Edited by: Heber C. Nielsen, Tufts Medical Center and Tufts School of Medicine, USA
Reviewed by: Laura Sasur Madore, Baystate Medical Center, USA; Shadi Nawaf Malaeb, Drexel University and St. Christopher’s Hospital for Children, USA
Specialty section: This article was submitted to Neonatology, a section of the journal Frontiers in Pediatrics
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Milk fat globule membrane (MFGM) and lactoferrin have been identified as two components that have potential to affect neurodevelopment. While concentrations of some MFGM constituents in infant formulas are within human milk range, they may not be present at optimal or clinically effective levels. However, lactoferrin levels of infant formulas are consistently reported to be lower than human milk. This study sought to provide a novel combination of prebiotics, bovine-derived MFGM, and lactoferrin and assess their influence on neurodevelopment.
Twenty-four male piglets were provided either TEST (
Diffusion tensor imaging revealed differences in radial (
Observed differences in microstructure maturation of the internal capsule and cortical tissue concentrations suggest that piglets provided TEST diet were more advanced developmentally than piglets provided CONT diet. Therefore, supplementation of infant formula with prebiotics, MFGM, and lactoferrin may support neurodevelopment in human infants.
Early life is a period of rapid neurodevelopment and nutrition during this critical phase can have lasting effects on structural and functional neurodevelopment. Human milk is generally considered the optimal source of nutrient provision for the human infant, and some studies have demonstrated improved cognitive development of breastfed infants (
Lactoferrin is an abundant functional protein in the whey fraction of human milk, which exerts antimicrobial effects and modulates immune responses (
Historically, MFGM has been discarded in the preparation of infant formulas, although many individual components of this membrane may positively impact neurodevelopment. The MFGM is composed of sialic acid, gangliosides, sphingomyelin, choline, glycerophospholipids, proteins, and cholesterol (
Emerging evidence suggests that dietary manipulation of the intestinal microbiome may impact the development and functions of the enteric and central nervous systems. Previous studies in humans, piglets, and rodents have shown that polydextrose and galactooligosaccharides can significantly alter the microbiome (
To our knowledge, no study has investigated a diet containing prebiotics, Lf, and MFGM and assessed their combined impact on whole brain development. Furthermore, research has demonstrated the omega-3 fatty acids docosohexaenoic acid (DHA) and arachidonic acid (ARA) are needed to support brain and visual development and as such are included in the vast majority of infant formulas on the market today. Importantly, this study was designed to seek additional brain benefits beyond DHA and ARA by including these in both the control and experimental formulations. Therefore, the aim of this study was to use the piglet as a pre-clinical model to elucidate potential mechanisms whereby a novel combination of prebiotics, Lf, and MFGM affected neurodevelopment beyond what is provided by DHA and ARA. We hypothesized that supplementation of this novel combination of ingredients would enhance the overall brain development of the supplemented group compared with piglets fed control formula.
All animal care and experimental procedures were in accordance with National Research Council Guide for the Care and Use of Laboratory Animals and approved by the University of Illinois at Urbana-Champaign Institutional Animal Care and Use Committee. Twenty-four naturally farrowed intact male Yorkshire piglets from the University of Illinois Imported Swine Research Laboratory were obtained 48 h after birth, to allow colostrum consumption, and artificially reared over a 30-day trial period. The trial was completed in two replicates (12 piglets per replicate), with four piglets selected from six litters to control for genetics and initial body weight. Piglets were individually housed, as previously described, in stainless steel cages (1.03 m deep × 0.77 m wide × 0.81 m high) with clear, Plexiglas facades and side walls bearing several small openings (2.54 cm in diameter) to allow for adequate ventilation. A towel and toy were included in each cage to provide enrichment, and piglets were allowed
Ambient room temperature was maintained between 27 and 29°C and heat lamps and mats provided supplemental heat within the cage. A 12 h light/dark cycle was maintained with light from 0600 to 1800 hours. Prior to placement in the artificial rearing system, piglets were administered 5 mL of
All researchers involved with conducting the study and acquiring and analyzing study results remained blinded to dietary treatment identity until final data analyses had been completed. Piglets (
Both CONT and TEST milk replacer powder was reconstituted at 200 g of dry powder per 800 g of water. At this reconstitution rate, both diets contained docosahexaenoic acid (182 mg/L) and ARA (364 mg/L), and the reconstituted TEST treatment contained PDX/GOS (2.4 and 7 g/L of PDX and GOS, respectively), Lf (0.6 g/L), and MFGM (5.0 g/L). Piglets received small volumes of milk treatments on the day of arrival to provide an adjustment period prior to the standard feeding regimen. Piglets were fed at 285, 305, and 310 mL of reconstituted diet per kg BW starting on 3, 5, and 12 days of age, respectively. Body weight was recorded daily to determine the volume of milk to be dispensed to individual animals throughout the day. Meals were administered five times a day, approximately every 4 h, between 0700 and 2200 hours, and each diet was reconstituted fresh at each feeding. Piglets were fasted prior to cognitive testing to incentivize the milk reward offered in the behavioral task. On days that behavioral testing occurred (between 17 and 28 days of age) piglets were provided four meals instead of five, while maintaining the aforementioned daily volume per kg body weight feeding rate.
Hippocampal-dependent learning and memory was assessed using a validated behavioral task of spatial working memory in a specially designed T-maze (
Piglets underwent a series of 10 trials per day with the number of correct choices as a proportion of 10 total choices used as the primary response parameter, and incidence of non-compliance (i.e., proportion of total choices where pig did not complete the task within 60 s) was also recorded. Latency to choice, or the number of seconds to complete the task, was determined manually by stopwatch in the first replicate and a time stamp hard-coded in a recorded video was used for the second replicate. Because the methodology differed between the two replicates, the time per trial for each pig was rounded to the whole second.
Individual piglet performance was evaluated in three stages to determine task participation before further analysis of learning was measured. The first phase documented the frequency of non-compliance of each trial for individual pigs. Next, participation was determined by the number of occurrences of non-compliance. Piglets were allowed up to three non-compliant trials per day before being considered non-participatory, and the entire day marked as non-compliant. Finally, if three or more days of non-compliance were documented for an individual pig, that subject’s behavioral data were removed from the final dataset.
At 30 days of age, piglets underwent magnetic resonance imaging (MRI) procedures. Piglets were scanned on a Siemens MAGNETOM Trio 3T Imager using a Siemens 32-channel head coil. Upon arrival to the Beckman Institute Biomedical Imaging Center, piglets were anesthetized via intramuscular injection of Telazol (0.07 mg/kg body weight; Zoetis, Florham Park, NJ, USA). Once sedated, piglets were transferred to the MRI scanner and maintained on 2% isoflurane/98% oxygen for the entirety of the 60 min scan. An MRI-compatible pulse oximeter was used to monitor piglet vital signs throughout the scan. Upon completion of the scan, vital signs were monitored and recorded until complete recovery from anesthesia. Specific details regarding piglet imaging sequences and post-imaging analysis of diffusion tensor imaging (DTI) and voxel-based morphometry were previously described (
Scanning procedures provided three 3D T1-weighted magnetization-prepared rapid gradient echo (MPRAGE) scans per piglet, with a 0.7 isotropic voxel size. Procedures for MPRAGE averaging and manual brain extraction were previously described (
Individual brains were segmented into 19 different regions of interest (ROI) using the piglet brain atlas. Total brain and individual region volume analysis was performed on diffeomorphic anatomical registration using exponentiated Lie algebra (DARTEL)-generated warp files for each region using the fslstats toolbox provided in the FSL 5.0 package (Analysis Group, FMRIB, Oxford, UK). Generation of region-specific warp files was previously described (
Voxel-based morphometry (VBM) analysis was performed, to assess gray matter and white matter tissue concentrations using SPM8 software (Wellcome Department of Clinical Neurology, London, UK). Manually extracted brains were aligned to piglet brain atlas space using a 12-parameter affine transformation. The “Segment” function of SMP and piglet-specific prior probability tissue maps were then used to segment the brains into gray matter, white matter, and cerebrospinal fluid. The DARTEL toolbox was used with the same piglet-specific specifications as described previously (
Diffusion tensor imaging values were generated using a diffusion-weighted echo-planar imaging sequence with a
Ribonucleic acid was extracted from the right hippocampus and prefrontal cortex brain tissues using RNeasy Plus Mini Kit (QIAGEN, Venlo, Limburg) according to manufacturer’s instructions. Extracted RNA yield was quantified by spectrophotometry (NanoDrop 1000; Thermo Fisher Scientific, Waltham, MA, USA) at 260 nm and quality was assessed with the 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) in the W.M. Keck Center at the University of Illinois; all samples had a RIN > 6. Reverse transcription was performed using 2 μg of total RNA in a volume of 10 μL using the High Capacity cDNA Reverse Transcription kit (Life technologies, Carlsbad, CA, USA).
Quantitative real-time PCR was conducted for BDNF (TaqMan Expression Assay: Ss03822335_s1, Life Technologies) in both right hippocampus and prefrontal cortex samples on a MicroAmp optical 384-well plate (Life Technologies, Carlsbad, CA, USA) using the 7900HT Fast Real-Time PCR system (Life Technologies, Carlsbad, CA, USA). Ribosomal protein L19 (RPL 19; Ss03375624_g1) was used as an endogenous control. Sample mRNA abundance was quantified with the use of the Relative Standard Curve method, where the standard curve, derived from a stock of pooled porcine hippocampal and midbrain cDNA, was prepared using serial 1:5 dilutions. Normalized values were calculated by dividing the target quantity mean by the RPL19 quantity mean, while fold-change differences were calculated by dividing the normalized target value (TEST) by the average normalized calibrator (CONT) value.
An analysis of variance (ANOVA) was conducted using the MIXED procedure of SAS 9.3 (SAS Inst. Inc., Cary, NC, USA) was applied to differentiate the effects of the CONT vs TEST diets provided to young pigs. Depending on the outcome, one of two statistical models used was as follows: (1) any data collected at a single time-point (i.e., brain volume, DTI, fatty acid, and gene expression) was analyzed by a simple one-way ANOVA and (2) any data collected from the same animal on more than one occasion (i.e., behavioral outcomes) were analyzed as a two-way, repeated-measures ANOVA. Both statistical models included replicate as a random effect and the level of significance was set at
Statistical analysis of VBM outcomes was performed as previously described (
Piglets in this study grew at rates consistent with artificially and sow-reared piglets of similar age. No signs of lameness or sickness were observed during daily observations of piglets on this study. For more informative data regarding piglet growth and health, the reader is referred to our companion paper (Berding et al., under review)1.
Based on the participation criteria set forth in this study, one piglet from the TEST diet was excluded from the behavioral dataset due to non-compliance on third day of the 11-day assessment period. Thus, 11 piglets from the TEST diet and 12 piglets from the CONT diet were included in the final dataset. No interactive effects (i.e., diet × day interaction) or the main effect of diet was observed for percentage of correct choices throughout the 11-day assessment (Figure
Due to excessive motion during MRI data acquisition, one piglet from the TEST diet was excluded from all MRI analyses. Thus, 11 piglets from the TEST diet and 12 piglets from the CONT diet were used. Absolute brain volumes were not different between dietary treatment groups. When brain regions were assessed relative to total brain volume within subject, there were no differences between diets observed in relative volume for any of the 19 anatomical regions analyzed. Analysis of brain volumes relative to intracranial volume (i.e., total brain volume) is consistent with current neuroimaging practices.
Voxel-based morphometric analysis of gray and white matter tissue segmentations revealed differences in regional tissue concentrations between treatment groups (Table
Tissue | Comparison | Anatomic region |
Cluster | Peak level | Local maxima coordinates |
|||
---|---|---|---|---|---|---|---|---|
(# voxels) | Pseudo- |
|||||||
Gray | CONT > TEST | Cerebellum | 147 | 0.004 | 3.40 | 0 | −18 | 2 |
Cerebellum | 41 | 0.010 | 2.89 | 10 | −19 | 1 | ||
Left cortex | 547 | 0.006 | 3.41 | −10 | 20 | 6 | ||
Left cortex | 173 | 0.010 | 3.06 | −11 | 20 | 16 | ||
Left cortex | 149 | 0.005 | 2.44 | −18 | 13 | 10 | ||
Left cortex | 129 | 0.008 | 2.27 | −6 | 36 | 3 | ||
Right cortex | 1051 | < 0.001 | 6.28 | 15 | 13 | 16 | ||
Right cortex | 371 | 0.009 | 3.81 | 20 | −3 | 10 | ||
Right cortex | 86 | 0.003 | 3.29 | 11 | 23 | 14 | ||
Right cortex | 42 | 0.007 | 2.82 | 8 | 29 | 7 | ||
TEST > CONT | Caudate | 40 | 0.006 | 1.56 | 6 | 15 | 8 | |
Cerebellum | 26 | 0.009 | 3.01 | 3 | −24 | 3 | ||
Cerebral aqueduct | 26 | 0.010 | 2.50 | 1 | −2 | −2 | ||
Left cortex | 392 | 0.005 | 4.12 | −11 | 9 | 1 | ||
Left cortex | 299 | 0.010 | 3.96 | −17 | −6 | 2 | ||
Midbrain | 34 | 0.010 | 2.13 | −6 | −6 | −8 | ||
Right cortex | 37 | 0.009 | 1.77 | 17 | −9 | −4 | ||
White | CONT > TEST | Cerebellum | 254 | 0.009 | 3.61 | −1 | −20 | −1 |
Left cortex | 143 | 0.009 | 3.62 | −15 | 1 | 15 | ||
Left cortex | 480 | 0.007 | 3.45 | −10 | 35 | 5 | ||
Left cortex | 62 | 0.010 | 2.80 | −9 | 6 | 13 | ||
Left Hippocampus | 100 | 0.009 | 1.25 | −12 | −2 | −4 | ||
Medulla | 712 | 0.006 | 3.66 | −6 | −15 | −14 | ||
Right cortex | 1026 | 0.001 | 7.10 | 14 | 13 | 15 | ||
Right cortex | 151 | 0.001 | 4.57 | 9 | 22 | 13 | ||
Right cortex | 175 | 0.006 | 4.12 | 10 | 35 | 5 | ||
Right cortex | 183 | 0.009 | 4.02 | 15 | 1 | 12 | ||
Right cortex | 70 | 0.008 | 1.23 | 9 | 27 | 0 | ||
TEST > CONT | Cerebellum | 29 | 0.009 | 1.88 | −4 | −16 | 3 | |
Lateral Ventricle | 21 | 0.010 | 2.18 | 4 | 20 | 8 | ||
Right cortex | 203 | 0.009 | 1.19 | 18 | −8 | 6 |
Assessment of water molecule diffusion revealed differences (
Analysis of fold change did not reveal differences due to diet in either the right hippocampus or the prefrontal cortex. In the right hippocampus, a BDNF fold change of 1.28 (
In this study, a novel combination of prebiotics, Lf, and MFGM was provided to piglets from 2 to 31 days of age to determine their influence on brain development. We hypothesized that supplementation of prebiotics, Lf, and MFGM would enhance overall brain development in the supplemented group compared with the control group. Previous studies in piglets indicated that supplementation of Lf elicited enhanced spatial learning and memory, as assessed by eight-arm radial maze task (
Whole brain volumetric analyses indicated no differences due to diet in total brain volume in the present study. Moreover, when anatomical subregions were analyzed relative to total brain volume, there were no observed volumetric differences due to diet. Whereas the vast majority of neurons are established prenatally, growth and expansion of those neurons occurs predominately during the postnatal period (
Voxel-based morphometry (VBM) revealed localized differences in gray and white matter tissue concentrations between treatment groups. The most notable differences in gray matter concentrations were observed with CONT piglets exhibiting more and larger clusters of cortical gray matter compared with TEST piglets. While VBM cannot pinpoint the physiological implications of these findings, this decrease in gray matter observed in the TEST group may indicate enhanced neurodevelopment due to this diet. Early in development, an overproduction of synaptic connections occurs, followed by pruning to ensure only necessary neuronal connections are retained (
Although the exact functional location of motor and sensory areas have not been defined in the piglet, visual inspection of gray matter VBM clusters indicates the observed differences may be in areas related to motor and sensory function (see Figure
In addition to the cortical differences in gray and white matter tissue concentrations shown in VBM, diffusion tensor measures revealed alterations in subcortical tissue microstructure between diets. Analysis revealed differences of RD and MD in the internal capsule between TEST and CONT groups. Piglets provided the TEST diet exhibited lower RD and MD values in the internal capsule compared with CONT piglets. RD is a measure of water movement perpendicular to axon bundles. As myelin maturation occurs around axons, RD tends to decrease due to the restriction of water movement across the axon. MD is a measure of overall water movement in a region, and decreases with age as microstructure increases (
A study of Lf supplementation in piglets revealed increased BDNF expression in the hippocampus and enhanced performance in an 8-arm radial maze task compared with control piglets (
Considering differences in gene expression and behavioral outcomes from our study were not consistent with those from Chen et al. (
To our knowledge, this is the first study to investigate how a novel combination of prebiotics, Lf, and MFGM influences early postnatal brain development. As such, we suggest that the presence of these dietary ingredients may have elicited enhanced brain development at 4 weeks of age. Neuroimaging outcomes including VBM differences in gray and white matter suggested that TEST-fed piglets experienced axonal pruning earlier than CONT-fed piglets. Moreover, diffusion tensor measures suggested enhanced maturation of the internal capsule, further supporting our hypothesis of increased maturation in TEST piglets compared with CONT piglets. While behavioral assessment did not indicate differences in learning, it is possible that the TEST diet may have reduced impulsivity and/or anxiety, yet further studies are needed to confirm this result. From this study, we conclude that combined dietary supplementation of prebiotics, Lf, and MFGM were well tolerated, supported normal growth (Berding et al., under review)1, and positively influenced postnatal brain development in the piglet beyond what is afforded by DHA and ARA.
RD, SD, RW, and BB were involved in project conceptualization. AM, LA, and RD were involved in daily project activities. AM, LA, and KB were involved in data collection. AM, LA, RD, KB, and SD were involved in data analysis. All authors were involved in data interpretation and manuscript preparation.
Sharon M. Donovan and Ryan N. Dilger have received grant funding. Sharon M. Donovan has served on advisory boards. Sharon M. Donovan, Ryan N. Dilger, and Lindsey S. Alexander have consulted for Mead Johnson Nutrition. Brian M. Berg and Rosaline V. Waworuntu are employees of Mead Johnson Nutrition. Austin T. Mudd and Kirsten Berding have no conflict of interest to declare.
The authors would like to acknowledge Jennifer Rytych and the University of Illinois Imported Swine Research Laboratory for their contributions to the preparation and execution of the animal phase of this study. We would also like to thank Antoinette Santos and Jasmine Nadhimi for their role in manual MRI brain extractions. The authors acknowledge the efforts of MJN employees, John Alvey and Zafir Gaygadzhiev, for assistance formulating and manufacturing the piglet diets.
This project was supported by Mead Johnson Nutrition.
CONT, control diet; Lf, lactoferrin; MD, mean diffusivity; MFGM, milk fat globule membrane; RD, radial diffusivity; TEST, test diet; VBM, voxel-based morphometry.
1Berding K, Wang M, Monaco MH, Alexander LS, Mudd AT, Chichlowski M, et al. Prebiotics and bioactive milk fractions influence gut development, microbiota and neurotransmitter expression in formula-fed piglets. J Pediatr Gastroenterol Nutr (under review).