Biology subjects

McIsaac, R. S.

Publications and source records attributed to McIsaac, R. S..

7 recordsLinked to original sources

bioRxiv2022

The Yeast Lifespan Machine: a microfluidic platform for automated replicative lifespan measurements

The budding yeast, Saccharomyces cerevisiae, has emerged as a model system for studying the aging processes in eukaryotic cells. However, the full complement of tools available in this organism has not been fully applied, in part because of limitations in throughput that restrict the ability to carry out detailed analyses. Recent advances in microfluidics have provided direct longitudinal observation of entire yeast lifespans, but have not yet achieved the normal scale of operation possible in this model system. Here we present a microfluidic platform, called the Yeast Lifespan Machine, where we combine improvements in microfluidics, image acquisition, and image analysis tools to increase robustness and throughput of lifespan measurements in aging yeast cells. We demonstrate the platforms ability to measure the lifespan of large populations of cells and distinguish long- and short-lived mutants, all with minimal involvement of the experimenter. We also show that environmental pH is capable of significantly modulating lifespan depending on the growth media, highlighting how microfluidic technologies reveal determinants of lifespan that are otherwise difficult to ascertain.

cell biology↗

bioRxiv2020

A genome-scale yeast library with inducible expression of individual genes

The ability to switch a gene from off to on and monitor dynamic changes provides a powerful approach for probing gene function and elucidating causal regulatory relationships, including instances of feedback control. Here, we developed and characterized YETI (Yeast Estradiol strains with Titratable Induction), a collection in which 5,687 yeast genes are engineered for transcriptional inducibility with single-gene precision at their native loci and without plasmids. Each strain contains Synthetic Genetic Array (SGA) screening markers and a unique molecular barcode, enabling high-throughput yeast genetics. We characterized YETI using quantitative growth phenotyping and pooled BAR-seq screens, and we used a YETI allele to characterize the regulon of ROF1, showing that it is a transcriptional repressor. We observed that strains with inducible essential genes that have low native expression can often grow without inducer. Analysis of data from other eukaryotic and prokaryotic systems shows that low native expression is a critical variable that can bias promoter-perturbing screens, including CRISPRi. We engineered a second expression system, Z3EB42, that gives lower expression than Z3EV, a feature enabling both conditional activation and repression of lowly expressed essential genes that grow without inducer in the YETI library.

synthetic biology↗

bioRxiv2019

MAPPING TRANSCRIPTION FACTOR NETWORKS BY COMPARING TF BINDING LOCATIONS TO TF PERTURBATION RESPONSES

BackgroundA transcription-factor (TF) network map indicates the direct, functional targets of each TF -- the genes it regulates by binding to their cis-regulatory DNA. Data on the genomic binding locations of each TF and the transcriptional responses to perturbations of its activity, such as overexpressing it, could support TF network mapping. Systematic data sets of both types exist for yeast and for human K562 and HEK293 cells.\n\nResultsIn previous data, most TF binding sites appear to be non-functional, so one cannot take the genes in whose promoters a TF binds as its direct, functional (DF) targets. Taking the genes that are both bound by a TF and responsive to a perturbation of it as its DF targets (intersection algorithm) is also not safe, as we show by deriving a new lower bound on the expected false discovery rate of the intersection algorithm. When there are many non-functional binding sites and many indirect targets, non-functional sites are expected to occur in the cis-regulatory DNA of indirect targets by chance. Dual threshold optimization, a new method for setting significance thresholds on binding and response data, improves the intersection algorithm, as does post-processing perturbation-response data with NetProphet 2.0. A comprehensive new data set measuring the transcriptional response shortly after inducing overexpression of a TF also helps, as does transposon calling cards, a new method for identifying TF binding locations.\n\nConclusionsThe combination of dual threshold optimization and NetProphet greatly expands the high-confidence TF network map in both yeast and human. In yeast, measuring the response shortly after inducing TF overexpression and measuring binding locations by using transposon calling cards improve the network synergistically.

genomics↗

bioRxiv2019

Time-resolved genome-scale profiling reveals a causal expression network

We present an approach for inferring genome-wide regulatory causality and demonstrate its application on a yeast dataset constructed by independently inducing hundreds of transcription factors and measuring timecourses of the resulting gene expression responses. We discuss the regulatory cascades in detail for a single transcription factor, Aft1; however, we have 201 TF induction timecourses that include >100,000 signal-containing dynamic responses. From a single TF induction timecourse we can often discriminate the direct from the indirect effects of the induced TF. Across our entire dataset, however, we find that the majority of expression changes are indirectly driven by unknown regulators. By integrating all timecourses into a single whole-cell transcriptional model, potential regulators of each gene can be predicted without incorporating prior information. In doing so, the indirect effects of a TF are understood as a series of direct regulatory predictions that capture how regulation propagates over time to create a causal regulatory network. This approach, which we call CANDID (Causal Attribution Networks Driven by Induction Dynamics), resulted in the prediction of multiple transcriptional regulators that were validated experimentally.

systems biology↗

bioRxiv2018

The Miniature-chemostat Aging Device: A new experimental platform facilitates assessment of the transcriptional and chromatin landscapes of replicatively aging yeast

Replicative aging of Saccharomyces cerevisiae is an established model system for eukaryotic cellular aging. A major limitation in yeast lifespan studies has been the difficulty of separating old cells from young cells in large quantities for in-depth comparative analyses. We engineered a new platform, the Miniature-chemostat Aging Device (MAD), that enables purification of aged cells at sufficient quantities to enable genomic and biochemical characterization of aging yeast populations. Using the MAD platform, we measured DNA accessibility (ATAC-Seq) and gene expression (RNA-Seq) changes in aging cells. Our data highlight an intimate connection between aging, growth rate, and stress, as many (but not all) genes that change with age have altered expression in cells that are subjected to stress. Stress-independent genes that change with age are highly enriched for targets of the signal recognition particle (SRP). By obtaining pure populations of old cells, we find that nucleosome occupancy does not change significantly with age; however, significant age-dependent changes in accessibility at ~12% of genomic loci reflect decreased replication and changing activities of cell cycle and metabolic regulators. Finally, ATAC-seq revealed that upregulating the proteasome by deleting UBR2 reduces rDNA instability usually observed in aging cells, demonstrating a connection between proteasome activity and genomic stability.

systems biology↗

bioRxiv2017

Monomerization of Far-Red Fluorescent Proteins

Anthozoa class red fluorescent proteins (RFPs) are frequently used as biological markers, with far-red emitting variants ({lambda}em ~ 600 - 900 nm) sought for whole animal imaging because biological tissues are permeable to light in this range. A barrier to the use of naturally occurring RFP variants as molecular markers is that all are tetrameric, which is not ideal for cell biological applications. Efforts to engineer monomeric RFPs have usually produced dimmer and blue-shifted variants, as the chromophore is sensitive to small structural perturbations. In fact, despite much effort, only four native RFPs have been successfully monomerized, leaving the vast majority of RFP biodiversity untapped in biomarker development. Here we report the generation of monomeric variants of HcRed and mCardinal, both far-red dimers, and describe a comprehensive methodology for the rapid monomerization of novel red-shifted oligomeric RFPs. Among the resultant variants, is mKelly1 (emission maximum: {lambda}em = 656 nm), which along with the recently reported mGarnet2 (1), forms a new class of bright, monomeric, far-red FPs.

biochemistry↗

bioRxiv2016

An Estradiol-Inducible Promoter Enables Fast, Graduated Control of Gene Expression in Fission Yeast

The fission yeast Schizosaccharomyces pombe lacks a diverse toolkit of inducible promoters for experimental manipulation. Available inducible promoters suffer from slow induction kinetics, limited control of expression levels and/or a requirement for defined growth medium. In particular, no S. pombe inducible promoter systems exhibit a linear dose response, which would allow expression to be tuned to specific levels. We have adapted a fast, orthogonal promoter system with a large dynamic range and a linear dose response, based on {beta}-estradiol-regulated function of the human estrogen receptor, for use in S. pombe. We show that this promoter system, termed Z3EV, turns on quickly, can reach a maximal induction of 20 fold, and exhibits a linear dose response over its entire induction range, with few off target effects. We demonstrate the utility of this system by regulating the mitotic inhibitor Wee1 to create a strain in which cell size is regulated by {beta}-estradiol concentration. This promoter system will be of great utility for experimentally regulating gene expression in fission yeast.

cell biology↗