Wenjing Zhao

Quantitative Genetic Background of the Host Influences Gut Microbiomes in Chickens

Host genotype and gender are among the factors that influence the composition of gut microbiota. We studied the population structure of gut microbiota in two lines of chickens maintained under the same husbandry and dietary regimes. The lines, which originated from a common founder population, had undergone 54 generations of selection for high (HW) or low (LW) 56-day body weight, and now differ by more than 10-fold in body weight at selection age. Of 190 microbiome species, 68 were affected by genotype (line), gender, and genotype by gender interactions. Fifteen of the 68 species belong to Lactobacillus. Species affected by genotype, gender, and the genotype by gender interaction, were 29, 48, and 12, respectively. Species affected by gender were 30 and 17 in the HW and LW lines, respectively. Thus, under a common diet and husbandry host quantitative genotype and gender influenced gut microbiota composite.

The dynamic distribution of porcine microbiota across different ages and gastrointestinal tract segments.

Metagenome of gut microbes has been implicated in metabolism, immunity, and health maintenance of its host. However, in most of previous studies, the microbiota was sampled from feces instead of gastrointestinal (GI) tract. In this study, we compared the microbial populations from feces at four different developmental stages and contents of four intestinal segments at maturity to examine the dynamic shift of microbiota in pigs and investigated whether adult porcine fecal samples could be used to represent samples of the GI tract. Analysis results revealed that the ratio of Firmicutes to Bacteroidetes from the feces of the older pigs (2-, 3-, 6- month) were 10 times higher compared to those from piglets (1-month). As the pigs matured, so did it seem that the composition of microbiome became more stable in feces. In adult pigs, there were significant differences in microbial profiles between the contents of the small intestine and large intestine. The dominant genera in the small intestine belonged to aerobe or facultative anaerobe categories, whereas the main genera in the large intestine were all anaerobes. Compared to the GI tract, the composition of microbiome was quite different in feces. The microbial profile in large intestine was more similar to feces than those in the small intestine, with the similarity of 0.75 and 0.38 on average, respectively. Microbial functions, predicted by metagenome profiles, showed the enrichment associated with metabolism pathway and metabolic disease in large intestine and feces while higher abundance of infectious disease, immune function disease, and cancer in small intestine. Fecal microbes also showed enriched function in metabolic pathways compared to microbes from pooled gut contents. Our study extended the understanding of dynamic shift of gut microbes during pig growth and also characterized the profiles of bacterial communities across GI tracts of mature pigs.

Genome sequences of wild and domestic bactrian camels

Bactrian camels serve as an important means of transportation in the cold desert regions of China and Mongolia. Here we present a 2.01 Gb draft genome sequence from both a wild and a domestic bactrian camel. We estimate the camel genome to be 2.38 Gb, containing 20,821 protein-coding genes. Our phylogenomics analysis reveals that camels shared common ancestors with other even-toed ungulates about 55–60 million years ago. Rapidly evolving genes in the camel lineage are significantly enriched in metabolic pathways, and these changes may underlie the insulin resistance typically observed in these animals. We estimate the genome-wide heterozygosity rates in both wild and domestic camels to be 1.0 × 10−3. However, genomic regions with significantly lower heterozygosity are found in the domestic camel, and olfactory receptors are enriched in these regions. Our comparative genomics analyses may also shed light on the genetic basis of the camels remarkable salt tolerance and unusual immune system.

Complete Genome Sequence of Streptococcus thermophilus Strain ND03

Streptococcus thermophilus strain ND03 is a Chinese commercial dairy starter used for the manufacture of yogurt. It was isolated from naturally fermented yak milk in Qinghai, China. We present here the complete genome sequence of ND03 and compare it to three other published genomes of Streptococcus thermophilus strains.

Complete Genome Sequence of Lactobacillus helveticus H10

Lactobacillus helveticus strain H10 was isolated from traditional fermented milk in Tibet, China. We sequenced the whole genome of strain H10 and compared it to the published genome sequence of Lactobacillus helveticus DPC4571.

Complete genome sequence of Lactobacillus delbrueckii subsp. bulgaricus strain ND02.

Lactobacillus delbrueckii subsp. bulgaricus strain ND02 is a Chinese commercial dairy starter used for the manufacture of yoghurt. It was isolated from naturally fermented yak milk in Qinghai, China. Here, we report the main genome features of ND02 and several differences with two other published genomes of Lactobacillus delbrueckii subsp. bulgaricus strains.

Validation of reference genes for real-time quantitative PCR studies in gene expression levels of Lactobacillus casei Zhang

Lactobacillus casei Zhang, a potential probiotic strain isolated from homemade koumiss in Inner Mongolia of China, has been sequenced and deposited in GenBank. Real-time quantitative PCR is one of the most widely used methods to study related gene expression levels of Lactobacillus casei Zhang. For accurate and reliable gene expression analysis, normalization of gene expression data using one or more appropriate reference genes is essential. We used three statistical methods (geNorm, NormFinder, and BestKeeper) to evaluate the expression levels of five candidate reference genes (GAPD, gyrB, LDH, 16s rRNA, and recA) under different culture conditions and different growth phases to find a suitable housekeeping gene which can be used as internal standard. The results showed that the best reference gene was GAPD, and a set of two genes, GAPD and gyrB (which were the most stable reference genes), is recommended for normalization of real-time quantitative PCR experiments under all the different experimental conditions tested. The systematic validation of candidate reference genes is important for obtaining reliable analysis results of real-time quantitative PCR studies in gene expression levels of Lactobacillus casei Zhang.

Body Weight Selection Affects Quantitative Genetic Correlated Responses in Gut Microbiota

The abundance of gut microbiota can be viewed as a quantitative trait, which is affected by the genetics and environment of the host. To quantify the effects of host genetics, we calculated the heritability of abundance of specific microorganisms and genetic correlations among them in the gut microbiota of two lines of chickens maintained under the same husbandry and dietary regimes. The lines, which originated from a common founder population, had undergone >50 generations of selection for high (HW) or low (LW) 56-day body weight and now differ by more than 10-fold in body weight at selection age. We identified families of Paenibacillaceae, Streptococcaceae, Helicobacteraceae, and Burkholderiaceae that had moderate heritabilities. Although there were no obvious phenotypic correlations among gut microbiota, significant genetic correlations were observed. Moreover, the effects were modified by genetic selection for body weight, which altered the quantitative genetic background of the host. Heritabilities for Bacillaceae, Flavobacteriaceae, Helicobacteraceae, Comamonadaceae, Enterococcaceae, and Streptococcaceae were moderate in LW line and little to zero in the HW line. These results suggest that loci associated with these microbiota families, while exhibiting genetic variation in LW, have been fixed in HW line. Also, long term selection for body weight has altered the genetic correlations among gut microbiota. No microbiota families had significant heritabilities in both the LW and HW lines suggesting that the presence and/or absence of a particular microbiota family either has a strong growth promoting or inhibiting effect, but not both. These results demonstrate that the quantitative genetics of the host have considerable influence on the gut microbiota.

Analysis of horse genomes provides insight into the diversification and adaptive evolution of karyotype

Karyotypic diversification is more prominent in Equus species than in other mammals. Here, using next generation sequencing technology, we generated and de novo assembled quality genomes sequences for a male wild horse (Przewalskis horse) and a male domestic horse (Mongolian horse), with about 93-fold and 91-fold coverage, respectively. Portion of Y chromosome from wild horse assemblies (3 M bp) and Mongolian horse (2 M bp) were also sequenced and de novo assembled. We confirmed a Robertsonian translocation event through the wild horses chromosomes 23 and 24, which contained sequences that were highly homologous with those on the domestic horses chromosome 5. The four main types of rearrangement, insertion of unknown origin, inserted duplication, inversion, and relocation, are not evenly distributed on all the chromosomes, and some chromosomes, such as the X chromosome, contain more rearrangements than others, and the number of inversions is far less than the number of insertions and relocations in the horse genome. Furthermore, we discovered the percentages of LINE_L1 and LTR_ERV1 are significantly increased in rearrangement regions. The analysis results of the two representative Equus species genomes improved our knowledge of Equus chromosome rearrangement and karyotype evolution.

Proteomic comparison of the probiotic bacterium Lactobacillus casei Zhang cultivated in milk and soy milk

Soy milk is regarded as a substitute for milk and has become popular in varied diets throughout the world. It has been shown that a newly characterized probiotic bacterium (Lactobacillus casei Zhang) actually grows faster in soy milk than in bovine milk. To elucidate the mechanism involved, we carried out a proteomic analysis to characterize bacterial proteins that varied upon growth in soy milk and bovine milk at 3 different growth phases, and compare their expression under these conditions. A total of 104 differentially expressed spots were identified from different phases using a peptide mass fingerprinting assay. Functional analysis revealed that a major part of these identified proteins is associated with transport and metabolism of carbohydrates, nucleotides, and amino acids as well. The results from our proteomic analysis were clarified by real-time quantitative PCR assay, which showed that Lb. casei Zhang loci involved in purine and pyrimidine biosynthesis were transcriptionally enhanced during growth in soy milk at lag phase (pH 6.4), whereas the loci involved in carbohydrate metabolism were upregulated in bovine milk. Particularly, our results showed that l-glutamine might play an important role in the growth of Lb. casei Zhang in soy milk and bovine milk, perhaps by contributing to purine, pyrimidine, and amino sugar metabolism.