RiboTRAP-seq identifies spatially distinct functions for the anterior and posterior intestine in immune and metabolic regulation in C. elegans

Reviewer #1 (Public review):

Summary

In this study, the authors have performed tissue-specific ribosome pulldown to identify gene expression (translatome) differences in the anterior vs posterior cells of the C. elegans intestine. They have performed this analysis in fed and fasted states of the animal. The data generated will be very useful to the C. elegans community, and the role of pyruvate shown in this study will result in interesting follow-up investigations.

However, several strong claims made in the study are solely based on in silico predictions and are not supported by experimental evidence.

Strengths:

Several studies in the past have predicted different functions of the anterior (INT1) vs posterior (INT2-9) epithelial cells of the C. elegans intestine based on their anatomy and ultrastructure, but detailed characterization of differences in gene expression between these cell types (and whether indeed these are different 'cell types') was lacking prior to this study. The genes and drivers identified to be exclusively expressed in the anterior vs posterior segments of the intestine will be very helpful to selectively modulate different parts of the C. elegans intestine in future studies.

Another strength of this study is the careful experimental design to test how the anterior vs posterior cell types of the intestine respond differently to food deprivation and recovery after return to food. These comparisons between 'states' of a cell in different physiological conditions are difficult to pick up in single-cell analyses due to low sequencing depth, which can fail to identify subtle modulation of gene expression.

The TRAP-associated bulk RNA-seq approach used in this study is more suitable for such comparisons and provides additional information on post-transcriptional regulation during metabolic stress.

A key finding of this study is that pyruvate levels modulate the translation state of anterior intestinal cells during fasting. Characterization of pyruvate metabolism genes, especially of the enzymes involved in its mitochondrial breakdown, provides novel insights into how gut epithelial cells respond to the acute absence of food.

Weaknesses:

Unlike previous TRAP-seq studies (PMID: 30580965, 36044259, 36977417) that reported sequencing data for both input and IP samples, this study only reports the sequencing data for IP samples. Since biochemical pulldowns are variable across replicates, it is difficult to know if the observed differences between different conditions are due to biological factors or differences in IP efficiency. More importantly, since two different TRAP lines were utilized in this study and a large proportion of the results focus on the differences between the translational profiles of INT1 vs INT2-9 cells, it is essential to know if the IP worked with similar efficiency for both TRAP strains that likely have different expression levels of the HA-tagged ribosomal protein. One way to estimate this would be to perform qRT-PCR of genes that are known to be enriched in all intestinal cells and determine whether their fold-enrichment over housekeeping genes (normalized to input) is similar in INT1 vs INT2-9 TRAP strains and across the fed vs fasted conditions. The authors, in fact, mention variability across biological replicates, due to which certain replicates were excluded from their WGCNA analysis.

It appears that GFP expression is also detectable in INT2 (in addition to strong expression in INT1 in Fig.1A). Compared to INT3-9, which looks red, INT2 cells appear yellow, suggesting that the expression patterns of the two TRAP drivers are not mutually exclusive, which changes the interpretation of many of the results described in the study.

Some parts of the study overemphasize the differences between the INT1 vs INT2-9 cell types, which is a biased representation of the results. For example, the authors specifically point out that 270 genes are differentially expressed in opposite directions in INT1 vs INT2-9 cell types during acute (30 min) fasting without mentioning the 1,268 genes that are differentially expressed in the same direction. They also do not mention here that 96% of the genes are differentially expressed in the same direction in INT1 and INT2-9 cell types after prolonged (180 min) fasting, suggesting that the divergent translational responses of these cell types are only observed in the first 30 minutes of food deprivation. Similar results have also been reported for the effect of fasting on locomotory and feeding behaviors, where 30 min of fasting produces more variable effects, which become more consistent after longer periods of fasting (PMID: 36083280). Hence, the effects of brief food deprivation should be interpreted with caution.

Many of the interpretations of this study primarily rely on pathway enrichment analyses, which are based on the known function of genes. The function of uncharacterized genes that were found to be differentially expressed in INT1 vs INT2-9 cell types, e.g., the ShKT proteins, was not explored in this study. In addition, overreliance on pathway enrichment tools (instead of functional validation) has resulted in several conflicting findings. For example, one of the main messages of this study is that INT1 cells specialize in immune and stress response in response to fasting, which relies on pathway analysis in Figs 5E and 5F. However, pathway analysis at a different time point (shown in Figure S5A) indicates that INT2-9 cells show a much stronger increase in translation of stress and pathogen-responsive genes compared to INT1 cells. Hence, some of the results should be interpreted as different translational effects in INT1 vs INT2-9 cells after different lengths of food deprivation, without making broad claims about selective pathways being affected only in specific cell types.

The authors have compared their TRAP-seq results with genes enriched in the anterior and posterior intestine clusters from a previously published whole-animal adult scRNA dataset (PMID: 37352352). They claim that their TRAP-seq results are in agreement with the findings of the scRNA study. However, among the 10 genes from the 'posterior intestine' scRNA cluster in Fig.S1E, six are downregulated in the INT1 vs INT2-9 comparison, while four are upregulated. Hence, there is no clear agreement between the two studies in terms of the top enriched genes in the anterior vs posterior intestine, which should be considered for cross-study comparisons in the future.

The authors describe in the manuscript that they have performed INT1-specific RNAi for two C-type lectin genes that are upregulated during fasting. Due to a recent expansion of C-type lectin genes in C. elegans, there is a high chance of off-target effects of RNAi that is designed for members of this gene family. More trustworthy results could have been obtained using CRISPR-based loss-of-function alleles for these genes, one of which is publicly available. Also, the authors do not provide any explanation for why knockdown of these stress-response genes, which are activated in INT1 cells in response to food deprivation, results in improved resistance to pathogens. This, in fact, suggests a role of INT1 cells in increasing pathogen susceptibility, and not pathogen resistance, during food deprivation.

Many of the studies in this field (e.g., references 2-4 in this article) have investigated the effects of food deprivation ranging from 4 hr to 24 hr, which results in activation of starvation responses in C. elegans. In contrast, the authors have used shorter time periods of fasting (30 min and 180 min), and most of their follow-up experiments have used 30 min of food deprivation. Previous work has shown that the effects of food deprivation can either accumulate over time (i.e., the effect gets stronger with longer food deprivation) or can be transient (i.e., only observed briefly after removal of food and not observed during long-term food deprivation). Starvation-induced transcription factors such as DAF-16/FoxO and HLH-30 show strong translocation to the nucleus only after 30 min of fasting. Though gene expression changes in all stages of food deprivation are of biological relevance, the authors have missed the opportunity to explore whether increased INS-7 secretion from the anterior intestine is dependent on these starvation-induced transcription factors (which can be easily tested using loss-of-function alleles) or is due to other fast-acting regulatory mechanisms induced due to the absence of food contents in the gut lumen. A previous study (PMID: 40991693) has shown that DAF-16 activation during prolonged starvation shuts down insulin peptide secretion from the intestinal epithelial cells. Hence, it is not clear if increased INS-7 secretion is only a feature of short-term food deprivation or is also a signature of long-term starvation (e.g., at 8 hr or 16 hr timepoints). Since most of the INS-7 secretion data in this study are for 30 min of fasting, it remains unknown whether the discovered regulators of INS-7 secretion can be generalized for extended food deprivation that triggers major metabolic changes, such as fat loss (e.g., conditions shown in Figure 1D).

Two previous studies (PMID: 18025456, 40991693) have shown a strong reduction in the expression of ins-7 in the anterior intestine using GFP-based reporters (both promoter fusions and endogenous CRISPR-generated) and in whole-animal RNA-seq data from starved animals. These results are in contrast to the increased INS-7 secretion from INT1 cells during fasting that is reported in this study. The authors here have reported that INS-7 translation is higher in INT1 compared to INT2-9 during fed, acute fasted, and chronic fasted conditions, but they have not shown whether INS-7 translation is upregulated during acute and chronic fasting in INT1 cells in their TRAP-seq analysis. Knowing whether increased INS-7 secretion during acute fasting is due to increased transcription, translation, or secretion of INS-7 is crucial to resolve the discrepancy between these studies.

Reviewer #2 (Public review):

Summary:

In this study, the authors set out to understand whether the discrete segments of the C.elegans intestine were specialized to carry out distinct functions during an animal's exposure and adaptation to a fast-changing nutrient environment. To achieve this, the authors used a method called Translating ribosome affinity purification (TRAP), which provides a snapshot of what genes are being translated into proteins (and therefore functionally prioritized by the animal) under different fasting and re-feeding conditions. By expressing the TRAP constructs in two distinct segments of the intestine (INT1) and (INT2-9), the authors were able to identify how these segments responded to changing nutrient availability.

Already under steady state nutrient conditions, the authors found that INT1 and INT2-9 appeared to have different 'tasks', with INT1 expressing more immune- and stress-response related genes. Exposing animals to different regimens of starvation and refeeding also showed marked differences between the intestinal segments, and the gene expression patterns in INT1 were consistent with INT1 cells playing an integrative role in linking nutrient cues to the secretion of insulin molecules that regulate fat metabolism with food intake. In summary, the data presented catalogue, for the first time, gene expression differences between two areas of the intestine, suspected to play different roles, and through clever experiments, links these gene expression changes to responses to nutrient availability.

Strengths:

The data presented catalogue - for the first time and in a careful manner - gene expression differences between two areas of the intestine. They strongly support the presence of intriguing differences between two areas of the intestine in immune, metabolic, and stress-response regulation, and link these gene expression changes to the responses of these regions to nutrient availability.

Weaknesses:

The conclusions of this paper are mostly well-supported by data, but the relevance of the changing gene expression patterns could be better clarified and extended in the discussion.

Reviewer #3 (Public review):

Summary:

In this study, Liu and colleagues utilize TRAP-seq to profile the repertoire of actively translated mRNAs in different intestinal cell types (anterior INT1 vs. posterior INT2-9 cells) in C. elegans. A key goal of this study was to identify transcripts differentially expressed/translated between these intestinal cell subtypes in the context of animals being well fed or subjected to acute (30 minutes) or chronic (3 hours) starvation, followed by refeeding.

The authors identify a number of differentially expressed genes across all of the conditions tested. They then provide an initial survey of the landscape of translatome changes through Weighted Gene Network Correlation Analysis (WGNA), and some high-level functional surveys via Gene Ontology (GO) term analysis and protein domain analysis. The authors validate the enriched expression patterns of some of their identified candidate genes using fluorescent promoter fusion reporters, confirming INT1-specific expression. The authors further implicate the role of several other candidate genes in pathogen avoidance and in response to nutritional cues by knocking them down specifically in INT1 cells by RNAi. Finally, the authors identify pyruvate as a major nutrient signal coming from the bacterial diet that suppresses the release of a key insulin peptide (INS-7), and identify some of the genes expressed in INT1 that are required for this response.

Strengths:

(1) Good use of and justification for TRAP-seq, because scRNA-seq would be difficult under the varied conditions used (starvation, refeeding).

(2) The manuscript is generally clear to read, and the data are generally well-presented with good supporting data that includes replicates, sample sizes, error measurements, and associated statistics.

(3) The dataset will be an interesting resource to mine for future studies focusing on mechanisms of how particular intestinal cell types respond to different environmental signals.

Weaknesses:

(1) A limitation of TRAP-seq, although powerful, is that only relative comparisons can be made between genotypes/conditions to identify differentially-expressed genes, rather than assessing whether a given gene is expressed at a certain level in a cell type under a certain condition. This limitation is due to the non-specific association of sticky RNA species with the beads during the immunoprecipitation step. This is a minor point, however, and the authors do a nice job of focusing their analysis on differentially expressed transcripts in the current study.

(2) Another limitation of the current study is that the experiments testing the role of candidate genes identified by their profiling experiments do not delve a bit deeper into providing a mechanistic understanding of the phenotypes being studied. At present, the results are thus viewed more as a genomics-based screen with some limited follow-up on interesting hits. However, this reviewer appreciates that when placed in the context of the work presented, a presentation of the profiling data along with some validation is an excellent starting point for future mechanistic studies elaborating on these interesting candidates.

Appraisal of whether the authors achieved their aims, and whether the results support their conclusions:

The main goal of the study was to survey the dynamic responses at the level of actively translated mRNAs of the INT1 vs INT2-9 cells in response to metabolic challenge.

Overall, the authors use established methods to perform their genome-wide analysis, and the set of differentially regulated genes is enriched for expected molecular functions and forms coherent networks in anticipated pathways.

The validation experiments (promoter::GFP fusion reporters, INT1-specific knockdowns of highly regulated genes) further corroborate the quality of the TRAP-seq datasets generated.

I have a few points for the authors that would further strengthen this work:

(1) The authors rightfully focus on the top differentially-regulated candidates, but it's unclear at present how far down their fold change list would lead to expression pattern validations. It would be useful to test a few more promoter::GFP fusion reporters at different enrichment/fold-change/statistical cutoffs.

(2) Although the INT1-specific RNAi provides a convenient strategy for rapidly perturbing and testing genes of interest for phenotypes, independently validating the knockdowns with genetic mutants, or alternatively (if genes are essential), degron alleles.

Impact:

The TRAP-seq data and list of differentially-expressed candidate genes will form an interesting set of high-priority candidates to study for their role in the reception and transduction of nutritional cues in response to food status and pathogens. This data will thus benefit the C. elegans community of researchers studying the mechanisms governing these phenomena.