1
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O'Brien JJ, Raj A, Gaun A, Waite A, Li W, Hendrickson DG, Olsson N, McAllister FE. A data analysis framework for combining multiple batches increases the power of isobaric proteomics experiments. Nat Methods 2024; 21:290-300. [PMID: 38110636 DOI: 10.1038/s41592-023-02120-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 10/31/2023] [Indexed: 12/20/2023]
Abstract
We present a framework for the analysis of multiplexed mass spectrometry proteomics data that reduces estimation error when combining multiple isobaric batches. Variations in the number and quality of observations have long complicated the analysis of isobaric proteomics data. Here we show that the power to detect statistical associations is substantially improved by utilizing models that directly account for known sources of variation in the number and quality of observations that occur across batches.In a multibatch benchmarking experiment, our open-source software (msTrawler) increases the power to detect changes, especially in the range of less than twofold changes, while simultaneously increasing quantitative proteome coverage by utilizing more low-signal observations. Further analyses of previously published multiplexed datasets of 4 and 23 batches highlight both increased power and the ability to navigate complex missing data patterns without relying on unverifiable imputations or discarding reliable measurements.
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Affiliation(s)
| | - Anil Raj
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | | | - Adam Waite
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | - Wenzhou Li
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | | | - Niclas Olsson
- Calico Life Sciences LLC, South San Francisco, CA, USA
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2
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Increasing the analytic power for multi-batch proteome profiling with isobaric mass tags. Nat Methods 2024; 21:168-169. [PMID: 38129620 DOI: 10.1038/s41592-023-02121-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
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3
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Marchak A, Neilson KM, Majumdar HD, Yamauchi K, Klein SL, Moody SA. The sulfotransferase XB5850668.L is required to apportion embryonic ectodermal domains. Dev Dyn 2023; 252:1407-1427. [PMID: 37597164 PMCID: PMC10842325 DOI: 10.1002/dvdy.648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/08/2023] [Accepted: 07/26/2023] [Indexed: 08/21/2023] Open
Abstract
BACKGROUND Members of the sulfotransferase superfamily (SULT) influence the activity of a wide range of hormones, neurotransmitters, metabolites and xenobiotics. However, their roles in developmental processes are not well characterized even though they are expressed during embryogenesis. We previously found in a microarray screen that Six1 up-regulates LOC100037047, which encodes XB5850668.L, an uncharacterized sulfotransferase. RESULTS Since Six1 is required for patterning the embryonic ectoderm into its neural plate, neural crest, preplacodal and epidermal domains, we used loss- and gain-of function assays to characterize the role of XB5850668.L during this process. Knockdown of endogenous XB5850668.L resulted in the reduction of epidermal, neural crest, cranial placode and otic vesicle gene expression domains, concomitant with neural plate expansion. Increased levels had minimal effects, but infrequently expanded neural plate and neural crest gene domains, and infrequently reduced cranial placode and otic vesicle gene domains. Mutation of two key amino acids in the sulfotransferase catalytic domain required for PAPS binding and enzymatic activity tended to reduce the effects of overexpressing the wild-type protein. CONCLUSIONS Our analyses indicates that XB5850668.L is a member of the SULT2 family that plays important roles in patterning the embryonic ectoderm. Some aspects of its influence likely depend on sulfotransferase activity.
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Affiliation(s)
- Alexander Marchak
- Department of Anatomy and Cell Biology, George Washington University, School of Medicine and Health Sciences, Washington, District of Columbia, USA
| | - Karen M Neilson
- Department of Anatomy and Cell Biology, George Washington University, School of Medicine and Health Sciences, Washington, District of Columbia, USA
| | - Himani D Majumdar
- Department of Anatomy and Cell Biology, George Washington University, School of Medicine and Health Sciences, Washington, District of Columbia, USA
| | - Kiyoshi Yamauchi
- Department of Biological Science, Shizuoka University, Shizuoka, Japan
| | - Steven L Klein
- Department of Anatomy and Cell Biology, George Washington University, School of Medicine and Health Sciences, Washington, District of Columbia, USA
| | - Sally A Moody
- Department of Anatomy and Cell Biology, George Washington University, School of Medicine and Health Sciences, Washington, District of Columbia, USA
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4
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Gastonguay MS, Keele GR, Churchill GA. The trouble with triples: Examining the impact of measurement error in mediation analysis. Genetics 2023; 224:iyad045. [PMID: 36932658 PMCID: PMC10158839 DOI: 10.1093/genetics/iyad045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 01/03/2023] [Accepted: 02/11/2023] [Indexed: 03/19/2023] Open
Abstract
Mediation analysis is used in genetic mapping studies to identify candidate gene mediators of quantitative trait loci (QTL). We consider genetic mediation analysis of triplets-sets of three variables consisting of a target trait, the genotype at a QTL for the target trait, and a candidate mediator that is the abundance of a transcript or protein whose coding gene co-locates with the QTL. We show that, in the presence of measurement error, mediation analysis can infer partial mediation even in the absence of a causal relationship between the candidate mediator and the target. We describe a measurement error model and a corresponding latent variable model with estimable parameters that are combinations of the causal effects and measurement errors across all three variables. The relative magnitudes of the latent variable correlations determine whether or not mediation analysis will tend to infer the correct causal relationship in large samples. We examine case studies that illustrate the common failure modes of genetic mediation analysis and demonstrate how to evaluate the effects of measurement error. While genetic mediation analysis is a powerful tool for identifying candidate genes, we recommend caution when interpreting mediation analysis findings.
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5
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Crook OM, Chung CW, Deane CM. Challenges and Opportunities for Bayesian Statistics in Proteomics. J Proteome Res 2022; 21:849-864. [PMID: 35258980 PMCID: PMC8982455 DOI: 10.1021/acs.jproteome.1c00859] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Indexed: 12/27/2022]
Abstract
Proteomics is a data-rich science with complex experimental designs and an intricate measurement process. To obtain insights from the large data sets produced, statistical methods, including machine learning, are routinely applied. For a quantity of interest, many of these approaches only produce a point estimate, such as a mean, leaving little room for more nuanced interpretations. By contrast, Bayesian statistics allows quantification of uncertainty through the use of probability distributions. These probability distributions enable scientists to ask complex questions of their proteomics data. Bayesian statistics also offers a modular framework for data analysis by making dependencies between data and parameters explicit. Hence, specifying complex hierarchies of parameter dependencies is straightforward in the Bayesian framework. This allows us to use a statistical methodology which equals, rather than neglects, the sophistication of experimental design and instrumentation present in proteomics. Here, we review Bayesian methods applied to proteomics, demonstrating their potential power, alongside the challenges posed by adopting this new statistical framework. To illustrate our review, we give a walk-through of the development of a Bayesian model for dynamic organic orthogonal phase-separation (OOPS) data.
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Affiliation(s)
- Oliver M. Crook
- Department
of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom
| | - Chun-wa Chung
- Structural
and Biophysical Sciences, GlaxoSmithKline
R&D, Stevenage SG1 2NY, United Kingdom
| | - Charlotte M. Deane
- Department
of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom
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6
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Xie H, Ding X. The Intriguing Landscape of Single-Cell Protein Analysis. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2105932. [PMID: 35199955 PMCID: PMC9036017 DOI: 10.1002/advs.202105932] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 01/27/2022] [Indexed: 05/15/2023]
Abstract
Profiling protein expression at single-cell resolution is essential for fundamental biological research (such as cell differentiation and tumor microenvironmental examination) and clinical precision medicine where only a limited number of primary cells are permitted. With the recent advances in engineering, chemistry, and biology, single-cell protein analysis methods are developed rapidly, which enable high-throughput and multiplexed protein measurements in thousands of individual cells. In combination with single cell RNA sequencing and mass spectrometry, single-cell multi-omics analysis can simultaneously measure multiple modalities including mRNAs, proteins, and metabolites in single cells, and obtain a more comprehensive exploration of cellular signaling processes, such as DNA modifications, chromatin accessibility, protein abundance, and gene perturbation. Here, the recent progress and applications of single-cell protein analysis technologies in the last decade are summarized. Current limitations, challenges, and possible future directions in this field are also discussed.
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Affiliation(s)
- Haiyang Xie
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Xianting Ding
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
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7
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Ctortecka C, Stejskal K, Krššáková G, Mendjan S, Mechtler K. Quantitative Accuracy and Precision in Multiplexed Single-Cell Proteomics. Anal Chem 2021; 94:2434-2443. [PMID: 34967612 PMCID: PMC8829824 DOI: 10.1021/acs.analchem.1c04174] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
![]()
Single-cell proteomics
workflows have considerably improved in
sensitivity and reproducibility to characterize as-yet unknown biological
phenomena. With the emergence of multiplexed single-cell proteomics,
studies increasingly present single-cell measurements in conjunction
with an abundant congruent carrier to improve the precursor selection
and enhance identifications. While these extreme carrier spikes are
often >100× more abundant than the investigated samples, the
total ion current undoubtably increases but the quantitative accuracy
possibly is affected. We here focus on narrowly titrated carrier spikes
(i.e., <20×) and assess their elimination for a comparable
sensitivity with superior accuracy. We find that subtle changes in
the carrier ratio can severely impact the measurement variability
and describe alternative multiplexing strategies to evaluate data
quality. Lastly, we demonstrate elevated replicate overlap while preserving
acquisition throughput at an improved quantitative accuracy with DIA-TMT
and discuss optimized experimental designs for multiplexed proteomics
of trace samples. This comprehensive benchmarking gives an overview
of currently available techniques and guides the conceptualization
of the optimal single-cell proteomics experiment.
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Affiliation(s)
- Claudia Ctortecka
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Campus Vienna Biocenter 1, 1030 Vienna, Austria
| | - Karel Stejskal
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Campus Vienna Biocenter 1, 1030 Vienna, Austria.,Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria.,The Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences (GMI), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Gabriela Krššáková
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Campus Vienna Biocenter 1, 1030 Vienna, Austria.,Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria.,The Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences (GMI), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Sasha Mendjan
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Campus Vienna Biocenter 1, 1030 Vienna, Austria.,Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria.,The Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences (GMI), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
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8
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Johnson A, Stadlmeier M, Wühr M. TMTpro Complementary Ion Quantification Increases Plexing and Sensitivity for Accurate Multiplexed Proteomics at the MS2 Level. J Proteome Res 2021; 20:3043-3052. [PMID: 33929851 DOI: 10.1021/acs.jproteome.0c00813] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Multiplexed proteomics is a powerful tool to assay cell states in health and disease, but accurate quantification of relative protein changes is impaired by interference from co-isolated peptides. Interference can be reduced by using MS3-based quantification, but this reduces sensitivity and requires specialized instrumentation. An alternative approach is quantification by complementary ions, the balancer group-peptide conjugates, which allows accurate and precise multiplexed quantification at the MS2 level and is compatible with most proteomics instruments. However, complementary ions of the popular TMT-tag form inefficiently and multiplexing is limited to five channels. Here, we evaluate and optimize complementary ion quantification for the recently released TMTpro-tag, which increases complementary ion plexing capacity to eight channels (TMTproC). Furthermore, the beneficial fragmentation properties of TMTpro increase sensitivity for TMTproC, resulting in ∼65% more proteins quantified compared to TMTpro-MS3 and ∼18% more when compared to real-time-search TMTpro-MS3 (RTS-SPS-MS3). TMTproC quantification is more accurate than TMTpro-MS2 and even superior to RTS-SPS-MS3. We provide the software for quantifying TMTproC data as an executable that is compatible with the MaxQuant analysis pipeline. Thus, TMTproC advances multiplexed proteomics data quality and widens access to accurate multiplexed proteomics beyond laboratories with MS3-capable instrumentation.
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Affiliation(s)
- Alex Johnson
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, United States.,Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, United States.,Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, United States
| | - Michael Stadlmeier
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, United States.,Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, United States
| | - Martin Wühr
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, United States.,Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, United States.,Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, United States
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9
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Cao WX, Kabelitz S, Gupta M, Yeung E, Lin S, Rammelt C, Ihling C, Pekovic F, Low TCH, Siddiqui NU, Cheng MHK, Angers S, Smibert CA, Wühr M, Wahle E, Lipshitz HD. Precise Temporal Regulation of Post-transcriptional Repressors Is Required for an Orderly Drosophila Maternal-to-Zygotic Transition. Cell Rep 2021; 31:107783. [PMID: 32579915 PMCID: PMC7372737 DOI: 10.1016/j.celrep.2020.107783] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 05/06/2020] [Accepted: 05/28/2020] [Indexed: 12/12/2022] Open
Abstract
In animal embryos, the maternal-to-zygotic transition (MZT) hands developmental control from maternal to zygotic gene products. We show that the maternal proteome represents more than half of the protein-coding capacity of Drosophila melanogaster’s genome, and that 2% of this proteome is rapidly degraded during the MZT. Cleared proteins include the post-transcriptional repressors Cup, Trailer hitch (TRAL), Maternal expression at 31B (ME31B), and Smaug (SMG). Although the ubiquitin-proteasome system is necessary for clearance of these repressors, distinct E3 ligase complexes target them: the C-terminal to Lis1 Homology (CTLH) complex targets Cup, TRAL, and ME31B for degradation early in the MZT and the Skp/Cullin/F-box-containing (SCF) complex targets SMG at the end of the MZT. Deleting the C-terminal 233 amino acids of SMG abrogates F-box protein interaction and confers immunity to degradation. Persistent SMG downregulates zygotic re-expression of mRNAs whose maternal contribution is degraded by SMG. Thus, clearance of SMG permits an orderly MZT. Cao et al. show that 2% of the proteome is degraded in early Drosophila embryos, including a repressive ribonucleoprotein complex. Two E3 ubiquitin ligases separately act on distinct components of this complex to phase their clearance. Failure to degrade a key component, the Smaug RNA-binding protein, disrupts an orderly maternal-to-zygotic transition.
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Affiliation(s)
- Wen Xi Cao
- Department of Molecular Genetics, University of Toronto, 661 University Avenue, Toronto, ON M5G 1M1, Canada
| | - Sarah Kabelitz
- Institute of Biochemistry and Biotechnology and Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Kurt-Mothes-Str. 3, 06099 Halle, Germany
| | - Meera Gupta
- Department of Molecular Biology and the Lewis-Sigler Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA
| | - Eyan Yeung
- Department of Molecular Biology and the Lewis-Sigler Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA
| | - Sichun Lin
- Department of Pharmaceutical Sciences, University of Toronto, 144 College Street, Toronto, ON M5S 3M2, Canada
| | - Christiane Rammelt
- Institute of Biochemistry and Biotechnology and Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Kurt-Mothes-Str. 3, 06099 Halle, Germany
| | - Christian Ihling
- Institute of Pharmacy and Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Kurt-Mothes-Str. 3, 06099 Halle, Germany
| | - Filip Pekovic
- Institute of Biochemistry and Biotechnology and Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Kurt-Mothes-Str. 3, 06099 Halle, Germany
| | - Timothy C H Low
- Department of Molecular Genetics, University of Toronto, 661 University Avenue, Toronto, ON M5G 1M1, Canada
| | - Najeeb U Siddiqui
- Department of Molecular Genetics, University of Toronto, 661 University Avenue, Toronto, ON M5G 1M1, Canada
| | - Matthew H K Cheng
- Department of Biochemistry, University of Toronto, 661 University Avenue, Toronto, ON M5G 1M1, Canada
| | - Stephane Angers
- Department of Pharmaceutical Sciences, University of Toronto, 144 College Street, Toronto, ON M5S 3M2, Canada; Department of Biochemistry, University of Toronto, 661 University Avenue, Toronto, ON M5G 1M1, Canada
| | - Craig A Smibert
- Department of Molecular Genetics, University of Toronto, 661 University Avenue, Toronto, ON M5G 1M1, Canada; Department of Biochemistry, University of Toronto, 661 University Avenue, Toronto, ON M5G 1M1, Canada
| | - Martin Wühr
- Department of Molecular Biology and the Lewis-Sigler Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA
| | - Elmar Wahle
- Institute of Biochemistry and Biotechnology and Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Kurt-Mothes-Str. 3, 06099 Halle, Germany.
| | - Howard D Lipshitz
- Department of Molecular Genetics, University of Toronto, 661 University Avenue, Toronto, ON M5G 1M1, Canada.
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10
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The M, Käll L. Triqler for MaxQuant: Enhancing Results from MaxQuant by Bayesian Error Propagation and Integration. J Proteome Res 2021; 20:2062-2068. [PMID: 33661646 PMCID: PMC8041382 DOI: 10.1021/acs.jproteome.0c00902] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Error estimation for differential protein quantification by label-free shotgun proteomics is challenging due to the multitude of error sources, each contributing uncertainty to the final results. We have previously designed a Bayesian model, Triqler, to combine such error terms into one combined quantification error. Here we present an interface for Triqler that takes MaxQuant results as input, allowing quick reanalysis of already processed data. We demonstrate that Triqler outperforms the original processing for a large set of both engineered and clinical/biological relevant data sets. Triqler and its interface to MaxQuant are available as a Python module under an Apache 2.0 license from https://pypi.org/project/triqler/.
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Affiliation(s)
- Matthew The
- Chair of Proteomics and Bioanalytics, Technische Universität München, Emil-Erlenmeyer Forum 5, 85354 Freising, Germany
| | - Lukas Käll
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology - KTH, Box 1031, 17121 Solna, Sweden
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11
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Defining the carrier proteome limit for single-cell proteomics. Nat Methods 2020; 18:76-83. [PMID: 33288958 DOI: 10.1038/s41592-020-01002-5] [Citation(s) in RCA: 119] [Impact Index Per Article: 29.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 10/22/2020] [Indexed: 11/09/2022]
Abstract
Single-cell proteomics by mass spectrometry (SCoPE-MS) is a recently introduced method to quantify multiplexed single-cell proteomes. While this technique has generated great excitement, the underlying technologies (isobaric labeling and mass spectrometry (MS)) have technical limitations with the potential to affect data quality and biological interpretation. These limitations are particularly relevant when a carrier proteome, a sample added at 25-500× the amount of a single-cell proteome, is used to enable peptide identifications. Here we perform controlled experiments with increasing carrier proteome amounts and evaluate quantitative accuracy, as it relates to mass analyzer dynamic range, multiplexing level and number of ions sampled. We demonstrate that an increase in carrier proteome level requires a concomitant increase in the number of ions sampled to maintain quantitative accuracy. Lastly, we introduce Single-Cell Proteomics Companion (SCPCompanion), a software tool that enables rapid evaluation of single-cell proteomic data and recommends instrument and data analysis parameters for improved data quality.
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12
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The gain-of-function allele bamA E470K bypasses the essential requirement for BamD in β-barrel outer membrane protein assembly. Proc Natl Acad Sci U S A 2020; 117:18737-18743. [PMID: 32675245 DOI: 10.1073/pnas.2007696117] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
The outer membrane (OM) of gram-negative bacteria confers innate resistance to toxins and antibiotics. Integral β-barrel outer membrane proteins (OMPs) function to establish and maintain the selective permeability of the OM. OMPs are assembled into the OM by the β-barrel assembly machine (BAM), which is composed of one OMP-BamA-and four lipoproteins-BamB, C, D, and E. BamB, C, and E can be removed individually with only minor effects on barrier function; however, depletion of either BamA or BamD causes a global defect in OMP assembly and results in cell death. We have identified a gain-of-function mutation, bamA E470K , that bypasses the requirement for BamD. Although bamD::kan bamA E470K cells exhibit growth and OM barrier defects, they assemble OMPs with surprising robustness. Our results demonstrate that BamD does not play a catalytic role in OMP assembly, but rather functions to regulate the activity of BamA.
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13
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Millikin RJ, Shortreed MR, Scalf M, Smith LM. A Bayesian Null Interval Hypothesis Test Controls False Discovery Rates and Improves Sensitivity in Label-Free Quantitative Proteomics. J Proteome Res 2020; 19:1975-1981. [PMID: 32243168 DOI: 10.1021/acs.jproteome.9b00796] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Statistical significance tests are a common feature in quantitative proteomics workflows. The Student's t-test is widely used to compute the statistical significance of a protein's change between two groups of samples. However, the t-test's null hypothesis asserts that the difference in means between two groups is exactly zero, often marking small but uninteresting fold-changes as statistically significant. Compensations to address this issue are widely used in quantitative proteomics, but we suggest that a replacement of the t-test with a Bayesian approach offers a better path forward. In this article, we describe a Bayesian hypothesis test in which the null hypothesis is an interval rather than a single point at zero; the width of the interval is estimated from population statistics. The improved sensitivity of the method substantially increases the number of truly changing proteins detected in two benchmark data sets (ProteomeXchange identifiers PXD005590 and PXD016470). The method has been implemented within FlashLFQ, an open-source software program that quantifies bottom-up proteomics search results obtained from any search tool. FlashLFQ is rapid, sensitive, and accurate and is available both as an easy-to-use graphical user interface (Windows) and as a command-line tool (Windows/Linux/OSX).
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Affiliation(s)
- Robert J Millikin
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Michael R Shortreed
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Mark Scalf
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
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14
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Multi-Omic Analyses Provide Links between Low-Dose Antibiotic Treatment and Induction of Secondary Metabolism in Burkholderia thailandensis. mBio 2020; 11:mBio.03210-19. [PMID: 32098820 PMCID: PMC7042699 DOI: 10.1128/mbio.03210-19] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Low doses of antibiotics can trigger secondary metabolite biosynthesis in bacteria, but the underlying mechanisms are generally unknown. We sought to better understand this phenomenon by studying how the antibiotic trimethoprim activates the synthesis of the virulence factor malleilactone in Burkholderia thailandensis Using transcriptomics, quantitative multiplexed proteomics, and primary metabolomics, we systematically mapped the changes induced by trimethoprim. Surprisingly, even subinhibitory doses of the antibiotic resulted in broad transcriptional and translational alterations, with ∼8.5% of the transcriptome and ∼5% of the proteome up- or downregulated >4-fold. Follow-up studies with genetic-biochemical experiments showed that the induction of malleilactone synthesis can be sufficiently explained by the accumulation of methionine biosynthetic precursors, notably homoserine, as a result of inhibition of the folate pathway. Homoserine activated the malleilactone gene cluster via the transcriptional regulator MalR and gave rise to a secondary metabolome which was very similar to that generated by trimethoprim. Our work highlights the expansive changes that low-dose trimethoprim induces on bacterial physiology and provides insights into its stimulatory effect on secondary metabolism.IMPORTANCE The discovery of antibiotics ranks among the most significant accomplishments of the last century. Although the targets of nearly all clinical antibiotics are known, our understanding regarding their natural functions and the effects of subinhibitory concentrations is in its infancy. Stimulatory rather than inhibitory functions have been attributed to low-dose antibiotics. Among these, we previously found that antibiotics activate silent biosynthetic genes and thereby enhance the metabolic output of bacteria. The regulatory circuits underlying this phenomenon are unknown. We take a first step toward elucidating these circuits and show that low doses of trimethoprim (Tmp) have cell-wide effects on the saprophyte Burkholderia thailandensis Most importantly, inhibition of one-carbon metabolic processes by Tmp leads to an accumulation of homoserine, which induces the production of an otherwise silent cytotoxin via a LuxR-type transcriptional regulator. These results provide a starting point for uncovering the molecular basis of the hormetic effects of antibiotics.
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Mugahid D, Kalocsay M, Liu X, Gruver JS, Peshkin L, Kirschner MW. YAP regulates cell size and growth dynamics via non-cell autonomous mediators. eLife 2020; 9:53404. [PMID: 31913124 PMCID: PMC6989120 DOI: 10.7554/elife.53404] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 12/16/2019] [Indexed: 12/18/2022] Open
Abstract
The Hippo pathway regulates organ size, regeneration, and cell growth by controlling the stability of the transcription factor, YAP (Yorkie in Drosophila). When there is tissue damage, YAP is activated allowing the restoration of homeostatic tissue size. The exact signals by which YAP is activated are still not fully understood, but its activation is known to affect both cell size and cell number. Here we used cultured cells to examine the coordinated regulation of cell size and number under the control of YAP. Our experiments in isogenic HEK293 cells reveal that YAP can affect cell size and number by independent circuits. Some of these effects are cell autonomous, such as proliferation, while others are mediated by secreted signals. In particular CYR61, a known secreted YAP target, is a non-cell autonomous mediator of cell survival, while another unidentified secreted factor controls cell size.
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Affiliation(s)
- Douaa Mugahid
- Department of Systems Biology, Harvard Medical School, Boston, United States
| | - Marian Kalocsay
- Department of Systems Biology, Harvard Medical School, Boston, United States
| | - Xili Liu
- Department of Systems Biology, Harvard Medical School, Boston, United States
| | | | - Leonid Peshkin
- Department of Systems Biology, Harvard Medical School, Boston, United States
| | - Marc W Kirschner
- Department of Systems Biology, Harvard Medical School, Boston, United States
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Hart EM, Gupta M, Wühr M, Silhavy TJ. The Synthetic Phenotype of Δ bamB Δ bamE Double Mutants Results from a Lethal Jamming of the Bam Complex by the Lipoprotein RcsF. mBio 2019; 10:e00662-19. [PMID: 31113901 PMCID: PMC6529638 DOI: 10.1128/mbio.00662-19] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 04/16/2019] [Indexed: 01/23/2023] Open
Abstract
The selective permeability of the Gram-negative outer membrane (OM) is maintained by integral β-barrel outer membrane proteins (OMPs). The heteropentomeric β-barrel assembly machine (Bam) folds and inserts OMPs into the OM. Coordination of the essential proteins BamA and BamD is critical for OMP assembly and therefore the viability of the cell. The role of the nonessential lipoproteins BamBCE has yet to be characterized; however, genetic evidence suggests that they have nonoverlapping roles in OMP assembly. In this work, we quantify changes of the proteome in the conditional lethal ΔbamB ΔbamE double mutant. We show that cells lacking BamB and BamE have a global OMP defect that is a result of a lethal obstruction of an assembly-competent Bam complex by the lipoprotein RcsF. RcsF is a stress-sensing lipoprotein that is threaded through the lumen of abundant β-barrel OMPs by the Bam complex to expose the amino terminus on the cell surface. We demonstrate that simply removing this lipoprotein corrects the severe OMP assembly defect of the double mutant nearly as efficiently as a previously isolated suppressor mutation in bamA We propose that BamB and BamE play crucial, nonoverlapping roles to coordinate the activities of BamA and BamD during OMP biogenesis.IMPORTANCE Protein assembly into lipid bilayers is an essential process that ensures the viability of diverse organisms. In Gram-negative bacteria, the heteropentomeric β-barrel assembly machine (Bam) folds and inserts proteins into the outer membrane. Due to its essentiality, outer membrane protein (OMP) assembly by the Bam complex is an attractive target for antibiotic development. Here, we show that the conditional lethal phenotype of a mutant lacking two of the three nonessential lipoproteins, BamB and BamE, is caused by lethal jamming of the stripped-down Bam complex by a normally surface-exposed lipoprotein, RcsF. The heterotrimeric Bam complex (BamA, BamD, BamC) is nearly as efficient as the wild-type complex in OMP assembly if RcsF is removed. Our study highlights the importance of BamB and BamE in regulating the interaction between BamA and BamD and expands our understanding of the role of the Bam complex in outer membrane biogenesis.
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Affiliation(s)
- Elizabeth M Hart
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
| | - Meera Gupta
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA
| | - Martin Wühr
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA
| | - Thomas J Silhavy
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
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