Islet Gene View—a tool to facilitate islet research

Islet Gene View (IGW) is a web resource that makes information on gene expression in human islets from donors easily accessible to the scientific community. The relationship of global RNA expression from 188 donor-islets with islet phenotypes is explored.

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Reviewer #1 (Comments to the Authors (Required)): The paper describes a new tool for organizing gene expression results. It has some novel features that are likely to be of value. The paper seems to have two subjects and that are somewhat related. The first is the presentation of the Islet Gene View, which is a tool that probably has value to some, although there are a growing number of programs that can help with the interpretation of large quantities of data, genetic and otherwise. This approach helped define the co-expression of T2D differentially expressed genes (DEGs) and islet hormone-encoding genes, which has not been as appreciated in other studies.
The second subject is an analysis of two differentially expressed genes, UNC5D and SERPINE2 The selection of these two genes for more detailed study seem somewhat arbitrary but the knock down of these genes in the beta cell line EndoC-betaH1 provided some novel findings.
It is of note that most of the contents of this paper were made public in 2000 on BioRxiv preprint, which led to the addition of data from the group of Solimena. This seems like healthy process for strengthening a study.
Other points: 1. Some care was taken to provide references for some of the techniques, but on page 6, more could have been said about SHAPEIT, Combat and the "Shiny web framework".
3. Page 10: It would be helpful to say more about why certain genes are thought to be interesting, such as HHATL, CHL1 and SLC2A2.
4. Page 12: Please say more about pancreatic stellate cells. How are they identified and why are they included in the analysis? 5. Page 16: The finding about SLC2A2 is of interest because in this study and others, it is a DEG in T2D. This finding has been puzzling because it is generally thought that the key glucose transporter in human beta cells is GLUT1 and not GLUT2. Glut2 has been shown to be important in rodent beta cells. Please comment about this interesting issue.
Reviewer #2 (Comments to the Authors (Required)): The authors developed a web-based tool, the Islet Gene View (IGW) and describe the data acquisition and analysis in detail in the very comprehensive and well written paper. The platform is very useful as "islet organ" is often missing in RNAseq atlas platforms; The organ "pancreas" is not suitable for any extrapolation to islet transcriptomes. Furthermore, the integration and comparison of distinct analyses is very well taken.
Islet transcriptome data acquisition faces some important problems. Addressing these points in the discussion section would explain how the authors deal with this problem and sensitize the reader.
First, the comparability of RNAseq data from different subjects is questionable: in particular the comparison of RNAseq data sets of two very distinct samples: islets of NGT and T2D subjects. The authors (try to) circumvent this problem by comparing multiple distinct data sets and via the correlation between mRNAs of islet hormones and the gene of interest. But the problem remains: NGT islets have a different cell composition then T2D islets, i.e. the proportion between beta cells:alpha cells:delta cells:epsilon cells:endothelial cells:fibroblast:immune cells etc. Thus, differences in RNAseq are not necessarily due to changes within beta cells. Furthermore, the isolation procedure of islets and islet cells differentially change individual mRNA levels. Some mRNAs are more labile and faster degraded then others. Although islet tissue isolated by LCM avoids the problem of enzymatic isolation of islets, the integrity of mRNA is often poor and the islet identification is not very specific as it relies on unspecific autofluorescence of beta cells. Consequently, beta cells are recognized preferentially, however, human islets contain large amounts of alpha cells and the percentage of beta cells decreases between NGT and T2D.
The second point is the interpretation of the functional data: the authors do not explain why, both, reduced expression of UNC5D and of serpine2 affects GSIS and increases apoptosis. However, SERPINE2 mRNA levels are higher, while UNC5D is mRNA levels are lower in T2D islets compared to NGT. Is it a compensatory upregulation of Serpine2 due to defective GSIS or is the expression higher in T2D since SERPINE2 is expressed in NON-beta cells? Do these data shift the correlation (association) to causation? Some minor points: Fat, liver and muscle expression pattern was examined in a subset of patients (n=12) In the discussion, page 15: the statement that the samples are from the same donors. Explain more precisely whether NGT or T2D donors were used for these extra tissues and add the data to suppl. table 1. Does it matter that the donor number is low? Is the variability of RNAseq data between donors lower in fat, liver and muscle then in islets?
Page 16: add the respective protein to the gene CHL1, SLC2A2 and HHATL. Was HHATL described before?
1st Authors' Response to Reviewers June 1, 2022 Reviewer #1 (Comments to the Authors (Required)): The paper describes a new tool for organizing gene expression results. It has some novel features that are likely to be of value. The paper seems to have two subjects and that are somewhat related. The first is the presentation of the Islet Gene View, which is a tool that probably has value to some, although there are a growing number of programs that can help with the interpretation of large quantities of data, genetic and otherwise. This approach helped define the co-expression of T2D differentially expressed genes (DEGs) and islet hormone-encoding genes, which has not been as appreciated in other studies.
The second subject is an analysis of two differentially expressed genes, UNC5D and SERPINE2 The selection of these two genes for more detailed study seem somewhat arbitrary but the knock down of these genes in the beta cell line EndoC-betaH1 provided some novel findings.
It is of note that most of the contents of this paper were made public in 2000 on BioRxiv preprint, which led to the addition of data from the group of Solimena. This seems like healthy process for strengthening a study.
Other points: 1. Some care was taken to provide references for some of the techniques, but on page 6, more could have been said about SHAPEIT, Combat and the "Shiny web framework". Response: Further explanations of the mentioned software have been added to the article. Please see page 6, section 2.4.2 2. Page 8, bottom: more should be said about "Lookups". Response: Further explanation of the term "Lookup" has been added.
3. Page 10: It would be helpful to say more about why certain genes are thought to be interesting, such as HHATL, CHL1 and SLC2A2. Response: We specifically mentioned these three genes since (a) they were also reported in our previous study based on a subset of the islets that were included in our current study and we were able to replicate this in a larger dataset (b) A second reason is elaborated in the discussion on pages 15-16, as potential biomarkers of T2D in islets and potential therapeutic targets. 4. Page 12: Please say more about pancreatic stellate cells. How are they identified and why are they included in the analysis? Response: In Segerstolpe et al, 54 pancreatic stellate cells were identified based on high expression of collagen genes, matrix metalloproteinases, TIMP1, FN1, POSTN, and ACTA2.
Given that bulk RNA sequencing reflects expression of multiple islet cell types, and our islets had varying purity, we looked-up the expression of our DEGs in single cell RNAseqencing from Segerstolpe et al to see in which cell types they were expressed, and to what extent the DEGs could from the exocrine component as well.

Page 16:
The finding about SLC2A2 is of interest because in this study and others, it is a DEG in T2D. This finding has been puzzling because it is generally thought that the key glucose transporter in human beta cells is GLUT1 and not GLUT2. Glut2 has been shown to be important in rodent beta cells. Please comment about this interesting issue. Response: It is indeed true that GLUT1 is more highly expressed in islets and have a higher affinity for glucose at lower glucose concentrations, while GLUT2 has a lower affinity and thus requires elevated glucose levels to be more active. However, both GLUT2 and GLUT3 have been observed in other studies to be expressed in human islets. GLUT2 may be affected by diabetes due to the differences in blood glucose levels.
Finally, we would like to thank Reviewer 1 for your very thoughtful, insightful and helpful comments.
Reviewer #2 (Comments to the Authors (Required)): The authors developed a web-based tool, the Islet Gene View (IGW) and describe the data acquisition and analysis in detail in the very comprehensive and well written paper. The platform is very useful as "islet organ" is often missing in RNAseq atlas platforms; The organ "pancreas" is not suitable for any extrapolation to islet transcriptomes. Furthermore, the integration and comparison of distinct analyses is very well taken.
Islet transcriptome data acquisition faces some important problems. Addressing these points in the discussion section would explain how the authors deal with this problem and sensitize the reader.
First, the comparability of RNAseq data from different subjects is questionable: in particular the comparison of RNAseq data sets of two very distinct samples: islets of NGT and T2D subjects. The authors (try to) circumvent this problem by comparing multiple distinct data sets and via the correlation between mRNAs of islet hormones and the gene of interest. But the problem remains: NGT islets have a different cell composition then T2D islets, i.e. the proportion between beta cells:alpha cells:delta cells:epsilon cells:endothelial cells:fibroblast:immune cells etc. Thus, differences in RNAseq are not necessarily due to changes within beta cells. Furthermore, the isolation procedure of islets and islet cells differentially change individual mRNA levels. Some mRNAs are more labile and faster degraded then others. Although islet tissue isolated by LCM avoids the problem of enzymatic isolation of islets, the integrity of mRNA is often poor and the islet identification is not very specific as it relies on unspecific autofluorescence of beta cells. Consequently, beta cells are recognized preferentially, however, human islets contain large amounts of alpha cells and the percentage of beta cells decreases between NGT and T2D.
Response: The reviewer's point is well-taken and we have added this to the discussion (page 19). We completely agree with the reviewer that bulk RNA sequencing of islets comes with its own set of challenges, the predominant one being the variation in cell composition between the T2D and NGT donors. We also agree that the RNAseq differences do not necessarily reflect changes within beta cells per se. Isolation procedures can also contribute towards variability in expression patterns across individuals. The expression changes that are seen between T2D and NGT donors indeed reflects this change in cell composition. Secondly, there are potentially genes which are expressed ubiquitously in islet cells and have common regulatory roles across multiple cell types. Furthermore, we have included single-cell expression data to show cell type specific expression patterns. One advantage conferred by the bulk-seq is that we can also observe the specific value of looking at gene expression data across a larger number of subjects, with bulk-seq capturing inter-individual differences to a much greater extent, which is prohibitively expensive to do at the single-cell level at present.
The second point is the interpretation of the functional data: the authors do not explain why, both, reduced expression of UNC5D and of serpine2 affects GSIS and increases apoptosis. However, SERPINE2 mRNA levels are higher, while UNC5D is mRNA levels are lower in T2D islets compared to NGT. Is it a compensatory upregulation of Serpine2 due to defective GSIS or is the expression higher in T2D since SERPINE2 is expressed in NON-beta cells? Do these data shift the correlation (association) to causation?

Response:
Thank you for raising this point. We agree with the reviewer's point of view regarding SERPINE2 and hypothesize that it could be both compensatory upregulation in beta-cells or paracrine effect from nonbeta-cells. Interestingly when human beta-cells (EndoC-βH1) exposed to cytokines (IL-1β, TNF-α and IFN-γ) for 48h which are implicated in T2D inflammation, a significant induction of SERPINE2 expression is observed ( Figure R1), indicates that it could be a compensatory upregulation during progression of T2D. Also, SERPINE2 is a secreted protein (ref. Farrell DH et. al. and Baker JB et. al.), being well expressed in exocrine and alpha-cell compartment their paracrine effect on beta-cells could not be ruled out and called for a new detailed study which we think not fit in the present manuscript scope ( Figure R2). Yes, we agree with the reviewer that it needs some caution while interpreting the differential expressed target genes.   Some minor points: Fat, liver and muscle expression pattern was examined in a subset of patients (n=12) In the discussion, page 15: the statement that the samples are from the same donors. Explain more precisely whether NGT or T2D donors were used for these extra tissues and add the data to suppl. Page 16: add the respective protein to the gene CHL1, SLC2A2 and HHATL. Was HHATL described before? Response: Further descriptions of the respective proteins will be added to the manuscript. HHATL was mentioned in our previous analysis including a smaller subset of islets (Fadista et al). The current study builds upon and reports additional results. Furthermore, functions of HHATL have previously been analyzed in the context of myocardial tissue and cellular apoptosis, but has not been characterized in islets.
Response: the mentioned references has been corrected.
Finally, we would like to thank Reviewer 2 for your very thoughtful, insightful and helpful comments. Thank you for submitting your revised manuscript entitled "Islet Gene View -a tool to facilitate islet research". We would be happy to publish your paper in Life Science Alliance pending final revisions necessary to meet our formatting guidelines.
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