Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells
Open accessAbstract
Devil in the Detail: Genetically identical cells in the same environment can show variation in gene expression that may cause phenotypic variation at the single-cell level. But how noisy are most genes? Taniguchi et al. (p. 533 ; see the Perspective by Tyagi ) now report single-cell global profiling of both messenger RNA (mRNA) and proteins in Escherichia coli using a yellow fluorescent protein fusion library. As well as a common extrinsic noise in high-abundance proteins, large fluctuations were observed in low-abundance proteins. Remarkably, in single-cell experiments, mRNA and protein levels for the same gene were uncorrelated.
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5 of 34 cited sources checked · 3 supported · 0 flagged · accuracy not yet measured
- Premisecitation
In genetically identical bacterial populations, protein and mRNA copy numbers differ between individual cells.
“Such stochasticity is manifested in fluctuations of mRNA and protein copy numbers within a cell lineage over time, and in variations of mRNA and protein copy numbers among a population of genetically identical cells at a particular time (1, 2, 3, 4).”
Quote in the paperSubstantial claim1 of 3 sources checked- cites [1] source
- cites [2] source
The Abstract says stochastic gene expression can produce variation among identical cells, and its model predicts cell-to-cell variability in mRNA levels for both eukaryotic and prokaryotic promoters. However, the paper's single-cell protein-reporter measurements were made in yeast, not bacteria; it does not establish that both protein and mRNA copy numbers differ among individual bacterial cells. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites [3] source
- Study design and conductown data
Single-molecule sensitivity of the imaging was confirmed by abrupt photobleaching of membrane-bound YFPs expressed at low level.
“Single molecule sensitivity was confirmed by abrupt photobleaching of membrane-bound YFPs expressed at low level (Fig. S14) (8, 18, 23).”
Quote in the paperSubstantial claim1 of 3 sources checked- cites [8] source
- cites [18] source
- cites [23] source
The Results and discussion passage on deletion-mutant verification describes PCR checks, while Materials and methods > Growth tests describes absorbance measurements; neither addresses single-molecule imaging. Searches for photobleaching, membrane-bound YFP, and fluorescence imaging found no passage confirming the claimed sensitivity test. Page numbers were not available in our copy. (LLM, conf=0.78)
Experimental — accuracy not yet measured
- Findingcitation
E. coli proteins generally had larger noise and Fano factors than yeast proteins, even for proteins present at similar copy numbers.
“We found that E. coli proteins generally had larger noise and Fano factors than yeast proteins, even for those present at similar copy numbers (Fig. S6) (18).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [18] source
- Findingown data
In a single cell, mRNA and protein levels for the same gene are completely uncorrelated.
“Furthermore, we found that in a single cell mRNA and protein levels for the same gene are completely uncorrelated.”
Quote in the paperSubstantial claim - Findingcitation
The protein distributions for 1,009 out of 1,018 strains can be well fit by the gamma distribution.
“The distributions for 1,009 out of the 1,018 strains can be well fit by the gamma distribution, Eq. 2 (Fig. S20) (18).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [18] source
- Findingown data
Below ten molecules per cell, protein noise is inversely proportional to protein abundance, indicative of intrinsic noise.
“Below ten molecules per cell, ηp2 is inversely proportional to protein abundance, indicative of intrinsic noise.”
Quote in the paperSubstantial claim - Findingown data
For EF-Tu in the TufA-YFP strain, mRNA and protein copy numbers in a single cell are not correlated (r = 0.01 ± 0.03, SEM, N = 5,447).
“mRNA and protein copy numbers in a single cell are not correlated (r = 0.01 ± 0.03, SEM, N = 5,447).”
Quote in the paperSubstantial claim - Findingown data
Protein noise exhibits two distinct scaling properties.
“The protein noise (ηp2 ≡ σp2/μp2) exhibits two distinct scaling properties (Fig. 2B).”
Quote in the paperSubstantial claim - Findingown data
Average protein abundances of essential genes are higher than those for all genes.
“The average protein abundances of essential genes are higher than those for all genes.”
Quote in the paperNot a substantial claim - Findingown data
Average protein abundances span five orders of magnitude, from 10^-1 to 10^4 molecules per cell.
“Average protein abundances span five orders of magnitude, ranging from 10-1 to 104 molecules per cell (Fig 2A).”
Quote in the paperSubstantial claim - Findingown data
Among many different highly expressed strains surveyed, correlation coefficients between single-cell mRNA and protein levels are all centered on zero, indicating a general lack of mRNA-protein correlation for the same gene within a single cell.
“In fact, among many different highly expressed strains surveyed, the correlation coefficients are all centered on zero (Fig. 4B), indicating a general lack of mRNA-protein correlation of the same gene within a single cell.”
Quote in the paperSubstantial claim - Findingcitation
About half of all measured proteins are present at fewer than ten molecules per cell.
“Of the 121 essential proteins in the library (24), 108 express at ten or more molecules per cell (Fig 2A), whereas about half of all the measured proteins are present at fewer than ten molecules per cell (18).”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationown data
At high expression levels, protein distributions are dominated by extrinsic noise.
“At high expression levels, the distributions are dominated by extrinsic noise.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The transcription and translation rates a and b have static or slowly varying heterogeneous distributions f(a) and g(b) across cells.
- Premisecitation
Measuring cell-to-cell variation in mRNA and protein copy numbers permits inference of gene expression dynamics within a cell.
“Because both manifestations of stochasticity are connected, measurement of the latter allows the deduction of the gene expression dynamics in a cell (5).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [5] source
- Study design and conductcitation
Absolute protein levels were obtained by calibration with single-molecule fluorescence intensities to determine protein concentration.
“The absolute protein level was obtained by calibration with single-molecule fluorescence intensities (Fig. S1) (18) to determine the protein concentration (copy numbers per average cell volume).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [18] source
- Study design and conductcitation
The validity of transcript measurements was confirmed with RNA-seq.
“We confirmed the validity of our transcript measurements with RNA-seq (Table S6) (18).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [18] source
- Study design and conductnone given
Normalization by cell size is necessary to account for cell size and gene copy number variation due to the cell cycle.
“Normalization by cell size is necessary to account for cell size and gene copy number variation due to the cell cycle.”
Quote in the paperSubstantial claim - Study design and conductown data
An independent reporter assay confirmed that the fluorescence accurately reports native protein abundance.
“An independent reporter assay confirmed that the resulting fluorescence accurately reports on native protein abundance (Fig. S4).”
Quote in the paperSubstantial claim - Interpretationcitation
Extrinsic translational noise or regulatory networks must also be present to account for the near-zero mRNA-protein correlation.
“However, extrinsic translational noise or regulatory networks must also be present to account for the near-zero mRNA-protein correlation we observe (18).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [18] source
- Premisenone given
Gene expression is often stochastic because regulation occurs at a single DNA locus per cell.
“Gene expression is often stochastic because gene regulation takes place at a single DNA locus within a cell.”
Quote in the paperSubstantial claim - Interpretationreasoning
The lack of mRNA-protein correlation can be explained by the difference in mRNA and protein lifetime.
“The lack of mRNA-protein correlation can be explained by the difference in mRNA and protein lifetime.”
Quote in the paperSubstantial claim - Interpretationown data
At low expression levels, the gamma distribution parameters have clear physical interpretations as transcription rate and protein burst size.
“We found that almost all protein number distributions can be described by the gamma distribution with two fitting parameters which, at low expression levels, have clear physical interpretations as the transcription rate and protein burst size.”
Quote in the paperSubstantial claim- The authors state this as an assumption: Gene expression dynamics follow a kinetic scheme with transcription, translation, mRNA degradation, and protein degradation rates.
- May combine two claims. 13
- Classified as probably not a substantial claim. 3
May combine two claims.
PremisecitationSingle-molecule fluorescence microscopy has counted mRNA or protein molecules in individual cells, especially bacteria, but only for a limited number of specific genes.
“In recent years, single-molecule fluorescence microscopy has been used to count mRNA (12-16) or protein (8, 17) molecules in individual cells, especially in bacteria. However, these methods have only been applied to limited number of specific genes.”
Quote in the paperSubstantial claim3 of 7 sources checkedMay combine two claims.
Findingown dataAt higher expression levels (>10 molecules per cell), protein noise reaches a plateau of ~0.1 and does not decrease further, suggesting each protein has at least 30% variation in expression level.
“In contrast, at higher expression levels (>10 molecules per cell), the noise reaches a plateau of ∼0.1 and does not decrease further, suggesting that each protein has at least 30% variation in its expression level.”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationThe noise floor does not result from cell size effects or measurement noise.
“We found that the noise floor does not result from cell size effects, nor did it arise from measurement noise (18).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [18] source
May combine two claims.
Findingown dataThe study discovered large fluctuations in low abundance proteins and a common extrinsic noise in high abundance proteins.
“We discovered large fluctuations in low abundance proteins as well as a common extrinsic noise in high abundance proteins.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The transcription and translation rates a and b have static or slowly varying heterogeneous distributions f(a) and g(b) across cells.
May combine two claims.
Findingown dataExtrinsic noise is global to all high expression genes, demonstrated by statistically significant correlations between expression levels of 13 pairs of randomly selected genes.
“We further demonstrate that the extrinsic noise is global to all high expression genes by analyzing the correlations between expression levels of 13 pairs of randomly selected genes.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The transcription and translation rates a and b have static or slowly varying heterogeneous distributions f(a) and g(b) across cells.
Probably not a substantial claim: may not pass S2 (checkable).
Interpretationown dataThe prevalence of proteins with very low copy number suggests that single-molecule experiments are necessary for bacteriology.
“The prevalence of proteins with very low copy number suggests that single-molecule experiments are necessary for bacteriology.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThis result highlights the disconnect between proteome and transcriptome analyses of a single cell and the need for single-cell proteome analysis.
“This striking result highlights the disconnect between proteome and transcriptome analyses of a single cell, as well as the need for single cell proteome analysis.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationA fluorescent protein reporter library in S. cerevisiae has been extremely useful for protein profiling.
“A fluorescent protein reporter library of Saccharomyces cerevisiae (9) has proven to be extremely useful in protein profiling (10, 11).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S2 (checkable). May combine two claims.
InterpretationreasoningThe result offers a cautionary note in interpreting single-cell transcriptome analysis and argues for the necessity of single-cell proteome analysis.
“However, our result offers a cautionary note in interpreting single-cell transcriptome analysis and argues for the necessity for single cell proteome analysis.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThe additional noise is attributed to extrinsic noise, i.e., slow variation of a and b, confirmed by real-time observation of protein levels for four randomly selected high-copy strains.
“We attribute the additional noise to extrinsic noise (3), that is the slow variation of the values of a and b, which we confirm with real time observation of protein levels for four randomly selected high copy library strains.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [3] source
- The authors state this as an assumption: The transcription and translation rates a and b have static or slowly varying heterogeneous distributions f(a) and g(b) across cells.
May combine two claims.
Interpretationown dataGiven that some proteins and most mRNAs of functional genes are present at low copy numbers in a bacterial cell, single-molecule sensitivity is necessary for understanding stochastic gene expression and regulation.
“Given that some proteins and most mRNAs of functional genes are present at low copy numbers in a bacterial cell, the single molecule sensitivity afforded by our measurements is necessary for the understanding of stochastic gene expression and regulation.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationIn E. coli, mRNA is typically degraded within minutes, whereas most proteins, including fluorescent proteins, have a lifetime longer than the cell cycle.
“In E. coli, mRNA is typically degraded within minutes (Table S6) (18), whereas most proteins, including fluorescent proteins, have a lifetime longer than the cell cycle (34).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [18] source
- cites [34]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductown dataOf 1,400 attempted strains, 1,018 YFP fusion strains were confirmed by sequencing and had no significant growth defects.
“Out of the 1,400 strains attempted, 1,018 strains were confirmed by sequencing and showed no significant growth defects.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductcitationThe same FISH probe was used for all strains, so optimized hybridization efficiency is unbiased for every measured gene.
“Because the same probe is used for all strains, the optimized hybridization efficiency is unbiased for every measured gene (18).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [18] source
May combine two claims.
PremisecitationPrior single-cell mRNA profiling methods lacked single-molecule sensitivity and are unsuitable for bacteria, which have low mRNA copy numbers.
“While single cell mRNA profiling has been carried out with cDNA microarray (6) and mRNA-seq (7), these studies did not have single molecule sensitivity and are not suitable for bacteria, which express mRNA at low copy numbers (8).”
Quote in the paperSubstantial claim0 of 3 sources checked
The authors state this as an assumption.
Gene expression dynamics follow a kinetic scheme with transcription, translation, mRNA degradation, and protein degradation rates.
“We consider the kinetic scheme”
The authors state this as an assumption.
The transcription and translation rates a and b have static or slowly varying heterogeneous distributions f(a) and g(b) across cells.
“Assuming that there exist static or slowly varying heterogeneities of a and b, with distributions f (a) and g(b), respectively, the protein distribution is”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Stochastic simulations are necessary when reactions involving few particles such as those in genetic information processing and the charging of the tRNAs can lead to large variations in the state of the cell.
“Stochastic simulations are necessary when reactions involving few particles such as those in genetic information processing and the charging of the tRNAs can lead to large variations in the state of the cell (Taniguchi et al., 2010).”
From Fundamental behaviors emerge from simulations of a living minimal cell (2022) · cites this paper as Taniguchi et al., 2010
The Conclusion (page not specified) reports that some proteins and most mRNAs occur at low copy numbers in E. coli and that low-abundance proteins show large fluctuations. The paper supports the claim about stochastic variation in gene expression, but does not establish that stochastic simulations are necessary or address tRNA charging. (LLM, conf=0.86)
Experimental — accuracy not yet measuredmRNA abundance is not always a faithful proxy of protein expression across various organisms.
“Although transcriptomic profiling has provided insights into Tex cell biology, mRNA abundance is not always a faithful proxy of protein expression across various organisms18–22.”
From Proteotoxic stress response drives T cell exhaustion and immune evasion (2025) · cites this paper as [22]
This finding contrasts with data from bacteria where productive protein expression is achieved with such low mRNA concentrations.
“This finding contrasts with data from bacteria where productive protein expression is achieved with such low mRNA concentrations (Taniguchi et al., 2010).”
From Quantitative Analysis of Fission Yeast Transcriptomes and Proteomes in Proliferating and Quiescent Cells (2012) · cites this paper as Taniguchi et al., 2010
These methods hold promise for elucidating the epigenetic controls of cellular identity.
“These methods hold promise for elucidating the epigenetic controls of cellular identity186,187.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [187]
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InfluentialMolecular basis and biological function of variability in spatial genome organization
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“In addition, different promoters have different sensitivities toward intrinsic noise, depending on their activity (41), their genomic location (42), and the biochemical mechanism of their activation (43).”
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MethodA dual function of the CRISPR–Cas system in bacterial antivirus immunity and DNA repair
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“coli, we constructed chromosomal yellow fluorescent protein (YFP) fusions (Taniguchi et al., 2010) in which YgbT, RuvA, RuvB and RuvC genes were tagged with the YFP-coding sequence at their C-terminal ends.”
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Bursty Gene Expression in the Intact Mammalian Liver
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“The levels of short-lived mRNA are expected to track the instantaneous promoter activity more tightly compared to long-lived mRNA, supporting our estimates for mRNA lifetimes (Taniguchi et al., 2010).”
Single-cell gene expression analysis reveals genetic associations masked in whole-tissue experiments
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Proteobacteria explain significant functional variability in the human gut microbiome
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“S8B), whereas copy numbers of transcription factors are typically <100 (53).”
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MethodDirect metabolomics for plant cells by live single-cell mass spectrometry
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- Authors
- Taniguchi, Y., Choi, P. J., Li, G.-W., Chen, H., Babu, M., Hearn, J., Emili, A., & Xie, X. S.
- Affiliations
- Harvard University (US)
- University of Toronto (CA)
- Corresponding author
- Taniguchi, Yuichi
- Choi, Paul J.
- Li, Gene-Wei
- Chen, Huiyi
- Xie, X. Sunney
- Venue
- Science
- Published
- 2010-07-30
- Volume
- 329
- Issue
- 5991
- Pages
- 533-538
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC2922915
- OpenAlex
- W2053460598
- Cited by
- 1,982
- References
- 33
- Citations by year
- 2026: 60 · 2025: 77 · 2024: 85 · 2023: 91 · 2022: 102 · 2021: 110 · 2020: 122 · 2019: 127 · 2018: 153 · 2017: 117 · 2016: 158 · 2015: 157 · 2014: 156 · 2013: 171 · 2012: 161
- FWCI
- 60.66
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (DP1OD000277)
- Canadian Institutes of Health Research (77639_1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- Escherichia coli, single-cell proteomics, single-cell transcriptomics, gamma distribution, transcription rate, extrinsic noise, intrinsic noise, mRNA-protein correlation, gene expression variation
- MeSH terms
- Escherichia coli, Luminescent Proteins, Microscopy, Fluorescence, RNA, Bacterial, RNA, Messenger, Saccharomyces cerevisiae, Transcription, Genetic, Protein Biosynthesis, Gene Library, Gene Expression, In Situ Hybridization, Fluorescence, Proteome, Gene Expression Profiling, RNA Stability, Escherichia coli Proteins, Microfluidic Analytical Techniques
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read under definition version 3 (extract-v3) on 2026-09-28.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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