Bacterial diversity index calculated from the DGGE banding patterns (Fig. 1A).

<p>N (negative control, basal diet); P (positive control, diet supplemented with neomycin); L, M, H (diets supplemented with probiotics 0.5×10⁹, 1.0×10⁹ and 2.5×10⁹ CFU/kg feed, respectively);</p><p>*1/D, the reciprocal of Simpson diversity index.</p><p>Bacterial diversity index calculated from the DGGE banding patterns (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116635#pone.0116635.g001" target="_blank">Fig. 1A</a>).</p

Identification of band fragments in DGGE gels (Fig. 1A).

<p>* Bands are numbered according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116635#pone.0116635.g001" target="_blank">Fig. 1A</a>.</p><p>^◆Identity represents the sequence identity (%) compared with that in the GenBank database.</p><p>Identification of band fragments in DGGE gels (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116635#pone.0116635.g001" target="_blank">Fig. 1A</a>).</p

<i>Lactobacillus</i> community of weaned piglets fed with neomycin or <i>E. faecalis</i>.

<p>(A) DGGE profiles of V3 region of the 16S rDNA gene fragments with the primes Lac1 and Lac2-GC. The denaturant gradient range is from 41% to 60%. Lanes N (negative control, basal diet); P (positive control, diet supplemented with neomycin); L, M, H (diets supplemented with probiotics 0.5×10⁹, 1.0×10⁹ and 2.5×10⁹ CFU/kg feed, respectively); (B) UPGMA cluster analysis of Dice similarity indices from DGGE profiles.</p

<i>Lactobacillus</i> diversity index calculated from the DGGE banding patterns (Fig. 2A).

<p>N (negative control, basal diet); P (positive control, diet supplemented with neomycin); L, M, H (diets supplemented with probiotics 0.5×10⁹, 1.0×10⁹ and 2.5×10⁹ CFU/kg feed, respectively);</p><p>*1/D, the reciprocal of Simpson diversity index.</p><p><i>Lactobacillus</i> diversity index calculated from the DGGE banding patterns (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116635#pone.0116635.g002" target="_blank">Fig. 2A</a>).</p

Bacterial community of weaned piglets fed with neomycin or <i>E. faecalis</i>.

<p>(A) DGGE profiles of the V6~V8 regions of the 16S rDNA gene fragments from the samples. The denaturant gradient range is from 42% to 58%. The major difference bands are numbered. Lane S (Standard ladder, which are PCR products generated from different bacterial 16S rDNA genes with primers 968F-GC and 1401R); N (negative control, basal diet); P (positive control, diet supplemented with neomycin); L, M, H (diets supplemented with probiotics 0.5×10⁹, 1.0×10⁹ and 2.5×10⁹ CFU/kg feed, respectively); (B) UPGMA cluster analysis of Dice similarity indices from DGGE profiles.</p

Dietary <i>Enterococcus faecalis</i> LAB31 Improves Growth Performance, Reduces Diarrhea, and Increases Fecal <i>Lactobacillus</i> Number of Weaned Piglets

<div><p>Lactic acid bacteria (LAB) have been shown to enhance performance of weaned piglets. However, few studies have reported the addition of LAB <i>Enterococcus faecalis</i> as alternatives to growth promoting antibiotics for weaned piglets. This study evaluated the effects of dietary <i>E. faecalis</i> LAB31 on the growth performance, diarrhea incidence, blood parameters, fecal bacterial and <i>Lactobacillus</i> communities in weaned piglets. A total of 360 piglets weaned at 26 ± 2 days of age were randomly allotted to 5 groups (20 pens, with 4 pens for each group) for a trial of 28 days: group N (negative control, without antibiotics or probiotics); group P (Neomycin sulfate, 100 mg/kg feed); groups L, M and H (supplemented with <i>E. faecalis</i> LAB31 0.5×10⁹, 1.0×10⁹, and 2.5×10⁹ CFU/kg feed, respectively). Average daily gain and feed conversion efficiency were found to be higher in group H than in group N, and showed significant differences between group H and group P (<i>P₀</i> < 0.05). Furthermore, groups H and P had a lower diarrhea index than the other three groups (<i>P₀</i> < 0.05). Denaturing gradient gel electrophoresis (DGGE) showed that the application of probiotics to the diet changed the bacterial community, with a higher bacterial diversity in group M than in the other four groups. Real-time PCR revealed that the relative number of <i>Lactobacillus</i> increased by addition of probiotics, and was higher in group H than in group N (<i>P₀</i> < 0.05). However, group-specific PCR-DGGE showed no obvious difference among the five groups in <i>Lactobacillus</i> composition and diversity. Therefore, the dietary addition of <i>E. faecalis</i> LAB31 can improve growth performance, reduce diarrhea, and increase the relative number of <i>Lactobacillus</i> in feces of weaned piglets.</p></div

Data_Sheet_1_Optimizing the scale-up production of fermented astragalus and its benefits to the performance and egg quality of laying hens.docx

Astragalus is a homologous medicine and food that benefits human beings and poultry rearing. Fermented astragalus (FA) is a valuable product obtained by fermentation, but its scale-up production requires optimization and expansion of solid-state fermentation (SSF). In this study, Lactobacillus pentosus Stm was screened as the most suitable LAB strain for fermenting astragalus due to its excellent capacity. After optimization and expansion of SSF, LAB count and lactic acid content reached 206 × 108 cfu/g and 15.0%, respectively. Meanwhile, the content of bioactive compounds in FA was significantly enhanced. Feeding experiments with laying hens indicated that supplementing FA in the diet significantly improved the performance and egg quality, as evidenced by reduced feed-to-egg ratio and egg cholesterol. This was due to the promotion of intestinal health by shifting intestinal microbiota. Therefore, this is a systematical endeavor of producing scaled-up FA with promising potential as a feed additive in the poultry breeding industry.</p

Data_Sheet_1_Unveiling the microbiota of sauce-flavor Daqu and its relationships with flavors and color during maturation.docx

This study investigated the microbial community in three-color sauce-flavor Daqu (black, yellow, and white) throughout their maturation processes, together with their physicochemical factors, culturable microbes, flavor components, and fermenting vitalities. Results from high-throughput sequencing revealed distinct microbial diversity, with more pronounced variations in bacterial community than in fungal community. Firmicutes and Ascomycota emerged as the most dominant bacterial and fungal phyla, respectively, during maturation. Genus-level analysis identified Kroppenstedia, Virgibacillus, and Bacillus as dominant bacteria in black Daqu, yellow Daqu, and white Daqu, severally, while Thermoascus was shared as the core dominant fungi for these Daqu. Physicochemical factors, particularly acidity, were found to exert a significant impact on microbial community. Kroppenstedtia was the key bacteria influencing the color formation of these Daqu. Furthermore, correlations between dominant microbes and flavor compounds highlighted their role in Daqu quality. Molds (Aspergillus, Rhizomucor, and Rhizopus), excepting Bacillus, played a crucial role in the formation of pyrazine compounds. Consequently, this study offers innovative insights into the microbial perspectives on color and pyrazine formation, establishing a groundwork for future mechanized Daqu production and quality control of sauce-flavor baijiu.</p

DataSheet1.ZIP

<p>Arid and semi-arid regions comprise nearly one-fifth of the earth's terrestrial surface. However, the diversities and functions of their soil microbial communities are not well understood, despite microbial ecological importance in driving biogeochemical cycling. Here, we analyzed the geochemistry and microbial communities of the desert soils from Tarim Basin, northwestern China. Our geochemical data indicated half of these soils are saline. Metagenomic analysis showed that bacterial phylotypes (89.72% on average) dominated the community, with relatively small proportions of Archaea (7.36%) and Eukaryota (2.21%). Proteobacteria, Firmicutes, Actinobacteria, and Euryarchaeota were most abundant based on metagenomic data, whereas genes attributed to Proteobacteria, Actinobacteria, Euryarchaeota, and Thaumarchaeota most actively transcribed. The most abundant phylotypes (Halobacterium, Halomonas, Burkholderia, Lactococcus, Clavibacter, Cellulomonas, Actinomycetospora, Beutenbergia, Pseudomonas, and Marinobacter) in each soil sample, based on metagenomic data, contributed marginally to the population of all microbial communities, whereas the putative halophiles, which contributed the most abundant transcripts, were in the majority of the active microbial population and is consistent with the soil salinity. Sample correlation analyses according to the detected and active genotypes showed significant differences, indicating high diversity of microbial communities among the Tarim soil samples. Regarding ecological functions based on the metatranscriptomic data, transcription of genes involved in various steps of nitrogen cycling, as well as carbon fixation, were observed in the tested soil samples. Metatranscriptomic data also indicated that Thaumarchaeota are crucial for ammonia oxidation and Proteobacteria play the most important role in other steps of nitrogen cycle. The reductive TCA pathway and dicarboxylate-hydroxybutyrate cycle attributed to Proteobacteria and Crenarchaeota, respectively, were highly represented in carbon fixation. Our study reveals that the microbial communities could provide carbon and nitrogen nutrients for higher plants in the sandy saline soils of Tarim Basin.</p