Chemical Screening Research Articles

Graphene Oxide Chemical Refining Screening to Improve Blood Compatibility of Graphene-Based Nanomaterials

Graphene oxide (GO) nanoparticles, due to their favorable water solubility, compared to graphene (GA), are a hot research topic in biomedical and pharmaceutical research. However, GO clinical translation may be complicated by its high surface/volume ratio enhancing the interaction with human blood components. In fact, GO’s bi-dimensional nature and strong negative charge may lead to severe biological effects, such as thrombogenicity and immune cell activation. This study explores the impact of further GO surface chemical modulation on major adverse effects: blood plasma coagulation and hemolysis. To this aim, we refined GO nanoparticles by fine-tuned reduction chemistry, esterification and introduction of negative or positive charges. With this approach, we were able to mitigate plasma coagulation and hemolysis at variable degrees and to identify GO derivatives with improved biocompatibility. This opens the door to the progress of graphene-based nanotheranostic applications.

A phenotypic screening platform for identifying chemical modulators of astrocyte reactivity.

Disease, injury and aging induce pathological reactive astrocyte states that contribute to neurodegeneration. Modulating reactive astrocytes therefore represent an attractive therapeutic strategy. Here we describe the development of an astrocyte phenotypic screening platform for identifying chemical modulators of astrocyte reactivity. Leveraging this platform for chemical screening, we identify histone deacetylase 3 (HDAC3) inhibitors as effective suppressors of pathological astrocyte reactivity. We demonstrate that HDAC3 inhibition reduces molecular and functional characteristics of reactive astrocytes in vitro. Transcriptional and chromatin mapping studies show that HDAC3 inhibition disarms pathological astrocyte gene expression and function while promoting the expression of genes associated with beneficial astrocytes. Administration of RGFP966, a small molecule HDAC3 inhibitor, blocks reactive astrocyte formation and promotes neuroprotection in vivo in mice. Collectively, these results establish a platform for discovering modulators of reactive astrocyte states, inform the mechanisms that control astrocyte reactivity and demonstrate the therapeutic benefits of modulating astrocyte reactivity for neurodegenerative diseases.

A chemical screen identifies structurally diverse metal chelators with activity against the fungal pathogen Candida albicans.

Candida albicans, one of the most prevalent human fungal pathogens, causes diverse diseases extending from superficial infections to deadly systemic mycoses. Currently, only three major classes of antifungal drugs are available to treat systemic infections: azoles, polyenes, and echinocandins. Alarmingly, the efficacy of these antifungals against C. albicans is hindered both by basal tolerance toward the drugs and the development of resistance mechanisms such as alterations of the drug's target, modulation of stress responses, and overexpression of efflux pumps. Thus, the need to identify novel antifungal strategies is dire. To address this challenge, we screened 3,049 structurally-diverse compounds from the Boston University Center for Molecular Discovery (BU-CMD) chemical library against a C. albicans clinical isolate and identified 17 molecules that inhibited C. albicans growth by >80% relative to controls. Among the most potent compounds were CMLD013360, CMLD012661, and CMLD012693, molecules representing two distinct chemical scaffolds, including 3-hydroxyquinolinones and a xanthone natural product. Based on structural insights, CMLD013360, CMLD012661, and CMLD012693 were hypothesized to exert antifungal activity through metal chelation. Follow-up investigations revealed all three compounds exerted antifungal activity against non-albicans Candida, including Candida auris and Candida glabrata, with the xanthone natural product CMLD013360 also displaying activity against the pathogenic mould Aspergillus fumigatus. Media supplementation with metallonutrients, namely ferric or ferrous iron, rescued C. albicans growth, confirming these compounds act as metal chelators. Thus, this work identifies and characterizes two chemical scaffolds that chelate iron to inhibit the growth of the clinically relevant fungal pathogen C. albicansIMPORTANCEThe worldwide incidence of invasive fungal infections is increasing at an alarming rate. Systemic candidiasis caused by the opportunistic pathogen Candida albicans is the most common cause of life-threatening fungal infection. However, due to the limited number of antifungal drug classes available and the rise of antifungal resistance, an urgent need exists for the identification of novel treatments. By screening a compound collection from the Boston University Center for Molecular Discovery (BU-CMD), we identified three compounds representing two distinct chemical scaffolds that displayed activity against C. albicans. Follow-up analyses confirmed these molecules were also active against other pathogenic fungal species including Candida auris and Aspergillus fumigatus. Finally, we determined that these compounds inhibit the growth of C. albicans in culture through iron chelation. Overall, this observation describes two novel chemical scaffolds with antifungal activity against diverse fungal pathogens.

Synthesis and ecotoxicity screening of reusable, magnetically harvestable metal oxide/hydroxide nanocomposites for safe and sustainable removal and recovery of phosphorus from wastewater

This study assesses the ecotoxicological hazard and suggests measures to improve the ecosafety of 10 highly-efficient metal oxide/hydroxide nanocomposite adsorbents for phosphorus removal/recovery from wastewater using the marine bacterium Vibrio fischeri - an ecotoxicological test organism commonly used for the screening of chemicals which is especially sensitive to zinc. Nanocomposites were synthesized through simple co-precipitation of two-, three- and four-valent metal precursors (Ca2+, Mg2+, Zn2+, Fe3+, Zr4+) at different molar ratios, and characterized with laser diffraction, ICP-OES, XRD and SEM. Among these, the pilot-scale tested ZnFeZr-6:1:1-oxyhydroxide was modified by reducing the zinc-fraction to minimize the leaching of harmful Zn2+. The presence of Zn, however, makes the materials technologically powerful by improving the adsorbent selectivity towards phosphate and the material reusability. Composites stability (d50 < 10 μm) was investigated in deionized water and 2% NaCl (V. fischeri test medium) addressing agglomeration, settling and solubilization (releasing metal ions and/or potentially hazardous nanoparticles). All composites, their filtered supernatants and precursor metal salt solutions were evaluated for their toxic potency (half-effective concentration, EC50 and minimum bactericidal concentration, MBC) using 30-min kinetic bioluminescence inhibition test (ISO-21338:2010) and 24-h viability assay with bacteria V. fischeri. Only the Zn-containing composites showed inhibitory effects to Vibrio fischeri. Those with highest zinc-fraction (ZnFeZr-18:5:1; ZnFeZr-10:1:1) were classified “harmful” (EC50 < 100 mg/L), thus environmentally unsafe for engineering applications. The ZnFeZr-6:1:1 (EC50 = 118 mg/L, MBC = 250 mg/L) proved assumingly safe once deposited on magnetic particles ZnFeZr-6:1:1@MPs (EC50 = 1123 mg/L, MBC > 1000 mg/L). All other composites without Zn were non-toxic to Vibrio fischeri.

A mutation in F-actin polymerization factor suppresses the distal arthrogryposis type 5 PIEZO2 pathogenic variant in Caenorhabditis elegans.

The mechanosensitive PIEZO channel family has been linked to over 26 disorders and diseases. Although progress has been made in understanding these channels at the structural and functional levels, the underlying mechanisms of PIEZO-associated diseases remain elusive. In this study, we engineered four PIEZO-based disease models using CRISPR/Cas9 gene editing. We performed an unbiased chemical mutagen-based genetic suppressor screen to identify putative suppressors of a conserved gain-of-function variant pezo-1[R2405P] that in human PIEZO2 causes distal arthrogryposis type 5 (DA5; p. R2718P). Electrophysiological analyses indicate that pezo-1(R2405P) is a gain-of-function allele. Using genomic mapping and whole-genome sequencing approaches, we identified a candidate suppressor allele in the C. elegans gene gex-3. This gene is an ortholog of human NCKAP1 (NCK-associated protein 1), a subunit of the Wiskott-Aldrich syndrome protein (WASP)-verprolin homologous protein (WAVE/SCAR) complex, which regulates F-actin polymerization. Depletion of gex-3 by RNAi, or with the suppressor allele gex-3(av259[L353F]), significantly increased brood size and ovulation rate, as well as alleviating the crushed oocyte phenotype of the pezo-1(R2405P) mutant. Expression of GEX-3 in the soma is required to rescue the brood size defects in pezo-1(R2405P) animals. Actin organization and orientation were disrupted and distorted in the pezo-1 mutants. Mutation of gex-3(L353F) partially alleviated these defects. The identification of gex-3 as a suppressor of the pathogenic variant pezo-1(R2405P) suggests that the PIEZO coordinates with the cytoskeleton regulator to maintain the F-actin network and provides insight into the molecular mechanisms of DA5 and other PIEZO-associated diseases.

Protein Structure-Based Organic Chemistry-Driven Ligand Design from Ultralarge Chemical Spaces.

Ultralarge chemical spaces describing several billion compounds are revolutionizing hit identification in early drug discovery. Because of their size, such chemical spaces cannot be fully enumerated and require ad-hoc computational tools to navigate them and pick potentially interesting hits. We here propose a structure-based approach to ultralarge chemical space screening in which commercial chemical reagents are first docked to the target of interest and then directly connected according to organic chemistry and topological rules, to enumerate drug-like compounds under three-dimensional constraints of the target. When applied to bespoke chemical spaces of different sizes and chemical complexity targeting two receptors of pharmaceutical interest (estrogen β receptor, dopamine D3 receptor), the computational method was able to quickly enumerate hits that were either known ligands (or very close analogs) of targeted receptors as well as chemically novel candidates that could be experimentally confirmed by in vitro binding assays. The proposed approach is generic, can be applied to any docking algorithm, and requires few computational resources to prioritize easily synthesizable hits from billion-sized chemical spaces.

An introduction to Criteria for Reporting and Evaluating Exposure Datasets (CREED) for use in environmental assessments.

Risks posed by environmental exposure to chemicals are routinely assessed to inform activities ranging from environmental status reporting to authorization and registration of chemicals for commercial uses. Environmental risk assessment generally relies on two key values generated from exposure data and ecotoxicity data. Data sets of measured concentrations of chemicals in environmental matrices, referred to here as exposure data, are widely used to support environmental risk management, decision-making, and reporting, such as for chemical screening, ecological or human health risk assessments, and establishment of guidelines. Practitioners have developed schemes to determine the suitability of ecotoxicity data for specific purposes, focused on evaluating reliability and relevance, but analogous schemes are not available for exposure data. Moreover, regulatory guidance arguably provides less resolution on reporting and evaluating exposure data sets compared to ecotoxicity data. The evaluation of exposure data sets is subject to limitations from variable or unreported data quality objectives and/or from differences in expert judgments, potentially introducing bias and leading to decisions based on flawed and/or inconsistent information. Exposure data sets should be evaluated for reliability and relevance prior to use in environmental assessments. This paper is the first of a four-paper series detailing the outcomes of a Society of Environmental Toxicology and Chemistry technical workshop that has developed Criteria for Reporting and Evaluating Exposure Datasets (CREED). The workshop participants developed practical, systematic criteria for consistent and transparent evaluation of the reliability (quality) and relevance (fitness for purpose) of exposure data. This guidance should apply to many different (unspecified) purposes of assessment. CREED can be used to evaluate existing data sets, but can also inform data generators interested in improving their data collection and reporting to maximize data utility to other users. This first paper details existing frameworks for the evaluation of exposure data sets and demonstrates the need for CREED, drawing from different regulatory assessments, and describes the technical workshop. Integr Environ Assess Manag 2024;20:975-980. © 2024 SETAC.

Rapid screening of chemicals for their potential to cause specific toxidromes

Toxidromes constitute patterns of symptoms and signs caused by specific toxic effects that guide emergency treatments. Computational identification of chemicals that cause different toxidromes allows us to rapidly screen novel compounds and compound classes as to their potential toxicity. The aim of the current study was to create a computational toolset that can map chemicals to their potential toxidromes. Hence, we evaluated the performance of a state-of-the-art deep learning method—the recently developed communicative message passing neural network (CMPNN)—for its ability to overcome the use of small datasets for training deep learning models. Our results indicated that multi-task training—a technique known for its ability to use multiple small datasets to train conventional deep neural networks—works equally well with CMPNN. We also showed that CMPNN-based ensemble learning results in more reliable predictions than those obtained using a single CMPNN model. In addition, we showed that the standard deviations of individual model predictions from an ensemble of CMPNN models correlated with the errors of ensemble predictions and could be used to estimate the reliability of ensemble predictions. For toxidromes that do not have well-defined molecular mechanisms or sufficient data to train a deep learning model, we used the similarity ensemble approach to develop molecular structural similarity-based toxidrome models. We made the toolset developed in this study publicly accessible via a web user interface at https://toxidrome.bhsai.org/.

Development of Potent Mcl-1 Inhibitors: Structural Investigations on Macrocycles Originating from a DNA-Encoded Chemical Library Screen.

Evasion of apoptosis is critical for the development and growth of tumors. The pro-survival protein myeloid cell leukemia 1 (Mcl-1) is an antiapoptotic member of the Bcl-2 family, associated with tumor aggressiveness, poor survival, and drug resistance. Development of Mcl-1 inhibitors implies blocking of protein-protein interactions, generally requiring a lengthy optimization process of large, complex molecules. Herein, we describe the use of DNA-encoded chemical library synthesis and screening to directly generate complex, yet conformationally privileged macrocyclic hits that serve as Mcl-1 inhibitors. By applying a conceptual combination of conformational analysis and structure-based design in combination with a robust synthetic platform allowing rapid analoging, we optimized in vitro potency of a lead series into the low nanomolar regime. Additionally, we demonstrate fine-tuning of the physicochemical properties of the macrocyclic compounds, resulting in the identification of lead candidates 57/59 with a balanced profile, which are suitable for future development toward therapeutic use.

Effects of 4 Testing Arena Sizes and 11 Types of Embryo Media on Sensorimotor Behaviors in Wild-Type and chd7 Mutant Zebrafish Larvae.

The larval zebrafish is a highly versatile model across research disciplines, and the expanding use of behavioral analysis has contributed to many advances in neuropsychiatric, developmental, and toxicological studies, often through large-scale chemical and genetic screens. In the absence of standardized approaches to larval zebrafish behavior analysis, however, it is critical to understand the impact on behavior of experimental variables such as the size of testing arenas and the choice of embryo medium. Using a custom-built, modular high-throughput testing system, we examined the effects of 4 testing arena sizes and 11 types of embryo media on conserved sensorimotor behaviors in zebrafish larvae. Our data show that testing arena size impacts acoustic startle sensitivity and kinematics, as well as spontaneous locomotion and thigmotaxis, with fish tested in larger arenas displaying reduced startle sensitivity and increased locomotion. We also find that embryo media can dramatically affect startle sensitivity, kinematics, habituation, and prepulse inhibition, as well as spontaneous swimming, turning, and overall activity. Common medium components such as methylene blue and high calcium concentration consistently reduced startle sensitivity and locomotion. To further address how the choice of embryo medium can impact phenotype expression in zebrafish models of disease, we reared chd7 mutant larvae, a model of CHARGE syndrome with previously characterized morphological and behavioral phenotypes, in five different types of media and observed impacts on all phenotypes. By defining the effects of these key extrinsic factors on larval zebrafish behavior, these data can help researchers select the most appropriate conditions for their specific research questions, particularly for genetic and chemical screens.

High-throughput screening for a SARS-CoV-2 frameshifting inhibitor using a cell-free protein synthesis system.

Programmed-1 ribosomal frameshifting (-1 PRF) is a translational mechanism adopted by some viruses, including SARS-CoV-2. To find a compound that can inhibit -1 PRF in SARS-CoV-2, we set up a high-throughput screening system using a HeLa cell extract-derived cell-free protein synthesis (CFPS) system. A total of 32,000 compounds were individually incubated with the CFPS system programmed with a -1 PRF-EGFP template. Several compounds were observed to decrease the -1 PRF-driven fluorescence, and one of them had some suppressive effect on -1 PRF of a SARS-CoV-2 genome sequence in transfected cells. Thus the CFPS system can be used as a tool for a high-throughput screening of chemicals.

Screening and Evaluation of Children's Sensitively Toxic Chemicals in New Mosquito Repellent Products Based on a Nationwide Investigation.

New mosquito repellent products (NMRPs) are emerging popular repellents among children. There are increasing reports on children's sensitization reactions caused by NMRPs, while regulations on their productions, sales, or usage are still lacking. One of the reasons could be the missing comprehensive risk assessment. We first conducted a nationwide investigation on children's NMRP usage preferences. Then, we high-throughput screened volatile or semivolatile organic chemicals (VOCs/SVOCs) in five representative NMRPs by the headspace gas chromatography-orbitrap high-resolution mass spectrometry analytical method. After that, toxic compounds were recognized based on the toxicity forecaster (ToxCast) database. A total of 277 VOCs/SVOCs were recognized, and 70 of them were identified as toxic compounds. In a combination of concentrations, toxicities, absorption, distribution, metabolism, and excretion characteristics in the body, 28 chemicals were finally proposed as priority-controlled compounds in NMRPs. Exposure risks of recognized toxic chemicals through NMRPs by inhalation and dermal intake for children across the country were also assessed. Average daily intakes were in the range of 0.20-7.31 mg/kg/day for children in different provinces, and the children in southeastern coastal provinces were found to face higher exposure risks. By controlling the high-priority chemicals, the risks were expected to be reduced by about 46.8% on average. Results of this study are therefore believed to evaluate exposure risks, encourage safe production, and promote reasonable management of NMRPs.

Multiplex single-cell chemical genomics reveals the kinase dependence of the response to targeted therapy

Chemical genetic screens are a powerful tool for exploring how cancer cells' response to drugs is shaped by their mutations, yet they lack a molecular view of the contribution of individual genes to the response to exposure. Here, we present sci-Plex-Gene-by-Environment (sci-Plex-GxE), a platform for combined single-cell genetic and chemical screening at scale. We highlight the advantages of large-scale, unbiased screening by defining the contribution of each of 522 human kinases to the response of glioblastoma to different drugs designed to abrogate signaling from the receptor tyrosine kinase pathway. In total, we probed 14,121 gene-by-environment combinations across 1,052,205 single-cell transcriptomes. We identify an expression signature characteristic of compensatory adaptive signaling regulated in a MEK/MAPK-dependent manner. Further analyses aimed at preventing adaptation revealed promising combination therapies, including dual MEK and CDC7/CDK9 or nuclear factor κB (NF-κB) inhibitors, as potent means of preventing transcriptional adaptation of glioblastoma to targeted therapy.

Discovery and Mechanistic Elucidation of NQO1‐Bioactivatable Small Molecules That Overcome Resistance to Degraders

AbstractDegraders hold the promise to efficiently inactivate previously intractable disease‐relevant targets. Unlike traditional inhibitors, degraders act substoichiometrically and rely on the hijacked proteolysis machinery, which can also act as an entry point for resistance. To fully harness the potential of targeted protein degradation, it is crucial to comprehend resistance mechanisms and formulate effective strategies to overcome them. We conducted a chemical screening to identify synthetic lethal vulnerabilities of cancer cells that exhibit widespread resistance to degraders. Comparative profiling followed by tailored optimization delivered the small molecule RBS‐10, which shows preferential cytotoxicity against cells pan‐resistant to degraders. Multiomics deconvolution of the mechanism of action revealed that RBS‐10 acts as a prodrug bioactivated by the oxidoreductase enzyme NQO1, which is highly overexpressed in our resistance models. Collectively, our work informs on NQO1 as an actionable vulnerability to overcome resistance to degraders and as a biomarker to selectively exploit bioactivatable prodrugs in cancer.

Discovery and Mechanistic Elucidation of NQO1-Bioactivatable Small Molecules That Overcome Resistance to Degraders.

Degraders hold the promise to efficiently inactivate previously intractable disease-relevant targets. Unlike traditional inhibitors, degraders act substoichiometrically and rely on the hijacked proteolysis machinery, which can also act as an entry point for resistance. To fully harness the potential of targeted protein degradation, it is crucial to comprehend resistance mechanisms and formulate effective strategies to overcome them. We conducted a chemical screening to identify synthetic lethal vulnerabilities of cancer cells that exhibit widespread resistance to degraders. Comparative profiling followed by tailored optimization delivered the small molecule RBS-10, which shows preferential cytotoxicity against cells pan-resistant to degraders. Multiomics deconvolution of the mechanism of action revealed that RBS-10 acts as a prodrug bioactivated by the oxidoreductase enzyme NQO1, which is highly overexpressed in our resistance models. Collectively, our work informs on NQO1 as an actionable vulnerability to overcome resistance to degraders and as a biomarker to selectively exploit bioactivatable prodrugs in cancer.

Abstract A052: Pharmacologic conversion of cancer-associated fibroblasts from a protumor phenotype to an antitumor phenotype improves the sensitivity of pancreatic cancer to immune checkpoint blockade therapy

Abstract Background/Purpose: Cancer-associated fibroblasts (CAFs) are one of the major cell subsets in the tumor microenvironment. Their proliferation is observed in almost all invasive cancers but is most prominent in aggressive cancers with marked desmoplastic stromal reactions, such as pancreatic ductal adenocarcinoma (PDAC). Recent single-cell transcriptomic analyses have revealed CAF heterogeneity. One approach to classify CAFs is based on their cellular roles in cancer progression: cancer-promoting CAFs (pCAFs) and cancer-restraining CAFs (rCAFs). We previously identified the glycosylphosphatidylinositol-anchored protein Meflin as a rCAF-specific marker and showed that Meflin-positive CAFs are converted into Meflin-negative CAFs during cancer progression by cell lineage experiments. Interestingly, another previous study demonstrated that the number of Meflin+ rCAFs positively correlated with the response to immune checkpoint blockade (ICB) therapy in patients with non-small cell lung cancer (NSCLC). This was also shown in mouse models, where tumors developed in Meflin KO mice and mice that overexpress Meflin showed lower and higher sensitivity to anti-PD1 antibody treatment, respectively. These data suggest the significance of the balance between pCAFs and rCAFs in ICB therapy, being consistent with recent studies that have shown the critical role of CAFs in anti-tumor immunity So, The aim of this study is to establish the effects of strategies to increase the number of rCAFs on the sensitivity to ICB therapy in PDAC. Material/Methods: A search for chemical compounds that upregulate Meflin expression was performed. We then investigated the effect of the compound on the efficacy of anti-PD-L1 antibody treatment using mouse murine models of PDAC. We also addressed the mechanism by which Meflin+ rCAFs shape the immune tumor microenvironment that potentiates the efficacy of ICB therapy. Results: We performed a chemical library screen for compounds that convert protumor CAFs into rCAFs by inducing Meflin expression. As a result, they identified the synthetic retinoid AM80 as a candidate drug that achieves that CAF conversion. Next, we observed that the induction of a Meflin-positive CAF subset with a cancer-suppressive role through the oral administration of Am80 improves intratumoral delivery and efficacy of anti-PD-L1 antibody treatment in pancreatic cancer models. Interestingly, Am80 exerted this effect when administered to tumors prior to, but not concomitant with, anti-PD-L1 antibody in wild-type but not Meflin-deficient mice. Meflin+ rCAFs induced polarization of macrophages to the M1-like phenotype and durable anti-PD-L1 treatment-mediated anti-tumor responses. Conclusion: Our data suggest that strategy of pharmacologic conversion of CAF from protumor phenotype to an antitumor phenotype CAF can improves the sensitivity of pancreatic cancer to ICB therapy. Citation Format: Tadashi Iida, Owaki Takayuki, Kota Uetsuki, Yamao Kentaro, Yasuyuki Mizutani, Takuya Ishikawa, Atsushi Enomoto, Hiroki Kawashima. Pharmacologic conversion of cancer-associated fibroblasts from a protumor phenotype to an antitumor phenotype improves the sensitivity of pancreatic cancer to immune checkpoint blockade therapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A052.

Amyloid Modifier SERF1a Accelerates Alzheimer's Amyloid-β Fibrillization and Exacerbates the Cytotoxicity.

Alzheimer's disease (AD) is a devastating, progressive neurodegenerative disease affecting the elderly in the world. The pathological hallmark senile plaques are mainly composed of amyloid-β (Aβ), in which the main isoforms are Aβ40 and Aβ42. Aβ is prone to aggregate and ultimately forms amyloid fibrils in the brains of AD patients. Factors that alter the Aβ aggregation process have been considered to be potential targets for treatments of AD. Modifier of aggregation 4 (MOAG-4)/small EDRK-rich factor (SERF) was previously selected from a chemical mutagenesis screen and identified as an amyloid modifier that promotes amyloid aggregation for α-synuclein, huntingtin, and Aβ40. The interaction and effect of yeast ScSERF on Aβ40 were previously described. Here, we examined the human SERF1a effect on Aβ40 and Aβ42 fibrillization by the Thioflavin T assay and found that SERF1a accelerated Aβ fibrillization in a dose-dependent manner without changing the fibril amount and without incorporation. By Fourier transform infrared spectroscopy (FTIR) and transmission electron microscopy (TEM), we found that SERF1a altered the secondary structures and the morphology of Aβ fibrils. The electrospray ionization mass spectrometry (ESI-MS) and analytical ultracentrifugation (AUC) results showed that SERF1a binds to Aβ in a 1:1 stoichiometry. Moreover, the NMR study showed that SERF1a interacts with Aβ via its N-terminal region. Cytotoxicity assay demonstrated that SERF1a enhanced toxicity of Aβ intermediates, and the effect can be rescued by SERF1a antibody. Overall, our study provides the underlying molecular mechanism for the SERF1a effect on Aβ fibrillization and facilitates the therapeutic development of AD.

HTSplotter: An end-to-end data processing, analysis and visualisation tool for chemical and genetic in vitro perturbation screening.

In biomedical research, high-throughput screening is often applied as it comes with automatization, higher-efficiency, and more and faster results. High-throughput screening experiments encompass drug, drug combination, genetic perturbagen or a combination of genetic and chemical perturbagen screens. These experiments are conducted in real-time assays over time or in an endpoint assay. The data analysis consists of data cleaning and structuring, as well as further data processing and visualisation, which, due to the amount of data, can easily become laborious, time-consuming and error-prone. Therefore, several tools have been developed to aid researchers in this process, but these typically focus on specific experimental set-ups and are unable to process data of several time points and genetic-chemical perturbagen screens. To meet these needs, we developed HTSplotter, a web tool and Python module that performs automatic data analysis and visualization of visualization of eitherendpoint or real-time assays from different high-throughput screening experiments: drug, drug combination, genetic perturbagen and genetic-chemical perturbagen screens. HTSplotter implements an algorithm based on conditional statements to identify experiment types and controls. After appropriate data normalization, including growth rate normalization, HTSplotter executes downstream analyses such as dose-response relationship and drug synergism assessment by the Bliss independence (BI), Zero Interaction Potency (ZIP) and Highest Single Agent (HSA) methods. All results are exported as a text file and plots are saved in a PDF file. The main advantage of HTSplotter over other available tools is the automatic analysis of genetic-chemical perturbagen screens and real-time assays where growth rate and perturbagen effect results are plotted over time. In conclusion, HTSplotter allows for the automatic end-to-end data processing, analysis and visualisation of various high-throughput in vitro cell culture screens, offering major improvements in terms of versatility, efficiency and time over existing tools.

HcHCR: High-Throughput Single-Cell Imaging of RNA in Human Primary Immune Cells.

Functional genomics and chemical screens can identify and characterize novel cellular factors regulating signaling networks and chemical tools to modulate their function for the treatment of disease. Screening methods have relied primarily on immortalized and/or transformed cancer cell lines, which can limit the generalization of results to more physiologically relevant systems. Most have also relied on immunofluorescence, or on stably expressed recombinant fluorescent proteins, to detect specific protein markers using high-content imaging readouts. In comparison, high-throughput methods to visualize and measure RNA species have been less explored. To address this, we have adapted an isothermal signal amplification chemistry for RNA FISH known as hybridization chain reaction (HCR) to an automated, high-content imaging assay format. We present a detailed protocol for this technique, which we have named high-content HCR (hcHCR). The protocol focuses on the measurement of changes in mRNA abundance at the single-cell level in human primary cells, but it can be applied to a variety of primary cell types and perturbing agents. We anticipate that hcHCR will be most suitable for low- to medium-throughput screening experiments in which changes in transcript abundance are the desired output measure.

Selective induction of Rab9-dependent alternative mitophagy using a synthetic derivative of isoquinoline alleviates mitochondrial dysfunction and cognitive deficits in Alzheimer's disease models.

Rationale: Promotion of mitophagy is considered a promising strategy for the treatment of neurodegenerative diseases including Alzheimer's disease (AD). The development of mitophagy-specific inducers with low toxicity and defined molecular mechanisms is essential for the clinical application of mitophagy-based therapy. The aim of this study was to investigate the potential of a novel small-molecule mitophagy inducer, ALT001, as a treatment for AD. Methods: ALT001 was developed through chemical optimization of an isoquinolium scaffold, which was identified from a chemical library screening using a mitophagy reporter system. In vitro and in vivo experiments were conducted to evaluate the potential of ALT001 as a mitophagy-targeting therapeutic agent and to investigate the molecular mechanisms underlying ALT001-induced mitophagy. The therapeutic effect of ALT001 was assessed in SH-SY5Y cells expressing mutant APP and mouse models of AD (5×FAD and PS2APP) by analyzing mitochondrial dysfunction and cognitive defects. Results: ALT001 specifically induces mitophagy both in vitro and in vivo but is nontoxic to mitochondria. Interestingly, we found that ALT001 induces mitophagy through the ULK1-Rab9-dependent alternative mitophagy pathway independent of canonical mitophagy pathway regulators such as ATG7 and PINK1. Importantly, ALT001 reverses mitochondrial dysfunction in SH-SY5Y cells expressing mutant APP in a mitophagy-dependent manner. ALT001 induces alternative mitophagy in mice and restores the decreased mitophagy level in a 5×FAD AD model mouse. In addition, ALT001 reverses mitochondrial dysfunction and cognitive defects in the PS2APP and 5×FAD AD mouse models. AAV-mediated silencing of Rab9 in the hippocampus further confirmed that ALT001 exerts its therapeutic effect through alternative mitophagy. Conclusion: Our results highlight the therapeutic potential of ALT001 for AD via alleviation of mitochondrial dysfunction and indicate the usefulness of the ULK1-Rab9 alternative mitophagy pathway as a therapeutic target.