One-Cell Doubling Evaluation by Living Arrays of Yeast, ODELAY!

A Normalization Protocol Reduces Edge Effect in High-Throughput Analyses of Hydroxyurea Hypersensitivity in Fission Yeast

Edge effect denotes better growth of microbial organisms situated at the edge of the solid agar media. Although the precise reason underlying edge effect is unresolved, it is generally attributed to greater nutrient availability with less competing neighbors at the edge. Nonetheless, edge effect constitutes an unavoidable confounding factor that results in misinterpretation of cell fitness, especially in high-throughput screening experiments widely employed for genome-wide investigation using microbial gene knockout or mutant libraries. Here, we visualize edge effect in high-throughput high-density pinning arrays and report a normalization approach based on colony growth rate to quantify drug (hydroxyurea)-hypersensitivity in fission yeast strains. This normalization procedure improved the accuracy of fitness measurement by compensating cell growth rate discrepancy at different locations on the plate and reducing false-positive and -negative frequencies. Our work thus provides a simple and coding-free solution for a struggling problem in robotics-based high-throughput screening experiments.

A repackaged CRISPR platform increases homology-directed repair for yeast engineering

Inefficient homology-directed repair (HDR) constrains CRISPR-Cas9 genome editing in organisms that preferentially employ nonhomologous end joining (NHEJ) to fix DNA double-strand breaks (DSBs). Current strategies used to alleviate NHEJ proficiency involve NHEJ disruption. To confer precision editing without NHEJ disruption, we identified the shortcomings of the conventional CRISPR platforms and developed a CRISPR platform-lowered indel nuclease system enabling accurate repair (LINEAR)-which enhanced HDR rates (to 67-100%) compared to those in previous reports using conventional platforms in four NHEJ-proficient yeasts. With NHEJ preserved, we demonstrate its ability to survey genomic landscapes, identifying loci whose spatiotemporal genomic architectures yield favorable expression dynamics for heterologous pathways. We present a case study that deploys LINEAR precision editing and NHEJ-mediated random integration to rapidly engineer and optimize a microbial factory to produce (S)-norcoclaurine. Taken together, this work demonstrates how to leverage an antagonizing pair of DNA DSB repair pathways to expand the current collection of microbial factories.

ODELAM: Rapid Sequence-independent Detection of Drug Resistance in Mycobacterium tuberculosis Isolates

Antimicrobial-resistant Mycobacterium tuberculosis (Mtb) causes over 200,000 deaths globally each year. Current assays of antimicrobial resistance require knowledge of the mutations that confer drug resistance or long periods of culture time to test growth under drug pressure. We present ODELAM (One-cell Doubling Evaluation of Living Arrays of Mycobacterium), a time-lapse microscopy-based method that observes individual cells growing into microcolonies. This protocol describes sample and media preparation and contains instructions for assembling the ODELAM sample chamber. The ODELAM sample chamber is designed to provide a controlled environment to safely observe the growth of Mtb by time-lapse microscopy on an inverted wide-field microscope. A brief description of the ODELAM software is also provided here. ODELAM tracks up to 1500 colony forming units per region of interest and can observe up to 96 regions for up to seven days in a single experiment. This technique allows the quantification of population heterogeneity. ODELAM enables rapid quantitative measurements of growth kinetics in as few as 30 h under a wide variety of environmental conditions. Graphic abstract: Schematic representation of the ODELAM platform.

LI Detector: a framework for sensitive colony-based screens regardless of the distribution of fitness effects

Microbial growth characteristics have long been used to investigate fundamental questions of biology. Colony-based high-throughput screens enable parallel fitness estimation of thousands of individual strains using colony growth as a proxy for fitness. However, fitness estimation is complicated by spatial biases affecting colony growth, including uneven nutrient distribution, agar surface irregularities, and batch effects. Analytical methods that have been developed to correct for these spatial biases rely on the following assumptions: (1) that fitness effects are normally distributed, and (2) that most genetic perturbations lead to minor changes in fitness. Although reasonable for many applications, these assumptions are not always warranted and can limit the ability to detect small fitness effects. Beneficial fitness effects, in particular, are notoriously difficult to detect under these assumptions. Here, we developed the linear interpolation-based detector (LI Detector) framework to enable sensitive colony-based screening without making prior assumptions about the underlying distribution of fitness effects. The LI Detector uses a grid of reference colonies to assign a relative fitness value to every colony on the plate. We show that the LI Detector is effective in correcting for spatial biases and equally sensitive toward increase and decrease in fitness. LI Detector offers a tunable system that allows the user to identify small fitness effects with unprecedented sensitivity and specificity. LI Detector can be utilized to develop and refine gene-gene and gene-environment interaction networks of colony-forming organisms, including yeast, by increasing the range of fitness effects that can be reliably detected.

Dissecting the Structural Dynamics of the Nuclear Pore Complex

Cellular processes are largely carried out by macromolecular assemblies, most of which are dynamic, having components that are in constant flux. One such assembly is the nuclear pore complex (NPC), an ∼50 MDa assembly comprised of ∼30 different proteins called Nups that mediates selective macromolecular transport between the nucleus and cytoplasm. We developed a proteomics method to provide a comprehensive picture of the yeast NPC component dynamics. We discovered that, although all Nups display uniformly slow turnover, their exchange rates vary considerably. Surprisingly, this exchange rate was relatively unrelated to each Nup's position, accessibility, or role in transport but correlated with its structural role; scaffold-forming Nups exchange slowly, whereas flexible connector Nups threading throughout the NPC architecture exchange more rapidly. Targeted perturbations in the NPC structure revealed a dynamic resilience to damage. Our approach opens a new window into macromolecular assembly dynamics.

Peroxisome prognostications: Exploring the birth, life, and death of an organelle

Peroxisomes play a central role in human health and have biochemical properties that promote their use in many biotechnology settings. With a primary role in lipid metabolism, peroxisomes share a niche with lipid droplets within the endomembrane-secretory system. Notably, factors in the ER required for the biogenesis of peroxisomes also impact the formation of lipid droplets. The dynamic interface between peroxisomes and lipid droplets, and also between these organelles and the ER and mitochondria, controls their metabolic flux and their dynamics. Here, we review our understanding of peroxisome biogenesis to propose and reframe models for understanding how peroxisomes are formed in cells. To more fully understand the roles of peroxisomes and to take advantage of their many properties that may prove useful in novel therapeutics or biotechnology applications, we recast mechanisms controlling peroxisome biogenesis in a framework that integrates inference from these models with experimental data.

ODELAM, rapid sequence-independent detection of drug resistance in isolates of Mycobacterium tuberculosis

Antimicrobial-resistant Mycobacterium tuberculosis (Mtb) causes over 200,000 deaths each year. Current assays of antimicrobial resistance need knowledge of mutations that confer drug resistance, or long periods of culture time to test growth under drug pressure. We present ODELAM (One-cell Doubling Evaluation of Living Arrays of Mycobacterium), a time-lapse microscopy-based method that observes individual cells growing into microcolonies. ODELAM enables rapid quantitative measures of growth kinetics in as little as 30 hrs under a wide variety of environmental conditions. We demonstrate ODELAM’s utility by identifying ofloxacin resistance in cultured clinical isolates of Mtb and benchmark its performance with standard minimum inhibitory concentration (MIC) assays. ODELAM identified ofloxacin heteroresistance and the presence of drug resistant colony forming units (CFUs) at 1 per 1000 CFUs in as little as 48 hrs. ODELAM is a powerful new tool that can rapidly evaluate Mtb drug resistance in a laboratory setting.

Systematic Y2H Screening Reveals Extensive Effector-Complex Formation

During infection pathogens secrete small molecules, termed effectors, to manipulate and control the interaction with their specific hosts. Both the pathogen and the plant are under high selective pressure to rapidly adapt and co-evolve in what is usually referred to as molecular arms race. Components of the host's immune system form a network that processes information about molecules with a foreign origin and damage-associated signals, integrating them with developmental and abiotic cues to adapt the plant's responses. Both in the case of nucleotide-binding leucine-rich repeat receptors and leucine-rich repeat receptor kinases interaction networks have been extensively characterized. However, little is known on whether pathogenic effectors form complexes to overcome plant immunity and promote disease. Ustilago maydis, a biotrophic fungal pathogen that infects maize plants, produces effectors that target hubs in the immune network of the host cell. Here we assess the capability of U. maydis effector candidates to interact with each other, which may play a crucial role during the infection process. Using a systematic yeast-two-hybrid approach and based on a preliminary pooled screen, we selected 63 putative effectors for one-on-one matings with a library of nearly 300 effector candidates. We found that 126 of these effector candidates interacted either with themselves or other predicted effectors. Although the functional relevance of the observed interactions remains elusive, we propose that the observed abundance in complex formation between effectors adds an additional level of complexity to effector research and should be taken into consideration when studying effector evolution and function. Based on this fundamental finding, we suggest various scenarios which could evolutionarily drive the formation and stabilization of an effector interactome.

ESCRT-III is required for scissioning new peroxisomes from the endoplasmic reticulum

Dynamic control of peroxisome proliferation is integral to the peroxisome's many functions. The endoplasmic reticulum (ER) serves as a source of preperoxisomal vesicles (PPVs) that mature into peroxisomes during de novo peroxisome biogenesis and support growth and division of existing peroxisomes. However, the mechanism of PPV formation and release from the ER remains poorly understood. In this study, we show that endosomal sorting complexes required for transport (ESCRT)-III are required to release PPVs budding from the ER into the cytosol. Absence of ESCRT-III proteins impedes de novo peroxisome formation and results in an aberrant peroxisome population in vivo. Using a cell-free PPV budding assay, we show that ESCRT-III proteins Vps20 and Snf7 are necessary to release PPVs from the ER. ESCRT-III is therefore a positive effector of membrane scission for vesicles budding both away from and toward the cytosol. These findings have important implications for the evolutionary timing of emergence of peroxisomes and the rest of the internal membrane architecture of the eukaryotic cell.

Integrative structure and functional anatomy of a nuclear pore complex

Despite the central role of Nuclear Pore Complexes (NPCs) as gatekeepers of RNA and protein transport between the cytoplasm and nucleoplasm, their large size and dynamic nature have impeded a full structural and functional elucidation. Here, we have determined a subnanometer precision structure for the entire 552-protein yeast NPC by satisfying diverse data including stoichiometry, a cryo-electron tomography map, and chemical cross-links. The structure reveals the NPC’s functional elements in unprecedented detail. The NPC is built of sturdy diagonal columns to which are attached connector cables, imbuing both strength and flexibility, while tying together all other elements of the NPC, including membrane-interacting regions and RNA processing platforms. Inwardly-directed anchors create a high density of transport factor-docking Phe-Gly repeats in the central channel, organized in distinct functional units. Taken together, this integrative structure allows us to rationalize the architecture, transport mechanism, and evolutionary origins of the NPC.

ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth

Growth phenotypes of microorganisms are a strong indicator of their underlying genetic fitness and can be segregated into 3 growth regimes: lag-phase, log-phase, and stationary-phase. Each growth phase can reveal different aspects of fitness that are related to various environmental and genetic conditions. High-resolution and quantitative measurements of all 3 phases of growth are generally difficult to obtain. Here we present a detailed method to characterize all 3 growth phases on solid media using an assay called One-cell Doubling Evaluation of Living Arrays of Yeast (ODELAY). ODELAY quantifies growth phenotypes of individual cells growing into colonies on solid media using time-lapse microscopy. This method can directly observe population heterogeneity with each growth parameter in genetically identical cells growing into colonies. This population heterogeneity offers a unique perspective for understanding genetic and epigenetic regulation, and responses to genetic and environmental perturbations. While the ODELAY method is demonstrated using yeast, it can be utilized on any colony forming microorganism that is visible by bright field microscopy.

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.