Modulatory Effects of A1 Milk, A2 Milk, Soy, and Egg Proteins on Gut Microbiota and Fermentation.

Milk can be divided into A1 and A2 types according to ß-casein variants, and there is a debate about whether A1 milk consumption exacerbates gut environments. This study examined the cecum microbiota and fermentation in mice fed A1 casein, A2 casein, mixed casein (commercial casein), soy protein isolate, and egg white. The cecum acetic acid concentration was higher, and the relative abundances of Muribaculaceae and Desulfovibrionaceae were greater in mice fed A1 versus A2 casein. The other parameters of cecum fermentation and microbiota composition were similar among the mice fed A1, A2, and mixed caseins. The differences were more distinctive among the three caseins, soy, and egg feedings. Chao 1 and Shannon indices of the cecum microbiota were lowered in egg white-fed mice, and the microbiota of mice fed milk, soy, and egg proteins were separately grouped by principal coordinate analysis. Mice fed the three caseins were characterized by a high abundance of Lactobacillaceae and Clostridiaceae, those fed soy were characterized by Corynebacteriaceae, Muribaculaceae, and Ruminococcaceae, and those fed egg white were characterized by Eggerthellaceae, Rikenellaceae, and Erysipelatoclostridiaceae. Thus, although several differences can arise between A1 and A2 caseins in terms of their modulatory effects on gut environments, the differences between milk, soy, and egg proteins can be more distinctive and are worth further consideration.

Cyclic Nigerosylnigerose Attenuates High-Fat Diet-Induced Fat Deposition, Colonic Inflammation, and Abnormal Glucose Metabolism and Modifies Gut Immunoglobulin a Reactivity to Commensal Bacteria.

SCOPE: High-fat diet (HFD) intake induces gut dysbiosis, inflammation in the peripheral tissues, and a reduction in immunoglobulin A (IgA) coating of gut bacteria, which is related to HFD-induced insulin resistance (IR). This study evaluates the effect of cyclic nigerosylnigerose (CNN), a dietary fiber that prevents gut inflammation and promotes IgA coating of gut bacteria, on the above-mentioned HFD-induced disorders. METHODS AND RESULTS: Balb/c mice are fed an HFD and administered CNN for 20 weeks. CNN administration reduces mesenteric adipose tissue weight, colonic tumor necrosis factor α (TNFα) mRNA expression, and serum endotoxin levels and ameliorates HFD-induced abnormal glucose metabolism. Additionally, CNN administration promotes gut bacteria-specific IgA secretion and alters IgA reactivity to gut bacteria. The alterations of IgA reactivity to specific bacteria such as Erysipelatoclostridium, Escherichia, Faecalibaculum, Lachnospiraceae genera, and Stenotrophomonas are correlated with mesenteric adipose tissue weight, colonic TNFα mRNA expression, serum endotoxin levels, and a homeostasis model assessment for IR. CONCLUSION: CNN-induced alterations in IgA reactivity to gut bacteria may be related to the suppression of HFD-induced fat deposition, colonic inflammation, endotoxemia, and IR. These observations indicate that dietary fiber that modulates IgA reactivity to gut bacteria may be useful in preventing HFD-induced disorders.

Monitoring the Milk Composition, Milk Microbiota, and Blood Metabolites of Jersey Cows throughout a Lactation Period.

This study aimed to determine how milk composition, milk microbiota, and blood metabolites may change during the lactation period in Jersey cows. Milk and jugular blood samples were collected from eight healthy cows every other month from the beginning to the end of their lactation period. Samples of airborne dust were also collected to determine whether the cowshed microbiota could affect milk microbiota. Milk yield peaked in the first two months and gradually decreased as the lactation period progressed. Milk fat, protein, and solids-not-fat contents were low in the first month, and then increased during the middle and late lactation periods. In the first month, plasma non-esterified fatty acids (NEFA), haptoglobin (Hp), and aspartate transaminase (AST) levels were elevated, and high abundances of Burkholderiaceae and Oxalobacteraceae were observed in milk and airborne dust microbiota. The finding that contamination of the environmental microbiota in milk was coupled with elevated plasma NEFA, Hp, and AST levels indicated that impaired metabolic function during the early lactation period may increase the invasion of opportunistic bacteria. This study can affirm the importance of feeding and cowshed management and should provide a helpful addition to improving Jersey cow farming.

Frequency of ß-Casein Gene Polymorphisms in Jersey Cows in Western Japan.

This study aimed to investigate ß-casein gene polymorphisms in Jersey cows in Japan. Blood samples were collected from 590 cows from eight Jersey farms in Okayama Prefecture, western Japan. Sequence analysis of exon 7 regions in chromosome 6 of the CSN2 gene revealed the genotype and allele frequencies of the ß-casein variants. Considering that variant B belongs to the A1 group and variant I to the A2 group, plasma metabolite concentrations were compared among the A1A1, A1A2, and A2A2 group-based genotypes. The most frequent genotype was A2A2 (0.558), followed by A2B (0.190) and A2I (0.103). No variants of A3, F, G, H1, or H2 were found. The frequencies of group-based genotypes were A1A1 (0.032), A1A2 (0.303), and A2A2 (0.665). Although farm-to-farm differences were observed in the plasma concentrations of urea nitrogen, calcium, and phosphorus, no differences were found between the A1A1, A1A2, and A2A2 group-based genotypes; hence, the ß-casein genotypes did not affect the metabolism of major nutrients. Owing to the high frequency of the A2 variant, Jersey cows can be considered an attractive breed for marker-assisted selection to create A2A2 herds.

Bacterial and fungal microbiota of total mixed ration silage stored at various temperatures.

AIMS: To obtain insights into how bacterial and fungal microbiota and fermentation products composition are affected by storage temperature for TMR silage, which can be manufactured year-round. METHODS AND RESULTS: TMR silage was stored at 10°C, 25°C, ambient temperature (AT; 20-35°C) and 40°C. Lactic acid production was delayed when stored at 10°C, and acid production stagnated after 2 weeks when stored at 40°C. The patterns of acetic acid and ethanol production were inversely related, with ethanol production promoted at 10°C and 25°C and acetic acid production promoted at AT and 40°C. The bacterial diversity was reduced in TMR silage with high lactic acid and acetic acid content, and the fungal diversity was reduced in TMR silage with high ethanol content. CONCLUSIONS: The intensity of lactic acid production was accounted for by the high abundance of Lactobacillus, and its stagnated production at a substantially high storage temperature was related to an increased abundance of Bacillus. The enhanced production of acetic acid or ethanol can be explained by differences in the fungal microbiota. SIGNIFICANCE AND IMPACT OF THE STUDY: The integrated analysis of bacterial and fungal microbiota can provide in-depth insights into the impact of storage temperature on TMR silage fermentation.

Aicda deficiency exacerbates high-fat diet-induced hyperinsulinemia but not gut dysbiosis in mice.

Immunoglobulin A (IgA) is a major antibody in the gut. We previously observed that a high-fat diet (HFD) reduces IgA reactivity to gut microbiota, but the physiological implications have yet to be elucidated. We hypothesized that a reduction of IgA reactivity to gut microbiota induced by a HFD may contribute to development of gut dysbiosis and inflammation that accompanies HFD feeding. To test our hypothesis, we used Aicda deficient mice, which have a deficiency in IgA production. Aicda deficient mice and wild-type mice were fed normal-fat diet or HFD for 12 weeks. We found that HFD feeding but not Aicda deficiency altered the fecal microbiota composition. Meanwhile, Aicda deficiency significantly increased gene expression of inflammatory cytokines in the ileum, but not in the colon despite no significant difference between diets. These results suggest that a reduction of IgA reactivity to gut microbiota induced by HFD partly contributes to development of inflammation in the ileum, but not to gut dysbiosis. We also found that the fasting blood insulin level was significantly increased by Aicda deficiency only under HFD feeding. Furthermore, the gene expression of monocyte chemoattractant protein1, a major chemokine responsible for the onset of hyperinsulinemia, in the liver was significantly increased by HFD feeding and tended to be increased by Aicda deficiency. These findings suggest that a reduction of IgA reactivity to gut microbiota induced by HFD contributes to hyperinsulinemia partly via increasing monocyte chemoattractant protein-1 expression in the liver.

Cecum microbiota in rats fed soy, milk, meat, fish, and egg proteins with prebiotic oligosaccharides.

Diet is considered the most influential factor in modulating the gut microbiota but how dietary protein sources differ in their modulatory effects is not well understood. In this study, soy, meat (mixture of beef and pork), and fish proteins (experiment 1) and soy, milk (casein), and egg proteins (experiment 2) were fed to rats with cellulose (CEL) and raffinose (RAF); the microbiota composition and short-chain fatty acid concentration in the cecum were determined. Egg protein feeding decreased the concentration of acetic acid and the richness and diversity of the cecum microbiota. RAF feeding increased the concentrations of acetic and propionic acids and decreased the richness and diversity of the cecum microbiota. When fed with CEL, the abundance of Ruminococcaceae and Christensenellaceae, Akkermansiaceae and Tannerellaceae, and Erysipelotrichaceae enhanced with soy protein, meat and fish proteins, and egg protein, respectively. The effects of dietary proteins diminished with RAF feeding and the abundance of Bifidobacteriaceae, Erysipelotrichaceae, and Lachnospiraceae increased and that of Ruminococcaceae and Christensenellaceae decreased regardless of the protein source. These results indicate that, although the effect of prebiotics is more robust and distinctive, dietary protein sources may influence the composition and metabolic activities of the gut microbiota. The stimulatory effects of soy, meat, and egg proteins on Christensenellaceae, Akkermansiaceae, and Erysipelotrichaceae deserve further examination to better elucidate the dietary manipulation of the gut microbiota.

Examination of milk microbiota, fecal microbiota, and blood metabolites of Jersey cows in cool and hot seasons.

Microbiota of individual cow milk, bulk tank milk, and feces of Jersey cows were examined. Samples were collected from two farms (F1 and F2) in cool (November, Nov) and hot (July, Jul) seasons. Milk yield and milk composition were similar between the two farms and between the two seasons. Prevalent taxa of the fecal microbiota, i.e. Ruminococcaceae, Bacteroidaceae, Lachnospiraceae, Rikenellaceae, and Clostridiaceae, were unaffected by the farm and season. Relative abundance of milk microbiota for Pseudomonadaceae, Enterobacteriaceae, and Streptococcaceae (F1 > F2) and Lactobacillaceae, Bifidobacteriaceae, and Cellulomonadaceae (F1 < F2) were different between the two farms, and those for Staphylococcaceae, Bacillaceae, Ruminococcaceae, and Veillonellaceae (Nov < Jul) and Methylobacteriaceae and Moraxellaceae (Nov > Jul) were different between the two seasons. The microbiota of bulk tank milk was numerically different from that of individual cow milk. Principal coordinate analysis indicated that the milk microbiota was unrelated to the fecal microbiota. The finding that relative abundance of Pseudomonadaceae and Moraxellaceae appeared greater than those reported for Holstein milk suggested that higher protein and fat content may result in a greater abundance of proteolytic and lipolytic taxa in Jersey cow milk.

Bacterial and Fungal Microbiota Associated with the Ensiling of Wet Soybean Curd Residue under Prompt and Delayed Sealing Conditions.

Wet soybean curd residue (SCR) obtained from two tofu factories (F1 and F2) was anaerobically stored with or without added beet pulp (BP). Sealing was performed on the day of tofu production (prompt sealing (PS)) or 2 days after SCR was piled and unprocessed (delayed sealing (DS)). Predominant lactic acid fermentation was observed regardless of the sealing time and BP addition. Acinetobacter spp. were the most abundant (>67%) bacteria in pre-ensiled SCR, regardless of the factory and sealing time. In PS silage, the abundances of typical lactic acid-producing bacteria, such as Lactobacillus, Pediococcus, and Streptococcus spp. reached >50%. In DS silage, Acinetobacter spp. were the most abundant in F1 products, whereas Bacillus spp. were the most abundant in long-stored F2 products. The fungal microbiota were highly diverse. Although Candida, Aspergillus, Cladosporium, Hannaella, and Wallemia spp. were found to be the most abundant fungal microbiota, no specific genera were associated with factory, sealing time, or fermentation products. These results indicated that owing to preceding processing, including heating, distinctive microbiota may have participated in the ensiling of wet by-products. Lactic acid fermentation was observed even in DS silage, and an association of Bacillus spp. was suggested.

Cyclic nigerosylnigerose ameliorates DSS-induced colitis with restoration of goblet cell number and increase in IgA reactivity against gut microbiota in mice.

Cyclic nigerosylnigerose (CNN) is a cyclic oligosaccharide. Oral administration of CNN promotes immunoglobulin A (IgA) secretion in the gut. IgA is a major antibody secreted into the gut and plays a crucial role in suppressing gut inflammation due to commensal gut microbiota. To investigate the effect of administration of CNN to promote IgA secretion on gut inflammation, experimental colitis was induced with dextran sulfate sodium (DSS) in Balb/c mice after 6 weeks of CNN pre-feeding. The severity of colitis was evaluated based on a disease activity index (DAI), the gene expression of inflammatory cytokines, and a histological examination. The CNN-treated mice with DSS-induced colitis (CNN-DSS group) showed significantly lower DAI scores and mRNA levels of interleukin-1 compared with the CNN-untreated mice with DSS-induced colitis (DSS group). Histological examination of the colon revealed that the pathological score was significantly lower in the CNN-DSS group compared with the DSS group due to the reduced infiltration of immune cells. The number of goblet cells was significantly higher in the CNN-DSS group compared with the DSS group. The IgA concentration and the ratio of microbiota coated with IgA were evaluated in the cecal content. Although there was no difference in the IgA concentration among groups, a higher proportion of cecal microbiota were coated with IgA in the CNN-DSS group compared with that in the DSS group. These results suggest that CNN might preserve goblet cells in the colon and promote IgA coating of gut microbiota, which synergistically ameliorate gut inflammation in mice with DSS-induced colitis.

An investigation of seasonal variations in the microbiota of milk, feces, bedding, and airborne dust.

OBJECTIVE: The microbiota of dairy cow milk varies with the season, and this accounts in part for the seasonal variation in mastitis-causing bacteria and milk spoilage. The microbiota of the cowshed may be the most important factor because the teats of a dairy cow contact bedding material when the cow is resting. The objectives of the present study were to determine whether the microbiota of the milk and the cowshed vary between seasons, and to elucidate the relationship between the microbiota. METHODS: We used 16S rRNA gene amplicon sequencing to investigate the microbiota of milk, feces, bedding, and airborne dust collected at a dairy farm during summer and winter. RESULTS: The seasonal differences in the milk yield and milk composition were marginal. The fecal microbiota was stable across the two seasons. Many bacterial taxa of the bedding and airborne dust microbiota exhibited distinctive seasonal variation. In the milk microbiota, the abundances of Staphylococcaceae, Bacillaceae, Streptococcaceae, Microbacteriaceae, and Micrococcaceae were affected by the seasons; however, only Micrococcaceae had the same seasonal variation pattern as the bedding and airborne dust microbiota. Nevertheless, canonical analysis of principle coordinates revealed a distinctive group comprising the milk, bedding, and airborne dust microbiota. CONCLUSION: Although the milk microbiota is related to the bedding and airborne dust microbiota, the relationship may not account for the seasonal variation in the milk microbiota. Some major bacterial families stably found in the bedding and airborne dust microbiota, e.g., Staphylococcaceae, Moraxellaceae, Ruminococcaceae, and Bacteroidaceae, may have greater influences than those that varied between seasons.

The Relationship between Uterine, Fecal, Bedding, and Airborne Dust Microbiota from Dairy Cows and Their Environment: A Pilot Study.

The aim of this study was to characterize uterine, fecal, bedding, and airborne dust microbiota from postpartum dairy cows and their environment. The cows were managed by the free-stall housing system, and samples for microbiota and serum metabolite assessment were collected during summer and winter when the cows were at one and two months postpartum. Uterine microbiota varied between seasons; the five most prevalent taxa were Enterobacteriaceae, Moraxellaceae, Ruminococcaceae, Staphylococcaceae, and Lactobacillaceae during summer, and Ruminococcaceae, Lachnospiraceae, Bacteroidaceae, Moraxellaceae, and Clostridiaceae during winter. Although Actinomycetaceae and Mycoplasmataceae were detected at high abundance in several uterine samples, the relationship between the uterine microbiota and serum metabolite concentrations was unclear. The fecal microbiota was stable regardless of the season, whereas bedding and airborne dust microbiota varied between summer and winter. With regards to uterine, bedding, and airborne dust microbiota, Enterobacteriaceae, Moraxellaceae, Staphylococcaceae, and Lactobacillaceae were more abundant during summer, and Ruminococcaceae, Lachnospiraceae, Bacteroidaceae, and Clostridiaceae were more abundant during winter. Canonical analysis of principal coordinates confirmed the relationship between uterine and cowshed microbiota. These results indicated that the uterine microbiota may vary when the microbiota in cowshed environments changes.

High-fat diet reduces the level of secretory immunoglobulin A coating of commensal gut microbiota.

Excessive fat intake is associated with changes in gut microbiota composition. In the present study, we focused on the secretory immunoglobulin A (SIgA) coating of gut microbiota as a mucosal immune response affecting the gut microbiota following a high-fat diet (HFD). The level of SIgA coating of gut microbiota was evaluated in normal-fat diet (NFD)- and HFD-fed mice. HFD significantly decreased the level of SIgA coating the gut microbiota compared with NFD. Of note, substitution of HFD with NFD resulted in a complete recovery of the level of SIgA coating. These findings suggest that dietary fat influences the SIgA coating of the gut microbiota. Furthermore, we analyzed the composition of the gut microbiota and the concentration of cecal short-chain fatty acids. HFD feeding changed the gut microbiota composition at the phylum and family levels. Pearson correlation analysis between the level of SIgA coating of gut microbiota and the relative abundance of gut microbiota showed that the relative abundances of Clostridiaceae, Mogibacteriaceae, Turicibacteraceae, and Bifidobacteriaceae were negatively correlated with the level of SIgA coating of gut microbiota. Conversely, the relative abundances of Desulfovibrionaceae, S24-7, and Lactobacillaceae were positively correlated with the level of SIgA coating. The concentrations of cecal acetate and butyrate were lower in HFD-fed mice and positively correlated with the level of SIgA coating of gut microbiota. Our observations suggest that a decrease in the level of SIgA coating of the gut microbiota through a HFD might relate to HFD-induced changes in microbial composition and microbial metabolites production.

Rumen fluid, feces, milk, water, feed, airborne dust, and bedding microbiota in dairy farms managed by automatic milking systems.

Microbiota of the gut, milk, and cowshed environment were examined at two dairy farms managed by automatic milking systems (AMS). Feed, rumen fluid, feces, milk, bedding, water, and airborne dust were collected and the microbiota on each was assessed by Illumina MiSeq sequencing. The most abundant taxa in feed, rumen fluid, feces, bedding, and water were Lactobacillaceae, Prevotellaceae, Ruminococcaceae, Ruminococcaceae, and Lactobacillaceae, respectively, at both farms. Aerococcaceae was the most abundant taxon in milk and airborne dust microbiota at farm 1, and Staphylococcaceae and Lactobacillaceae were the most abundant taxa in milk and airborne dust microbiota at farm 2. The three most prevalent taxa (Aerococcaceae, Staphylococcaceae, and Ruminococcaceae at farm 1 and Staphylococcaceae, Lactobacillaceae, and Ruminococcaceae at farm 2) were shared between milk and airborne dust microbiota. Indeed, SourceTracker indicated that milk microbiota was related with airborne dust microbiota. Meanwhile, hierarchical clustering and canonical analysis of principal coordinates demonstrated that the milk microbiota was associated with the bedding microbiota but clearly separated from feed, rumen fluid, feces, and water microbiota. Although our findings were derived from only two case studies, the importance of cowshed management for milk quality control and mastitis prevention was emphasized at farms managed by AMS.

Identification of lactic acid bacteria in the feces of dairy cows fed whole crop maize silage to assess the survival of silage bacteria in the gut.

In order to assess the survival of lactic acid bacteria (LAB) in whole crop maize silage in the gut of dairy cows, one representative silage sample and three different feces samples were collected from dairy cows on three dairy farms in Hua Bei, China and three dairy farms in Kyushu, Japan. The composition of the bacterial community was examined by denaturing gradient gel electrophoresis and quantitative polymerase chain reaction. Lactobacillus acetotolerans was detected in all bunker-made maize silage samples, regardless of the dairy farm or sampling region from which they were sourced. A total of eight LAB species were detected in the maize silage samples, of which three (L. acetotolerans, L. pontis and L. casei) appeared to survive digestion. The populations of L. acetotolerans in silage and feces were 106-7 and 103-4 copies/g, respectively, indicating that, even for the LAB species showing potential survival in the gut, competition in this niche may be harsh and the population may substantially decrease during the digestion process. It may be difficult for silage LAB to survive in the gut of silage-fed dairy cows, because marked decrease in population can take place during the digestion process, even for surviving species.

Dietary soy, meat, and fish proteins modulate the effects of prebiotic raffinose on composition and fermentation of gut microbiota in rats.

Soy, meat (mixture of pork and beef), and fish proteins were fed to rats with and without prebiotic raffinose (RAF), and the composition and fermentation of gut microbiota were examined. Bifidobacterium spp. populations were higher, and propionic acid concentration was lower in soy protein-fed than meat protein-fed rats. Likewise, Enterobacteriaceae populations were higher in fish protein-fed rats than other rats. RAF feeding increased Bifidobacterium spp. and decreased Faecalibacterium prausnitzii populations regardless of the dietary protein source. Interactions between dietary proteins and RAF were shown for Lactobacillus spp. and Clostridium perfringens group; the increase of Lactobacillus spp. populations by RAF was seen only for soy protein-fed rats, whereas the reduction of C. perfringens group by RAF was evident in fish and meat protein-fed rats. It is concluded that dietary proteins may differentially modulate the effects of prebiotic oligosaccharides on gut fermentation and microbiota, with differences observed between plant and animal proteins.

Variability, stability, and resilience of fecal microbiota in dairy cows fed whole crop corn silage.

The microbiota of whole crop corn silage and feces of silage-fed dairy cows were examined. A total of 18 dairy cow feces were collected from six farms in Japan and China, and high-throughput Illumina sequencing of the V4 hypervariable region of 16S rRNA genes was performed. Lactobacillaceae were dominant in all silages, followed by Acetobacteraceae, Bacillaceae, and Enterobacteriaceae. In feces, the predominant families were Ruminococcaceae, Bacteroidaceae, Clostridiaceae, Lachnospiraceae, Rikenellaceae, and Paraprevotellaceae. Therefore, Lactobacillaceae of corn silage appeared to be eliminated in the gastrointestinal tract. Although fecal microbiota composition was similar in most samples, relative abundances of several families, such as Ruminococcaceae, Christensenellaceae, Turicibacteraceae, and Succinivibrionaceae, varied between farms and countries. In addition to the geographical location, differences in feeding management between total mixed ration feeding and separate feeding appeared to be involved in the variations. Moreover, a cow-to-cow variation for concentrate-associated families was demonstrated at the same farm; two cows showed high abundance of Succinivibrionaceae and Prevotellaceae, whereas another had a high abundance of Porphyromonadaceae. There was a negative correlation between forage-associated Ruminococcaceae and concentrate-associated Succinivibrionaceae and Prevotellaceae in 18 feces samples. Succinivibrionaceae, Prevotellaceae, p-2534-18B5, and Spirochaetaceae were regarded as highly variable taxa in this study. These findings help to improve our understanding of variation and similarity of the fecal microbiota of dairy cows with regard to individuals, farms, and countries. Microbiota of naturally fermented corn silage had no influence on the fecal microbiota of dairy cows.

Comparative microbiota assessment of wilted Italian ryegrass, whole crop corn, and wilted alfalfa silage using denaturing gradient gel electrophoresis and next-generation sequencing.

The microbiota of pre-ensiled crop and silage were examined using denaturing gradient gel electrophoresis (DGGE) and next-generation sequencing (NGS). Wilted Italian ryegrass (IR), whole crop corn (WC), and wilted alfalfa (AL) silages stored for 2 months were examined. All silages contained lactic acid as a predominant fermentation product. Across the three crop species, DGGE detected 36 and 28 bands, and NGS identified 253 and 259 genera in the pre-ensiled crops and silages, respectively. The NGS demonstrated that, although lactic acid bacteria (LAB) became prevalent in all silages after 2 months of storage, the major groups were different between crops: Leuconostoc spp. and Pediococcus spp. for IR silage, Lactobacillus spp. for WC silage, and Enterococcus spp. for AL silage. The predominant silage LAB genera were also detected by DGGE, but the presence of diverse non-LAB species in pre-ensiled crops was far better detected by NGS. Likewise, good survival of Agrobacterium spp., Methylobacterium spp., and Sphingomonas spp. in IR and AL silages was demonstrated by NGS. The diversity of the microbiota described by principal coordinate analysis was similar between DGGE and NGS. Our finding that analysis of pre-ensiled crop microbiota did not help predict silage microbiota was true for both DGGE and NGS.

Diversity of lactic acid bacteria in vegetable-based and meat-based fermented foods produced in the central region of Vietnam.

The diversity of lactic acid bacteria (LAB) in naturally fermented foods produced in Hue, a city in the central region of Vietnam, was examined. From local markets, a total of 25 samples of three vegetable-based fermented products, specifically dua gia (bean sprouts), dua cai (cabbage), and mang chua (bamboo shoots), and two meat-based fermented products, specifically nem chua (uncooked pork) and tre (cooked pork) were obtained. The LAB diversity was assessed by quantitative real-time polymerase chain reaction (PCR) and qualitative denaturing gradient gel electrophoresis. Lactic and acetic acid contents were greater in meat-based products than in vegetable-based products. Major LAB species found in vegetable-based products (Lactobacillus plantarum, Lactobacillus fermentum, and Lactobacillus helveticus) were different from those identified in meat-based products (Pediococcus pentosaceus, Weissella cibaria, and Lactococcus lactis). The total bacterial population was approximately 109-10 copies/g regardless of the food item, with the proportion of Lactobacillus spp. determined to be from 78% (dua cai) to 94% (nem chua).

Dietary Casein and Soy Protein Isolate Modulate the Effects of Raffinose and Fructooligosaccharides on the Composition and Fermentation of Gut Microbiota in Rats.

Although diet has an important influence on the composition of gut microbiota, the impact of dietary protein sources has only been studied to a minor extent. In this study, we examined the influence of different dietary protein sources regarding the effects of prebiotic oligosaccharides on the composition and metabolic activity of gut microbiota. Thirty female rats were fed casein and soy protein isolate with cellulose, raffinose (RAF), and fructooligosaccharides (FOS). Microbiota composition was examined by real-time qPCR and denaturing gradient gel electrophoresis. Dietary protein source affected cecum microbiota; acetic acid concentration and Lactobacillus spp. populations were greater with soy protein than with casein. Prebiotic oligosaccharides had distinctive effects on gut microbiota; RAF increased the acetic acid concentration and Bifidobacterium spp. populations, and FOS increased the butyric acid concentration regardless of the dietary protein. Likewise, Bifidobacterium sp., Collinsella sp., and Lactobacillus sp. were detected in microbiota of the rats fed RAF, and Bacteroides sp., Roseburia sp., and Blautia sp. were seen in microbiota of the rats fed FOS. Interactions between dietary proteins and prebiotic oligosaccharides were observed with Clostridium perfringens group populations and cecum IgA concentration. RAF and FOS decreased C. perfringens group populations in casein-fed rats, and the combination of soy protein and RAF substantially increased cecum IgA concentration. These results indicate that dietary proteins can differentially modulate the effects of prebiotic oligosaccharides on gut fermentation and microbiota, depending on the type of carbohydrate polymers involved.