Abstract
Maternal overnutrition during lactation predisposes offspring to
develop metabolic diseases and exacerbates the relevant syndromes in
males more than females in later life. The hypothalamus is a
heterogenous brain region that regulates energy balance. Here we
combined metabolic trait quantification of mother and offspring mice
under low and high fat diet (HFD) feeding during lactation, with single
nucleus transcriptomic profiling of their offspring hypothalamus at
peak lacation to understand the cellular and molecular alterations in
response to maternal dietary pertubation. We found significant
expansion in neuronal subpopulations including histaminergic (Hdc),
arginine vasopressin/retinoic acid receptor-related orphan receptor β
(Avp/Rorb) and agouti-related peptide/neuropeptide Y (AgRP/Npy) in male
offspring when their mothers were fed HFD, and increased Npy-astrocyte
interactions in offspring responding to maternal overnutrition. Our
study provides a comprehensive offspring hypothalamus map at the peak
lactation and reveals how the cellular subpopulations respond to
maternal dietary fat in a sex-specific manner during development.
Subject terms: Epigenetics in the nervous system, Obesity
__________________________________________________________________
Maternal high fat diet during lactation predisposes offspring to
develop obesity in males more than females. Here, authors show
expansion of key metabolic related hypothalamic neuron populations in
male but not female mice, in response to maternal fat intake.
Introduction
Obesity has increased rapidly in the past five decades with currently
more than 2.5 billion people being overweight or obese^[42]1. Emerging
evidence suggests that maternal nutrition during pregnancy or lactation
is crucial for offspring growth and development^[43]2–[44]8. The impact
of maternal diet exposure may interact with overnutrition in later life
to exacerbate offspring adiposity. Previous studies^[45]9,[46]10
demonstrated that lactation is an important period for maternal effects
since during lactation offspring rely solely on the mother’s milk for
their nutrition and growth. In both human and animals, maternal
overnutrition during pregnancy and/or lactation predisposes offspring
to obesity, and increases the risk of metabolic syndrome, insulin
resistance and hypertension in offspring^[47]6,[48]8,[49]11–[50]18.
However, these effects may vary depending on the sex of the offspring
with male offspring being more sensitive^[51]8,[52]14,[53]18–[54]22.
Although numerous studies have studied such effects in both
sexes^[55]23–[56]25, the majority of previous studies primarily focused
on male offspring^[57]12–[58]14,[59]16. Since at least half of the
world population is female, understanding similarities and differences
in maternal diet effects on both sexes is an important goal.
The hypothalamus regulates energy balance and other vital physiological
processes, including hormone release from the pituitary, temperature
regulation, circadian rhythms and social/sexual
behaviors^[60]26–[61]29. Neurons, glial and immune cells with diverse
cellular functions organize into spatially distinct but structurally
contiguous nuclei^[62]30–[63]34. In the hypothalamic arcuate nucleus
(ARC), canonical neuropeptides agouti-related peptide (AgRP) and
pro-opiomelanocortin (POMC) play central roles in regulating food
intake and energy homeostasis^[64]35–[65]39. Offspring raised by
mothers with maternal obesity or exposure to a high fat diet (HFD)
during pregnancy and/or lactation usually have a higher ratio of
AgRP/POMC expressing neurons^[66]5,[67]8,[68]40–[69]42. Previous
studies of the transcriptomic profiles of the offspring hypothalamus in
response to maternal overnutrition were addressed at the tissue level
using bulk RNA-seq^[70]43–[71]45, which makes it difficult to reveal
the complicated hypothalamic heterogeneity, key functional pathways and
cellular communications between cell subpopulations. Single
cell/nucleus transcriptomics is a powerful technique that enables the
dissection of the cellular heterogeneity and pathways in the offspring
hypothalamus in response to maternal overnutrition. Multiple studies
have recently employed single cell/nucleus RNA-seq to better understand
the development of the rodent hypothalamus^[72]44,[73]46–[74]58. The
‘HypoMap’ integrated multiple datasets and generated the largest single
cell gene expression atlas of the murine hypothalamus to date^[75]59.
However, no previous study profiled the postnatal offspring
transcriptomic landscapes in the hypothalamus to understand the impact
of maternal nutrition during lactation at the single cell level, which
may enhance our understanding of the sex-specific offspring response to
the maternal diet. This could facilitate the development of
interventions to reduce the risk of obesity in offspring when exposed
to an unhealthy maternal diet.
Here we performed maternal and offspring physiological measurements of
mice exposed to maternal high fat diet (HFD) or low fat diet (LFD)
during lactation and generated a single nucleus transcriptomic
(snRNA-seq) atlas of 38,594 high quality nuclei after quality control
of the male and female offspring hypothalamus during peak lactation
(age postnatal day 15, P15). Mothers fed with HFD had significantly
elevated milk energy output than those fed with LFD. Their offspring
were also significantly heavier than those from the maternal LFD group.
We identified nine key cell populations including neurons, astrocytes,
tanycytes, ependymal cells, oligodendrocyte precursor cells and
oligodendrocytes, microglia, stromal cells, and immune cells including
macrophages and B cells in the offspring hypothalamus. Histaminergic
(Hdc) and arginine vasopressin/retinoic acid receptor-related orphan
receptor β (Avp/Rorb) neuronal subpopulations and the well-known AgRP
neurons were enriched in the male offspring specifically when their
mothers were fed HFD, highlighting that maternal dietary exposure
during lactation has significant effects on neurogenesis, particularly
in male offspring, which may contribute to their later susceptibility
to obesity when exposed to HFD themselves. Although previous work has
highlighted differential expansion of AgRP neuron populations in males
under maternal HFD feeding^[76]5,[77]8,[78]40–[79]42, expansion of
Avp/Rorb and Hdc cell populations has not been previously suggested. We
found increased celluar interactions in male offspring when their
mothers were fed HFD, compared to the other groups, suggesting
extensive modulation resulting from over-nutrition in male offspring.
We further experimentally validated that there were increased
neuronpeptide Y (Npy) neuron-astrocyte interactions in the offspring
responding to maternal HFD. Our findings provide a comprehensive atlas
of the mouse offspring hypothalamus at P15 (peak lactation of their
mothers) responding to mothers fed with different levels of dietary
fat^[80]60, and unravel how the celluar subpopulations respond to
overnutrition in a sex-specific manner. We have made the dataset
publicly available ([81]https://mouse10x.shinyapps.io/p15atlas/).
Results
In this study, we integrated physiological measurements from both
mothers and their offspring to investigate the impact of maternal diet
during lactation on energy balance and utilized single nucleus
transcriptomic sequencing to gain insights into the alterations
occurring in the offspring hypothalamus driven by maternal diet.
Higher energy intake in mothers fed HFD during lactation
12-Week old female C57BL/6 N mice were fed with LFD for a 2 week
baseline period and during pregnancy. After birth (day 0), mothers were
fed LFD (n = 9) and HFD (n = 6) across the lactation period (diet
swapped from lactation day 1) (Fig. [82]1a). There were no significant
differences observed in maternal body weight (BW) between LFD and HFD
groups before mating (baseline) (ANOVA, F = 0.021, P = 0.887), during
late pregnancy (7 days before parturition) (RM GLM, F = 0.133,
P = 0.722) and during lactation (RM GLM, F = 0.398, P = 0.539)
(Fig. [83]1b, Supplementary Data [84]1). A significant effect of day of
lactation (RM GLM, F = 50.992, P < 0.001) on maternal BW was observed
during lactation (Fig. [85]1b), reflecting a significant increase in
the maternal BW across the lactation period in both maternal LFD and
HFD groups (Fig. [86]1b). In addition, no significant differences were
observed in body fat mass and lean mass before mating (ANOVA, fat mass:
F = 0.636, P = 0.439; lean mass: F = 0.944, P = 0.349) on lactating day
1 (ANOVA, fat mass: F = 0.039, P = 0.847; lean mass: F = 0.213,
P = 0.652), day 10 (ANOVA, fat mass: F = 0.469, P = 0.505; lean mass:
F = 0.549, P = 0.472) and day 16 (ANOVA, fat mass: F = 0.063,
P = 0.807; lean mass: F = 0.006, P = 0.937) (Fig. [87]1c, d).
Fig. 1. Metabolic measurements for mothers fed with different dietary fat
during lactation as well as their offspring.
[88]Fig. 1
[89]Open in a new tab
a Diagram of experimental design. b Maternal body weight (BW) (c) body
fat mass, d body lean mass, e food intake (FI) and (f) energy intake
(EI) from low fat and high fat dietary groups during lactation. Sample
sizes of mothers fed low fat diet (LFD) during lactation were 9, for
those fed high fat diet (HFD) were 6. g Maternal metabolizable energy
intake (MEI), daily energy expenditure (DEE) and milk energy output
(MEO) during peak lactation. Sample sizes of maternal LFD group for the
measurements were 8, for those from maternal HFD group were 3. p value
by GLM adjusted with BW. h Litter and (i) pup mass of offspring raised
by mothers fed with different dietary fat during lactation. j Litter
fat and lean mass of postnatal day16 offspring raised by mothers fed
with different dietary fat. Sample sizes of litters from maternal LFD
group were 8, for those from maternal HFD group were 5. p value by
one-way ANOVA. * represents p < 0.05, ** represents p < 0.01. ns
represents no significance between comparisons. Values are means±s.d.
LFD represents low fat diet, HFD represents high fat diet, P represents
postnatal in (a). BL represents baseline, L represents lactation in
(b−i). Source data are provided as a [90]Source Data file.
There was no significant difference in maternal gross food intake (FI)
before mating (ANOVA, F = 0.346, P = 0.567) and during late pregnancy
(RM GLM, F < 0.001, P = 0.998) between groups when they were all eating
the LFD. Between lactation days 1 to 15 there was a highly significant
effect of day of lactation (RM GLM F = 35.18, P < 0.001) as well as a
significant effect of diet (F = 5.134, P = 0.041) on maternal gross FI.
Mothers fed HFD had a lower daily FI (by weight) than those fed LFD
(Fig. [91]1e, Supplementary Data [92]1). The gross energy content of
the foods was 18.234 and 23.101 KJ/g for 10% and 45% fat diets
respectively. Significant effects of day of lactation (RM GLM,
F = 37.967, P < 0.001) and diet (F = 10.192, P = 0.007) were also
observed on gross food energy intake (GE[food]) during lactation.
Contrasting the observation on the weight of food eaten, mothers fed
HFD had a higher daily energy intake than those fed LFD (Fig. [93]1f,
Supplementary Data [94]1).
There was no significant difference in daily energy expenditure (DEE,
measured by doubly-labeled water between lactation days 13 to 15) (GLM,
diet: F = 2.766, P = 0.131; BW: F = 2.135, P = 0.182) and metabolizable
energy intake (MEI) (GLM, diet: F = 3.175, P = 0.108; BW: F = 0.722,
P = 0.42) between maternal dietary groups after adjustment for BW
(Fig. [95]1g, Supplementary Data [96]1). The mothers fed HFD had higher
milk energy output (MEO) (GLM, diet: F = 11.941, P = 0.007; BW:
F = 0.145, P = 0.713) than those fed LFD. The MEO from the mice fed HFD
(134.23 kJ/d) was approximately 36% more than the LFD group
(86.22 kJ/d) (Fig. [97]1g, Supplementary Data [98]1).
Offspring raised by mothers fed HFD during lactation are heavier
There were significant differences between days of lactation
(F = 618.94, P < 0.001) and a significant day×diet interaction
(F = 6.709, P = 0.006) on litter mass (LM) in both maternal dietary
groups. There was no maternal dietary effect on the LM before peak
lactation (day 1 to 11) (F = 2.044, P = 0.176). During peak lactation,
a significant increase in the LM was observed in the litters of mothers
fed the HFD (diet: F = 7.521, P = 0.017). The pups raised by mothers
fed HFD had significantly greater LM than those fed LFD (Fig. [99]1h).
Similarly, pup mass (PM) of offspring raised by mothers fed HFD was
significantly increased over peak lactation (days 12–16) compared with
those fed LFD (RM GLM: diet: F = 5.89, P = 0.031; day of lactation:
F = 56.449, P < 0.001; day×diet: F = 2.636, P = 0.093) (Fig. [100]1i).
Final LM and PM at P16 showed the same patterns of significance in
different dietary groups (LM: F = 9.069, P = 0.01; PM: F = 7.068,
P = 0.02). Offspring from HFD fed mothers were 5.57 g heavier in LM and
1.17 g heavier in PM compared with those raised by mothers fed LFD
(Supplementary Data [101]1). The fat and lean contents of the litters
raised by HFD fed mothers were both significantly higher than the LFD
ones (ANOVA, fat mass: F = 22.505, P = 0.001, lean mass: F = 7.506,
P = 0.019). The litters from HFD fed mothers had 45.37% higher fat mass
and 13.74% greater lean mass than those fed LFD (Fig. [102]1j,
Supplementary Data [103]1).
In male offspring, masses of the subcutaneous fat and spleen were 57%
and 32% heavier when raised by HFD fed mothers compared to those fed
LFD (subcutaneous fat: F = 18.983, P = 0.001; spleen: F = 12.877,
P = 0.004). A significant maternal dietary effect on subcutaneous fat
in male offspring was still observed even after correcting for total BW
(subcutaneous: diet, F = 11.127, P = 0.007; BW, F = 35.965, P < 0.001)
(Supplementary Fig. [104]1a). Significant maternal dietary effects were
also observed in the masses of subcutaneous fat and spleen, as well as
in BAT and heart, in female offspring (subcutaneous fat: F = 10.024,
P = 0.009; spleen: F = 5.732, P = 0.036; BAT: F = 6.485, P = 0.027;
heart: F = 13.408, P = 0.004). However, after adjusting for total BW,
the significance of the differences disappeared except for the mass of
the heart (diet, F = 5.994, P = 0.034; BW, F = 8.016, P = 0.018), with
20.73% larger heart mass in females from the maternal HFD group
(Supplementary Fig. [105]1b). These results suggested that male
offspring were more sensitive in response to maternal diet in
particular in fat mass.
A high-resolution cellular atlas of the offspring hypothalamus at peak of
lactation
To enable a comprehensive understanding of the cellular landscape of
sex specificity in different cell populations in the postnatal
offspring hypothalamus, we generated a single nucleus atlas at peak
lactation (offspring P15). We isolated nuclei from female offspring
raised by mothers fed LFD (abbreviated as fLFD below) and HFD (fHFD),
as well as male offspring raised by mothers fed LFD (mLFD) and HFD
(mHFD) (Fig. [106]2a). A total of 38,594 nuclei were included in the
downstream analyses after quality control, doublet removal and batch
correction, including 19,159 and 19,435 nuclei from female and male
offspring respectively (Supplementary Fig. a, b, Supplementary
Data [107]2). We identified nine major cell types (Fig. [108]2b−d)
annotated by canonical marker genes, cell type specific genes and
SingleR^[109]61. Neurons (marked by Snhg11, Meg3) comprised 66.3% of
the total nuclei followed by non-neuronal cells including astrocytes
(9.7%, Ntsr2), oligodendrocyte precursor cells and oligodendrocytes
(OPCs and ODCs, 8.9%, Pdgfra, Plp1), stromal cells (7.4%, Col3a1),
tanycytes and ependymal cells (4.5%, Col23a1 for tanycytes and Dnah12
for ependymal cells), endothelial cells (0.4%, Flt1), interneurons
(0.6%, Chga, Cga), microglia/macrophages (2.1%, Siglech, Mrc1) and a
tiny population (0.2%) of B cells (Cd74, Cd79a) (Supplementary
Data [110]3–[111]4).
Fig. 2. Establishing a single nucleus atlas of mouse hypothalamus from
postnatal day 15 (P15) male and female offspring raised by mothers fed with
different dietary fat during lactation.
[112]Fig. 2
[113]Open in a new tab
a Diagram of single nucleus RNA-seq experiment using 10x Genomics
(n = 2 for each maternal dietary group, groups including: fLHD female
offspring under maternal low fat diet during lactation, fHFD, female
offspring under maternal high fat diet during lactation, mLFD male
offspring under maternal low fat diet during lactation, mHFD male
offspring under maternal high fat diet during lactation). This image
was adapted and created with BioRender.com. b Uniform Manifold
Approximation and Projection (UMAP) visualization of key lineages after
data integration, colored by different cell types (total cell number
after QC = 38,594). c Canonical marker genes for key lineages shown on
the UMAP. d Dotplots show the marker genes for key lineages. e Donut
plots of the cell proportions of key lineages from female and male
offspring under maternal LFD and HFD exposure.
In addition, we quantified and compared the percentage of each cell
type in the hypothalamus across the fHFD, fLFD, mHFD, and mLFD groups
as well as individual samples. There were no overall significant
differences in terms of the percentage of nuclei between the four
groups and cellular composition was similar across the replicates
(Fig. [114]2e, Supplementary Fig. [115]2c). The neuronal population was
consistently the largest in all four groups as in the integrated data
(fHFD = 67.8%, fLFD = 68.7%, mHFD = 65.6%, mLFD = 63.3%). We further
adapted DAseq^[116]62, a differential abundant cell subpopulations
detection method and found that astrocytes and OPCs were expanded in
the fHFD group compared with the mHFD group, however, there were no
compositional differences between the fLFD and mLFD groups, nor between
the mHFD and mLFD groups(Supplementary Fig. [117]2d). Differentially
expressed gene (DEG) analyses between different groups revealed that
the top 3 maternal dietary perturbed cell populations are neurons (5289
DEGs across all the comparisons), astrocytes (398 DEGs) and
oligodendrocytes (288 DEGs) (Supplemental Data [118]4). Top/bottom 5
DEGs ordered by log2 fold change of each comparison in neurons,
astrocytes and oligodendrocytes were shown in Supplementary
Fig. [119]2e and/or Supplemental Data. [120]4. Astrocytes and
oligodendrocytes are two important gila cells that regulate neuronal
synaptic structure and plasticity in the central nervous
system^[121]63. Rorb is functionally related to astrocyte maturation
and might be critical for the maintenance of normal neuronal
excitability^[122]64. We observed that Rorb hits as one of the top DEGs
in maternal HFD feeding groups in astrocytes (mHFD vs fHFD,
P[adj] = 0.002; mHFD vs mLFD, P[adj] < 0.001). GO enrichment analyses
were performed using the DEGs between different dietary groups in the
top 3 perturbed cell populations (Supplemental Data [123]4). GO-BP
pathways such as “myelination” or “regulation of myelination” are
significantly enriched in oligodendrocytes between the comparisons of
maternal HFD vs LFD or male vs female offspring. The induction of
hypothalamic myelin disruption was observed when mice were exposed
under chronic HFD feeding^[124]65. Pathways such as “regulation of
neuron death” are significantly enriched in neurons between different
maternal dietary groups. HFD induced apoptosis of hypothalamic neurons
was observed in rodents^[125]66.
To compare our dataset with the published integrated adult murine
hypothalamic dataset HypoMap^[126]59, we projected the cells in our
dataset onto the HypoMap dataset using the Symphony^[127]67 reference
mapping algorithm and confirmed that the annotation in our dataset is
consistent with the HypoMap results in the adult mouse hypothalamus
(Supplementary Fig. [128]2f). This indicated that cell types observed
in adult mice are already committed in the newly developed hypothalamus
at postnatal day 15. Our dataset therefore represents a comprehensive
cellular atlas of the female and male offspring hypothalamus at P15.
Transcriptional heterogeneity of neurons in the postnatal day 15 offspring
hypothalamus
To understand cellular heterogeneity in the neurons, the largest and
most diverse cell type in the newly developed hypothalamus, in response
to different maternal diets during lactation in both male and female
offspring, we sub-clustered the 25,570 neuronal cells into 30 neuronal
subpopulations and separated them into excitatory glutamatergic
(Slc32a1, Gad1, Gad2), inhibitory gamma-aminobutyic acid-ergic
(GABAergic) (Slc17a6) and histaminergic (Hdc) neurons (Fig. [129]3a,
b). The neuronal subclusters present 29 subpopulations annotated by
known markers and one unassigned subtype. Then we colored the neurons
according to the hypothalamic regions including the ARC, the
dorsomedial hypothalamic nucleus (DMH), the lateral hypothalamic area
(LHA), the paraventricular hypothalamic nucleus (PVH), the supraoptic
nucleus (SON) and the ventromedial nucleus of the hypothalamus (VMH)
etc (Supplementary Fig. [130]3a). A list of marker genes was identified
for each sub-cluster as shown in Supplementary Data [131]4. We also
examined the gene expressions of some well-known neurotransmitters and
neuropeptides in our dataset and we were able to identify key neuron
clusters encoding neuropeptides controlling food intake including Agrp,
Pomc, Cocaine and amphetamine-related transcript (Cartpt),
cholecystokinin (Cck), neuropeptide Y (Npy), galanin (Gal),
hypocretin/orexin (Hcrt) etc (Fig. [132]3c, Supplementary
Fig. [133]3b). As expected, all the neuron subpopulations were present
in all four groups (Supplementary Fig. [134]3b). To better understand
the heterogeneitic metabolic functional roles in different neuronal
subpopulations, we performed GO pathway enrichment analysis using
cell-type specific marker genes and identified 18 neuronal
subpopulations, including AgRP and POMC neurons (the key regulators of
food intake and energy homeostasis), were enriched in the metabolic
related pathways of “feeding behavior”, “insulin signaling”, “response
to glucose” and “circadian rhythm” categories (Fig. [135]3d).
Fig. 3. Heterogeneity of P15 offspring hypothalamic neuronal subpopulations.
[136]Fig. 3
[137]Open in a new tab
a UMAP of canonical maker genes of glutamatergic, gamma-aminobutyric
acid-ergic (GABAergic) as well as histaminergic (HA) neurons. b UMAP of
neuronal subpopulations, colored by different neuronal subpopulations.
c Dotplot shows the canonical marker genes for neuronal subpopulations.
d GO enrichment analysis of cell type specific transcriptomic
signatures shows significant enrichment (P[adj] < 0.05) in metabolic
relevant categories of feeding behavior, insulin signaling, glucose
homeostasis and circadian rhythm in several neuronal subpopulations. p
value was adjusted by Benjamin-Hochberg correction. e Differential
abundance analysis (DAseq) shows the enrichment of the abundance of
cells from different neuronal subpopulations when comparing fHFD vs
mHFD. Colored dots represent the enrichment of abundance in different
groups.
We next investigated the differential abundance across the neuronal
subpopulations for the four groups using DAseq and validated using
scCODA^[138]68, we found an increased number of AgRP neurons in the
offspring from maternal HFD groups compared to LFD ones in both sexes
(Fig. [139]3e and Supplementary Fig. [140]3d). We further found an
expansion of the number of AgRP neurons in mHFD group vs fLFD group.
Arginine vasopressin (Avp)/retinoic acid receptor-related orphan
receptor β (Rorb) neurons were also expanded in the mHFD group compared
with the other three groups. The transcriptomic signatures of Avp/Rorb
neurons were enriched in the GO-BP “insulin secretion” and “response to
glucose” terms (Fig. [141]3d), in line with the previous finding that
AVP neurons modulate diverse metabolic functions including glucose
homeostasis^[142]69, insulin secretion^[143]70 and feeding
behavior^[144]69. We also observed increased Hdc neurons in the mHFD
group compared with the fHFD group. The enriched pathways of the
transcriptomic signatures of Hdc neurons were found to play important
roles in feeding behavior, response to dietary excess, insulin
secretion, response to glucose, and circadian rhythm. A small
population of Limhomedomain transcription factor 1 (Lhx1) neurons was
also expanded in the mHFD group compared to the fHFD group and showed
enrichment in pathways of insulin secretion and response to glucose. We
identified a large neuronal subpopulation marked by Nr5a1 and found the
number of these neurons was increased in the mLFD group compared with
fLFD group, as well as in fHFD groups compared with fLFD groups. GO
pathway enrichment analysis of Nr5a1 specific transcriptomic signatures
exhibited enrichment in the feeding behavior pathway, consistent with
the fact that Nr5a1 neurons in VMH region can sense glucose levels and
conduct insulin and leptin signaling in energy expenditure and glucose
homeostasis, with minor feeding control^[145]71. DEG analysis between
maternal dietary groups in neuronal subpopulations also showed that
Nr5a1 hits one of the top 3 DEG hubs in neurons (222 DEGs across all
the comparisons) (Supplementary Data [146]4). Together, the single
nucleus atlas we generated illustrates the complex neuronal
heterogeneities of the offspring hypothalamus under different maternal
dietary fat exposures during lactation.
Heterogeneity of key neurons that regulate food intake
AgRP and POMC neurons are well known to be associated with food intake
and energy homeostasis. We subclustered the AgRP neurons based on their
transcriptional similarities and found three distinct subpopulations:
AgRP-1 (Agrp^high/Npy^high), AgRP-2 (Agrp/Npy), and AgRP-3
(Agrp^low/Npy^low) (Fig. [147]4a, b, Supplementary Fig. [148]4a, b).
DAseq and fraction analyses showed there were no abundance differences
in the cell proportions of all the AgRP subclusters between offspring
sexes and diet groups (Fig. [149]4c). We have further quantified the
percentage of cells expressing Agrp and Npy and their expression in the
four offspring groups and there was no significant difference between
groups. Lepr was co-expressed in AgRP neurons in our dataset
(Supplementary Fig. [150]4c), but not all the AgRP subpopulations
co-expressed Lepr, suggesting AgRP heterogeneity is possibly driven by
leptin. AgRP neurons could integrate the action of leptin to regulate
both energy balance and glucose homeostasis^[151]72,[152]73. We also
compared the Agrp expression across four groups and found no
significant difference (Fig. [153]4d). We further quantified the
AgRP/POMC ratio and found a higher ratio in the mHFD group (2.69)
compared to other groups (fHFD = 2.22, fLFD = 1.91, mLFD = 2.08
respectively). The long non-coding RNA Xist, is widely considered as
the master regulator of X inactivation since Xist is part of the X
inactivation center (XICC), which harbors additional non-coding RNA
genes involved in the same process. It has been recently found as a
marker of neuronal aging in female mammal hypothalamus^[154]50. We
found Xist was one of the top upregulated genes in female offspring
raised by mothers fed with HFD in all the AgRP neuronal subpopulations
in our dataset (Fig. [155]4d). We also found Brd1 was upregulated in
the offspring from maternal HFD groups in both sexes (fHFD vs fLFD:
P[adj] = 0.002, mHFD vs mLFD: P[adj] < 0.001) and notably, there were
more cells expressing Brd1 in the mHFD group with a higher expression
level, revealing the hypothalamic adaptation to maternal HFD
(Fig. [156]4d). Previous studies suggested the roles of HDACs as key
epigenetic players in obesity development and we observed a higher
expression of Hdac3 per cell as well as a higher number of cells
expressing Hdac3 in mLFD group (P[adj] < 0.001, mHFD vs mLFD)
(Fig. [157]4d). We also subclustered the POMC into three subpopulations
(POMC-1, POMC-2, POMC-3) by different expression levels of Pomc
(Supplementary Fig. [158]4e−h). Brd1 was significantly upregulated in
mHFD group (P[adj] = 0.022, mHFD vs mLFD).
Fig. 4. Heterogeneity of AgRP/Npy and Avp/Rorb neurons in P15 offspring
hypothalamus.
[159]Fig. 4
[160]Open in a new tab
a UMAP of canonical marker genes for AgRP neurons (Agrp and Npy) in
neuronal subpopulations. b UMAP of canonical marker genes for AgRP
neurons (Agrp and Npy) on the extracted AgRP/Npy neurons. Unsupervised
clustering of extracted AgRP/Npy subclusters identified three distinct
subtypes. c Barplot of the cell proportions of AgRP subclusters from
fHFD, fLFD, mHFD and mLFD groups. d Violin plots of the expression of
Agrp, Xist, Brd1 and Hdac3 genes in four groups in AgRP/Npy neurons. *
represents P < 0.05 for Wilcoxon test. e Unsupervised clustering of
extracted Avp/Rorb subclusters identified two distinct subtypes. f
Heatmap of the top 10 differentially expressed genes in each Avp/Rorb
subcluster. g Umap and Violin plots of the expressions of Avp, Rorb,
Igfbp5 and Gm42418 genes in four groups in Avp/Rorb neurons. *
represents p < 0.05, ** represents p < 0.01 and *** represents
p < 0.001 for Wilcoxon test. ns represents no significance between
comparisons.
Avp/Rorb neurons were uniquely expanded in mHFD group (Fig. [161]3e)
and we subclustered the Avp/Rorb neurons into two subpopulations
(Avp/Rorb-1 and Avp/Rorb-2, Fig. [162]4e, f). The Avp/Rorb-1 cluster
had higher expression of Dlk1, Vgf and Gnas genes, suggesting a more
proliferated cellular status. We further analyzed the differentially
expressed genes in the Avp/Rorb clusters and found both Avp and Rorb
expression were higher in mHFD group compared with fHFD group
(Fig. [163]4g). We also found Igfbp5, the insulin like growth
factor-binding protein 5, was upregulated specifically in the mHFD
group compared to fHFD group (P[adj] < 0.001, mHFD vs fHFD). Gm42418
was highly expressed in male offspring under maternal HFD
(P[adj] < 0.001, mHFD vs mLFD) and this is consistent with previous
studies suggesting Gm42418 is involved in the response to HFD^[164]74.
Top/bottom 5 DEGs from the key neuronal populations (AgRP, Avp/Rorb and
POMC) were summarized in Supplementary Fig. [165]4i and Supplementary
Data [166]4.
Key non-neuronal populations
Over 30% of the cells in the P15 hypothalamus were non-neuronal. The
astrocytes were the second-largest population in our atlas, consistent
with previous findings in the adult hypothalamus^[167]59. We identified
two distinct astrocyte clusters on the basis of transcripomic
similarities: Astrocyte-1 (Gfap) and Astrocyte-2 (Slc7a10)
(Fig. [168]5a, Supplementary Fig. [169]5a, Supplementary Data [170]5).
We didn’t observe an enrichment difference between these two clusters
of astrocytes in offspring raised by mothers fed with different diets
by DAseq analysis. We further explored the variation among different
sub-clusters through pseudotime ordering of nuclei using Monocle3 and
identified a trajectory from the Astrocyte-1 to the Astrocyte-2 cluster
(Fig. [171]5b). We further compared Mulan’s I test modules and
visualized the trajectory related gene expressions along the pseudotime
from the Gfap cluster to the Slc7a10 cluster. We found genes including
Myoc, Id1, Id3 and Id4 that represents a more-stemmed status were
pseudo-gradually down-regulated whereas genes including Plpp3, Cst3
were up-regulated along the trajectory (Fig. [172]5b).
Fig. 5. Heterogeneity of astrocytes and oligodendrocytes in P15 offspring
hypothalamus.
[173]Fig. 5
[174]Open in a new tab
a Unsupervised clustering of extracted astrocytes identified two
distinct subtypes and the expression of canonical marker genes Gfap
(Astrocytes-1) and Slc7a10 (Astrocytes-2) on UMAP. b Trajectory
analysis of astrocytes identified a trajectory from subtype Astrocyte-1
to Astrocyte-2. Trajectory related gene expressions along the
pseudotime including Myoc, Id1, Id3 and Id4 that represents a
more-stemmed status were pseudo-gradually down-regulated wheares genes
including Plpp3, Cst3 were up-regulated along the trajectory. c, d UMAP
of unsupervised clustering of extracted oligodendrocytes identified
five distinct subtypes and the expression of canonical marker genes
Pdgfra (oligodendrocyte precursor cells) and Plp1 (oligodendrocytes).
Trajectory analysis shows the trajectory from ODC-1 to ODC-5. e Violin
plots of canonical marker genes Pdgfra and Plp1 in five oligodendrocyte
subclusters. Plp1 shows a gradual change of expression along the
differentiation trajectory.
Recent studies have shown that oligodendrocytes also play important
roles in regulating energy balance^[175]75,[176]76. We further
subclustered these cells into five subpopulations referred to as ODC-1
to ODC-5. ODC-1 was annotated as oligodendrocyte precursor cells with
higher expression of the progenitor marker Pdgfra. The rest of the
subpopulations were more differentiated ODCs with Plp1 expression
(Supplementary Data [177]5). We observed a gradual change of Plp1 along
the differentiation trajectory (Fig. [178]5c−e). Tanycytes are
hypothalamic-specific cells and we further subclusted them into
ependymal cells (Dnah12, Ccdc153), tanycytes alpha+beta1 (Fzrb, Vcan)
and beta2 subpopulations (Col24a1, Scn7a) (Supplementary Fig. [179]5b,
c, Supplementary Data [180]5). We did not observe significant changes
of the cellular proportions in ependymal/tanycytic subclusters between
different maternal dietary groups.
Cell-cell communications in offspring hypothalamus revealed sex- and maternal
diet-specific effects
To understand the cell-cell interactions between cell populations, we
first applied CellChat to the nine key lineages. We found that neuron
populations were the hotspot of cellular interactions in all four
groups. Both female and male offspring from maternal HFD groups had
significantly enriched cell-cell interactions compared with those from
maternal LFD groups. Because neurons exhibited the most intensive
cellular interactions among all the cell types, we further performed
cell-cell interaction analysis on neuronal subclusters with non
neuronal clusters. We identified 10,595 cell-cell interactions in mHFD
groups and 9949 in mLFD, 8120 in fHFD and 7050 in fLFD groups
(Fig. [181]6a). There were more interactions in the offspring raised by
maternal HFD compared with those by maternal LFD.
Fig. 6. Cell-cell interactions in offspring hypothalamus revealed sex- and
maternal diet-specific effects.
[182]Fig. 6
[183]Open in a new tab
a Total numbers of cell-cell interactions in fHFD, fLFD, mHFD and mLFD
groups. b Overall interactive signaling changes on key neuronal
subpopulations and top scoring non-neuronal populations between mHFD
and fHFD groups. c Immunohistochemistry staining shows the
co-localization of AgRP/Npy neurons and astrocytes. Green cells marked
by GFP represent AgRP/Npy neurons, purple cells marked by S100β
represent astrocytes, blue dots marked by DAPI represent the nuclei.
White overlapping by both GFP and S100β represents the colocalization
of AgRP/Npy neurons and astrocytes. d Cell counts of colocalized
AgRP/Npy neurons and astrocytes in four groups. Biologically
independent animals for fHFD group were 5, for fLFD group were 5, for
mHFD group were 5, for mLFD group were 4. p value by two-sided
Student’s t test. Values are means ± s.d. * represents p < 0.05 for
Wilcoxon test. e The identified key pathways of the interactive
signaling between mHFD and fHFD groups. f, g The identified key
up-regulated and down-regulated signaling ligand-receptor pairs between
the interactions of AgRP neurons and astrocytes in mHFD and fHFD
groups. Source data is provided as a [184]Source Data file.
We then focused on the interactions between food intake regulator
AgRP/Npy neurons and astrocytes (top scoring non-neuronal populations)
as the interaction weight was the strongest across key metabolic
relevant clusters (Fig. [185]6b, Supplementary Fig. [186]6a−c). We
validated the differential interaction strengths using
immunohistochemistry staining. Using a Npy-hrGFP mouse model exposed to
the same maternal diets, we stained astrocytes on postnatal day 15 in
male and female offspring brains using the canonical marker S100β. We
found Npy-GFP positive cells were largely enriched in the hypothalamic
ARC region. Some Npy neurons marked by GFP also co-expressed S100β,
which indicated that Npy neurons and astrocytes were co-localized in
the ARC area. To further determine the effect of maternal dietary fat
on the co-localization of Npy neurons and astrocytes in both male and
female offspring, we quantified the amount of Npy/astrocyte
co-localized cells in the ARC region for all four groups. The
co-localization of cells in male offspring raised by mothers fed on HFD
was significantly higher than the male offspring raised by mothers
feeding on LFD (t test, F = 0.346, P = 0.046). However, there is no
significant difference between the co-localization of cells from female
offspring raised by mothers fed with HFD during lactation and those
female offspring raised by mothers fed the LFD (t test, F = 0.32,
P = 0.408). (Fig. [187]6c, d). No significant differences (t test, fHFD
vs fLFD: F = 0.155, P = 0.764; mHFD vs mLFD: F = 0.324, P = 0.0826)
were observed between groups after normalization (computed by the ratio
of the cells co-localized with Npy neurons and astrocytes to the total
number of cells stained by DAPI) (Supplementary Fig. [188]6j). The same
trends were shared using both the number of co-localized cells as well
as the ratio of co-localized cells to total cells in four groups,
indicating that increased cellular interactions might be occurring
between AgRP/Npy neurons and astrocytes in male and female offspring
raised by mothers fed HFD during lactation and the response to maternal
effect in a sexually dimorphic manner, coherent with the predictions
using CellChat.
Notably, we observed that male offspring under maternal HFD exhibited
highly enriched interactions of NEGR (neuronal growth regulator)
pathway (Negr1-Negr1 interaction pair) within AgRP neurons in male
offspring raised by mothers fed with HFD (Fig. [189]6e−g, Supplementary
Fig. [190]6d−h, Supplementary Data [191]6), in comparison with male
offspring under maternal LFD or female offspring under maternal HFD.
Furthermore, we found an enrichment of NCAM1 (Ncam1-Ncam2/1) pathway
interactions between AgRP neurons and astrocytes in male offspring
under maternal HFD.
Discussion
Studies in both rodents^[192]6,[193]8,[194]14,[195]19,[196]77,[197]78
and humans^[198]17 have shown that high maternal dietary fat intake
during pregnancy and/or lactation increases the susceptibility of
offspring to later obesity, combined with insulin and leptin resistance
during adulthood. In this study, we combined quantification of the
metabolic traits from mothers and offspring C57BL/6 mice under low and
high fat feeding during lactation, with a single nucleus transcriptomic
atlas of the female and male offspring hypothalamus at P15 (peak
lactation) to understand the cellular functional states and
transcriptomic alterations in response to the maternal dietrary fat
pertubation.
Multiple rodent studies have shown that elevated maternal dietary fat
content increased offspring BW^[199]18,[200]79,[201]80. Maternal HFD
during lactation increased adiposity of early postnatal offspring mice
and this maternal effect exacerbates offspring obesity and related
metabolic syndrome in males, but less so in females, in later
life^[202]15,[203]18,[204]21,[205]23–[206]25. Consistent with the
previous results in different mouse strains, our study showed that
offspring raised by mothers fed HFD during lactation had higher body
weight, fat and lean mass than those mothers were fed LFD.
The hypothalamus is a major brain region for energy homeostasis and has
been shown to be a critical target of maternal
HFD^[207]8,[208]42,[209]81,[210]82. To understand why males are more
sensitive to the maternal HFD exposure than females in adulthood, and
how the early postnatal hypothalamic transcriptomic landscape is
altered in response to the maternal diet is an important goal. The
diversity of neuronal and non-neuronal cell subpopulations and states
has enabled the identification of the cellular heterogeneity of rare
and/or transitory cell types and statuses. We captured all the major
cell types that were observed in other single cell atlases of adult
murine hypothalamus^[211]44,[212]46–[213]55,[214]57,[215]58 and
identified 30 neuronal subpopulations across the different regions in
the hypothalamus. Although the key cell populations were similar
between maternal HFD and LFD groups, there was an expansion in the
numbers of Hdc, AgRP and Avp/Rorb neurons in mHFD groups when compared
with fHFD and/or mLFD groups. Histamine (HA) is a monoaminergic
neurotransmitter synthesized from L-histidine through histidine
decarboxylase (HDC)^[216]83. Hypothalamic neuronal HA has also been
shown to regulate feeding behavior and energy metabolism as a target of
leptin action in the brain^[217]84,[218]85. Hdc neurons are activated
by fasting^[219]34, and a small population of Hdc neurons is sensitive
to insulin-induced hypoglycemia^[220]86. Hypothalamic AgRP and POMC are
‘yin/yang’ master regulators that promote/inhibit food intake, previous
studies observed a higher ratio of AgRP/POMC expressing neurons in
offspring raised by mothers with maternal overnutrition during
pregnancy and/or lactation^[221]5,[222]8,[223]40,[224]41. AVP neurons
in the PVN region acutely inhibit food intake in mice^[225]87. Retinoic
acid receptor-related orphan receptor-β (RORβ) together with RORα
and/or RORγ regulate the transcription of Clock and Bmal1 in the
hypothalamic SCN^[226]88. Whereas the roles of AVP/Rorb neurons have
not been addressed previously. Lhx1 is essential for terminal
differentiation and function of the hypothalamic SCN, the key regulator
of light-entrained cicadian rhythms that spontaneously synchronize
circadian clocks^[227]89,[228]90. These neurons are functionally
categorized to glucose and energy homeostasis, insulin signaling,
feeding behavior and circadian rhythm related cellular pathways by our
GO enrichment pathway analyses. The expanding of these neurons in mHFD
groups indicates that male offspring are more sensitive in response to
the maternal programming when exposed under the same maternal HFD
during lactation by changing the proportions of multiple neuronal
subpopulations, which might contribute to the increased susceptibility
to adiposity in later life.
Hypothalamic astrocytes are particularly affected by high caloric
diets. Astrocytes located in the ARC altered morphologically in
response to a high caloric diet, affecting their physical interactions
with neurons and blood vessels in mice^[229]91, and exhibited
distinctive temporal high caloric diet-induced transcriptomic
modifications^[230]92. We observed increased cell-cell interactions
between AgRP/Npy neurons and astrocytes in the offspring raised by
mothers exposed to HFD exposure. The altered physical interactions of
astrocytes-AgRP/Npy neurons together with expanded AgRP/Npy populations
in male offspring under maternal HFD programming might be important in
increasing their susceptibility for developing obesity at adulthood.
Genome-wide association studies (GWAS) in large cohorts have identified
about more than two thousand loci linked to body mass index (BMI), a
trait that is often used as a proxy for obesity^[231]93–[232]95. The
majority of the variants identified by GWAS are enriched in
neurodevelopment^[233]96–[234]98. NEGR1 is one of the top genes
associated with BMI by GWAS^[235]27,[236]99,[237]100. NEGR1 is a cell
surface molecule extensively found in the brain, and involved centrally
in synaptogenesis, neurite outgrowth and cell-cell
adhesion^[238]101, also plays a role in brain
connectivity^[239]102,[240]103, an important process in
obesity^[241]104. Through cell-cell interaction analysis, we observed
that outgoing and incoming signals of the NEGR pathway were highly
enriched in obesity relevant cell subpopulations such as Lhx1, Nr5a1
and Sst in offspring from maternal HFD groups which further highlighted
the higher chance of developing obesity and related metabolic disorders
in offspring raised by mothers fed HFD.
In summary, our study reveals the key lineages of the postnatal
hypothalamus at peak lactation under maternal dietary fat exposure
during lactation and links together alterations in the metabolic
phenotype of male and female offspring with the corresponding
hypothalamic cellular subpopulation expansions and cell-cell
interactions. We observed transcriptional variations across cell
subpopulations among different maternal dietary fat groups, which were
consistent with male offspring being more sensitive to maternal diet.
These results revealed the sex-specific effect in response to maternal
over-nutrition at early life at single cell resolution. We further
built a web portal ([242]https://mouse10x.shinyapps.io/p15atlas/) to
enable the users to explore the genes of interest, which would be of
great value to the scientific community concerned with maternal obesity
or maternal overnutrition and their effects on early life development
in offspring. It would also expand the knowledge of existing resources
of murine hypothalamic single cell atlas. Although we observed a
sexually dimorphic response of offspring to maternal high fat diet
combined with physiological and single nucleus transcriptomics
analyses, further studies are needed to include a wider time window
including puberty, adult and aging as well as a larger sample size of
individuals to address the detailed mechanisms of when and how the male
and female offspring diverge in response to maternal over-nutrition at
the single cell level and the effect on the adulthood. Additionally,
the experimental validation for the expansion of other key neuronal
subpopulations such as Avp/Rorb and Hdc is needed in separate studies.
Furthermore, in this study we only fed the mothers diets with two fat
contents (45% and 10%), more dedicated dietary design (such as dietary
fat composition, low fat high sucrose diet etc) is required in
the future to address the specific components in the maternal diet
affecting sex dimorphic manner.
Methods
Ethical statement
All animal procedures were reviewed and approved by the animal ethical
panel at Institute of Genetics and Developmental Biology, Chinese
Academy of Sciences (approval number: AP2020001).
Mice
C57BL/6 N mice were purchased at 5 weeks old from Charles Rivers,
Beijing and acclimated to the SPF facility before starting the
baseline. Npy-hrGFP (#006417) with a C57BL/6J background was obtained
from Jackson Laboratory and maintained at the facility afterwards.
Primers and PCR conditions for genotyping were followed by the protocol
of the Jackson lab. All animals were kept at 23 ± 1 °C with a
dark–light cycle of 12 h–12 h (lights on at 0730 h). Mice were fed a
standard low fat chow diet [crude fat ≥4% by weight, crude protein ≥20%
by weight (Huafukang Bioscience, Beijing, China)] before the baseline.
Female mice at 11 weeks of age were fed with LFD (10% fat by energy,
D12450B, Research Diets, New Brunswick, NJ, USA) for 2 weeks as the
baseline. Mice were mated at 13 weeks old and remained on LFD until
parturition. Female mice were then randomly allocated to LFD and HFD
(45% fat by energy, D12451, Research Diets, New Brunswick, USA) on
lactation day 1 (Fig. [243]1a). Litter sizes were manipulated to 6 at
lactation day 1 for all dams and recorded daily during lactation.
Female mice occasionally cull pups during lactation. We retained
litters with a litter size over 5. Mice were sacrificed by CO[2]
overdose before sample collection as well as at the end of experiment.
Final sample sizes of C57BL/6 N mice allocated to maternal LFD and HFD
were 9 and 6 for metabolic traits measurements. Final sample sizes of
Npy-hrGFP mice offspring included in immunohistochemistry validation
from fHFD group were 5, from fLFD group were 5, from mHFD group were 5,
from mLFD group were 4.
Metabolic phenotype measurements
Maternal BW and FI were measured daily during the whole experimental
period. Litter mass and pup mass were measured daily during lactation.
Total in vivo body fat and lean content of the females were evaluated
by magnetic resonance spectroscopy (EchoMRI, Houston, TX, USA) on the
day before mating, lactation days 1, 10 and 16. The total in vivo body
fat and lean content of the litters were also measured at lactation day
16. Feces produced by female mice during lactating days 13–15 were
collected, separated from the bedding manually, and oven-dried at 60 °C
to a constant mass (14 days). Samples of each diet were also weighed
and dried to a constant mass to obtain dry mass. The water content of
the diets was measured to correct the FI. The calorific values of feces
and diets were determined by a Parr 6400 Calorimeter (Parr Instrument
Company, Moline, IL, USA). Metabolizable energy intake (MEI) was
calculated as below^[244]79:
[MATH: MEI=(Mfood×GEfood)−(Mfeces×GEfeces)
:MATH]
where M[food] is the dry mass of FI in g day^−1, M[feces] is the dry
mass of feces produced in g day^−1, GE[Food] is the gross energy
content of the food (KJ g^−1) and GE[feces] is the gross energy lost in
feces (KJ g^−1).
The doubly labeled water (DLW) method^[245]105 was used to measure
daily energy expenditure (DEE) from the elimination rates of ^2H
(deuterium) and ^18O in lactating females during peak lactation (day
13–15). Measurements of DEE were made to determine the milk energy
output (MEO) from the difference between MEI and DEE^[246]106.
Individual mice were weighed to ±0.01 g using a balance (BSA2202S;
Sartorius, Göttingen, Germany) and labeled with an intraperitoneal
injection of approximately 0.1 g of water containing enriched ^2H (36.3
atoms%) and ^18O (59.9 atoms%). Syringes used to inject the DLW were
weighed (±0.001 g; JA2003N; Hangping, Shanghai, China) immediately
before and after the injection to provide an accurate measurement of
the amount of isotope injected. Mice were placed in their cages during
the 1 h equilibration period. An initial 30–80 μl blood sample was
collected from the orbit 1 h after the injection^[247]107. Blood
samples were immediately flame-sealed into pre-calibrated 100 μl
capillaries. A final blood sample was collected 48 h after the initial
blood sample to estimate isotope elimination rates. Samples of blood in
capillaries were vacuum-distilled^[248]108. A liquid water analyzer
(Los Gatos Research, Mountain View, CA, USA) was used to analyze the
isotope ratios of ^18O:^16O and ^2H:^1H. The samples were run alongside
a range of international and in-house standards that were used to
correct the raw data for daily machine variation. For each lactating
mouse, initial ^2H and ^18O dilution spaces were calculated by the
intercept method and then converted to mass, assuming a molecular mass
of body water of 18.02 and expressed as a percentage of body mass
before injection. The intercept method was used to estimate the body
water pool as this gives the best estimate compared with
desiccation^[249]109. The final ^2H and ^18O dilution spaces were
inferred from the final body mass, assuming the same percentage of body
mass as measured for the initial dilution space. For calculation of DEE
based on CO[2] production, single pool model^[250]110 was used as
recommended for small mammals^[251]111. Energy equivalents of rates of
CO[2] production were calculated using a conversion factor of
24.03 J ml^−1 CO[2], derived from the Weir equation^[252]112. Mice were
scarified at lactation day 16, one male pup and one female pup from
each litter were dissected. The brain, brown adipose tissue (BAT),
subcutaneous fat (SUB), mesenteric fat (MWAT), heart, liver, lungs,
kidneys, pancreas, stomach, spleen, small intestine, caecum, colon and
testes (only for male pups) were immediately dissected and weighed on
a ± 0.001 g balance (JA2003N; Hangping).
Single nucleus isolation
The dissociation protocol was revised based on the 10X Sample Prep
Demonstrated Protocol ([253]CG000124, Rev D). Briefly, male and female
pup brains at P15 were rapidly dissected between 9 and 12 am and the
hypothalamus was spooned out immediately and cut into tiny pieces in
HEB buffer (Hibernate A®, 2% B27®, 0.5 mM GlutaMAX^TM). Hypothalamus
pieces were then incubated in 2 ml pre-chilled lysis buffer (10 mM
Tris-HCl, 10 mM NaCl, 3 mM MgCl[2], and 0.1% Nonidet^TM P40 Substitute
in Nuclease-Free Water, 0.1 U/μl RNase Inhibitor) on ice for 15 min.
2 ml of HEB buffer were added to the lysed tissue and triturated the
tissue with a fire polished silanized Pasteur pipette 10–15 times.
After trituration, a 30 μm MACS® SmartStrainer was used to remove cell
debris and large clumps. The single nucleus suspension was centrifuged
at 400 g for 5 min at 4 °C and washed in a wash and resuspension buffer
(1X PBS with 1.0% BSA and 0.2 U/μl RNase Inhibitor). Subsequently, the
dissociated hypothalamic single nuclei were stained with Trypan Blue
(1:1) to evaluate the nuclei quality under a microscope. The nuclei
suspension concentration was determined by CountStar Rigel S2 (Alit
Biotech, Shanghai), once the target nuclei concentration of 300−600
nuclei/μl was obtained, proceed immediately with the 10x Genomics®
Single Cell Protocol.
Single-nucleus RNA-seq library preparation, sequencing and data
pre-processing
Single nucleus RNA-seq libraries were constructed using the 10x
Genomics® Chromium Single Cell Controller and the next GEM Single Cell
3’ Reagent Kit v3 (10x Genomics, USA) according to the user’s guide.
Nuclei suspensions were loaded on the Chromium Controller to generate
single nuclei gel beads in the emulsion (GEM). Captured nuclei were
lysed to release mRNA which was subsequently barcoded through reverse
transcription of individual GEMs. Using a thermo cycler (Eppendorf 6321
Mastercycler pro, Hamburg, Germany) to reverse transcribe, the GEMs
were programmed at 53 °C for 45 min, followed by 85 °C for 5 min, and
held at 4 °C. The cDNA library was then generated, amplified, and
assessed for quality control using the Agilent 4200. The single nucleus
RNA sequencing was further performed on the Illumina Novaseq 6000
sequencer. Raw data were processed with Cell Ranger (version 4.0.0)
with default parameters for each sample and mapped to the mm10-3.0.0
genome to generate unique molecular identifier (UMI) expression
matrices.
Quality control and integration of single nucleus transcriptomic data
Nuclei in which <200 or >6000 detected genes, <500 or >30000 UMIs, or
with more than 5% reads mapping to mitochondrial genes were removed.
SCTransform normalization (v2) in Seurat (4.1.0) was performed
separately for each sample. Subsequently, 3000 variable feature genes
were selected using the ‘SelectIntegrationFeatures’ function. PCs were
found with variable genes using the ‘RunPCA’ function, and the top 40
PCs were used for downstream analysis. We further integrated all the
samples using ‘PrepSCTIntegration’, ‘FindIntegrationAnchors’ and
‘IntegrateData ‘ functions to integrate individual samples as suggested
by Seurat tutorials.
Clustering and cell type annotation
Uniform Manifold Approximation and Projection (UMAP) analysis was
performed to further reduce variation to two dimensions with ‘RunUMAP’
function. These two UMAP dimensions were used to identify major
clusters with the ‘FindNeighbors’ and ‘FindClusters’ function at a
resolution of 0.1. Cell identities were determined by marker genes
generated from ‘FindAllMarkers’ function as well as the canonical
marker genes from published literature. For subclustering, neurons,
astrocytes, tanycytes and oligodendrocytes were subsetted and
subclustered respectively, AgRP, POMC and Avp/Rorb subclusters were
further subsetted on neuron subclusters. All the reclustering was done
using the above method with refined resolution.
Symphony analysis
Symphony is an efficient single cell reference atlas mapping
tool^[254]67. We build a Symphony reference using the hypoMap dataset.
We downloaded the hypoMap.rds file and extracted the expression matrix
(counts), metadata and UMAP embeddings. For reference building, we
chose the 2000 most variable genes and subsetted the dataset with the
variable genes, then ran PCA with 20 dimensions and calculated the
UMAP. To make use of the UMAP in original Seurat object and the query
dataset, we substituted the UMAP embeddings calculated by Symphony with
the one stored in the original Seurat object with the function
‘buildReference_on_UMAP’. For query mapping, we extracted the
expression matrix (counts), metadata from the query dataset, then we
mapped the query dataset on the reference dataset using the ‘mapQuery’
function in Symphony.
Differential abundance analysis (DAseq)
DAseq was adapted to compare the composition enrichment on the full
dataset as well as the neurons. Briefly, we extracted the meta.data
from the Seurat object and did a pair-wise comparison between fHFD
group with mHFD group, fHFD group with fLFD group, fLFD with mLFD group
and mHFD with mLFD group by including the replicates information in
labels.
Differential expressed genes (DEGs) analysis
To run differential gene expression analysis, we used normalized counts
that are stored in the data slot of the SCT assay. Prior to performing
differential expression, we first ran ‘PrepSCTFindMarker’ to set the
fixed value, followed by ‘FindMarkers’ function by “MAST” method
(assay = “SCT”, test.use = “MAST”, logfc.threshold = 0, min.pct = 0,
min.cells.feature = 1) to identify differentially expressed genes
between the comparisons of mHFD vs mLFD, fHFD vs fLFD, mLFD vs fLFD and
mHFD vs fHFD groups including the replicates. Genes with an adjusted P
value < 0.05 were considered as significant DEGs between groups based
on previous publications. Marker genes of each cell population were
determined by FindAllMarkers function (logfc.threshold = 0.25, assay =
“SCT”) with adjusted P value < 0.05.
Pathway enrichment analysis
Marker genes of each major cluster that identified by FindAllMarkers
function described above were used as the input to perform GO pathway
enrichment analysis using ‘enrichGO’ function from ClusterProlifier
(version 4.9.1^[255]113). All the significant DEGs between different
comparisons (mHFD vs mLFD, fHFD vs fLFD, mLFD vs fLFD and mHFD vs fHFD)
were also extracted by ‘Findmarker’ function described above,
significant DEGs were then fed to ‘enrichGO’ for GO^[256]114 enrichment
analysis.
Trajectory analysis
Monocle 3 was used to run the trajectory analysis on the astrocyte and
oligodendrocyte clusters. We first extracted the meta.data and
expression counts from Seurat object to build a monocle3 cds object. We
further substitute the umap embeddings and cluster information in the
monocle3 cds object with integrated Seurat object. We used
‘learn-graph’ for the trajectory analysis and ‘plot_cells’ to plot the
trajectory.
Cell-cell interaction analysis
Cellchat was used to profile the cellular interactions. We first
performed the cellular interaction analyses on the full dataset on the
key lineages and then included all the neuron subclusters on four
groups separately and then compared the cell-cell interactions.
Immunohistochemistry
Female and male NPY-hrGFP mice offspring raised by mothers fed HFD and
LFD during lactation were sacrificed on postnatal day15. Fresh brain
tissues were dissected and proceeded with perfusion. Brain samples were
immersed with 4% PFA overnight and treated with 30% sucrose solution at
4 °C for 48 h. Samples were then embedded with OCT and serially sliced
with a thickness of 30 μm and stored at −20 °C for further use. For
staining, brain sections were incubated with solution containing 5% BSA
(Bovine Serum Abumin) and 0.3% Triton for 1 h. S100 beta rabbit
monoclonal antibody was used as primary antibodies (AF1945, Beyotime)
(1:500) at 4 °C for 8−12 h. Goat anti-rabbit IgG antibody (Alexa Fluor®
647, ab150087, Abcam) (1:1000) was used as secondary antibody by
incubating the slides at room temperature for 1 h in the dark. Nuclei
were counterstained with Dapiprazole hydrochloride (DAPI) (D9542,
Sigma-Aldrich) (1:1000). After PBST washing for 3 times, the slides
were sealed with mounting solution. The fluorescence images were
acquired using confocal microscope (LSM980, Zeiss). Imaris (version
9.8.0) was applied for the cell counting and co-localization analysis.
It was used to locate different fluorescent labeled cells in the ARC
area of hypothalamus, all fluorescent signals were then automatically
adjusted by the threshold and manually labeled. We then set up a
certain area to normalize cell counting between different slides. After
the generation of spots, the cell numbers at different channels were
calculated, co-localization was determined by setting the distance
threshold of spots (10 μm).
Statistical analysis
BW and FI differences during baseline were measured using ANONA.
Repeated measures general linear models (RM GLM) during pregnancy and
lactation. Day is a repeated factor. Differences in BW, FI, litter/pup
mass and body composition during experiments were tested using RM GLM
with diet as the fixed factor, and day as the repeated factor. Body fat
and lean content of both mothers and weaned offspring were tested using
ANOVA with diet as a fixed factor. Changes in MEI, DEE and MEO between
dietary groups were compared using GLM with diet as fixed factor and BW
as a covariate^[257]115, interaction between the fixed factor and the
covariate was also tested. Organ morphology changes between dietary
groups were also conducted using GLM with diet as fixed factor and BW
as a covariate. If the result showed no significant effects while
including the interaction or covariate effect, the significance
analysis of the fixed factor was analysed individually. If found, the
effects by the interaction or covariate would be taken into
consideration. Imaging data were tested using t test. Data are
represented as means ± s.d. All data were tested for normality prior to
analysis. All statistical analyses were performed using IBM SPSS
Statistics for Macintosh (version 24).
Reporting summary
Further information on research design is available in the [258]Nature
Portfolio Reporting Summary linked to this article.
Supplementary information
[259]Supplementary Information^ (21MB, pdf)
[260]Peer Review File^ (766.4KB, pdf)
[261]41467_2024_46589_MOESM3_ESM.pdf^ (48.7KB, pdf)
Description of Additional Supplementary Information
[262]Supplementary Data 1^ (19.8KB, xlsx)
[263]Supplementary Data 2^ (10.5KB, xlsx)
[264]Supplementary Data 3^ (12.2KB, xlsx)
[265]Supplementary Data 4^ (1.2MB, xlsx)
[266]Supplementary Data 5^ (2.2MB, xlsx)
[267]Supplementary Data 6^ (2.3MB, xlsx)
[268]Reporting Summary^ (3MB, pdf)
Source data
[269]Source Data^ (42.2KB, xlsx)
Acknowledgements