Single molecule imaging of transcription dynamics, RNA localization and fate in human T cells
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Abstract
T cells are critical effector cells against infections and malignancies. To achieve this, they produce pro-inflammatory cytokines, including IFN-γ and TNF. Cytokine production is a tightly regulated process. The relative contribution of transcriptional and post-transcriptional regulation to mRNA expression is, however, unknown. We therefore optimized single-molecule FISH for primary human T cells (T-cell smFISH) to simultaneously quantify nascent RNA, mature mRNA levels and its localization with single-cell resolution. T-cell smFISH uncovered heterogeneous cytokine mRNA levels, with high cytokine producers displaying biallelic IFNG / TNF RNA transcription activity. Throughout activation, nuclear cytokine mRNAs accumulated, whereas cytoplasmic cytokine mRNA was degraded through translation-dependent decay. Lastly, T-cell smFISH uncovered cytokine-specific regulation by the RNA-binding protein HuR. Thus, T-cell smFISH provides novel insights in the intricate (post)-transcriptional processes in T cells.
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Referee #2
Evidence, reproducibility and clarity
The authors describe a modified version of single molecule Fluorescence In-situ Hybridization (smFISH) method they have adapted to successfully measure RNA levels in isolated human donor T cells, that are very hard to grow on glass and have small amounts of cytoplasm relative to cell size, a challenge for all researchers working with small cells that only grow in suspension cultures. Using this methodology, the authors have queried transcription status and mRNA localization and fate of the two cytokines, IFNG and TNF, upon T-cell activation. The main findings of the study are: (1) activation of T-cells results in rapid accumulation …
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Referee #2
Evidence, reproducibility and clarity
The authors describe a modified version of single molecule Fluorescence In-situ Hybridization (smFISH) method they have adapted to successfully measure RNA levels in isolated human donor T cells, that are very hard to grow on glass and have small amounts of cytoplasm relative to cell size, a challenge for all researchers working with small cells that only grow in suspension cultures. Using this methodology, the authors have queried transcription status and mRNA localization and fate of the two cytokines, IFNG and TNF, upon T-cell activation. The main findings of the study are: (1) activation of T-cells results in rapid accumulation of IFNG an TNF mRNA; there is differential distribution of the cytokine mRNAs between the nucleus and cytoplasm with greater accumulation in the cytoplasm as activation progresses resulting in increased protein production. There is significant transcriptional heterogeneity in response to T-cell activation. (2) The cytokine mRNA turnover appears to be controlled by translation. (3) HUR, an RBP appears to control poly(A) tail length of TNF mRNA in response to T-cell activation. The successful implementation of a modified smFISH protocol used in this study is a welcome resource for all labs that want to study small human primary cells that are difficult to culture on glass coverslips and grow as suspension cultures. Although the authors have very exciting observations, they have shied away from discussing their results in the context of the biology of T-cell activation and how their observations may explain prior studies on cytokine gene expression patterns during T-cell activation.
In my opinion, the authors should discuss their observations in depth from the context of T-cell activation and cytokine expression. I have enumerated several specific comments that may help the authors in revising the manuscript if they choose to do so.
Specific comments:
- Based on the data presented in Figure 1 D and E, it is clear there is depletion of IFNG and TNF mRNA 4hrs after activation and then the mRNA levels go up at 6h in both cases. However, the authors suggest that only TNF mRNA is depleted at 4hrs of activation (lines 169-172). The median number of IFNG mRNA gradually decreases after 1h of activation and reaches a low at 4h and then substantially increases by 6h. Did the authors measure gene expression of these mRNAs at later time points in the activation process? Perhaps transcription is coupled to mature mRNA levels in the cytoplasm and transcription is ramped up again once the cytoplasmic mRNA levels reach a lower threshold. Is this just an anomaly of the system or is gene expression pattern of cytokines upon T-cell activation cyclical?
- In data presented Figure 2 and Suppl Figure 2, the authors show correlation between dual cytokine expression and biallelic expression. However, not all dual cytokine expressing cells show bi-allelic expression of both cytokines. It will be useful to know what fraction of cells are biallelic for both genes. Since the experiment was done using two color smFISH, a scatter plot will cluster those dual expressor cells for both cytokines that are also bi-allelic for both genes. Extending this further would be to systematically address protein expression in the various combination of expression patterns. Combining smFISH with immunofluorescence will help address this. Overall, these results will be helpful in getting a better understanding of gene expression patterns during T-cell activation.
- The mRNA localization data presented in Figure 3A and the associated supplemental figure: A better analysis and representation of the data presented in 3A would be a scatter plot of individual cells for their nuclear and cytoplasmic localization of mature mRNA. The authors might also want to extend this analysis based on the data presented in Figure 2 for dual expressors and bi-allelic expression. In other words, do cells with bi-allelic expression have more mRNA localized in the cytoplasm, and does this hold true in dual expressor cells? In the context of translation dependent decay of mRNA, do the dual expressor cells with biallelic expression fare better thereby producing and secreting cytokines continuously?
- The data presented for IFNG in Figure 4 is quite intriguing. In HuR-KO cells at 2h post induction, two of the three donors cell lines have only a small fraction of cells producing protein compared to the controls, however, they are substantially higher than the KO cells at time "0". Surprisingly, the amount of protein produced by these cells (panel B), although statistically lower than the control, is substantially higher than KO cells at "0"h. Does the lone donor cell line with higher number of protein producing cells contribute to majority of the protein produced? There appears to be substantial difference between the three donor cell lines in the number of protein producing cells and mature IFNG mRNA after activation (Suppl Figure 1G & H). The authors may wish to compare the results before combining the data of all three donor cell lines before interpreting the data.
- Also intriguing, HuR knock out results in a significant increase in transcription of IFNG at time "0" (Figure 4, panel E). Despite this, there is a significant loss in transcription of IFNG 2h post activation. However, there is significant accumulation of mature mRNA (panel D). Combined with the protein expression data presented in panels A & B, and the fact that translation induces mRNA decay, how do the authors reconcile this data?
- The differential effect of HuR knock out on poly(A) tail length of IFNG and TNF mRNA is of great importance and the most striking finding in this study! It is generally accepted that poly(A) tail length contributes to mRNA stability and survival. The results presented in Figures 4 and 5 argue otherwise. Only a small fraction of TNF mRNA have full length poly(A) tails, however, the number of mature TNF mRNA in KO cells is much greater than the control even at "0"h. In addition, the TNF mRNA appear to be well translocated into the cytoplasm and effectively translated. Given these conflicting observations, what possible mechanism do the authors envision that can explain this result.
Again, plotting the data presented in Figure 5A as a scatter plot between # of RNA in the cytosol vs nucleus will give a better picture of the localization changes in individual cells. - A more elaborate discussion of the results as it relates to the biology of cytokine gene expression during T-cell activation will immensely strengthen the manuscript.
Minor comment:
- Images of cells with smFISH data (Figures 1, 3 & 4) must be bigger for better visualization. Show images with only a couple of cells enlarged to show the mRNA spots more visibly. Include images with more cells in the supplement instead.
Referee's cross-commenting
I must confess I am not an immunologist, so my knowledge of the intricacies of gene expression in T-cells in very limited. However, I do have a fair sense of transcription regulation and use single molecule approaches, especially smFISH, to address these questions. I agree with the other reviewer the study is of significance, especially the advancement in the ability to do smFISH in primary cells, a challenge that I know first hand. I also have to agree with the other reviewer that the discussion was too short and the authors shied away from the bigger picture of being able to comment on regulation of expression of cytokines during T-cell activation. It is remarkable that they see heterogeneity in gene expression of the individual target genes and bi-allelic expression. The other point of interest is the difference in p(A) tail length and its potential role in regulating TNF gene expression.
Significance
The successful implementation of a modified smFISH protocol used in this study is a welcome resource for all labs that want to study small human primary cells that are difficult to culture on glass coverslips and grow as suspension cultures.
Overall, this work is of high quality and can be better presented to fully explore and discuss the biological implications of the observations from the study. It is not clear to me if the authors wished to present this manuscript reporting an advancement in technology tool to study gene expression during T-cell activation, or a more in-depth study of gene expression.
The study will benefit the larger community that use single molecule approaches to understand genew expression.
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Referee #1
Evidence, reproducibility and clarity
The manuscript by Lattanzio and colleagues uses advanced single molecule FISH, adapted specifically for T cells, to examine RNA transcriptional dynamics in polyclonally stimulated human T cells. By examining the subcellular localisation of both IFNg and TNF mRNAs (nascent and mature), they are able to characterise rate things like rate of transcription and RNA stability. Key findings include the identification of bi-allelic vs mono-allelic transcription at the single cell level which maps to polyfucntion vs monofunctional T cells. Moreover, they identified distinct mechanisms regulating RNA stability and the role of RNA binding …
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
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Referee #1
Evidence, reproducibility and clarity
The manuscript by Lattanzio and colleagues uses advanced single molecule FISH, adapted specifically for T cells, to examine RNA transcriptional dynamics in polyclonally stimulated human T cells. By examining the subcellular localisation of both IFNg and TNF mRNAs (nascent and mature), they are able to characterise rate things like rate of transcription and RNA stability. Key findings include the identification of bi-allelic vs mono-allelic transcription at the single cell level which maps to polyfucntion vs monofunctional T cells. Moreover, they identified distinct mechanisms regulating RNA stability and the role of RNA binding protein HuR in mediating that.
Overall, this is really a proof of concept paper that uses elegant technologies and analysis tools showing just how much information can be obtained from this approach. The ability to examine RNA dynamics and the imapct of RNA binding proteins in regulating RNA stability/translation/transriptoin at a single cell level will be an advance for the field, not just those interested in T cell biology but all cell types.
There are no specific experimental issues that came to mind that need to be addressed and it is really only some minor comments, particularly for the discussion that would strengthen the implicaitons of the study.
- I might have missed it but it wasn't exactly clear from the results or from the methods exactly how nascent vs mature RNA was discriminated. Was this just from the subcellular localisation (i.e nuclear vs cytoplasmic)? RNA imaged close to the TSS? If so, this should be noted somewhere. If there was some other way of precisely ascribing RNA status, this should be outlined (use of primers that targeted intergenic sequences).
- The discussion was very brief and would have benefited from a bit more speculation about the implications of their findings. Specifically, why would there be a need for different cytokine RNAs to be regulated in such distinct ways (IFNg vs IL-2)? Do the authors have any thoughts? Another point is the proposed explanations for the distinct T cell subsets observed that produce cytokines at different levels. While the authors propose three possible explanations, they are presented as being mutually exclusive, of course it could be a combination of all three. Moreover, putting the importance of higher functioning T cells (i.e those that produce more cytokines) into context is also important. Early studies from La Gruta et al., (J Immunol, 2004; doi: 10.4049/jimmunol.172.9.5553), Betts et al, (Blood, 2006 doi.org/10.1182/blood-2005-12-4818) and Darrah et al. (Nat Med, 2007 doi.org/10.1038/nm1592) linked higher cytokine production/multifunctionality to better immune outcomes, while Denton et al (PNAS, 2011, 10.1073/pnas.1112520108) linked the extent of cytokine production to cellular differentiation (and epigenetic landscape at the TNF and IFNg locus). These studies should be cited to provide a setting where this approach will be relevant.
A minor point relates to line 329, that sentence stating "Even though most activated Teff cells express cytokine mRNAs, they display a two order of magnitude difference in mRNA and protein expression."
It is not clear what this is relevant or compared to. A two order of magnitude difference compared to what?
Significance
This is a proof of concept study that demonstrates the utility of the T cell smFISH approach to delineate high resolution analysis of cytokine RNA dynamics at a single cell level, for multiple cytokine RNA species. It clearly provides interesting biology and further understanding of RNA dynamics in activated T cells. I especially appreciated the observation of bi-allelic vs mono-allelic transcription, and the ability to explore the role of RNA binding proteins in RNA regulation.
This technique will have broader applicability and hence will be of interest to those outside T cell immunology. It only requires some minor corrections/revisions.
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