Biology subjects

Sherlock, G.

Publications and source records attributed to Sherlock, G..

13 recordsLinked to original sources

bioRxiv2026

The Candida Genome Database: New Interface and New Tools

The Candida Genome Database (CGD; www.candidagenome.org) is both a model organism database and a fungal pathogen database. As a model organism database, CGD stores data for Candida albicans, which serves as a model species both for other Candida spp. and for non-Candida fungi that form biofilms and undergo routine morphogenic switching. As a fungal pathogen database, CGD now hosts locus pages for six species of the best-studied pathogenic fungi in the Candida group. Pathogenic Candida species have become increasingly drug resistant and there is thus a pressing need for research into basic Candida biology, epidemiology, phylogeny, and potential new antifungals, as well as a single location where all of the available data are collected, curated, and made easily searchable. CGD curates the gene-based Candida experimental literature in real time, extracting, organizing and standardizing gene annotations. CGD also links clinical data on disease to relevant Literature Topics to improve searchability for clinical researchers. Because CGD curates the literature for multiple species and most research focuses on aspects related to pathogenicity, we focus our curation efforts on assigning Literature Topic tags, collecting detailed mutant phenotype data, and assigning controlled Gene Ontology terms with accompanying evidence codes. Our Summary pages for each locus include the primary name and all aliases for that locus, a description of the gene and/or gene product, detailed ortholog information with links, a synteny view, a JBrowse window with a visual view of the gene on its chromosome, links to Phenotype, Gene Ontology, Interactions, and Expression pages, as well as sequence information, references cited on the summary page itself, and any locus notes. The database also serves as a community hub, where we link to various types of reference material of relevance to Candida researchers, including colleague information, news, and notice of upcoming meetings. We routinely survey the community to learn how the field is evolving and how needs may have changed. Here we describe CGDs new modern web interface and multiple new tools that have been added in the last 6 months, allowing, among other things, users to better understand the available expression data for a locus and seamlessly switch between species for a given locus.

genetics↗

bioRxiv2026

Capsular polysaccharide can sensitize bacteria to non-antibiotic drugs

Medications administered over long durations, such as phenothiazine antipsychotics, accumulate in the gut at concentrations that affect microbial growth. However, the bacterial features influencing sensitivity to these non-antibiotics remain poorly understood. Bacterial capsular polysaccharides (CPSs) typically confer protection against environmental stressors, including chemical, viral, and immunological pressures within the gut. But their roles under non-antibiotic drug pressure are unknown. Here, we show that the K5 CPS of Escherichia coli Nissle 1917 (EcN) sensitizes it to thioridazine (TDZ) and related antipsychotics. Among a panel of E. coli strains grown in minimal medium, EcN exhibited the highest sensitivity to TDZ. Experimentally evolving EcN under gut-relevant TDZ concentrations selected for resistant populations with convergent variants affecting the CPS locus, and TDZ-resistant clones correspondingly had lower CPS expression than their drug-susceptible counterparts. Genetic, transcriptomic, and phenotypic analyses confirmed that the K5 CPS enhances, rather than mitigates, TDZ sensitivity. These findings demonstrate that canonically protective surface structures can become vulnerabilities under non-antibiotic pharmaceutical pressure. Human medications may therefore inadvertently shape the expression and evolution of bacterial surface structures in the gastrointestinal tract, challenging presumptions of CPS-mediated environmental protection.

microbiology↗

bioRxiv2024

The Candida Genome Database: Annotation and Visualization Updates

The Candida Genome Database (CGD; www.candidagenome.org) is unique in being both a model organism database and a fungal pathogen database. As a fungal pathogen database, CGD hosts locus pages for five species of the best-studied pathogenic fungi in the Candida group. As a model organism database, the species Candida albicans serves as a model both for other Candida spp. and for non-Candida fungi that form biofilms and undergo routine morphogenic switching from the planktonic form to the filamentous form, which is not done by other model yeasts. As pathogenic Candida species have become increasingly drug resistant, the high lethality of invasive candidiasis in immunocompromised people is increasingly alarming. There is a pressing need for additional research into basic Candida biology, epidemiology and phylogeny, and potential new antifungals. CGD serves the needs of this diverse research community by curating the entire gene-based Candida experimental literature as it is published, extracting, organizing and standardizing gene annotations. Most recently, we have begun linking clinical data on disease to relevant Literature Topics to improve searchability for clinical researchers. Because CGD curates for multiple species and most research focuses on aspects related to pathogenicity, we focus our curation efforts on assigning Literature Topic tags, collecting detailed mutant phenotype data, and assigning controlled Gene Ontology terms with accompanying evidence codes. Our Summary pages for each feature include the primary name and all aliases for that locus, a description of the gene and/or gene product, detailed ortholog information with links, a JBrowse window with a visual view of the gene on its chromosome, summarized phenotype, Gene Ontology, and sequence information, references cited on the summary page itself, and any locus notes. The database serves as a community hub, where we link to various types of reference material of relevance to Candida researchers, including colleague information, news, and notice of upcoming meetings. We routinely survey the community to learn how the field is evolving and how needs may have changed. A key future challenge is management of the flood of high-throughput expression data to make it as useful as possible to as many researchers as possible. The central challenge for any community database is to turn data into knowledge, which the community can access, use, and build upon.

genetics↗

bioRxiv2024

Saccharomyces Genome Database: Advances in Genome Annotation, Expanded Biochemical Pathways, and Other Key Enhancements

Budding yeast (Saccharomyces cerevisiae) is the most extensively characterized eukaryotic model organism and has long been used to gain insight into the fundamentals of genetics, cellular biology, and the functions of specific genes and proteins. The Saccharomyces Genome Database (SGD) is a scientific resource that provides information about the genome and biology of S. cerevisiae. For more than 30 years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation for budding yeast along with search and analysis tools to explore these data. Here we describe recent updates at SGD, including the two most recent reference genome annotation updates, expanded biochemical pathways representation, changes to SGD search and data files, and other enhancements to the SGD website and user interface. These activities are part of our continuing effort to promote insights gained from yeast to enable the discovery of functional relationships between sequence and gene products in fungi and higher eukaryotes.

genetics↗

bioRxiv2023

Arrayed in vivo barcoding for multiplexed sequence verification of plasmid DNA and demultiplexing of pooled libraries

Sequence verification of plasmid DNA is critical for many cloning and molecular biology workflows. To leverage high-throughput sequencing, several methods have been developed that add a unique DNA barcode to individual samples prior to pooling and sequencing. However, these methods require an individual plasmid extraction and/or in vitro barcoding reaction for each sample processed, limiting throughput and adding cost. Here, we develop an arrayed in vivo plasmid barcoding platform that enables pooled plasmid extraction and library preparation for Oxford Nanopore sequencing. This method has a high accuracy and recovery rate, and greatly increases throughput and reduces cost relative to other plasmid barcoding methods or Sanger sequencing. We use in vivo barcoding to sequence verify >45,000 plasmids and show that the method can be used to transform error-containing dispersed plasmid pools into sequence-perfect arrays or well-balanced pools. In vivo barcoding does not require any specialized equipment beyond a low-overhead Oxford Nanopore sequencer, enabling most labs to flexibly process hundreds to thousands of plasmids in parallel.

synthetic biology↗

bioRxiv2022

An Improved Algorithm for Inferring Mutational Parameters from Bar-Seq Evolution Experiments

Genetic barcoding provides a high-throughput way to simultaneously track the frequencies of large numbers of competing and evolving microbial lineages. However making inferences about the character of the evolution that is taking place remains a difficult task. Here we describe a step toward more accurate inference of fitness effects and establishment times of beneficial mutations, which builds upon a prior method by enforcing self-consistency between the population mean fitness and the individual effects of mutations within lineages. By testing our inference method on a simulation of 40,000 barcoded lineages evolving in serial batch culture, we find that this new method outperforms its predecessor, identifying more adaptive mutations and more accurately inferring their mutational parameters. We have made available our code for the joint Bayesian inference of population mean fitness and lineage-specific mutational parameters, in the hope that it can find broader use by the microbial evolution community.

evolutionary biology↗

bioRxiv2022

S. cerevisiae cells can grow without the Pds5 cohesin subunit

During DNA replication, the newly created sister chromatids are held together until their separation at anaphase. The cohesin complex is in charge of creating and maintaining sister-chromatid cohesion (SCC) in all eukaryotes. In S. cerevisiae cells, cohesin is composed of two elongated proteins, Smc1 and Smc3, bridged by the kleisin Mcd1/Scc1. The latter also acts as a scaffold for three additional proteins, Scc3/Irr1, Wpl1/Rad61, and Pds5. Although the HEAT-repeat protein Pds5 is essential for cohesion, its precise function is still debated. Deletion of the ELG1 gene, encoding a PCNA unloader, can partially suppress the temperature-sensitive pds5-1 allele, but not a complete deletion of PDS5. We carried out a genetic screen for high copy number suppressors and another for spontaneously arising mutants, allowing the survival of a pds5{Delta} elg1{Delta} strain. Our results show that cells remain viable in the absence of Pds5 provided that there is both an elevation in the level of Mcd1 (which can be due to mutations in the CLN2 gene, encoding a G1 cyclin), and an increase in the level of SUMO-modified PCNA on chromatin (caused by lack of PCNA unloading in elg1{Delta} mutants). The elevated SUMO-PCNA levels increase the recruitment of the Srs2 helicase, which evicts Rad51 molecules from the moving fork, creating ssDNA regions that serve as sites for increased cohesin loading and SCC establishment. Thus, our results delineate a double role for Pds5 in protecting the cohesin ring and interacting with the DNA replication machinery. IMPORTANCESister chromatid cohesion is vital for faithful chromosome segregation, chromosome folding into loops, and gene expression. A multisubunit protein complex known as cohesin holds the sister chromatids from S-phase until the anaphase stage. In this study, we explore the function of the essential cohesin subunit Pds5 in the regulation of sister chromatid cohesion. We performed two independent genetic screens to bypass the function of the Pds5 protein. We observe that Pds5 protein is a cohesin stabilizer, and elevating the levels of Mcd1 protein along with SUMO-PCNA accumulation on chromatin can compensate for the loss of the PDS5 gene. In addition, Pds5 plays a role in coordinating the DNA replication and sister chromatid cohesion establishment. This work elucidates the function of cohesin subunit Pds5, the G1 cyclin Cln2, and replication factors PCNA, Elg1 and Srs2 in the proper regulation of sister chromatid cohesion.

genetics↗

bioRxiv2022

Paths to adaptation under fluctuating nitrogen starvation: The spectrum of adaptive mutations in Saccharomyces cerevisiae is shaped by transposons and microhomology-mediated recombination

There are many mechanisms that give rise to genomic change: while point mutations are often emphasized in genomic analyses, evolution acts upon many other types of genetic changes that can result in less subtle perturbations. Changes in chromosome structure, DNA copy number, and novel transposon insertions all create large genomic changes, which can have correspondingly large impacts on phenotypes and fitness. In this study we investigate the spectrum of adaptive mutations that arise in a population under consistently fluctuating nitrogen conditions. We specifically contrast these adaptive alleles and the mutational mechanisms that create them, with mechanisms of adaptation under batch glucose limitation and constant selection in low, non-fluctuating nitrogen conditions. We observe that retrotransposon activity accounts for a substantial number of adaptive events, along with microhomology-mediated mechanisms of insertion, deletion, and gene conversion. In addition to loss of function alleles, which are often exploited in genetic screens, we identify adaptive gain of function alleles and alleles acting through as-of-yet unclear mechanisms. Taken together, our findings emphasize that how selection (fluctuating vs. non-fluctuating) is applied also shapes adaptation, just as the selective pressure (nitrogen vs. glucose) does itself. Fluctuating environments can activate different mutational mechanisms, shaping adaptive events accordingly. Experimental evolution, which allows a wider array of adaptive events to be assessed, is thus a complementary approach to both classical genetic screens and natural variation studies to characterize the genotype-to-phenotype-to-fitness map.

evolutionary biology↗

bioRxiv2020

Quantifying the interplay between rapid bacterial evolution within the mouse intestine and transmission between hosts

Due to limitations on high-resolution strain tracking, selection dynamics during gut-microbiota colonization and transmission between hosts remain mostly mysterious. Here, we introduced hundreds of barcoded Escherichia coli strains into germ-free mice and quantified strain-level dynamics and metagenomic changes. Mutants involved in motility and utilization of abundant metabolites were reproducibly selected within days. Even with rapid selection, coprophagy enforced similar barcode distributions across co-housed mice. Whole-genome sequencing of hundreds of isolates quantified evolutionary dynamics and revealed linked alleles. A population-genetics model predicted substantial fitness advantages for certain mutants and that migration accounted for ~10% of the resident microbiota each day. Treatment with ciprofloxacin demonstrated the interplay between selection and transmission. While initial colonization was mostly uniform, in two mice a bottleneck reduced diversity and selected for ciprofloxacin resistance in the absence of drug. These findings highlight the interplay between environmental transmission and rapid, deterministic selection during evolution of the intestinal microbiota.

microbiology↗

bioRxiv2020

Changes in the distribution of fitness effects and adaptive mutational spectra following a single first step towards adaptation

The fitness effects of random mutations are contingent upon the genetic and environmental contexts in which they occur, and this contributes to the unpredictability of evolutionary outcomes at the molecular level. Despite this unpredictability, the rate of adaptation in homogeneous environments tends to decrease over evolutionary time, due to diminishing returns epistasis, causing relative fitness gains to be predictable over the long term. Here, we studied the extent of diminishing returns epistasis and the changes in the adaptive mutational spectra after yeast populations have already taken their first adaptive mutational step. We used three distinct adaptive clones that arose under identical conditions from a common ancestor, from which they diverge by a single point mutation, to found populations that we further evolved. We followed the evolutionary dynamics of these populations by lineage tracking and determined adaptive outcomes using fitness assays and whole genome sequencing. We found compelling evidence for diminishing returns: fitness gains during the 2nd step of adaptation are smaller than those of the 1st step, due to a compressed distribution of fitness effects in the 2nd step. We also found strong evidence for historical contingency at the genic level: the beneficial mutational spectra of the 2nd-step adapted genotypes differ with respect to their ancestor and to each other, despite the fact that the three founders 1st-step mutations provided their fitness gains due to similar phenotypic improvements. While some targets of selection in the second step are shared with those seen in the common ancestor, other targets appear to be contingent on the specific first step mutation, with more phenotypically similar founding clones having more similar adaptive mutational spectra. Finally, we found that disruptive mutations, such as nonsense and frameshift, were much more common in the first step of adaptation, contributing an additional way that both diminishing returns and historical contingency are evident during 2nd step adaptation.

evolutionary biology↗

bioRxiv2019

Adaptation is influenced by the complexity of environmental change during evolution in a dynamic environment

The environmental conditions of microorganisms habitats may fluctuate in unpredictable ways, such as changes in temperature, carbon source, pH, and salinity to name a few. Environmental heterogeneity presents a challenge to microorganisms, as they have to adapt not only to be fit under a specific condition, but they must also be robust across many conditions and be able to deal with the switch between conditions itself. While experimental evolution has been used to gain insight into the adaptive process, this has largely been in either unvarying or consistently varying conditions. In cases where changing environments have been investigated, relatively little is known about how such environments influence the dynamics of the adaptive process itself, as well as the genetic and phenotypic outcomes. We designed a systematic series of evolution experiments where we used two growth conditions that have differing timescales of adaptation and varied the rate of switching between them. We used lineage tracking to follow adaptation, and whole genome sequenced adaptive clones from each of the experiments. We find that both the switch rate and the order of the conditions influences adaptation, and that switching can both speed up and slow down adaptation, depending on those parameters. We also find different adaptive outcomes, at both the genetic and phenotypic levels, even when populations spent the same amount of total time in the two different conditions, but the order and/or switch rate differed. Thus, in a variable environment adaptation depends not only on the nature of the conditions and phenotypes under selection, but also on the complexity of the manner in which those conditions are combined to result in a given dynamic environment.

evolutionary biology↗

bioRxiv2019

Single Nucleotide Mapping of the Locally Accessible Trait Space in Yeast Reveals Pareto Fronts that Constrain Initial Adaptation

Tradeoffs constrain the improvement of performance of multiple traits simultaneously. Such tradeoffs define Pareto fronts, which represent a set of optimal individuals that cannot be improved in any one trait without reducing performance in another. Surprisingly, experimental evolution often yields genotypes with improved performance in all measured traits, perhaps indicating an absence of tradeoffs at least in the short-term. Here we densely sample adaptive mutations in S. cerevisiae to ask whether first-step adaptive mutations result in tradeoffs during the growth cycle. We isolated thousands of adaptive clones evolved under carefully chosen conditions and quantified their performances in each part of the growth cycle. We too find that some first-step adaptive mutations can improve all traits to a modest extent. However, our dense sampling allowed us to identify tradeoffs and establish the existence of Pareto fronts between fermentation and respiration, and between respiration and stationary phases. Moreover, we establish that no single mutation in the ancestral genome can circumvent the detected tradeoffs. Finally, we sequenced hundreds of these adaptive clones, revealing novel targets of adaptation and defining the genetic basis of the identified tradeoffs.

evolutionary biology↗

bioRxiv2019

Evolutionary dynamics of de novo mutations and mutant lineages arising in a simple, constant environment

A large, asexual population founded by a single clone evolves into a population teeming with many, whether or not its environment is structured, and whether or not resource levels are constant or fluctuating. The maintenance of genetic complexity in such populations has been attributed to balancing selection, or to either clonal interference or clonal reinforcement, arising from antagonistic or synergistic interactions, respectively. To distinguish among these possibilities, to identify targets of selection and establish when and how often they are hit, as well as to gain insight into how de novo mutations interact, we carried out 300-500 generation glucose-limited chemostat experiments founded by an E. coli mutator. To discover all de novo mutations reaching [≥]1% frequency, we performed whole-genome, whole-population sequencing at [~]1000X-coverage every 50 generations. To establish linkage relationships among these mutations and depict the dynamics of evolving lineages we sequenced the genomes of 96 clones from each population when allelic diversity was greatest. Operon-specific mutations that enhance glucose uptake arose to high frequency first, followed by global regulatory mutations. Late-arising mutations were related to energy conservation as well as to mitigating pleiotropic effects wrought by earlier regulatory changes. We discovered extensive polymorphism at relatively few loci, with identical mutations arising independently in different lineages, both between and within replicate populations. Out of more than 3,000 SNPs detected in nearly 1,800 genes or intergenic regions, only 17 reached a frequency [≥] 98%, indicating that the evolutionary dynamics of adaptive lineages was dominated by clonal interference. Finally, our data show that even when mutational input is increased by an ancestral defect in DNA repair, the spectrum of beneficial mutations that reach high frequency in a simple, constant resource-limited environment is narrow, resulting in extreme parallelism where many adaptive mutations arise but few ever go to fixation. Author SummaryMicrobial evolution experiments open a window on the tempo and dynamics of evolutionary change in asexual populations. High-throughput sequencing can be used to catalog de novo mutations, determine in which lineages they arise, and assess allelic interactions by tracking the fate of those lineages. This adaptive genetics approach makes it possible to discover whether clonal interactions are antagonistic or synergistic, and complements genetic screens of induced deleterious/loss-of-function mutants. We carried out glucose-limited chemostat experiments founded by an E. coli mutator and performed whole-genome, whole-population sequencing on 300-500 generation evolutions, cataloging 3,346 de novo mutations that reached [≥]1% frequency. Mutations enhancing glucose uptake rose to high frequency first, followed by global regulatory changes that modulate growth rate and limiting resource assimilation, then by mutations that favor energy conservation or mitigate pleiotropic effects of earlier regulatory changes. We discovered that a few loci were highly polymorphic, with identical mutations arising independently in different lineages, both between and within replicate populations. Thus, when mutational input is increased by an ancestral defect in DNA repair, the spectrum of beneficial mutations that arises under constant resource-limitation is narrow, resulting in extreme parallelism where many adaptive mutations arise but few ever become fixed.

evolutionary biology↗