Metabolic heterogeneity and cross-feeding within isogenic yeast populations captured by DILAC

[1]  J. Rabinowitz,et al.  Glucose feeds the tricarboxylic acid cycle via excreted ethanol in fermenting yeast , 2022, Nature Chemical Biology.

[2]  Guo Ci Teo,et al.  dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts , 2022, Nature Communications.

[3]  Christoph B. Messner,et al.  The proteomic landscape of genome-wide genetic perturbations , 2022, Cell.

[4]  Christoph B. Messner,et al.  Microbial communities form rich extracellular metabolomes that foster metabolic interactions and promote drug tolerance , 2022, Nature Microbiology.

[5]  M. Wühr,et al.  Gut bacterial nutrient preferences quantified in vivo , 2022, Cell.

[6]  O. Kuipers,et al.  Diversity of bet‐hedging strategies in microbial communities—Recent cases and insights , 2021, WIREs mechanisms of disease.

[7]  T. Bollenbach,et al.  Intron-mediated induction of phenotypic heterogeneity , 2021, Nature.

[8]  L. Váchová,et al.  Spatially structured yeast communities: Understanding structure formation and regulation with omics tools , 2021, Computational and structural biotechnology journal.

[9]  Christoph B. Messner,et al.  Ultra-fast proteomics with Scanning SWATH , 2021, Nature Biotechnology.

[10]  Ben C. Collins,et al.  diaPASEF: parallel accumulation–serial fragmentation combined with data-independent acquisition , 2020, Nature Methods.

[11]  Lisbeth Olsson,et al.  The future of self-selecting and stable fermentations , 2020, Journal of industrial microbiology & biotechnology.

[12]  S. Krishna,et al.  Resource plasticity-driven carbon-nitrogen budgeting enables specialization and division of labor in a clonal community , 2020, eLife.

[13]  J. Nielsen,et al.  Proteome reallocation from amino acid biosynthesis to ribosomes enables yeast to grow faster in rich media , 2020, Proceedings of the National Academy of Sciences.

[14]  Dominika M. Wloch-Salamon,et al.  Aspects of Multicellularity in Saccharomyces cerevisiae Yeast: A Review of Evolutionary and Physiological Mechanisms , 2020, Genes.

[15]  L. Váchová,et al.  Cell Distribution within Yeast Colonies and Colony Biofilms: How Structure Develops , 2020, International journal of molecular sciences.

[16]  K. Verstrepen,et al.  A new protocol for single-cell RNA-seq reveals stochastic gene expression during lag phase in budding yeast , 2020, eLife.

[17]  A. Beyer,et al.  Pyruvate kinase variant of fission yeast tunes carbon metabolism, cell regulation, growth and stress resistance , 2020, Molecular systems biology.

[18]  Yasset Perez-Riverol,et al.  The ProteomeXchange consortium in 2020: enabling ‘big data’ approaches in proteomics , 2019, Nucleic Acids Res..

[19]  Joel Nothman,et al.  SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python , 2019, ArXiv.

[20]  Jan Michiels,et al.  Bacterial Heterogeneity and Antibiotic Survival: Understanding and Combatting Persistence and Heteroresistance. , 2019, Molecular cell.

[21]  Christoph B. Messner,et al.  DIA-NN: Neural networks and interference correction enable deep proteome coverage in high throughput , 2019, Nature Methods.

[22]  O. Méndez-Lucio,et al.  Lysine harvesting is an antioxidant strategy and triggers underground polyamine metabolism , 2019, Nature.

[23]  M. Kleiner.  Metaproteomics: Much More than Measuring Gene Expression in Microbial Communities , 2019, mSystems.

[24]  J. Vilo,et al.  g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update) , 2019, Nucleic Acids Res..

[25]  Dayanne M. Castro,et al.  Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments , 2019, bioRxiv.

[26]  S. Krishna,et al.  Metabolic constraints drive self-organization of specialized cell groups , 2019, bioRxiv.

[27]  V. Shahrezaei,et al.  Single-cell imaging and RNA sequencing reveal patterns of gene expression heterogeneity during fission yeast growth and adaptation , 2019, Nature Microbiology.

[28]  M. Ackermann,et al.  Emergent microscale gradients give rise to metabolic cross-feeding and antibiotic tolerance in clonal bacterial populations , 2019, bioRxiv.

[29]  L. Steinmetz,et al.  Sensitive high-throughput single-cell RNA-Seq reveals within-clonal transcript-correlations in yeast populations , 2019, Nature Microbiology.

[30]  Martin Eisenacher,et al.  The PRIDE database and related tools and resources in 2019: improving support for quantification data , 2018, Nucleic Acids Res..

[31]  M. Taubert.  SIP-Metaproteomics: Linking Microbial Taxonomy, Function, and Activity. , 2019, Methods in molecular biology.

[32]  M. Siegal,et al.  Control of nongenetic heterogeneity in growth rate and stress tolerance of Saccharomyces cerevisiae by cyclic AMP-regulated transcription factors , 2018, PLoS genetics.

[33]  Matthias Heinemann,et al.  Metabolic heterogeneity in clonal microbial populations. , 2018, Current opinion in microbiology.

[34]  Jian-Jun Dong,et al.  Transcriptional profiling of amino acid supplementation and impact on aroma production in a lager yeast fermentation , 2018, Journal of the Institute of Brewing.

[35]  Christopher P. Long,et al.  Metabolism in dense microbial colonies: 13C metabolic flux analysis of E. coli grown on agar identifies two distinct cell populations with acetate cross-feeding. , 2018, Metabolic engineering.

[36]  S. Oeljeklaus,et al.  Complete Native Stable Isotope Labeling by Amino Acids of Saccharomyces cerevisiae for Global Proteomic Analysis , 2018, Analytical chemistry.

[37]  J. Berman,et al.  Antifungal tolerance is a subpopulation effect distinct from resistance and is associated with persistent candidemia , 2018, Nature Communications.

[38]  Peer Bork,et al.  iPath3.0: interactive pathways explorer v3 , 2018, Nucleic Acids Res..

[39]  Roland Bruderer,et al.  Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition , 2018, Scientific Reports.

[40]  Michael J MacCoss,et al.  Panorama Public: A Public Repository for Quantitative Data Sets Processed in Skyline* , 2018, Molecular & Cellular Proteomics.

[41]  G. Gilfillan,et al.  Transcriptome Remodeling of Differentiated Cells during Chronological Ageing of Yeast Colonies: New Insights into Metabolic Differentiation , 2018, Oxidative medicine and cellular longevity.

[42]  Anil Wipat,et al.  Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling , 2017, Front. Microbiol..

[43]  M. Ralser,et al.  A High-Throughput Method for the Quantitative Determination of Free Amino Acids in Saccharomyces cerevisiae by Hydrophilic Interaction Chromatography-Tandem Mass Spectrometry. , 2017, Cold Spring Harbor protocols.

[44]  Manuel A. S. Santos,et al.  Phenotypic heterogeneity promotes adaptive evolution , 2017, PLoS biology.

[45]  A. Zelezniak,et al.  Functional Metabolomics Describes the Yeast Biosynthetic Regulome , 2016, Cell.

[46]  N. Jehmlich,et al.  Protein-SIP in environmental studies. , 2016, Current opinion in biotechnology.

[47]  Kate Campbell,et al.  Cell‐to‐cell heterogeneity emerges as consequence of metabolic cooperation in a synthetic yeast community , 2016, Biotechnology journal.

[48]  Michael Springer,et al.  Identifying Metabolic Subpopulations from Population Level Mass Spectrometry , 2016, PloS one.

[49]  R. Schwarz,et al.  The metabolic background is a global player in Saccharomyces gene expression epistasis , 2016, Nature Microbiology.

[50]  M. Keller,et al.  Self-establishing communities enable cooperative metabolite exchange in a eukaryote , 2015, eLife.

[51]  Miguel C. Teixeira,et al.  New Mechanisms of Flucytosine Resistance in C. glabrata Unveiled by a Chemogenomics Analysis in S. cerevisiae , 2015, PloS one.

[52]  S. Gygi,et al.  Comprehensive Temporal Protein Dynamics during the Diauxic Shift in Saccharomyces cerevisiae , 2015, Molecular & Cellular Proteomics.

[53]  Zaida Luthey-Schulten,et al.  Spatially-resolved metabolic cooperativity within dense bacterial colonies , 2015, BMC Systems Biology.

[54]  Martin Taubert,et al.  MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics. , 2015, Journal of proteome research.

[55]  B. Regenberg,et al.  Saccharomyces cerevisiae biofilm tolerance towards systemic antifungals depends on growth phase , 2014, BMC Microbiology.

[56]  Paul D. Adams,et al.  A Peptide-Based Method for 13C Metabolic Flux Analysis in Microbial Communities , 2014, PLoS Comput. Biol..

[57]  Marco Y. Hein,et al.  Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * , 2014, Molecular & Cellular Proteomics.

[58]  A. Murray,et al.  Growing Yeast into Cylindrical Colonies , 2014, Biophysical journal.

[59]  S. Avery,et al.  Phenotypic heterogeneity is a selected trait in natural yeast populations subject to environmental stress , 2013, Environmental microbiology.

[60]  T. Walther,et al.  Native SILAC: Metabolic Labeling of Proteins in Prototroph Microorganisms Based on Lysine Synthesis Regulation* , 2013, Molecular & Cellular Proteomics.

[61]  Wenying Shou,et al.  Strong inter-population cooperation leads to partner intermixing in microbial communities , 2013, eLife.

[62]  T. Beilharz,et al.  Transcriptional Profiling of a Yeast Colony Provides New Insight into the Heterogeneity of Multicellular Fungal Communities , 2012, PloS one.

[63]  U. Sauer,et al.  A prototrophic deletion mutant collection for yeast metabolomics and systems biology , 2012, Nature Biotechnology.

[64]  L. Váchová,et al.  Cell differentiation within a yeast colony: metabolic and regulatory parallels with a tumor-affected organism. , 2012, Molecular cell.

[65]  Sasha F. Levy,et al.  Bet Hedging in Yeast by Heterogeneous, Age-Correlated Expression of a Stress Protectant , 2012, PLoS biology.

[66]  K. Jefimovs,et al.  Carbon-13 labelling strategy for studying the ATP metabolism in individual yeast cells by micro-arrays for mass spectrometry. , 2011, Molecular bioSystems.

[67]  Brendan MacLean,et al.  Bioinformatics Applications Note Gene Expression Skyline: an Open Source Document Editor for Creating and Analyzing Targeted Proteomics Experiments , 2022 .

[68]  K. Foster,et al.  FLO1 Is a Variable Green Beard Gene that Drives Biofilm-like Cooperation in Budding Yeast , 2008, Cell.

[69]  M. Grimson,et al.  Spatial-temporal modelling of bacterial colony growth on solid media. , 2008, Molecular bioSystems.

[70]  Jean-Marc Daran,et al.  Transcriptional responses of Saccharomyces cerevisiae to preferred and nonpreferred nitrogen sources in glucose-limited chemostat cultures. , 2007, FEMS yeast research.

[71]  Kevin Kontos,et al.  Effect of 21 Different Nitrogen Sources on Global Gene Expression in the Yeast Saccharomyces cerevisiae , 2007, Molecular and Cellular Biology.

[72]  Simon V. Avery,et al.  Microbial cell individuality and the underlying sources of heterogeneity , 2006, Nature Reviews Microbiology.

[73]  Kara Dolinski,et al.  Homeostatic adjustment and metabolic remodeling in glucose-limited yeast cultures. , 2005, Molecular biology of the cell.

[74]  S. Leibler,et al.  Bacterial Persistence as a Phenotypic Switch , 2004, Science.

[75]  D. Yuan.  Zinc-regulated genes in Saccharomyces cerevisiae revealed by transposon tagging. , 2000, Genetics.

[76]  H J Schüller,et al.  The acetyl‐CoA synthetase gene ACS2 of the yeast Saccharomyces cerevisiae is coregulated with structural genes of fatty acid biosynthesis by the transcriptional activators Ino2p and Ino4p , 1997, FEBS letters.

[77]  E. Dubois,et al.  Repression of the genes for lysine biosynthesis in Saccharomyces cerevisiae is caused by limitation of Lys14-dependent transcriptional activation , 1994, Molecular and cellular biology.

[78]  R. Bode,et al.  Distribution of three lysine‐catabolizing enzymes in various yeast species , 1991 .

[79]  J. Gancedo,et al.  Studies on the regulation and localization of the glyoxylate cycle enzymes in Saccharomyces cerevisiae. , 2005 .

[80]  C. Hinshelwood,et al.  Factors affecting the growth of bacterial colonies on agar plates , 1968, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[81]  S. Pirt,et al.  A kinetic study of the mode of growth of surface colonies of bacteria and fungi. , 1967, Journal of general microbiology.

[82]  H. Kornberg.  The role and control of the glyoxylate cycle in Escherichia coli. , 1966, The Biochemical journal.