A Genome-wide Functional Signature Ontology Map and Applications to Natural Product Mechanism of Action Discovery

Transcriptional profiling upon T cell stimulation reveals down-regulation of inflammatory pathways in T and B cells in SLE versus Sjögren's syndrome

Systemic lupus erythematosus (SLE) and primary Sjögren's syndrome (pSS) share clinical as well as pathogenic similarities. Although previous studies suggest various abnormalities in different immune cell compartments, dedicated cell-type specific transcriptomic signatures are often masked by patient heterogeneity. Here, we performed transcriptional profiling of isolated CD4, CD8, CD16 and CD19 lymphocytes from pSS and SLE patients upon T cell stimulation, in addition to a steady-state condition directly after blood drawing, in total comprising 581 sequencing samples. T cell stimulation, which induced a pronounced inflammatory response in all four cell types, gave rise to substantial re-modulation of lymphocyte subsets in the two autoimmune diseases compared to healthy controls, far exceeding the transcriptomic differences detected at steady-state. In particular, we detected cell-type and disease-specific down-regulation of a range of pro-inflammatory cytokine and chemokine pathways. Such differences between SLE and pSS patients are instrumental for selective immune targeting by future therapies.

Modulation of in Vitro SARS-CoV-2 Infection by Stephania tetrandra and Its Alkaloid Constituents

Botanical natural products have been widely consumed for their purported usefulness against COVID-19. Here, six botanical species from multiple sources and 173 isolated natural product compounds were screened for blockade of wild-type (WT) SARS-CoV-2 infection in human 293T epithelial cells overexpressing ACE-2 and TMPRSS2 protease (293TAT). Antiviral activity was demonstrated by an extract from Stephania tetrandra. Extract fractionation, liquid chromatography-mass spectrometry (LC-MS), antiviral assays, and computational analyses revealed that the alkaloid fraction and purified alkaloids tetrandrine, fangchinoline, and cepharanthine inhibited WT SARS-CoV-2 infection. The alkaloids and alkaloid fraction also inhibited the delta variant of concern but not WT SARS-CoV-2 in VeroAT cells. Membrane permeability assays demonstrate that the alkaloids are biologically available, although fangchinoline showed lower permeability than tetrandrine. At high concentrations, the extract, alkaloid fractions, and pure alkaloids induced phospholipidosis in 293TAT cells and less so in VeroAT cells. Gene expression profiling during virus infection suggested that alkaloid fraction and tetrandrine displayed similar effects on cellular gene expression and pathways, while fangchinoline showed distinct effects on cells. Our study demonstrates a multifaceted approach to systematically investigate the diverse activities conferred by complex botanical mixtures, their cell-context specificity, and their pleiotropic effects on biological systems.

Exocyst protein subnetworks integrate Hippo and mTOR signaling to promote virus detection and cancer

The exocyst is an evolutionarily conserved protein complex that regulates vesicular trafficking and scaffolds signal transduction. Key upstream components of the exocyst include monomeric RAL GTPases, which help mount cell-autonomous responses to trophic and immunogenic signals. Here, we present a quantitative proteomics-based characterization of dynamic and signal-dependent exocyst protein interactomes. Under viral infection, an Exo84 exocyst subcomplex assembles the immune kinase Protein Kinase R (PKR) together with the Hippo kinase Macrophage Stimulating 1 (MST1). PKR phosphorylates MST1 to activate Hippo signaling and inactivate Yes Associated Protein 1 (YAP1). By contrast, a Sec5 exocyst subcomplex recruits another immune kinase, TANK binding kinase 1 (TBK1), which interacted with and activated mammalian target of rapamycin (mTOR). RALB was necessary and sufficient for induction of Hippo and mTOR signaling through parallel exocyst subcomplex engagement, supporting the cellular response to virus infection and oncogenic signaling. This study highlights RALB-exocyst signaling subcomplexes as mechanisms for the integrated engagement of Hippo and mTOR signaling in cells challenged by viral pathogens or oncogenic signaling.

Chemoproteomic-enabled phenotypic screening

The ID of disease-modifying, chemically accessible targets remains a central priority of modern therapeutic discovery. The phenotypic screening of small-molecule libraries not only represents an attractive approach to identify compounds that may serve as drug leads but also serves as an opportunity to uncover compounds with novel mechanisms of action (MoAs). However, a major bottleneck of phenotypic screens continues to be the ID of pharmacologically relevant target(s) for compounds of interest. The field of chemoproteomics aims to map proteome-wide small-molecule interactions in complex, native systems, and has proved a key technology to unravel the protein targets of pharmacological modulators. In this review, we discuss the application of modern chemoproteomic methods to identify protein targets of phenotypic screening hits and investigate MoAs, with a specific focus on the development of chemoproteomic-enabled compound libraries to streamline target discovery.

A Gene Expression High-Throughput Screen (GE-HTS) for Coordinated Detection of Functionally Similar Effectors in Cancer

Genome-wide, loss-of-function screening can be used to identify novel vulnerabilities upon which specific tumor cells depend for survival. Functional Signature Ontology (FUSION) is a gene expression-based high-throughput screening (GE-HTS) method that allows researchers to identify functionally similar proteins, small molecules, and microRNA mimics, revealing novel therapeutic targets. FUSION uses cell-based high-throughput screening and computational analysis to match gene expression signatures produced by natural products to those produced by small interfering RNA (siRNA) and synthetic microRNA libraries to identify putative protein targets and mechanisms of action (MoA) for several previously undescribed natural products. We have used FUSION to screen for functional analogues to Kinase suppressor of Ras 1 (KSR1), a scaffold protein downstream of Ras in the Raf-MEK-ERK kinase cascade, and biologically validated several proteins with functional similarity to KSR1. FUSION incorporates bioinformatics analysis that may offer higher resolution of the endpoint readout than other screens which utilize Boolean outputs regarding a single pathway activation (i.e., synthetic lethal and cell proliferation). Challenges associated with FUSION and other high-content genome-wide screens include variation, batch effects, and controlling for potential off-target effects. In this review, we discuss the efficacy of FUSION to identify novel inhibitors and oncogene-induced changes that may be cancer cell-specific as well as several potential pitfalls within FUSION and best practices to avoid them.

High-throughput identification of protein functional similarities using a gene-expression-based siRNA screen

A gene expression-based siRNA screen was used to evaluate functional similarity between genetic perturbations to identify functionally similar proteins. A siRNA library (siGenome library, Dharmacon) consisting of multiple siRNAs per gene that have been pooled in to one well per gene was arrayed in a 384-well format and used to individually target 14,335 proteins for depletion in HCT116 colon cancer cells. For each protein depletion, the gene expression of eight genes was quantified using the multiplexed Affymetrix Quantigene 2.0 assay in technical triplicate. As a proof of concept, six genes (BNIP3, NDRG1, ALDOC, LOXL2, ACSL5, BNIP3L) whose expression pattern reliably reflect the disruption of the molecular scaffold KSR1 were measured upon each protein depletion. The remaining two genes (PPIB and HPRT) are housekeeping genes used for normalization. The gene expression signatures from this screen can be used to estimate the functional similarity between any two proteins and successfully identified functional relationships for specific proteins such as KSR1 and more generalized processes, such as autophagy.

Measurement(s)	gene expression • KSR1 pathway regulation
Technology Type(s)	Microarray • RNA interference
Factor Type(s)	target RNA
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11418018

The Natural Products Atlas: An Open Access Knowledge Base for Microbial Natural Products Discovery

Despite rapid evolution in the area of microbial natural products chemistry, there is currently no open access database containing all microbially produced natural product structures. Lack of availability of these data is preventing the implementation of new technologies in natural products science. Specifically, development of new computational strategies for compound characterization and identification are being hampered by the lack of a comprehensive database of known compounds against which to compare experimental data. The creation of an open access, community-maintained database of microbial natural product structures would enable the development of new technologies in natural products discovery and improve the interoperability of existing natural products data resources. However, these data are spread unevenly throughout the historical scientific literature, including both journal articles and international patents. These documents have no standard format, are often not digitized as machine readable text, and are not publicly available. Further, none of these documents have associated structure files (e.g., MOL, InChI, or SMILES), instead containing images of structures. This makes extraction and formatting of relevant natural products data a formidable challenge. Using a combination of manual curation and automated data mining approaches we have created a database of microbial natural products (The Natural Products Atlas, www.npatlas.org) that includes 24 594 compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. This database is accompanied by an interactive web portal that permits searching by structure, substructure, and physical properties. The Web site also provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. These interactive tools offer a powerful knowledge base for natural products discovery with a central interface for structure and property-based searching and presents new viewpoints on structural diversity in natural products. The Natural Products Atlas has been developed under FAIR principles (Findable, Accessible, Interoperable, and Reusable) and is integrated with other emerging natural product databases, including the Minimum Information About a Biosynthetic Gene Cluster (MIBiG) repository, and the Global Natural Products Social Molecular Networking (GNPS) platform. It is designed as a community-supported resource to provide a central repository for known natural product structures from microorganisms and is the first comprehensive, open access resource of this type. It is expected that the Natural Products Atlas will enable the development of new natural products discovery modalities and accelerate the process of structural characterization for complex natural products libraries.