Dynamic profiling of the protein life cycle in response to pathogens

In the paper

“Conversely, the preexisting proteome of proteins performing basic cellular functions is remodeled primarily through changes in protein production or degradation, accounting for over half of the absolute change in protein molecules in the cell.”

In the paper

“We quantified 6,079 proteins by LC-MS/MS in at least one sample and 2,288 proteins in all samples (time points, conditions and replicates; Fig. 2A, table S1).”

In the paper

“we found good reproducibility of the LPS/MOCK ratios of key fitted values (Figs. 2B, S4) and of the relative differences in per-mRNA translation rates (e.g., ΔTi(12h) = Ti(12h)LPS/Ti(12h)MOCK, Pearson r = 0.68, fig. S5A) or degradation rates (e.g., ΔDi(12h) = Di(12h)LPS/Di(12h)MOCK, r = 0.62, fig. S5B).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“In Trafd1 and hundreds of other genes, a transient, strong, spiked change in mRNA, combined with a time-constant protein half life, much longer than the 12h time course, result in a monotonous increase in protein levels, such that global protein fold changes at 12h post LPS correlate best to mRNA changes at 5h (fig. S13).”

In the paper

“Of these 79%, mRNA levels explained 59–68%, per-mRNA translation rates 18–26%, and degradation rates 8–22%. (Figs. 3A, S11A, (29)).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“However, changes in per-mRNA translation rates contributed more substantially to protein level induction, whereas changes in protein degradation rates mostly contributed to protein level repression (fig. S12, table S5, (29)).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“We found that mRNA levels explain ~87–92%, per-mRNA translation rates ~4–7%, and degradation rates ~3–6% of protein fold changes after 12 hours (Figs. 3C, S11B, (29)).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“Only a handful of proteins (e.g., Tnfaip2 (26, 35, 36)), show peaked, transient protein expression within our time scale; all have very high basal degradation rates, which typically do not increase further.”

What the sources say

• Not checked yetcites [26] Chevrier N Systematic Discovery of TLR Signaling Components Delineates Viral-Sensing Circuits Cell 147 853 867 2011 22078882 PMC3809888 source
• Not checked yetcites [35] Kuan AP Genetic control of autoimmune myocarditis mediated by myosin-specific antibodies Immunogenetics 49 79 85 1999 9887344 source
• Not checked yetcites [36] Burton PR Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls Nature 447 661 678 2007 17554300 PMC2719288 source

In the paper

“There was no significant change in the ratio of mitochondrial-to-nuclear DNA at 12h post LPS stimulation, but a significant (~25%; P=0.016, t-test) reduction at 24h post stimulation (Fig. 4C).”

In the paper

“Both structural mitochondrial proteins and enzymes in key mitochondrial metabolic pathways have increased degradation.”

In the paper

“we saw a decrease in the M/L ratios (a proxy for increased degradation) of ~80% of annotated mitochondrial proteins in LPS vs. MOCK samples (Fig. 4D)”

• Also stated in: § An increase in degradation rates of mitochondrial proteins is associated with mitophagy · plain

  “in nearly all mitochondrial proteins with a higher mitochondrial localization prediction score (from MitoCarta (43) – over 95% of the 156 proteins with a score > 20 of the 472 measured mitochondrial proteins) (fig. S17).”

What the sources say

• Not checked yetcites [43] Pagliarini DJ A mitochondrial protein compendium elucidates complex I disease biology Cell 134 112 123 2008 18614015 PMC2778844 source

In the paper

“First, while the 3,147 modeled genes are somewhat enriched for higher expressed genes (fig. S14), we do model a substantial number of lowly expressed mRNAs (fig. S14).”

In the paper

“Upon LPS stimulation, a substantial decrease in the level of mitochondrial proteins is associated with increased degradation rates, although these proteins are among the most stable in unstimulated DCs (Figs. 2B, 3E, 4B, table S6).”

In the paper

“protein synthesis and degradation rates do change significantly for 357 proteins (~11% of consistently detected proteins, tables S7, S8, (29)), and in particular for proteins performing essential cellular functions (‘housekeeping proteins’, Figs. 2B, 3E, table S6), including cytoskeletal, metabolic, ribosomal (Fig. 4A) and mitochondrial proteins (Fig. 4B).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“Finally, a few key regulators of DCs and the LPS response (e.g., Cebpb, a pioneer transcription factor whose mRNA is already very highly expressed pre-stimulation, and Rela, Fig. 3F) are considerably dynamically regulated at the protein level, such that increased protein degradation rates (Rela) and/or increased per-mRNA translation rates (Rela and Cebpb) are main drivers for protein change.”

In the paper

“Indeed, whereas from raw data mRNA explains 27% of the gene-to-gene variation in protein levels at baseline (t=0), using modeled expression values it explains 42%, and, once correcting for data reproducibility (29), it explains 52%.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“the quantitative contribution of each process to changes in protein expression levels (Fig. 1A) remains largely unknown and much debated (5, 6).”

What the sources say

• Not checked yetcites [5] Vogel C Marcotte EM Insights into the regulation of protein abundance from proteomic and transcriptomic analyses Nat Rev Genet 13 227 232 2012 22411467 PMC3654667 source
• Not checked yetcites [6] Li JJ Bickel PJ Biggin MD System wide analyses have underestimated protein abundances and the importance of transcription in mammals PeerJ 2 e270 2014 24688849 PMC3940484 source

In the paper

“only a few studies (5, 12, 17–20) have attempted to shed light on how changes in each of these processes determine differential protein expression – either relative (ratios) or absolute (differences) – during dynamic responses and only one recent report (20) has attempted to quantitate each process. However, none of these has comprehensively accounted for experimental measurement errors, nor have”

What the sources say

• Not checked yetcites [5] Vogel C Marcotte EM Insights into the regulation of protein abundance from proteomic and transcriptomic analyses Nat Rev Genet 13 227 232 2012 22411467 PMC3654667 source
• Not checked yetcites [12] Marguerat S Quantitative Analysis of Fission Yeast Transcriptomes and Proteomes in Proliferating and Quiescent Cells Cell 151 671 683 2012 23101633 PMC3482660 source
• Not checked yetcites [17] Vogel C Silva GM Marcotte EM Protein Expression Regulation under Oxidative Stress Mol Cell Proteomics 10 2011 10.1074/mcp.M111.009217 PMC3237073 21933953 source
• Not checked yetcites [18] Lee MV A dynamic model of proteome changes reveals new roles for transcript alteration in yeast Mol Syst Biol 7 2011 10.1038/msb.2011.48 PMC3159980 21772262 source
• Not checked yetcites [19] Maier T Quantification of mRNA and protein and integration with protein turnover in a bacterium Mol Syst Biol 7 511 2011 21772259 PMC3159969 source
• Not checked yetcites [20] Kristensen AR Gsponer J Foster LJ Protein synthesis rate is the predominant regulator of protein expression during differentiation Mol Syst Biol 9 2013 10.1038/msb.2013.47 PMC3792347 24045637 source

In the paper

“Thus, the proteome is regulated by transcriptional induction of novel cellular functions and remodeling of preexisting functions through the protein life cycle.”

In the paper

“This ensures a low rate of false positives (calling a change where none exists), but may result in false negatives, and hence in some underestimation of the contribution of protein synthesis and degradation.”

In the paper

“a good correlation between our per-mRNA translation rates and our independent measurement of TE values in DCs using ribosome profiling at t=0h (r = 0.5, table S4, fig. S8A), comparable to the correlation between TE values in mouse DCs and mouse fibroblasts (r = 0.54, fig. S8B)”

In the paper

“DCs are mostly post-mitotic, and LPS synchronizes them (27) and causes dramatic regulatory changes from the expression of thousands of transcripts (22, 24, 25) to protein phosphorylation (26).”

What the sources say

• Not checked yetcites [27] Shalek AK Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells Nature 498 236 240 2013 23685454 PMC3683364 source
• Not checked yetcites [22] Rabani M Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells Nat Biotechnol 2011 10.1038/nbt.1861 PMC3114636 21516085 source
• Not checked yetcites [24] Amit I Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses Science 326 257 263 2009 19729616 PMC2879337 source
• Not checked yetcites [25] Garber M A High-Throughput Chromatin Immunoprecipitation Approach Reveals Principles of Dynamic Gene Regulation in Mammals Mol Cell 47 810 822 2012 22940246 PMC3873101 source
• Not checked yetcites [26] Chevrier N Systematic Discovery of TLR Signaling Components Delineates Viral-Sensing Circuits Cell 147 853 867 2011 22078882 PMC3809888 source

In the paper

“our most differential and reliable parameter estimates correspond to the well-quantified genes (29), whereas proteins with less reliable measurements are not associated with reliable changes.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“the fair correlation of our translation and protein degradation rate estimates in resting cells (table S3, fig. S6) with previous estimates in mouse fibroblasts (NIH3T3) based on a similar pulsed-SILAC approach (16) (r(Ti(0))= 0.35; r(Di(0)) = 0.58; fig. S7A, S7B)”

What the sources say

• Not checked yetcites [16] Schwanhausser B Global quantification of mammalian gene expression control Nature 473 337 342 2011 21593866 source
• Not checked yetcites [30] Subtelny AO Eichhorn SW Chen GR Sive H Bartel DP Poly(A)-tail profiling reveals an embryonic switch in translational control Nature 508 66 71 2014 24476825 PMC4086860 source

In the paper

“These dynamic changes cannot be observed solely from total protein and transcript levels, but the corresponding rate changes are readily apparent (Fig. 3F).”

In the paper

“suggesting decreased production of new mitochondrial proteins and increased destruction of old ones.”

In the paper

“We find similar patterns of contributions when we use the Spearman rank correlation rather than Pearson correlation (fig. S20, (29)), suggesting that our conclusions are robust to outliers with particularly strong changes.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“Furthermore, our analysis corrected for RNA-Seq expression reproducibility, intra-library protein expression reproducibility, and library-dependent protein expression biases ((29), fig. S21), all essential to avoid inadvertent attribution of measurement errors to modeled translation and protein degradation rates.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [29] Supplementary Online Material (SOM).

In the paper

“For example, the increased role we observed for protein degradation, in contrast to prior studies (16, 20), may be needed by postmitotic cells that cannot simply renew their protein pool by division-coupled passive dilution.”

What the sources say

• Not checked yetcites [16] Schwanhausser B Global quantification of mammalian gene expression control Nature 473 337 342 2011 21593866 source
• Not checked yetcites [20] Kristensen AR Gsponer J Foster LJ Protein synthesis rate is the predominant regulator of protein expression during differentiation Mol Syst Biol 9 2013 10.1038/msb.2013.47 PMC3792347 24045637 source

In the paper

“While our study does not directly address which steps in mRNA regulation account for this, our related work on the RNA life cycle during the first 3 hours in LPS stimulated DCs suggests that transcriptional changes may in turn dominate differential mRNA expression, whereas dynamic changes in RNA processing or degradation affect only a minority of genes, albeit with important functions (46).”

What the sources say

• Not checked yetcites [46] Rabani M High-resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies Cell 159 1698 1710 2014 25497548 PMC4272607 source