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At least 145 records · Page 8

Genetic circuit design automation for yeast

Cells can be programmed to monitor and react to their environment using genetic circuits. Design automation software maps a desired circuit function to a DNA sequence, a process that requires units of gene regulation (gates) that are simple to connect and behave predictably. This poses a challenge for eukaryotes due to their complex mechanisms of transcription and translation. To this end, we have developed gates for yeast (Saccharomyces cerevisiae) that are connected using RNA polymerase flux as the signal carrier and are insulated from each other and host regulation. They are based on minimal constitutive promoters (~120 base pairs), for which rules are developed to insert operators for DNA-binding proteins. Using this approach, in this work we constructed nine NOT/NOR gates with nearly identical response functions and 400-fold dynamic range. In circuits, they are transcriptionally insulated from each other by placing ribozymes downstream of terminators to block nuclear export of messenger RNAs resulting from RNA polymerase readthrough. Based on these gates, Cello 2.0 was used to build circuits with up to 11 regulatory proteins. A simple dynamic model predicts the circuit response over days. Genetic circuit design automation for eukaryotes simplifies the construction of regulatory networks as part of cellular engineering projects, whether it be to stage processes during bioproduction, serve as environmental sentinels or guide living therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

RCSB Protein Data Bank tools for 3D structure-guided cancer research: human papillomavirus (HPV) case study

Abstract Atomic-level three-dimensional (3D) structure data for biological macromolecules often prove critical to dissecting and understanding the precise mechanisms of action of cancer-related proteins and their diverse roles in oncogenic transformation, proliferation, and metastasis. They are also used extensively to identify potentially druggable targets and facilitate discovery and development of both small-molecule and biologic drugs that are today benefiting individuals diagnosed with cancer around the world. 3D structures of biomolecules (including proteins, DNA, RNA, and their complexes with one another, drugs, and other small molecules) are freely distributed by the open-access Protein Data Bank (PDB). This global data repository is used by millions of scientists and educators working in the areas of drug discovery, vaccine design, and biomedical and biotechnology research. The US Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) provides an integrated portal to the PDB archive that streamlines access for millions of worldwide PDB data consumers worldwide. Herein, we review online resources made available free of charge by the RCSB PDB to basic and applied researchers, healthcare providers, educators and their students, patients and their families, and the curious public. We exemplify the value of understanding cancer-related proteins in 3D with a case study focused on human papillomavirus.

60 APPLIED LIFE SCIENCES↗

Host analysis-guided selection and targeted engineering (HASTE) of Lipomyces tetrasporus for the conversion of CO2-derived feedstocks

Efficient and cost-competitive bioproduction calls for utilizing CO2-derived feedstocks, such as products from electro-reduction of CO2 and hydrolysate from lignocellulosic biomass. However, efficiently using all their carbon components, including acetate, glucose, and xylose, remains a challenge. Here, we characterize Lipomyces tetrasporus, a novel, robust yeast strain capable of effectively assimilating these carbon sources. We used an integrated systems biology approach combining ¹³C metabolic flux analysis, dynamic labeling experiments, and RNA sequencing. We conducted the first metabolic flux analysis for glucose, xylose, and acetate catabolism in this species. Dynamic labeling revealed a highly active TCA cycle during acetate metabolism, evidenced by rapid citrate and malate accumulation. The strain demonstrated strong NADH/NADPH production and acetyl-CoA synthase activity. Using insights and gene targets from this analysis, we engineered L. tetrasporus for malate production. The engineered strain produced 7.5 g/L malic acid (0.25 g/g yield) in shake flasks with glucose-acetate media and 28.8 g/L malic acid at a yield of 0.20 g/g in fed-batch mode with corn-stover hydrolysate. Together, these insights and rational strain engineering establish L. tetrasporus as a versatile, Crabtree-negative platform that is an energy-CO2-bioproduction nexus for channeling CO2 carbon into value-added bioproducts.

Xiao, Zhengyang↗

Unravelling the dynamics of the maturation protein in MS2 bacteriophage via molecular simulations

The MS2 bacteriophage capsid serves as a model system for studying viral structure and function. Mature MS2 virus consists of 178 capsid proteins and a single maturation protein (MP), which is essential for host receptor binding and infection initiation. Despite its critical role, the dynamic behavior of the capsid with the MP remains poorly understood. To address this, we conducted 0.5 µs all-atom molecular dynamics (MD) simulations of the MS2 capsid with and without the MP, revealing key insights into its structural dynamics. Our simulations showed that MP exhibits high flexibility, particularly in the “tip” and “side-loop” regions, which undergo significant motions that likely enhance its ability to engage with the F-pilus receptor. Detailed analysis of MP conformational states revealed that loop rearrangements around H357 enable transient switching between “semi-closed” and “open” conformations, suggesting a conformational selection mechanism for pilus binding. Additionally, ion interaction analyses revealed distinct sodium and chloride binding patterns, where sodium ions were mostly found at the outer capsid shell, while chloride ions interacted with the basic residues on the RNA-facing side. We also found that the presence of the MP enhances salt-bridge interactions, contributing to increased capsid stability, yet it does not significantly alter the pore sizes of pentameric and hexameric units. Together, these findings provide new insights into the functional role of the MP, highlighting its contribution to capsid stability and host receptor engagement. This study offers a foundation for understanding capsid dynamics relevant to viral infectivity and may guide future rational strategies aimed at disrupting host-virus interactions.

Capsid stability↗

Systems analysis of Lipomyces starkeyi during growth on various plant-based sugars

Oleaginous yeasts have received significant attention due to their substantial lipid storage capability. The accumulated lipids can be utilized directly or processed into various bioproducts and biofuels. Lipomyces starkeyi is an oleaginous yeast capable of using multiple plant-based sugars, such as glucose, xylose, and cellobiose. It is, however, a relatively unexplored yeast due to limited knowledge about its physiology. In this study, we have evaluated the growth of L. starkeyi on different sugars and performed transcriptomic and metabolomic analyses to understand the underlying mechanisms of sugar metabolism. Principal component analysis showed clear differences resulting from growth on different sugars. We have further reported various metabolic pathways activated during growth on these sugars. We also observed non-specific regulation in L. starkeyi and have updated the gene annotations for the NRRL Y-11557 strain. Furthermore, this analysis provides a foundation for understanding the metabolism of these plant-based sugars and potentially valuable information to guide the metabolic engineering of L. starkeyi to produce bioproducts and biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits

Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compound which can reduce the inflammation caused by SD-LPS. To understand the gene regulatory networks of these processes, we have generated scRNA-seq data from mouse monocytes treated with these compounds and identified 11 novel cell clusters. We have developed a machine learning method to integrate scRNA-seq, ATAC-seq, and binding motifs to characterize gene regulatory networks underlying these cell clusters. Using guided regularized random forest and feature selection, our method achieved high performance and outperformed a traditional enrichment-based method in selecting candidate regulatory genes. Our method is particularly efficient in selecting a few candidate genes to explain observed expression pattern. In particular, among 531 candidate TFs, our method achieves an auROC of 0.961 with only 10 motifs. Finally, we found two novel subpopulations of monocyte cells in response to SD-LPS and we confirmed our analysis using independent flow cytometry experiments. Our results suggest that our new machine learning method can select candidate regulatory genes as potential targets for developing new therapeutics against low grade inflammation.

60 APPLIED LIFE SCIENCES↗

A structure-based mechanism for displacement of the HEXIM adapter from 7SK small nuclear RNA

Productive transcriptional elongation of many cellular and viral mRNAs requires transcriptional factors to extract pTEFb from the 7SK snRNP by modulating the association between HEXIM and 7SK snRNA. In HIV-1, Tat binds to 7SK by displacing HEXIM. However, without the structure of the 7SK-HEXIM complex, the constraints that must be overcome for displacement remain unknown. Furthermore, while structure details of the Tat NL4-3 -7SK complex have been elucidated, it is unclear how subtypes with more HEXIM-like Tat sequences accomplish displacement. Here we report the structures of HEXIM, Tat G , and Tat Fin arginine rich motifs in complex with the apical stemloop-1 of 7SK. While most interactions between 7SK with HEXIM and Tat are similar, critical differences exist that guide function. First, the conformational plasticity of 7SK enables the formation of three different base pair configurations at a critical remodeling site, which allows for the modulation required for HEXIM binding and its subsequent displacement by Tat. Furthermore, the specific sequence variations observed in various Tat subtypes all converge on remodeling 7SK at this region. Second, we show that HEXIM primes its own displacement by causing specific local destabilization upon binding — a feature that is then exploited by Tat to bind 7SK more efficiently.

59 BASIC BIOLOGICAL SCIENCES↗

Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets

Identifying genomic alterations of cancer proteins has guided the development of targeted therapies, but proteomic analyses are required to validate and reveal new treatment opportunities. Herein, we develop a new algorithm, OPPTI, to discover overexpressed kinase proteins across 10 cancer types using global mass spectrometry proteomics data of 1,071 cases. OPPTI outperforms existing methods by leveraging multiple co-expressed markers to identify targets overexpressed in a subset of tumors. OPPTI-identified overexpression of ERBB2 and EGFR proteins correlates with genomic amplifications, while CDK4/6, PDK1, and MET protein overexpression frequently occur without corresponding DNA- and RNA-level alterations. Analyzing CRISPR screen data, we confirm expression-driven dependencies of multiple currently-druggable and new target kinases whose expressions are validated by immunochemistry. Identified kinases are further associated with up-regulated phosphorylation levels of corresponding signaling pathways. Collectively, our results reveal protein-level aberrations—sometimes not observed by genomics—represent cancer vulnerabilities that may be targeted in precision oncology.

60 APPLIED LIFE SCIENCES↗

Structural Analysis of 23S rRNA Methylating Enzyme Cfr Reveals RNA-Binding Determinants for Methylation Regiospecificity and Antibiotic Resistance

The 23S rRNA methylating enzyme Cfr, found in pathogens including Staphylococcus aureus, Clostridium difficile, Escherichia coli, and Klebsiella pneumoniae, confers resistance to phenicols, lincosamides, oxazolidinones (including linezolid), pleuromutilins, and streptogramins A (the PhLOPS A phenotype). Cfr catalyzes methylation of the C8 position of the A2503 base in 23S rRNA, the recognition site of the above antibiotic classes. Along with the RlmN housekeeping enzyme, Cfr can also promote methylation of the C2 position of the same base. The molecular and structural basis of Cfr’s dual substrate specificity is not known, which hinders our ability to design Cfr-targeting inhibitors necessary to curb PhLOPS A resistance. Here, we present the first crystal structure of Cfr and a detailed analysis of its possible interactions with rRNA. Using structure-guided mutagenesis, mass spectrometry analysis of in cellulo 23S rRNA methylated species, and in cellulo resistance studies, we identify the key amino acids essential for Cfr methylation and multidrug resistance activity. In particular, we found that Cfr’s Q329 residue is important for C8- specific methylation. These data provide a framework for further studies of the biochemistry, structure, and inhibition of this important resistance determinant.

AlphaFold↗

Chemoproteogenomic stratification of the missense variant cysteinome

Abstract Cancer genomes are rife with genetic variants; one key outcome of this variation is widespread gain-of-cysteine mutations. These acquired cysteines can be both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain unidentified via chemoproteomics; identification is a critical step to enable functional analysis, including assessment of potential druggability and susceptibility to oxidation. Here, we pair cysteine chemoproteomics—a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues—with genomics to reveal the hidden landscape of cysteine genetic variation. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized two-stage false discovery rate (FDR) error controlled proteomic search, which is further enhanced with a user-friendly FragPipe interface. Chemoproteogenomics analysis reveals that cysteine acquisition is a ubiquitous feature of both healthy and cancer genomes that is further elevated in the context of decreased DNA repair. Reference cysteines proximal to missense variants are also found to be pervasive, supporting heretofore untapped opportunities for variant-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and is compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.

Desai, Heta (ORCID:0000000343621707)↗

A census of the lung: CellCards from LungMAP

The human lung plays vital roles in respiration, host defense, and basic physiology. Recent technological advancements such as single-cell RNA sequencing and genetic lineage tracing have revealed novel cell types and enriched functional properties of existing cell types in lung. The time has come to take a new census. Initiated by members of the NHLBI-funded LungMAP Consortium and aided by experts in the lung biology community, we synthesized current data into a comprehensive and practical cellular census of the lung. Identities of cell types in the normal lung are captured in individual cell cards with delineation of function, markers, developmental lineages, heterogeneity, regenerative potential, disease links, and key experimental tools. This publication will serve as the starting point of a live, up-to-date guide for lung research at https://www.lungmap.net/cell-cards/. We hope that Lung CellCards will promote the community-wide effort to establish, maintain, and restore respiratory health.

COVID↗

RCSB protein data Bank: Next‐generation advanced search for exploration of experimental structures and computed structure models

Abstract The Protein Data Bank (PDB), established in 1971, is the primary global, open‐access archive for experimentally determined 3D macromolecular structures (proteins, RNA, DNA). The research‐focused RCSB.org web‐portal provides access to these data alongside more than one million machine‐learning‐predicted structure models, greatly expanding the available structural landscape. Rapid growth of both experimental and computational structures has increased the need for powerful yet accessible search tools that serve a broad and diverse scientific community. Herein, we describe a redesigned RCSB Protein Data Bank RCSB.org Advanced Search capability that supports intuitive discovery of 3D structures through a unified interface. This interface integrates annotation‐, sequence‐, and 3D structure‐based searches, embeds an interactive 3D viewer, and incorporates curated biological knowledge, such as catalytic site definitions from Mechanism and Catalytic Site Atlas and ligand‐guided structural motifs, for constructing geometry‐driven queries. A new Chemical Search tool allows definition of chemical queries via an integrated drawing tool or standard identifiers, seamlessly combining them with annotation filters. By allowing query definition directly within spatial and chemical contexts, these search interfaces reduce the need for detailed knowledge of residue numbering, chain identifiers, or external cheminformatics software. This capability enables efficient exploration of structures, chemical diversity, and structure–function relationships across all life domains. The redesigned interfaces can be accessed directly at rcsb.org/search/advanced for Advanced Search and rcsb.org/search/chemical for Chemical Search.

Rose, Yana [Research Collaboratory for Structural ↗

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗

$\mathrm{CROPSR}$: an automated platform for complex genome-wide $\mathrm{CRISPR}$ g$\mathrm{RNA}$ design and validation

CRISPR/Cas9 technology has become an important tool to generate targeted, highly specific genome mutations. The technology has great potential for crop improvement, as crop genomes are tailored to optimize specific traits over generations of breeding. Many crops have highly complex and polyploid genomes, particularly those used for bioenergy or bioproducts. The majority of tools currently available for designing and evaluating gRNAs for CRISPR experiments were developed based on mammalian genomes that do not share the characteristics or design criteria for crop genomes. We have developed an open source tool for genome-wide design and evaluation of gRNA sequences for CRISPR experiments, CROPSR. The genome-wide approach provides a significant decrease in the time required to design a CRISPR experiment, including validation through PCR, at the expense of an overhead compute time required once per genome, at the first run. To better cater to the needs of crop geneticists, restrictions imposed by other packages on design and evaluation of gRNA sequences were lifted. A new machine learning model was developed to provide scores while avoiding situations in which the currently available tools sometimes failed to provide guides for repetitive, A/T-rich genomic regions. We show that our gRNA scoring model provides a significant increase in prediction accuracy over existing tools, even in non-crop genomes. CROPSR provides the scientific community with new methods and a new workflow for performing CRISPR/Cas9 knockout experiments. CROPSR reduces the challenges of working in crops, and helps speed gRNA sequence design, evaluation and validation. We hope that the new software will accelerate discovery and reduce the number of failed experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural basis for a highly conserved RNA-mediated enteroviral genome replication

Abstract Enteroviruses contain conserved RNA structures at the extreme 5′ end of their genomes that recruit essential proteins 3CD and PCBP2 to promote genome replication. However, the high-resolution structures and mechanisms of these replication-linked RNAs (REPLRs) are limited. Here, we determined the crystal structures of the coxsackievirus B3 and rhinoviruses B14 and C15 REPLRs at 1.54, 2.2 and 2.54 Å resolution, revealing a highly conserved H-type four-way junction fold with co-axially stacked sA-sD and sB-sC helices that are stabilized by a long-range A•C•U base-triple. Such conserved features observed in the crystal structures also allowed us to predict the models of several other enteroviral REPLRs using homology modeling, which generated models almost identical to the experimentally determined structures. Moreover, our structure-guided binding studies with recombinantly purified full-length human PCBP2 showed that two previously proposed binding sites, the sB-loop and 3′ spacer, reside proximally and bind a single PCBP2. Additionally, the DNA oligos complementary to the 3′ spacer, the high-affinity PCBP2 binding site, abrogated its interactions with enteroviral REPLRs, suggesting the critical roles of this single-stranded region in recruiting PCBP2 for enteroviral genome replication and illuminating the promising prospects of developing therapeutics against enteroviral infections targeting this replication platform.

Biochemistry & Molecular Biology↗

Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

Abstract Background Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. Methods We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. Results We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations inTP53,PLXNB3, Zinc finger genes, and fewer mutations inSDC2,CDH1,PIK3CA,SVIL, andPTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA–protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, includingKIAA1522,DCK,FOXO3,MYO9B,ARID1A,EPRS,ZC3HAV1, andRBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. Conclusions This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Oncology↗

Structural basis for ring-opening fluorescence by the RhoBAST RNA aptamer

Abstract Tagging RNAs with fluorogenic aptamers has enabled imaging of transcripts in living cells, revealing novel aspects of RNA metabolism and dynamics. While a diverse set of fluorogenic aptamers has been developed, a new generation of aptamers uses the ring-opening of spirocyclic rhodamine dyes to achieve robust performance in live mammalian cells. These fluorophores have two chemical states: a cell-permeable spirocyclic state and a fluorescent zwitterionic state. The SpyRho555 dye is mostly non-fluorescent in solution and becomes fluorescent in complex with the RhoBAST aptamer. To understand the basis for RhoBAST-SpyRho555 fluorogenicity, we have determined crystal structures of RhoBAST in complex with 5-carboxytetramethylrhodamine and a SpyRho555 analogue, MaP555. RhoBAST is organized by a perfect four-way junction that positions two loops to form the dye-binding pocket. The core of the ligand resides between a tri-adenine floor and a single guanine base, largely driven by π-stacking interactions. Importantly, the unpaired guanine interacts with the 3-position group of MaP555 to stabilize the open conformation, supported by mutagenesis data, and may play an active role in promoting the open conformation of the dye. This work has implications for the development of new fluorogenic aptamers with improved properties using structure-guided design approaches.

Biochemistry & Molecular Biology↗