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Modern life is essentially homochiral, containing D-sugars in nucleic acid backbones and L-amino acids in proteins. Since coded proteins are theorized to have developed from a prebiotic RNA World, the homochirality of L-amino acids observed in all known life presumably resulted from chiral transfer from a homochiral D-RNA World. This transfer would have been mediated by aminoacyl-RNAs defining the genetic code. Previous work on aminoacyl transfer using tRNA mimics has suggested that aminoacylation using D-RNA may be inherently biased toward reactivity with L-amino acids, implying a deterministic path from a D-RNA World to L-proteins. Using a model system of self-aminoacylating D-ribozymes and epimerizable activated amino acid analogs, we test the chiral selectivity of 15 ribozymes derived from an exhaustive search of sequence space. All of the ribozymes exhibit detectable selectivity, and a substantial fraction react preferentially to produce the D-enantiomer of the product. Furthermore, chiral preference is conserved within sequence families. These results are consistent with the transfer of chiral information from RNA to proteins but do not support an intrinsic bias of D-RNA for L-amino acids. Different aminoacylation structures result in different directions of chiral selectivity, such that L-proteins need not emerge from a D-RNA World.

ConspectusCreating a living system from nonliving matter is a great challenge in chemistry and biophysics. The early history of life can provide inspiration from the idea of the prebiotic RNA World established by ribozymes, in which all genetic and catalytic activities were executed by RNA. Such a system could be much simpler than the interdependent central dogma characterizing life today. At the same time, cooperative systems require a mechanism such as cellular compartmentalization in order to survive and evolve. Minimal cells might therefore consist of simple vesicles enclosing a prebiotic RNA metabolism.The internal volume of a vesicle is a distinctive environment due to its closed boundary, which alters diffusion and available volume for macromolecules and changes effective molecular concentrations, among other considerations. These physical effects are mechanistically distinct from chemical interactions, such as electrostatic repulsion, that might also occur between the membrane boundary and encapsulated contents. Both indirect and direct interactions between the membrane and RNA can give rise to nonintuitive, emergent behaviors in the model protocell system. We have been examining how encapsulation inside membrane vesicles would affect the folding and activity of entrapped RNA.Using biophysical techniques such as FRET, we characterized ribozyme folding and activity inside vesicles. Encapsulation inside model protocells generally promoted RNA folding, consistent with an excluded volume effect, independently of chemical interactions. This energetic stabilization translated into increased ribozyme activity in two different systems that were studied (hairpin ribozyme and self-aminoacylating RNAs). A particularly intriguing finding was that encapsulation could rescue the activity of mutant ribozymes, suggesting that encapsulation could affect not only folding and activity but also evolution. To study this further, we developed a high-throughput sequencing assay to measure the aminoacylation kinetics of many thousands of ribozyme variants in parallel. The results revealed an unexpected tendency for encapsulation to improve the better ribozyme variants more than worse variants. During evolution, this effect would create a tilted playing field, so to speak, that would give additional fitness gains to already-high-activity variants. According to Fishers Fundamental Theorem of Natural Selection, the increased variance in fitness should manifest as faster evolutionary adaptation. This prediction was borne out experimentally during in vitro evolution, where we observed that the initially diverse ribozyme population converged more quickly to the most active sequences when they were encapsulated inside vesicles.The studies in this Account have expanded our understanding of emergent protocell behavior, by showing how simply entrapping an RNA inside a vesicle, which could occur spontaneously during vesicle formation, might profoundly affect the evolutionary landscape of the RNA. Because of the exponential dynamics of replication and selection, even small changes to activity and function could lead to major evolutionary consequences. By closely studying the details of minimal yet surprisingly complex protocells, we might one day trace a pathway from encapsulated RNA to a living system.

The relationship between genotype and phenotype, or the fitness landscape, is the foundation of genetic engineering and evolution. However, mapping fitness landscapes poses a major technical challenge due to the amount of quantifiable data that is required. Catalytic RNA is a special topic in the study of fitness landscapes due to its relatively small sequence space combined with its importance in synthetic biology. The combination of in vitro selection and high-throughput sequencing has recently provided empirical maps of both complete and local RNA fitness landscapes, but the astronomical size of sequence space limits purely experimental investigations. Next steps are likely to involve data-driven interpolation and extrapolation over sequence space using various machine learning techniques. We discuss recent progress in understanding RNA fitness landscapes, particularly with respect to protocells and machine representations of RNA. The confluence of technical advances may significantly impact synthetic biology in the near future.

Artificial intelligence and machine learning applications are emerging as transformative technologies in medicine. With greater access to a diverse range of big datasets, researchers are turning to these powerful techniques for data analysis. Machine learning can reveal patterns and interactions between variables in large and complex datasets more accurately and efficiently than traditional statistical methods. Machine learning approaches open new possibilities for studying SLE, a multifactorial, highly heterogeneous and complex disease. Here, we discuss how machine learning methods are rapidly being integrated into the field of SLE research. Recent reports have focused on building prediction models and/or identifying novel biomarkers using both supervised and unsupervised techniques for understanding disease pathogenesis, early diagnosis and prognosis of disease. In this review, we will provide an overview of machine learning techniques to discuss current gaps, challenges and opportunities for SLE studies. External validation of most prediction models is still needed before clinical adoption. Utilisation of deep learning models, access to alternative sources of health data and increased awareness of the ethics, governance and regulations surrounding the use of artificial intelligence in medicine will help propel this exciting field forward.

All lineages of SARS-CoV-2, the coronavirus responsible for the COVID-19 pandemic, contain mutations between amino acids 199 and 205 in the nucleocapsid (N) protein that are associated with increased infectivity. The effects of these mutations have been difficult to determine because N protein contributes to both viral replication and viral particle assembly during infection. Here, we used single-cycle infection and virus-like particle assays to show that N protein phosphorylation has opposing effects on viral assembly and genome replication. Ancestral SARS-CoV-2 N protein is densely phosphorylated, leading to higher levels of genome replication but 10-fold lower particle assembly compared to evolved variants with low N protein phosphorylation, such as Delta (N:R203M), Iota (N:S202R), and B.1.2 (N:P199L). A new open reading frame encoding a truncated N protein called N*, which occurs in the B.1.1 lineage and subsequent lineages of the Alpha, Gamma, and Omicron variants, supports high levels of both assembly and replication. Our findings help explain the enhanced fitness of viral variants of concern and a potential avenue for continued viral selection.

The emergence of SARS-CoV-2 recombinants is of particular concern as they can result in a sudden increase in immune evasion due to antigenic shift. Recent recombinants XBB and XBB.1.5 have higher transmissibility than previous recombinants such as "Deltacron." We hypothesized that immunity to a SARS-CoV-2 recombinant depends on prior exposure to its parental strains. To test this hypothesis, we examined whether Delta or Omicron (BA.1 or BA.2) immunity conferred through infection, vaccination, or breakthrough infection could neutralize Deltacron and XBB/XBB.1.5 recombinants. We found that Delta, BA.1, or BA.2 breakthrough infections provided better immune protection against Deltacron and its parental strains than did the vaccine booster. None of the sera were effective at neutralizing the XBB lineage or its parent BA.2.75.2, except for the sera from the BA.2 breakthrough group. These results support our hypothesis. In turn, our findings underscore the importance of multivalent vaccines that correspond to the antigenic profile of circulating variants of concern and of variant-specific diagnostics that may guide public health and individual decisions in response to emerging SARS-CoV-2 recombinants.

The identification of catalytic RNAs is typically achieved through primarily experimental means. However, only a small fraction of sequence space can be analyzed even with high-throughput techniques. Methods to extrapolate from a limited data set to predict additional ribozyme sequences, particularly in a human-interpretable fashion, could be useful both for designing new functional RNAs and for generating greater understanding about a ribozyme fitness landscape. Using information theory, we express the effects of epistasis (i.e., deviations from additivity) on a ribozyme. This representation was incorporated into a simple model of the epistatic fitness landscape, which identified potentially exploitable combinations of mutations. We used this model to theoretically predict mutants of high activity for a self-aminoacylating ribozyme, identifying potentially active triple and quadruple mutants beyond the experimental data set of single and double mutants. The predictions were validated experimentally, with nine out of nine sequences being accurately predicted to have high activity. This set of sequences included mutants that form a previously unknown evolutionary bridge between two ribozyme families that share a common motif. Individual steps in the method could be examined, understood, and guided by a human, combining interpretability and performance in a simple model to predict ribozyme sequences by extrapolation.

Genetically engineered MRI-visible phages enable the noninvasive detection of bacteria in deep tissues with tunable cell-type specificity.

OBJECTIVES: A novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes. METHODS: Demographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset. RESULTS: Cluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2. CONCLUSION: Four discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk.

Viruses targeting mammalian cells can indirectly alter the gut microbiota, potentially compounding their phenotypic effects. Multiple studies have observed a disrupted gut microbiota in severe cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that require hospitalization. Yet, despite demographic shifts in disease severity resulting in a large and continuing burden of non-hospitalized infections, we still know very little about the impact of mild SARS-CoV-2 infection on the gut microbiota in the outpatient setting. To address this knowledge gap, we longitudinally sampled 14 SARS-CoV-2-positive subjects who remained outpatient and 4 household controls. SARS-CoV-2 cases exhibited a significantly less stable gut microbiota relative to controls. These results were confirmed and extended in the K18-humanized angiotensin-converting enzyme 2 mouse model, which is susceptible to SARS-CoV-2 infection. All of the tested SARS-CoV-2 variants significantly disrupted the mouse gut microbiota, including USA-WA1/2020 (the original variant detected in the USA), Delta, and Omicron. Surprisingly, despite the fact that the Omicron variant caused the least severe symptoms in mice, it destabilized the gut microbiota and led to a significant depletion in Akkermansia muciniphila. Furthermore, exposure of wild-type C57BL/6J mice to SARS-CoV-2 disrupted the gut microbiota in the absence of severe lung pathology.IMPORTANCETaken together, our results demonstrate that even mild cases of SARS-CoV-2 can disrupt gut microbial ecology. Our findings in non-hospitalized individuals are consistent with studies of hospitalized patients, in that reproducible shifts in gut microbial taxonomic abundance in response to SARS-CoV-2 have been difficult to identify. Instead, we report a long-lasting instability in the gut microbiota. Surprisingly, our mouse experiments revealed an impact of the Omicron variant, despite producing the least severe symptoms in genetically susceptible mice, suggesting that despite the continued evolution of SARS-CoV-2, it has retained its ability to perturb the intestinal mucosa. These results will hopefully renew efforts to study the mechanisms through which Omicron and future SARS-CoV-2 variants alter gastrointestinal physiology, while also considering the potentially broad consequences of SARS-CoV-2-induced microbiota instability for host health and disease.

One of the primary global health concerns is the increase in antimicrobial resistance. Polymer chemistry enables the preparation of macromolecules with hydrophobic and cationic side chains that kill bacteria by destabilizing their membranes. In the current study, macromolecules are prepared by radical copolymerization of caffeine methacrylate as the hydrophobic monomer and cationic- or zwitterionic-methacrylate monomers. The synthesized copolymers bearing tert-butyl-protected carboxybetaine as cationic side chains showed antibacterial activity toward Gram-positive bacteria (S. aureus) and Gram-negative bacteria (E. coli). By tuning the hydrophobic content, we prepared copolymers with optimal antibacterial activity against S. aureus, including methicillin-resistant clinical isolates. Moreover, the caffeine-cationic copolymers presented good biocompatibility in a mouse embryonic fibroblast cell line, NIH 3T3, and hemocompatibility with erythrocytes even at high hydrophobic monomer content (30-50%). Therefore, incorporating caffeine and introducing tert-butyl-protected carboxybetaine as a quaternary cation in polymers could be a novel strategy to combat bacteria.

Many statistical methods have been developed for the analysis of microbial community profiles, but due to the complexity of typical microbiome measurements, inference of interactions between microbial features remains challenging. We develop a Bayesian zero-inflated rounded log-normal kernel method to model interaction between microbial features in a community using multivariate count data in the presence of covariates and excess zeros. The model carefully constructs the interaction structure by imposing joint sparsity on the covariance matrix of the kernel and obtains a reliable estimate of the structure with a small sample size. The model also includes zero inflation to account for excess zeros observed in data and infers differential abundance of microbial features associated with covariates through log-linear regression. We provide simulation studies and real data analysis examples to demonstrate the developed model. Comparison of the model to a simpler model and popular alternatives in simulation studies shows that, in addition to an added and important insight on the feature interaction, it yields superior parameter estimates and model fit in various settings.

Despite unprecedented efforts, our therapeutic arsenal against SARS-CoV-2 remains limited. The conserved macrodomain 1 (Mac1) in NSP3 is an enzyme exhibiting ADP-ribosylhydrolase activity and a possible drug target. To determine the role of Mac1 catalytic activity in viral replication, we generated recombinant viruses and replicons encoding a catalytically inactive NSP3 Mac1 domain by mutating a critical asparagine in the active site. While substitution to alanine (N40A) reduced catalytic activity by ~10-fold, mutations to aspartic acid (N40D) reduced activity by ~100-fold relative to wild-type. Importantly, the N40A mutation rendered Mac1 unstable in vitro and lowered expression levels in bacterial and mammalian cells. When incorporated into SARS-CoV-2 molecular clones, the N40D mutant only modestly affected viral fitness in immortalized cell lines, but reduced viral replication in human airway organoids by 10-fold. In mice, the N40D mutant replicated at >1000-fold lower levels compared to the wild-type virus while inducing a robust interferon response; all animals infected with the mutant virus survived infection. Our data validate the critical role of SARS-CoV-2 NSP3 Mac1 catalytic activity in viral replication and as a promising therapeutic target to develop antivirals.

Although the SARS-CoV-2 Omicron variant (BA.1) spread rapidly across the world and effectively evaded immune responses, its viral fitness in cell and animal models was reduced. The precise nature of this attenuation remains unknown as generating replication-competent viral genomes is challenging because of the length of the viral genome (~30 kb). Here, we present a plasmid-based viral genome assembly and rescue strategy (pGLUE) that constructs complete infectious viruses or noninfectious subgenomic replicons in a single ligation reaction with >80% efficiency. Fully sequenced replicons and infectious viral stocks can be generated in 1 and 3 weeks, respectively. By testing a series of naturally occurring viruses as well as Delta-Omicron chimeric replicons, we show that Omicron nonstructural protein 6 harbors critical attenuating mutations, which dampen viral RNA replication and reduce lipid droplet consumption. Thus, pGLUE overcomes remaining barriers to broadly study SARS-CoV-2 replication and reveals deficits in nonstructural protein function underlying Omicron attenuation.

The creation of oral microcosms with reproducible composition is important for developing model systems of the oral microbiome. However, oral microbiomes vary substantially across individuals. To derive a reproducible composition from inocula sourced from different individuals, we tested whether selective conditions from cold storage and culturing in defined media would generate a reproducible community composition despite individual variations. In this pilot study, we collected dental plaque scrapings from three individuals, inoculated media under anaerobic conditions, and characterized the bacterial community compositions after cold storage and subsequent propagation in liquid media. Harvested cultures were extracted and bacterial composition was determined by 16S rRNA gene amplicon sequencing and the mothur pipeline. Our results show that samples from two out of three individuals clustered into a specific compositional type (termed attractor here). In addition, the samples from the third individual could adopt this attractor compositional type after propagation in vitro, even though its original composition did not display this type. These results indicate that simple selective environments could help create reproducible microcosms despite variation among dental plaque samples sourced from different individuals. The findings illustrate important parameters to consider for creating reproducible microcosms from the human oral microbiome.

Protein aggregation is an important problem for human health and biotechnology, with consequences in areas ranging from neurodegenerative diseases to protein production yields. Methods to modulate protein aggregation are therefore essential. One suggested method to modulate protein aggregation is the use of nucleic acid aptamers, that is, single-stranded nucleic acids that have been selected to specifically bind to a target. Previous studies in some systems have demonstrated that aptamers may inhibit protein aggregation, including for α-synuclein, a protein implicated in synucleinopathies. However, the mechanisms by which aptamers might affect or modulate aggregation have not been fully determined. In this study, we investigated the effect of an aptamer that binds α-synuclein oligomer, T-SO508, on α-synuclein aggregation in vitro using thioflavin T to monitor aggregation kinetics, and we performed atomic force microscopy, transmission electron microscopy, and analytical ultracentrifugation to characterize intermediate structures. The results indicated that T-SO508, but not control DNA sequences, extends the lag phase of aggregation and stabilizes formation of a small non-fibrillar aggregate complex. Attempts to use the aptamer-induced complexes to seed fibril formation did not in fact accelerate aggregation, indicating that these structures are off-pathway for aggregation. This study highlights a potential mechanism by which aptamers may modulate the aggregation properties of proteins.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant contains extensive sequence changes relative to the earlier-arising B.1, B.1.1, and Delta SARS-CoV-2 variants that have unknown effects on viral infectivity and response to existing vaccines. Using SARS-CoV-2 virus-like particles (VLPs), we examined mutations in all four structural proteins and found that Omicron and Delta showed 4.6-fold higher luciferase delivery overall relative to the ancestral B.1 lineage, a property conferred mostly by enhancements in the S and N proteins, while mutations in M and E were mostly detrimental to assembly. Thirty-eight antisera samples from individuals vaccinated with Pfizer/BioNTech, Moderna, or Johnson & Johnson vaccines and convalescent sera from unvaccinated COVID-19 survivors had 15-fold lower efficacy to prevent cell transduction by VLPs containing the Omicron mutations relative to the ancestral B.1 spike protein. A third dose of Pfizer vaccine elicited substantially higher neutralization titers against Omicron, resulting in detectable neutralizing antibodies in eight out of eight subjects compared to one out of eight preboosting. Furthermore, the monoclonal antibody therapeutics casirivimab and imdevimab had robust neutralization activity against B.1 and Delta VLPs but no detectable neutralization of Omicron VLPs, while newly authorized bebtelovimab maintained robust neutralization across variants. Our results suggest that Omicron has similar assembly efficiency and cell entry compared to Delta and that its rapid spread is due mostly to reduced neutralization in sera from previously vaccinated subjects. In addition, most currently available monoclonal antibodies will not be useful in treating Omicron-infected patients with the exception of bebtelovimab.

SARS-CoV-2 Delta and Omicron are globally relevant variants of concern. Although individuals infected with Delta are at risk of developing severe lung disease, infection with Omicron often causes milder symptoms, especially in vaccinated individuals1,2. The question arises of whether widespread Omicron infections could lead to future cross-variant protection, accelerating the end of the pandemic. Here we show that without vaccination, infection with Omicron induces a limited humoral immune response in mice and humans. Sera from mice overexpressing the human ACE2 receptor and infected with Omicron neutralize only Omicron, but not other variants of concern, whereas broader cross-variant neutralization was observed after WA1 and Delta infections. Unlike WA1 and Delta, Omicron replicates to low levels in the lungs and brains of infected animals, leading to mild disease with reduced expression of pro-inflammatory cytokines and diminished activation of lung-resident T cells. Sera from individuals who were unvaccinated and infected with Omicron show the same limited neutralization of only Omicron itself. By contrast, Omicron breakthrough infections induce overall higher neutralization titres against all variants of concern. Our results demonstrate that Omicron infection enhances pre-existing immunity elicited by vaccines but, on its own, may not confer broad protection against non-Omicron variants in unvaccinated individuals.

Inhibitors of bromodomain and extraterminal domain (BET) proteins are possible anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prophylactics as they downregulate angiotensin-converting enzyme 2 (ACE2). Here we show that BET proteins should not be inactivated therapeutically because they are critical antiviral factors at the post-entry level. Depletion of BRD3 or BRD4 in cells overexpressing ACE2 exacerbates SARS-CoV-2 infection; the same is observed when cells with endogenous ACE2 expression are treated with BET inhibitors during infection and not before. Viral replication and mortality are also enhanced in BET inhibitor-treated mice overexpressing ACE2. BET inactivation suppresses interferon production induced by SARS-CoV-2, a process phenocopied by the envelope (E) protein previously identified as a possible "histone mimetic." E protein, in an acetylated form, directly binds the second bromodomain of BRD4. Our data support a model where SARS-CoV-2 E protein evolved to antagonize interferon responses via BET protein inhibition; this neutralization should not be further enhanced with BET inhibitor treatment.

Two leading impediments to chronic wound healing are polymicrobial infection and biofilm formation. Recent studies have characterized the bacterial fraction of these microbiomes and have begun to elucidate compositional correlations to healing outcomes. However, the factors that drive compositional shifts are still being uncovered. The virome may play an important role in shaping bacterial community structure and function. Previous work on the skin virome determined that it was dominated by bacteriophages, viruses that infect bacteria. To characterize the virome, we enrolled 20 chronic wound patients presenting at an outpatient wound care clinic in a microbiome survey, collecting swab samples from healthy skin and chronic wounds (diabetic, venous, arterial, or pressure) before and after a single, sharp debridement procedure. We investigated the virome using a virus-like particle enrichment procedure, shotgun metagenomic sequencing, and a k-mer-based, reference-dependent taxonomic classification method. Taxonomic composition, diversity, and associations with covariates are presented. We find that the wound virome is highly diverse, with many phages targeting known pathogens, and may influence bacterial community composition and functionality in ways that impact healing outcomes. IMPORTANCE Chronic wounds are an increasing medical burden. These wounds are known to be rich in microbial content, including both bacteria and bacterial viruses (phages). The viruses may play an important role in shaping bacterial community structure and function. We analyzed the virome and bacterial composition of 20 patients with chronic wounds. The viruses found in wounds are highly diverse compared to normal skin, unlike the bacterial composition, where diversity is decreased. These data represent an initial look at this relatively understudied component of the chronic wound microbiome and may help inform future phage-based interventions.

Infections caused by drug-resistant bacteria, particularly Gram-negative organisms, are increasingly difficult to treat using antibiotics. A potential alternative is "phage therapy", in which phages infect and lyse the bacterial host. However, phage therapy poses serious drawbacks and safety concerns, such as the risk of genetic transduction of antibiotic resistance genes, inconsistent pharmacokinetics, and unknown evolutionary potential. In contrast, metallic nanoparticles possess precise, tunable properties, including efficient conversion of electronic excitation into heat. In this work, we demonstrate that engineered phage-nanomaterial conjugates that target the Gram-negative pathogen Pseudomonas aeruginosa are highly effective as a treatment of infected wounds in mice. Photothermal heating, performed as a single treatment (15 min) or as two treatments on consecutive days, rapidly reduced the bacterial load and released Zn2+ to promote wound healing. The phage-nanomaterial treatment was significantly more effective than systemic standard-of-care antibiotics, with a >10× greater reduction in bacterial load and ∼3× faster healing as measured by wound size reduction when compared to fluoroquinolone treatment. Notably, the phage-nanomaterial was also effective against a P. aeruginosa strain resistant to polymyxins, a last-line antibiotic therapy. Unlike these antibiotics, the phage-nanomaterial showed no detectable toxicity or systemic effects in mice, consistent with the short duration and localized nature of phage-nanomaterial treatment. Our results demonstrate that phage therapy controlled by inorganic nanomaterials can be a safe and effective antimicrobial strategy in vivo.

SARS-CoV-2 non-structural protein Nsp14 is a highly conserved enzyme necessary for viral replication. Nsp14 forms a stable complex with non-structural protein Nsp10 and exhibits exoribonuclease and N7-methyltransferase activities. Protein-interactome studies identified human sirtuin 5 (SIRT5) as a putative binding partner of Nsp14. SIRT5 is an NAD-dependent protein deacylase critical for cellular metabolism that removes succinyl and malonyl groups from lysine residues. Here we investigated the nature of this interaction and the role of SIRT5 during SARS-CoV-2 infection. We showed that SIRT5 interacts with Nsp14, but not with Nsp10, suggesting that SIRT5 and Nsp10 are parts of separate complexes. We found that SIRT5 catalytic domain is necessary for the interaction with Nsp14, but that Nsp14 does not appear to be directly deacylated by SIRT5. Furthermore, knock-out of SIRT5 or treatment with specific SIRT5 inhibitors reduced SARS-CoV-2 viral levels in cell-culture experiments. SIRT5 knock-out cells expressed higher basal levels of innate immunity markers and mounted a stronger antiviral response, independently of the Mitochondrial Antiviral Signaling Protein MAVS. Our results indicate that SIRT5 is a proviral factor necessary for efficient viral replication, which opens novel avenues for therapeutic interventions.

During the origin of life, encapsulation of RNA inside vesicles is believed to have been a defining feature of the earliest cells (protocells). The confined biophysical environment provided by membrane encapsulation differs from that of bulk solution and has been shown to increase activity as well as evolutionary rate for functional RNA. However, the structural basis of the effect on RNA has not been clear. Here, we studied how encapsulation of the hairpin ribozyme inside model protocells affects ribozyme kinetics, ribozyme folding into the active conformation, and cleavage and ligation activities. We further examined the effect of encapsulation on the folding of a stem-loop RNA structure and on the formation of a triplex structure in a pH-sensitive DNA switch. The results indicate that encapsulation promotes RNA-RNA association, both intermolecular and intramolecular, and also stabilizes tertiary folding, including the docked conformation characteristic of the active hairpin ribozyme and the triplex structure. The effects of encapsulation were sufficient to rescue the activity of folding-deficient mutants of the hairpin ribozyme. Stabilization of multiple modes of nucleic acid folding and interaction thus enhanced the activity of encapsulated nucleic acids. Increased association between RNA molecules may facilitate the formation of more complex structures and cooperative interactions. These effects could promote the emergence of biological functions in an "RNA world" and may have utility in the construction of minimal synthetic cells.

Systems of catalytic RNAs presumably gave rise to important evolutionary innovations, such as the genetic code. Such systems may exhibit particular tolerance to errors (error minimization) as well as coding specificity. While often assumed to result from natural selection, error minimization may instead be an emergent by-product. In an RNA world, a system of self-aminoacylating ribozymes could enforce the mapping of amino acids to anticodons. We measured the activity of thousands of ribozyme mutants on alternative substrates (activated analogs for tryptophan, phenylalanine, leucine, isoleucine, valine, and methionine). Related ribozymes exhibited shared preferences for substrates, indicating that adoption of additional amino acids by existing ribozymes would itself lead to error minimization. Furthermore, ribozyme activity was positively correlated with specificity, indicating that selection for increased activity would also lead to increased specificity. These results demonstrate that by-products of ribozyme evolution could lead to adaptive value in specificity and error tolerance.

Efforts to determine why new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants demonstrate improved fitness have been limited to analyzing mutations in the spike (S) protein with the use of S-pseudotyped particles. In this study, we show that SARS-CoV-2 virus-like particles (SC2-VLPs) can package and deliver exogenous transcripts, enabling analysis of mutations within all structural proteins and at multiple steps in the viral life cycle. In SC2-VLPs, four nucleocapsid (N) mutations found universally in more-transmissible variants independently increased messenger RNA delivery and expression ~10-fold, and in a reverse genetics model, the serine-202→arginine (S202R) and arginine-203→methionine (R203M) mutations each produced >50 times as much virus. SC2-VLPs provide a platform for rapid testing of viral variants outside of a biosafety level 3 setting and demonstrate N mutations and particle assembly to be mechanisms that could explain the increased spread of variants, including B.1.617.2 (Delta, which contains the R203M mutation).