Lower Diet Quality Associated with Subclinical Gastrointestinal Inflammation in Healthy United States Adults

BACKGROUND

Higher diet quality has been associated with lower risk of developing inflammatory bowel disease, but associations between diet and gastrointestinal (GI) inflammation in healthy adults prior to disease onset are understudied.

OBJECTIVES

The purpose of this project was to examine associations between reported dietary intake and markers of GI inflammation in a healthy adult human cohort.

METHODS

In a cross-sectional observational trial of 358 healthy adults, participants completed ≤3 unannounced 24-h dietary recalls using the Automated Self-Administered Dietary Assessment Tool and a Block 2014 Food Frequency Questionnaire to assess recent and habitual intake, respectively. Those who provided a stool sample were included in this analysis. Inflammation markers from stool, including calprotectin, neopterin, and myeloperoxidase, were measured by ELISA along with LPS-binding protein from plasma.

RESULTS

Recent and habitual fiber intake was negatively correlated with fecal calprotectin concentrations (n = 295, P = 0.011, 0.009). Habitual soluble fiber intake was also negatively correlated with calprotectin (P = 0.01). Recent and habitual legume and vegetable intake was negatively correlated with calprotectin (P = 0.013, 0.026, 0.01, 0.009). We observed an inverse correlation between recent Healthy Eating Index (HEI) scores and calprotectin concentrations (n = 295, P = 0.026). Dietary Inflammatory Index scores were calculated and positively correlated with neopterin for recent intake (n = 289, P = 0.015). When participants with clinically elevated calprotectin were excluded, recent and habitual fiber, legume, vegetable, and fruit intake were negatively correlated with calprotectin (n = 253, P = 0.00001, 0.0002, 0.045, 0.001, 0.009, 0.001, 0.004, 0.014). Recent total HEI score was inversely correlated with subclinical calprotectin (P = 0.003).

CONCLUSIONS

Higher diet quality may be protective against GI inflammation even in healthy adults. This trial was registered at clinicaltrials.gov as NCT02367287.

Surveying Nutrient Assessment with Photographs of Meals (SNAPMe): A Benchmark Dataset of Food Photos for Dietary Assessment

Photo-based dietary assessment is becoming more feasible as artificial intelligence methods improve. However, advancement of these methods for dietary assessment in research settings has been hindered by the lack of an appropriate dataset against which to benchmark algorithm performance. We conducted the Surveying Nutrient Assessment with Photographs of Meals (SNAPMe) study (ClinicalTrials ID: NCT05008653) to pair meal photographs with traditional food records. Participants were recruited nationally, and 110 enrollment meetings were completed via web-based video conferencing. Participants uploaded and annotated their meal photos using a mobile phone app called Bitesnap and completed food records using the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24®) version 2020. Participants included photos before and after eating non-packaged and multi-serving packaged meals, as well as photos of the front and ingredient labels for single-serving packaged foods. The SNAPMe Database (DB) contains 3311 unique food photos linked with 275 ASA24 food records from 95 participants who photographed all foods consumed and recorded food records in parallel for up to 3 study days each. The use of the SNAPMe DB to evaluate ingredient prediction demonstrated that the publicly available algorithms FB Inverse Cooking and Im2Recipe performed poorly, especially for single-ingredient foods and beverages. Correlations between nutrient estimates common to the Bitesnap and ASA24 dietary assessment tools indicated a range in predictive capacity across nutrients (cholesterol, adjusted R2 = 0.85, p < 0.0001; food folate, adjusted R2 = 0.21, p < 0.05). SNAPMe DB is a publicly available benchmark for photo-based dietary assessment in nutrition research. Its demonstrated utility suggested areas of needed improvement, especially the prediction of single-ingredient foods and beverages.

TaxaHFE: a machine learning approach to collapse microbiome datasets using taxonomic structure

Motivation

Biologists increasingly turn to machine learning models not just to predict, but to explain. Feature reduction is a common approach to improve both the performance and interpretability of models. However, some biological datasets, such as microbiome data, are inherently organized in a taxonomy, but these hierarchical relationships are not leveraged during feature reduction. We sought to design a feature engineering algorithm to exploit relationships in hierarchically organized biological data.

Results

We designed an algorithm, called TaxaHFE, to collapse information-poor features into their higher taxonomic levels. We applied TaxaHFE to six previously published datasets and found, on average, a 90% reduction in the number of features (SD = 5.1%) compared to using the most complete taxonomy. Using machine learning to compare the most resolved taxonomic level (i.e. species) against TaxaHFE-preprocessed features, models based on TaxaHFE features achieved an average increase of 3.47% in receiver operator curve area under the curve. Compared to other hierarchical feature engineering implementations, TaxaHFE introduces the novel ability to consider both categorical and continuous response variables to inform the feature set collapse. Importantly, we find TaxaHFE's ability to reduce hierarchically organized features to a more information-rich subset increases the interpretability of models.

Availability and implementation

TaxaHFE is available as a Docker image and as R code at https://github.com/aoliver44/taxaHFE.

No Associations between Dairy Intake and Markers of Gastrointestinal Inflammation in Healthy Adult Cohort

Dairy products are a good source of essential nutrients and past reviews have shown associations of dairy consumption with decreased systemic inflammation. Links between dairy intake and gastrointestinal (GI) inflammation are under-investigated. Therefore, we examined associations between reported dairy intake and markers of GI inflammation in healthy adults in a cross-sectional observational study, hypothesizing a negative association with yogurt intake, suggesting a protective effect, and no associations with total dairy, fluid milk, and cheese intake. Participants completed 24-h dietary recalls and a food frequency questionnaire (FFQ) to assess recent and habitual intake, respectively. Those who also provided a stool sample (n = 295), and plasma sample (n = 348) were included in analysis. Inflammation markers from stool, including calprotectin, neopterin, and myeloperoxidase, were measured along with LPS-binding protein (LBP) from plasma. Regression models tested associations between dairy intake variables and inflammation markers with covariates: age, sex, and body mass index (BMI). As yogurt is episodically consumed, we examined differences in inflammation levels between consumers (>0 cup equivalents/day reported in recalls) and non-consumers. We found no significant associations between dairy intake and markers of GI inflammation. In this cohort of healthy adults, dairy intake was not associated with GI inflammation.

Association of Estimated Daily Lactose Consumption, Lactase Persistence Genotype (rs4988235), and Gut Microbiota in Healthy Adults in the United States

BACKGROUND

Lactase persistence (LP) is a heritable trait in which lactose can be digested throughout adulthood. Lactase nonpersistent (LNP) individuals who consume lactose may experience microbial adaptations in response to undigested lactose.

OBJECTIVES

The objective of the study was to estimate lactose from foods reported in the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) and determine the interaction between lactose consumption, LP genotype, and gut microbiome in an observational cross-sectional study of healthy adults in the United States (US).

METHODS

Average daily lactose consumption was estimated for 279 healthy US adults, genotyped for the lactase gene -13910G>A polymorphism (rs4988235) by matching ASA24-reported foods to foods in the Nutrition Coordinating Center Food and Nutrient Database. Analysis of covariance was used to identify whether the A genotype (LP) influenced lactose and total dairy consumption, with total energy intake and weight as covariates. The 16S rRNA V4/V5 region, amplified from bacterial DNA extracted from each frozen stool sample, was sequenced using Illumina MiSeq (300 bp paired-end) and analyzed using Quantitative Insights Into Microbial Ecology (QIIME)2 (version 2019.10). Differential abundances of bacterial taxa were analyzed using DESeq2 likelihood ratio tests.

RESULTS

Across a diverse set of ethnicities, LP subjects consumed more lactose than LNP subjects. Lactobacillaceae abundance was highest in LNP subjects who consumed more than 12.46 g/d (upper tercile). Within Caucasians and Hispanics, family Lachnospiraceae was significantly enriched in the gut microbiota of LNP individuals consuming the upper tercile of lactose across both sexes.

CONCLUSIONS

Elevated lactose consumption in individuals with the LNP genotype is associated with increased abundance of family Lactobacillaceae and Lachnospriaceae, taxa that contain multiple genera capable of utilizing lactose. This trial was registered on clinicaltrials.gov as NCT02367287.

Creation of a milk oligosaccharide database, MilkOligoDB, reveals common structural motifs and extensive diversity across mammals

The carbohydrate fraction of most mammalian milks contains a variety of oligosaccharides that encompass a range of structures and monosaccharide compositions. Human milk oligosaccharides have received considerable attention due to their biological roles in neonatal gut microbiota, immunomodulation, and brain development. However, a major challenge in understanding the biology of milk oligosaccharides across other mammals is that reports span more than 5 decades of publications with varying data reporting methods. In the present study, publications on milk oligosaccharide profiles were identified and harmonized into a standardized format to create a comprehensive, machine-readable database of milk oligosaccharides across mammalian species. The resulting database, MilkOligoDB, includes 3193 entries for 783 unique oligosaccharide structures from the milk of 77 different species harvested from 113 publications. Cross-species and cross-publication comparisons of milk oligosaccharide profiles reveal common structural motifs within mammalian orders. Of the species studied, only chimpanzees, bonobos, and Asian elephants share the specific combination of fucosylation, sialylation, and core structures that are characteristic of human milk oligosaccharides. However, agriculturally important species do produce diverse oligosaccharides that may be valuable for human supplementation. Overall, MilkOligoDB facilitates cross-species and cross-publication comparisons of milk oligosaccharide profiles and the generation of new data-driven hypotheses for future research.

Associations among Milk Microbiota, Milk Fatty Acids, Milk Glycans, and Inflammation from Lactating Holstein Cows

Milk oligosaccharides (MOs) can be prebiotic and antiadhesive, while fatty acids (MFAs) can be antimicrobial. Both have been associated with milk microbes or mammary gland inflammation in humans. Relationships between these milk components and milk microbes or inflammation have not been determined for cows and could help elucidate a novel approach for the dairy industry to promote desired milk microbial composition for improvement of milk quality and reduction of milk waste. We aimed to determine relationships among milk microbiota, MFAs, MOs, lactose, and somatic cell counts (SCC) from Holstein cows, using our previously published data. Raw milk samples were collected at three time points, ranging from early to late lactation. Data were analyzed using linear mixed-effects modeling and repeated-measures correlation. Unsaturated MFA and short-chain MFA had mostly negative relationships with potentially pathogenic genera, including Corynebacterium, Pseudomonas, and an unknown Enterobacteriaceae genus but numerous positive relationships with symbionts Bifidobacterium and Bacteroides. Conversely, many MOs were positively correlated with potentially pathogenic genera (e.g., Corynebacterium, Enterococcus, and Pseudomonas), and numerous MOs were negatively correlated with the symbiont Bifidobacterium. The neutral, nonfucosylated MO composed of eight hexoses had a positive relationship with SCC, while lactose had a negative relationship with SCC. One interpretation of these trends might be that in milk, MFAs disrupt primarily pathogenic bacterial cells, causing a relative increase in abundance of beneficial microbial taxa, while MOs respond to and act on pathogenic taxa primarily through antiadhesive methods. Further research is needed to confirm the potential mechanisms driving these correlations. IMPORTANCE Bovine milk can harbor microbes that cause mastitis, milk spoilage, and foodborne illness. Fatty acids found in milk can be antimicrobial and milk oligosaccharides can have antiadhesive, prebiotic, and immune-modulatory effects. Relationships among milk microbes, fatty acids, oligosaccharides, and inflammation have been reported for humans. To our knowledge, associations among the milk microbial composition, fatty acids, oligosaccharides, and lactose have not been reported for healthy lactating cows. Identifying these potential relationships in bovine milk will inform future efforts to characterize direct and indirect interactions of the milk components with the milk microbiota. Since many milk components are associated with herd management practices, determining if these milk components impact milk microbes may provide valuable information for dairy cow management and breeding practices aimed at minimizing harmful and spoilage-causing microbes in raw milk.

Dietary Intake of Monosaccharides from Foods is Associated with Characteristics of the Gut Microbiota and Gastrointestinal Inflammation in Healthy US Adults

BACKGROUND

Current assessment of dietary carbohydrates does not adequately reflect the nutritional properties and effects on gut microbial structure and function. Deeper characterization of food carbohydrate composition can serve to strengthen the link between diet and gastrointestinal health outcomes.

OBJECTIVES

The present study aims to characterize the monosaccharide composition of diets in a healthy US adult cohort and use these features to assess the relationship between monosaccharide intake, diet quality, characteristics of the gut microbiota, and gastrointestinal inflammation.

METHODS

This observational, cross-sectional study enrolled males and females across age (18-33 y, 34-49 y, and 50-65 y) and body mass index (normal, 18.5-24.99 kg/m2; overweight, 25-29.99 kg/m2; and obese, 30-44 kg/m2) categories. Recent dietary intake was assessed by the automated self-administered 24-h dietary recall system, and gut microbiota were assessed with shotgun metagenome sequencing. Dietary recalls were mapped to the Davis Food Glycopedia to estimate monosaccharide intake. Participants with >75% of carbohydrate intake mappable to the glycopedia were included (N = 180).

RESULTS

Diversity of monosaccharide intake was positively associated with the total Healthy Eating Index score (Pearson's r = 0.520, P = 1.2 × 10-13) and negatively associated with fecal neopterin (Pearson's r = -0.247, P = 3.0 × 10-3). Comparing high with low intake of specific monosaccharides revealed differentially abundant taxa (Wald test, P < 0.05), which was associated with the functional capacity to break down these monomers (Wilcoxon rank-sum test, P < 0.05).

CONCLUSIONS

Monosaccharide intake was associated with diet quality, gut microbial diversity, microbial metabolism, and gastrointestinal inflammation in healthy adults. As specific food sources were rich in particular monosaccharides, it may be possible in the future to tailor diets to fine-tune the gut microbiota and gastrointestinal function. This trial is registered at www.

CLINICALTRIALS

gov as NCT02367287.

A Low-Starch and High-Fiber Diet Intervention Impacts the Microbial Community of Raw Bovine Milk

Background

A more sustainable dairy cow diet was designed that minimizes use of feed components digestible by monogastric animals by increasing the quantity of forages.

Objectives

This study determined if feeding lactating cows the more sustainable, low-starch and high-fiber (LSHF) diet was associated with changes in raw milk microbiota composition and somatic cell count (SCC).

Methods

In a crossover design, 76 lactating Holstein cows were assigned to an LSHF diet or a high-starch and low-fiber (HSLF) diet, similar to common dairy cow diets in the United States, for 10 wk then placed on the opposite diet for 10 wk. The LSHF diet contained greater quantities of forages, beet pulp, and corn distillers' grain, but contained less canola meal and no high-moisture corn compared with the HSLF diet. Raw milk samples were collected from each cow 4-5 d before intervention and 5 wk into each diet treatment. Within 4 d, additional milk samples were collected for measurement of SCC using Fossmatic 7. The microbial community was determined by sequencing the 16S rRNA gene V4-V5 region and analyzing sequences with QIIME2. After quality filtering, 53 cows remained.

Results

Raw milk microbial communities differed by diet and time. Taxa associated with fiber consumption, such as Lachnospiraceae, Lactobacillus, Bacteroides, and Methanobrevibacter, were enriched with the LSHF diet. Meanwhile, taxa associated with mastitis, such as Pseudomonas, Stenotrophomonas, and Enterobacteriaceae, were enriched with the HSLF diet. Relatedly, an interaction of diet and time was found to impact SCC.

Conclusions

In raw milk, consumption of an LSHF diet compared with an HSLF diet was associated with changes in abundance of microbes previously associated with fiber consumption, udder health, and milk spoilage. Further research is needed to determine if an LSHF diet indeed leads to lower rates of mastitis and milk spoilage, which could benefit the dairy industry.

Dietary Fiber to Starch Ratio Affects Bovine Milk Oligosaccharide Profiles

Background

Bovine milk oligosaccharides (BMOs) have several demonstrated and hypothesized benefits including roles in cognitive development and antipathogenic activities, making them promising ingredients for infant formulas and nutraceutical applications. BMO extraction from bovine milk is challenged by low concentrations relative to nonbioactive simple sugars like lactose. BMO abundances are known to vary with a cow's lactation stage, breed, and parity, but these characteristics are difficult to modify in existing dairy herds. In contrast, diet modification is an accessible target, and is already known to influence milk yield, lipid content, protein levels, and monosaccharide compositions.

Objectives

To determine the impact of a low starch high fiber versus a high starch low fiber diet on overall BMO profiles and individual BMO abundances in Holstein dairy cattle.

Methods

Milk samples were collected from 59 midlactation Holsteins in a crossover study featuring dietary modification with either a low starch high fiber or high starch low fiber feed. BMO profiles were evaluated by nano-LC quadrupole time-of-flight tandem MS, and differences in BMO abundances between diets were evaluated using linear mixed effects modeling.

Results

A total of 19 BMOs were identified across the sample set, including 4 large fucosylated compounds. Seven BMOs were found to have significantly more positive percent changes in yield-adjusted abundance from the pre-experiment baseline period for milk samples collected during feeding with the low starch high fiber diet compared with the high starch low fiber diet.

Conclusions

Consuming the low starch high fiber diet promoted greater overall BMO production than the high starch low fiber diet in a population of midlactation Holsteins. Additionally, this study afforded the opportunity to investigate the impact of other factors potentially influencing BMO abundances, furthering understanding of how dairy herd management practices can positively impact milk composition and support the potential use of BMOs as functional ingredients.

Tree-Based Analysis of Dietary Diversity Captures Associations Between Fiber Intake and Gut Microbiota Composition in a Healthy US Adult Cohort

BACKGROUND

Diet patterns are a significant and modifiable contributing factor to the composition of the human gut microbiota.

OBJECTIVES

We set out to identify reproducible relationships between diet and gut microbial community composition in a diverse, healthy US adult cohort.

METHODS

We collected 2 to 3 automated self-administered 24-hour dietary recalls over 10-14 days, together with a single stool sample, from 343 healthy adults in a cross-sectional phenotyping study. This study examined a multi-ethnic cohort balanced for age (18-65 years), sex, and BMI (18.5-45 kg/m2). Dietary data were edited to a tree format according to published methods. The tree structure was annotated with the average total grams of dry weight, fat, protein, carbohydrate, or fiber from each food item reported. The alpha and beta diversity measurements, calculated using the tree structure, were analyzed relative to the microbial community diversity, determined by a Quantitative Insights Into Microbial Ecology (QIIME) 2 analysis of the bacterial 16S ribosomal RNA V4 region, sequenced from stool samples. K-means clustering was used to form groups of individuals consuming similar diets, and gut microbial communities were compared among groups using differential expression analysis for sequence count data.

RESULTS

The alpha diversity of diet dry weight was significantly correlated with the gut microbial community alpha diversity (r = 0.171). The correlation improved when diet was characterized using grams of carbohydrates (r = 0.186) or fiber (r = 0.213). Bifidobacterium was enriched with diets containing higher levels of total carbohydrate from cooked grains. Lachnospira, was enriched with diet patterns containing high consumption of fiber from fruits excluding berries.

CONCLUSIONS

The tree structure, annotated with grams of carbohydrate, is a robust analysis method for comparing self-reported diet to the gut microbial community composition. This method identified consumption of fiber from fruit robustly associated with an abundance of pectinolytic bacterial genus, Lachnospira, in the guts of healthy adults. This trial was registered at clinicaltrials.gov as NCT02367287.

Unique Transcriptomic Changes Underlie Hormonal Interactions During Mammary Histomorphogenesis in Female Pigs

Successful lactation and the risk for developing breast cancer depend on growth and differentiation of the mammary gland (MG) epithelium that is regulated by ovarian steroids (17β-estradiol [E] and progesterone [P]) and pituitary-derived prolactin (PRL). Given that the MG of pigs share histomorphogenic features present in the normal human breast, we sought to define the transcriptional responses within the MG of pigs following exposure to all combinations of these hormones. Hormone-ablated female pigs were administered combinations of E, medroxyprogesterone 17-acetate (source of P), and either haloperidol (to induce PRL) or 2-bromo-α-ergocryptine. We subsequently monitored phenotypic changes in the MG including mitosis, receptors for E and P (ESR1 and PGR), level of phosphorylated STAT5 (pSTAT5), and the frequency of terminal ductal lobular unit (TDLU) subtypes; these changes were then associated with all transcriptomic changes. Estrogen altered the expression of approximately 20% of all genes that were mostly associated with mitosis, whereas PRL stimulated elements of fatty acid metabolism and an inflammatory response. Several outcomes, including increased pSTAT5, highlighted the ability of E to enhance PRL action. Regression of transcriptomic changes against several MG phenotypes revealed 1669 genes correlated with proliferation, among which 29 were E inducible. Additional gene expression signatures were associated with TDLU formation and the frequency of ESR1 or PGR. These data provide a link between the hormone-regulated genome and phenome of the MG in a species having a complex histoarchitecture like that in the human breast, and highlight an underexplored synergy between the actions of E and PRL during MG development.

Machine Learning Identifies Stool pH as a Predictor of Bone Mineral Density in Healthy Multiethnic US Adults

BACKGROUND

A variety of modifiable and nonmodifiable factors such as ethnicity, age, and diet have been shown to influence bone health. Previous studies are usually limited to analyses focused on the association of a few a priori variables or on a specific subset of the population.

OBJECTIVE

Dietary, physiological, and lifestyle data were used to identify directly modifiable and nonmodifiable variables predictive of bone mineral content (BMC) and bone mineral density (BMD) in healthy US men and women using machine-learning models.

METHODS

Ridge, lasso, elastic net, and random forest models were used to predict whole-body, femoral neck, and spine BMC and BMD in healthy US men and women ages 18-66 y, with a BMI (kg/m2) of 18-44 (n = 313), using nonmodifiable anthropometric, physiological, and demographic variables; directly modifiable lifestyle (physical activity, tobacco use) and dietary (via FFQ) variables; and variables approximating directly modifiable behavior (circulating 25-hydroxycholecalciferol and stool pH).

RESULTS

Machine-learning models using nonmodifiable variables explained more variation in BMC and BMD (highest R2 = 0.75) compared with when using only directly modifiable variables (highest R2 = 0.11). Machine-learning models had better performance compared with multivariate linear regression, which had lower predictive value (highest R2 = 0.06) when using directly modifiable variables only. BMI, body fat percentage, height, and menstruation history were predictors of BMC and BMD. For directly modifiable features, betaine, cholesterol, hydroxyproline, menaquinone-4, dihydrophylloquinone, eggs, cheese, cured meat, refined grains, fruit juice, and alcohol consumption were predictors of BMC and BMD. Low stool pH, a proxy for fermentable fiber intake, was also predictive of higher BMC and BMD.

CONCLUSIONS

Modifiable factors, such as diet, explained less variation in the data compared with nonmodifiable factors, such as age, sex, and ethnicity, in healthy US men and women. Low stool pH predicted higher BMC and BMD. This trial was registered at www.clinicaltrials.gov as NCT02367287.

Technician-Scored Stool Consistency Spans the Full Range of the Bristol Scale in a Healthy US Population and Differs by Diet and Chronic Stress Load

BACKGROUND

Prior studies of adults with constipation or diarrhea suggest that dietary intake, physical activity, and stress may affect stool consistency. However, the influence of these factors is unresolved and has not been investigated in healthy adults.

OBJECTIVES

We assessed the relations of technician-scored stool consistency in healthy adults with self-reported diet, objectively monitored physical activity, and quantifiable markers of stress.

METHODS

Stool consistency was scored by an independent technician using the Bristol Stool Form Scale (BSFS) to analyze samples provided by healthy adults, aged 18-65 y, BMI 18-44 kg/m2, in the USDA Nutritional Phenotyping Study (n = 364). A subset of participants (n = 109) were also asked to rate their sample using the BSFS. Dietary intake was assessed with two to three 24-h recalls completed at home and energy expenditure from physical activity was monitored using an accelerometer in the 7-d period preceding the stool collection. Stress was measured using the Wheaton Chronic Stress Inventory and allostatic load (AL). Statistical and machine learning analyses were conducted to determine which dietary, physiological, lifestyle, and stress factors differed by stool form.

RESULTS

Technician-scored BSFS scores were significantly further (P = 0.003) from the central score (mean ± SEM distance: 1.41 ± 0.089) than the self-reported score (1.06 ± 0.086). Hard stool was associated with higher (P = 0.005) intake of saturated fat (13.8 ± 0.40 g/1000 kcal) than was normal stool (12.5 ± 0.30 g/1000 kcal). AL scores were lower for normal stool (2.49 ± 0.15) than for hard (3.07 ± 0.18) (P = 0.009) or soft stool (2.89 ± 0.18) (P = 0.049). Machine learning analyses revealed that various dietary components, physiological characteristics, and stress hormones predicted stool consistency.

CONCLUSIONS

Technician-scored stool consistency differed by dietary intake and stress hormones, but not by physical activity, in healthy adults.This trial was registered at clincialtrials.gov as NCT02367287.

Effect of Manual Data Cleaning on Nutrient Intakes Using the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24)

BACKGROUND

Automated dietary assessment tools such as ASA24® are useful for collecting 24-hour recall data in large-scale studies. Modifications made during manual data cleaning may affect nutrient intakes.

OBJECTIVES

We evaluated the effects of modifications made during manual data cleaning on nutrient intakes of interest: energy, carbohydrate, total fat, protein, and fiber.

METHODS

Differences in mean intake before and after data cleaning modifications for all recalls and average intakes per subject were analyzed by paired t-tests. The Chi-squared test was used to determine whether unsupervised recalls had more open-ended text responses that required modification than supervised recalls. We characterized food types of text response modifications. Correlations between predictive energy requirements, measured total energy expenditure (TEE), and mean energy intake from raw and modified data were examined.

RESULTS

After excluding 11 recalls with invalidating technical errors, 1499 valid recalls completed by 393 subjects were included in this analysis. We found significant differences before and after modifications for energy, carbohydrate, total fat, and protein intakes for all recalls (P < 0.05). Limiting to modified recalls, there were significant differences for all nutrients of interest, including fiber (P < 0.02). There was not a significantly greater proportion of text responses requiring modification for home compared with supervised recalls (P = 0.271). Predicted energy requirements correlated highly with TEE. There was no significant difference in correlation of mean energy intake with TEE for modified compared with raw data. Mean intake for individual subjects was significantly different for energy, protein, and fat intakes following cleaning modifications (P < 0.001).

CONCLUSIONS

Manual modifications can change mean nutrient intakes for an entire cohort and individuals. However, modifications did not significantly affect the correlation of energy intake with predictive requirements and measured expenditure. Investigators can consider their research question and nutrients of interest when deciding to make cleaning modifications.

Association of the Lactase Persistence Haplotype Block With Disease Risk in Populations of European Descent

Among people of European descent, the ability to digest lactose into adulthood arose via strong positive selection of a highly advantageous allele encompassing the lactase gene. Lactose-tolerant and intolerant individuals may have different disease risks due to the shared genetics of their haplotype block. Therefore, the overall objective of the study was to assess the genetic association of the lactase persistence haplotype to disease risk. Using data from the 1000Genomes project, we estimated the size of the lactase persistence haplotype block to be 1.9 Mbp containing up to 9 protein-coding genes and a microRNA. Based on the function of the genes and microRNA, we studied health phenotypes likely to be impacted by the lactase persistence allele: prostate cancer status, cardiovascular disease status, and bone mineral density. We used summary statistics from large genome-wide metanalyses—32,965 bone mineral density, 140,306 prostate cancer and 184,305 coronary artery disease subjects—to evaluate whether the lactase persistence allele was associated with these disease phenotypes. Despite the fact that previous work demonstrated that the lactase persistence haplotype block harbors increased deleterious mutations, these results suggest little effect on the studied disease phenotypes.

Reservoirs of antimicrobial resistance genes in retail raw milk

BACKGROUND

It has been estimated that at least 3% of the USA population consumes unpasteurized (raw) milk from animal sources, and the demand to legalize raw milk sales continues to increase. However, consumption of raw milk can cause foodborne illness and be a source of bacteria containing transferrable antimicrobial resistance genes (ARGs). To obtain a comprehensive understanding of the microbiome and antibiotic resistome in both raw and processed milk, we systematically analyzed 2034 retail milk samples including unpasteurized milk and pasteurized milk via vat pasteurization, high-temperature-short-time pasteurization, and ultra-pasteurization from the United States using complementary culture-based, 16S rRNA gene, and metagenomic sequencing techniques.

RESULTS

Raw milk samples had the highest prevalence of viable bacteria which were measured as all aerobic bacteria, coliform, and Escherichia coli counts, and their microbiota was distinct from other types of milk. 16S rRNA gene sequencing revealed that Pseudomonadaceae dominated raw milk with limited levels of lactic acid bacteria. Among all milk samples, the microbiota remained stable with constant bacterial populations when stored at 4 °C. In contrast, storage at room temperature dramatically enriched the bacterial populations present in raw milk samples and, in parallel, significantly increased the richness and abundance of ARGs. Metagenomic sequencing indicated raw milk possessed dramatically more ARGs than pasteurized milk, and a conjugation assay documented the active transfer of blaCMY-2, one ceftazidime resistance gene present in raw milk-borne E. coli, across bacterial species. The room temperature-enriched resistome differed in raw milk from distinct geographic locations, a difference likely associated with regionally distinct milk microbiota.

CONCLUSION

Despite advertised "probiotic" effects, our results indicate that raw milk microbiota has minimal lactic acid bacteria. In addition, retail raw milk serves as a reservoir of ARGs, populations of which are readily amplified by spontaneous fermentation. There is an increased need to understand potential food safety risks from improper transportation and storage of raw milk with regard to ARGs. Video Abstract.

Pre- and post-sequencing recommendations for functional annotation of human fecal metagenomes

Background

Shotgun metagenomes are often assembled prior to annotation of genes which biases the functional capacity of a community towards its most abundant members. For an unbiased assessment of community function, short reads need to be mapped directly to a gene or protein database. The ability to detect genes in short read sequences is dependent on pre- and post-sequencing decisions. The objective of the current study was to determine how library size selection, read length and format, protein database, e-value threshold, and sequencing depth impact gene-centric analysis of human fecal microbiomes when using DIAMOND, an alignment tool that is up to 20,000 times faster than BLASTX.

Results

Using metagenomes simulated from a database of experimentally verified protein sequences, we find that read length, e-value threshold, and the choice of protein database dramatically impact detection of a known target, with best performance achieved with longer reads, stricter e-value thresholds, and a custom database. Using publicly available metagenomes, we evaluated library size selection, paired end read strategy, and sequencing depth. Longer read lengths were acheivable by merging paired ends when the sequencing library was size-selected to enable overlaps. When paired ends could not be merged, a congruent strategy in which both ends are independently mapped was acceptable. Sequencing depths of 5 million merged reads minimized the error of abundance estimates of specific target genes, including an antimicrobial resistance gene.

Conclusions

Shotgun metagenomes of DNA extracted from human fecal samples sequenced using the Illumina platform should be size-selected to enable merging of paired end reads and should be sequenced in the PE150 format with a minimum sequencing depth of 5 million merge-able reads to enable detection of specific target genes. Expecting the merged reads to be 180-250 bp in length, the appropriate e-value threshold for DIAMOND would then need to be more strict than the default. Accurate and interpretable results for specific hypotheses will be best obtained using small databases customized for the research question.

Fecal metatranscriptomics and glycomics suggest that bovine milk oligosaccharides are fully utilized by healthy adults

Human milk oligosaccharides play a vital role in the development of the gut microbiome in the human infant. Although oligosaccharides derived from bovine milk (BMO) differ in content and profile with those derived from human milk (HMO), several oligosaccharide structures are shared between the species. BMO are commercial alternatives to HMO, but their fate in the digestive tract of healthy adult consumers is unknown. Healthy human subjects consumed two BMO doses over 11-day periods each and provided fecal samples. Metatranscriptomics of fecal samples were conducted to determine microbial and host gene expression in response to the supplement. Fecal samples were also analyzed by mass spectrometry to determine levels of undigested BMO. No changes were observed in microbial gene expression across all participants. Repeated sampling enabled subject-specific analyses: four of six participants had minor, yet statistically significant, changes in microbial gene expression. No significant change was observed in the gene expression of host cells exfoliated in stool. Levels of BMO excreted in feces after supplementation were not significantly different from baseline and were not correlated with dosage or expressed microbial enzyme levels. Collectively, these data suggest that BMO are fully fermented in the human gastrointestinal tract upstream of the distal colon. Additionally, the unaltered host transcriptome provides further evidence for the safety of BMO as a dietary supplement or food ingredient. Further research is needed to investigate potential health benefits of this completely fermentable prebiotic that naturally occurs in cow's milk.

Nutrient Estimation from 24-Hour Food Recalls Using Machine Learning and Database Mapping: A Case Study with Lactose

The Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a free dietary recall system that outputs fewer nutrients than the Nutrition Data System for Research (NDSR). NDSR uses the Nutrition Coordinating Center (NCC) Food and Nutrient Database, both of which require a license. Manual lookup of ASA24 foods into NDSR is time-consuming but currently the only way to acquire NCC-exclusive nutrients. Using lactose as an example, we evaluated machine learning and database matching methods to estimate this NCC-exclusive nutrient from ASA24 reports. ASA24-reported foods were manually looked up into NDSR to obtain lactose estimates and split into training (n = 378) and test (n = 189) datasets. Nine machine learning models were developed to predict lactose from the nutrients common between ASA24 and the NCC database. Database matching algorithms were developed to match NCC foods to an ASA24 food using only nutrients ("Nutrient-Only") or the nutrient and food descriptions ("Nutrient + Text"). For both methods, the lactose values were compared to the manual curation. Among machine learning models, the XGB-Regressor model performed best on held-out test data (R2 = 0.33). For the database matching method, Nutrient + Text matching yielded the best lactose estimates (R2 = 0.76), a vast improvement over the status quo of no estimate. These results suggest that computational methods can successfully estimate an NCC-exclusive nutrient for foods reported in ASA24.

The fecal resistome of dairy cattle is associated with diet during nursing

Antimicrobial resistance is a global public health concern, and livestock play a significant role in selecting for resistance and maintaining such reservoirs. Here we study the succession of dairy cattle resistome during early life using metagenomic sequencing, as well as the relationship between resistome, gut microbiota, and diet. In our dataset, the gut of dairy calves serves as a reservoir of 329 antimicrobial resistance genes (ARGs) presumably conferring resistance to 17 classes of antibiotics, and the abundance of ARGs declines gradually during nursing. ARGs appear to co-occur with antibacterial biocide or metal resistance genes. Colostrum is a potential source of ARGs observed in calves at day 2. The dynamic changes in the resistome are likely a result of gut microbiota assembly, which is closely associated with diet transition in dairy calves. Modifications in the resistome may be possible via early-life dietary interventions to reduce overall antimicrobial resistance.

Association of Lactase Persistence Genotypes (rs4988235) and Ethnicity with Dairy Intake in a Healthy U.S. Population

Lactase persistence (LP) is a trait in which lactose can be digested throughout adulthood, while lactase non-persistence (LNP) can cause lactose intolerance and influence dairy consumption. One single nucleotide polymorphism (SNP ID: rs4988235) is often used as a predictor for dairy intake, since it is responsible for LP in people in European descent, and can occur in other ethnic groups. The objective of this study was to determine whether rs4988235 genotypes and ethnicity influence reported dairy consumption in the United States (U.S.). A food frequency questionnaire (FFQ) and multiple Automated Self-Administered 24-h recalls (ASA24®) were used to measure habitual and recent intake, respectively, of total dairy, cheese, cow's milk, plant-based alternative milk, and yogurt in a multi-ethnic U.S. cohort genotyped for rs4988235. Within Caucasian subjects, LP individuals reported consuming more recent total dairy and habitual total cow's milk intake. For subjects of all ethnicities, LP individuals consumed more cheese (FFQ p = 0.043, ASA24 p = 0.012) and recent total dairy (ASA24 p = 0.005). For both dietary assessments, Caucasians consumed more cheese than all non-Caucasians (FFQ p = 0.036, ASA24 p = 0.002) independent of genotype, as well as more recent intake of yogurt (ASA24 p = 0.042). LP subjects consumed more total cow's milk than LNP, but only when accounting for whether subjects were Caucasian or not (FFQ p = 0.015). Fluid milk and alternative plant-based milk consumption were not associated with genotypes or ethnicity. Our results show that both LP genotype and ethnicity influence the intake of some dairy products in a multi-ethnic U.S. cohort, but the ability of rs4988235 genotypes to predict intake may depend on ethnic background, the specific dairy product, and whether intake is reported on a habitual or recent basis. Therefore, ethnicity and the dietary assessment method should also be considered when determining the suitability of rs4988235 as a proxy for dairy intake.

Temporal changes in postprandial blood transcriptomes reveal subject-specific pattern of expression of innate immunity genes after a high-fat meal

White blood cells are among the first responders to dietary components and their metabolites absorbed from the gut. The objective of this study was to determine the whole blood transcriptome response to high-fat challenge meals. A total of 45 fasting and postprandial (3-h and 6-h) whole blood transcriptomes from 5 subjects in a crossover intervention trial of a high-fat meal supplemented with placebo, blueberry powder or docosahexaenoic acid (DHA) were analyzed using RNA sequencing. Select target genes were validated by quantitative reverse-transcription polymerase chain reaction in 180 samples from 20 subjects. The largest contributor to variance was the subject (13,856 genes differentially expressed), followed by the subject on a specific day (2276 genes), followed by the subject's postprandial response (651 genes). After determining the nonsignificance of individual dietary treatments (blueberry, DHA, placebo), treatments were used as replicates to examine postprandial responses to a high-fat meal. The universal postprandial response (95 genes) was associated with lipid utilization, fatty acid beta-oxidation and circadian rhythms. Subject-specific postprandial responses were enriched for genes involved in the innate immune response, particularly those of pattern recognition receptors and their downstream signaling components. Genes involved in innate immune responses are differentially expressed in a subject-specific and time-dependent manner in response to the high-fat meals. These genes can serve as biomarkers to assess individual responsiveness to a high-fat diet in inducing postprandial inflammation. Furthermore, the dynamic temporal change in gene expression in postprandial blood suggests that monitoring these genes at multiple time points is necessary to reveal responders to dietary intervention.

Fecal metatranscriptomics of macaques with idiopathic chronic diarrhea reveals altered mucin degradation and fucose utilization

BACKGROUND

Idiopathic chronic diarrhea (ICD) is a common cause of morbidity and mortality among juvenile rhesus macaques. Characterized by chronic inflammation of the colon and repeated bouts of diarrhea, ICD is largely unresponsive to medical interventions, including corticosteroid, antiparasitic, and antibiotic treatments. Although ICD is accompanied by large disruptions in the composition of the commensal gut microbiome, no single pathogen has been concretely identified as responsible for the onset and continuation of the disease.

RESULTS

Fecal samples were collected from 12 ICD-diagnosed macaques and 12 age- and sex-matched controls. RNA was extracted for metatranscriptomic analysis of organisms and functional annotations associated with the gut microbiome. Bacterial, fungal, archaeal, protozoan, and macaque (host) transcripts were simultaneously assessed. ICD-afflicted animals were characterized by increased expression of host-derived genes involved in inflammation and increased transcripts from bacterial pathogens such as Campylobacter and Helicobacter and the protozoan Trichomonas. Transcripts associated with known mucin-degrading organisms and mucin-degrading enzymes were elevated in the fecal microbiomes of ICD-afflicted animals. Assessment of colon sections using immunohistochemistry and of the host transcriptome suggests differential fucosylation of mucins between control and ICD-afflicted animals. Interrogation of the metatranscriptome for fucose utilization genes reveals possible mechanisms by which opportunists persist in ICD. Bacteroides sp. potentially cross-fed fucose to Haemophilus whereas Campylobacter expressed a mucosa-associated transcriptome with increased expression of adherence genes.

CONCLUSIONS

The simultaneous profiling of bacterial, fungal, archaeal, protozoan, and macaque transcripts from stool samples reveals that ICD of rhesus macaques is associated with increased gene expression by pathogens, increased mucin degradation, and altered fucose utilization. The data suggest that the ICD-afflicted host produces fucosylated mucins that are leveraged by potentially pathogenic microbes as a carbon source or as adhesion sites.

Pilot study of probiotic/colostrum supplementation on gut function in children with autism and gastrointestinal symptoms

Over half of all children with autism spectrum disorders (ASD) have gastrointestinal (GI) co-morbidities including chronic constipation, diarrhea, and irritable bowel syndrome. The severity of these symptoms has been correlated with the degree of GI microbial dysbiosis. The study objective was to assess tolerability of a probiotic (Bifidobacterium infantis) in combination with a bovine colostrum product (BCP) as a source of prebiotic oligosaccharides and to evaluate GI, microbiome and immune factors in children with ASD and GI co-morbidities. This pilot study is a randomized, double blind, controlled trial of combination treatment (BCP + B. infantis) vs. BCP alone in a cross-over study in children ages 2-11 with ASD and GI co-morbidities (n = 8). This 12-week study included 5 weeks of probiotic-prebiotic supplementation, followed by a two-week washout period, and 5 weeks of prebiotic only supplementation. The primary outcome of tolerability was assessed using validated questionnaires of GI function and atypical behaviors, along with side effects. Results suggest that the combination treatment is well-tolerated in this cohort. The most common side effect was mild gassiness. Some participants on both treatments saw a reduction in the frequency of certain GI symptoms, as well as reduced occurrence of particular aberrant behaviors. Improvement may be explained by a reduction in IL-13 and TNF-α production in some participants. Although limited conclusions can be drawn from this small pilot study, the results support the need for further research into the efficacy of these treatments.

SAMSA2: a standalone metatranscriptome analysis pipeline

Background

Complex microbial communities are an area of growing interest in biology. Metatranscriptomics allows researchers to quantify microbial gene expression in an environmental sample via high-throughput sequencing. Metatranscriptomic experiments are computationally intensive because the experiments generate a large volume of sequence data and each sequence must be compared with reference sequences from thousands of organisms.

Results

SAMSA2 is an upgrade to the original Simple Annotation of Metatranscriptomes by Sequence Analysis (SAMSA) pipeline that has been redesigned for standalone use on a supercomputing cluster. SAMSA2 is faster due to the use of the DIAMOND aligner, and more flexible and reproducible because it uses local databases. SAMSA2 is available with detailed documentation, and example input and output files along with examples of master scripts for full pipeline execution.

Conclusions

SAMSA2 is a rapid and efficient metatranscriptome pipeline for analyzing large RNA-seq datasets in a supercomputing cluster environment. SAMSA2 provides simplified output that can be examined directly or used for further analyses, and its reference databases may be upgraded, altered or customized to fit the needs of any experiment.

The Transcriptome of Estrogen-Independent Mammary Growth in Female Mice Reveals That Not All Mammary Glands Are Created Equally

Allometric growth of ducts in the mammary glands (MGs) is widely held to be estrogen dependent. We previously discovered that the dietary fatty acid trans-10, cis-12 conjugated linoleic acid (CLA) stimulates estrogen-independent allometric growth and terminal end bud formation in ovariectomized mice. Given the similar phenotype induced by estrogen and CLA, we investigated the shared and/or divergent mechanisms underlying these changes. We confirmed MG growth induced by CLA is temporally distinct from that elicited by estrogen. We then used RNA sequencing to compare the transcriptome of the MG during similar proliferative and morphological states. Both estrogen and CLA affected the genes involved in proliferation. The transcriptome for estrogen-treated mice included canonical estrogen-induced genes, including Pgr, Areg, and Foxa1. In contrast, their expression was unchanged by CLA. However, CLA, but not estrogen, altered expression of a unique set of inflammation-associated genes, consistent with stromal changes. This CLA-altered signature included increased expression of epidermal growth factor receptor (EGFR) pathway components, consistent with the demonstration that CLA-induced MG growth is EGFR dependent. Our findings highlight a unique role for diet-induced inflammation that underlies estrogen-independent MG development.

SAMSA: a comprehensive metatranscriptome analysis pipeline

BACKGROUND

Although metatranscriptomics-the study of diverse microbial population activity based on RNA-seq data-is rapidly growing in popularity, there are limited options for biologists to analyze this type of data. Current approaches for processing metatranscriptomes rely on restricted databases and a dedicated computing cluster, or metagenome-based approaches that have not been fully evaluated for processing metatranscriptomic datasets. We created a new bioinformatics pipeline, designed specifically for metatranscriptome dataset analysis, which runs in conjunction with Metagenome-RAST (MG-RAST) servers. Designed for use by researchers with relatively little bioinformatics experience, SAMSA offers a breakdown of metatranscriptome transcription activity levels by organism or transcript function, and is fully open source. We used this new tool to evaluate best practices for sequencing stool metatranscriptomes.

RESULTS

Working with the MG-RAST annotation server, we constructed the Simple Annotation of Metatranscriptomes by Sequence Analysis (SAMSA) software package, a complete pipeline for the analysis of gut microbiome data. SAMSA can summarize and evaluate raw annotation results, identifying abundant species and significant functional differences between metatranscriptomes. Using pilot data and simulated subsets, we determined experimental requirements for fecal gut metatranscriptomes. Sequences need to be either long reads (longer than 100 bp) or joined paired-end reads. Each sample needs 40-50 million raw sequences, which can be expected to yield the 5-10 million annotated reads necessary for accurate abundance measures. We also demonstrated that ribosomal RNA depletion does not equally deplete ribosomes from all species within a sample, and remaining rRNA sequences should be discarded. Using publicly available metatranscriptome data in which rRNA was not depleted, we were able to demonstrate that overall organism transcriptional activity can be measured using mRNA counts. We were also able to detect significant differences between control and experimental groups in both organism transcriptional activity and specific cellular functions.

CONCLUSIONS

By making this new pipeline publicly available, we have created a powerful new tool for metatranscriptomics research, offering a new method for greater insight into the activity of diverse microbial communities. We further recommend that stool metatranscriptomes be ribodepleted and sequenced in a 100 bp paired end format with a minimum of 40 million reads per sample.

Human milk oligosaccharides in premature infants: absorption, excretion, and influence on the intestinal microbiota

BACKGROUND

Human milk oligosaccharides (HMOs) shape the intestinal microbiota in term infants. In premature infants, alterations in the intestinal microbiota (dysbiosis) are associated with risk of necrotizing enterocolitis (NEC) and sepsis, and the influence of HMOs on the microbiota is unclear.

METHODS

Milk, urine, and stool specimens from 14 mother-premature infant dyads were investigated by mass spectrometry for HMO composition. The stools were analyzed by next-generation sequencing to complement a previous analysis.

RESULTS

Percentages of fucosylated and sialylated HMOs were highly variable between individuals but similar in urine, feces, and milk within dyads. Differences in urine and fecal HMO composition suggest variability in absorption. Secretor status of the mother correlated with the urine and fecal content of specific HMO structures. Trends toward higher levels of Proteobacteria and lower levels of Firmicutes were noted in premature infants of nonsecretor mothers. Specific HMO structures in the milk, urine, and feces were associated with alterations in fecal Proteobacteria and Firmicutes.

CONCLUSION

HMOs may influence the intestinal microbiota in premature infants. Specific HMOs, for example those associated with secretor mothers, may have a protective effect by decreasing pathogens associated with sepsis and NEC, while other HMOs may increase dysbiosis in this population.

Comparative transcriptomics reveals key differences in the response to milk oligosaccharides of infant gut-associated bifidobacteria

Breast milk enhances the predominance of Bifidobacterium species in the infant gut, probably due to its large concentration of human milk oligosaccharides (HMO). Here we screened infant-gut isolates of Bifidobacterium longum subsp. infantis and Bifidobacterium bifidum using individual HMO, and compared the global transcriptomes of representative isolates on major HMO by RNA-seq. While B. infantis displayed homogeneous HMO-utilization patterns, B. bifidum were more diverse and some strains did not use fucosyllactose (FL) or sialyllactose (SL). Transcriptomes of B. bifidum SC555 and B. infantis ATCC 15697 showed that utilization of pooled HMO is similar to neutral HMO, while transcriptomes for growth on FL were more similar to lactose than HMO in B. bifidum. Genes linked to HMO-utilization were upregulated by neutral HMO and SL, but not by FL in both species. In contrast, FL induced the expression of alternative gene clusters in B. infantis. Results also suggest that B. bifidum SC555 does not utilize fucose or sialic acid from HMO. Surprisingly, expression of orthologous genes differed between both bifidobacteria even when grown on identical substrates. This study highlights two major strategies found in Bifidobacterium species to process HMO, and presents detailed information on the close relationship between HMO and infant-gut bifidobacteria.

Bifidobacteria grown on human milk oligosaccharides downregulate the expression of inflammation-related genes in Caco-2 cells

Background

Breastfed human infants are predominantly colonized by bifidobacteria that thrive on human milk oligosaccharides (HMO). Two predominant species of bifidobacteria in infant feces are Bifidobacterium breve (B. breve) and Bifidobacterium longum subsp. infantis (B. infantis), both of which include avid HMO-consumer strains. Our laboratory has previously shown that B. infantis, when grown on HMO, increases adhesion to intestinal cells and increases the expression of the anti-inflammatory cytokine interleukin-10. The purpose of the current study was to investigate the effects of carbon source—glucose, lactose, or HMO—on the ability of B. breve and B. infantis to adhere to and affect the transcription of intestinal epithelial cells on a genome-wide basis.

Results

HMO-grown B. infantis had higher percent binding to Caco-2 cell monolayers compared to B. infantis grown on glucose or lactose. B. breve had low adhesive ability regardless of carbon source. Despite differential binding ability, both HMO-grown strains significantly differentially affected the Caco-2 transcriptome compared to their glucose or lactose grown controls. HMO-grown B. breve and B. infantis both downregulated genes in Caco-2 cells associated with chemokine activity.

Conclusion

The choice of carbon source affects the interaction of bifidobacteria with intestinal epithelial cells. HMO-grown bifidobacteria reduce markers of inflammation, compared to glucose or lactose-grown bifidobacteria. In the future, the design of preventative or therapeutic probiotic supplements may need to include appropriately chosen prebiotics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-015-0508-3) contains supplementary material, which is available to authorized users.

Changes in intestinal barrier function and gut microbiota in high-fat diet-fed rats are dynamic and region dependent

A causal relationship between the pathophysiological changes in the gut epithelium and altered gut microbiota with the onset of obesity have been suggested but not defined. The aim of this study was to determine the temporal relationship between impaired intestinal barrier function and microbial dysbiosis in the small and large intestine in rodent high-fat (HF) diet-induced obesity. Rats were fed HF diet (45% fat) or normal chow (C, 10% fat) for 1, 3, or 6 wk; food intake, body weight, and adiposity were measured. Barrier function ex vivo using FITC-labeled dextran (4,000 Da, FD-4) and horseradish peroxidase (HRP) probes in Ussing chambers, gene expression, and gut microbial communities was assessed. After 1 wk, there was an immediate but reversible increase in paracellular permeability, decrease in IL-10 expression, and decrease in abundance of genera within the class Clostridia in the ileum. In the large intestine, HRP flux and abundance of genera within the order Bacteroidales increased with time on the HF diet and correlated with the onset of increased body weight and adiposity. The data show immediate insults in the ileum in response to ingestion of a HF diet, which were rapidly restored and preceded increased passage of large molecules across the large intestinal epithelium. This study provides an understanding of microbiota dysbiosis and gut pathophysiology in diet-induced obesity and has identified IL-10 and Oscillospira in the ileum and transcellular flux in the large intestine as potential early impairments in the gut that might lead to obesity and metabolic disorders.

Comparative Proteomics of Human and Macaque Milk Reveals Species-Specific Nutrition during Postnatal Development

Milk has been well established as the optimal nutrition source for infants, yet there is still much to be understood about its molecular composition. Therefore, our objective was to develop and compare comprehensive milk proteomes for human and rhesus macaques to highlight differences in neonatal nutrition. We developed a milk proteomics technique that overcomes previous technical barriers including pervasive post-translational modifications and limited sample volume. We identified 1606 and 518 proteins in human and macaque milk, respectively. During analysis of detected protein orthologs, we identified 88 differentially abundant proteins. Of these, 93% exhibited increased abundance in human milk relative to macaque and include lactoferrin, polymeric immunoglobulin receptor, alpha-1 antichymotrypsin, vitamin D-binding protein, and haptocorrin. Furthermore, proteins more abundant in human milk compared with macaque are associated with development of the gastrointestinal tract, the immune system, and the brain. Overall, our novel proteomics method reveals the first comprehensive macaque milk proteome and 524 newly identified human milk proteins. The differentially abundant proteins observed are consistent with the perspective that human infants, compared with nonhuman primates, are born at a slightly earlier stage of somatic development and require additional support through higher quantities of specific proteins to nurture human infant maturation.

Comparative genomics reveals tissue-specific regulation of prolactin receptor gene expression

Prolactin (PRL), acting via the PRL receptor (PRLR), controls hundreds of biological processes across a range of species. Endocrine PRL elicits well-documented effects on target tissues such as the mammary glands and reproductive organs in addition to coordinating whole-body homeostasis during states such as lactation or adaptive responses to the environment. While changes in PRLR expression likely facilitates these tissue-specific responses to circulating PRL, the mechanisms regulating this regulation in non-rodent species has received limited attention. We performed a wide-scale analysis of PRLR 5' transcriptional regulation in pig tissues. Apart from the abundantly expressed and widely conserved exon 1, we identified alternative splicing of transcripts from an additional nine first exons of the porcine PRLR (pPRLR) gene. Notably, exon 1.5 transcripts were expressed most abundantly in the heart, while expression of exon 1.3-containing transcripts was greatest in the kidneys and small intestine. Expression of exon 1.3 mRNAs within the kidneys was most abundant in the renal cortex, and increased during gestation. A comparative analysis revealed a human homologue to exon 1.3, hE1N2, which was also principally transcribed in the kidneys and small intestines, and an exon hE1N3 was only expressed in the kidneys of humans. Promoter alignment revealed conserved motifs within the proximal promoter upstream of exon 1.3, including putative binding sites for hepatocyte nuclear factor-1 and Sp1. Together, these results highlight the diverse, conserved and tissue-specific regulation of PRLR expression in the targets for PRL, which may function to coordinate complex physiological states such as lactation and osmoregulation.

Maternal fucosyltransferase 2 status affects the gut bifidobacterial communities of breastfed infants

BACKGROUND

Individuals with inactive alleles of the fucosyltransferase 2 gene (FUT2; termed the 'secretor' gene) are common in many populations. Some members of the genus Bifidobacterium, common infant gut commensals, are known to consume 2'-fucosylated glycans found in the breast milk of secretor mothers. We investigated the effects of maternal secretor status on the developing infant microbiota with a special emphasis on bifidobacterial species abundance.

RESULTS

On average, bifidobacteria were established earlier and more often in infants fed by secretor mothers than in infants fed by non-secretor mothers. In secretor-fed infants, the relative abundance of the Bifidobacterium longum group was most strongly correlated with high percentages of the order Bifidobacteriales. Conversely, in non-secretor-fed infants, Bifidobacterium breve was positively correlated with Bifidobacteriales, while the B. longum group was negatively correlated. A higher percentage of bifidobacteria isolated from secretor-fed infants consumed 2'-fucosyllactose. Infant feces with high levels of bifidobacteria had lower milk oligosaccharide levels in the feces and higher amounts of lactate. Furthermore, feces containing different bifidobacterial species possessed differing amounts of oligosaccharides, suggesting differential consumption in situ.

CONCLUSIONS

Infants fed by non-secretor mothers are delayed in the establishment of a bifidobacteria-laden microbiota. This delay may be due to difficulties in the infant acquiring a species of bifidobacteria able to consume the specific milk oligosaccharides delivered by the mother. This work provides mechanistic insight into how milk glycans enrich specific beneficial bacterial populations in infants and reveals clues for enhancing enrichment of bifidobacterial populations in at risk populations - such as premature infants.

The human colostrum whey proteome is altered in gestational diabetes mellitus

Proteomics of human milk has been used to identify the comprehensive cargo of proteins involved in immune and cellular function. Very little is known about the effects of gestational diabetes mellitus (GDM) on lactation and breast milk components. The objective of the current study was to examine the effect of GDM on the expression of proteins in the whey fraction of human colostrum. Colostrum was collected from women who were diagnosed with (n = 6) or without (n = 12) GDM at weeks 24-28 in pregnancy. Colostral whey was analyzed for protein abundances using high-resolution, high-mass accuracy liquid chromatography tandem mass spectrometry. A total of 601 proteins were identified, of which 260 were quantified using label free spectral counting. Orthogonal partial least-squares discriminant analysis identified 27 proteins that best predict GDM. The power law global error model corrected for multiple testing was used to confirm that 10 of the 27 proteins were also statistically significantly different between women with versus without GDM. The identified changes in protein expression suggest that diabetes mellitus during pregnancy has consequences on human colostral proteins involved in immunity and nutrition.

Sequencing the transcriptome of milk production: milk trumps mammary tissue

BACKGROUND

Studies of normal human mammary gland development and function have mostly relied on cell culture, limited surgical specimens, and rodent models. Although RNA extracted from human milk has been used to assay the mammary transcriptome non-invasively, this assay has not been adequately validated in primates. Thus, the objectives of the current study were to assess the suitability of lactating rhesus macaques as a model for lactating humans and to determine whether RNA extracted from milk fractions is representative of RNA extracted from mammary tissue for the purpose of studying the transcriptome of milk-producing cells.

RESULTS

We confirmed that macaque milk contains cytoplasmic crescents and that ample high-quality RNA can be obtained for sequencing. Using RNA sequencing, RNA extracted from macaque milk fat and milk cell fractions more accurately represented RNA from mammary epithelial cells (cells that produce milk) than did RNA from whole mammary tissue. Mammary epithelium-specific transcripts were more abundant in macaque milk fat, whereas adipose or stroma-specific transcripts were more abundant in mammary tissue. Functional analyses confirmed the validity of milk as a source of RNA from milk-producing mammary epithelial cells.

CONCLUSIONS

RNA extracted from the milk fat during lactation accurately portrayed the RNA profile of milk-producing mammary epithelial cells in a non-human primate. However, this sample type clearly requires protocols that minimize RNA degradation. Overall, we validated the use of RNA extracted from human and macaque milk and provided evidence to support the use of lactating macaques as a model for human lactation.

From genes to milk: genomic organization and epigenetic regulation of the mammary transcriptome

Even in genomes lacking operons, a gene's position in the genome influences its potential for expression. The mechanisms by which adjacent genes are co-expressed are still not completely understood. Using lactation and the mammary gland as a model system, we explore the hypothesis that chromatin state contributes to the co-regulation of gene neighborhoods. The mammary gland represents a unique evolutionary model, due to its recent appearance, in the context of vertebrate genomes. An understanding of how the mammary gland is regulated to produce milk is also of biomedical and agricultural importance for human lactation and dairying. Here, we integrate epigenomic and transcriptomic data to develop a comprehensive regulatory model. Neighborhoods of mammary-expressed genes were determined using expression data derived from pregnant and lactating mice and a neighborhood scoring tool, G-NEST. Regions of open and closed chromatin were identified by ChIP-Seq of histone modifications H3K36me3, H3K4me2, and H3K27me3 in the mouse mammary gland and liver tissue during lactation. We found that neighborhoods of genes in regions of uniquely active chromatin in the lactating mammary gland, compared with liver tissue, were extremely rare. Rather, genes in most neighborhoods were suppressed during lactation as reflected in their expression levels and their location in regions of silenced chromatin. Chromatin silencing was largely shared between the liver and mammary gland during lactation, and what distinguished the mammary gland was mainly a small tissue-specific repertoire of isolated, expressed genes. These findings suggest that an advantage of the neighborhood organization is in the collective repression of groups of genes via a shared mechanism of chromatin repression. Genes essential to the mammary gland's uniqueness are isolated from neighbors, and likely have less tolerance for variation in expression, properties they share with genes responsible for an organism's survival.

RNA sequencing of the human milk fat layer transcriptome reveals distinct gene expression profiles at three stages of lactation

Aware of the important benefits of human milk, most U.S. women initiate breastfeeding but difficulties with milk supply lead some to quit earlier than intended. Yet, the contribution of maternal physiology to lactation difficulties remains poorly understood. Human milk fat globules, by enveloping cell contents during their secretion into milk, are a rich source of mammary cell RNA. Here, we pair this non-invasive mRNA source with RNA-sequencing to probe the milk fat layer transcriptome during three stages of lactation: colostral, transitional, and mature milk production. The resulting transcriptomes paint an exquisite portrait of human lactation. The resulting transcriptional profiles cluster not by postpartum day, but by milk Na:K ratio, indicating that women sampled during similar postpartum time frames could be at markedly different stages of gene expression. Each stage of lactation is characterized by a dynamic range (10(5)-fold) in transcript abundances not previously observed with microarray technology. We discovered that transcripts for isoferritins and cathepsins are strikingly abundant during colostrum production, highlighting the potential importance of these proteins for neonatal health. Two transcripts, encoding β-casein (CSN2) and α-lactalbumin (LALBA), make up 45% of the total pool of mRNA in mature lactation. Genes significantly expressed across all stages of lactation are associated with making, modifying, transporting, and packaging milk proteins. Stage-specific transcripts are associated with immune defense during the colostral stage, up-regulation of the machinery needed for milk protein synthesis during the transitional stage, and the production of lipids during mature lactation. We observed strong modulation of key genes involved in lactose synthesis and insulin signaling. In particular, protein tyrosine phosphatase, receptor type, F (PTPRF) may serve as a biomarker linking insulin resistance with insufficient milk supply. This study provides the methodology and reference data set to enable future targeted research on the physiological contributors of sub-optimal lactation in humans.

G-NEST: a gene neighborhood scoring tool to identify co-conserved, co-expressed genes

BACKGROUND

In previous studies, gene neighborhoods-spatial clusters of co-expressed genes in the genome-have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Scoring Tool (G-NEST) which combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all possible window sizes simultaneously.

RESULTS

Using G-NEST on atlases of mouse and human tissue expression data, we found that large neighborhoods of ten or more genes are extremely rare in mammalian genomes. When they do occur, neighborhoods are typically composed of families of related genes. Both the highest scoring and the largest neighborhoods in mammalian genomes are formed by tandem gene duplication. Mammalian gene neighborhoods contain highly and variably expressed genes. Co-localized noisy gene pairs exhibit lower evolutionary conservation of their adjacent genome locations, suggesting that their shared transcriptional background may be disadvantageous. Genes that are essential to mammalian survival and reproduction are less likely to occur in neighborhoods, although neighborhoods are enriched with genes that function in mitosis. We also found that gene orientation and protein-protein interactions are partially responsible for maintenance of gene neighborhoods.

CONCLUSIONS

Our experiments using G-NEST confirm that tandem gene duplication is the primary driver of non-random gene order in mammalian genomes. Non-essentiality, co-functionality, gene orientation, and protein-protein interactions are additional forces that maintain gene neighborhoods, especially those formed by tandem duplicates. We expect G-NEST to be useful for other applications such as the identification of core regulatory modules, common transcriptional backgrounds, and chromatin domains. The software is available at http://docpollard.org/software.html.

Lactation and neonatal nutrition: defining and refining the critical questions

This paper resulted from a conference entitled "Lactation and Milk: Defining and refining the critical questions" held at the University of Colorado School of Medicine from January 18-20, 2012. The mission of the conference was to identify unresolved questions and set future goals for research into human milk composition, mammary development and lactation. We first outline the unanswered questions regarding the composition of human milk (Section I) and the mechanisms by which milk components affect neonatal development, growth and health and recommend models for future research. Emerging questions about how milk components affect cognitive development and behavioral phenotype of the offspring are presented in Section II. In Section III we outline the important unanswered questions about regulation of mammary gland development, the heritability of defects, the effects of maternal nutrition, disease, metabolic status, and therapeutic drugs upon the subsequent lactation. Questions surrounding breastfeeding practice are also highlighted. In Section IV we describe the specific nutritional challenges faced by three different populations, namely preterm infants, infants born to obese mothers who may or may not have gestational diabetes, and infants born to undernourished mothers. The recognition that multidisciplinary training is critical to advancing the field led us to formulate specific training recommendations in Section V. Our recommendations for research emphasis are summarized in Section VI. In sum, we present a roadmap for multidisciplinary research into all aspects of human lactation, milk and its role in infant nutrition for the next decade and beyond.

Lactosomes: structural and compositional classification of unique nanometer-sized protein lipid particles of human milk

Milk fat globules (MFGs) are accepted primarily as triacylglycerol delivery systems. The identification of nanometer-sized lipid-protein particles termed "lactosomes" that do not contain triacylglycerol raises the question of their possible functions. MFGs were isolated by slow centrifugation, and lactosomes were isolated by ultracentrifugation at a density equivalent to plasma high-density lipoproteins (HDL) (d > 1.063 g/mL) from human milk obtained from six volunteers at different lactation stages. Isolated lactosomes were analyzed and compared with MFGs for their size distribution, lipidome, proteome, and functional activity. Lactosomes from early milk, day 8, were found to be similar in size as those from mature milk >28 days, averaging ∼ 25 nm in diameter. In total, 97 nonredundant proteins were identified in the MFG and lactosome fractions, 46 of which were unique to the MFG fraction and 29 of which were unique to the lactosome fraction. The proteins identified in the lactosome and MFG fractions were enriched with proteins identified with immunomodulatory pathways. Unlike MFGs and GM1-laden reconstituted HDL that served as a positive control, lactosomal binding capacity to cholera toxin was weak. Lipidomic analyses found that lactosomes were devoid of triacylglycerol and gangliosides, unlike MFGs, but rich in a variety of phospholipid species. The data found differences in structure, composition, and function between lactosomes and MFG, suggesting that these two particles are derived from different biosynthetic and/or secretory pathways. The results reveal a bioactive lipid-protein, nanometer-length scale particle that is secreted into milk not to supply energy to the infant but to play unique, protective, and regulatory roles.