Contribution of high-content imaging technologies to the development of anti-infective drugs

Apoptosis assessment in high-content and high-throughput screening assays

Here the authors describe the development of AUTOptosis, an economical and rapid apoptosis monitoring method suitable for high-content and high-throughput screening assays. AUTOptosis is based on the quantification of nuclei intensity via staining with Hoechst 33342. First, the authors calibrated the method using standard apoptosis inducers in multiple cell lines. Next, the authors validated the applicability of this approach to high-content screening using a small library of compounds and compared it with the terminal deoxynucleotidyl transferase dUTP nick end labeling gold standard. Finally, the authors demonstrated the specificity of the method by using AUTOposis to detect apoptosis triggered by Mycobacterium tuberculosis intracellular infections.

High-Content Imaging to Phenotype Antimicrobial Effects on Individual Bacteria at Scale

High-content imaging (HCI) is a technique for screening multiple cells in high resolution to detect subtle morphological and phenotypic variation. The method has been commonly deployed on model eukaryotic cellular systems, often for screening new drugs and targets. HCI is not commonly utilized for studying bacterial populations but may be a powerful tool in understanding and combatting antimicrobial resistance. Consequently, we developed a high-throughput method for phenotyping bacteria under antimicrobial exposure at the scale of individual bacterial cells. Imaging conditions were optimized on an Opera Phenix confocal microscope (Perkin Elmer), and novel analysis pipelines were established for both Gram-negative bacilli and Gram-positive cocci. The potential of this approach was illustrated using isolates of Klebsiella pneumoniae, Salmonella enterica serovar Typhimurium, and Staphylococcus aureus HCI enabled the detection and assessment of subtle morphological characteristics, undetectable through conventional phenotypical methods, that could reproducibly distinguish between bacteria exposed to different classes of antimicrobials with distinct modes of action (MOAs). In addition, distinctive responses were observed between susceptible and resistant isolates. By phenotyping single bacterial cells, we observed intrapopulation differences, which may be critical in identifying persistence or emerging resistance during antimicrobial treatment. The work presented here outlines a comprehensive method for investigating morphological changes at scale in bacterial populations under specific perturbation.IMPORTANCE High-content imaging (HCI) is a microscopy technique that permits the screening of multiple cells simultaneously in high resolution to detect subtle morphological and phenotypic variation. The power of this methodology is that it can generate large data sets comprised of multiple parameters taken from individual cells subjected to a range of different conditions. We aimed to develop novel methods for using HCI to study bacterial cells exposed to a range of different antibiotic classes. Using an Opera Phenix confocal microscope (Perkin Elmer) and novel analysis pipelines, we created a method to study the morphological characteristics of Klebsiella pneumoniae, Salmonella enterica serovar Typhimurium, and Staphylococcus aureus when exposed to antibacterial drugs with differing modes of action. By imaging individual bacterial cells at high resolution and scale, we observed intrapopulation differences associated with different antibiotics. The outlined methods are highly relevant for how we begin to better understand and combat antimicrobial resistance.

Technologies for High-Throughput Identification of Antibiotic Mechanism of Action

There are two main strategies for antibiotic discovery: target-based and phenotypic screening. The latter has been much more successful in delivering first-in-class antibiotics, despite the major bottleneck of delayed Mechanism-of-Action (MOA) identification. Although finding new antimicrobial compounds is a very challenging task, identifying their MOA has proven equally challenging. MOA identification is important because it is a great facilitator of lead optimization and improves the chances of commercialization. Moreover, the ability to rapidly detect MOA could enable a shift from an activity-based discovery paradigm towards a mechanism-based approach. This would allow to probe the grey chemical matter, an underexplored source of structural novelty. In this study we review techniques with throughput suitable to screen large libraries and sufficient sensitivity to distinguish MOA. In particular, the techniques used in chemical genetics (e.g., based on overexpression and knockout/knockdown collections), promoter-reporter libraries, transcriptomics (e.g., using microarrays and RNA sequencing), proteomics (e.g., either gel-based or gel-free techniques), metabolomics (e.g., resourcing to nuclear magnetic resonance or mass spectrometry techniques), bacterial cytological profiling, and vibrational spectroscopy (e.g., Fourier-transform infrared or Raman scattering spectroscopy) were discussed. Ultimately, new and reinvigorated phenotypic assays bring renewed hope in the discovery of a new generation of antibiotics.

High-Content Screening for Cryptosporidium Drug Discovery

High-content screening (HCS) is a cell-based type of phenotypic screening that combines multiple simultaneous readouts with a high level of throughput. A particular benefit of this form of screening for drug discovery is the ability to perform the interrogation in a biologically relevant system. This approach has greatly advanced the field of drug discovery for cryptosporidiosis, a diarrheal disease caused by protozoan parasites of Cryptosporidium spp. These parasites are obligate intracellular parasites and cannot be cultured in vitro without the support of a host cell, limiting the options for potential assay readout. Here we describe an established 384- or 1536-well format high-content imaging (HCI) assay of Cryptosporidium-infected HCT-8 human ileocecal adenocarcinoma cells. This HCS assay is a powerful tool to assess large numbers of compounds to power drug discovery, as well as to phenotypically characterize known Cryptosporidium-active compounds.

A high content screening assay for identifying inhibitors against active and dormant state intracellular Mycobacterium tuberculosis

The antitubercular drug development pipeline could start with an in vitro investigation of several compounds to examine their effect on active and dormant state Mycobacterium tuberculosis (Mtb). However, in vitro screening of dormant state bacilli cannot provide enough information on the simultaneous effect of a compound on the host. Therefore, we developed a live cell fluorescence based screening protocol by utilizing the high content system for determining the effect of inhibitors against active and dormant state intracellular mycobacteria. THP-1 macrophages infected with an actively growing and hypoxia derived dormant Mtb culture were standardized to develop the screening protocol. The signal to noise ratio and the Z' factor of this assay were found to be 7.5-29 and 0.6-0.8, respectively, which confirm the robustness of the protocol. The protocol was then validated with standard inhibitors. This newly developed drug screening assay offers an easy, safe, image based high content screening tool to search for novel antitubercular inhibitors against both active and dormant state intracellular mycobacteria. Therefore, this assay could fill in the gap between in vitro and in vivo latent tuberculosis drug screening programs.

Natural-Product-Inspired Compounds as Countermeasures against the Liver Carcinogen Aflatoxin B1

Aflatoxin B₁ (AfB₁) ranks among the most potent liver carcinogens known, and the accidental or intentional exposure of humans and livestock to this toxin remains a serious global threat. One protective measure that had been proposed is employing small-molecule therapeutics capable of mitigating the toxicity of AfB₁; however, to date, these efforts have had little clinical success. To identify molecular scaffolds that reduce the toxicity of AfB₁, we developed a cell-based high-throughput high-content imaging assay that enabled our team to test natural products (pure compounds, fractions, and extracts) for protection of monolayers and spheroids composed of HepG2 liver cells against AfB₁. The spheroid assay showed notable potential for further development, as it afforded greater sensitivity of HepG2 cells to AfB1, which is believed to better mimic the in vivo response of hepatocytes to the toxin. One of the most bioactive compounds to arise from this investigation was alternariol-9-methyl ether (1, purified from an Alternaria sp. isolate), which inspired the synthesis and testing of several structurally related molecules. Based on these findings, it is proposed that several types of natural and synthetic polyarene molecules that have undergone oxidative functionalization (e.g., compounds containing 3-methoxyphenol moieties) are promising starting points for the development of new agents that protect against AfB₁ toxicity.

Defining host-pathogen interactions employing an artificial intelligence workflow

For image-based infection biology, accurate unbiased quantification of host-pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentation. Host protein recruitment to pathogens is often refractory to accurate automated assessment due to its heterogeneous nature. An intuitive intelligent image analysis program to assess host protein recruitment within general cellular pathogen defense is lacking. We present HRMAn (Host Response to Microbe Analysis), an open-source image analysis platform based on machine learning algorithms and deep learning. We show that HRMAn has the capacity to learn phenotypes from the data, without relying on researcher-based assumptions. Using Toxoplasma gondii and Salmonella enterica Typhimurium we demonstrate HRMAn's capacity to recognize, classify and quantify pathogen killing, replication and cellular defense responses. HRMAn thus presents the only intelligent solution operating at human capacity suitable for both single image and high content image analysis.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Thinking Outside the Box-Novel Antibacterials To Tackle the Resistance Crisis

The public view on antibiotics as reliable medicines changed when reports about "resistant superbugs" appeared in the news. While reasons for this resistance development are easily spotted, solutions for re-establishing effective antibiotics are still in their infancy. This Review encompasses several aspects of the antibiotic development pipeline from very early strategies to mature drugs. An interdisciplinary overview is given of methods suitable for mining novel antibiotics and strategies discussed to unravel their modes of action. Select examples of antibiotics recently identified by using these platforms not only illustrate the efficiency of these measures, but also highlight promising clinical candidates with therapeutic potential. Furthermore, the concept of molecules that disarm pathogens by addressing gatekeepers of virulence will be covered. The Review concludes with an evaluation of antibacterials currently in clinical development. Overall, this Review aims to connect select innovative antimicrobial approaches to stimulate interdisciplinary partnerships between chemists from academia and industry.

Challenges and recent progress in drug discovery for tropical diseases

Infectious tropical diseases have a huge effect in terms of mortality and morbidity, and impose a heavy economic burden on affected countries. These diseases predominantly affect the world's poorest people. Currently available drugs are inadequate for the majority of these diseases, and there is an urgent need for new treatments. This Review discusses some of the challenges involved in developing new drugs to treat these diseases and highlights recent progress. While there have been notable successes, there is still a long way to go.