Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “structured RNA”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

Structures of diverse poxin cGAMP nucleases reveal a widespread role for cGAS-STING evasion in host–pathogen conflict

DNA viruses in the family Poxviridae encode poxin enzymes that degrade the immune second messenger 2'3'-cGAMP to inhibit cGAS-STING immunity in mammalian cells. The closest homologs of poxin exist in the genomes of insect viruses suggesting a key mechanism of cGAS-STING evasion may have evolved outside of mammalian biology. Here we use a biochemical and structural approach to discover a broad family of 369 poxins encoded in diverse viral and animal genomes and define a prominent role for 2'3'-cGAMP cleavage in metazoan host-pathogen conflict. Structures of insect poxins reveal unexpected homology to flavivirus proteases and enable identification of functional self-cleaving poxins in RNA-virus polyproteins. Our data suggest widespread 2'3'-cGAMP signaling in insect antiviral immunity and explain how a family of cGAS-STING evasion enzymes evolved from viral proteases through gain of secondary nuclease activity. Poxin acquisition by poxviruses demonstrates the importance of environmental connections in shaping evolution of mammalian pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

Circularization of 23S rRNA but not 16S rRNA within archaeal ribosomes

Background Processing of archaeal 16S and 23S rRNAs is believed to involve excision of individual rRNAs from polycistronic precursors, circularization of excised rRNAs, and re-linearization before the incorporation into ribosomes. However, all the knowledge is derived from several isolated species, leaving open the possibility that different processes may occur in other archaeal groups. Results Here, we investigate rRNAs from diverse and mostly uncultivated archaea. Sequencing of total cellular RNA from eight phylum-level lineages indicates that archaeal circular 23S rRNA transcript abundances vastly exceed those of linear counterparts, and linear versions are often undetectable. As the majority of rRNAs derive from mature ribosomes, the data suggest that ribosomes contain circular 23S rRNAs. Thus, we directly sequence RNA extracted from isolated ribosomes of a model archaeon, Methanosarcina acetivorans, and confirm that the 23S rRNAs in the ribosomes are circular. Structural modeling places the 5′ and 3′ ends of the linear precursors of archaeal 23S rRNAs in close proximity to form a GNRA tetraloop (in which N is A, C, G, or U and R is A or G), consistent with their existence as circular molecules. We also confirm the existence of circular 16S rRNA intermediates in transcriptomes of most archaea, yet a circular form is not evident in some distinct archaeal groups, suggesting that certain archaea do not circularize 16S rRNA during processing. Conclusions Our findings uncover unexpected variations in the processing required to generate mature rRNAs and the conformation of functional molecules in archaeal ribosomes.

Archaea↗

cGAS-like receptors sense RNA and control 3'2'-cGAMP signalling in Drosophila

Cyclic GMP–AMP synthase (cGAS) is a cytosolic DNA sensor that produces the second messenger cG[2'–5']pA[3'–5']p (2'3'-cGAMP) and controls activation of innate immunity in mammalian cells. Animal genomes typically encode multiple proteins with predicted homology to cGAS, but the function of these uncharacterized enzymes is unknown. Here we show that cGAS-like receptors (cGLRs) are innate immune sensors that are capable of recognizing divergent molecular patterns and catalysing synthesis of distinct nucleotide second messenger signals. Crystal structures of human and insect cGLRs reveal a nucleotidyltransferase signalling core shared with cGAS and a diversified primary ligand-binding surface modified with notable insertions and deletions. We demonstrate that surface remodelling of cGLRs enables altered ligand specificity and used a forward biochemical screen to identify cGLR1 as a double-stranded RNA sensor in the model organism Drosophila melanogaster. We show that RNA recognition activates Drosophila cGLR1 to synthesize the novel product cG[3'–5']pA[2'–5']p (3'2'-cGAMP). A crystal structure of Drosophila stimulator of interferon genes (dSTING) in complex with 3'2'-cGAMP explains selective isomer recognition, and 3'2'-cGAMP induces an enhanced antiviral state in vivo that protects from viral infection. Similar to radiation of Toll-like receptors in pathogen immunity, our results establish cGLRs as a diverse family of metazoan pattern recognition receptors.

59 BASIC BIOLOGICAL SCIENCES↗

A DNA packaging motor inchworms along one strand allowing it to adapt to alternative double-helical structures

Abstract Ring ATPases that translocate disordered polymers possess lock-washer architectures that they impose on their substrates during transport via a hand-over-hand mechanism. Here, we investigate the operation of ring motors that transport ordered, helical substrates, such as the bacteriophage ϕ29 dsDNA packaging motor. This pentameric motor alternates between an ATP loading dwell and a hydrolysis burst wherein it packages one turn of DNA in four steps. When challenged with DNA-RNA hybrids and dsRNA, the motor matches its burst to the shorter helical pitches, keeping three power strokes invariant while shortening the fourth. Intermittently, the motor loses grip on the RNA-containing substrates, indicating that it makes optimal load-bearing contacts with dsDNA. To rationalize these observations, we propose a helical inchworm translocation mechanism in which, during each cycle, the motor increasingly adopts a lock-washer structure during the ATP loading dwell and successively regains its planar form with each power stroke during the burst.

59 BASIC BIOLOGICAL SCIENCES↗

End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman

Abstract Motivation Multiple sequence alignments (MSAs) of homologous sequences contain information on structural and functional constraints and their evolutionary histories. Despite their importance for many downstream tasks, such as structure prediction, MSA generation is often treated as a separate pre-processing step, without any guidance from the application it will be used for. Results Here, we implement a smooth and differentiable version of the Smith–Waterman pairwise alignment algorithm that enables jointly learning an MSA and a downstream machine learning system in an end-to-end fashion. To demonstrate its utility, we introduce SMURF (Smooth Markov Unaligned Random Field), a new method that jointly learns an alignment and the parameters of a Markov Random Field for unsupervised contact prediction. We find that SMURF learns MSAs that mildly improve contact prediction on a diverse set of protein and RNA families. As a proof of concept, we demonstrate that by connecting our differentiable alignment module to AlphaFold2 and maximizing predicted confidence, we can learn MSAs that improve structure predictions over the initial MSAs. Interestingly, the alignments that improve AlphaFold predictions are self-inconsistent and can be viewed as adversarial. This work highlights the potential of differentiable dynamic programming to improve neural network pipelines that rely on an alignment and the potential dangers of optimizing predictions of protein sequences with methods that are not fully understood. Availability and implementation Our code and examples are available at: https://github.com/spetti/SMURF. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft tissue sarcomas that often develop in patients with neurofibromatosis type 1 (NF1). To address the critical need for novel therapeutics in MPNST, we aimed to establish an ex vivo 3D platform that accurately captured the genomic diversity of MPNST and could be utilized in a medium-throughput manner for drug screening studies to be validated in vivo using patient-derived xenografts (PDX). Genomic analysis was performed on all PDX-tumor pairs. Selected PDX were harvested for assembly into 3D microtissues. Based on prior work in our labs, we evaluated drugs (trabectedin, olaparib, and mirdametinib) ex vivo and in vivo. For 3D microtissue studies, cell viability was the endpoint as assessed by Zeiss Axio Observer. For PDX drug studies, tumor volume was measured twice weekly. Bulk RNA sequencing was performed to identify pathways enriched in cells. We developed 13 NF1-associated MPNST-PDX and identified mutations or structural abnormalities in NF1 (100%), SUZ12 (85%), EED (15%), TP53 (15%), CDKN2A (85%), and chromosome 8 gain (77%). We successfully assembled PDX into 3D microtissues, categorized as robust (>90% viability at 48 h), good (>50%), or unusable (<50%). We evaluated drug response to “robust” or “good” microtissues, namely MN-2, JH-2-002, JH-2-079-c, and WU-225. Drug response ex vivo predicted drug response in vivo, and enhanced drug effects were observed in select models. These data support the successful establishment of a novel 3D platform for drug discovery and MPNST biology exploration in a system representative of the human condition.

60 APPLIED LIFE SCIENCES↗

Host genotype controls ecological change in the leaf fungal microbiome

Leaf fungal microbiomes can be fundamental drivers of host plant success, as they contain pathogens that devastate crop plants and taxa that enhance nutrient uptake, discourage herbivory, and antagonize pathogens. We measured leaf fungal diversity with amplicon sequencing across an entire growing season in a diversity panel of switchgrass ( Panicum virgatum ). We also sampled a replicated subset of genotypes across 3 additional sites to compare the importance of time, space, ecology, and genetics. We found a strong successional pattern in the microbiome shaped both by host genetics and environmental factors. Further, we used genome-wide association (GWA) mapping and RNA sequencing to show that 3 cysteine-rich receptor-like kinases (crRLKs) were linked to a genetic locus associated with microbiome structure. We confirmed GWAS results in an independent set of genotypes for both the internal transcribed spacer (ITS) and large subunit (LSU) ribosomal DNA markers. Fungal pathogens were central to microbial covariance networks, and genotypes susceptible to pathogens differed in their expression of the 3 crRLKs, suggesting that host immune genes are a principal means of controlling the entire leaf microbiome.

59 BASIC BIOLOGICAL SCIENCES↗

Unified Nanotechnology Format: One Way to Store Them All

The domains of DNA and RNA nanotechnology are steadily gaining in popularity while proving their value with various successful results, including biosensing robots and drug delivery cages. Nowadays, the nanotechnology design pipeline usually relies on computer-based design (CAD) approaches to design and simulate the desired structure before the wet lab assembly. To aid with these tasks, various software tools exist and are often used in conjunction. However, their interoperability is hindered by a lack of a common file format that is fully descriptive of the many design paradigms. Therefore, in this paper, we propose a Unified Nanotechnology Format (UNF) designed specifically for the biomimetic nanotechnology field. UNF allows storage of both design and simulation data in a single file, including free-form and lattice-based DNA structures. By defining a logical and versatile format, we hope it will become a widely accepted and used file format for the nucleic acid nanotechnology community, facilitating the future work of researchers and software developers. Together with the format description and publicly available documentation, we provide a set of converters from existing file formats to simplify the transition. Finally, we present several use cases visualizing example structures stored in UNF, showcasing the various types of data UNF can handle.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Multidimensional quantitative phenotypic and molecular analysis reveals neomorphic behaviors of p53 missense mutants

Abstract Mutations in the TP53 tumor suppressor gene occur in >80% of the triple-negative or basal-like breast cancer. To test whether neomorphic functions of specific TP53 missense mutations contribute to phenotypic heterogeneity, we characterized phenotypes of non-transformed MCF10A-derived cell lines expressing the ten most common missense mutant p53 proteins and observed a wide spectrum of phenotypic changes in cell survival, resistance to apoptosis and anoikis, cell migration, invasion and 3D mammosphere architecture. The p53 mutants R248W, R273C, R248Q, and Y220C are the most aggressive while G245S and Y234C are the least, which correlates with survival rates of basal-like breast cancer patients. Interestingly, a crucial amino acid difference at one position—R273C vs. R273H—has drastic changes on cellular phenotype. RNA-Seq and ChIP-Seq analyses show distinct DNA binding properties of different p53 mutants, yielding heterogeneous transcriptomics profiles, and MD simulation provided structural basis of differential DNA binding of different p53 mutants. Integrative statistical and machine-learning-based pathway analysis on gene expression profiles with phenotype vectors across the mutant cell lines identifies quantitative association of multiple pathways including the Hippo/YAP/TAZ pathway with phenotypic aggressiveness. Further, comparative analyses of large transcriptomics datasets on breast cancer cell lines and tumors suggest that dysregulation of the Hippo/YAP/TAZ pathway plays a key role in driving the cellular phenotypes towards basal-like in the presence of more aggressive p53 mutants. Overall, our study describes distinct gain-of-function impacts on protein functions, transcriptional profiles, and cellular behaviors of different p53 missense mutants, which contribute to clinical phenotypic heterogeneity of triple-negative breast tumors.

60 APPLIED LIFE SCIENCES↗

Structured sequences emerge from random pool when replicated by templated ligation

The central question in the origin of life is to understand how structure can emerge from randomness. The Eigen theory of replication states, for sequences that are copied one base at a time, that the replication fidelity has to surpass an error threshold to avoid that replicated specific sequences become random because of the incorporated replication errors [M. Eigen, Naturwissenschaften 58 (10), 465–523 (1971)]. Here, we showed that linking short oligomers from a random sequence pool in a templated ligation reaction reduced the sequence space of product strands. We started from 12-mer oligonucleotides with two bases in all possible combinations and triggered enzymatic ligation under temperature cycles. Surprisingly, we found the robust creation of long, highly structured sequences with low entropy. At the ligation site, complementary and alternating sequence patterns developed. However, between the ligation sites, we found either an A-rich or a T-rich sequence within a single oligonucleotide. Our modeling suggests that avoidance of hairpins was the likely cause for these two complementary sequence pools. What emerged was a network of complementary sequences that acted both as templates and substrates of the reaction. This self-selecting ligation reaction could be restarted by only a few majority sequences. The findings showed that replication by random templated ligation from a random sequence input will lead to a highly structured, long, and nonrandom sequence pool. This is a favorable starting point for a subsequent Darwinian evolution searching for higher catalytic functions in an RNA world scenario.

60 APPLIED LIFE SCIENCES↗

Structural insights into RNase H catalytic mechanism from room-temperature X-ray and neutron crystallography of apo- and RNA/DNA hybrid-bound enzyme

RNase H enzymes are sequence-nonspecific endonucleases that cleave RNA strands in RNA/DNA hybrid duplexes, an enzymatic process essential in DNA replication and repair in both prokaryotes and eukaryotes. Also, RNase H activity of the reverse transcriptase in human immunodeficiency viruses (HIV-1 and HIV-2) is indispensable for the viral replication cycle. RNase H enzymes play an central role in the development of gene therapies and are targets for novel antivirals. It is therefore of great importance to gain a detailed understanding of the RNase H catalytic mechanism to improve drug design. We utilized Bacillus halodurans RNase H1 (BhRNase H1) to shed light on its function and catalytic mechanism. Room-temperature neutron crystallography of the wild-type and inactive D132N mutant enzymes revealed that E109, belonging to the catalytic DEDD motif, can change its protonation state, allowing us to propose its role in the protonation of the leaving O3′ hydroxyl group of RNA. X-ray crystallography has demonstrated the ability of the RNA/DNA duplex to slide along the protein surface upon metal ion binding at site M A , transforming a product mimic into a Michaelis-like complex, which confirms an essential role of the M A metal ion in catalysis.

Enzyme mechanisms↗

Impact of storage and extraction methods on peat soil microbiomes

Recovered microbial community structure is known to be influenced by sample storage conditions and nucleic acid extraction methods, and the impact varies by sample type. Peat soils store a large portion of soil carbon and their microbiomes mediate climate feedbacks. Here, we tested three storage conditions and five extraction protocols on peat soils from three physicochemically distinct habitats in Stordalen Mire, Sweden, revealing significant methodological impacts on microbial (here, meaning bacteria and archaea) community structure. Initial preservation method impacted alpha but not beta diversity, with in-field storage in LifeGuard buffer yielding roughly two-thirds the richness of in-field flash-freezing or transport from the field on ice (all samples were stored at −80 °C after return from the field). Nucleic acid extraction method impacted both alpha and beta diversity; one method (the PowerSoil Total RNA Isolation kit with DNA Elution Accessory kit) diverged from the others (PowerMax Soil DNA Isolation kit-High Humic Acid Protocol, and three variations of a modifiedPowerMax Soil DNA/RNA isolation kit), capturing more diverse microbial taxa, with divergent community structures. Although habitat and sample depth still consistently dominated community variation, method-based biases in microbiome recovery for these climatologically-relevant soils are significant, and underscore the importance of methodological consistency for accurate inter-study comparisons, long-term monitoring, and consistent ecological interpretations.

Science & Technology - Other Topics↗

Global overview and major challenges of host prediction methods for uncultivated phages

Bacterial communities play critical roles across all of Earth’s biomes, affecting human health and global ecosystem functioning. They do so under strong constraints exerted by viruses, i.e., bacteriophages or “phages”. Phages can reshape bacterial communities’ structure, influence long-term evolution of bacterial populations, and alter host cell metabolism during infection. Metagenomics approaches, i.e., shotgun sequencing of environmental DNA or RNA, recently enabled large-scale exploration of phage genomic diversity, yielding several millions of phage genomes now to be further analyzed and characterized. One major challenge however is the lack of direct host information for these phages. Several methods and tools have been proposed to bioinformatically predict the potential host(s) of uncultivated phages based only on genome sequence information. Here we review these different approaches and highlight their distinct strengths and limitations. We also outline complementary experimental assays which are being proposed to validate and refine these bioinformatic predictions.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of driver genes for critical forms of COVID-19 in a deeply phenotyped young patient cohort

The drivers of critical coronavirus disease 2019 (COVID-19) remain unknown. Given major confounding factors such as age and comorbidities, true mediators of this condition have remained elusive. We used a multi-omics analysis combined with artificial intelligence in a young patient cohort where major comorbidities were excluded at the onset. The cohort included 47 “critical” (in the intensive care unit under mechanical ventilation) and 25 “non-critical” (in a non-critical care ward) patients with COVID-19 and 22 healthy individuals. The analyses included whole-genome sequencing, whole-blood RNA sequencing, plasma and blood mononuclear cell proteomics, cytokine profiling, and high-throughput immunophenotyping. An ensemble of machine learning, deep learning, quantum annealing, and structural causal modeling were used. Patients with critical COVID-19 were characterized by exacerbated inflammation, perturbed lymphoid and myeloid compartments, increased coagulation, and viral cell biology. Among differentially expressed genes, we observed up-regulation of the metalloprotease ADAM9. This gene signature was validated in a second independent cohort of 81 critical and 73 recovered patients with COVID-19 and was further confirmed at the transcriptional and protein level and by proteolytic activity. Ex vivo ADAM9 inhibition decreased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uptake and replication in human lung epithelial cells. In conclusion, within a young, otherwise healthy, cohort of individuals with COVID-19, we provide the landscape of biological perturbations in vivo where a unique gene signature differentiated critical from non-critical patients. We further identified ADAM9 as a driver of disease severity and a candidate therapeutic target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mechanistic studies of small molecule ligands selective to RNA single G bulges

Abstract Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated molecular dynamics simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity relationship studies and transverse relaxation measurements by nuclear magnetic resonance spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Our work deepened the understanding of RNA-small molecule interactions and integrated a new framework for the rational design of selective small-molecule RNA binders.

Biochemistry & Molecular Biology↗

Serodominant SARS-CoV-2 Nucleocapsid Peptides Map to Unstructured Protein Regions

The SARS-CoV-2 nucleocapsid (N) protein is highly immunogenic, and anti-N antibodies are commonly used as markers for prior infection. While several studies have examined or predicted the antigenic regions of N, these have lacked consensus and structural context. Using COVID-19 patient sera to probe an overlapping peptide array, we identified six public and four private epitope regions across N, some of which are unique to this study. We further report the first deposited X-ray structure of the stable dimerization domain at 2.05 Å as similar to all other reported structures. Structural mapping revealed that most epitopes are derived from surface-exposed loops on the stable domains or from the unstructured linker regions. An antibody response to an epitope in the stable RNA binding domain was found more frequently in sera from patients requiring intensive care. Since emerging amino acid variations in N map to immunogenic peptides, N protein variation could impact detection of seroconversion for variants of concern.

60 APPLIED LIFE SCIENCES↗

Structural Studies of Inhibitors with Clinically Relevant Influenza Endonuclease Variants

Vital to the treatment of influenza is the use of antivirals such as Oseltamivir (Tamiflu) and Zanamivir (Relenza); however, antiviral resistance is becoming an increasing problem for these therapeutics. The RNA-dependent RNA polymerase acidic N-terminal (PA N ) endonuclease, a critical component of influenza viral replication machinery, is an antiviral target that was recently validated with the approval of Baloxavir Marboxil (BXM). Despite its clinical success, BXM has demonstrated susceptibility to resistance mutations, specifically the I38T, E23K, and A36 V mutants of PAN. To better understand the effects of these mutations on BXM resistance and improve the design of more robust therapeutics, this study examines key differences in protein–inhibitor interactions with two inhibitors and the I38T, E23K, and A36 V mutants. Differences in inhibitor binding were evaluated by measuring changes in binding to PA N using two biophysical methods. The binding mode of two distinct inhibitors was determined crystallographically with both wild-type and mutant forms of PA N . Collectively, these studies give some insight into the mechanism of antiviral resistance of these mutants.

60 APPLIED LIFE SCIENCES↗

Expression of a mammalian RNA demethylase increases flower number and floral stem branching in Arabidopsis thaliana

Abstract RNA methylation plays a central regulatory role in plant biology and is a relatively new target for plant improvement efforts. In nearly all cases, perturbation of the RNA methylation machinery results in deleterious phenotypes. However, a recent landmark paper reported that transcriptome‐wide use of the human RNA demethylase FTO substantially increased the yield of rice and potatoes. Here, we have performed the first independent replication of those results and demonstrated broader transferability of the trait, finding increased flower and fruit count in the model species Arabidopsis thaliana . We also performed RNA‐seq of our FTO‐transgenic plants, which we analyzed in conjunction with previously published datasets to detect several previously unrecognized patterns in the functional and structural classification of the upregulated and downregulated genes. From these, we present mechanistic hypotheses to explain these surprising results with the goal of spurring more widespread interest in this promising new approach to plant engineering.

59 BASIC BIOLOGICAL SCIENCES↗