Neonatal nutritional programming induces gliosis and alters the expression of T-cell protein tyrosine phosphatase and connexins in male rats

Hormones and Behavior 120 (2020) 104690

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Neonatal nutritional programming induces gliosis and alters the expression of T-cell protein tyrosine phosphatase and connexins in male rats

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Lucas Kniess Debarba , Paula Beatriz Marangon, Beatriz C. Borges, Hellen Veida-Silva, Jade Cabestre Venâncio, Gislaine Almeida-Pereira, José Antunes-Rodrigues, Lucila Leico Kagohara Elias Department of Physiology, Ribeirao Preto Medical School, University of Sao Paulo, Sao Paulo, Brazil. 14049-900

A R T I C LE I N FO

A B S T R A C T

Keywords: Nutritional programming Hypothalamus Glia TCPTP CX30 CX43

Changes to neonatal nutrition result in long-lasting impairments in energy balance, which may be described as metabolic programing. Astrocytes, which are interconnected by gap junctions, have emerged as important players in the hypothalamic control of food intake. In order to study the effects of nutritional programming on glial morphology and protein expression, cross-fostered male Wistar rats at postnatal day 3 were assigned to three groups based on litter size: small litter (3 pups per dam, SL), normal litter (10 pups per dam, NL), and large litter (16 pups per dam, LL). Rats from the SL group exhibited higher body weight throughout the study and hyperphagia after weaning. LL animals exhibited hyperphagia, high energy efficiency and catch-up of body weight after weaning. Both the SL and LL groups at postnatal day 60 (PN60) exhibited increased levels of plasma leptin, the Lee index (as an index of obesity), adiposity content, immunoreactivity toward T-cell protein tyrosine phosphatase (TCPTP), and glial fibrillary acidic protein (GFAP) in the arcuate nucleus (ARC) of the hypothalamus. Astrocyte morphology was altered in the ARC of SL and LL animals, and this effect occurred in parallel with a reduction in immunoreactivity toward connexin 30 (CX30). The data obtained demonstrate that both neonatal over- and underfeeding promote not only alterations in the metabolic status but also morphological changes in glial cells in parallel with increasing TCPTP and changes in connexin expression.

1. Introduction The prevalence of overweight and obesity is noticeable worldwide, impacting 39% of adults aged 18 years or older who were overweight in 2016. The number of overweight or obese infants and young children (aged 0 to 5 years) increased from 32 million globally in 1990 to 41 million in 2016 (World Health Organization, 2016). Nutritional changes during a critical neonatal window have been shown to affect neurodevelopment and to program long-lasting metabolic alterations, such as diabetes, glucose intolerance, obesity, and hyperlipidemia (Harding, 2001; De Boo and Harding, 2006). The epidemiological study from the Dutch Famine (1944–1945) demonstrated that food restriction during pregnancy led to low weight at birth associated with hypertension, obesity, and type two diabetes later in life (Ravelli et al., 1976; Roseboom et al., 2001). Early life nutritional insults with a high risk of hypertension and impaired glucose tolerance in adult life inspired the development of the Barker hypothesis and the concept of the developmental origin of health and disease (Hales et al., 1991; Hanson

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and Gluckman, 2014). On the other hand, maternal obesity has been shown to be related to the prevalence of adiposity in children and adult offspring (Gaillard, 2015). Therefore, both a paucity and excess of nutrients during prenatal and perinatal life can increase the risk of obesity and metabolic alterations in adult humans. As one of the experimental models of undernutrition or overnutrition during the neonatal period, manipulation of litter size in rodents during lactation has been used (Remmers et al., 2008; Glavas et al., 2010; Zhang et al., 2011; Liu et al., 2013). Offspring raised in large litters show reduced weight gain during lactation with growth catch-up and hyperphagia after weaning (Remmers et al., 2008). Conversely, offspring raised in small litters presented increased susceptibility to obesity and hypothalamic leptin resistance (Glavas et al., 2010; Zhang et al., 2011; Rodrigues et al., 2011; Liu et al., 2013). The neonatal period is critical for “programming” the hypothalamus and increasing the later risk of obesity and related metabolic dysfunction (Dearden and Ozanne, 2015; Vogt et al., 2014). Rat neurodevelopment continues after birth and beyond weaning until multipotent

Corresponding author at: Avenida Bandeirantes, 3900 Ribeirao Preto Medical School, University of Sao Paulo, 14049-900 Ribeirao Preto, SP, Brazil. E-mail address: [email protected] (L.K. Debarba).

https://doi.org/10.1016/j.yhbeh.2020.104690 Received 14 July 2019; Received in revised form 20 December 2019; Accepted 12 January 2020 0018-506X/ © 2020 Elsevier Inc. All rights reserved.

Hormones and Behavior 120 (2020) 104690

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as a litter. The body weight during lactation was determined by the average body weight of a pup in a given litter (litter weight/total number of pups). At PN21, the pups were weaned and maintained in cages with 5 animals from the same experimental group. Individual body weight was measured every 5 days until PN60. Between PN50 and PN60, rats were placed in individual cages for measurement of daily food intake. The parameters obtained during this period were (1) food intake (g) and energy intake (kcal); and (2) energy efficiency (body weight gain/kcal intake). At PN21 and PN60, one set of rats was euthanized by decapitation for plasma and brain collection under RNAsefree conditions. Epididymal, retroperitoneal, and perirenal fat pads were collected and weighed to assess adiposity at PN60. The Lee index, a predictor of obesity (Lee, 1929), was calculated using the formula [(body weight)1/3/ (nasoanal length)], with body weight in grams and length in centimeters. Another set of rats at PN21 and PN60 was anesthetized with 2.5% tribromoethanol (1 mL/100 g body weight i.p.) and perfused through the heart with 150 mL of 0.01 M phosphate buffered saline (PBS) followed by 350 mL of 4% paraformaldehyde in 0.1 M phosphate buffer. Brains were collected, postfixed in the same fixative for 1 h, placed in PBS containing 30% sucrose, embedded in OCT and sliced at 30 μm on a cryostat for immunostaining.

neural stem cells differentiate into neurons and glial cells and achieve mature neural networks and adult patterns of myelination and brain function (Grandbarbe et al., 2003; Grove et al., 2005; Miller and Gauthier, 2007; Semple et al., 2013). The role of glial cells in neurogenesis, synaptogenesis, and neuronal function has been well recognized (Haydon and Carmignoto, 2006; Remmers et al., 2008; Li et al., 2012, Miller and Spencer, 2014). Obesity-related neuroinflammation has been attributed to the excessive production of IKKβ/ NF-kB-dependent cytokines such as TNF-α and IL-1β from microglial cells (Li et al., 2012). Recently, IKKβ/NF-kB signaling in astrocytes was shown to be required for astrogliosis and hypothalamic inflammation induced by a high-fat diet (HFD) (Douglass et al., 2017). Glial cells have been implicated in the development of leptin and insulin resistance in the hypothalamus (Jayaram et al., 2013; Djogo et al., 2016; Douglass et al., 2017). The demonstration of expression of leptin receptors (LepRs) in hypothalamic astrocytes raised the idea that this metabolic cue might play a role in astrocyte morphology (García-Cáceres et al., 2011; Kim et al., 2014), proliferation (Rottkamp et al., 2015), synaptic modulation of hypothalamic neurons and the control of feeding (Kim et al., 2014). Obesity and leptin resistance induced by a HFD have been linked to increased levels of T-cell protein tyrosine phosphatase (TCPTP), encoded by the Ptpn2 gene, in the hypothalamus (Loh et al., 2011). TCPTP counter-regulates the leptin effects on body weight and food intake (Dodd et al., 2019). We have recently demonstrated that leptin treatment changes astrocyte morphology in vitro and that this effect was associated with increased expression of TCPTP (Debarba et al., 2019). In vitro studies have shown that TCPTP regulates the expression of connexins in the membranes of renal cells (Li et al., 2014) and astrocytes (Debarba et al., 2019). Connexins 43 (CX43) and 30 (CX30) are known to play a role in the gap junctions of the astrocyte network and astrocyte morphology (Clasadonte and Haydon, 2014; Pannasch et al., 2014; Ghézali et al., 2018; Debarba et al., 2019). Connexins are believed to have a role in the proliferation of hypothalamic cells (Recabal et al., 2018) and in the control of glucose metabolism and insulin secretion/sensitivity (Allard et al., 2014) and HFD-induced obesity (Sasaki et al., 2018). Therefore, understanding how nutritional programming modulates TCPTP and connexins to favor gliosis during energy imbalance is of great relevance. In this study, we hypothesized that changes in neonatal nutrition promote gliosis in the hypothalamus, and this effect might be associated with the upregulation of TCPTP expression and changes in the expression of connexins.

2.2. Hypothalamic microdissection Using a stainless-steel punch needle with a 1.5-mm diameter, microdissections (1500 μm) of the ARC were obtained in a cryostat according to the coordinates −2.3 to −3.5 mm from bregma according to the Paxinos and Watson Atlas (Paxinos and Watson, 1997). Samples were transferred to microtubes with the RNAlater reagent (Ambion, #AM7020) and stored at −80 °C for a maximum of 24 h until use for RNA isolation, as described below. 2.3. Hormone measurement Blood samples were collected in tubes with heparin [20 UI/mL] at PN21 and PN60 from rats fasted for 16 h (overnight) and centrifuged at 3000 rpm for 20 min at 4 °C. Plasma was stored at −20 °C until use for the assays. Plasma leptin and insulin levels were determined in duplicate by commercial ELISA kits (Edm Millipore Corporation, #EZRL83 K and #EZRMI-13 K, respectively). The sensitivities of the leptin and insulin assays were 0.04 ng/mL and 0.2 ng/mL, respectively. 2.4. Western blotting

2. Materials and methods Hypothalamic fragments were dissected out (thickness: 2.7 mm) from an area 1.0 mm lateral to the midline at the anterior border of the optic chiasm and the anterior border of the mammillary bodies. Tissue was homogenized using micropestle mechanical dissociation. Total hypothalamic protein was extracted using 100 mM Tris-HCl [pH 7.4], 1% Triton-X 100, 2 mM EDTA solution, and an EDTA-free 1% halt protease and phosphatase inhibitor cocktail [Thermo Scientific, #78443], pH 7.2. Samples were centrifuged at 15,000 g for 50 min at 4 °C. Aliquots of the lysates containing 30 μg of protein were denatured in Laemmli sample buffer, pH 6.8 (4% SDS, 20% glycerol, 0.02% bromophenol blue, Tris 1 M [pH 6.8], and DTT 0.1 M) at 95 °C for 5 min. The samples were blotted onto nitrocellulose membranes. Nonspecific binding was prevented by immersing the membranes in a blocking buffer (5% nonfat dry milk in Tris-buffered saline-Tween [TBS-T]) for one hour at room temperature. The membranes were then exposed overnight to the primary antibody rabbit anti-TCPTP [1:3000] (Abcam, #AB180764; RRID: AB_2722704) or rabbit anti- b-Actin (13E5) [1:40,000] (Cell Signaling, #7970; RRID: AB_2223172). The blots were rinsed in TBS-T and then incubated with horseradish peroxidase-conjugated anti-rabbit-IgG antibody [1:10,000] (Cell Signaling, #CST7074; RRID: AB_2099233) for one hour at room temperature. Antibody-antigen complexes were visualized by detecting enhanced

2.1. Neonatal nutritional programming We received the Wistar rat dams with one-day-old male pups from the Central Animal Facility of the University of Sao Paulo, Campus of Ribeirao Preto, Brazil. The rats were maintained under controlled temperature (23 ± 1 °C), a 12-h light/dark cycle (lights on at 6:00 AM), and water and food ad libitum (Quimtia Nuvilab®. 3.86 kcal/ g; 4% lipid, 22% protein and 60% carbohydrate). All experiments were approved by the Ethics Committee for Animal Use of the Ribeirao Preto Medical School (N. 53/2013). Three days after birth, pups were divided according to litter size per dam: 3 pups (small litter - SL), 10 pups (normal litter - NL), or 16 pups (large litter - LL) (Remmers et al., 2008; Glavas et al., 2010). Considering the genetic variability, each protocol was composed of animals from different dams. Therefore, animals from each dam were split into different protocols at PN21 and PN60. In every experiment, n = 7–18 from 7 to 17 different progenitors were used in each experimental group, and a total of 200 rats were used. Cross-fostering was employed to obtain litters of only males. Only males were used to avoid metabolic differences triggered by the estrous cycle in females. From postnatal day 3 (PN3) to postnatal day 21 (PN21), all pups were weighed together 2

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blocking buffer (Tris, normal horse serum, and Triton X-100) for one hour at room temperature. The sections were incubated for 48 h at 4 °C with one of the following primary antibodies: rabbit anti-IBA1 [1:5000] (Wako, #01919741; RRID:AB_839504) or rabbit anti-GFAP [1:4000]. After being rinsed, the sections were incubated for one hour with biotinylated goat anti-rabbit secondary antibody [1:200] (Vector, #BA1000) and then processed using the Vectastain Elite avidin-biotin immunoperoxidase method (Vector Laboratories). Solutions of diaminobenzidine, nickel sulfate, and H2O2 were used to generate blue-black immunolabeling. Negative controls were included in both immunofluorescence and immunohistochemistry procedures by omitting the primary antibodies.

chemiluminescence using an ECL detection system (Amersham Biosciences, #RPN2232) and digital images with Quantity One 4.5.0 software (Bio-Rad). The expression of TCPTP was normalized to the expression of b-Actin (endogenous control) for each sample. 2.5. Total RNA isolation and quantitative real-time PCR Total RNA was isolated from each sample using TRIzol reagent (Invitrogen, #15596018), and sterile micropestles were used for mechanical homogenization of tissues. The concentration of 500 ng of RNA was used for cDNA synthesis using a High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, #4368814). Samples processed with the omission of the transcriptase reverse enzyme were used as the negative control for contaminating DNA detection. Quantitative realtime PCR was performed using the Applied Biosystems 7500 Real-Time PCR System. The following TaqMan Gene Expression Assays (Applied Biosystems) were used in this study: Rn01423685_m1 (Ptpn1 - PTP1B); Rn00588846_m1 (Ptpn2 - TCPTP); Rn00584528_m1 (Gjb6 - CX30); Rn01433957_m1 (Gja1 CX43); Rn01410330_m1 (Il6); Rn00580432_m1 (Il1b); Rn99999017_m1 (Tnf); and 4352340E (Actb ß-actin). Each PCR reaction was performed in triplicate. Water instead of cDNA was used as a negative control, and the housekeeping gene, ßactin, was measured in each cDNA sample. Gene transcripts in each sample were determined by the ΔΔCT method. For each sample, the threshold cycle (CT) was measured and normalized to the average of the housekeeping gene (ΔCT = CT gene of interest - CT housekeeping gene). The fold change of mRNA in the unknown sample relative to the control group was determined by 2-ΔΔCT, where ΔΔCT = ΔCT treatment group - ΔCT control group. Data are shown as mRNA expression levels relative to the NL group (control).

2.7. Image processing Immunofluorescence images were taken using a multiphoton laserscanning microscope (LSM 780 AxioObserver, ZEISS) equipped with a 63× objective for hypothalamic tissue. Stacks of consecutive images taken at 0.4-μm intervals were sequentially acquired, and 35 optical sectioning, along the optical axis (z-axis), were reconstructed using FijiImageJ. Measurements of the immunofluorescence intensity (TCPTP, CX30, CX43, GFAP and IBA1) and soma size were analyzed using FijiImageJ software. Measurements of process extensions were analyzed using the Sample Neurite Tracer of Fiji-ImageJ software (Pool et al., 2008; Longair et al., 2011). The colocalization of TCPTP, CX30, CX43 and GFAP or IBA1 was examined in the ARC by calculating Manders colocalization coefficient (Manders et al., 1993) using Fiji-ImageJ software. This coefficient has been widely used in microscopic analyses and provides an objective metric for most biological colocalization studies (Dunn et al., 2011). The Manders coefficient ranges from zero to one, and it is independent of the pixel intensity in individual channels (Zinchuk and Grossenbacher-Zinchuk, 2009). A constant area at a similar hypothalamic level was used to calculate the Manders colocalization coefficient, M1, for channel one. The Manders M1 coefficient represents the fraction of green fluorescence (TCPTP, CX30, CX43) that overlapped spatially with the immunostaining for IBA1 or GFAP, representing the colocalization of TCPTP/GFAP, CX30/GFAP and CX43/ GFAP or TCPTP/IBA1, CX30/IBA1 and CX43/IBA1. Immunohistochemistry images were captured using a Leica microscope equipped with a DC 200 digital camera attached to a contrast enhancement device. The number of immunoreactive-positive cells of all sections in the series per rat (three sections) was obtained by counting the microglia or astrocyte staining from a constant area of the ARC, VMH, DMH, PVN, CA3, and DG using Fiji-ImageJ software.

2.6. Immunofluorescence and immunohistochemistry Coronal brain sections were sliced according to the coordinates from the Paxinos and Watson Atlas (Paxinos and Watson, 1998), where the ARC, ventromedial hypothalamic nucleus (VMH), dorsomedial hypothalamic nucleus (DMH) and hippocampus were − 2.3 to −3.5 mm and the paraventricular nucleus (PVN) was −0.92 mm to −2.12 mm from bregma. Sections were sliced at a thickness of 30 μm and preserved in cryoprotectant at −20 °C. One in every three sections was used for immunofluorescence staining. Sections were rinsed with Tris buffer and incubated for 48 h at 4 °C with one of the following primary antibodies: rabbit anti-TCPTP [1:500] (Abcam, #AB180764; RRID: AB_2722704), rabbit anti-connexin 30 [1:500] (Life Technologies; #712200 RRID:AB_2533979), mouse anti-connexin 43 [1:500] (Pharmingen #610062; RRID:AB_ 397474); goat anti-IBA1 (ionized calcium binding adaptor molecule 1) [1:1000] (Abcam #AB5076; RRID:AB_2224402), a positive marker of microglia cells; mouse anti-GFAP [1:400] (Sigma, G3893; RRID:AB_ 477010), a positive marker of astrocytes; or rabbit anti-GFAP [1400] (Sigma, #G9269; RRID:AB_477035). After rinsing, the following secondary antibodies were used for a 1-h incubation at room temperature: donkey anti-rabbit IgG conjugated to Alexa Fluor 488 (#A21206; RRID:AB_141708); donkey anti-goat IgG conjugated to Alexa Fluor 488 (#A11055; RRID:AB_142672) from Molecular Probes; donkey antimouse IgG conjugated to Alexa Fluor 594 (#715587003; RRID:AB_ 2340859); donkey anti-rabbit IgG conjugated to Alexa Fluor 594 (#711585152; RRID:AB_2340621); donkey anti-mouse IgG conjugated to Alexa Fluor 647 (#715605151; RRID:AB_2340863); or biotinylated donkey anti-goat IgG (#705065147; RRID:AB_2340397) from Jackson Immunoresearch with streptavidin-Alexa Fluor 350-Tyramide, buffered with H2O2 (Life Technologies, #T20935). Tissue was mounted on slides and coverslipped for imaging analysis. For the immunohistochemistry, the sections were rinsed with Tris buffer, followed by 10% H2O2 in methanol for 10 min. After rinsing, nonspecific binding was prevented by immersing the sections in

2.8. Statistical analysis The results are expressed as the mean ± standard error and were analyzed using Statistica software (version 10). An analysis of variance (ANOVA) with repeated measurements was used to analyze body weight and food intake. One-way ANOVA analysis was used for other parameters. The Newman-Keuls test was used as a post hoc test, and the level of significance (α) was set at 5%. 3. Results 3.1. Effects of litter size on body weight gain and food intake At PN7 (Newman-Keuls test: p < 0.046), PN14 (Newman-Keuls test: p < 0.0001) and PN21 (Newman-Keuls test: p < 0.0001), the SL group showed an increase in body weight gain compared to the NL group, whereas the LL group showed a decrease (Fig. 1A; RM ANOVA main effect of days: F4.116 = 907.58, p < 0.0001, η2 = 0.771; main effect of litter size: F2.29 = 35.82, p < 0.0001, η2 = 0.71; and litter size x time interaction F8.116 = 51.29, p < 0.0001, η2 = 0.087). After weaning, the SL (Newman-Keuls test: p < 0.0001) group showed an 3

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Fig. 1. The litter size affects the metabolic parameters. (A) pre-weaning body weight – grams (g); n = 8–18; (B) post-weaning body weight (g) (repeated measures ANOVA followed by Newman–Keuls test); (C) post-weaning overall weight gain (g) (D) cumulative food intake (g) and (E) cumulative energy efficiency (g/kcal) from PN50 to PN60, n = 16–25 (One way ANOVA followed by Newman–Keuls test); Data shown the groups small litter (SL), normal litter (NL), and large litter (LL). Data are expressed as the mean ± SEM. *p < 0.05 vs NL group.

increase in body weight gain between PN21 and PN60 compared to the NL group (Fig. 1B; RM ANOVA main effect of days: F8.424 = 1501.93, p < 0.0001, η2 = 0.887; main effect of litter size: F2.53 = 95.03, p < 0.0001, ηp2 = 0.059; and litter size x time interaction F16.424 = 4.92, p < 0.0001, η2 = 0.006). At PN21 (Newman-Keuls test: p < 0.040), PN25 (Newman-Keuls test: p < 0.014), and PN30 (Newman-Keuls test: p < 0.017), the LL group showed lower body weight gain compared to that of the NL group (Fig. 1B); however, after this period, the LL group showed similar body weight gain compared to that of the NL group. A higher overall weight gain (PN21- PN60) was observed (Fig. 1C; one-way ANOVA: F2.47 = 12.91, p < 0.0001, η2 = 0.355) only in the SL (Newman-Keuls test: p < 0.0001) when compared to that of the NL group. Both the SL and LL groups had an increase in cumulative food intake (Fig. 1D; one-way ANOVA: F2.32 = 25.001, p < 0.0001, η2 = 0.610). In turn, the energy efficiency was higher (Newman-Keuls test: p < 0.001) only in the LL group when compared to that of the NL group (Fig. 1E; one-way ANOVA: F2.33 = 9.06, p < 0.0007, η2 = 0.355). The SL and LL groups showed a higher Lee index (one-way ANOVA: F2.27 = 13.48, p < 0.0001, η2 = 0.500; SL and LL x NL: Newman-Keuls test: p = 0.0003), and epididymal (one-way ANOVA: F2.29 = 11.33, p < 0.0002, η2 = 0.439; Newman-Keuls test: SL x NL: p < 0.034; LL x NL: p < 0.0002), retroperitoneal (one-way ANOVA: F2.29 = 6.41, p < 0.005, η2 = 0.310; Newman-Keuls test: SL x NL: p < 0.021; LL x NL: p < 0.004), and perirenal fat pads (one-way ANOVA: F2.29 = 6.94, p < 0.003, η2 = 0.323; Newman-Keuls test: SL x NL p < 0.024; LL x NL: p < 0.002) compared to those of the NL group. No difference was observed in the content of brown adipose tissue (Table 1). There was a reduction in the nasal-anal length in the LL group compared to that of the NL group (one-way ANOVA: F2.26 = 12.351, p < 0.0001, η2 = 0.487); (Newman-Keuls test: p < 0.001).

Table 1 Effects of litter size on body composition at PN60. SL Lee index Nasal-anal length (cm) Epididymal fat pad (g/ 100 g bw) Retroperitoneal fat pad (g/ 100 g bw) Perirenal fat pad (g/100 g bw) Brown adipose tissue (g/ 100 g bw)

NL

LL

0.33 ± 0.04 24.01 ± 0.6 1.8 ± 0.2⁎

0.28 ± 0.01 24.4 ± 0.6 1.3 ± 0.1

0.33 ± 0.002⁎ 21.1 ± 0.4⁎ 2.3 ± 0.1⁎

2.3 ± 0.2⁎

1.6 ± 0.2

2.7 ± 0.2⁎

0.4 ± 0.02⁎ 0.1 ± 0.01

0.3 ± 0.04 0.1 ± 0.09

0.5 ± 0.07⁎ 0.1 ± 0.1

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Data are expressed as the mean ± SEM. One-way ANOVA followed by Newman–Keuls test. ⁎ p < 0.05 vs NL group, n = 10–12 rats.

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3.2. Effects of litter size on plasma leptin and insulin concentrations At PN21, the SL group showed an increase in the plasma 4

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η2 = 0.295; Newman-Keuls test: SL x NL: p < 0.027 and LL x NL: p < 0.050).

concentrations of leptin (Fig. 2A; one-way ANOVA: F2.17 = 18.54, p < 0.0001, η2 = 0.686; Newman-Keuls test: SL x NL: p < 0.006) and insulin (Fig. 2B; one-way ANOVA: F2.17 = 10.72 p < 0.001, η2 = 0.558; Newman-Keuls test: SL x NL: p < 0.008) compared to both the NL and LL groups. Conversely, the LL group had a decrease in plasma leptin concentration compared to that of the NL group (Newman-Keuls test: p < 0.007). At PN60, there was an increase in the plasma concentrations of leptin (one-way ANOVA: F2.17 = 5.34, p < 0.015, η2 = 0.385; Newman-Keuls test: SL x NL: p < 0.017; LL x NL: p < 0.039) and insulin (one-way ANOVA: F2.16 = 11.62, p < 0.001, η2 = 0.592; Newman-Keuls test: SL and LL x NL: p < 0.001) in both the SL and LL groups compared to levels in the NL group.

3.4. Effects of litter size on Ptpn1 and Ptpn2 gene expression in the ARC and TCPTP protein expression in the MBH Because in previous in vitro studies astrocyte morphology was affected by protein tyrosine phosphatase nonreceptor type 2 (Ptpn2) expression, we decided to evaluate the expression of this gene in rats under litter size manipulation. The litter size did not affect Ptpn1 mRNA expression in the ARC at PN21 or PN60 (Fig. 3D). However, at PN21, the SL group showed an increase in Ptpn2 mRNA expression (one-way ANOVA: F2.15 = 5.34, p < 0.018, η2 = 0.415; Newman-Keuls test: SL x NL: p < 0.014) and TCPTP protein expression (Fig. 3 F; one-way ANOVA: F2.17 = 3.72, p < 0.045, η2 = 0.305; Newman-Keuls test: SL x NL: p < 0.037) compared to expression in the NL group. At PN60, both the SL and LL groups showed an increase in Ptpn2 mRNA (Fig. 3E; oneway ANOVA: F2.24 = 9.46, p < 0.001, η2 = 0.440; Newman-Keuls test: SL x NL p < 0.001 and LL x NL: p < 0.014) and TCPTP protein (oneway ANOVA: F2.12 = 4.45, p < 0.036, η2 = 0.426; Newman-Keuls test: SL x NL p < 0.047 and LL x NL: p < 0.031) expression compared to that in the NL group.

3.3. Effects of litter size on proinflammatory cytokine gene expression in the ARC The litter size did not affect the mRNA expression of interleukin-6 (Il6) in the ARC at PN21 or PN60 (Fig. 3A). At PN21, both the SL and LL groups showed an increase in interleukin-1 beta (Il1b) mRNA expression compared to expression in the NL group (Fig. 3B; one-way ANOVA: F2.24 = 4.95, p < 0.016, η2 = 0.292; Newman-Keuls test: SL x NL: p < 0.017 and LL x NL: p < 0.030). However, at PN60, only the LL group showed an increase in Il1b mRNA expression compared to that of the NL group (one-way ANOVA: F2.21 = 6.24, p < 0.007, η2 = 0.373; Newman-Keuls test: LL x NL: p < 0.017). At PN21, the mRNA expression of tumor necrosis factor (Tnf) in the ARC was not different between groups (Fig. 3C). However, at PN60, both the SL and LL groups showed an increase (p < 0.05) in Tnf mRNA expression compared to that of the NL group (one-way ANOVA: F2.21 = 3.39, p < 0.025,

3.5. Effects of litter size on TCPTP, GFAP, and IBA1 immunoreactivity in the ARC of juvenile and adult rats At PN21, the SL group showed increased immunoreactivity toward TCPTP (Fig. 4A and Supplemental Fig. 1; one-way ANOVA: F2.27 = 53.30, p < 0.001, η2 = 0.798; Newman-Keuls test: SL x NL: p < 0.001), GFAP (Fig. 4B and Supplemental Fig. 2; one-way ANOVA: 5

Hormones and Behavior 120 (2020) 104690

TCPTP GFAP

( A v e r a g e p ix e l in t e n s it y )

D

ARC – PN60 A SL 40

NL *

3V

LL *

30 20

*

TCPTP

10 0

PN21

PN60

GFAP

B 100

( A v e r a g e p ix e l in t e n s it y )

IB A 1

( A v e r a g e p ix e l in t e n s it y )

L.K. Debarba, et al.

*

80

*

60 40

*

20

IBA1

0

PN21

PN60

C

Merge

20 15 10

*

*

*

*

5 0

PN21

PN60

SL

NL

LL

Fig. 4. The litter size promotes gliosis in the ARC. (A) TCPTP; (B) GFAP (C) and IBA1 average pixel intensity in the ARC of the SL, NL and LL groups at PN21 and PN60, n = 10. Data are expressed as the mean ± SEM. One way ANOVA followed by Newman–Keuls test. *p < 0.05 vs NL group. Representative photomicrographs (D) of the triple immunofluorescence for TCPTP (green), GFAP (red) for astrocytes and IBA1 (blue) for microglia in the ARC at PN60. ARC scale: 200 μm; TCPTP, GFAP and IBA1 scale: 25 μm. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

F2.27 = 19.19, p < 0.001, η2 = 0.587; Newman-Keuls test: SL x NL: p < 0.001), and IBA1 (Fig. 4C and Supplemental Fig. 3; one-way ANOVA: F2.27 = 29.30, p < 0.001, η2 = 0.684; Newman-Keuls test: SL x NL: p < 0.001), compared to that of the NL group. Conversely, at PN21, the LL group showed a decrease in IBA1 immunoreactivity compared to that of the NL group (Newman-Keuls test: LL x NL: p < 0.020). At PN60, both the SL and LL (Newman-Keuls test: p < 0.001) groups showed increased immunoreactivity toward TCPTP (Fig. 4A and D; one-way ANOVA: F2.30 = 71.30, p < 0.001, η2 = 0.826), GFAP (Fig. 4B and D; one-way ANOVA: F2.30 = 177.25, p < 0.001, η2 = 0.921), and IBA1 (Fig. 4C and D; one-way ANOVA: F2.29 = 20.54, p < 0.001, η2 = 0.586) in the ARC. At PN60, both the SL and LL groups showed an increase in the number of GFAP- (Supplemental Fig. 4A) and IBA1- (Supplemental Fig. 4B) positive cells in the ARC (GFAP: one-way ANOVA: F2.16 = 29.79, p < 0.001, η2 = 0.788; Newman-Keuls test: SL and LL x NL: p < 0.001) (IBA1: one-way ANOVA: F2.15 = 7.462, p < 0.005, η2 = 0.499; NewmanKeuls test: SL x NL: p < 0.006 and LL x NL: p < 0.011) and VMH (GFAP: one-way ANOVA: F2.15 = 23.63, p < 0.001, η2 = 0.759; Newman-Keuls test: SL and LL x NL: p < 0.001) (IBA1: one-way ANOVA: F2.15 = 22.62, p < 0.001, η2 = 0.751; Newman-Keuls test: SL

and LL x NL: p < 0.001). Notably, the litter size did not affect the number of GFAP- and IBA1-positive cells in the PVN, CA3 and DG (Supplemental Figs. 4A and B, respectively). The Manders coefficient varies from zero to one, and a value above 0.6 represents colocalization. At PN21, the SL group showed an increase in the Manders coefficient value for TCPTP/GFAP immunolabeling overlap compared to that of the NL group (Table 2; one-way ANOVA: F2.27 = 113.01, p < 0.001, η2 = 0.893; Newman-Keuls test: SL x NL: p < 0.001). At PN60, both the SL and LL groups showed an increase in the Manders coefficient value for TCPTP/GFAP immunolabeling overlap compared to that of the NL group (Table 2; one-way ANOVA: F2.30 = 51.92, p < 0.001, η2 = 0.776; Newman-Keuls test: SL and LL x NL: p < 0.001). The Manders coefficient value for TCPTP/IBA1 did not indicate immunolabeling overlap (Table 2).

3.6. Effects of litter size on CX30, GFAP and IBA1 immunoreactivity and Gja6 mRNA expression in the ARC of juvenile and adult rats At PN21, the litter size did not change the CX30 immunoreactivity (Fig. 5A; Supplemental Fig. 2), but both the SL and LL groups showed a decrease in the mRNA expression of gap junction protein alpha 6 6

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Table 2 Effects of litter size on TCPTP overlap. PN

Overlap

PN21 PN60 PN21 PN60

SL

TCPTP/GFAP TCPTP/GFAP TCPTP/IBA1 TCPTP/IBA1

0.9450 0.9796 0.2286 0.1903

± ± ± ±

⁎

0.0180 0.0065⁎ 0.0330 0.0249

NL

LL

0.554 ± 0.0230 0.7912 ± 0.0247 0.2738 ± 0.0330 0.2349 ± 0.0341

0.5042 0.9832 0.2423 0.2186

± ± ± ±

0.0265 0.0065⁎ 0.0399 0.04146

Data are expressed as the mean ± SEM. One-way ANOVA followed by Newman–Keuls test. ⁎ p < 0.05 vs NL group, n = 10.

to that of the LL group (Newman-Keuls test: SL x LL: p < 0.001). The Manders coefficient value for CX30/GFAP immunolabeling overlap at PN21 was similar between the three groups (Table 3). At PN60, however, the SL and LL groups showed a decrease in the Manders coefficient value for CX30/GFAP immunolabeling overlap compared to the value of the NL group (Table 3; one-way ANOVA: F2.27 = 28.77, p < 0.001, η2 = 0.681; Newman-Keuls test: SL and LL x NL: p < 0.001). There was no difference in the Manders coefficient value for CX30/IBA1 immunolabeling overlap at PN21 and PN60 (Table 3).

(Gja6), a gene that encodes CX30 protein, compared to that of the NL group (Fig. 5B; one-way ANOVA: F2.21 = 6.12, p < 0.008, η2 = 0.368; Newman-Keuls test: SL x NL: p < 0.034 and LL x NL: p < 0.007). However, at PN60, both the SL and LL groups showed a decrease in CX30 immunoreactivity (Fig. 5A and C; one-way ANOVA: F2.27 = 149.22, p < 0.001, η2 = 0.917; Newman-Keuls test: SL and LL x NL: p < 0.001) and Gja6 mRNA expression (Fig. 5B; one-way ANOVA: F2.23 = 4.76, p < 0.019, η2 = 0.293; Newman-Keuls test:: SL x NL: p < 0.024 and LL x NL: p < 0.040) compared to those of the NL group. The SL group showed lower CX30 immunoreactivity compared

CX30

C 3V

A SL

NL

LL

15 10

*

*

CX30

#

5 0

PN21

PN60

GFAP B

( A r b it r a r y u n it s )

G ja 6 m R N A e x p r e s s io n

( A v e r a g e p ix e l in t e n s it y )

ARC – PN60

2 .0 1 .5 1 .0

*

*

*

*

0 .5

IBA1

0 .0

PN21

PN60

Merge

SL

NL

LL

Fig. 5. The litter size changes the CX30 expression in the ARC. (A) CX43 average pixel intensity and (B) the relative expression of Gja6 mRNA in the ARC of the SL, NL and LL groups at PN21 and PN60, n = 10. Data are expressed as the mean ± SEM. One way ANOVA followed by Newman–Keuls test. *p < 0.05 vs NL group; #p < 0.05 vs LL group. Representative photomicrographs (C) of the triple immunofluorescence for CX30 (green), GFAP (red) and IBA1 (blue) in the ARC at PN60. ARC scale: 200 μm; CX30, GFAP and IBA1 scale: 25 μm. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 7

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Table 3 Effects of litter size on CX30 overlap. PN

Overlap

SL

PN21 PN60 PN21 PN60

CX30/GFAP CX30/GFAP CX30/IBA1 CX30/IBA1

0.8985 0.6379 0.7862 0.6683

NL ± ± ± ±

0.0233 0.0197⁎ 0.0225 0.0095

0.8630 0.8905 0.7870 0.6455

LL ± ± ± ±

0.0283 0.0325 0.0290 0.0240

0.8637 0.6792 0.7459 0.7043

± ± ± ±

0.0240 0.0216⁎ 0.0265 0.0532

Data are expressed as the mean ± SEM. One-way ANOVA followed by Newman–Keuls test. ⁎ p < 0.05 vs NL group, n = 10.

C

( A v e r a g e p ix e l in t e n s it y )

3V

A 8 6

*

CX43

4 2 0

PN21

PN60

GFAP B

( A r b it r a r y u n it s )

G ja 1 m R N A e x p r e s s io n

CX43

ARC – PN60

2 .0 1 .5

*

1 .0

IBA1

0 .5 0 .0

PN21

PN60

Merge

SL

NL

LL

Fig. 6. The litter size changes the CX43 expression in the ARC. (A) CX43 average pixel intensity (B) and the relative expression of Gja1 mRNA in the ARC of the SL, NL and LL groups at PN21 and PN60, n = 10. Data are expressed as the mean ± SEM. One way ANOVA followed by Newman–Keuls test. *p < 0.05 vs NL group. Representative photomicrographs (C) of the triple immunofluorescence for CX43 (green), GFAP (red) and IBA1 (blue) in the ARC at PN60. ARC scale: 200 μm; CX43, GFAP and IBA1 scale: 25 μm. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Table 4 Effects of litter size on CX43 overlap. PN PN21 PN60 PN21 PN60

Overlap CX43/GFAP CX43/GFAP CX43/IBA1 CX43/IBA1

SL 0.9336 0.8817 0.8803 0.7176

NL ± ± ± ±

⁎

0.014 0.0096 0.0225 0.0458

Data are expressed as the mean ± SEM. One-way ANOVA followed by Newman–Keuls test. ⁎ p < 0.05 vs NL group, n = 10.

8

0.7777 0.9051 0.8383 0.8189

LL ± ± ± ±

0.2215 0.0181 0.0243 0.0198

0.7376 0.8526 0.8519 0.7230

± ± ± ±

0.0323 0.0302 0.0273 0.0265

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F2.24 = 4.80, p < 0.018, η2 = 0.285; Newman-Keuls test: SL x NL: p < 0.013) compared to those of the NL group. At PN60, both the SL and LL groups showed increased astrocyte somata size (Fig. 7A; oneway ANOVA: F2.27 = 18.80, p < 0.001, η2 = 0.582; Newman-Keuls test: SL and LL x NL: p < 0.001) and the average length of process extensions (Fig. 7B; one-way ANOVA: F2.27 = 15.87, p < 0.001, η2 = 0.540; Newman-Keuls test: SL and LL x NL: p < 0.001) compared to those of the NL group. At PN21, the SL group showed an increase in microglia somata size (Fig. 7C; one-way ANOVA: F2.21 = 13.13, p < 0.001, η2 = 0.555; Newman-Keuls test: SL x NL: p < 0.001) and the average length of process extensions (Fig. 7D; one-way ANOVA: F2.29 = 13.18, p < 0.001, η2 = 0.476; Newman-Keuls test: SL x NL: p < 0.001) compared to those of the NL group. However, at PN60, the SL group showed an increase (Fig. 7C; one-way ANOVA: F2.21 = 9.503, p < 0.001, η2 = 0.476; Newman-Keuls test: SL x NL: p < 0.003) in only microglia somata size compared to that of the NL group.

3.7. Effects of litter size on CX43, GFAP and IBA1 immunoreactivity and Gja1 mRNA expression in the ARC of juvenile and adult rats At PN21, the SL group showed an increase in CX43 immunoreactivity (Fig. 6A and Supplemental Fig. 3; one-way ANOVA: F2.27 = 21.81, p < 0.001, η2 = 0.618; Newman-Keuls test: SL x NL: p < 0.001) and gap junction protein alpha 1 (Gja1) mRNA expression (Fig. 6B; one-way ANOVA: F2.22 = 7.75, p < 0.003, η2 = 0.413; Newman-Keuls test: SL x NL: p < 0.027). However, the litter size did not affect CX43 immunoreactivity (Fig. 6A and D) or Gja1 mRNA expression (Fig. 6B) at PN60. At PN21, the SL group showed an increase in the Manders coefficient value for CX43/GFAP immunolabeling overlap (Table 4; one-way ANOVA: F2.27 = 28.77, p < 0.001, η2 = 0.681; Newman-Keuls test: SL x NL: p < 0.001). However, at PN60, there was no difference in the Manders coefficient values for CX43/GFAP immunolabeling overlap. No differences in the CX43/IBA1 immunolabeling overlap at PN21 or PN60 were observed (Table 4).

4. Discussion

3.8. Effects of litter size on glial cell morphology in the ARC of juvenile and adult rats

4.1. Neonatal over- and undernutrition change body weight gain and food intake

*

100

*

* 50 0

PN21

PN60

50 40 30

*

*

*

20 10 0

PN21

PN60

C 200

*

150 100 50

*

0

PN21

PN60

D e x t e n s io n ( µ m )

150

B

M ic r o g lia p r o c e s s

LL

M ic r o g lia s o m a

NL

The present study reinforces the concept that both overnutrition and undernutrition during the neonatal period affect body weight gain and ( A v e r a g e p ix e l in t e n s it y )

SL

e x t e n s io n ( µ m )

A

A s tro c y te p ro c e s s

A s tro c y te s o m a

( A v e r a g e p ix e l in t e n s it y )

At PN21, the SL group showed an increase in both astrocyte somata size (Fig. 7A and E; one-way ANOVA: F2.27 = 44.22, p < 0.001, η2 = 0.766; Newman-Keuls test: SL x NL: p < 0.001) and the average length of process extensions (Fig. 7B and E; one-way ANOVA:

50 40

*

30 20 10 0

PN21

PN60

E

GFAP

IBA1

SL

NL

LL

Fig. 7. The litter size affects the glial morphology in the ARC. (A) astrocyte soma average pixel intensity and (B) processes extensions (μm); (C) microglia soma average pixel intensity (D) and processes extensions (μm) in the ARC of the SL, NL, LL groups at PN21 and PN60, n = 8–14. Data are expressed as mean ± SEM. One way ANOVA followed by Newman–Keuls test. *p < 0.05 vs NL group. Representative photomicrographs (E) of GFAP and IBA1 immunofluorescence in the ARC at PN60. Arrows indicate the soma of astrocytes and microglia, labeled with GFAP or IBA1. Scale: 10 μm. 9

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increased cytokine expression observed in the present study might be related to the elevated food intake promoted by neonatal nutritional programming. IKKβ/NF-кB signaling in astrocytes is required for dietinduced astrogliosis and the subsequent increase in food intake (Douglass et al., 2017).

adiposity later in life. These effects are observed in parallel to high plasma leptin levels, elevated expression of TCPTP, and changes in glial cell morphology in the hypothalamus. Nutritional changes during the lactation period influence neurodevelopment and may promote changes in central metabolic control in adult life (Glavas et al., 2010; Rodrigues et al., 2011). After weaning, rats raised in small litters were heavier than controls and presented higher food intake, confirming the energy homeostasis alterations promoted by neonatal overnutrition later in life (Li et al., 2013). Epigenetic mechanisms, for example, the hypermethylation of the gene that encodes proopiomelanocortin (POMC), an anorexigenic neuropeptide expressed in the ARC (Plagemann et al., 2010), have been implicated in litter size nutritional programming. Rats raised in large litters showed higher energy intake and efficiency and catch-up of body weight gain, as previously shown by Remmers et al. (2008). Neonatal undernutrition has been shown to increase the number of neuropeptide Y (NPY)-, agouti-related peptide (AgRP)-, and gamma-aminobutyric acid (GABA)-expressing neurons in the ARC (Cripps et al., 2009; Rocha et al., 2014; López et al., 2005). This model also increases the AgRP projections from the ARC to the PVN and the number of NPY/AgRP neuron synapses in the PVN between the 3rd and 4th postnatal weeks (Cripps et al., 2009; Rocha et al., 2014; López et al., 2005). Additionally, a reduction in KATP channel expression in NPY, AgRP, and GABA neurons in the ARC was found in underfed juvenile rats during lactation, leading to a reduced ability of these neurons to hyperpolarize (Juan De Solis et al., 2016). Hence, it is clear that neuronal plasticity can be modulated by neonatal undernutrition, which in turn leads to altered feeding behavior in juvenile and adult life. The present study investigated only male rats to avoid the effects of the estrous cycle on metabolic changes. This is a limitation of the study, as sexual dimorphism was reported in the effect of neonatal overnutrition and the impact on weight gain and hypothalamic inflammation/gliosis (Argente-Arizón et al., 2018).

4.4. Over- and undernutrition lead to gliosis in the ARC Excessive neonatal feeding in the small litter group induced changes in microglial morphology in the ARC at PN21 and PN60. TapiaGonzález et al. (2011) demonstrated that rats raised in small litters (4 pups per dam) show an increased number of activated microglia cells in the hypothalamus at PN60. We show that the increase in microglia cells in rats overfed during the neonatal period is an early event, seen at weaning and sustained at PN60, even in the absence of hyperphagia. This early increase in microglial cells in the small litter group may be related to the increase in leptin secretion induced by higher body weight during lactation. In fact, leptin treatment increases the number of microglial cells and their branching in ob/ob mice, even with body weight loss (Gao et al., 2014). However, the increase in the number of microglial cells might also be related to hyperphagia (André et al., 2017). Glial cells in the hypothalamus are known to participate in the control of energy homeostasis (Argente-Arizón et al., 2015). In this study, we demonstrate that both under- and overnutrition altered astrocyte morphology in adult life. Similar results were reported in adult rats raised in small litters (4 pups per dam) at PN70 (García-Cáceres et al., 2011), at PN90 (Fuente-Martín et al., 2012), and at PN150 (Argente-Arizón et al., 2018). As mentioned above for microglia, in rats raised in small litters, the alteration of astrocyte morphology was observed at weaning and may be related to increased leptin secretion. Leptin promotes a marked effect on astrocyte morphology in the hypothalamic primary cell culture (Debarba et al., 2019). The ablation of LepR in astrocytes reduces astrocyte proliferation in the hypothalamus, and the opposite was observed with leptin treatment in mice during the early postnatal period (Rottkamp et al., 2015). Conditioned LepR ablation in adult mice promoted a reduction in the number and length of astrocyte processes; again, an opposite effect was observed with chronic leptin infusions in the ARC of rats (García-Cáceres et al., 2011; Kim et al., 2014). Insulin receptor signaling has also been shown to affect the number and length of astrocyte processes in the hypothalamus (García-Cáceres et al., 2016). Therefore, the increase in insulin and leptin concentrations in the SL group might contribute at least in part to the hypothalamic astrogliosis observed at weaning.

4.2. Neonatal over- and undernutrition affect plasma leptin and insulin levels and TCPTP expression in the ARC Plasma leptin and insulin concentrations were elevated in both rats raised in small and large litters at PN60. It has been proposed that leptin action is impaired in young adult rats that have been overfed during lactation (Glavas et al., 2010). TCPTP is a counter-regulatory mediator of leptin signaling, as it dephosphorylates the signal transducer and activator of transcription factor 3 (STAT3) in the nucleus and cytoplasm (Yamamoto et al., 2002; Tiganis and Bennett, 2007; Shields et al., 2008; Loh et al., 2011). Due to its counter-regulatory action on leptin signaling (Loh et al., 2011) and insulin (Galic et al., 2003; Tsou and Bence, 2013; Dodd et al., 2015), TCPTP has been associated with leptin resistance in the hypothalamus during obesity. We demonstrated for the first time an increase in TCPTP mRNA and protein expression in the ARC of rats after overnutrition (raised in small litters) at weaning, as well as in rats subjected to either neonatal over- or undernutrition at PN60. Our data suggest that neonatal nutritional programming induces TCPTP increases in the ARC, contributing to hypothalamic leptin resistance and metabolic imbalance in adult life.

4.5. Neonatal over- and undernutrition modulate the expression of connexins in the ARC Astrocytes are interconnected through gap junctions formed by connexins and organized into a neuroglial network. After weaning (PN21), we observed an increase in the expression of CX43 in rats raised in small litters. CX43 in the hypothalamus was shown to be related to glucose homeostasis (Allard et al., 2014) and diet-induced obesity (Sasaki et al., 2018). We previously showed that leptin in vitro was able to induce CX43 expression in astrocyte cell culture (Debarba et al., 2019). Further studies are necessary to understand the role of the hormonal milieu, e.g., increased leptin release, during the neonatal period and connexin expression in the ARC. We observed an increase in the soma size and process extensions of astrocytes in parallel with a decrease in the expression of CX30 at PN60 in rats raised in small and large litters. The participation of CX30 in the integrity of astrocyte morphology has been demonstrated in vitro (Ghézali et al., 2018; Debarba et al., 2019) and in CX30 knockout mice that show an increase in astrocytic processes in the hippocampus (De Bock et al., 2014; Clasadonte and Haydon, 2014). Therefore, a reduction in CX30 may contribute to the marked changes in the astrocyte

4.3. Neonatal nutritional changes alter the inflammatory profile in the hypothalamus The expression of genes encoding proinflammatory cytokines such as Tnf was enhanced by neonatal over- and undernutrition in the ARC of adult rats (PN60). Low-grade inflammation is a well-described condition associated with obesity (Milanski et al., 2009; Li et al., 2012). Studies have shown that hypothalamic inflammation occurs as a consequence of a fat-rich diet (Milanski et al., 2009; Li et al., 2012; Valdearcos et al., 2014) and also after neonatal overnutrition (TapiaGonzález et al., 2011; Argente-Arizón et al., 2018). It is likely that the 10

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morphology observed in neonatal nutritional programming in rats. The interplay between connexins and metabolism imbalance remains to be elucidated. The effects of protein phosphatases on cell morphology and the microtubule networks in BHK-21 cells were demonstrated by Eriksson et al. (1992). Specific tyrosine residues (Y247 and Y265) on CX43 undergo phosphorylation (Saidi Brikci-Nigassa et al., 2012) and are targets of TCPTP (Li et al., 2014). We previously showed in an in vitro study that LPS and leptin stimulate TCPTP expression in astrocytes with a concomitant increase in CX43 and an opposite effect on CX30 expression and changes in astrocyte size (Debarba et al., 2019). Remarkably, TCTP gene silencing reversed these effects of leptin and LPS on astrocyte morphology and the reciprocal changes in CX43 and CX30 expression. In vitro studies do not replicate in vivo conditions; therefore, the significance of TCPTP on glial cell morphology in vivo requires further investigation. The inflammatory stimulus promoted by LPS in macrophage cell line culture was able to increase CX43 (Qin et al., 2016). The prenatal LPS exposure model promotes an increase in CX43 protein and activity in astrocytes (Avendaño et al., 2015). The increase in the CX43 protein in the prenatal LPS-exposure model is related to the arborization of hippocampal astrocytes (Chávez et al., 2019). The upregulation of CX43 in chronic astrogliosis has also been described in CNS injury models (Theriault et al., 1997; Lee et al., 2005; Cronin et al., 2008; Markoullis et al., 2012; Tonkin et al., 2015; Zhang et al., 2010). These results in the literature seem to be related to the time course of inflammatory stimulus (Markoullis et al., 2012; Liu et al., 2012). LPS-stimulated C6 cells (Rattus norvegicus glioma cells) increased CX43 gene and protein expression at the third and sixth hours. It then decreased from the 12th to the 48th hour (Liu et al., 2012). The present data shows that in small litters, CX43 expression increases at PN21, but no changes were observed at PN60. Further studies are necessary to clarify the inflammatory temporal interaction with CX43. In conclusion, our study describes the impact of over- and undernutrition during the neonatal period on body weight in later periods of life. Changes in neonatal nutrition lead to changes in glial cell morphology in the ARC, which is associated with increased circulating leptin and insulin levels, increased TCPTP expression, and reduced CX30 expression. Further investigation using conditional postnatal deletion of leptin and TCPTP in astrocytes could reveal the precise role of these factors in neonatal nutritional programming and their impact on metabolic status in adult life. Of note, it will be important to consider the sex dimorphism on these long-lasting effects in future studies. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.yhbeh.2020.104690.

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Declaration of competing interest The authors declare no competing financial interests. Acknowledgments We would like to thank Maria Valci dos Santos, Milene Mantovani, Roberta Ribeiro Costa Rosales, and Rubens Fernando de Melo for their excellent technical assistance. Financial support: São Paulo Research Foundation (FAPESP), National Council for Scientific and Technological Development (CNPq), Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES). References Allard, C., Carneiro, L., Grall, S., Cline, B.H., Fioramonti, X., Chrétien, C., Baba-Aissa, F., Giaume, C., Pénicaud, L., Leloup, C., 2014. Hypothalamic astroglial connexins are required for brain glucose sensing-induced insulin secretion. J. Cereb. Blood Flow Metab. 34 (2), 339–346. André, C., Guzman-Quevedo, O., Rey, C., Rémus-Borel, J., Clark, S., CastellanosJankiewicz, A., Ladeveze, E., Leste-Lasserre, T., Nadjar, A., Abrous, D.N., Laye, S.,

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