Drug screening at single-organoid resolution via bioprinting and interferometry.

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection.

The landscape of drug sensitivity and resistance in sarcoma.

Sarcomas are a family of rare malignancies composed of over 100 distinct histological subtypes. The rarity of sarcoma poses significant challenges in conducting clinical trials to identify effective therapies, to the point that many rarer subtypes of sarcoma do not have standard-of-care treatment. Even for established regimens, there can be substantial heterogeneity in responses. Overall, novel, personalized approaches for identifying effective treatments are needed to improve patient out-comes. Patient-derived tumor organoids (PDTOs) are clinically relevant models representative of the physiological behavior of tumors across an array of malignancies. Here, we use PDTOs as a tool to better understand the biology of individual tumors and characterize the landscape of drug resistance and sensitivity in sarcoma. We collected n=194 specimens from n=126 sarcoma patients, spanning 24 distinct subtypes. We characterized PDTOs established from over 120 biopsy, resection, and metastasectomy samples. We leveraged our organoid high-throughput drug screening pipeline to test the efficacy of chemotherapeutics, targeted agents, and combination therapies, with results available within a week from tissue collection. Sarcoma PDTOs showed patient-specific growth characteristics and subtype-specific histopathology. Organoid sensitivity correlated with diagnostic subtype, patient age at diagnosis, lesion type, prior treatment history, and disease trajectory for a subset of the compounds screened. We found 90 biological pathways that were implicated in response to treatment of bone and soft tissue sarcoma organoids. By comparing functional responses of organoids and genetic features of the tumors, we show how PDTO drug screening can provide an orthogonal set of information to facilitate optimal drug selection, avoid ineffective therapies, and mirror patient outcomes in sarcoma. In aggregate, we were able to identify at least one effective FDA-approved or NCCN-recommended regimen for 59% of the specimens tested, providing an estimate of the proportion of immediately actionable information identified through our pipeline. Highlights: Standardized organoid culture preserve unique sarcoma histopathological featuresDrug screening on patient-derived sarcoma organoids provides sensitivity information that correlates with clinical features and yields actionable information for treatment guidanceHigh-throughput screenings provide orthogonal information to genetic sequencingSarcoma organoid response to treatment correlates with patient response to therapyLarge scale, functional precision medicine programs for rare cancers are feasible within a single institution.

An Optimized Workflow for the Discovery of New Antimicrobial Compounds Targeting Bacterial RNA Polymerase Complex Formation.

Bacterial resistance represents a major health problem worldwide and there is an urgent need to develop first-in-class compounds directed against new therapeutic targets. We previously developed a drug-discovery platform to identify new antimicrobials able to disrupt the protein-protein interaction between the ß' subunit and the σ70 initiation factor of bacterial RNA polymerase, which is essential for transcription. As a follow-up to such work, we have improved the discovery strategy to make it less time-consuming and more cost-effective. This involves three sequential assays, easily scalable to a high-throughput format, and a subsequent in-depth characterization only limited to hits that passed the three tests. This optimized workflow, applied to the screening of 5360 small molecules from three synthetic and natural compound libraries, led to the identification of six compounds interfering with the ß'-σ70 interaction, and thus was capable of inhibiting promoter-specific RNA transcription and bacterial growth. Upon supplementation with a permeability adjuvant, the two most potent transcription-inhibiting compounds displayed a strong antibacterial activity against Escherichia coli with minimum inhibitory concentration (MIC) values among the lowest (0.87-1.56 µM) thus far reported for ß'-σ PPI inhibitors. The newly identified hit compounds share structural feature similarities with those of a pharmacophore model previously developed from known inhibitors.

Cervical organoids go viral.

In this issue of Cell Stem Cell, Lõhmussaar et al. (2021) describe a versatile platform for generating long-term patient-derived organoids from hysterectomies and Pap brush cells. They establish malignant and benign cervix tissue organoids from both endo- and ectocervix that have applications ranging from precision medicine to infection modeling.

New Antimicrobials Targeting Bacterial RNA Polymerase Holoenzyme Assembly Identified with an in Vivo BRET-Based Discovery Platform.

Bacterial resistance represents a major health threat worldwide, and the development of new therapeutics, including innovative antibiotics, is urgently needed. We describe a discovery platform, centered on in silico screening and in vivo bioluminescence resonance energy transfer in yeast cells, for the identification of new antimicrobials that, by targeting the protein-protein interaction between the ß'-subunit and the initiation factor σ70 of bacterial RNA polymerase, inhibit holoenzyme assembly and promoter-specific transcription. Out of 34 000 candidate compounds, we identified seven hits capable of interfering with this interaction. Two derivatives of one of these hits proved to be effective in inhibiting transcription in vitro and growth of the Gram-positive pathogens Staphylococcus aureus and Listeria monocytogenes. Upon supplementation of a permeability adjuvant, one derivative also effectively inhibited Escherichia coli growth. On the basis of the chemical structures of these inhibitors, we generated a ligand-based pharmacophore model that will guide the rational discovery of increasingly effective antibacterial agents.

Screening for Protein-Protein Interaction Inhibitors Using a Bioluminescence Resonance Energy Transfer (BRET)-Based Assay in Yeast.

The bioluminescence resonance energy transfer (BRET) technology is a widely used live cell-based method for monitoring protein-protein interactions as well as conformational changes within proteins or molecular complexes. Considering the emergence of protein-protein interactions as a new promising class of therapeutic targets, we have adapted the BRET method in budding yeast. In this technical note, we describe the advantages of using this simple eukaryotic model rather than mammalian cells to perform high-throughput screening of chemical compound collections: genetic tractability, tolerance to solvent, rapidity, and no need of expensive robotic systems. Here, the HDM2/p53 interaction, related to cancer, is used to highlight the interest of this technology in yeast. Sharing the protocol of this BRET-based assay with the scientific community will extend its application to other protein-protein interactions, even though it is toxic for mammalian cells, in order to discover promising therapeutic candidates.

Dry and wet approaches for genome-wide functional annotation of conventional and unconventional transcriptional activators.

Transcription factors (TFs) are master gene products that regulate gene expression in response to a variety of stimuli. They interact with DNA in a sequence-specific manner using a variety of DNA-binding domain (DBD) modules. This allows to properly position their second domain, called "effector domain", to directly or indirectly recruit positively or negatively acting co-regulators including chromatin modifiers, thus modulating preinitiation complex formation as well as transcription elongation. At variance with the DBDs, which are comprised of well-defined and easily recognizable DNA binding motifs, effector domains are usually much less conserved and thus considerably more difficult to predict. Also not so easy to identify are the DNA-binding sites of TFs, especially on a genome-wide basis and in the case of overlapping binding regions. Another emerging issue, with many potential regulatory implications, is that of so-called "moonlighting" transcription factors, i.e., proteins with an annotated function unrelated to transcription and lacking any recognizable DBD or effector domain, that play a role in gene regulation as their second job. Starting from bioinformatic and experimental high-throughput tools for an unbiased, genome-wide identification and functional characterization of TFs (especially transcriptional activators), we describe both established (and usually well affordable) as well as newly developed platforms for DNA-binding site identification. Selected combinations of these search tools, some of which rely on next-generation sequencing approaches, allow delineating the entire repertoire of TFs and unconventional regulators encoded by the any sequenced genome.

Moonlighting transcriptional activation function of a fungal sulfur metabolism enzyme.

Moonlighting proteins, including metabolic enzymes acting as transcription factors (TF), are present in a variety of organisms but have not been described in higher fungi so far. In a previous genome-wide analysis of the TF repertoire of the plant-symbiotic fungus Tuber melanosporum, we identified various enzymes, including the sulfur-assimilation enzyme phosphoadenosine-phosphosulfate reductase (PAPS-red), as potential transcriptional activators. A functional analysis performed in the yeast Saccharomyces cerevisiae, now demonstrates that a specific variant of this enzyme, PAPS-red A, localizes to the nucleus and is capable of transcriptional activation. TF moonlighting, which is not present in the other enzyme variant (PAPS-red B) encoded by the T. melanosporum genome, relies on a transplantable C-terminal polypeptide containing an alternating hydrophobic/hydrophilic amino acid motif. A similar moonlighting activity was demonstrated for six additional proteins, suggesting that multitasking is a relatively frequent event. PAPS-red A is sulfur-state-responsive and highly expressed, especially in fruitbodies, and likely acts as a recruiter of transcription components involved in S-metabolism gene network activation. PAPS-red B, instead, is expressed at low levels and localizes to a highly methylated and silenced region of the genome, hinting at an evolutionary mechanism based on gene duplication, followed by epigenetic silencing of this non-moonlighting gene variant.