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Bromodomain testis (BRDT), a member of the bromodomain and extraterminal (BET) subfamily that includes the cancer targets BRD2, BRD3, and BRD4, is a validated contraceptive target. All BET subfamily members have two tandem bromodomains (BD1 and BD2). Knockout mice lacking BRDT-BD1 or both bromodomains are infertile. Treatment of mice with JQ1, a BET BD1/BD2 nonselective inhibitor with the highest affinity for BRD4, disrupts spermatogenesis and reduces sperm number and motility. To assess the contribution of each BRDT bromodomain, we screened our collection of DNA-encoded chemical libraries for BRDT-BD1 and BRDT-BD2 binders. High-enrichment hits were identified and resynthesized off-DNA and examined for their ability to compete with JQ1 in BRDT and BRD4 bromodomain AlphaScreen assays. These studies identified CDD-1102 as a selective BRDT-BD2 inhibitor with low nanomolar potency and >1,000-fold selectivity over BRDT-BD1. Structure-activity relationship studies of CDD-1102 produced a series of additional BRDT-BD2/BRD4-BD2 selective inhibitors, including CDD-1302, a truncated analog of CDD-1102 with similar activity, and CDD-1349, an analog with sixfold selectivity for BRDT-BD2 versus BRD4-BD2. BROMOscan bromodomain profiling confirmed the great affinity and selectivity of CDD-1102 and CDD-1302 on all BET BD2 versus BD1 with the highest affinity for BRDT-BD2. Cocrystals of BRDT-BD2 with CDD-1102 and CDD-1302 were determined at 2.27 and 1.90 Å resolution, respectively, and revealed BRDT-BD2 specific contacts that explain the high affinity and selectivity of these compounds. These BD2-specific compounds and their binding to BRDT-BD2 are unique compared with recent reports and enable further evaluation of their nonhormonal contraceptive potential in vitro and in vivo.

The paired measurement of RNA and surface proteins in single cells with cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is a promising approach to connect transcriptional variation with cell phenotypes and functions. However, combining these paired views into a unified representation of cell state is made challenging by the unique technical characteristics of each measurement. Here we present Total Variational Inference (totalVI; https://scvi-tools.org ), a framework for end-to-end joint analysis of CITE-seq data that probabilistically represents the data as a composite of biological and technical factors, including protein background and batch effects. To evaluate totalVI's performance, we profiled immune cells from murine spleen and lymph nodes with CITE-seq, measuring over 100 surface proteins. We demonstrate that totalVI provides a cohesive solution for common analysis tasks such as dimensionality reduction, the integration of datasets with different measured proteins, estimation of correlations between molecules and differential expression testing.

Organelles are responsible for biochemical and cellular processes that sustain life and their dysfunction causes diseases from cancer to neurodegeneration. While researchers are continuing to appreciate new roles of organelles in disease, the rapid development of specifically targeted fluorescent probes that report on the structure and function of organelles will be critical to accelerate drug discovery. Here, we highlight four organelles that collectively exemplify the progression of phenotypic discovery, starting with mitochondria, where many functional probes have been described, then continuing with lysosomes and Golgi and concluding with nascently described membraneless organelles. We introduce emerging probe designs to explore organelle-specific morphology and dynamics and highlight recent case studies using high-content analysis to stimulate further development of probes and approaches for organellar high-throughput screening.

Computational models based on recent maps of the RBC proteome suggest that mature erythrocytes may harbor targets for common drugs. This prediction is relevant to RBC storage in the blood bank, in which the impact of small molecule drugs or other xenometabolites deriving from dietary, iatrogenic, or environmental exposures ("exposome") may alter erythrocyte energy and redox metabolism and, in so doing, affect red cell storage quality and posttransfusion efficacy. To test this prediction, here we provide a comprehensive characterization of the blood donor exposome, including the detection of common prescription and over-the-counter drugs in blood units donated by 250 healthy volunteers in the Recipient Epidemiology and Donor Evaluation Study III Red Blood Cell-Omics (REDS-III RBC-Omics) Study. Based on high-throughput drug screenings of 1366 FDA-approved drugs, we report that approximately 65% of the tested drugs had an impact on erythrocyte metabolism. Machine learning models built using metabolites as predictors were able to accurately predict drugs for several drug classes/targets (bisphosphonates, anticholinergics, calcium channel blockers, adrenergics, proton pump inhibitors, antimetabolites, selective serotonin reuptake inhibitors, and mTOR), suggesting that these drugs have a direct, conserved, and substantial impact on erythrocyte metabolism. As a proof of principle, here we show that the antacid ranitidine - though rarely detected in the blood donor population - has a strong effect on RBC markers of storage quality in vitro. We thus show that supplementation of blood units stored in bags with ranitidine could - through mechanisms involving sphingosine 1-phosphate-dependent modulation of erythrocyte glycolysis and/or direct binding to hemoglobin - improve erythrocyte metabolism and storage quality.

Cutaneous T-cell lymphoma is a form of non-Hodgkin lymphoma that manifests initially in the skin and disseminates systemically as the disease progresses. Mycosis fungoides and Sézary syndrome are the most common subtypes of cutaneous T-cell lymphoma. Advanced mycosis fungoides and Sézary syndrome are life threatening with few treatment options. We searched for new agents by high-throughput screening of selected targeted compounds and identified high-value targets, including phosphatidylinositol 3-kinase (PI3K) and cyclin-dependent kinases. To validate these hits from the screen, we developed patient-derived xenograft mouse models that recapitulated the cardinal features of mycosis fungoides and Sézary syndrome and maintained histologic and molecular characteristics of their clinical counterparts. Importantly, we established a blood-based biomarker assay using tumor cell-free DNA to measure systemic tumor burden longitudinally in living mice during drug therapy. A PI3K inhibitor, BKM120, was tested in our patient-derived xenograft model leading to disease attenuation and prolonged survival. Isoform-specific small interfering RNA knockdowns and isoform-selective PI3K inhibitors identified PI3K-δ as required for tumor proliferation. Additional studies showed a synergistic combination of PI3K-α/δ inhibitors with histone deacetylase inhibitors. The strong preclinical efficacy of this potent combination against multiple patient-derived xenograft models makes it an excellent candidate for further clinical development.

BACKGROUND: Serology tests for detecting the antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can identify previous infection and help to confirm the presence of current infection. OBJECTIVE: The aim of this study was to evaluate the performances of a newly developed high throughput immunoassay for anti-SARS-CoV-2 IgG antibody detection. RESULTS: Clinical agreement studies were performed in 107 COVID-19 patient serum samples and 226 negative donor serum/plasma samples. Positive percent agreement (PPA) was 46.15 % (95 % CI: 19.22 % ∼74.87 %), 61.54 % (95 % CI: 31.58 % ∼86.14 %), and 97.53 % (95 % CI: 91.36 % ∼99.70 %) for samples collected on 0-7 days, 8-14 days, and ≥15 days from symptom onset, respectively. Negative Percent Agreement (NPA) was 98.23 % (95 % CI: 95.53 % ∼99.52 %). No cross-reactivity was observed to patient samples positive for IgG antibodies against the following pathogens: HIV, HAV, HBV, RSV, CMV, EBV, Rubella, Influenza A, and Influenza B. Hemoglobin (200 mg/dL), bilirubin (2 mg/dL) and EDTA (10 mM) showed no significant interfering effect on this assay. CONCLUSION: An anti-SARS-CoV-2 IgG antibody assay with high sensitivity and specificity has been developed. With the high throughput, this assay will speed up anti-SARS-CoV-2 IgG testing.

G protein-coupled receptors (GPCRs) are a group of seven-transmembrane receptor proteins that have proven to be successful drug targets. Antibodies are becoming an increasingly promising modality to target these receptors due to their unique properties, such as exquisite specificity, long half-life, and fewer side effects, and their improved pharmacokinetic and pharmacodynamic profiles compared to peptides and small molecules, which results from their more favorable biodistribution. To date, there are only two US Food and Drug Administration-approved GPCR antibody drugs, namely erenumab and mogamulizumab, and this highlights the challenges encountered in identifying functional antibodies against GPCRs. Utilizing Twists precision DNA writing technologies, we have created a GPCR-focused phage display library with 1 × 1010 diversity. Specifically, we mined endogenous GPCR binding ligand and peptide sequences and incorporated these binding motifs into the heavy chain complementarity-determining region 3 in a synthetic antibody library. Glucagon-like peptide-1 receptor (GLP-1 R) is a class B GPCR that acts as the receptor for the incretin GLP-1, which is released to regulate insulin levels in response to food intake. GLP-1 R agonists have been widely used to increase insulin secretion to lower blood glucose levels for the treatment of type 1 and type 2 diabetes, whereas GLP-1 R antagonists have applications in the treatment of severe hypoglycemia associated with bariatric surgery and hyperinsulinomic hypoglycemia. Here we present the discovery and creation of both antagonistic and agonistic GLP-1 R antibodies by panning this GPCR-focused phage display library on a GLP-1 R-overexpressing Chinese hamster ovary cell line and demonstrate their in vitro and in vivo functional activity.

Regulating protein production and degradation is critical to maintaining cellular homeostasis. The proteasome is a key player in keeping proteins at the proper levels. However, proteasome activity can be altered in certain disease states, such as blood cancers and neurodegenerative diseases. Cancers often exhibit enhanced proteasomal activity, as protein synthesis is increased in these cells compared with normal cells. Conversely, neurodegenerative diseases are characterized by protein accumulation, leading to reduced proteasome activity. As a result, the proteasome has emerged as a target for therapeutic intervention. The potential of the proteasome as a therapeutic target has come from studies involving chemical stimulators and inhibitors, and the development of a suite of assays and probes that can be used to monitor proteasome activity with purified enzyme and in live cells.

Microbial interactions are expected to be major determinants of microbiome structure and function. Although fungi are found in diverse microbiomes, their interactions with bacteria remain largely uncharacterized. In this work, we characterize interactions in 16 different bacterial-fungal pairs, examining the impacts of 8 different fungi isolated from cheese rind microbiomes on 2 bacteria (Escherichia coli and a cheese-isolated Pseudomonas psychrophila). Using random barcode transposon-site sequencing with an analysis pipeline that allows statistical comparisons between different conditions, we observed that fungal partners caused widespread changes in the fitness of bacterial mutants compared to growth alone. We found that all fungal species modulated the availability of iron and biotin to bacterial species, which suggests that these may be conserved drivers of bacterial-fungal interactions. Species-specific interactions were also uncovered, a subset of which suggested fungal antibiotic production. Changes in both conserved and species-specific interactions resulted from the deletion of a global regulator of fungal specialized metabolite production. This work highlights the potential for broad impacts of fungi on bacterial species within microbiomes.

Proteases are among the largest protein families and critical regulators of biochemical processes like apoptosis and blood coagulation. Knowledge of proteases has been expanded by the development of proteomic approaches, however, technology for multiplexed screening of proteases within native environments is currently lacking behind. Here we introduce a simple method to profile protease activity based on isolation of protease products from native lysates using a 96FASP filter, their analysis in a mass spectrometer and a custom data analysis pipeline. The method is significantly faster, cheaper, technically less demanding, easy to multiplex and produces accurate protease fingerprints. Using the blood cascade proteases as a case study, we obtain protease substrate profiles that can be used to map specificity, cleavage entropy and allosteric effects and to design protease probes. The data further show that protease substrate predictions enable the selection of potential physiological substrates for targeted validation in biochemical assays.

Protein kinases control nearly every facet of cellular function. These key signaling nodes integrate diverse pathway inputs to regulate complex physiological processes, and aberrant kinase signaling is linked to numerous pathologies. While fluorescent protein-based biosensors have revolutionized the study of kinase signaling by allowing direct, spatiotemporally precise kinase activity measurements in living cells, powerful new molecular tools capable of robustly tracking kinase activity dynamics across diverse experimental contexts are needed to fully dissect the role of kinase signaling in physiology and disease. Here, we report the development of an ultrasensitive, second-generation excitation-ratiometric protein kinase A (PKA) activity reporter (ExRai-AKAR2), obtained via high-throughput linker library screening, that enables sensitive and rapid monitoring of live-cell PKA activity across multiple fluorescence detection modalities, including plate reading, cell sorting and one- or two-photon imaging. Notably, in vivo visual cortex imaging in awake mice reveals highly dynamic neuronal PKA activity rapidly recruited by forced locomotion.

Droplet libraries consisting of many reagents encapsulated in separate droplets are necessary for applications of microfluidics, including combinatorial chemical synthesis, DNA-encoded libraries, and massively multiplexed PCR. However, existing approaches for generating them are laborious and impractical. Here, we describe an automated approach using a commercial array spotter. The approach can controllably emulsify hundreds of different reagents in a fraction of the time of manual operation of a microfluidic device, and without any user intervention. We demonstrate that the droplets produced by the spotter are similarly uniform to those produced by microfluidics and automate the generation of a ~ 2 mL emulsion containing 192 different reagents in ~ 4 h. The ease with which it can generate high diversity droplet libraries should make combinatorial applications more feasible in droplet microfluidics. Moreover, the instrument serves as an automated droplet generator, allowing execution of droplet reactions without microfluidic expertise.

Drug-induced liver injury is an important cause of non-approval in drug development and the withdrawal of already approved drugs from the market. Screening human hepatic cell lines for toxicity has been used extensively to predict drug-induced liver injury in preclinical drug development. Assessing hepatic-cell health with more diverse markers will increase the value of in vitro assays and help predict the mechanism of toxicity. We describe three live cell-based assays using HepG2 cells to measure cell health parameters indicative of hepatotoxicity. The first assay measures cellular ATP levels using luciferase. The second and third assays are multiparametric high-content screens covering a panel of cell health markers including cell count, mitochondrial membrane potential and structure, nuclear morphology, vacuolar density, and reactive oxygen species and glutathione levels. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Measurement of cellular ATP content Basic Protocol 2: High-content analysis assay to assess cell count, mitochondrial membrane potential and structure, and reactive oxygen species Basic Protocol 3: High-content analysis assay to assess nuclear morphology, vacuoles, and glutathione content Support Protocol 1: Subculturing and maintaining HepG2 cells Support Protocol 2: Plating HepG2 cell line Support Protocol 3: Transferring compounds by pin tool Support Protocol 4: Generating dose-response curves.

Medulloblastoma is among the most common malignant brain tumors in children. Recent studies have identified at least four subgroups of the disease that differ in terms of molecular characteristics and patient outcomes. Despite this heterogeneity, most patients with medulloblastoma receive similar therapies, including surgery, radiation, and intensive chemotherapy. Although these treatments prolong survival, many patients still die from the disease and survivors suffer severe long-term side effects from therapy. We hypothesize that each patient with medulloblastoma is sensitive to different therapies and that tailoring therapy based on the molecular and cellular characteristics of patients' tumors will improve outcomes. To test this, we assembled a panel of orthotopic patient-derived xenografts (PDX) and subjected them to DNA sequencing, gene expression profiling, and high-throughput drug screening. Analysis of DNA sequencing revealed that most medulloblastomas do not have actionable mutations that point to effective therapies. In contrast, gene expression and drug response data provided valuable information about potential therapies for every tumor. For example, drug screening demonstrated that actinomycin D, which is used for treatment of sarcoma but rarely for medulloblastoma, was active against PDXs representing Group 3 medulloblastoma, the most aggressive form of the disease. Functional analysis of tumor cells was successfully used in a clinical setting to identify more treatment options than sequencing alone. These studies suggest that it should be possible to move away from a one-size-fits-all approach and begin to treat each patient with therapies that are effective against their specific tumor. SIGNIFICANCE: These findings show that high-throughput drug screening identifies therapies for medulloblastoma that cannot be predicted by genomic or transcriptomic analysis.

Generating mammalian cells with desired mitochondrial DNA (mtDNA) sequences is enabling for studies of mitochondria, disease modeling, and potential regenerative therapies. MitoPunch, a high-throughput mitochondrial transfer device, produces cells with specific mtDNA-nuclear DNA (nDNA) combinations by transferring isolated mitochondria from mouse or human cells into primary or immortal mtDNA-deficient (ρ0) cells. Stable isolated mitochondrial recipient (SIMR) cells isolated in restrictive media permanently retain donor mtDNA and reacquire respiration. However, SIMR fibroblasts maintain a ρ0-like cell metabolome and transcriptome despite growth in restrictive media. We reprogrammed non-immortal SIMR fibroblasts into induced pluripotent stem cells (iPSCs) with subsequent differentiation into diverse functional cell types, including mesenchymal stem cells (MSCs), adipocytes, osteoblasts, and chondrocytes. Remarkably, after reprogramming and differentiation, SIMR fibroblasts molecularly and phenotypically resemble unmanipulated control fibroblasts carried through the same protocol. Thus, our MitoPunch "pipeline" enables the production of SIMR cells with unique mtDNA-nDNA combinations for additional studies and applications in multiple cell types.

Macrophages are critical effector cells of the immune system, and understanding genes involved in their viability and function is essential for gaining insights into immune system dysregulation during disease. We use a high-throughput, pooled-based CRISPR-Cas screening approach to identify essential genes required for macrophage viability. In addition, we target 3' UTRs to gain insights into previously unidentified cis-regulatory regions that control these essential genes. Next, using our recently generated nuclear factor κB (NF-κB) reporter line, we perform a fluorescence-activated cell sorting (FACS)-based high-throughput genetic screen and discover a number of previously unidentified positive and negative regulators of the NF-κB pathway. We unravel complexities of the TNF signaling cascade, showing that it can function in an autocrine manner in macrophages to negatively regulate the pathway. Utilizing a single complex library design, we are capable of interrogating various aspects of macrophage biology, thus generating a resource for future studies.

BackgroundDuchenne muscular dystrophy (DMD) is a degenerative muscle disease caused by mutations in the dystrophin gene. Loss of dystrophin prevents the formation of a critical connection between the muscle cell membrane and the extracellular matrix. Overexpression of sarcospan (SSPN) in the mouse model of DMD restores the membrane connection and reduces disease severity, making SSPN a promising therapeutic target for pharmacological upregulation.MethodsUsing a previously described cell-based promoter reporter assay of SSPN gene expression (hSSPN-EGFP), we conducted high-throughput screening on libraries of over 200,000 curated small molecules to identify SSPN modulators. The hits were validated in both hSSPN-EGFP and hSSPN-luciferase reporter cells. Hit selection was conducted on dystrophin-deficient mouse and human myotubes with assessments of (1) SSPN gene expression using quantitative PCR and (2) SSPN protein expression using immunoblotting and an ELISA. A membrane stability assay using osmotic shock was used to validate the functional effects of treatment followed by cell surface biotinylation to label cell surface proteins. Dystrophin-deficient mdx mice were treated with compound, and muscle was subjected to quantitative PCR to assess SSPN gene expression.ResultsWe identified and validated lead compounds that increased SSPN gene and protein expression in dystrophin-deficient mouse and human muscle cells. The lead compound OT-9 increased cell membrane localization of compensatory laminin-binding adhesion complexes and improved membrane stability in DMD myotubes. We demonstrated that the membrane stabilizing benefit is dependent on SSPN. Intramuscular injection of OT-9 in the mouse model of DMD increased SSPN gene expression.ConclusionsThis study identifies a pharmacological approach to treat DMD and sets the path for the development of SSPN-based therapies.

Intratumoral heterogeneity is a common feature of many myeloid leukemias and a significant reason for treatment failure and relapse. Thus, identifying the cells responsible for residual disease and leukemia re-growth is critical to better understanding how they are regulated. Here, we show that a knock-in reporter mouse for the stem cell gene Musashi 2 (Msi2) allows identification of leukemia stem cells in aggressive myeloid malignancies, and provides a strategy for defining their core dependencies. Specifically, we carry out a high throughput screen using Msi2-reporter blast crisis chronic myeloid leukemia (bcCML) and identify several adhesion molecules that are preferentially expressed in therapy resistant bcCML cells and play a key role in bcCML. In particular, we focus on syndecan-1, whose deletion triggers defects in bcCML growth and propagation and markedly improves survival of transplanted mice. Further, live imaging reveals that the spatiotemporal dynamics of leukemia cells are critically dependent on syndecan signaling, as loss of this signal impairs their localization, migration and dissemination to distant sites. Finally, at a molecular level, syndecan loss directly impairs integrin β7 function, suggesting that syndecan exerts its influence, at least in part, by coordinating integrin activity in bcCML. These data present a platform for delineating the biological underpinnings of leukemia stem cell function, and highlight the Sdc1-Itgβ7 signaling axis as a key regulatory control point for bcCML growth and dissemination.

Clinical features of Kawasaki disease (KD) display overlap with common pediatric viral illnesses, leading some to hypothesize that a viral infection is the inciting event for KD. To investigate viral infection history in KD patients, we performed comprehensive serological profiling using a high-throughput phage immunoprecipitation sequencing assay covering the complete reference protein sequences of known viruses with human tropism. KD and matched febrile control sera did not demonstrate differences in antiviral antibody profiles. We conclude that in the acute and subacute phases of disease, KD patients do not exhibit serologic evidence of exposure to known viruses that differs from controls.

Emulsions offer the means to miniaturize and parallelize high-throughput screening but require a robust method to localize activity-based fluorescent probes in each droplet. Multiplexing probes in droplets is impractical, though highly desirable for identifying library members that possess very specific activity. Here, we present multiplexed probe immobilization on library beads for emulsion screening. During library bead preparation, we quantitated ∼106 primers per bead by fluorescence in situ hybridization, however emulsion PCR yielded only ∼103 gene copies per bead. We leveraged the unextended bead-bound primers to hybridize complementary probe-oligonucleotide heteroconjugates to the library beads. The probe-hybridized bead libraries were then used to program emulsion in vitro transcription/translation reactions and analyzed by FACS to perform multiplexed activity-based screening of trypsin and chymotrypsin mutant libraries for novel proteolytic specificity. The approach's modularity should permit a high degree of probe multiplexing and appears extensible to other enzyme classes and library types.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread around the world, there is an urgent need for new assay formats to characterize the humoral response to infection. Here, we present an efficient, competitive serological assay that can simultaneously determine an individual's seroreactivity against the SARS-CoV-2 Spike protein and determine the proportion of anti-Spike antibodies that block interaction with the human angiotensin-converting enzyme 2 (ACE2) required for viral entry. In this approach based on the use of enzyme-linked immunosorbent assays (ELISA), we present natively folded viral Spike protein receptor-binding domain (RBD)-containing antigens via avidin-biotin interactions. Sera are then competed with soluble ACE2-Fc, or with a higher-affinity variant thereof, to determine the proportion of ACE2 blocking anti-RBD antibodies. Assessment of sera from 144 SARS-CoV-2 patients ultimately revealed that a remarkably consistent and high proportion of antibodies in the anti-RBD pool targeted the epitope responsible for ACE2 engagement (83% ± 11%; 50% to 107% signal inhibition in our largest cohort), further underscoring the importance of tailoring vaccines to promote the development of such antibodies.IMPORTANCE With the emergence and continued spread of the SARS-CoV-2 virus, and of the associated disease, coronavirus disease 2019 (COVID-19), there is an urgent need for improved understanding of how the body mounts an immune response to the virus. Here, we developed a competitive SARS-CoV-2 serological assay that can simultaneously determine whether an individual has developed antibodies against the SARS-CoV-2 Spike protein receptor-binding domain (RBD) and measure the proportion of these antibodies that block interaction with the human angiotensin-converting enzyme 2 (ACE2) required for viral entry. Using this assay and 144 SARS-CoV-2 patient serum samples, we found that a majority of anti-RBD antibodies compete for ACE2 binding. These results not only highlight the need to design vaccines to generate such blocking antibodies but also demonstrate the utility of this assay to rapidly screen patient sera for potentially neutralizing antibodies.

Sphingolipids constitute a heterogeneous lipid category that is involved in many key cellular functions. For high-throughput analyses of sphingolipids, tandem mass spectrometry (MS/MS) is the method of choice, offering sufficient sensitivity, structural information, and quantitative precision for detecting hundreds to thousands of species simultaneously. While glycerolipids and phospholipids are predominantly non-hydroxylated, sphingolipids are typically dihydroxylated. However, species containing one or three hydroxylation sites can be detected frequently. This variability in the number of hydroxylation sites on the sphingolipid long-chain base and the fatty acyl moiety produces many more isobaric species and fragments than for other lipid categories. Due to this complexity, the automated annotation of sphingolipid species is challenging, and incorrect annotations are common. In this study, we present an extension of the Lipid Data Analyzer (LDA) "decision rule set" concept that considers the structural characteristics that are specific for this lipid category. To address the challenges inherent to automated annotation of sphingolipid structures from MS/MS data, we first developed decision rule sets using spectra from authentic standards and then tested the applicability on biological samples including murine brain and human plasma. A benchmark test based on the murine brain samples revealed a highly improved annotation quality as measured by sensitivity and reliability. The results of this benchmark test combined with the easy extensibility of the software to other (sphingo)lipid classes and the capability to detect and correctly annotate novel sphingolipid species make LDA broadly applicable to automated sphingolipid analysis, especially in high-throughput settings.

Patients with pancreatic adenocarcinoma (PDAC) have a 5-year survival rate of 8%, the lowest of any cancer in the United States. Traditional chemotherapeutic regimens, such as gemcitabine- and fluorouracil-based regimens, often only prolong survival by months. Effective precision targeted therapy is therefore urgently needed to substantially improve survival. In an effort to expedite approval and delivery of targeted therapy to patients, we utilized a platform to develop a novel combination of FDA approved drugs that would target pancreaticoduodenal homeobox1 (PDX1) and baculoviral inhibitor of apoptosis repeat-containing 5 (BIRC5) utilizing super-promoters of the target genes to interrogate an FDA approved drug library. We identified and selected metformin, simvastatin and digoxin (C3) as a novel combination of FDA approved drugs, which were shown to effectively target PDX1 and BIRC5 in human PDAC tumors in mice with no toxicity.

Strategies to increase energy expenditure are an attractive approach to reduce excess fat storage and body weight to improve metabolic health. In mammals, uncoupling protein-1 (UCP1) in brown and beige adipocytes uncouples fatty acid oxidation from ATP generation in mitochondria and promotes energy dissipation as heat. We set out to identify small molecules that enhance UCP1 levels and activity using a high-throughput screen of nearly 12,000 compounds in mouse brown adipocytes. We identified a family of compounds that increase Ucp1 expression and mitochondrial activity (including un-coupled respiration) in mouse brown adipocytes and human brown and white adipocytes. The mechanism of action may be through compound binding to A kinase anchoring protein (AKAP) 1, modulating its localization to mitochondria and its interaction with protein kinase A (PKA), a known node in the β-adrenergic signaling pathway. In mice, the hit compound increased body temperature, UCP1 protein levels, and thermogenic gene expression. Some of the compound effects on mitochondrial function were UCP1- or AKAP1-independent, suggesting compound effects on multiple nodes of energy regulation. Overall, our results highlight a role for AKAP1 in thermogenesis, uncoupled respiration, and regulation energy balance.

The generation of reliable mAb of unique and desired specificities serves as a valuable technology to study protein expression and function. However, standard approaches to mAb generation usually involve large-scale protein purification and intensive screening. In this study, we describe an optimized high-throughput proof-of-principle method for the expanded generation, enrichment, and screening of mouse hybridomas secreting mAb specific for a protein of interest. Briefly, we demonstrate that small amounts of a biotinylated protein of interest can be used to generate tetramers for use as prime-boost immunogens, followed by selective enrichment of Ag-specific B cells by magnetic sorting using the same tetramers prior to hybridoma generation. This serves two purposes: 1) to effectively expand both low- and high-affinity B cells specific for the antigenic bait during immunization and 2) to minimize subsequent laborious hybridoma efforts by positive selection of Ag-specific, Ab-secreting cells prior to hybridoma fusion and validation screening. Finally, we employ a rapid and inexpensive screening technology, CELLISA, a high-throughput validation method that uses a chimeric Ag fused to the CD3ζ signaling domain expressed on enzyme-generating reporter cells; these reporters can detect specific mAb in hybridoma supernatants via plate-bound Ab-capture arrays, thereby easing screening. Using this strategy, we generated and characterized novel mouse mAb specific for a viral immunoevasin, the mouse CMV m12 protein, and suggest that these mAb may protect mice from CMV infection via passive immunity.

Tumor organoids are promising tools for cancer biology investigations and preclinical drug screenings because they are often representative of the histology and drug responses of patients. Here, we introduce a facile protocol to overcome technical limitations by generating patient-derived tumor organoids using a simplified ring-like geometry. This facilitates media exchange and drug treatment for histopathology characterization and automated high-throughput drug screenings. For complete details on the use and execution of this protocol, please refer to Phan et al. (2019).

Understanding metabolism is indispensable in unraveling the mechanistic basis of many physiological and pathological processes. However, in situ metabolic imaging tools are still lacking. Here we introduce a framework for mid-infrared (MIR) metabolic imaging by coupling the emerging high-information-throughput MIR microscopy with specifically designed IR-active vibrational probes. We present three categories of small vibrational tags including azide bond, 13C-edited carbonyl bond and deuterium-labeled probes to interrogate various metabolic activities in cells, small organisms and mice. Two MIR imaging platforms are implemented including broadband Fourier transform infrared microscopy and discrete frequency infrared microscopy with a newly incorporated spectral region (2,000-2,300 cm-1). Our technique is uniquely suited to metabolic imaging with high information throughput. In particular, we performed single-cell metabolic profiling including heterogeneity characterization, and large-area metabolic imaging at tissue or organ level with rich spectral information.

Diverse assays spanning from immunohistochemistry (IHC), to microarrays (protein, DNA), to high-throughput screens rely on probe-target hybridization to detect analytes. These large-format 'chips' array numerous hybridization sites across centimeter-scale areas. However, the reactions are prone to intra-assay spatial variation in hybridization efficiency. The mechanism of spatial bias in hybridization efficiency is poorly understood, particularly in IHC and in-gel immunoassays, where immobilized targets are heterogeneously distributed throughout a tissue or hydrogel network. In these systems, antibody probe hybridization to a target protein antigen depends on the interplay of dilution, thermodynamic partitioning, diffusion, and reaction. Here, we investigate parameters governing antibody probe transport and reaction (i.e., immunoprobing) in a large-format hydrogel immunoassay. Using transport and bimolecular binding theory, we identify a regime in which immunoprobing efficiency (η) is sensitive to the local concentration of applied antibody probe solution, despite the antibody probe being in excess compared to antigen. Sandwiching antibody probe solution against the hydrogel surface yields spatially nonuniform dilution. Using photopatterned fluorescent protein targets and a single-cell immunoassay, we identify regimes in which nonuniformly distributed antibody probe solution causes intra-assay variation in background and η. Understanding the physicochemical factors affecting probe-target hybridization reduces technical variation in large-format chips, improving measurement precision.

Sortase enzymes are attractive antivirulence drug targets that attach virulence factors to the surface of Staphylococcus aureus and other medically significant bacterial pathogens. Prior efforts to discover a useful sortase inhibitor have relied upon an in vitro activity assay in which the enzyme is removed from its native site on the bacterial surface and truncated to improve solubility. To discover inhibitors that are effective in inactivating sortases in vivo, we developed and implemented a novel cell-based screen using Actinomyces oris, a key colonizer in the development of oral biofilms. A. oris is unique because it exhibits sortase-dependent growth in cell culture, providing a robust phenotype for high throughput screening (HTS). Three molecules representing two unique scaffolds were discovered by HTS and disrupt surface protein display in intact cells and inhibit enzyme activity in vitro. This represents the first HTS for sortase inhibitors that relies on the simple metric of cellular growth and suggests that A. oris may be a useful platform for discovery efforts targeting sortase.

Small GTPases are essential signaling molecules for regulating glucose uptake in adipose tissues upon insulin stimulation, and this regulation maintains an appropriate range of glycemia. The involvement of small GTPases in adipogenesis, however, has not been systemically investigated. In this study, we applied a high-throughput scheduled multiple-reaction monitoring (MRM) method, along with the use of synthetic stable isotope-labeled peptides, to identify differentially expressed small GTPase proteins during adipogenesis of cultured murine cells. We were able to quantify the relative levels of expression of 55 and 49 small GTPases accompanied by adipogenic differentiation in 3T3-L1 and C3H10T1/2 cells, respectively. When compared with analysis conducted in the data-dependent acquisition (DDA) mode, the MRM-based proteomic platform substantially increased the coverage of the small GTPase proteome. Western blot analysis further corroborated the MRM quantification results for selected small GTPases. Interestingly, overall a significant number of small GTPases were down-regulated during adipogenesis. Among them, the expression levels of Rab32 protein were consistently lower in differentiated adipocytes than the corresponding undifferentiated precursors in both cell lines. Overexpression of Rab32 in 3T3-L1 and C3H10T1/2 cells prior to adipogenesis induction suppressed their differentiation. Together, this is the first comprehensive analysis of the alterations in small GTPase proteome during adipogenesis, and we reveal a previously unrecognized role of Rab32 in adipogenic differentiation.

Oxidative stress is a central part of innate immune-induced neurodegeneration. However, the transcriptomic landscape of central nervous system (CNS) innate immune cells contributing to oxidative stress is unknown, and therapies to target their neurotoxic functions are not widely available. Here, we provide the oxidative stress innate immune cell atlas in neuroinflammatory disease and report the discovery of new druggable pathways. Transcriptional profiling of oxidative stress-producing CNS innate immune cells identified a core oxidative stress gene signature coupled to coagulation and glutathione-pathway genes shared between a microglia cluster and infiltrating macrophages. Tox-seq followed by a microglia high-throughput screen and oxidative stress gene network analysis identified the glutathione-regulating compound acivicin, with potent therapeutic effects that decrease oxidative stress and axonal damage in chronic and relapsing multiple sclerosis models. Thus, oxidative stress transcriptomics identified neurotoxic CNS innate immune populations and may enable discovery of selective neuroprotective strategies.

Phospholipase A2 (PLA2) enzymes play a major role in many diseases including the inflammatory cascade and specific potent small molecule inhibitors could be useful in studying their physiological role as well as for the development of drugs. In order to discover novel small molecule inhibitor platforms for members of the PLA2 superfamily of enzymes, we have applied computational approaches to determine the binding mode of potent inhibitors specific for particular PLA2s to the screening of chemical libraries. This has including the U.S. National Institutes of Health (NIH) National Cancer Institute (NCI) Diversity Set V and the ChemBridge commercial compound libraries. We have then subjected identified inhibitor structures to recently developed lipidomics based screening assays to determine the XI(50) and specificity of the identified compounds for specific PLA2s. Herein we review this approach and report the identity of initial hits for both the Group IVA cytosolic PLA2 and the Group VIA calcium-independent PLA2 that are worthy of further structural modification to develop novel platforms for inhibitor development.

Establishing causal links between non-coding variants and human phenotypes is an increasing challenge. Here, we introduce a high-throughput mouse reporter assay for assessing the pathogenic potential of human enhancer variants in vivo and examine nearly a thousand variants in an enhancer repeatedly linked to polydactyly. We show that 71% of all rare non-coding variants previously proposed as causal lead to reporter gene expression in a pattern consistent with their pathogenic role. Variants observed to alter enhancer activity were further confirmed to cause polydactyly in knockin mice. We also used combinatorial and single-nucleotide mutagenesis to evaluate the in vivo impact of mutations affecting all positions of the enhancer and identified additional functional substitutions, including potentially pathogenic variants hitherto not observed in humans. Our results uncover the functional consequences of hundreds of mutations in a phenotype-associated enhancer and establish a widely applicable strategy for systematic in vivo evaluation of human enhancer variants.

Complex, time-varying responses have been observed widely in cell signaling, but how specific dynamics are generated or regulated is largely unknown. One major obstacle has been that high-throughput screens are typically incompatible with the live-cell assays used to monitor dynamics. Here, we address this challenge by screening a library of 429 kinase inhibitors and monitoring extracellular-regulated kinase (Erk) activity over 5 h in more than 80,000 single primary mouse keratinocytes. Our screen reveals both known and uncharacterized modulators of Erk dynamics, including inhibitors of non-epidermal growth factor receptor (EGFR) receptor tyrosine kinases (RTKs) that increase Erk pulse frequency and overall activity. Using drug treatment and direct optogenetic control, we demonstrate that drug-induced changes to Erk dynamics alter the conditions under which cells proliferate. Our work opens the door to high-throughput screens using live-cell biosensors and reveals that cell proliferation integrates information from Erk dynamics as well as additional permissive cues.

Abstract As agricultural production is reaching its limits regarding outputs and land use, the need to further improve crop yield is greater than ever. The limited translatability from in vitro lab results into more natural growth conditions in soil remains problematic. Although considerable progress has been made in developing soil‐growth assays to tackle this bottleneck, the majority of these assays use pots or whole trays, making them not only space‐ and resource‐intensive, but also hampering the individual treatment of plants. Therefore, we developed a flexible and compact screening system named PhenoWell® in which individual seedlings are grown in wells filled with soil allowing single‐plant treatments. The system makes use of an automated image‐analysis pipeline that extracts multiple growth parameters from individual seedlings over time, including projected rosette area, relative growth rate, compactness, and stockiness. Macronutrient, hormone, salt, osmotic, and drought stress treatments were tested in the PhenoWell® system. The system is also optimized for maize with results that are consistent with Arabidopsis while different in amplitude. We conclude that the PhenoWell® system enables a high‐throughput, precise, and uniform application of a small amount of solution to individually soil‐grown plants, which increases the replicability and reduces variability and compound usage.

Which neural circuits undergo synaptic changes when an animal learns? Although it is widely accepted that changes in synaptic strength underlie many forms of learning and memory, it remains challenging to connect changes in synaptic strength at specific neural pathways to specific behaviors and memories. Here we introduce SYNPLA (synaptic proximity ligation assay), a synapse-specific, high-throughput, and potentially brain-wide method capable of detecting circuit-specific learning-induced synaptic plasticity.

Epistasis emerges when the effects of an amino acid depend on the identities of interacting residues. This phenomenon shapes fitness landscapes, which have the power to reveal evolutionary paths and inform evolution of desired functions. However, there is a need for easily implemented, high-throughput methods to capture epistasis particularly at distal sites. Here, we combine deep mutational scanning (DMS) with a straightforward data processing step to bridge reads in distal sites within genes (BRIDGE). We use BRIDGE, which matches non-overlapping reads to their cognate templates, to uncover prevalent epistasis within the binding pocket of a human G protein-coupled receptor (GPCR) yielding variants with 4-fold greater affinity to a target ligand. The greatest functional improvements in our screen result from distal substitutions and substitutions that are deleterious alone. Our results corroborate findings of mutational tolerance in GPCRs, even in conserved motifs, but reveal inherent constraints restricting tolerated substitutions due to epistasis.

Mechanisms underpinning airway epithelial homeostatic maintenance and ways to prevent its dysregulation remain elusive. Herein, we identify that β-catenin phosphorylated at Y489 (p-β-cateninY489) emerges during human squamous lung cancer progression. This led us to develop a model of airway basal stem cell (ABSC) hyperproliferation by driving Wnt/β-catenin signaling, resulting in a morphology that resembles premalignant lesions and loss of ciliated cell differentiation. To identify small molecules that could reverse this process, we performed a high-throughput drug screen for inhibitors of Wnt/β-catenin signaling. Our studies unveil Wnt inhibitor compound 1 (WIC1), which suppresses T-cell factor/lymphoid enhancer-binding factor (TCF/LEF) activity, reduces ABSC proliferation, induces ciliated cell differentiation, and decreases nuclear p-β-cateninY489. Collectively, our work elucidates a dysregulated Wnt/p-β-cateninY489 axis in lung premalignancy that can be modeled in vitro and identifies a Wnt/β-catenin inhibitor that promotes airway homeostasis. WIC1 may therefore serve as a tool compound in regenerative medicine studies with implications for restoring normal airway homeostasis after injury.

Like cervical cancer, anal cancer is caused by human papillomavirus (HPV). HPV is the most common sexually transmitted agent and is found in the anal canal of almost all HIV-positive men who have sex with men (MSM). Rates of HPV anal cancer are disproportionately higher in this population. Although the nanovalent HPV vaccine is efficacious in protecting against oncogenic HPV types, a substantial proportion of MSM remains unvaccinated and anal HPV infection continues to be an important public health burden. Therefore, it is important to identify strategies to prevent HPV infection. We report on two promising and interlinked strategies: (1) the development of a cell-based Renilla luminescence reporter assay using HPV-16 pseudovirions that encapsidate SV40-driven Renilla luminescence reporter expression plasmid and (2) use of this assay for high-throughput screening (HTS) of FDA- and internationally approved drugs to identify those that could be repurposed to prevent HPV infection. We conducted a screen of 1906 drugs. The assay was valid with a Z' of 0.67 ± 0.04, percent coefficient of variance of 10.0, and signal-to-background noise window of 424.0 ± 8.0. Five drugs were chosen for further analyses based on selection parameters of ≥77.0% infection of HPV-16 pseudovirion-driven Renilla expression with

Organoids are in vitro three-dimensional (3D) multicellular cultures that are generated through deploying the self-renewal and self-organizing capacities of stem cells. They recapitulate key structural and functional features of corresponding organs or tissues, providing an ideal in vitro model and research platform for the study of developmental biology, regenerative medicine, disease modeling and drug development. The conventional organoid culture system mainly relies on manual operations with lengthy and complicated procedures, which generate organoid cultures of individual variations and batch differences, limiting their translational applications. Therefore, to engineer the organoid culture system by introducing microfluidic chip technology to enhance the throughput and automation level, is of great significance for achieving large-scale, homogeneous, and standardized organoid cultures. This article reviews the current research progress of high-throughput and automated organoid chips and discusses the main limitations and potential challenges for the future study. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus strains have been continuously evolving resistance to numerous classes of antibiotics including methicillin, vancomycin, daptomycin and linezolid, compounding the enormous healthcare and economic burden of the pathogen. Cation-adjusted Mueller-Hinton broth (CA-MHB) is the standard bacteriological media for measuring antibiotic susceptibility in the clinical lab, but the use of media that more closely mimic the physiological state of the patient, e.g. mammalian tissue culture media, can in certain circumstances reveal antibiotic activities that may be more predictive of effectiveness in vivo. In the current study, we use both types of media to explore antibiotic resistance phenomena in hospital-acquired USA100 lineage methicillin-resistant, vancomycin-intermediate Staphylococcus aureus (MRSA/VISA) strain D712 via multidimensional high throughput analysis of growth rates, bacterial cytological profiling, RNA sequencing, and exo-metabolomics (HPLC and LC-MS). Here, we share data generated from these assays to shed light on the antibiotic resistance behavior of MRSA/VISA D712 in both bacteriological and physiological media.

BACKGROUND:Duchenne muscular dystrophy (DMD) is caused by loss of sarcolemma connection to the extracellular matrix. Transgenic overexpression of the transmembrane protein sarcospan (SSPN) in the DMD mdx mouse model significantly reduces disease pathology by restoring membrane adhesion. Identifying SSPN-based therapies has the potential to benefit patients with DMD and other forms of muscular dystrophies caused by deficits in muscle cell adhesion. METHODS:Standard cloning methods were used to generate C2C12 myoblasts stably transfected with a fluorescence reporter for human SSPN promoter activity. Assay development and screening were performed in a core facility using liquid handlers and imaging systems specialized for use with a 384-well microplate format. Drug-treated cells were analyzed for target gene expression using quantitative PCR and target protein expression using immunoblotting. RESULTS:We investigated the gene expression profiles of SSPN and its associated proteins during myoblast differentiation into myotubes, revealing an increase in expression after 3 days of differentiation. We created C2C12 muscle cells expressing an EGFP reporter for SSPN promoter activity and observed a comparable increase in reporter levels during differentiation. Assay conditions for high-throughput screening were optimized for a 384-well microplate format and a high-content imager for the visualization of reporter levels. We conducted a screen of 3200 compounds and identified seven hits, which include an overrepresentation of L-type calcium channel antagonists, suggesting that SSPN gene activity is sensitive to calcium. Further validation of a select hit revealed that the calcium channel inhibitor felodipine increased SSPN transcript and protein levels in both wild-type and dystrophin-deficient myotubes, without increasing differentiation. CONCLUSIONS:We developed a stable muscle cell line containing the promoter region of the human SSPN protein fused to a fluorescent reporter. Using the reporter cells, we created and validated a scalable, cell-based assay that is able to identify compounds that increase SSPN promoter reporter, transcript, and protein levels in wild-type and dystrophin-deficient muscle cells.

PurposeCombined MAPK pathway inhibition using dual BRAF and MEK inhibitors has prolonged the duration of clinical response in patients with BRAFV600E-driven tumors compared with either agent alone. However, resistance frequently arises.Experimental designWe generated cell lines resistant to dual BRAF/MEK inhibition and utilized a pharmacologic synthetic lethal approach to identify a novel, adaptive resistance mechanism mediated through the fibroblast growth factor receptor (FGFR) pathway.ResultsIn response to drug treatment, transcriptional upregulation of FGF1 results in autocrine activation of FGFR, which potentiates extracellular signal-regulated kinases (ERK) activation. FGFR inhibition overcomes resistance to dual BRAF/MEK inhibitors in both cell lines and patient-derived xenograft (PDX) models. Abrogation of this bypass mechanism in the first-line setting enhances tumor killing and prevents the emergence of drug-resistant cells. Moreover, clinical data implicate serum FGF1 levels in disease prognosis.ConclusionsTaken together, these results describe a new, adaptive resistance mechanism that is more commonly observed in the context of dual BRAF/MEK blockade as opposed to single-agent treatment and reveal the potential clinical utility of FGFR-targeting agents in combination with BRAF and MEK inhibitors as a promising strategy to forestall resistance in a subset of BRAF-driven cancers.

BackgroundThere is great interest in and excitement about the concept of personalized or precision medicine and, in particular, advancing this vision via various 'big data' efforts. While these methods are necessary, they are insufficient to achieve the full personalized medicine promise. A rigorous, complementary 'small data' paradigm that can function both autonomously from and in collaboration with big data is also needed. By 'small data' we build on Estrin's formulation and refer to the rigorous use of data by and for a specific N-of-1 unit (i.e., a single person, clinic, hospital, healthcare system, community, city, etc.) to facilitate improved individual-level description, prediction and, ultimately, control for that specific unit.Main bodyThe purpose of this piece is to articulate why a small data paradigm is needed and is valuable in itself, and to provide initial directions for future work that can advance study designs and data analytic techniques for a small data approach to precision health. Scientifically, the central value of a small data approach is that it can uniquely manage complex, dynamic, multi-causal, idiosyncratically manifesting phenomena, such as chronic diseases, in comparison to big data. Beyond this, a small data approach better aligns the goals of science and practice, which can result in more rapid agile learning with less data. There is also, feasibly, a unique pathway towards transportable knowledge from a small data approach, which is complementary to a big data approach. Future work should (1) further refine appropriate methods for a small data approach; (2) advance strategies for better integrating a small data approach into real-world practices; and (3) advance ways of actively integrating the strengths and limitations from both small and big data approaches into a unified scientific knowledge base that is linked via a robust science of causality.ConclusionSmall data is valuable in its own right. That said, small and big data paradigms can and should be combined via a foundational science of causality. With these approaches combined, the vision of precision health can be achieved.

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin - the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as 'revolutionary' and 'disruptive', is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is 'fit-for-purpose' is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

Elevated glucose consumption is fundamental to cancer, but selectively targeting this pathway is challenging. We develop a high-throughput assay for measuring glucose consumption and use it to screen non-small-cell lung cancer cell lines against bioactive small molecules. We identify Milciclib that blocks glucose consumption in H460 and H1975, but not in HCC827 or A549 cells, by decreasing SLC2A1 (GLUT1) mRNA and protein levels and by inhibiting glucose transport. Milciclib blocks glucose consumption by targeting cyclin-dependent kinase 7 (CDK7) similar to other CDK7 inhibitors including THZ1 and LDC4297. Enhanced PIK3CA signaling leads to CDK7 phosphorylation, which promotes RNA Polymerase II phosphorylation and transcription. Milciclib, THZ1, and LDC4297 lead to a reduction in RNA Polymerase II phosphorylation on the SLC2A1 promoter. These data indicate that our high-throughput assay can identify compounds that regulate glucose consumption and that CDK7 is a key regulator of glucose consumption in cells with an activated PI3K pathway.

Available CFTR modulators provide no therapeutic benefit for cystic fibrosis (CF) caused by many loss-of-function mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel, including N1303K. We previously introduced the concept of 'co-potentiators' (combination-potentiators) to rescue CFTR function in some minimal function CFTR mutants. Herein, a screen of ~120,000 drug-like synthetic small molecules identified active co-potentiators of pyrazoloquinoline, piperidine-pyridoindole, tetrahydroquinoline and phenylazepine classes, with EC50 down to ~300 nM following initial structure-activity studies. Increased CFTR chloride conductance by up to 8-fold was observed when a co-potentiator (termed 'Class II potentiator') was used with a classical potentiator ('Class I potentiator') such as VX-770 or GLPG1837. To investigate the range of CFTR mutations benefitted by co-potentiators, 14 CF-associated CFTR mutations were studied in transfected cell models. Co-potentiator efficacy was found for CFTR missense, deletion and nonsense mutations in nucleotide binding domain-2 (NBD2), including W1282X, N1303K, c.3700A > G and Q1313X (with corrector for some mutations). In contrast, CFTR mutations G85E, R334W, R347P, V520F, R560T, A561E, M1101K and R1162X showed no co-potentiator activity, even with corrector. Co-potentiator efficacy was confirmed in primary human bronchial epithelial cell cultures generated from a N1303K homozygous CF subject. The Class II potentiators identified here may have clinical benefit for CF caused by mutations in the NBD2 domain of CFTR.

Single-molecule Förster resonance energy transfer (smFRET) is a powerful technique for nanometer-scale studies of single molecules. Solution-based smFRET, in particular, can be used to study equilibrium intra- and intermolecular conformations, binding/unbinding events and conformational changes under biologically relevant conditions without ensemble averaging. However, single-spot smFRET measurements in solution are slow. Here, we detail a high-throughput smFRET approach that extends the traditional single-spot confocal geometry to a multispot one. The excitation spots are optically conjugated to two custom silicon single photon avalanche diode (SPAD) arrays. Two-color excitation is implemented using a periodic acceptor excitation (PAX), allowing distinguishing between singly- and doubly-labeled molecules. We demonstrate the ability of this setup to rapidly and accurately determine FRET efficiencies and population stoichiometries by pooling the data collected independently from the multiple spots. We also show how the high throughput of this approach can be used o increase the temporal resolution of single-molecule FRET population characterization from minutes to seconds. Combined with microfluidics, this high-throughput approach will enable simple real-time kinetic studies as well as powerful molecular screening applications.

Kinases, which function in numerous cell signaling processes, are among the best characterized groups of client proteins for the 90-kDa heat shock protein (HSP90), a molecular chaperone that suppresses the aggregation and maintains the proper folding of its substrate proteins (i.e., clients). No high-throughput proteomic method, however, has been developed for the characterizations of the interactions between HSP90 and the human kinome. Herein, by employing a parallel-reaction monitoring (PRM)-based targeted proteomic method, we found that 99 out of the 249 detected kinase proteins display diminished expression in cultured human cells upon treatment with ganetespib, a small-molecule HSP90 inhibitor. PRM analysis of kinase proteins in the affinity pull-down samples showed that 86 out of the 120 detected kinases are enriched from the CRISPR-engineered cells where a tandem affinity tag was conjugated with the C-terminus of endogenous HSP90β protein over the parental cells. Together, our results from the two complementary quantitative proteomic experiments offer systematic characterizations about the HSP90-kinase interactions at the entire proteome scale and reveal extensive interactions between HSP90 and kinase proteins in human cells.