Author
Zhiliang Tan
Bio: Zhiliang Tan is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Rumen & Fermentation. The author has an hindex of 22, co-authored 158 publications receiving 1661 citations.
Topics: Rumen, Fermentation, Medicine, Dry matter, Biology
Papers published on a yearly basis
Papers
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TL;DR: It is indicated that the application of fibrolytic enzyme preparation and yeast culture could improve in vitro gas production fermentation of cereal straws.
Abstract: The effects of yeast culture and fibrolytic enzyme preparation (containing cellulase and xylanase) on in vitro fermentation characteristics of rice straw, wheat straw, maize stover, and maize stover silage were examined using an in vitro gas production technique. Four levels of yeast culture and fibrolytic enzyme supplements (0, 2.5, 5.0, and 7.5 g/kg of straw DM, respectively) were tested in a 4 x 4 factorial arrangement. Supplementation of yeast culture increased the cumulative gas production, theoretical maximum of gas production, rate of gas production, IVDMD, and in vitro OM disappearance (IVOMD), and decreased the lag time for each type of straw. Fibrolytic enzyme supplementation tended to increase cumulative gas production, theoretical maximum of gas production, and rate of gas production; prolonged lag time of gas production; and enhanced IVDMD and IVOMD for 4 types of cereal straws, with the significance of this effect being dependent on the level of supplemented enzymes. There were significant interactions between fibrolytic enzymes and yeast on all in vitro gas production parameters, IVDMD, and IVOMD of each type of straw. The outcome of this research indicated that the application of fibrolytic enzyme preparation and yeast culture could improve in vitro gas production fermentation of cereal straws.
115 citations
TL;DR: In this article, a simple apparatus was used to measure dissolved H2 (dH2) and H2 gas (gH2), and the results indicated that higher dH2 concentrations forced the fermentation pathways towards those producing less H2, and more butyrate and propionate, which as electron sinks that spare H2 production.
80 citations
TL;DR: In this article, a Logistic-Exponential (LE) model was developed by introducing a shape parameter d into the logistic function, which revealed whether rate of gas production was or was not increased during in vitro incubation.
79 citations
TL;DR: In this article, the authors used shotgun metagenomics to profile the microbiota of 370 samples that represent 10 GIT regions of seven ruminant species and identified 8745 uncultured candidate species from over 10,000 metagenome-assembled genomes.
Abstract: Gastrointestinal tract (GIT) microbiomes in ruminants play major roles in host health and thus animal production. However, we lack an integrated understanding of microbial community structure and function as prior studies are predominantly biased towards the rumen. In this study, we used shotgun metagenomics to profile the microbiota of 370 samples that represent 10 GIT regions of seven ruminant species. Our analyses reconstructed a GIT microbial reference catalog with > 154 million nonredundant genes and identified 8745 uncultured candidate species from over 10,000 metagenome-assembled genomes. The integrated gene catalog across the GIT regions demonstrates spatial associations between the microbiome and physiological adaptations, and 8745 newly characterized genomes substantially expand the genomic landscape of ruminant microbiota, particularly those from the lower gut. This substantially expands the previously known set of endogenous microbial diversity and the taxonomic classification rate of the GIT microbiome. These candidate species encode hundreds of enzymes and novel biosynthetic gene clusters that improve our understanding concerning methane production and feed efficiency in ruminants. Overall, this study expands the characterization of the ruminant GIT microbiota at unprecedented spatial resolution and offers clues for improving ruminant livestock production in the future. Having access to a comprehensive gene catalog and collections of microbial genomes provides the ability to perform efficiently genome-based analysis to achieve a detailed classification of GIT microbial composition and function. Our study will bring unprecedented power in future association studies to investigate the impact of the GIT microbiota in ruminant health and production.
73 citations
TL;DR: This review work revealed that the addition of S. cerevisiae in poultry feed causes a phenomenon called competitive exclusion of pathogenic bacteria capable of causing disease adhere to the yeast surface, and so these benefits are reflected on the overall poultry health.
Abstract: The production of livestock and poultry faces major challenges to meet the global demand for meat and dairy products and eggs due to a steady increase in the world's population and the ban of antibiotics in animal production. This ban has forced animal nutritionists to seek for natural alternatives to antibiotics. In this context, the yeast Saccharomyces cerevisiae has received considerable attention in the last decade. It has been reported that feed supplementation with live yeast cells improve feed efficiency, enhance feed digestibility, increase animal performance, reduce the number of pathogenic bacteria, improve animal health and reduce the negative environmental impacts of livestock production. The current review sheds light on the effects of the use of live Saccharomyces cerevisiae cells in the diets of non-ruminant and pseudo-ruminant's animals and the mechanisms by which they exert its effects. This review work revealed that the addition of Saccharomyces cerevisiae in poultry feed causes a phenomenon called competitive exclusion of pathogenic bacteria capable of causing disease adhere to the yeast surface, and so removing a large amount of harmful microorganisms and allowing the Animal defend more effectively, the production of antimicrobial agents, the balancing the gut microbiota and stimulation of host adaptive immune system and improving gut morphological structure, thus these benefits are reflected on the overall poultry health. In addition, in the presence of live Saccharomyces cerevisiae cells, the immunity of rabbits was improved due to the high number of white blood cell. In addition, apparent digestibility of acid and neutral detergent fiber was improved in horses and rabbits. Saccharomyces cerevisiae in pig diets augment mucosal immunity by increasing IgM and IgA activity against pathogens, enhance intestinal development and function, adsorb mycotoxins, modulate gut microbiota and reduce post-weaning diarrhea. This article is protected by copyright. All rights reserved.
68 citations
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01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
10,141 citations
Journal Article•
TL;DR: FastTree as mentioned in this paper uses sequence profiles of internal nodes in the tree to implement neighbor-joining and uses heuristics to quickly identify candidate joins, then uses nearest-neighbor interchanges to reduce the length of the tree.
Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.
2,436 citations
Journal Article•
509 citations
TL;DR: The current status, consumer acceptance, and market for functional foods from the global viewpoints is discussed, and future prospects for functional meat and meat products are also discussed.
459 citations
TL;DR: This dataset substantially improves the coverage of rumen microbial genomes in the public databases and represents a valuable resource for biomass-degrading enzyme discovery and studies of the rumen microbiome.
Abstract: The cow rumen is adapted for the breakdown of plant material into energy and nutrients, a task largely performed by enzymes encoded by the rumen microbiome Here we present 913 draft bacterial and archaeal genomes assembled from over 800 Gb of rumen metagenomic sequence data derived from 43 Scottish cattle, using both metagenomic binning and Hi-C-based proximity-guided assembly Most of these genomes represent previously unsequenced strains and species The draft genomes contain over 69,000 proteins predicted to be involved in carbohydrate metabolism, over 90% of which do not have a good match in public databases Inclusion of the 913 genomes presented here improves metagenomic read classification by sevenfold against our own data, and by fivefold against other publicly available rumen datasets Thus, our dataset substantially improves the coverage of rumen microbial genomes in the public databases and represents a valuable resource for biomass-degrading enzyme discovery and studies of the rumen microbiome
360 citations