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Selective targeting of a histone-like silencer Sfx to the R6K conjugal transfer operon.

Conjugative plasmids drive bacterial evolution and antibiotic resistance spread, yet their gene expression must be silenced to protect the host. A histone-like protein H-NS represses many mobile and sedentary xenogenes but fails to silence the conjugal transfer vir operon of R6K, a prototype IncX plasmid. Instead, R6K encodes its own H-NS homolog, Sfx, to repress the vir operon. Here, we show that, unlike other plasmid silencers that target promoters, Sfx cooperates with Rho factor to arrest transcription elongation. ChIP-seq reveals that Sfx and H-NS share similar DNA motifs and a preference for negative supercoiling, but occupy reciprocal genomic niches; Sfx is enriched on the R6K vir operon despite weak chromosomal binding, whereas H-NS displays the opposite preference. We show that Sfx binding to vir DNA critically depends on DNA topology and hypothesize that its selective targeting to R6K is mediated by Sfx-vir interactions and phase separation. Our results suggest that Sfx phase separates with R6K to ensure its preferential recruitment to the plasmid DNA and forms stable bridged nucleoprotein filaments that are impermeable to competitors such as H-NS. These findings reveal how histone-like proteins can partition the genome into distinct regulatory niches, a strategy likely mirrored across all life.

Operon

Mechanisms of enhanced or impaired DNA target selectivity driven by protein dimerization.

Successful DNA transcription demands coordination between proteins that bind DNA while simultaneously binding to one another to form dimers or higher-order complexes. For proteins with numerous DNA targets throughout the genome, measurements that report on their dwell time or occupancy thus represent a convolution over a population interacting with specific DNA, nonspecific DNA, or protein partners on DNA. Dimerization is known to add contacts that can help a single protein to stably bind DNA. However, we show here that dimerization can also impair measured dwell times and occupancy on target sequences because the population redistributes across DNA. We combine mass-action kinetic models of pairwise reversible reactions between proteins and DNA with theory and spatial stochastic simulations to isolate the role of dimerization on observed DNA dwell times, occupancy, and spatial distribution of proteins on DNA. Three key themes emerge: (i) Protein-protein interactions, in addition to protein-DNA interactions, can localize a protein to DNA, and relative binding rates can thus widely tune dwell times. (ii) Dimensional reduction achieved through nonspecific binding and subsequent 1D diffusion controls the order-of-magnitude of enhancements despite nucleosome barriers. (iii) Dimerization enhances selectivity for locally clustered targets and often impairs binding to widely-spaced targets by sequestration. Compared with ChIP-seq data, our model explains how the distribution of the essential GAF protein throughout the genome is highly selective for clustered targets due to protein interactions. This model framework predicts when even weak dimerization can redistribute and stabilize proteins on DNA as a necessary part of transcription.

DNA binding

Cell type-selective targeting by heterobifunctional protein binders via in-cell enrichment.

Non-catalytic heterobifunctional protein binders promise to expand the range of therapeutic options by establishing complexes between key target proteins and accessory presenter proteins equipped with additional properties. Here, we systematically investigate the rational design of such molecules, explore the biochemical basis of complex formation and determine how they achieve cellular efficacy using the endogenously expressed immunophilin FKBP12 as presenter protein and the transcriptional regulator BRD4 as target protein. We present classes of bifunctional molecules that enable selective, FKBP12-dependent killing of specific cell types at subnanomolar concentrations and allow to differentiate between closely related bromodomains of the BET family. We propose that the strongly potentiated efficacy of these bifunctional compounds is based on cellular enrichment through binding to the highly abundant presenter protein FKBP12, a mechanism we term "CellTrap". Our findings substantiate the concept that highly expressed, non-essential proteins can be repurposed as selective recruiters to expand therapeutic windows of existing small-molecule inhibitors, opening new avenues for designing targeted drugs with improved cell-type specificity.

Tacrolimus Binding Protein 1A

Continuously proliferating T killer cells specific for H-2b targets: selection and characterization.

BALB/c (H-2d) thymus-derived lymphocytes sensitized to C57BL/6 (H-2b) alloantigens have been propagated in vitro for over 9 months. These T lymphocytes are specifically cytotoxic to H-2b target cells but are stimulated to proliferate by both H-2b and H-2k spleen cells. This indicates that for these selected cells the antigen requirements for cell proliferation are different from those for cell-mediated cytotoxicity. If not continuously stimulated with allogeneic spleen cells, the cytotoxic cultures fail to divide and rapidly lose their cytotoxic activity. Allogeneic erythrocytes do not stimulate cell proliferation in "quiescent" cell cultures and allogeneic tumor cells do so only in the presence of spleen cells. However, "quiescent" cell cultures display cytotoxicity in the presence of phytohemagglutinin A as do cell cultures which have lost their cytotoxic activity although they proliferate upon allogeneic stimulation. The significance of these findings is discussed.

Animals

EZH1/2 inhibition selectively targets SMARCA4/2 co-deficient lung cancer cells by suppressing stemness and proliferation.

SMARCA4-deficient thoracic malignancies comprise biologically heterogeneous tumors, ranging from conventional non-small cell lung cancer with SMARCA4 alterations to thoracic SMARCA4-deficient undifferentiated tumor (SMARCA4-UT), an aggressive entity frequently associated with concomitant SMARCA2 loss. However, the extent to which SMARCA4-deficient lung cancer cell lines recapitulate SMARCA4-UT-like biology remains incompletely defined. Here, we characterized lung cancer cell lines across distinct SMARCA4 and SMARCA2 states and identified a subgroup with SMARCA4/2 co-deficiency that exhibited reduced expression of epithelial lineage markers and transcriptional similarity to SMARCA4-UT and other SWI/SNF-deficient malignancies. The EZH1/2 inhibitor HM97662 selectively suppressed growth in SMARCA4/2-deficient cells, with limited effects in SMARCA2-proficient cells. EZH1/2 inhibition broadly reduced H3K27me3 and induced derepression of PRC2 targets regardless of drug sensitivity. However, its biological effects were most pronounced in SMARCA4/2-deficient cells, where it promoted apoptosis, reduced stemness marker expression, attenuated the SMARCA4-UT-associated transcriptional signature, and suppressed proliferative and mTORC1-related programs. Chromatin accessibility analysis further revealed cell-line-specific patterns of accessibility loss, with reduced accessibility at stemness-associated transcription factor motif-enriched regions coupled with transcriptional repression of nearby genes in SMARCA4/2-deficient cells. These findings support dual EZH1/2 inhibition as a potential therapeutic vulnerability in SMARCA4/2-deficient, SMARCA4-UT-like lung cancer cells.

Humans

The histone modifier KAT2A presents a selective target in a subset of well-differentiated microsatellite-stable colorectal cancers.

Lysine acetyltransferase 2 A (KAT2A) plays a pivotal role in epigenetic gene regulation across various types of cancer. In colorectal cancer (CRC), increased KAT2A expression is associated with a more aggressive phenotype. Our study aims to elucidate the molecular underpinnings of KAT2A dependency in CRC and assess the consequences of KAT2A depletion. We conducted a comprehensive analysis by integrating CRISPR-Cas9 screening data with genomics, transcriptomics, and global acetylation patterns in CRC cell lines to pinpoint molecular markers indicative of KAT2A dependency. Additionally, we characterized the phenotypic effect of a CRISPR-interference-mediated KAT2A knockdown in CRC cell lines and patient-derived 3D spheroid cultures. Moreover, we assessed the effect of KAT2A depletion within a patient-derived xenograft mouse model in vivo. Our findings reveal that KAT2A dependency is closely associated with microsatellite stability, lower mutational burden, and increased molecular differentiation signatures in CRC, independent of the KAT2A expression levels. KAT2A-dependent CRC cells display higher gene expression levels and enriched H3K27ac marks at gene loci linked to enterocytic differentiation. Furthermore, loss of KAT2A leads to decreased cell growth and viability in vitro and in vivo, downregulation of proliferation- and stem cell-associated genes, and induction of differentiation markers. Altogether, our data show that a specific subset of CRCs with a more differentiated phenotype relies on KAT2A. For these CRC cases, KAT2A might represent a promising novel therapeutic target.

Humans

Private specificities of H-2K and H-2D loci as possible selective targets for effector lymphocytes in cell-mediated immunity.

Receptors of effector T lymphocytes of congeneic strains of mice do not recognize public H-2 specificities and react to private H-2 specificities only. This has been established with the use of three tests: direct cytotoxicity assay of immune lymphocytes upon target cells, specific absorption of the lymphocytes on the target cells, and rejection of skin grafts at an accelerated fashion. Immunization with two private H-2 specificities in the system C57BL/10ScSn leads to B10.D2 induces formation of two corresponding populations of effector lymphocytes in unequal proportion: a greater part of them is directed against the private specificity H-2.33 (Kb), while the smaller part is towards H-2.2 (Db) private specificity. These two populations of effector lymphocytes do not overlap, as demonstrated by experiments on their cross-absorption on B10.D2 (R107), B10.D2 (R101), B10.A(2R), and B10.A(5R) target cells, as well as on mixtures of R107 and R101 targets. Following removal of lymphocytes reacting with one of the private H-2 specificities, lymphocytes specific to the other specificity are fully maintained. A mixture of target cells, each bearing one of the two immunizing private specificities, absorbs 100% of the immune lymphocytes and is totally destroyed by them. It is suggested that H-2 antigens are natural complexes of hapten-carrier type, in which the role of hapten is played by public H-2 specifities and that of the carrier determinant by either private H-2 specificities or structures closely linked to them. Various models of steric arrangement of MHC determinants recognized by receptors of effector T lymphocytes are discussed.

Animals

Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma.

The embryonic transcription factor TBXT (brachyury) drives chordoma, a spinal neoplasm without effective drug therapies. TBXT's regulatory network is poorly understood, and strategies to disrupt its activity for therapeutic purposes are lacking. We developed designed ankyrin repeat proteins that block TBXT-DNA binding (T-DARPins). In chordoma cells, T-DARPins reduced cell cycle progression, spheroid formation, and tumor growth in mice and induced signs of senescence and differentiation. Transcriptomic and proteomic analyses identified gene networks involved in cell cycle regulation, embryonic cell identity, and interferon response and revealed features of regulome components, such as susceptibility to pharmacologic inhibition and the fine-tuning of TBXT downstream effectors through IGFBP3. Finally, we found high interferon signaling in chordoma cell lines and patient tumors, which was promoted by TBXT and associated with sensitivity to JAK2 inhibitors. These findings demonstrate the potential of DARPins for probing nuclear proteins to understand the regulatory networks of transcription factor-driven cancers, including entry points for therapies that warrant testing in patients.

Humans

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets.

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Escherichia coli

Target site selection and P1 engineering enable highly efficient circular RNA production via end-to-end self-targeting and splicing.

Circular RNAs (circRNAs) are more stable than linear RNAs, enabling expanding applications in RNA vaccines and therapeutics. We previously developed an in vitro circRNA preparation method based on end-to-end self-targeting and splicing (STS) using the Tetrahymena group I intron, which generates circRNAs without extraneous sequences. However, self-circularization efficiency declines as gene of interest (GOI) length increases, limiting its application to longer GOIs. Here, we systematically optimized key determinants of STS efficiency, including target site selection and P1 construct engineering. Target site screening revealed that selection of optimal target sites within each GOI markedly improved self-circularization efficiency. Moreover, engineering of the P1 construct, including incorporation of a polyA10 sequence upstream of the internal guide sequence of the intron and an antisense sequence complementary to the target site and its upstream region at the 5' side of polyA10, further enhanced efficiency. Notably, the optimized STS strategy achieved up to two-fold higher self-circularization efficiency than the conventional permuted intron-exon (PIE) method for long GOIs (∼8 K-nt). Collectively, these results establish an improved STS workflow for efficient circRNA production without extraneous sequences across a wide range of GOI lengths, outperforming the PIE method for long GOIs, and broadening biomedical applications.

RNA, Circular

Target-Site Selection by Transcription Factors: Roles of DNA, Chromatin, and Cofactor-Mediated Regulation.

Transcription factors (TFs) are sequence-specific DNA-binding proteins that regulate gene-expression programs and cell fate. The ability of a defined combination of four TFs to reprogram differentiated cells into induced pluripotent stem cells illustrates the powerful role of TFs in determining cellular identity. However, TFs usually recognize short and degenerate DNA motifs of approximately 6-12 base pairs, generating thousands to millions of potential motif matches in mammalian genomes. In living cells, TFs occupy only a restricted subset of these sites, indicating that motif presence alone is insufficient for functional target selection. Several layers of regulation contribute to this selective occupancy, including DNA methylation, nucleosome organization, histone modifications, chromatin remodeling, TF oligomerization, TF availability and localization, and cofactors that regulate DNA-binding domains. This review outlines how DNA/chromatin features and TF-centered mechanisms contribute to target-site selection. The principal aim is to highlight DNA-binding domain-directed cofactor regulation as an underappreciated mechanism that modulates TF-DNA binding and may help explain selective genomic occupancy.

Target-site selection

Targeting the MYC oncogene with a selective bi-steric mTORC1 inhibitor elicits tumor regression in MYC-driven cancers.

The MYC oncogene is causally involved in the pathogenesis of most human cancers. The mTORC1 complex regulates MYC translation through 4EBP1 and S6K. However, agents that selectively target mTORC1 (without affecting mTORC2) have so far failed to reactivate 4EBP1 and, thus, cannot effectively suppress MYC in vivo. In contrast, nonselective inhibitors that block both mTOR complexes can activate 4EBP1, but often lack tolerability and induce immunosuppression. Here, we introduce bi-steric mTORC1-selective inhibitors, including the clinical candidate RMC-5552, which potently reactivate 4EBP1 and decrease MYC protein expression levels. Consequently, suppression of MYC signaling occurs, resulting in tumor growth inhibition through both direct effects on tumor cells and immune activation. RMC-5552 exhibits anti-tumor activity in human patient-derived xenografts models harboring genomic MYC amplifications and reduces MYC protein levels in vivo. Furthermore, bi-steric mTORC1-selective inhibitors enhance the efficacy of immune checkpoint blockade, leading to tumor regression.

Mechanistic Target of Rapamycin Complex 1

Protocol to improve isoform-level quantification of low-abundance transcripts via STALARD pre-amplification.

STALARD (selective target amplification for low-abundance RNA detection) enables isoform-level quantification of low-abundance RNAs using conventional laboratory equipment. Here, we describe steps for RNA isolation, primer design, reverse transcription, selective target amplification, and downstream analysis. The protocol couples selective pre-amplification with a quantitative reverse-transcription PCR (RT-qPCR) readout and optional nanopore sequencing. Using 1 μg input RNA and 12 pre-amplification cycles, STALARD reduces Cq values by approximately 10-12 cycles, bringing the target into a reliably quantifiable range. For complete details on the use and execution of this protocol, please refer to Jeong et al.1.

Gene Expression

Dual recognition drives site-directed G-quadruplex stabilization: Oligonucleotide design in G4 ligand-oligonucleotide conjugates.

G-quadruplex (G4) DNA structures are increasingly recognized for their roles in transcriptional regulation and genome stability, making them attractive therapeutic targets. Selective recognition of individual G4s remains challenging due to the high structural similarity among G4 motifs. G4 Ligand-Oligonucleotides conjugates (GL-Os) address this challenge by combining small-molecule G4 ligands with the sequence specificity of oligonucleotides, targeting sequences flanking the intended G4 target. Here, we systematically investigate how oligonucleotide length, backbone composition, and sequence complementarity govern GL-O binding, selectivity, and G4 stabilization. We show that effective G4 recognition depends on the interdependence between oligonucleotide hybridization and G4 ligand binding, such that both elements cooperatively reinforce complex stability and site specificity. Longer oligonucleotides promote more stable complexes and stronger G4 stabilization, whereas central mismatches disrupt this dual-recognition mechanism. Replacement of DNA with peptide nucleic acids (PNAs) enhances binding strength, thermal stability, and metabolic stability. Importantly, ligand conjugation redirects PNA oligonucleotides from nonspecific polymerase stalling toward selective G4 stabilization. Finally, we demonstrate receptor-mediated cellular uptake of modified GL-Os, supporting the feasibility of cellular delivery while highlighting remaining delivery barriers. Together, these findings show the molecular design principles governing GL-O behavior and provide a foundation for the future development and evaluation of selective G4-targeting therapeutics.

G-quadruplex DNA

Social validation: the evolution of standards of competency for target behaviors.

The use of social validation procedures has become widespread in recent years. Although most researchers have used social validation procedures to select target behaviors and to evaluate whether the changes produced by a treatment program should be considered socially useful, little attention has been focused upon using the social validation process to determine the optimal levels for target behaviors. This paper suggests several ways in which social validation procedures can be employed in order to select when and how much to change target behaviors.

Behavior Therapy

Proximity Labeling of Cell Surface Proteins via Cell Surface Remodeling.

Within the complex interplay of proteins, lipids and carbohydrates at the cell surface is the surfaceome, a dense layer of proteins and their posttranslationally modified counterparts that serves as a hub for cell signaling and signal transduction. The surfaceome plays crucial roles in mediating interactions between cells and the extracellular environment, which combined with their availability at the cell surface make it an attractive therapeutic target. Despite its importance, the development of technologies to selectively target cell surface proteins for empirical identification is challenged by their structural complexity. Here, we describe a proximity labeling-based technique to covalently label proteins at the cell surface with a biotin handle, enabling downstream streptavidin-based enrichment and manipulation in a variety of modalities, including fluorescence imaging, western blotting, and mass spectrometry-based proteomics.

Membrane Proteins

PROLONG: penalized regression for outcome guided longitudinal omics analysis with network and group constraints.

MOTIVATION: There is a growing interest in longitudinal omics data paired with some longitudinal clinical outcome. Given a large set of continuous omics variables and some continuous clinical outcome, each measured for a few subjects at only a few time points, we seek to identify those variables that co-vary over time with the outcome. To motivate this problem we study a dataset with hundreds of urinary metabolites along with Tuberculosis mycobacterial load as our clinical outcome, with the objective of identifying potential biomarkers for disease progression. For such data clinicians usually apply simple linear mixed effects models which often lack power given the low number of replicates and time points. We propose a penalized regression approach on the first differences of the data that extends the lasso + Laplacian method [Li and Li (Network-constrained regularization and variable selection for analysis of genomic data. Bioinformatics 2008;24:1175-82.)] to a longitudinal group lasso + Laplacian approach. Our method, PROLONG, leverages the first differences of the data to increase power by pairing the consecutive time points. The Laplacian penalty incorporates the dependence structure of the variables, and the group lasso penalty induces sparsity while grouping together all contemporaneous and lag terms for each omic variable in the model. RESULTS: With an automated selection of model hyper-parameters, PROLONG correctly selects target metabolites with high specificity and sensitivity across a wide range of scenarios. PROLONG selects a set of metabolites from the real data that includes interesting targets identified during EDA. AVAILABILITY AND IMPLEMENTATION: An R package implementing described methods called "prolong" is available at https://github.com/stevebroll/prolong. Code snapshot available at 10.5281/zenodo.14804245.

Humans