
==== Front
iScience
iScience
iScience
2589-0042
Elsevier

S2589-0042(24)01869-8
10.1016/j.isci.2024.110644
110644
Article
Disruption of perinatal myeloid niches impacts the aging clock of pancreatic β cells
O’Sell Jessica 1
Cirulli Vincenzo 1
Pardike Stephanie 1
Aare-Bentsen Marie 1
Sdek Patima 1
Anderson Jasmine 1
Hailey Dale W. 2
Regier Mary C. 3
Gharib Sina A. 4
Crisa Laura lcrisa@uw.edu
15∗
1 Department of Medicine, Diabetes Institute, and Institute of Stem Cells and Regenerative Medicine, University of Washington, Seattle WA 98109, USA
2 Department of Laboratory Medicine and Pathology, and Institute of Stem Cells and Regenerative Medicine, University of Washington, Seattle WA 98109, USA
3 Institute of Stem Cells and Regenerative Medicine, University of Washington, Seattle WA 98109, USA
4 Computational Medicine Core at Center for Lung Biology, Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle, WA 98109, USA
∗ Corresponding author lcrisa@uw.edu
5 Lead contact

07 8 2024
20 9 2024
07 8 2024
27 9 11064425 2 2024
25 6 2024
30 7 2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Summary

Perinatal expansion of pancreatic β cells is critical to metabolic adaptation. Yet, mechanisms surveying the fidelity by which proliferative events generate functional β cell pools remain unknown. We have previously identified a CCR2+ myeloid niche required for peri-natal β cell replication, with β cells dynamically responding to loss and repopulation of these myeloid cells with growth arrest and rebound expansion, respectively. Here, using a timed single-cell RNA-sequencing approach, we show that transient disruption of perinatal CCR2+ macrophages change islet β cell repertoires in young mice to resemble those of aged mice. Gene expression profiling and functional assays disclose prominent mitochondrial defects in β cells coupled to impaired redox states, NAD depletion, and DNA damage, leading to accelerated islets’ dysfunction with age. These findings reveal an unexpected vulnerability of mitochondrial β cells’ bioenergetics to the disruption of perinatal CCR2+ macrophages, implicating these cells in surveying early in life both the size and energy homeostasis of β cells populations.

Graphical abstract

Highlights

• Perinatal loss of CCR2+ macrophages changes the repertoire of pancreatic β cells

• It primes β cells for premature aged phenotypes and mitochondrial failure

• Impaired redox states lead to accelerated decline of pancreatic islets’ function

Physiology; Immunology; Cell biology; Transcriptomics

Subject areas

Physiology
Immunology
Cell biology
Transcriptomics
Published: August 7, 2024
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pmcIntroduction

Timed cell proliferation and functional specialization of cellular progenies are critical determinants of organ functions in virtually all tissues. The development of functional pancreatic islets is no exception to this rule. Hence, pancreatic islets and, specifically, β cells are formed by a timed progression of events that include endocrine specification during embryogenesis, maximal cell expansion in perinatal life, and then quiescence and functional specialization in adulthood.1 These programs establish not only the size but also the cellular diversity of β cell pools, both of which can affect long-lasting glucose homeostasis.

Single-cell transcriptomic and proteomic studies have shown that in both humans and mice, the heterogeneity of pancreatic β cells reflects a broad spectrum of cell functionalities. Thus, the existence of β cell subpopulations differing in the levels of hormone production, resistance to ER stress, replicative capabilities, and susceptibility to senescence has emerged from those studies.2,3,4,5,6 Adding to this complexity, there is evidence that environmental cues may impact the diversity of pancreatic islet cell pools with outcomes that either allow for metabolic adaptation or lead to glucose intolerance or diabetes. Thus, injuries that lead to the sudden loss of most β cells in youth can trigger the trans-differentiation of new β-like cells from other endocrine cell types, allowing to re-establish metabolic control.7,8 Conversely, under- or over-nutrition in fetal life and chronic exposure to heightened metabolic pressure in adulthood may expand pools of dedifferentiated β cells that can no longer ensure glycemic control.9,10,11,12,13 While these studies have highlighted the plasticity of endocrine cell types in response to extrinsic signals, there is limited knowledge on whether there are cellular components of the islet microenvironment that can condition the emergence of adaptive or maladaptive β cell pools. Indeed, to what extent β cell diversity reflects a fixed set of endocrine subpopulations arising during development or is dynamically shaped by changes of the islet niche over time remains unclear. To date, the type and timing of tissue environmental cues permissive to β cell adaptation vs. those predisposing to β cell failure remain poorly characterized.

A setting in which β cell heterogeneity may arise is cell proliferation. In the mouse, the perinatal period, i.e., the time at which islet cell proliferation is at its peak may, therefore, represent a stage in which functionally diverse pools of β cells are established. Among extrinsic cues contributing to the expansion of β cells at this stage in life, we have previously identified neonatal CCR2+ macrophages, a population of myeloid cells of fetal origin14,15 resident in the neonatal pancreas, as critical to β cell expansion.16 Selective depletion of this macrophage population dramatically blocks β cell proliferation at birth, leading to transient glucose intolerance in neonates. Nevertheless, allowing for myeloid cell repopulation of the pancreas permits a recovery of islet growth competency and reestablishment of glucose homeostasis in young mice.16 Here, we set out to investigate whether, beyond this adaptive response, transiently stalling β cell replication through perinatal disruption of CCR2+ macrophages impact islet β cell repertoires and tissue function long-term. Using an animal model that allows for transient ablation of CCR2+ macrophages17 and profiling of β cell transcriptome by scRNA-seq over time, we find that perinatal disruption of these innate immune cells triggers prematurely, in young mice, changes in β cell phenotypes and function resembling those observed in aged mice. These include decreased glucose tolerance, drifting of β cell identity toward conflicted poly-hormonal phenotypes, and prominent mitochondrial defects from which β cells do not seem to recover. These findings document a functional link between peri-natal myeloid niches and mitochondrial bioenergetics in β cells and indicate that changes in this functional relationship may condition early in life both the size and the quality of functional β cell pools, setting the clock by which islets’ endocrine functions decline with age.

Results

Transient ablation of CCR2+ myeloid cells in peri-natal life leads to glucose intolerance and defective insulin secretion in late adulthood

We previously reported that ablation of CCR2+ myeloid cells in newborn CCR2DTR/+ mice during the first ten days of life results in transient glucose intolerance, which, upon withdrawal of DT treatment, resolves by 4 weeks of age.16 The return to normal glucose homeostasis is associated with repopulation by CCR2+ macrophages, catch-up growth of the whole pancreas, and apparent normalization of β cell mass as measured by morphometric analysis of insulin+ areas across the organ.16

To determine whether these mice would be able to maintain glucose homeostasis throughout late adulthood, DT-treated CCR2DTR/+ mice and wild-type littermates, as well as untreated controls, were weaned to regular chow at 21 days, grouped by sex, and monitored for changes in glucose homeostasis by intra-peritoneal glucose tolerance tests (IPGTT). We found that by 12 weeks of age, DT-treated CCR2DTR/+ female mice displayed reduced glucose tolerance compared to controls (Figure 1A) in the absence of significant weight gain (Figure S1A). In contrast, no significant differences in glucose tolerance were detected in DT-treated CCR2DTR/+ males as compared to controls (Figure 1B), presumably due to overlapping effects of weight gain and decreased peripheral insulin sensitivity known to occur in male C57BL/6J mice over time.18Figure 1 Transient perinatal disruption of CCR2+ macrophages leads to impaired glucose tolerance and defective insulin secretion in adult female C57/B6LJ mice

(A and B) Glucose tolerance curves and area under the curves (AUCs) assessed by IPGTT in 12 weeks old female (A) and male (B) CCR2DTR/+ and WT mice. Mice were untreated (gray curves) or treated with DT (red curves) for 10 days after birth. At 21 days, they were weaned to and maintained on a regular chow diet. Mean ± SEM, n = 6–8 in A, and n = 7–10 in B.

(C–E) Glucose-stimulated insulin secretion (C), insulin secretion in response to KCl stimulation (D), and total insulin content (E) in islets isolated from 6 months old DT-treated WT and CCR2DTR/+ mice and untreated controls. Mean ± SEM, n = 6–9. ∗p < 0.05. ∗∗p < 0.001. Statistical analyses are unpaired one-tailed Student’s t tests in A and B, and unpaired two-tailed Student’s t tests in C–E.

To further compare the ability of DT-treated CCR2DTR/+ and control mice to compensate for dietary stress, cohorts of female mice were maintained on chow up to the age of 12 months and then subjected to a high-fat diet for 4 months. These studies revealed a significant worsening of glucose intolerance to overt diabetic ranges in DT-treated CCR2DTR/+ mice compared to controls (Figure S1B). Under these feeding conditions, blood glucose concentrations in aged DT-treated CCR2DTR/+ mice averaged ∼205 mg/dL at fasting and 280 mg/mL 2 h after glucose challenge, with an overall 30% increase of the whole glucose excursion after glucose loading, as measured by the area under the curve (AUC) of glucose tolerance tests (Figure S1B). There were no statistically significant differences in body weights between groups undergoing the same treatment (i.e., DT-treated CCR2DTR/+ = 48.6 ± 8.9 g, DT-treated WT = 49.9 ± 8.9 g; untreated CCR2DTR/+ = 40 ± 0 g; untreated WT = 38.1 ± 5.5 g; mean ± SD, n = 2–3). Hence, progression from glucose intolerance to frank diabetes induced by aging and dietary stress is accelerated in DT-treated CCR2DTR/+ females.

To further investigate insulin secretory functions independently of the potentially confounding effects of peripheral mechanisms of glucose disposal, pancreatic islets were isolated from chow-fed 6-months old mice and stimulated with either 2.8 mM or 16.7 mM glucose in vitro. We found that islets from DT-treated CCR2DTR/+ mice exhibited decreased insulin secretory response to glucose (Figure 1C), whereas insulin secretion in response to KCl depolarization was unaffected (Figure 1D). Total insulin content was also markedly reduced in the islets of DT-treated CCR2DTR/+ mice (Figure 1E).

Taken together, these results indicate that despite the apparent recovery in islet cell mass, β cells that experience transient depletion of pro-replicative myeloid cells and growth arrest in perinatal life are programmed to become dysfunctional later in life, prematurely losing adaptive capacity to dietary stress with age.

Single-cell resolution analysis of islet cell types reveals accumulation of β-like populations following CCR2+ myeloid cell depletion

To investigate possible changes in islet cell composition following perinatal depletion of CCR2+ macrophages, pancreatic islets were isolated from DT-treated CCR2DTR/+ and WT control females 4 weeks and 6 months after DT withdrawal and processed for scRNA-seq. Graph-based clustering using t-distributed stochastic neighbor embedding (tSNE) identified transcriptionally distinct cell populations. The identity of endocrine and non-endocrine cell types was established based on the expression of cell type-specific genes. Cell populations included transcriptionally heterogeneous β and “β-like cells (identified by Ins1 and Ins2, Ucn3, MafA, NxK6.1, Pdx-1, Pax6, Prlr, and Glp1r), α- and α-like cells (Gcg, Arx, Irx1, Irx2, and MafB), delta cells (Sst and Pyy) gamma cells (Ppy), endothelial cells (Cd31, Flk1, and Kdr), ductal cells (Krt19), smooth muscle cells (Acta2), and myeloid cells (Lyz2) (Figure 2A). Smaller clusters included acinar cells and cells with uncertain identities, which were cataloged as “other”. Further analysis of the clusters by sample revealed that select clusters, herein referred to as “β-like”, were over-represented in the islets of young 4 weeks old DT-treated CCR2DTR/+ mice as compared to those of WT littermate controls (Figure 2A, left panel), as well as in aged 6 months old mice of either genotype as compared to young mice (Figure 2A, right panels). Cells identified as β-like represented a minor subpopulation, i.e., 8% of total endocrine cells in young WT mice, accounting for about 17% of the total β cells (Figure 2B). In contrast, in young CCR2DTR/+ mice they represented 24% of total islet endocrine cells, i.e., about 50% of total β cells (Figure 2B). In aged mice of either genotype, they represented up to about 70% of total β cells (Figure 2B, right panel).Figure 2 Integrated scRNA-seq analysis of islet cell populations from 1 month to 6 months old DT-treated wild type and CCR2DTR/+ mice

(A) tSNE plots of islet cell populations identified by Partek in 1 month- and 6 months-old DT-treated WT and CCR2DTR/+ female mice. Each population is colored based on cell type-specific biomarkers.

(B) Percentages of endocrine cell populations calculated from each islet sample shown in A. Values were derived from the analysis of 8,834 and 9,423 islet cells from 1 month-old WT and CCR2DTR/+, and 3,774 and 4,460 islet cells from 6 months-old WT and CCR2DTR/+ mice, respectively.

Distinct poly-hormonal and mitochondrial transcriptional profiles of β and β-like cell populations from DT-treated CCR2DTR/+ mice

Analysis of transcriptional profiles revealed that whole β-like cells expressed similar levels of Ins1 and Ins2 transcripts compared to conventional β cells but exhibited increased levels of glucagon (Gcg) and pancreatic polypeptide (Ppy) transcripts (Figures 3A and 3B). Furthermore, levels of transcription of β cell maturation markers and transcription factors critical to maintaining β cell identity (e.g., Ucn3, Pdx-1, MafA, and Nkx6.1) were profoundly down-regulated in β-like cells (Figure 3B). In contrast, they maintained relatively high levels of Mlxipl, a transcription factor functioning as a negative regulator of β cell maturity19 and had negligible expression of transcription factors marking early endocrine progenitors (e.g., Neurog3) and α-cell lineage (e.g., Arx) (Figure 3B). Compared to conventional β cells, genes involved in hormone processing and secretion, including Pcsk1, Pcsk2, Syt13, and Sytl4, were expressed at much lower levels in β-like cells (Figure 3B). Interestingly, analysis of glucagon transcription across the 4 islet samples revealed that aberrant subliminal transcription of this gene, while most evident in the β-like clusters, also occurs in some conventional β cells of young DT-treated CCR2DTR/+ mice (Figure 3C). Multiplex in situ hybridization of glucagon and insulin gene transcripts using RNAscope confirmed higher counts of glucagon-specific transcripts within insulin-positive areas in DT-treated CCR2DTR/+ mice (Figures 3D and 3E).Figure 3 Poly-hormonal and de-differentiated phenotypes of β-like cell populations

(A) Violin plots showing expression levels of select genes in whole β and β-like populations (colored violin plots) as compared to other islet cell populations (white violin plots). Within each violin plot, the continuous line indicates the mean, and the dashed line the median of gene expression.

(B) Heatmaps comparing expression levels of hormones, hormone-processing enzymes, transcription factors, and mitochondrial genes in whole β and β-like populations.

(C) Expression map of glucagon (Gcg) transcription in β and β-like populations in the indicated islet samples. Refer to Figure 2A for position of β and β-like clusters in tSNE plots. Data show log2 counts of Gcg expression above those detected in conventional β cells of 1 month-old WT mice, as baseline reference. Glucagon transcription above this baseline is detected in β-like clusters at all ages and in some β cells of young DT-treated CCR2DTR/+ mice.

(D) RNAscope of pancreatic islets isolated from 1 month-old DT-treated WT and CCR2DTR/+ female mice, probed for Gcg (green), Ins1 (red), and Ins2 (white) RNAs. Nuclei are stained with DAPI. Middle panels show the Ins1+ area (yellow contour) in which Gcg-specific RNA puncta were counted, and right panels show magnified insets for visualization of Gcg RNA puncta detected within Ins1+ areas.

(E) Boxplot showing the quantification of Gcg RNA puncta expressed within Ins1+ areas counted in the indicated experimental groups. The line at the center of each box represents the medians. Counts were normalized to Ins1+ areas. Statistical analysis is one-way ANOVA followed by Bonferroni post-hoc test. ∗p < 0.05. ∗∗p < 0.001. ∗∗∗p < 0.0001.

Another class of genes down-regulated in β-like compared to conventional β cells was related to mitochondrial functions (Figure 3B, far right heatmap). This observation suggested further heterogeneity of β cells with regard to transcription of mitochondrial genes. We, therefore, analyzed cell populations, focusing on the abundance of mitochondrial reads. Visualization of low to intermediate ranges of mitochondrial reads on tSNE plots showed that cell populations with this signature were similarly enriched in α- and β-like clusters across the four islet samples (Figure 4A). However, a quantitative analysis of cell populations expressing low, intermediate, or high % of mitochondrial reads revealed notable differences in population frequencies in WT and CCR2DTR/+ mice as a function of age and macrophage depletion. Specifically, a moderate increase in the frequency of cells with low (i.e., <3%) mitochondrial reads, mainly limited to β-like cells, was noted in aged WT mice (Figure 4B, left panels, first column). This age-dependent phenotype was more prominent in β-like cells from DT-treated CCR2DTR/+ mice and extended to conventional β cells of young CCR2DTR/+ mice (Figure 4B, left panels, second column). A similar increase in the frequency of cells with low mitochondrial reads was evident in the comparison of β and β-like cells from CCR2DTR/+ vs. WT mice matched by age (Figure 4B, right panels), indicating that both aging and macrophage loss correlate with this phenotype. In contrast, no significant differences in the frequency distribution of mitochondrial reads were detected within α-cells across age- or genotype-based comparisons (Figure 4B, first row).Figure 4 Frequency distribution of mitochondrial reads in α-, β-, and β-like populations

(A) tSNE plots showing the distribution of cells expressing the lowest levels (i.e., bottom 75%) of mtDNA reads of the indicated islet samples. The lowest mtDNA reads map to α-cell and β-like clusters (upper and lower panels, respectively).

(B) Frequency distribution analysis of mtDNA reads in α-, β-, and β-like populations, arbitrarily grouped as low (0–3%), intermediate (3–6%), and high (6–10%) expressors. Comparisons by age (left panels) and by genotype/MAC (macrophage) depletion (right panels) are shown. In DT-treated WT mice, cells exhibiting low mtDNA reads are enriched primarily in β-like populations and more so as mice age, whereas their frequency increases substantially in both β and β-like populations of young DT-treated CCR2DTR/+ mice and β-like populations of aged DT-treated CCR2DTR/+ mice. Minor changes in frequency of mtDNA reads are observed in α-cells across ages and genotypes.

These data provide evidence for an accelerated progression of β cell populations from young DT-treated CCR2DTR/+ mice toward an increased heterogeneity. This heterogeneity, commonly only observed with aging, is characterized by an increased number of poly-hormonal cells, loss of β cell identity, and impaired transcription of mitochondrial genes.

Functional heterogeneity of β-like subpopulations revealed by differential gene expression profiling and pseudotime analysis

Further differential gene expression profiling indicated that β-like cells consist of four sub-clusters (β-like 1–4) distinguished by the expression of unique marker genes (Figure S2; Table S1).

Sub-cluster β-like 1 was characterized by high levels of expression of genes involved in epithelial branching morphogenesis, cell growth, and survival (e.g., the homeodomain transcription factor Barx2, Mslnl, Wnt5b, and Nrtn)20,21 as well as genes encoding for negative regulators of insulin secretions (e.g., Kcnab3, Fxyd3, and Sytl3)22,23,24 (Table S1). As compared to conventional β cells, this β-like subpopulation expressed similar levels of hormone transcripts, hormone-processing gene transcripts, and β cell-specific transcription factors (Figure S2B). However, it expressed lower levels of Ucn3 and MafA and higher levels of MafB and Neurog3, suggesting an immature phenotype25,26 (Figure S2B). Consistent with this hypothesis, the β-like 1 population was only found in young 4-week-old islet samples (Figure 2). On the other end, high levels of expression of long non-coding RNAs and microRNAs were hallmarks of β-like populations 2 and 3 (Table S1), primarily enriched in aged mice and young DT-treated CCR2DTR/+ mice. Among the non-coding RNAs expressed in these populations were lncRNAs (e.g., Malat1, Meg3, Xist, and Mirg) previously associated with X chromosome inactivation ahead of cell cycle entry and stress responses.27,28 These two β-like populations were also enriched for direct or indirect negative modulators of insulin exocytosis, acting on mitochondrial (e.g., Olfm4)29 and ciliary functions (e.g., P2ry14 and Hook2).30,31,32 Lastly, as compared to β cells, the β-like 4 sub-cluster had the lowest levels of hormone and hormone processing transcripts (Figure S2B) and was highly enriched for disallowed gene transcripts (e.g., Hbb and Igkc) as well as acinar proteases (e.g., Try5, Cela3b, Ctrb1, and Cela2a) (Table S1), suggesting de-repression of non-β lineage genes.11,33,34

To capture transitions in functional states between β and β-like populations, we further analyzed these populations by pseudotime inference and trajectory analysis using Monocle 2. We then performed canonical pathway enrichment analysis of differentially expressed genes between the identified functional states. Pseudotime analysis mapped islets’ endocrine cells to 9 functional states (Figure 5A), of which conventional β cells occupied state 5 and 4 in young and older mice, respectively (Figure 5B). Relative to β cells in state 5, the Monocle 2 trajectory identified three branching points or nodes, each leading to a state populated by one or more β-like populations, i.e., β-like 1 in state 3, β-like 2 and 3 in state 6, and β-like 4 in state 7.Figure 5 Trajectory analysis identifies distinct functional states enriched for select β-like populations and canonical pathways

(A and B) Single-cell trajectories inferred by Monocle 2 on all (A) and individual islet samples (B). Conventional β and β-like cells are color-coded as indicated in (A). Non-β cells are colored gray. This analysis subdivides islet endocrine cells into 9 functional states, of which conventional β cells populate states 4 and 5, and β-like cells populate states 3, 6, and 7.

(C–E) Select signaling pathways differentially expressed in state 3 vs. state 5 (C), state 6 vs. state 5 (D), and state 7 vs. state 5 (E). Pathway enrichment is expressed as –log(p-value).

(F–H) Heatmaps of significantly differentially expressed genes (FDR<0.01) related to cell cycle control and DNA repair (F), mitochondrial function (G), ER stress responses (H), NAD/sirtuin signaling (I), inflammation (J), and epithelial-mesenchymal transition (K), in cells populating the indicated states, as compared to cells in state 5. Scaled values for the heatmaps represent log2 fold changes.

As compared to cells in state 5, the processes most significantly enriched in cells in state 3 (comprising β-like 1 cells) were related to the regulation of cell cycle, chromatin replication, and DNA repair (Figures 5C and 5F) (e.g., Pcna, Mki67, Mcm3, Mcm5, Mcm7, Ccna2, Ccnb2, Ccne2, Cdk1, Brc2, Chek1, and Top2A),35,36 indicating that cells in this state are actively replicating.

On the other end, top signaling pathways enriched in state 6 vs. state 5 were related to mitochondrial dysfunction, ER stress response, oxidative phosphorylation, and sirtuin signaling (Figure 5D). Specifically, cells in state 6, comprising β-like 2 and 3 populations, displayed a profound down-regulation of genes encoding for several components of the mitochondrial electron transport chain (e.g., Nudufa1, Ndufa11, Ndufb2, Gpx4, and Cox5a) and exhibited a maladaptive ER stress signature characterized by high levels of the ER stress sensors and cell death effectors Atf6, Dddit3, Casp7, and Casp9,37 and low levels of protective anti-oxidant NRF2-target genes (e.g., Hmox1, Fth1, Ftl, and Txn1)38 (Figures 5G and 5H). Cells in state 6 also up-regulated expression of genes involved in NAD signaling and biogenesis (e.g., Sirts, Parps, and Nampt2)39 (Figure 5I), as well as genes of the inflammatory nuclear factor kB (NF-kB) (e.g., RelB/A, c-Rel, Ikbkg, and Nfkb1) and JAK/STAT (e.g., Cish, Socs2, Socs3, and Stat1-6) signaling pathways40,41 (Figure 5J).

Lastly, cells in state 7, which comprised the β-like 4 population, were enriched for pathways previously linked to epithelial-mesenchymal transition (EMT) processes, namely thrombin signaling, integrin signaling, IL8 signaling, and hepatic fibrosis42,43 (Figure 5E). Indeed, a comparison of differentially expressed genes highlighted the up-regulation of several known markers of EMT (e.g., Tgfbr2, Dcn, Nrp1, Sox18, and Vim)44 and down-regulation of Ovol2, a transcriptional repressor of this process45 (Figure 5K). Interestingly, while cells in state 6 lacked an overt EMT signature, they exhibited down-regulation of markers of epithelial identity (e.g., Cdh1 and EpCAM), which is a hallmark of the initial stages of EMT, suggesting cells in state 6 and 7 may represent two sequential phases of the same de-differentiation process.

Overall, these data identify a continuum of dynamic functional states by which newly developed replicating β cells transition into mature β cells, some of which may then progress to energetically impaired and/or frankly dedifferentiated β-like cell types with age, a phenotype that is accelerated by disruption of perinatal macrophages.

Evidence for oxidative stress responses and increased reactive oxygen species production in β cells from DT-treated CCR2DTR/+ mice

To investigate phenotypic and functional changes in conventional β cells over time, we performed pathway analysis on genes differentially expressed in β cells from DT-treated CCR2DTR/+ mice vs. WT littermates at 1 and 6 months of age.

At 1 month of age, the most significantly differentially expressed pathways included protein ubiquitination, EIF2 signaling, unfolded protein response, and oxidative phosphorylation (Figure 6A, ≥1.5-fold changes, p < 0.05). Under the oxidative phosphorylation pathway, β cells from DT-treated CCR2DTR/+mice showed up-regulation of protective genes critical for adaptation to oxidative stress (e.g., Rgs2, Nnat, Txnip, Sod2, and Prdx1)46,47,48,49 and down-regulation of metallothioneins (Mt1 and Mt2) (Figure 6B), a β cell compensatory response previously reported in pre-diabetic animal models.50 Interestingly, similarly to β-like 2 and 3 populations, mitochondrial dysfunction was a prominent pathway enriched in β cells of DT-treated CCR2DTR/+ mice compared to WT controls. This gene signature was characterized by the down-regulation of several components of the mitochondrial electron transport chain, most dramatically affecting Complex I (e.g., Ndufb2, Nndufa13, Ndufa5, Nndufa3, and mt-Nd4l) and up-regulation of the mitochondrial oxidative stress sensor Park7 and transporter Vdac2. Other up-regulated genes included targets of sirtuin signaling involved in stress-mediated DNA repair and autophagy (e.g., Gadd45 and Atg3)51,52 and modulators of inflammatory responses (e.g., Cebpd, Cish, Trib, Car15, Fkbp5, Socs3, Nfkbia, and Ikbip)40,41,53 (Figure 6B). Further screening of differentially expressed genes that could directly or indirectly impact endocrine functions demonstrated up-regulation of circadian modulators (i.e., Per1 and Cry2) (ref.54), as well as repressors (i.e., Gem, Pde10a, and Klf11)55 and stimulators (P2ry1)56 of insulin secretion.Figure 6 Top signaling pathways differentially expressed in β cells of DT-treated CCR2DTR/+ mice vs. DT-treated WT controls over time

(A) Analysis of select signaling pathways differentially expressed in conventional β cells from DT-treated young CCR2DTR/+ mice as compared to aged-matched WT controls.

(B) Heatmaps of differentially expressed genes (FDR<0.01) within the indicated pathways detected in 1 month old DT-treated CCR2DTR/+ mice as compared to aged-matched WT controls.

(C) Ingenuity pathway analysis comparing signaling pathways enriched in β cells from 6 months old DT-treated CCR2DTR/+ mice relative to their young counterpart. Many of the same pathways enriched in the comparison shown in A remain significantly enriched.

(D) Heatmaps of differentially expressed genes within select pathways, illustrating changes in expression in β cells from DT-treated 6 months vs. 1 month old mice of either WT or CCR2DTR/+ genotypes.

(E) Pathway analysis comparing signaling pathways enriched in β cells from 6 months old DT-treated CCR2DTR/+ mice to those of aged-matched WT controls.

(F) Heatmaps of differentially expressed genes within the indicated pathways detected in 6 months old DT-treated CCR2DTR/+ mice vs. those of aged-matched WT controls. Scaled values in heatmaps represent log2 fold changes.

Responses to oxidative stress and sirtuin/NAD signaling were gene signatures that remained significantly differentially expressed in the comparison between β cells from 6- and 1-month-old DT-treated CCR2DTR/+ mice (Figure 6C), indicating that engagement of these pathways persisted in time. The same pathways were also significantly differentially expressed in the comparison between β cells from 6- and 1-month-old WT β cells, indicating they likely reflected responses to age-driven metabolic pressure in both strains. Although qualitatively similar, side-by-side comparisons of differentially expressed genes showed a sharper decline in the expression of protective anti-oxidative genes (e.g., Txn1, Gpx2, and Gpx3) and chaperones critical for effective unfolded protein responses (e.g., Hsp90b1, Hspa5, Calr, and Derl3) in β cells of aged DT-treated CCR2DTR/+ mice (Figure 6D). Furthermore, while expression of sirtuin-targeted genes positively regulating adaptive cell replication (e.g., Myc and E2f1) as well as mitochondrial metabolism and bioenergetics (e.g., Acadl, Acadm, Etfa, Nqo1, and Slc25a4)57,58,59 increased with age in WT β cells, the same genes in aged DT-treated CCR2DTR/+ β cells showed an opposite trend (Figure 6D).

At 6 months of age, among the top differentially expressed pathways identified by Ingenuity Pathway analysis was the pro-survival neuregulin pathway, which appeared to be down-regulated in β cells of DT-treated CCR2DTR/+ mice as compared to controls (Figure 6E). The top differentially expressed genes at this time were suggestive of chromatin remodeling and transcriptional reprogramming in aged DT-treated CCR2DTR/+ β cells. This signature included up-regulation of exocrine-like proteases and lipases (e.g., Ctrb1, PRSS2, Cela2a, Cela3b, and Pnlip), and down-regulation of DNA-methyltransferases previously implicated in the repression of disallowed genes (e.g., Dnmt3b)60 as well as of transcriptional regulators (Smarca1 and Ovol2) and core components of the nucleosomes (e.g., Hist2h2aa1, Histh2ap, and Histh4h)61 (Figure 6F). In addition, consistent with the impaired glucose homeostasis and defects in insulin secretion detected in vivo (Figures 1D–1F), down-regulation of several effectors of insulin exocytosis was observed (Figure 6F).

Next, we set to validate the prominent transcriptional signature related to oxidative stress responses with functional and biochemical assays. Flow cytometric analysis of islet cells freshly isolated from 1- to 3-month-old DT-treated CCR2DTR/+ and WT mice stained with the mitochondrial reactive oxygen species (ROS) indicator MitoSOX Red confirmed a higher frequency of MitoSOX Red+EpCAM+ islet cells in DT-treated CCR2DTR/+ mice, which further increased upon culture in low and high glucose (% MitoSOX-Red+ cells in fresh islets from DT-treated WT vs. DT-treated CCR2DTR/+mice = 6.6 ± 1.3 vs. 14.3 ± 2.5; in KRB/2.8 mM glucose = 8.3 ± 2.5 vs. 19.6 ± 5; in KRB/16 mM glucose = 11.8 ± 2.2 vs. 20 ± 3.5; mean ± SD n = 3 experiments, all p < 0.03 by unpaired t test, Figures 7A–7C). Furthermore, β cells expressing nuclear puncta of phosphorylated H2AX (γ-H2AX), a marker of double-strand DNA breaks,62,63 were significantly more numerous in the islets of DT-treated CCR2DTR/+ mice as compared to all controls (Figures S3A and S3B). Nevertheless, number of apoptotic cells measured in the islet and spleens by TUNEL was not significantly different among experimental groups (Figures S3F and S3G). Lastly, among the top markers of oxidative stress detected by scRNA-seq, we were able to validate the up-regulation of the stress sensor and chromatin remodeler GADD45b in the islets of DT-treated CCR2DTR/+ by both immunostaining and western blotting analysis (Figures S3C and S3D). Increased levels of phosphorylated JNK in nuclear extracts confirmed the engagement of this stress-related pathway downstream of GADD45 signaling64 (Figure S3D).Figure 7 Increased frequency of mitochondrial ROS-expressing islet cells in DT-treated CCR2DTR/+ mice

(A and B) Flow cytometric analysis of islet cells isolated from 4 weeks-old untreated (A) or DT-treated (B) WT and CCR2DTR/+ female mice, stained with both SYTOX-Green, for detection of dying cells and viable cell gating (upper panels), and the mitochondrial ROS indicator MitoSOX Red (lower panels). Contour plots in lower panels show percentages of MitoSOX Red+ cells in SYTOXneg live gates from freshly isolated islet cells (time 0) or islets cells cultured for 1 h in either KRB 2.8 mM glucose or KRB 16 mM glucose.

(C) Three-color flow cytometric analysis of islet cells freshly isolated from 4 weeks-old DT-treated WT and CCR2DTR/+ female mice, stained for SYTOX-Green, the epithelial marker EpCAM, and MitoSOX Red. Quadrants in contour plots on the left show the cell percentages in EpCAMneg and EpCAMpos SYTOXneg live gates. Contour plots on the right show the percentage of MitoSOX Red+ cells in EpCAMneg and EpCAMpos live gates. MitoSOX Red+ cells are mostly EpCAM+ indicating their epithelial identity. Data are representative of 3 experiments.

Together, these results provide strong evidence for increased ROS production starting early in β cells from DT-treated CCR2DTR/+ mice and rapidly progressing toward failure of adaptive responses to oxidative stress with age and abnormally sustained DNA damage responses. This process is paralleled by gene signatures of mitochondrial impairment, inflammation, and transcriptional reprogramming like the ones identified in β-like cell populations, reiterating the existence of a continuum process of cell demise in β cell types.

Mitochondrial impairment in β cells of DT-treated CCR2DTR/+ mice: Evidence for ultrastructural and biochemical defects triggered by macrophage loss in perinatal life

The transcriptome data outlined above revealed significantly decreased expression of components of mitochondrial complex I and IV in β and β-like cells of DT-treated CCR2DTR/+ mice. Primarily, this signature affected accessory subunits of the membrane arm of complex I, previously involved in complex assembly and stabilization65 and inner membrane organization.66 To investigate whether these defects were associated with impaired mitochondrial ultrastructure, pancreatic islets isolated from 6-month-old mice were analyzed by transmission electron microscopy. These studies demonstrated a striking increase of morphologically abnormal mitochondria in β cells from DT-treated CCR2DTR/+ mice compared to DT-treated WT and untreated controls (Figure 8). In those samples, several mitochondria had disrupted cristae, exhibited precipitated matrix proteins (Figure 8I), and remnants were often engulfed within giant lysosomes to form multivesicular bodies (Figure 8J, arrowheads), suggesting enhanced mitophagy. Enlarged endoplasmic reticulum, a morphological feature of ER stress, was also noted in β cells of DT-treated CCR2DTR/+ mice (Figure 8K, asterisks).Figure 8 Altered mitochondrial ultrastructure detected in the β cells of DT-treated CCR2DTR/+ mice

(A–C, E–G, and I–K) Transmission electron microscopy images of islet’s β cells isolated from DT-treated WT (A–C), untreated CCR2DTR/+ (E–G), and DT-treated CCR2DTR/+ (I–K) female mice at 6 months of age. (A, E, and I) Normal mitochondria morphologies are apparent in A and E, whereas mitochondria exhibiting loss of cristae and precipitated matrix are evident in β cells of DT-treated CCR2DTR/+ mice (I, arrowheads). (B, F, and J) Representative images of autophagy and mitophagy (arrowheads). Remnants of mitochondria and other organelles engulfed in auto-phagosomes appear more numerous in β cells of DT-treated CCR2DTR/+ mice (J, arrowheads).

(C, G, and K) Morphologically normal endoplasmic reticulum (ER) cisternae are easily identifiable in C and G, whereas enlarged ER cisternae (asterisk) suggestive of ER stress are evident in β cells of DT-treated CCR2DTR/+ mice in K.

(D, H, and L) Morphometric analysis of mitochondrial ultrastructural defects detected in DT-treated WT (D), untreated CCR2DTR/+ (H), and DT-treated CCR2DTR/+ mice (L). The total number of mitochondria scored in β cells of each sample is shown at the bottom of each pie chart. Scale bar in J, 600nm. Scale bar in K, 300 nm.

Mitochondrial complex I is the primary site regulating NAD oxidation through transferring electrons from NADH into the respiratory chain.67 To investigate whether the decreased transcription of this complex’s components identified by scRNA-seq was associated with altered cellular NAD content, we measured NAD and NADH in islets’ lysates. This analysis revealed decreased NAD/NADH ratios in the islets of DT-treated CCR2DTR/+ mice compared to DT-treated WT controls at 3–6 months of age (Figure S4A). In addition, consistent with the scRNA-seq data, western blotting analysis confirmed a decreased expression of select mitochondrial complex I proteins (e.g., Ndufa3) in islets extracts from DT-treated CCR2DTR/+ mice relative to controls, as well as increased expression of Parkin, required for targeting damaged mitochondria for mitophagy68 (Figures S4B and S4C).

Experimental evidence supports an association between mitochondrial defects and inflammation.69,70 Hence, we considered the possibility that such mitochondrial phenotype could result from a rebound infiltration of myeloid cells secondary to the depletion of CCR2+ macrophages in perinatal life. Indeed, we previously reported that, while during DT-mediated depletion of CCR2+ macrophages in vivo, there are no detectable changes in the number of other F480+ macrophage populations, DT withdrawal is followed by a wave of CD11b+ myeloid cells repopulating the pancreas.16 In further follow-up studies, by 4 weeks of age, we measured frequencies of whole CD11b+ myeloid cells, which trended to be higher in the pancreas of DT-treated CCR2DTR/+ female but not male mice, as compared to WT controls (Figure S5A). Nevertheless, by 4 weeks of age, the numbers of F480+CCR2+ macrophages in the whole pancreas were comparable across all groups (Figure S5A). Analysis of tSNE plots of myeloid cells associated with the islets showed CCR2+F480+ myeloid cells slightly enriched in the islet samples of CCR2DTR/+ mice at 1 month but not 6 months of age and expressing higher levels of chemokine receptors (Figures S5B and S5C), consistent with a transiently enhanced myeloid repopulation of the pancreas in CCR2DTR/+ mice.

To evaluate mitochondrial health in islet cells under depletion of CCR2+ macrophages, yet independently of potential effects from in-bound leukocytes re-populating the tissue from the periphery, we isolated pancreatic islets and CD11b+ myeloid cell fractions from P5 pancreas of CCR2DTR/+ and WT pups, co-cultured them for 10 days in the presence of DT and processed them for transmission electron microscopy. These studies revealed an increased frequency of ultra-structural mitochondrial defects in the islets of CCR2DTR/+ mice, similar to those detected in vivo in older mice (Figure S6).

These results show that the mitochondrial dysfunctional signature of β cells of DT-treated CCR2DTR/+ mice is associated with the depletion of intracellular NAD pools and compromised mitochondria structure. Our data further indicates that the depletion of neonatal CCR2+ macrophages, rather than leukocyte repopulation or systemic signals secondary to the depletion, is a primary trigger of the observed mitochondrial defects.

Discussion

The importance of perinatal β cell expansion in metabolic adaptation throughout life has long been recognized.71 To date, mechanisms invoked to explain how such early events may condition β cells’ performance into adulthood have primarily focused on nutrient deficiencies or excess and their possible effects on β cell replication,9,72 epigenetic regulation of metabolically critical genes,73 or mitochondrial function.74 Our results point to perinatal CCR2+ macrophages as a tissue component capable of influencing β cell population dynamics in youth independent of dietary stress and provide evidence for a vulnerability of mitochondrial bioenergetics in young β cells linked to perinatal disruption of those innate immune cells.

A striking finding in our timed scRNA-seq studies is the increased frequency and accelerated appearance, in young DT-treated CCR2DTR/+ mice, of poly-hormonal β-like cell populations that have lost markers of functional maturity. Relative to conventional β cells, these β-like populations are characterized by conflicted insulin/glucagon gene transcription, decreased expression of transcription factors critical to the maintenance of β cell identity, as well as lower levels of expression of genes encoding for hormone processing enzymes and SNARE protein complexes involved in insulin secretion. The sharing of glucagon transcription with few conventional β cells and the lack of α-cell lineage transcription factors (e.g., Arx and Irx1/2) (Figures 3B–3E) suggest a continuum of β cell states and argue against an α-cell identity of these cells. We found that accumulation of such β-like cell populations also occurs in normal mice, but at a much slower pace, becoming more abundant only in advanced age. Consistently with these results, β- cell populations with similar phenotypes have been reported in pancreatic islets from normal human subjects, with an increased number detected in type 2 diabetes (T2D) and aging individuals.75,76,77

Except for the β-like population 1, many features indicate decreased endocrine functions of β-like populations. First, their increased frequency is associated with accelerated impairment of glucose tolerance and defective glucose-regulated insulin secretion with age (Figures 1 and S1). In addition, they share several hallmarks (e.g., dysfunctional mitochondrial phenotypes, increased expression of select lncRNAs and disallowed genes as well as EMT-like features) (Figures 5G and 5K; Table S1) with failing β cells reported in T2D mouse models78,79 Notwithstanding the drifting in islet function associated with the increased frequency of such β-like cell populations, it is remarkable that diabetes ensues relatively late in adulthood in DT-treated CCR2DTR/+ mice (Figure S1B). De-differentiated/immature phenotypes, such as the ones detected here, may confer some survival advantages to stressed β cells. For example, in injury settings, there is evidence that EMT is a mechanism activated in epithelial cells to circumvent cell death, avoid elimination by inflammatory cells, and achieve reprogramming into other cell types for tissue repair.45,80 Thus, de-differentiation through EMT could be part of a stepwise β cell regenerative program going awry with aging and premature loss of perinatal CCR2+ macrophages. Based on these observations, it will be interesting to evaluate whether susceptibility to T2D diabetes in animal models can be traced back to early defects in CCR2+ macrophages populating the pancreas in perinatal life.

Mitochondria biogenesis and health are critical to β cell endocrine functions.81 Our analysis identifies heterogeneity of β cell populations with regard to mitochondrial DNA (mtDNA) reads and mitochondrial functions. Specifically, we found an increased frequency of subpopulations harboring low mtDNA reads in β and β-like, but not α-cells of both young DT-treated CCR2DTR/+ and aged mice of either wild type or CCR2DTR/+ genotypes (Figure 4). This latter observation is consistent with the reported decline in mitochondrial DNA copy number in aging and age-related degenerative diseases82,83 and the detection of β cell subtypes diverging by mtDNA content in mouse and human islets.84 Regarding possible mechanisms underlying this phenotype in our model, it is noteworthy that the dysfunctional mitochondrial gene signature identified in DT-treated CCR2DTR/+ mice includes defective expression of mitochondrial transcription factors required for basal replication of mitochondrial DNA (e.g., Tfb1M, Figure 6B). Defects of these transcription factors have been shown to directly influence mitochondrial biogenesis in β cells, ultimately negatively affecting insulin secretion and increasing the risk of diabetes progression.85,86

We further detected a prominent dysfunctional mitochondrial gene signature in both β and β-like cells of DT-treated CCR2DTR/+ mice (Figures 5 and 6). This signature is characterized by significant down-regulation of several components of complex I and complex IV of the electron transport chain, coupled with cellular NAD depletion and accumulation of reactive oxidative species. (Figures S4A and 7). Initially, in young DT-treated CCR2DTR/+ mice, this signature is consistent with adaptive compensatory responses to oxidative stress. These include up-regulation of mitochondrial stress sensors and ion transporters (Park7 and Vdac2), regulators of protein translation and processing (Rgs2 and Nnat), as well as protective genes directly involved in scavenging of oxidative species (Sod2, Gpx3, Gpx4, and Prdx1-6) (Figure 6B). Further evidence of early defense responses to stress is provided by the upregulation of genes controlled by sirtuin signaling (Figure 6B), including mediators of autophagy (e.g., Atg3), a process involved in the clearance of protein aggregates and dysfunctional mitochondria.52 Intriguingly, these adaptive phenotypes appear to turn maladaptive in both β cells of aged DT-treated CCR2DTR/+ mice and β-like cells progressively accumulating in these mice. In β cells, the maladaptive trend is marked by the downregulation of the neuregulin pathway, a protective pathway previously implicated in regulating mitochondrial turnover and respiration87,88 and endocrine differentiation.89 In addition, the analysis of β-like populations in state 6 reveals up-regulation of death-related genes (Casp7, Casp9, and Ddit3) and down-regulation of antioxidant genes and NRF2 targets (Txn1, Fth1, and Ftl) in the presence of an ER stress signature (Atf6, Eif2ak3, Crebbp, Ep300, Fos, and Gsk3b) (Figure 5H). Upregulation of some of these genes has been previously reported in transcriptomic studies of aging human islets.90 Notably, this signature in state 6 is associated with substantial up-regulation of sirtuins and PARP genes (Figure 5I), all NAD-consuming enzymes that could further lower intracellular NAD pools already depleted by the mitochondrial dysfunction. Hence, it is possible that β-like cells in this state are engaged in a vicious cycle of defective NAD production and increased NAD consumption. Reiteration of this vicious cycle may explain the transition between β-like cells in State 6 and those in state 7 inferred by Monocle 2 since there is evidence that extreme NAD depletion may be a driver of de-differentiation to EMT-like phenotypes.91 Lastly, our studies demonstrate significant ultra-structural impairment of mitochondria in β cells of DT-treated CCR2DTR/+ mice (Figures 8 and S6). Importantly, we show that mitochondria damage is established across an unexpectedly short timescale in young mice, independently of dietary stresses and inbound inflammatory cells. These results point to the loss of cues dependent on perinatal CCR2+ macrophages as a trigger of early mitochondrial damage that does not seem to recover and is perpetuated into adulthood.

It is known that, at low levels, mitochondria-derived ROS drive essential cellular functions,92 including β cell proliferation.93 However, at sustained high levels, ROS can be toxic to β cells and drive increased rates of mutational loads with age.77 Increased susceptibility to ROS-inflicted DNA damage may also result from slowing the cell cycle.94 Thus, ROS overproduction, especially if exceeding protective antioxidant cellular activities (Figures 5G and 5H), and in the context of the slowed down cell growth caused by myeloid cell disruption,16 may explain the sustained DNA damage responses we detected in the islets of DT-treated CCR2DTR/+ mice (Figures S3A and S3B). Notably, genomic instability has been linked to premature senescence95 and immune surveillance.96 Accordingly, in β and β-like cells in state 6 from 4-week-old DT-treated CCR2DTR/+ mice, we found evidence of an inflammation-related gene signature dominated by NF-kB signaling mediators (Figures 5J and 6B). These results indicate that oxidative stress and DNA damage are associated with the need to control inflammation early on in β cells of DT-treated CCR2DTR/+ mice. Damaged mitochondria may also release signals capable of exacerbating inflammatory responses.97 As unresolved islet inflammation plays a role in the progression toward glucose intolerance and diabetes,98 likely pathologic ROS accumulation, impaired mitochondria, and sustained DNA damage are key risk factors for diabetes development in adult DT-treated CCR2DTR/+ mice.

Collectively, our findings provide evidence that mitochondrial bioenergetics in neonatal β cells may be irreversibly disabled by disruption of perinatal CCR2+ macrophages. Premature loss of these fetal macrophages followed by spontaneous myeloid cell repopulation postnatally is still compatible with the adaptive recovery of β cell mass in youth. Yet, it unleashes the emergence of energetically impaired and de-differentiated β-like subpopulations at the expense of functionally mature β cells, predisposing to glucose intolerance later in life. As pancreatic CCR2+ macrophages decline with age,16 similar shifts in β cell repertoires are observed, suggesting the possibility that they may result from adaptive β cell replicative attempts insufficiently supported by post-natal myeloid cells. While further work is warranted to dissect the myeloid-dependent functions required to support mitochondrial health, our studies offer new insights that β cells’ mitochondrial dysfunctions capable of silently progressing toward glucose intolerance may arise as early as in perinatal life irrespective of dietary changes and be triggered by disturbances of innate immune tissue components. Interestingly, recent studies on cardiomyocytes, another highly metabolic cell type, point to a similar dependence of mitochondrial function on tissue macrophages.99 Therefore, maintenance of early macrophage populations may grant long-term sustenance of high metabolic performance in β cells.

Limitations of the study

Further investigation will be required to identify the mechanisms underlying the sex-specific effects of CCR2+ macrophage depletion on islet dysfunction. In addition, our analysis is limited to the C57BL/6J genetic background, which per se is prone to developing reduced glucose tolerance with aging. Since, in this genetic background, male mice develop glucose intolerance faster than females due to peripheral insulin resistance, the apparent female-biased phenotype observed here may reflect a metabolic disturbance masked in males, but not in females, by the already impaired glucose tolerance of wild type controls. Alternatively, the lower glucose-coupled insulin secretion and adaptive β cell replication associated with aging previously described in female C57/BL6J mice100 may contribute to the sex-biased phenotype observed in our model. The increased frequency of beta-like populations, shown here to express lower levels of Prlr and Glp1r (Figure S2), two receptors required for adaptive replication and potentiation of insulin secretion, may directly bear upon these responses. Lastly, defective mitochondrial gene signatures of β cells were recently reported in human islets from female but not male donors affected by T2DM, suggesting a high susceptibility of female β cells to mitochondrial failure.101

Previous reports have provided evidence that, compared to β cells, α-cells may be more resilient to oxidative stress, disruption of autophagy, and apoptosis.102,103,104 While our analysis of mitochondrial reads in α-cell populations shows phenotypes unaffected by either macrophage depletion or aging, further studies will need to be undertaken to define other possible dysfunctions of α-cells in our model, if any.

Although our scRNA-seq approach captured significant alterations in the β cell compartment resulting from the disruption of CCR2+ cells, the low frequency of myeloid cells populating the islet tissue limited a comprehensive analysis of myeloid signaling pathways that could explain the noted phenotypes. Enrichment of myeloid cell populations by cell sorting and their analysis by bulk RNA-seq at multiple time points and from various organs after DT withdrawal will be informative to draw an accurate representation of myeloid cell subsets repopulating the pancreas and define dynamic tissue-specific changes of their functional states over time.

Many β cell features identified in this study (i.e., poly-hormonal states, up-regulation of select lncRNAs and disallowed genes, EMT, and ER stress gene signatures) recapitulate phenotypes previously described in failing β cells from T2DM subjects and diabetic rodent models,75,76,77,78,79 pointing to a functional link between disturbance of early myeloid compartments and progression to diabetes. Tissue and transcriptomic datasets of perinatal islet milieus in T2DM models will need to be collected to draw further evidence supporting such interplay.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER	
Antibodies	
	
Rat monoclonal anti-mouse CD16/32 (clone 93)	Biolegend	Cat# 101301, RRID: AB_312800	
Biotin-Rat monoclonal anti-mouse CD11b-Biotin (clone M1/70)	Biolegend	Cat#101203, RRID: AB_312786	
Alexa 488-Rat monoclonal anti-mouse F40/80 (clone BM8)	Biolegend	Cat#123119, RRID: AB_893491	
APC-Rat monoclonal anti-mouse CD326 (EpCAM) (clone G8.8)	Biolegend	Cat#118213, RRID: AB_1134105	
Guinea pig polyclonal anti-Insulin (A0564)	Dako	A0564, N/A	
Mouse monoclonal anti-Glucagon (clone K79bB10)	Sigma	Cat#G2654, RRID: AB_259852	
Rabbit Monoclonal anti-Phospho-Histone H2A.X (Ser139) (Clone 20E3)	Cell Signaling Technology	Cat#9718, RRID: AB_2118009	
Mouse Monoclonal anti-mouse PCNA (clone PC10)	Santa Cruz Biotechnology	Cat#sc-56, RRID: AB_628110	
Rabbit Polyclonal anti-mouse GADD45B	Abcam	Cat#ab230646, N/A	
Rabbit monoclonal anti-Phospho SAPK/JNK (Thr183/Tyr185) (clone 81E11)	Cell Signaling Technology	Cat#4668, RRID: AB_823588	
Rabbit polyclonal anti-SAPK/JNK	Cell Signaling Technology	Cat#9252, RRID: AB_2250373	
Rat monoclonal anti-mouse Hsp90 (clone 16F1)	Abcam	Cat#13494, RRID: AB_300398	
Rabbit polyclonal anti-mouse PAX6	Millipore	Cat# AB2237, RRID: AB_1587367	
Mouse monoclonal anti-Parkin (clone PRK8)	Santa Cruz Biotechnology	Cat#sc-32282, RRID: AB_628104	
Mouse monoclonal anti-NDUFA3 (clone B-12)	Santa Cruz Biotechnology	Cat#365351, RRID: AB_10846952	
Mouse Monoclonal anti-NDUFB8 (clone 20E9DH10C12)	Invitrogen	Cat#459210, N/A	
	
Chemicals, peptides, and recombinant proteins	
	
Diphtheria Toxin from Corynebacterium Diphtheria (unnicked)	List Biological Laboratories Inc	Cat# 150	
Liberase TL	Roche-Millipore	Cat#05401020001	
Dnase I	Sigma	Cat#4536282001	
Ficoll-Hystopaque 1077	Sigma	Cat#H8889	
MitoSOX Red	Invitrogen	Cat#M36008	
SYTOX Green	Invitrogen	Cat#S7020	
Collagenase A	Roche-Fisher	Cat#50-100-3278	
NE-PER Nuclear and Cytoplasmic Extraction Reagents	Cell Signaling Technology	Cat# 78833	
Complete Proteases Inhibitors Cocktail	Millipore	Cat# 11697498001	
Durcupan ACM, Araldite embedding resin	Electron Microscopy Sciences	Cat# 14040	
	
Critical commercial assays	
	
Click-IT EdU Cell proliferation assay	ThemoFisher	Cat# C10637	
Ultrasensitive mouse insulin ELISA kit	Alpco	Cat# 80-INSHUU-E01.1	
Mouse Insulin ELISA kit	Mercodia	Cat# 10-1247-01	
LS Columns	Miltenyi Biotec	Cat# 130-042-401	
Anti-PE Microbeads	Miltenyi Biotec	Cat# 130-048-801	
RNAscope Multiplex Fluorescent Reagent Kit v2	ACD	Cat# 323100	
Chromium Next GEM Single Cell 3' GEM,
Library & Gel Bead Kit v3.1	10X Genomics	Cat# 1000128	
Clarity ECL Western Blotting Reagent	Biorad	Cat# 1705060	
NAD/NADH Colorimetric Assay Kit	Abcam	Cat# ab65348	
	
Deposited data	
	
Raw scRNAseq data	This paper	GEO: GSE232461	
	
Experimental models: Organisms/strains	
	
Mouse: CCR2-DTR Transgenic	This paper	Hohl et al.17	
	
Oligonucleotides	
	
RNAscope probe Mm-Ins2	ACD	Cat# 310751	
RNAscope probe Mm-Ins1-C2	ACD	Cat #414661-C2	
RNAscope probe Mm-Gcg-C3	ACD	Cat# 400601-C3	
RNAscope™ 3-plex Positive Control Probe-Mm	ACD	Cat# 320381	
RNAscope™ 3-plex Negative Control Probe	ACD	Cat# 320871	
	
Software and algorithms	
	
Partek Flow	Partek	https://www.partek.com/partek-flow/	
Imaris v9.9	Oxford Instruments	http://www.bitplane.com/imaris/imaris
RRID:SCR_007370	
QuPath software (v0.4.4)	QuPath	https://doi.org/10.1038/s41598-017-17204-5	
ImageProPlus (v4.5)	Media-Cybernetics	https://www.mediacy.com/imageproplus	
Prism (V10)	GraphPad	https://www.graphpad.com/scientific-software/prism/	

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to the lead contact Laura Crisa (lcrisa@uw.edu).

Materials availability

This study did not generate new unique reagents.

Data and code availability

• All raw and processed sequencing data meeting Minimum Information about a Next-generation Sequencing Experiment (MINSEQE) guidelines have been deposited at GEO (https://www.ncbi.nlm.nih.gov/geo/, GSE232461). The accession number is listed in the key resources table.

• This paper does not report an original code.

• Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Experimental model and study participant details

Mouse breeding and treatments

Wild type C57BL/6J females were obtained from The Jackson Laboratory (Bar Harbor, ME). Male mice carrying CCR2 promoter-driven Diphteria Toxin Receptor (DTR) were originally obtained from Hohl et al.17 and thereafter bred with C57BL/6J females to generate CCR2DTR/+ heterozygous mice. All mice were bred and housed at the University of Washington pathogen-free facility. Diphtheria toxin (List Biological Laboratories Inc., Campbell, CA) was injected intra-peritoneally at 10 ng/gr of body weight every 48 hours starting at P2 for a total of 4 injections. The DT-treatment is generally well tolerated and does not appear to alter feeding behaviors, as judged by the daily presence of stomach's milk spots in both wild type and CCR2DTR/+ pups. DT-injected mice and untreated control littermates were weaned at 21 days and thereafter maintained under a conventional chow diet. For in vivo EDU labeling, mice were injected twice every 48 hours with EDU (25 ug/gr body weight) prior to harvesting of pancreatic tissue at 4 weeks of age. In select experiments, mice maintained under chow diet up to 12 months of age, were switched to high fat diet for 4 months. Glucose tolerance tests (GTT) were performed on 5 hours fasted animals by intra-peritoneal injection of a glucose solution (1.5 mg/g of body weight) and glycemia measured at 15’, 30’, 60’ 90’ and 120’ post glucose load. Blood glucose levels were monitored by tail prick using a FreeStyle glucose monitoring system (Abbott Diabetes Care Inc., Alameda, CA). Plasma insulin levels were measured using an ultra-sensitive mouse insulin ELISA kit (Alpco, Salem, NH).

Study approval

All procedures using animal subjects were approved by the Institutional Animal Care and Use Committee of the University of Washington.

Method details

Tissue dissection, islet isolation and cell culture

Pancreatic islets were isolated by cannulation of the pancreatic duct and injection of HBSS/0.1 mg/ml Liberase/20 ug/ml DNase I followed by mechanical dissociation and separation on a Ficoll gradient as previously described.16 Briefly, after laparotomy, the pancreas was exposed and distended by intra-ductal infusion of 6 ml ice-cold Hanks’ balanced salt solution (HBSS), pH 7.4, containing 6 mmol/l CaCl2, 0.1mg/ml Liberase TL (Roche) and 20 ug/ml DNase I (Sigma). The pancreas was then dissected out, digested at 37C for 20 minutes in a water bath, and the reaction stopped by addition of ice-cold HBSS containing 0.2% bovine serum albumin (BSA). The digested pancreas was then homogenized by five passages through a 14-gauge (3" length) syringe needle, washed once in HBSS-0.2% BSA, and fragments of undigested pancreatic tissue removed by filtering through a strainer. The filtrate of each pancreas was transferred to a 50 ml Falcon tube and centrifuged for 10 seconds at 450g. The dry pellet was then resuspended in 20 ml Histopaque 1077 (Sigma) and overlaid with 20 ml HBSS-0.2% BSA. Samples were centrifuged at 1,000g at 15 C for 20 minutes. Islets at the interface of the Histopaque 1077/HBSS-BSA were then harvested with a 14-gauge syringe needle and washed twice in HBSS-0.2% BSA. Islets were then hand-picked using a 200ul Gilson pipette under a stereo-microscope (Nikon ZM, 1200).

For isolation of neonatal islets, tissues were finely minced and then digested in HBSS/0.1 mg/ml Liberase /20ug/ml DNase I for 15 minutes at 37C in a shaking incubator. Following collagenase digestion, islets were separated on a Ficoll gradient and further purified by hand-picking, as described above. For isolation of pancreatic myeloid fractions from neonatal pancreas, total pancreatic tissue or the exocrine fractions recovered from Liberase digestion were further microdissected under the microscope to remove pancreatic lymph nodes, and then dissociated by digestion for 1 hour at 37°C in HBSS/0.1% collagenase A/20 μg/ml DNase I (Sigma), followed by a 5’ incubation in non-enzymatic dissociation medium (Sigma). The resulting single cell suspension was surface labeled with a Biotin-conjugated anti-CD11b Ab (Clone M1/70, Biolegend) followed by RPE-conjugated Streptavidin and anti-RPE magnetic beads (Mylteni Biotech). Labeled cells were then purified by Magnetic-Activated Cell Sorting through positive selection on a magnetic LS column (Mylteni Biotech) following the manufacturer’s instructions, as described.105 Islets and myeloid fractions obtained from each pancreas were combined by overnight culture in AggreWells (Stem Cells Technology) in RPMI-10% FCS-5mM glucose; recovered islets/myeloid cell aggregates were then cultured up to 10 days in the same medium in the presence or absence of 50 ng/ml of DT. Culture medium and DT were replaced every 48 hours.

For in vitro glucose stimulation, 20 freshly isolated islets, were first cultured for 2 hours in Krebs-Rings Buffer (KRB) (10 mM HEPES, 1.19 mM MgSO4, 1.19 mM NaCl, 4.74 mM KCl, 1.19 mM KH2PO4, 2.54 mM CaCl2-2H2O, 25 mM NaHCO3, pH 7.4) 2.8 mM glucose, and subsequently incubated for 30 minutes in KRB 2.8 mM glucose followed by 30 minutes incubation in 16 mM glucose and another 30 minute incubation in the presence of 16mM glucose and 30mM KCl. Supernatants resulting from each incubation were collected and stored at -80°C. For insulin content, the 20 islets were lysed by acid/ethanol extraction and frozen at -80°C until analysis. Insulin in the culture supernatants and cell extracts was measured using a mouse insulin ELISA kit (Mercodia, Uppsala, Sweden). Results were normalized to protein content measured by a BCA protein assay (Pierce™, Thermo Scientific).

scRNA-seq and analysis

For scRNA-seq, three hundred islets pooled from 2-3 DT-treated CCR2DTR/+ and WT females, 4 weeks or 6 months old, were freshly isolated by collagenase digestion, Ficoll gradient and hand picking as described above. Library preparation was performed using the 10X Genomics Chromium platform (10X Genomics, Pleasanton, CA) following the manufacturer’s instructions, and sequencing performed at a depth of 30,000 reads/cell using a NextSeq2000 sequencer (Fred Hutch Genomic Core, Seattle WA). QC, raw data processing and statistical analysis were performed using Partek Flow software (Partek Inc., St. Louis, MO). Briefly, a total of 35,079 cells underwent quality control. Cells expressing less that 200 genes or with over 10% mitochondrial or over 15% ribosomal reads were excluded, resulting in a total of 26,491 cells for downstream analysis. After excluding genes with value of “0” in at least 99.5% of cells, counts were normalized using log2[counts per million +1] transformation yielding a total of 14,622 genes. After dimensional reduction using the first 100 principal components, cells were graphically clustered using the Louvain algorithm and biomarkers for each cluster identified (minimum 1.5-fold difference between groups). Classification and merging of clusters into cell-types was performed after data visualization via three-dimensional t-distributed Stochastic Neighbor Embedding (t-SNE) maps and cluster-specific expression of top biomarkers. Since Partek does not have an option for doublet/multiplet identification and removal, we also applied DoubletFinder R package as implemented in Seurat and removed flagged cells. We further assessed the presence of ambient RNA in the raw data using SoupX R package106 via its autoEstCont function which showed minimal potential contamination (rho values between 0.01-0.021 across samples). Differential gene expression between conditions was performed in Partek using ANOVA with P-values adjusted using Benjamin-Hochberg’s false discovery rate (FDR) method and significance defined as FDR <0.01 and absolute (log2[fold change])>0.322 (e.g., ± 1.25-fold change). Trajectory and pseudotime analyses were performed in Partek using Monocle 2’s algorithm. Due to the large number of differentially expressed genes between the states identified from the trajectory analysis, significance was defined more strictly using FDR<0.01 and absolute (log2[fold change])>0.585 (e.g., ± 1.5-fold change). Canonical pathway enrichment analysis was performed on differentially expressed genes using Ingenuity Pathway Analysis (IPA, Qiagen, Redwood City, CA).

RNA in situ hybridization

RNA in situ hybridization was performed using the RNAscope technology (ACD, Newark, CA).107 In brief, pancreatic islets isolated by collagenase digestion, Ficoll gradient and hand-picking from pools of at least 2 pancreas per experimental group, were let to recover overnight by culturing in RPMI-10% FCS and fixed in 4% Neutral Buffered Formalin overnight at 4°C. Cell pellets were embedded first in Hystogel (Thermo Scientific) and then in paraffin and sectioned. In situ hybridization was performed on at least 5 tissue sections per group using the RNAscope® Multiplex Fluorescent Reagent Kit v2 and the probes Mm-Ins2 (ACD, cat# 310751), Mm-Ins1-C2 (ACD, cat #414661-C2) and Mm-Gcg-C3 (ACD, cat# 400601-C3) as per manufacturer’s instructions for fluorescent assays. Nuclei were stained by DAPI. Negative and positive control probes, targeting bacterial DapB gene and POLR2A respectively, were used in parallel on additional sections. Slides were imaged at a Nikon Eclipse Ti Microscope equipped with a Yokogawa W1 Spinning Disk confocal attachment and an iXON Life 888 camera, using a Nikon Plan Apo 60X 1.2NA water immersion lens and laser lines at 405, 488, 561 and 640 nm. Z-stacked images were deconvoluted using the Imaris Clear-View-GPU Deconvolution software (v9.9) and processed for morphometric analysis using the QuPath software (v0.4.4). Statistical analysis of the morphometric data was performed using one-way Anova followed by Bonferroni post-hoc test.

Flow cytometry and measurements of mitochondrial superoxide by MitoSOX Red labeling

For flow cytometric analysis of myeloid cells, pancreatic single-cell suspensions were blocked with mouse IgGs and anti-CD16/32 antibodies (clone 93) and stained with biotin anti-CD11b (clone M1/70), followed by Cy5.5-conjugated streptavidin and Alexa-488 anti-F480 (clone BM8), all from Biolegend. For measurement of mitochondrial superoxide, freshly isolated islets (isolated from pools of 2-3 pancreas) were quickly dissociated using non-enzymatic dissociation medium and incubated in PBS/0.1% BSA in the presence of 2.5 uM MitoSOX-Red (Invitrogen) for 15’ at 37°C. After washing, cells were incubated in the presence of 2.5 nM cell death dye SYTOX Green (Invitrogen) with or without an APC-conjugated anti-EpCAM Ab (clone G8.8, Biolegend) and thereafter analyzed at a FACScalibur (Beckton Dickinson).

Histology and morphometric analysis

Pancreatic tissue from untreated and DT-treated CCR2DTR/+ and WT mice (2-3 mice per group) was fixed in 4% PFA and embedded in OCT or paraffin for histology. Five seven-micron sections were cut and processed for immunofluorescence. Briefly, after citrate antigen retrieval, sections were permeabilized in 0.05% Triton-X 100 and blocked in 50 mM glycine for 10 minutes at room temperature, followed by incubation in 1% BSA/2% donkey serum for 1 hour at room temperature. In select experiments pancreatic islets isolated from DT-treated CCR2DTR/+ and WT mice as well untreated controls were let to adhere to HTB9-matrix coated coverslips prepared as previously described.108 After incubation overnight in RPMI-5% FCS, the islets on coverslips were fixed in 2% PFA, permeabilized and blocked as described above. EDU incorporation in islet cells was detected by click-reaction using the Click-It cell proliferation kit, as per manufacturer’s instructions (ThermoFisher). Sections or islets on coverslips were incubated overnight at 4°C with primary antibodies. These included guinea pig anti-insulin (A0564, Dako), rabbit anti-GADD45B (ab230646, Abcam, Cambridge, UK), mouse anti-glucagon (Sigma, clone K79bB10), rabbit anti-phospho-Histone H2A.X (Ser139) (Cell Signaling Technology #9718), and mouse anti-PCNA (Santa Cruz, clone PC10). Binding of primary antibodies was revealed with Fab2-species-specific Alexa647-conjugated donkey anti-guinea pig-IgG, Rhodamine-conjugated anti-rabbit IgG, and Alexa488-conjugated anti-mouse-IgG secondary antibodies. After staining, slides and coverslips were mounted and visualized either at a NIKON Eclipse-i90 or at a confocal NIKON A1R microscope equipped with a Spot II CCD camera. Morphometric analysis was performed on tissue sections collected at approximately 100-μm intervals throughout the pancreas of each mouse, using the Spot Advanced and ImageProPlus software. At least 25 sections were imaged and analyzed per experimental group.

Electron microscopy

Islets and islets/myeloid cells organ cultures isolated by Ficoll gradient and hand picking from 2-3 mice per experimental group, were fixed in 0.1 M sodium cacodylate trihydrate buffer (pH 7.4) containing 2% (w/v) paraformaldehyde, 2.5% (w/v) glutaraldehyde, 3 μM CaCl2 for 4 hours at room temperature, and then transferred at 4°C overnight. Samples were then post-fixed with osmium tetraoxide (1% (w/v) in H2O) and counterstained with uranyl acetate (2% (w/v) in H2O). Following gradual dehydration in ethanol, samples were embedded in Durcupan resin (Electron Microscopy Sciences, Fort Washington, PA) and polymerized overnight at 60°C as described.109 Ultrathin sections (80 nm) were then cut using a 35° angle Diatome diamond knife and mounted on 300 mesh gold grids (Electron Microscopy Sciences, Fort Washington, PA). Following counterstaining with uranyl acetate (1% (w/v) in H2O) and Sato lead [1% (w/v) in H2O] sections were imaged at 80 keV using an electron microscope (1200FX; JEOL, Akashima, Japan).

Western blotting

Cell extracts were prepared using the NE-PER Cell Extraction Kit (Pierce) in the presence of a cocktail of protease inhibitors (Complete, Roche), phosphorylase inhibitors, and PMSF (1 mM). Protein concentration of lysates was determined by the BCA protein assay (Pierce). Total protein (10 μg) were then separated under reducing conditions onto 4%–12% polyacrilamide gels (Nu-Page, Invitrogen), transferred by Western blotting onto PVDF membranes (Immobilon, Millipore) and blocked in 5% BSA−0.1% Tween-20 overnight at 4°C. Primary antibodies used to probe the membrane were: rabbit anti-GADD45B (ab230646), rabbit anti-phospho JNK (Th3183/Tyr185) (clone 81E11, Cell Signaling), rabbit anti-pan JNK (#9252, Cell Signaling), rat anti-Hsp90 (ab13494, Abcam), rabbit anti-PAX6 (Millipore), mouse anti-Parkin (Santa Cruz Biotechnology, clone PRK8), mouse anti-NDUFA3 (clone B-12, Santa Cruz Biotechnology), mouse anti-NDUFB8 (Invitrogen, clone 20E9DH10C12). Secondary antibodies were HRP-donkey- anti-rat, anti-mouse, or anti-rabbit Fab2 (Jackson Abs). Membrane-bound antibodies were detected by chemiluminescence using the Clarity ECL-detection kit (Biorad).

NAD/NADH measurements

Cellular NAD and NADH were measured using a colorimetric assay (Abcam ab65348) as per manufacture instructions, with some modifications. Briefly, islets isolated from 2-3 mice per experimental groups were let to recover overnight in RPMI-10% FCS. Cells were then lysed in the manufacturer’s extraction buffer supplemented with proteases inhibitors by two rounds of 20’ freezing in dry ice and 10’ defrosting at room temperature. After removal of insoluble material by centrifugation at 10,000g, a small aliquot of each supernatant was set aside for measurement of total proteins by BCA assay. After de-proteinization of the supernatants by centrifugation through a 10kDA microcon, the extracts were then divided into two aliquots. One aliquot designated for measurement of total NAD and NADH was kept in ice, and the other, designated as “NAD decomposed sample” or “NADH only” was heated at 60°C for 10 minutes to decompose NAD+. Addition of the reaction mix and developer solution was as per manufacturer’s instructions. Reaction color development in each sample and standard curve was monitored over 4 hours using an Envision Plate Reader (Perkin Elmer) equipped with a 450nm excitation filter. NAD concentrations were calculated subtracting the NADH only reading to the reading of total NAD+NADH. All NAD/NADH measurements were normalized to the protein concentrations of each sample and expressed as pmoles/ug of protein.

Quantification and statistical analysis

Statistical significance of differences in assays and morphometric analysis was validated by 2-tailed Student’s t test or by ANOVA 1-group variance test for multiple comparisons using the Prism Software (v10). Limit of significance was set at P<0.05.

Supplemental information

Document S1. Figures S1–S6 and Table S1

Acknowledgments

We thank Ms. S. Valente for technical assistance with the maintenance of the mouse colony and Drs. Feinan Wu and Fitzgibbon M (Fred-Hutchison Genomic Core, Seattle, WA) for valuable assistance with the analysis of scRNA-seq data. With further thanks Dr. Bruce Torbett (10.13039/100010514 Seattle Children's Hospital , Seattle WA) and Dr. Stan McKnight (10.13039/100007812 University of Washington , Seattle, WA) for critical reading of the manuscript. This work was supported by 10.13039/100000002 NIH 5R01DK114693 to L.C., and 10.13039/100000002 NIH R01 DK121275 to V.C.

Author contributions

J.O., S.P., A.B.M., P.S., and J.A. performed experiments; V.C. conducted experiments, analyzed data, and provided resources; S.A.G. analyzed the scRNA-seq data, performed DEG and trajectory bioinformatic analysis, and prepared scRNA-seq-related figures; M.C.R. and D.H. performed the RNAscope experiments, collected and deconvoluted tissue images, and performed morphometric analysis of gene transcripts. L.C. designed and conducted experiments, provided resources, analyzed data, and wrote the manuscript.

Declaration of interests

The authors declare no competing interest.

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2024.110644.
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