Biology subjects

Place, M.

Publications and source records attributed to Place, M..

11 recordsLinked to original sources

bioRxiv2024

Physiological Roles of an Acinetobacter-specific σ Factor

The Gram-negative pathogen Acinetobacter baumannii is considered an "urgent threat" to human health due to its propensity to become antibiotic resistant. Understanding the distinct regulatory paradigms used by A. baumannii to mitigate cellular stresses may uncover new therapeutic targets. Many {gamma}-proteobacteria use the extracytoplasmic function (ECF) {sigma} factor, RpoE, to invoke envelope homeostasis networks in response to stress. Acinetobacter species contain the poorly characterized ECF "SigAb;" however, it is unclear if SigAb has the same physiological role as RpoE. Here, we show that SigAb is a metal stress-responsive ECF that appears unique to Acinetobacter species and distinct from RpoE. We combine promoter mutagenesis, motif scanning, and ChIP-seq to define the direct SigAb regulon, which consists of sigAb itself, the stringent response mediator, relA, and the uncharacterized small RNA, "sabS." However, RNA-seq of strains overexpressing SigAb revealed a large, indirect regulon containing hundreds of genes. Metal resistance genes are key elements of the indirect regulon, as CRISPRi knockdown of sigAb or sabS resulted in increased copper sensitivity and excess copper induced SigAb-dependent transcription. Further, we found that two uncharacterized genes in the sigAb operon, "aabA" and "aabB", have anti-SigAb activity. Finally, employing a targeted Tn-seq approach that uses CRISPR-associated transposons, we show that sigAb, aabA, and aabB are important for fitness even during optimal growth conditions. Our work reveals new physiological roles for SigAb and SabS, provides a novel approach for assessing gene fitness, and highlights the distinct regulatory architecture of A. baumannii. ImportanceAcinetobacter baumannii is a hospital-acquired pathogen, and many strains are resistant to multiple antibiotics. Understanding how A. baumannii senses and responds to stress may uncover novel routes to treat infections. Here, we examine how the Acinetobacter-specific transcription factor, SigAb, mitigates stress. We find that SigAb directly regulates only a small number of genes, but indirectly controls hundreds of genes that have substantial impacts on cell physiology. We show that SigAb is required for maximal growth, even during optimal conditions, and is acutely required during growth in the presence of elevated copper. Given that copper toxicity plays roles in pathogenesis and on copper-containing surfaces in hospitals, we speculate that SigAb function may be important in clinically-relevant contexts.

microbiology↗

bioRxiv2024

Premature aging in aneuploid yeast is caused in part by aneuploidy-induced defects in Ribosome Quality Control

Premature aging is a hallmark of Down syndrome, caused by trisomy of human chromosome 21, but the reason is unclear and difficult to study in humans. We used an aneuploid model in wild yeast to show that chromosome amplification disrupts nutrient-induced cell-cycle arrest, quiescence entry, and healthy aging, across genetic backgrounds and amplified chromosomes. We discovered that these defects are due in part to aneuploidy-induced dysfunction in Ribosome Quality Control (RQC). Compared to euploids, aneuploids entering quiescence display aberrant ribosome profiles, accumulate RQC intermediates, and harbor an increased load of protein aggregates. Although they have normal proteasome capacity, aneuploids show signs of ubiquitin dysregulation, which impacts cyclin abundance to disrupt arrest. Remarkably, inducing ribosome stalling in euploids produces similar aberrations, while up-regulating limiting RQC subunits or proteins in ubiquitin metabolism alleviates many of the aneuploid defects. Our results provide implications for other aneuploidy disorders including Down syndrome.

molecular biology↗

bioRxiv2024

Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will only be maintained if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74-94% of the variance in aneuploid strains growth rates is explained by the additive cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of snoRNAs and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.

genomics↗

bioRxiv2024

Generation of diversity in the blue cheese mold Penicillium roqueforti and identification of pleiotropic QTL for key cheese-making phenotypes

Elucidating the genomic architecture of quantitative traits is essential for our understanding of adaptation and for breeding in domesticated organisms. Penicillium roqueforti is the mold used worldwide for the blue cheese maturation, contributing to flavors through proteolytic and lipolytic activities. The two domesticated cheese populations display very little genetic diversity, but are differentiated and carry opposite mating types. We produced haploid F1 progenies from five crosses, using parents belonging to cheese and non-cheese populations. Analyses of high-quality genome assemblies of the parental strains revealed five large translocations, two having occurred via a circular intermediate. Offspring genotyping with genotype-by-sequencing (GBS) revealed several genomic regions with segregation distortion, possibly linked to degeneration in cheese lineages. We found transgressions for several traits relevant for cheese making, with offspring having more extreme trait values than parental strains. We identified quantitative trait loci (QTLs) for colony color, lipolysis, proteolysis, extrolite production, including mycotoxins, but not for growth rates. Some genomic regions appeared rich in QTLs for both lipid and protein metabolism, and other regions for the production of multiple extrolites, indicating that QTLs have pleiotropic impacts. Some QTLs corresponded to known biosynthetic gene clusters, e.g., for the production of melanin or extrolites. F1 hybrids constitute valuable strains for cheese producers, with new traits and genetic diversity, and allowed identifying target genomic regions for traits important in cheese making, paving the way for strain improvement. The findings further contribute to our understanding of the genetic mechanisms underlying rapid adaptation, revealing convergent adaptation targeting major regulators.

evolutionary biology↗

bioRxiv2023

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation (CNV) provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene over-expression (OE), revealing that the fitness costs of CNV can vary substantially with genetic background in a common-garden environment. But the interplay between CNV tolerance and environment remains unexplored on a genomic scale. Here we measured the tolerance to gene OE in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride (NaCl) stress. OE genes that are commonly deleterious during NaCl stress recapitulated those commonly deleterious under standard conditions. However, NaCl stress uncovered novel differences in strain responses to gene OE. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to NaCl stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to gene OE. Although most genes were deleterious, hundreds were beneficial when overexpressed - remarkably, most of these effects were strain specific. Few beneficial genes were shared between the NaCl-sensitive isolates, implicating mechanistic differences behind their NaCl sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural CNV of a sodium export pump that likely contributes to strain-specific responses to OE of other genes. Our results reveal extensive strain-by-environment interaction in the response to gene CNV, raising important implications for the accessibility of CNV-dependent evolutionary routes under times of stress.

evolutionary biology↗

bioRxiv2021

Natural variation in the consequences of gene overexpression and its implications for evolutionary trajectories

Copy number variation (CNV) through gene or chromosome amplification provides a route for rapid phenotypic variation and supports long-term evolution of gene functions. Although the evolutionary importance of CNV is known, little is understood about how genetic background influences CNV tolerance. Here, we measured fitness costs of over 4,000 over-expressed genes in 15 Saccharomyces cerevisiae strains representing different lineages, to explore natural variation in tolerating gene overexpression (OE). Strain-specific effects dominated the fitness costs of gene OE. We report global differences in the consequences of gene OE, independent of the amplified gene, as well as gene-specific effects that were dependent on the genetic background. Natural variation in the response to gene OE could be explained by several models, including strain-specific physiological differences, resource limitations, and regulatory sensitivities. This work provides new insight on how genetic background influences tolerance to gene amplification and the evolutionary trajectories accessible to different backgrounds.

genomics↗

bioRxiv2020

CRISpy-pop: a web tool for designing CRISPR/Cas9-driven genetic modifications in diverse populations

CRISPR/Cas9 is a powerful tool for editing genomes, but design decisions are generally made with respect to a single reference genome. With population genomic data becoming available for an increasing number of model organisms, researchers are interested in manipulating multiple strains and lines. CRISpy-pop is a web application that generates and filters guide RNA sequences for CRISPR/Cas9 genome editing for diverse yeast and bacterial strains. The current implementation designs and predicts the activity of guide RNAs against more than 1000 Saccharomyces cerevisiae genomes, including 167 strains frequently used in bioenergy research. Zymomonas mobilis, an increasingly popular bacterial bioenergy research model, is also supported. CRISpy-pop is available as a web application (https://CRISpy-pop.glbrc.org/) with an intuitive graphical user interface. CRISpy-pop also cross-references the human genome to allow users to avoid the selection of sgRNAs with potential biosafety concerns. Additionally, CRISpy-pop predicts the strain coverage of each guide RNA within the supported strain sets, which aids in functional population genetic studies. Finally, we validate how CRISpy-pop can accurately predict the activity of guide RNAs across strains using population genomic data.

genetics↗

bioRxiv2020

Strong effect of Penicillium roqueforti populations on volatile and metabolic compounds responsible for aromas, flavour and texture in blue cheeses

Studies of food microorganism domestication can provide important insight into adaptation mechanisms and lead to commercial applications. Penicillium roqueforti is a fungus with four genetically differentiated populations, two of which were independently domesticated for blue cheese-making, with the other two populations thriving in other environments. Most blue cheeses are made with strains from a single P. roqueforti population, whereas Roquefort cheeses are inoculated with strains from a second population. We made blue cheeses in accordance with the production specifications for Roquefort-type cheeses, inoculating each cheese with a single P. roqueforti strain, using a total of three strains from each of the four populations. We investigated differences between the cheeses made with the strains from the four P. roqueforti populations, in terms of the induced flora, the proportion of blue color, water activity and the identity and abundance of aqueous and organic metabolites as proxies for proteolysis and lipolysis as well as volatile compounds responsible for flavor and aroma. We found that the population-of-origin of the P. roqueforti strains used for inoculation had a minor impact on bacterial diversity and no effect on the abundance of the main microorganism. The cheeses produced with P. roqueforti strains from cheese populations had a higher percentage of blue area and a higher abundance of the volatile compounds typical of blue cheeses, such as methyl ketones and secondary alcohols. In particular, the Roquefort strains produced higher amounts of these aromatic compounds, partly due to more efficient proteolysis and lipolysis. The Roquefort strains also led to cheeses with a lower water availability, an important feature for preventing spoilage in blue cheeses, which is subject to controls for the sale of Roquefort cheese. The typical appearance and flavors of blue cheeses thus result from human selection on P. roqueforti, leading to the acquisition of specific features by the two cheese populations. These findings have important implications for our understanding of adaptation and domestication, and for cheese improvement.

evolutionary biology↗

bioRxiv2017

Genome-wide association across Saccharomyces cerevisiae strains reveals substantial variation in underlying gene requirements for toxin tolerance.

Cellulosic plant biomass is a promising sustainable resource for generating alternative biofuels and biochemicals with microbial factories. But a remaining bottleneck is engineering microbes that are tolerant of toxins generated during biomass processing, because mechanisms of toxin defense are only beginning to emerge. Here, we exploited natural diversity in 165 Saccharomyces cerevisiae strains isolated from diverse geographical and ecological niches, to identify mechanisms of hydrolysate-toxin tolerance. We performed genome-wide association (GWA) analysis to identify genetic variants underlying toxin tolerance, and gene knockouts and allele-swap experiments to validate the involvement of implicated genes. In the process of this work, we uncovered a surprising difference in genetic architecture depending on strain background: in all but one case, knockout of implicated genes had a significant effect on toxin tolerance in one strain, but no significant effect in another strain. In fact, whether or not the gene was involved in tolerance in each strain background had a bigger contribution to strain-specific variation than allelic differences. Our results suggest a major difference in the underlying network of causal genes in different strains, suggesting that mechanisms of hydrolysate tolerance are very dependent on the genetic background. These results could have significant implications for interpreting GWA results and raise important considerations for engineering strategies for industrial strain improvement.\n\nAuthor summaryUnderstanding the genetic architecture of complex traits is important for elucidating the genotype-phenotype relationship. Many studies have sought genetic variants that underlie phenotypic variation across individuals, both to implicate causal variants and to inform on architecture. Here we used genome-wide association analysis to identify genes and processes involved in tolerance of toxins found in plant-biomass hydrolysate, an important substrate for sustainable biofuel production. We found substantial variation in whether or not individual genes were important for tolerance across genetic backgrounds. Whether or not a gene was important in a given strain background explained more variation than the alleleic differences in the gene. These results suggest substantial variation in gene contributions, and perhaps underlying mechanisms, of toxin tolerance.

genomics↗

bioRxiv2017

Single-cell RNA-seq reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single S. cerevisiae cells treated with and without salt stress, to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells decouple expression of ribosomal protein genes from the environmental stress response, in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results reveal that cells maintain a cellular filter against decoupled bursts of transcription-factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.

systems biology↗

bioRxiv2017

Network inference reveals novel connections in pathways regulating growth and defense in the yeast salt response

Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae, the upstream regulatory network controlling protein phosphorylation is less well dissected. Here, we developed a computational approach to infer the signaling network that regulates phosphorylation changes in response to salt stress. The method uses integer linear programming (ILP) to integrate stress-responsive phospho-proteome responses in wild-type and mutant strains, predicted phosphorylation motifs on groups of coregulated peptides, and published protein interaction data. A key advance is that by grouping peptides into submodules before inference, the method can overcome missing protein interactions in published datasets to predict novel, stress-dependent protein interactions and phosphorylation events. The network we inferred predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. We confirmed several network predictions with co-immunoprecipitations coupled with mass-spectrometry protein identification and mutant phospho-proteomic analysis. Results show that the cAMP-phosphodiesterase Pde2 physically interacts with many stress-regulated transcription factors targeted by PKA, and that reduced phosphorylation of those factors during stress requires the Rck2 kinase that we show physically interacts with Pde2. Together, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during osmotic stress.

systems biology↗