Clinical translation of transcription factor therapeutics is limited by delivery problems. Now, an oligonucleotide that can bind and deliver transcription factors with high in vivo efficiency and treat acetaminophen-induced liver injury is reported. Therapeutics based on transcription factors have the potential to revolutionize medicine but have had limited clinical success as a consequence of delivery problems1,2,3,4. The delivery of transcription factors is challenging because it requires the development of a delivery vehicle that can complex transcription factors, target cells and stimulate endosomal disruption, with minimal toxicity5,6. Here, we present a multifunctional oligonucleotide, termed DARTs (DNA assembled recombinant transcription factors), which can deliver transcription factors with high efficiency in vivo. DARTs are composed of an oligonucleotide that contains a transcription-factor-binding sequence and hydrophobic membrane-disruptive chains that are masked by acid-cleavable galactose residues. DARTs have a unique molecular architecture, which allows them to bind transcription factors, trigger endocytosis in hepatocytes, and stimulate endosomal disruption. The DARTs have enhanced uptake in hepatocytes as a result of their galactose residues and can disrupt endosomes efficiently with minimal toxicity, because unmasking of their hydrophobic domains selectively occurs in the acidic environment of the endosome. We show that DARTs can deliver the transcription factor nuclear erythroid 2-related factor 2 (Nrf2) to the liver, catalyse the transcription of Nrf2 downstream genes, and rescue mice from acetaminophen-induced liver injury.

The construction of polymer-based mimicry on cell surface to manipulate cell behaviors and functions offers promising prospects in the field of biotechnology and cell therapy. However, precise control of polymer grafting sites is essential to successful implementation of biomimicry and functional modulation, which has been overlooked by most current research. Herein, we report a biological site-selected, in situ controlled radical polymerization platform for living cell surface engineering. The method utilizes metabolic labeling techniques to confine the growth sites of polymers and designs a Fenton-RAFT polymerization technique with cytocompatibility. Polymers grown at different sites (glycans, proteins, lipids) have different membrane retention time and exhibit differential effects on the recognition behaviors of cellular glycans. Of particular importance is the achievement of in situ copolymerization of glycomonomers on the outermost natural glycan sites of cell membrane, building a biomimetic glycocalyx with distinct recognition properties.

Flow cytometry holds promise to accelerate antibiotic susceptibility determinations; however, without robust multidimensional statistical analysis, general discrimination criteria have remained elusive. In this study, a new statistical method, probability binning signature quadratic form (PB-sQF), was developed and applied to analyze flow cytometric data of bacterial responses to antibiotic exposure. Both sensitive lab strains (Escherichia coli and Pseudomonas aeruginosa) and a multidrug resistant, clinically isolated strain (E. coli) were incubated with the bacteria-targeted dye, maltohexaose-conjugated IR786, and each of many bactericidal or bacteriostatic antibiotics to identify changes induced around corresponding minimum inhibition concentrations (MIC). The antibiotic-induced damages were monitored by flow cytometry after 1-h incubation through forward scatter, side scatter, and fluorescence channels. The 3-dimensional differences between the flow cytometric data of the no-antibiotic treated bacteria and the antibiotic-treated bacteria were characterized by PB-sQF into a 1-dimensional linear distance. A 99% confidence level was established by statistical bootstrapping for each antibiotic-bacteria pair. For the susceptible E. coli strain, statistically significant increments from this 99% confidence level were observed from 1/16x MIC to 1x MIC for all the antibiotics. The same increments were recorded for P. aeruginosa, which has been reported to cause difficulty in flow-based viability tests. For the multidrug resistant E. coli, significant distances from control samples were observed only when an effective antibiotic treatment was utilized. Our results suggest that a rapid and robust antimicrobial susceptibility test (AST) can be constructed by statistically characterizing the differences between sample and control flow cytometric populations, even in a label-free scheme with scattered light alone. These distances vs paired controls coupled with rigorous statistical confidence limits offer a new path toward investigating initial biological responses, screening for drugs, and shortening time to result in antimicrobial sensitivity testing.