplification24, and logic operations25. Unsurprisingly, these devices and circuits, with their ability to control cell behavior, have already been extensively applied to the development of novel diagnostic strategies and therapeutics . These devices have been engineered to detect a wide range of viral pathogens, including SARS-CoV-2 and other coronavirueses35, West Nile Virus36, Zika virus37, and Ebola virus38. In recent years, aptamer-based sensors, or aptasensors, have also gained prominence for the detection of cancer biomarkers 40, cardiovascular disease 42, neurological disease (amyloid β)44, and infectious disease46.While different RNA devices can be employed in these tools, the general strategy remains the same: design an RNA molecule that can bind to a sequence of pathogenic nucleic acid sequence, or other non-nucleic acid targets, which then results in the generation of a detectable signal 47. Such cell therapies include circulating cells, implantable cells, and tissue resident human cells47. For example, there has been growing interest in using RNA devices to control engineered T cells  to improve the safety profile and therapeutic outcomes of CAR-T therapy17. CAR-T cells represent a form of immunotherapy where CARs have been engineered to recognize and eliminate cells expressing tumor antigens. This approach has demonstrated profound clinical efficacy against hematological cancers50. Despite promising clinical results, severe adverse events, such as cytokine release syndrome, have complicated treatment and have occasionally proven fatal51. RNA devices, such as RNA switches, can be engineered to respond to cues such as changes in temperature or the presence of a small molecule to trigger the deactivation of the engineered T cells52. Such devices can also be designed to be activated in the presence of a specific molecule or environmental cue, triggering the expression of the CAR and enabling the T cells to target cancer cells52. This approach has the potential to reduce the risk of adverse events associated with CAR-T cell therapy and improve patient outcomes.The use of RNA devices allows for the engineering of living therapeutics, such as cell therapies, that have the ability to sense and respond to environmental factors that provide information about their location, relevant disease states, and the therapeutic window timingRNA devices have also become increasingly popular as a means of modulating gene expression and have enabled researchers to develop gene therapies for a range of diseases. As such, significant efforts have been made to manipulate the expression or activity of therapeutic targets utilizing three main approaches (1) ASOs, (2) siRNAs, and (3) CRISPR. Each of these strategies utilize different mechanisms to repress gene expression.53. ASO therapeutics can be broken down into two main categories, (1) those that cleave target mRNA and (2) those that regulate the splicing of pre-mRNA54. The first category of drugs cleaves target mRNA by binding to the target mRNA sequence, cleaving the sequence between the DNA and RNA duplex via RNase H activity, and thus promoting the degradation of the target mRNA54. FDA-approved drugs using this mechanism of action (MoA) include mipomersen and inotersen, which are used to treat homozygous familial hypercholesterolemia55 and hereditary transthyretin amyloidosis56, respectively. The second category of ASO therapeutics uses a steric hindrance-based mechanism to regulate the splicing of pre-mRNAs54. This MoA has been of particular interest in the treatment of inheritable diseases and the drugs golodirsen and eteplirsen, both of which target Duchenne muscular dystrophy57, and nusinersen, which targets spinal muscular atrophy, have already been approved59.ASOs are single-stranded RNA that are complementary to mRNA and that regulate gene expression by inhibiting translation and promoting degradation of RNA60. Unlike ASOs and most other RNA pharmaceuticals, siRNA molecules are double-stranded, which facilitates their activity without chemical modification. Currently, there are only three FDA-approved drugs that take advantage of siRNA; these drugs include patisiran, givosiran, and lumasiran, which target hereditary transthyretin-mediated (hATTR) amyloidosis61, acute hepatic porphyria62, and primary hypercholesterolemia or mixed dyslipidemia63, respectively.siRNA make use of the RNA interference (RNAi) pathway, in which siRNA interacts with Argonaute (AGO) protein to form RNA-induced silencing complexes (RICS) that suppress target mRNA expression32. This method has been extensively studied and successfully employed in the treatment of age-related macular degeneration (AMD) through the use of Vascular Endothelial Growth Factor-binding Pegaptanib64.RNA aptamers also provide an effective way to control gene expression by engineering them to bind only to specific proteins that are engaged in the process of gene expression, such as transcription factors. RNA aptamers offer several advantages due to their ability to target both intracellular and extracellular molecules. Unlike other RNA-based therapeutics that require entry into the cell to perform their functions, RNA aptamers can directly bind to extracellular targets and hinder or, in some cases, stimulate their functions65. To date, synthetic biology has been applied to this system in several ways. For example, RNA devices which use small molecule- and light-responsive aptamers to regulate the spacer region of a gRNA can be devised66. In one case, an RNA aptamer was designed to bind to an small molecule, resulting in a conformation change that prevented Cas9 from binding to target DNA67. Upon the removal of stimuli, however, the RNA structure of the aptamer is changed into an active state that allows a catalytically inert ‘dead’ CRISPR-Cas9 (dCas9) to bind and regulate gene expression. Other systems use riboswiches in the 5′ region of the gRNA functioning cis-acting ribozyme that exposes the spacer sequence in the presence of the aptamer ligand68. Furthermore, combining a CRISPR effector with an anti-CRISPR gene and microRNA (miRNA) response elements (MREs) in the 3′ untranslated region has enabled researchers to restrict gene editing to certain tissues69. With this method, tissue-specific MREs direct repression of the anti-CRISPR proteins and enable tissue-specific inhibition or activation of the CRISPR effector.The development of the CRISPR-Cas system has been revolutionary within the field of gene therapy by empowering direct and specific genome editing. This is achieved through using guide RNA (gRNA) to direct introduction of a double-stranded break in DNA70. Compared to conventional vaccines, such as virus-, viral-vector-, and protein-based vaccines, the synthetic nature of RNA vaccines offers advantages in terms of speed of development, scalability, safety, and immunogenicity71. For example, their synthetic, cell-free production method enable mRNA vaccines can be produced quickly and at a large scale making them particularly well-suited for addressing emerging infectious diseases, such as COVID-1972. In fact, mRNA vaccines from Pfizer/BioNTech and Moderna were conceived of, designed, clinically tested, and granted Emergency Use Authorization in under a year73.RNA vaccines represent an exciting new opportunity for the application of synthetic biology as they are designed to introduce synthetic RNA encoding for pathogen-specific antigens, such as the SARS-CoV-2 spike protein, into cells to trigger an immune response against target pathogens74, dengue virus75, herpes simplex virus type 2 (HSV-2)76, rabies77, and Zika virus78. There have also been efforts to develop mRNA vaccines to protect against bacterial diseases such as Mycobacterium tuberculosis (M.tb), one of the world’s leading infectious killers79. However, using host synthetic machinery to produce bacterial proteins can lead to issues such as difficulties in folding, transport, and post-translational modifications80. There is also currently no way to produce more complex biomolecule antigens, such as the polysaccharides found in the Streptococcus pneumoniae vaccines  in human cells using mRNA vaccines, limiting their ability to compete with well-established bacterial vaccines. Additionally, mRNA vaccines are being investigated for potential use in cancer therapy81. Initial studies have demonstrated the ability of mRNA vaccines to induce an immune response against cancer cells, enabling the body’s own defense system to recognize and attack them, with promising results for the treatment of breast cancer82 and prostate cancer83.The uses of mRNA vaccines are not limited to COVID-19. Recent studies have revealed the potential of mRNA vaccines to be a powerful means of protective immunization against a variety of infectious diseases, such as influenza84. However, factors such as gene size or number, organism-dependent codons, protein confirmation, and posttranslational modifications can, in practice, limit which antigens can be effectively delivered using mRNA vaccines. However, the synthetic nature of mRNA vaccines offers many opportunities to apply synthetic biology principles to overcome such potential impediments . Codon optimization can increase and improve the translation of RNA, therefore increasing antigen production. This process has been greatly advanced by the use of computational tools, such as deep learning87. However, there are some risks associated with codon optimization that should be considered when applying this process to vaccine design. For example, too rapid translation can result in misfolded proteins88. Moreover, there is evidence indicating that codon optimization is context dependent, impacted by both adjacent codons and the cellular metabolic state89. This suggests that further information can be gathered to enhance the application of codon optimization within pharmaceutical applications.One such tool is codon optimization, the process by which the codons within a synthetic construct are optimized for the environment in which protein expression will occur. Each cellular environment  has a unique codon distribution linked with cognate tRNA molecules91. In this way, epitopes from proteins associated with different strains, disease phases, or even different pathogens can be combined to provide more comprehensive protection. This principle is already being applied to some mRNA vaccines, including SARS-CoV-2 mRNA vaccines that encode for a chimeric spike protein92. Furthermore, a chimeric mRNA vaccine is under development that combines the SARS-CoV-2 spike with the influenza hemagglutinin matrix protein 1 proteins93.Due to size constraints associated with mRNA vaccines, design of vaccines for bacterial pathogens can be particularly challenging due to the need for multiple antigens to account for the complexity of the pathogen physiology or pathology. Synthetic biology principles developed for recombinant protein expression can also be exploited to overcome such impediments which will result in increased cost and complexity and may result in reduced delivery efficacy. For example, size restrictions of genetic vaccine constructs can be sidestepped by encoding for chimeric proteins, or proteins made up of immunogenic epitopes of multiple proteins95. However, there are some disadvantages to using IRESs, including size (>500 bps) and inefficient downstream gene expression that is dependent on the sequence of the gene upstream99. Self-cleaving 2A peptides represent an attractive alternative to IRESs due to their smaller size (<100 bps) and high gene expression efficiency97. These peptides, when encoded directly upstream of glycine, inhibit ribosomes from forming a peptide bond between the glycine and subsequent amino acid, thereby facilitating the expression of two separate protein antigens100. However, the cleavage is not 100%, which can have implications on therapeutic protein stability and activity101.Additional strategies to load multiple antigens onto a genetic vaccine construct include the use internal ribosome entry sites (IRESs) and self-cleaving 2A peptides. IRESs are RNA sequences used to initiate translation at an internal location within an mRNA construct, thereby facilitating the coding of polycistronic RNA. This is particularly important when designing circular RNA (circRNA) vaccines which do not have a 5’ cap to support classical cap-dependent translation102. Further modification of mRNA can be done through encoding a replicase within the nucleotide sequence. This enables the mRNA to self-amplify ), therefore reducing the required dose103. One of the more promising developments in mRNA technology has been the development of circRNA. This technology utilizes self-splicing introns to circularize mRNA into a ribonucleic acid “plasmid”. This can also be achieved through enzymatic means104. This provides similar improvements in stability as compared to the chemical modifications in modRNA102. The application of this approach has demonstrated promising results in various systems. For example, a circRNA vaccine encoding for the SARS-CoV-2 receptor-binding domain was found to induce a more potent and prolonged immune response than an equivalent dose of modRNA105. Importantly, the circRNA construct was also found to be highly heat stable and could be stored at room temperature for up to 2 weeks, which could facilitate easier distribution to geographical regions where a cold chain is difficult to maintain105. In addition to these mechanisms, origami-based approaches can be employed to generate nanoscale molecular RNA structures. Such structures have shown the ability to improve delivery and stability of such constructs107.Synthetic biology can also be applied to the RNA construct to overcome some of the existing limitations of mRNA vaccines, such as the poor stability and lifespan of mRNA within a physiological environment, which has limited success of native mRNA in pharmaceutical applications Fig. . For exa108. This is because signal proteins, when fused with the antigen, can lead to the excretion and subsequent loading of the antigen onto an MHC class II molecule. Additional tags, such as secretory or organelle-targeting tags can be implemented to impart delivery to specific locations as desired. Protein adjuvants can also be encoded in such a way to fuse the adjuvant with the antigen, thus leading to a more effective adaptive and innate immune response112.These advances in RNA technology potentially offer exciting opportunities to express additional factors that influence vaccine efficacy. Signal proteins, for example, can redirect the immune response of an intracellularly produced antigen, which would typically be loaded on to a major histocompatibility (MHC) class I moleculeThe ability of saRNA and circRNA constructs to reduce the required vaccine dose while still expressing multiple antigens on the same construct may one day lead to the expression of complex processes within the host cell, such as those required to facilitate pathogen-specific posttranslational modifications or produce pathogen polysaccharides. Moreover, further application of synthetic biology to these constructs has the potential to further enhance or otherwise modulate antigen expression to address diverse applications.114. Additionally, the negatively charged mRNA is repulsed by the negatively charged cell membrane, and is susceptible to degradation by extracellular ribonucleases115. As such, a delivery vehicle for mRNA vaccines should facilitate cellular uptake and protect mRNA from degradation116.Synthetic biology principles can be applied not only to the genetic content of an RNA vaccine, but also to the vehicle in which it is delivered. The choice of delivery system for mRNA vaccines is particularly important, as its size (~1.7 MDa) can make intracellular delivery difficult118. Tools have been developed to control AAV functions and have been described in detail previously119. In brief, these tools include synthetic biological switches  that can control cellular processes such as receptor activation, transgene expression, and protein trafficking. Gene expression following AAV delivery can also be controlled by tailoring the regulatory parts of the inverted terminal repeat-flanked expression cassette within the AAV capsid119. Interestingly, AAVs can also be hybridized with other viral delivery vectors, such as parvoviruses and bacteriophages, and with extracellular vesicles  from eukaryotic cells.Characterizing biological delivery vectors, such as viruses and bacteria, allows for the use of synthetic biology tools to make targeted modifications, therefore enhancing desired delivery characteristics. One of the most notable examples of a biologic delivery vector for genetic vaccines is the adeno-associated virus (AAV), which has been used to deliver RNA encoding for the SARS-CoV-2 spike proteinEscherichia coli, represent another potential category of delivery vehicles for genetic vaccines. A key driver of this approach is the compatibility between the molecular biology underpinnings of synthetic biology and the microbiology advantages and knowledge collected for associated microbes. E. coli, for example, has perhaps the most expansive knowledge base and associated molecular biology tools of any microorganism122. As a result, advanced efforts in vaccine design can be accomplished using this carrier system while taking advantage of its ability to serve as a natural adjuvant. Attenuated, nonpathogenic strains of E. coli represent attractive options for use in vaccine design, as many tools are available to influence antigen number, expression level, and type using this host. Moreover, other recombinant features enabled by synthetic biology tools could serve in ways to assist with antigen delivery. For example, certain endosomal lysis proteins such as listeriolysin, natively associated with the intracellular pathogenic bacterium Listeria monocytogenes, facilitate the endosomal escape and cytosolic trafficking required to better deliver antigenic content to antigen presentation cells during administration of an engineered bacterial-based vaccine carrier127.Bacterial vectors, such as 129. Such a synthetic cell would be designed for a specific biological purpose with minimal extraneous cellular features.One drawback to antigen delivery within the confines of a microbial delivery vehicle is its biological complexity. Though bacterial or viral particles offers potential advantages with regards to adjuvant patterning and synthetic biology tools, there are other biological features that do not enhance vaccine efficacy. These same features may have a negative impact on the overall vaccine design, as extraneous elements of the microbial vaccine carrier system may spur unwanted immune reactions or cause undesirable toxicity. Furthermore, bacteria are prone to the degradation of mRNA and are thus not suited for its delivery. However, by using synthetic biology tools , it is possible to construct a synthetic, minimalized bacterial genome within a hollowed-out cellular framework131, but the approach gained wider recognition due to their use in the COVID-19 mRNA vaccines133. Such liposomes represent an intersection of antigen delivery with synthetic biology as they can be further modified to impart delivery specificity. For example, there have been multiple strategies developed for the attachment of proteins to liposomal surfaces136. These mechanisms can be adapted to surface localization of an antibody or similar targeting ligand to directly deliver RNA to a specific tissue. This would enable directed RNA therapy in an approach like radioimmunotherapy.Genetic payloads can also be delivered in fully chemical carrier systems, such as liposomes. Liposomal delivery systems have often accompanied studies in gene and drug deliveryThe union of synthetic biology and RNA technology has led to remarkable advances in medical treatments, allowing us to create novel therapeutics and vaccines that hold the potential to revolutionize global health care. However, the application of this technology is still in its early stages and has not come close to reaching its full potential.We are currently in the midst of rapidly advancing artificial intelligence (AI) and machine learning that will further expand the horizons of RNA therapeutics and vaccines. AI and advanced computer-based models can be used to suggest modifications to RNA sequences for enhanced efficacy, identify novel disease targets, and computationally design specialized RNA sequences, such as aptamers and encoded antibodies, with precise specificity to unique targets. For example, we can imagine the use of AI to analyze large datasets of genetic information and proposing RNA construct designs for the expression of complex, multidomain proteins such as monoclonal antibodies. Antibody sequence and binding information can be utilized to train AI to propose antibody sequences with desired target or neutralizing abilities. We can also envision the use of AI to identify novel regulatory and ribozyme functions that could be incorporated into RNA medical products in order to detect specific disease states such as an increase in blood glucose levels in diabetes patients. Such regulatory and ribozyme functions could be used to develop an “on/off switch” that would then stimulate the production of insulin, thereby providing precise blood sugar level control for patients.The application of AI and machine learning to synthetic biology can also potentially be used to overcome current limitations of mRNA vaccines, such as an inability to express multidomain antigens or polysaccharide antigens. Without the capability to produce these antigens, RNA vaccines will remain limited in the diseases it can target and will not be able to fully replace traditional vaccines. AI could potentially help design complex circuits that could carry out the multistage processes required for production of such antigens and that could be administered as an RNA vaccine, thereby opening new possibilities for vaccine development.While there are still many challenges to be tackled when it comes to using synthetic biology for developing vaccines and RNA therapeutics, the potential is undeniable. With continued research and innovation, we may soon be able to see groundbreaking new technologies that can improve the lives of millions. Through careful consideration and creative design, synthetic biology can provide an effective and safe platform to develop novel treatments for a range of diseases. In the years ahead, we are sure to see amazing advances in this field that could change the face of healthcare forever.Further information on research design is available in the Reporting Summary


Results showed that the porous TAB could physically adsorb and chemically interact with LiPSs during charging and discharging processes, inhibiting the LiPSs’ shuttle effect, and the TAB’s heterostructure and PPy conductive layer are conducive to the rapid transport of Li+ and improve the conductivity of the electrode. By benefitting from these merits, Li-S batteries with TAB@S/PPy electrodes could deliver a high initial capacity of 1250.4 mAh g−1 at 0.1 C and show an excellent cycling stability (the average capacity decay rate was 0.042% per cycle after 1000 cycles at 1 C). This work brings a new idea for the design of functional sulfur cathodes for high-performance Li-S battery.Despite having ultra-high theoretical specific capacity and theoretical energy density, lithium-sulfur (Li-S) batteries suffer from their low Coulombic efficiency and poor lifespan, and the commercial application of Li-S batteries is seriously hampered by the severe “shuttle effect” of lithium polysulfides (LiPSs) and the large volume expansion ratio of the sulfur electrode during cycling. Designing functional hosts for sulfur cathodes is one of the most effective ways to immobilize the LiPSs and improve the electrochemical performance of a Li-S battery. In this work, a polypyrrole (PPy)-coated anatase/bronze TiO In th−1) , low cos−1) . However−1) ,6. To so−1) ,8, elect−1) , separat−1) ,11,12,13−1) ,15,16. U−1) ,18,19, c−1) ,21,22, c−1) ,24, carb−1) ,26, poro−1) ,28,29 an−1) , due to −1) ,32. In t−1) ,34,35, m−1) , metal n−1) , metal c−1)  and meta−1) , and the−1) .2) has been extensively investigated as a sulfur host because of the advantages of non-toxicity, adjustable morphology and good polysulfides immobilization ability [2, anatase TiO2 is one of the most commonly used types for the hosts of sulfur cathode, but its electrical conductivity is limited, making it unable to efficiently transport Li+ [2 is a kind of metastable monoclinic TiO2 with an open channel structure, which exhibits special pseudo-capacitive behavior and can accommodate more Li+ than anatase TiO2 [2-VOx [2 [3C2-TiO2 [2 and bronze TiO2 were reported to be different in band gap [2 hetero-structural boundary could facilitate the generation of more lithium storage sites, and the reaction kinetics of interfacial storage processes are faster than in bulk [Recently, as one of the most promising metal oxide sulfur host materials, titanium dioxide  heterostructure and investigated it as a sulfur host for Li-S batteries. Various characterizations and tests illustrated that the TAB/PPy composite material could not only provide a sufficient space to accommodate the sulfur’s volume expansion during cycling, but could also physically adsorb and chemically interact with LiPSs, inhibiting the “shuttle effect”. The PPy coated TAB heterojunction structure could improve the electron conductivity and Li ion transport efficiency, and the Li-S battery with the TAB@S/PPy electrode exhibited an excellent rate capability and cycling stability.Based on the above research, we successfully fabricated a new PPy-coated anatase/bronze TiO2 precursor was obtained after hydrothermal treatment (2 (A) and the (110) lattice plane of TiO2 (B), respectively, indicating that the TAB heterostructure had been successfully synthesized during the process of high temperature calcination [The synthetic process of the TAB@S/PPy compound is shown in reatment . In the cination .The selected electron diffraction pattern (the insert) in 2 precursors before and after annealing. The XRD spectra of the precursor in 2 precursor was amorphous, mainly due to the presence of P123, consistent with the SEM and TEM images. However, the XRD of TiO2 after annealing showed strong crystallization peaks, and the diffraction peaks centered at 14.21°, 28.61° and 43.31° corresponded to the TiO2 (B) standard card JCPDS 74-1940. The peaks at 25.28°, 36.94°, 48.04°, 62.68° and 74.02° corresponded to the (101), (103), (200), (204) and (107) crystal planes of TiO2 (A) (JCPDS 21-1272), which was consistent with the HRTEM in 4+ in TAB, but there was also a small amount of Ti3+ on the surface, which was possibly caused by the P123-derived carbon as the reducing agent during the annealing process. The existence of Ti3+ would also introduce a certain amount of oxygen vacancy, which is beneficial to the adsorption of LiPSs [In order to ensure the successful preparation of TAB, X-ray diffraction (XRD) tests were carried out for TiOof LiPSs .2 g−1. The large specific surface area can provide abundant space for the adsorption of polysulfides, inhibiting their shuttle effect. 2 g−1, and the average pore size decreased to only 5 nm, indicating that sulfur molecules had been uniformly diffused to TAB mesoporous, but the TAB host still had a part of space that could be used to relieve the sulfur volume expansion in the process of charging and discharging processes, which was conductive to improving the stability of the cathode. Moreover, the sulfur content in positive electrodes is an important parameter, so thermogravimetric analysis tests were carried out to examine the content of S in TAB@S/PPy. As shown in The pore size distribution and specific surface area of TAB, TAB/PPy and TAB@S/PPy c,d were 2S6 for TAB and TAB/PPy samples, optical visualization experiments and UV-vis spectroscopy tests were performed , indicating that TAB and TAB/PPy have strong adsorption capacities for LiPSs. To further confirm the adsorption ability of TAB/PPy, we performed UV-vis tests on the three electrolytes after 24 h of rest , XPS tests of TAB/PPy adsorbed powder before and after the adsorption of Li2S6 were performed. The XPS spectra  and further transformation into short-chain Li2S2 or Li2S, respectively [−1, much higher than that with TAB@S and sulfur cathodes. These batteries exhibited two distinct discharge plateaus and one charging plateau, which corresponded to two reduction peaks and one oxidation peak in the CV curves, respectively [−1. After that, the charging and discharging plateaus of TAB@S/PPy cell did not change obviously, and the battery could deliver a discharge capacity of ~600 mAh g−1 at 1 C after 100 cycles, which indicated that the Li-S battery with the TAB@S/PPy electrode had excellent cycling stability and reversibility.The electrochemical performances of the Li-S batteries with TAB@S/PPy, TAB@S and sulfur electrodes were further investigated . The cycectively . During ectively . As show−1) was higher than that of the TAB@S and sulfur cathodes, at 0.1 C, and when the current density increased to 2 C the specific discharge capacity of nearly 380.4 mAh g−1 could still be maintained. In contrast, the battery with the sulfur cathode could only deliver a capacity of 254 mAh g−1. When re-switched to 0.2 C, the discharge capacity of TAB@S/PPy could still be restored to the same degree as before, showing good reversibility. In order to test the long cycle performance of the full battery composed of the TAB@S/PPy composite, we carried out the activation process at a low current of 0.1 C, and then tested the cyclic performance at 1 C  plots before and after 200 cycles at 0.5 C of the battery with TAB@S/PPy, TAB@S and sulfur cathodes are shown in −1 in the environment of argon gas. The TAB sample was obtained after being kept for 4 h and naturally cooled to room temperature.The TAB heterostructure was prepared using the hydrothermal method and subsequent annealing process, as described elsewhere . First, 2 and 6 mL DMF were mixed to form a solution. Then, 0.12 g TAB and 0.28 g nano sulfur were added into the above mixed solution, and ultrasound was applied for 0.5 h. The mixture was then stirred at 45 °C for 12 h and washed with distilled water and anhydrous ethanol two times, respectively, and dried in a vacuum drying oven at 60 °C for 4 h. Finally, the pulverized solids were heated in a tubular furnace at the heat-up rate of 5 °C·per min to 155 °C for 12 h and 220 °C for 30 min, respectively, in an Ar atmosphere. After cooling, TAB@S sample was obtained.Totals of 15 mL CS4) S2O3 were added to that solution and stirred in ice bath for 4 h. Then, the product was washed twice with deionized H2O and C2H5OH. TAB@S/PPy composites were obtained after vacuum drying at 60 °C for 12 h.A 3 mL quantity of anhydrous ethanol was added into 27 mL distilled water, and then 0.3 g TAB@S, 0.02 g sodium dodecyl sulfate and 10 μL triton were mixed into the above solution and stirred for 0.5 h. After that, 5 μL pyrrole and 10 mL 0.1 M  was dissolved in 1, 3-dioxane (DOL): 1, 2-dimethoxy-ethane (DME) (v:v = 1:1) and magnetically stirred at 60 °C for 24 h. Then, 2 mmol L−1 Li2S6 solution was prepared by diluting 0.5 M Li2S6 solution with equal volume of DOL/DME. Then, 15 mg TAB/PPy was added to 3 mL 2 mmol L−1 Li2S6 solution. The color change of the Li2S6 solution can be observed within a few minutes. The supernatant was detected with the ultraviolet spectrum, and the precipitated products were dried for XPS analysis. The above sample preparation was carried out in an Ar-filled glove box (H2O and O2 were both less than 0.1 ppm).The solution of 0.5 M Li2 atmosphere. The state of the elements and the surface composition of the compounds were analyzed with X-ray photoelectron spectroscopy , and the binding energies were referenced to the C1s line at 284.8 eV from adventitious carbon The adsorption effect of the composites on sulfide was tested with the UV-visible spectrum . The specific surface area and pore size distributions of the composites were measured using a fully automated specific surface and porosity analyzer .The phase and composition of the prepared materials were analyzed with XRD . The crystal structure and morphology of the materials were characterized with scanning electron microscopy (SEM)  and transmission electron microscopy (TEM) . The content of sulfur in the composites was calculated with thermogravimetric analysis  under N−2. The lithium foil as the negative electrode and the Celgard 2500 as the separator were used for the 2032 coin cells assembly. The electrolyte was 1 M lithium difluoromethane sulfonimide (LiTFSI) + dioxolame (DOL): diethyl carbonate (DME) (1:1 in volume) added to 1% LiNO3. LiNO3 alters the solvation structure of Li+, which has a profound impact on the electrochemical performance of batteries [−1 and electrochemical impedance spectroscopy (EIS) measurements with a frequency ranging from 100 kHz to 0.01 Hz were performed at the electrochemical workstation . In this work, the specific capacity value was calculated based on the mass of S.For the cathode slurry preparation, TAB@S/PPy (70 wt%), Super P (20 wt%) and polyvinylidene fluoride (PVDF) (10 wt%) were thoroughly mixed. Then, N-methyl-2-pyrrolidone (NMP) was added to the above mixture. The slurry was evenly applied on the carbon-coated aluminum foil with a scraper and dried for 12 h under 60 °C under vacuum. Then, the dried electrode plate was cut into a diameter of 12 nm. The loading of TAB@S/PPy in the positive electrode of the coin cell was 1.0–1.5 mg cmatteries . Then, 4atteries . LAND CT+ transport, greatly improving the conductivity of the electrode. Consequently, the battery using TAB@S/PPy as the cathode obtained a high initial capacity (1250.4 mAh g−1 at 0.1 C), long cycle life and excellent cycle stability (the average capacity decay rate of per cycle was only about 0.042% after 1000 cycles at 1C). The work provides a new strategy for the design of high-performance Li-S battery cathode materials.In summary, the porous TAB@S/PPy composite material was synthesized with hydrothermal and subsequent annealing treatment, followed by sulfur loading, and coated with a thin PPy layer. Due to its unique porous heterostructure, TAB/PPy not only has enough volume to hold sulfur and relieve volume expansion during cycling, but can also physically and chemically adsorb polysulfides and inhibit their shuttle effect. In addition, the heterostructure of TAB and the conductive PPy coating layer can promote Li