Jason Moffat

CellProfiler: image analysis software for identifying and quantifying cell phenotypes

Biologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining).

A Lentiviral RNAi Library for Human and Mouse Genes Applied to an Arrayed Viral High-Content Screen

To enable arrayed or pooled loss-of-function screens in a wide range of mammalian cell types, including primary and nondividing cells, we are developing lentiviral short hairpin RNA (shRNA) libraries targeting the human and murine genomes. The libraries currently contain 104,000 vectors, targeting each of 22,000 human and mouse genes with multiple sequence-verified constructs. To test the utility of the library for arrayed screens, we developed a screen based on high-content imaging to identify genes required for mitotic progression in human cancer cells and applied it to an arrayed set of 5,000 unique shRNA-expressing lentiviruses that target 1,028 human genes. The screen identified several known and approximately 100 candidate regulators of mitotic progression and proliferation; the availability of multiple shRNAs targeting the same gene facilitated functional validation of putative hits. This work provides a widely applicable resource for loss-of-function screens, as well as a roadmap for its application to biological discovery.

MECHANISM OF INHIBITION OF PROTEIN-TYROSINE PHOSPHATASES BY VANADATE AND PERVANADATE

Vanadate and pervanadate (the complexes of vanadate with hydrogen peroxide) are two commonly used general protein-tyrosine phosphatase (PTP) inhibitors. These compounds also have insulin-mimetic properties, an observation that has generated a great deal of interest and study. Since a careful kinetic study of the two inhibitors has been lacking, we sought to analyze their mechanisms of inhibition. Our results show that vanadate is a competitive inhibitor for the protein-tyrosine phosphatase PTP1B, with a Ki of 0.38 ± 0.02 μM. EDTA, which is known to chelate vanadate, causes an immediate and complete reversal of the inhibition due to vanadate when added to an enzyme assay. Pervanadate, by contrast, inhibits by irreversibly oxidizing the catalytic cysteine of PTP1B, as determined by mass spectrometry. Reducing agents such as dithiothreitol that are used in PTP assays to keep the catalytic cysteine reduced and active were found to convert pervanadate rapidly to vanadate. Under certain conditions, slow time-dependent inactivation by vanadate was observed; since catalase blocked this inactivation, it was ascribed to in situ generation of hydrogen peroxide and subsequent formation of pervanadate. Implications for the use of these compounds as inhibitors and rationalization for some of their in vivo effects are considered.

Exploration of Essential Gene Functions via Titratable Promoter Alleles

Nearly 20% of yeast genes are required for viability, hindering genetic analysis with knockouts. We created promoter-shutoff strains for over two-thirds of all essential yeast genes and subjected them to morphological analysis, size profiling, drug sensitivity screening, and microarray expression profiling. We then used this compendium of data to ask which phenotypic features characterized different functional classes and used these to infer potential functions for uncharacterized genes. We identified genes involved in ribosome biogenesis (HAS1, URB1, and URB2), protein secretion (SEC39), mitochondrial import (MIM1), and tRNA charging (GSN1). In addition, apparent negative feedback transcriptional regulation of both ribosome biogenesis and the proteasome was observed. We furthermore show that these strains are compatible with automated genetic analysis. This study underscores the importance of analyzing mutant phenotypes and provides a resource to complement the yeast knockout collection.

High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities

The ability to perturb genes in human cells is crucial for elucidating gene function and holds great potential for finding therapeutic targets for diseases such as cancer. To extend the catalog of human core and context-dependent fitness genes, we have developed a high-complexity second-generation genome-scale CRISPR-Cas9 gRNA library and applied it to fitness screens in five human cell lines. Using an improved Bayesian analytical approach, we consistently discover 5-fold more fitness genes than were previously observed. We present a list of 1,580 human core fitness genes and describe their general properties. Moreover, we demonstrate that context-dependent fitness genes accurately recapitulate pathway-specific genetic vulnerabilities induced by known oncogenes and reveal cell-type-specific dependencies for specific receptor tyrosine kinases, even in oncogenic KRAS backgrounds. Thus, rigorous identification of human cell line fitness genes using a high-complexity CRISPR-Cas9 library affords a high-resolution view of the genetic vulnerabilities of a cell.

Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning.

Many biological pathways were first uncovered by identifying mutants with visible phenotypes and by scoring every sample in a screen via tedious and subjective visual inspection. Now, automated image analysis can effectively score many phenotypes. In practical application, customizing an image-analysis algorithm or finding a sufficient number of example cells to train a machine learning algorithm can be infeasible, particularly when positive control samples are not available and the phenotype of interest is rare. Here we present a supervised machine learning approach that uses iterative feedback to readily score multiple subtle and complex morphological phenotypes in high-throughput, image-based screens. First, automated cytological profiling extracts hundreds of numerical descriptors for every cell in every image. Next, the researcher generates a rule (i.e., classifier) to recognize cells with a phenotype of interest during a short, interactive training session using iterative feedback. Finally, all of the cells in the experiment are automatically classified and each sample is scored based on the presence of cells displaying the phenotype. By using this approach, we successfully scored images in RNA interference screens in 2 organisms for the prevalence of 15 diverse cellular morphologies, some of which were previously intractable.

Dissecting DNA damage response pathways by analysing protein localization and abundance changes during DNA replication stress

Relocalization of proteins is a hallmark of the DNA damage response. We use high-throughput microscopic screening of the yeast GFP fusion collection to develop a systems-level view of protein reorganization following drug-induced DNA replication stress. Changes in protein localization and abundance reveal drug-specific patterns of functional enrichments. Classification of proteins by subcellular destination enables the identification of pathways that respond to replication stress. We analysed pairwise combinations of GFP fusions and gene deletion mutants to define and order two previously unknown DNA damage responses. In the first, Cmr1 forms subnuclear foci that are regulated by the histone deacetylase Hos2 and are distinct from the typical Rad52 repair foci. In a second example, we find that the checkpoint kinases Mec1/Tel1 and the translation regulator Asc1 regulate P-body formation. This method identifies response pathways that were not detected in genetic and protein interaction screens, and can be readily applied to any form of chemical or genetic stress to reveal cellular response pathways.

INHIBITION OF MITOCHONDRIAL TRANSLATION AS A THERAPEUTIC STRATEGY FOR HUMAN ACUTE MYELOID LEUKEMIA

To identify FDA-approved agents targeting leukemic cells, we performed a chemical screen on two human leukemic cell lines and identified the antimicrobial tigecycline. A genome-wide screen in yeast identified mitochondrial translation inhibition as the mechanism of tigecycline-mediated lethality. Tigecycline selectively killed leukemia stem and progenitor cells compared to their normal counterparts and also showed antileukemic activity in mouse models of human leukemia. ShRNA-mediated knockdown of EF-Tu mitochondrial translation factor in leukemic cells reproduced the antileukemia activity of tigecycline. These effects were derivative of mitochondrial biogenesis that, together with an increased basal oxygen consumption, proved to be enhanced in AML versus normal hematopoietic cells and were also important for their difference in tigecycline sensitivity.

Building mammalian signalling pathways with RNAi screens.

Technological advances in mammalian systems are providing new tools to identify the molecular components of signalling pathways. Foremost among these tools is the ability to knock down gene function through the use of RNA interference (RNAi). The fact that RNAi can be scaled up for use in high-throughput techniques has motivated the creation of genome-wide RNAi reagents. We are now at the brink of being able to harness the power of RNAi for large-scale functional discovery in mammalian cells.

MBNL proteins repress ES-cell-specific alternative splicing and reprogramming

Previous investigations of the core gene regulatory circuitry that controls the pluripotency of embryonic stem (ES) cells have largely focused on the roles of transcription, chromatin and non-coding RNA regulators. Alternative splicing represents a widely acting mode of gene regulation, yet its role in regulating ES-cell pluripotency and differentiation is poorly understood. Here we identify the muscleblind-like RNA binding proteins, MBNL1 and MBNL2, as conserved and direct negative regulators of a large program of cassette exon alternative splicing events that are differentially regulated between ES cells and other cell types. Knockdown of MBNL proteins in differentiated cells causes switching to an ES-cell-like alternative splicing pattern for approximately half of these events, whereas overexpression of MBNL proteins in ES cells promotes differentiated-cell-like alternative splicing patterns. Among the MBNL-regulated events is an ES-cell-specific alternative splicing switch in the forkhead family transcription factor FOXP1 that controls pluripotency. Consistent with a central and negative regulatory role for MBNL proteins in pluripotency, their knockdown significantly enhances the expression of key pluripotency genes and the formation of induced pluripotent stem cells during somatic cell reprogramming.