Abstract:Background: Wheat straw is one of the most abundant crop residues produced in the world, making it highly interesting as a substrate for biogas production. However, due to the complex structure, its degradability and gas yield are low. The degradability can be improved by pre-treatment, making the material more accessible to microbial degradation. Methods: To investigate the microbial response to straw as a feed stock for biogas production, this study examined the community structure of cellulose-degrading bac… Show more
“…A 1 : 10 dilution (v/v) of DNA template was included for each sample to identify potential inhibition of the PCR reaction. Melt curve analysis and qPCR data processing were conducted as described previously (Sun et al ). To determine differences in abundance of different bacteria between skimmed and whole milk samples, the Welch's t ‐test was conducted using r (Welch ; R Core Team ).…”
Section: Methodsmentioning
confidence: 99%
“…The primers used in this study are listed in Table 2. The standard curve for each primer set was constructed using genomic DNA prepared from the corresponding strain as described previously (Sun et al 2014 Melt curve analysis and qPCR data processing were conducted as described previously (Sun et al 2013). To determine differences in abundance of different bacteria between skimmed and whole milk samples, the Welch's t-test was conducted using R (Welch 1947; R Core Team 2019).…”
Aims
To develop a protocol for DNA extraction using whole milk and further, to investigate how the use of whole instead of skimmed milk during DNA extraction affected the resulting microbial composition.
Methods and Results
In a model study, three selected bacterial species (Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 11775 and Lactobacillus reuteri PTA 4659) were added to raw milk and their distribution between different milk fractions was examined by cultivation on selective agar plates. Quantitative real‐time PCR (qPCR) assays and Illumina amplicon sequencing were conducted after DNA extraction of whole milk and skimmed milk. In addition, fluorescent microscopy was used to visualize the distribution of Lactobacillus reuteri R2LC mCherry in milk samples with different fat contents. Depending on spike‐in bacterial species, recovery rates of 7·4–26·5% of added bacteria were obtained in the fat fraction in culture‐based enumeration. qPCR showed a 7‐9 fold increase in recovery of spike‐in bacteria when the milk fat fraction was combined with the pellet during the DNA extraction step. In the Illumina 16S amplicon approach, relative abundance of six of the top 11 operational taxonomic units identified differed significantly when comparing skimmed milk and whole milk as starting material. Fluorescent microscopy images demonstrated that L. reuteri R2LC mCherry was associated with fat globules in whole milk samples.
Conclusions
This study demonstrates that milk fat harbours bacterial species that might be underestimated when skimmed milk, rather than whole milk, is used for DNA extraction.
Significance and Impact of the Study
This study emphasizes the importance of using whole instead of skimmed milk for DNA extraction. A protocol for extracting DNA from whole milk is suggested.
“…A 1 : 10 dilution (v/v) of DNA template was included for each sample to identify potential inhibition of the PCR reaction. Melt curve analysis and qPCR data processing were conducted as described previously (Sun et al ). To determine differences in abundance of different bacteria between skimmed and whole milk samples, the Welch's t ‐test was conducted using r (Welch ; R Core Team ).…”
Section: Methodsmentioning
confidence: 99%
“…The primers used in this study are listed in Table 2. The standard curve for each primer set was constructed using genomic DNA prepared from the corresponding strain as described previously (Sun et al 2014 Melt curve analysis and qPCR data processing were conducted as described previously (Sun et al 2013). To determine differences in abundance of different bacteria between skimmed and whole milk samples, the Welch's t-test was conducted using R (Welch 1947; R Core Team 2019).…”
Aims
To develop a protocol for DNA extraction using whole milk and further, to investigate how the use of whole instead of skimmed milk during DNA extraction affected the resulting microbial composition.
Methods and Results
In a model study, three selected bacterial species (Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 11775 and Lactobacillus reuteri PTA 4659) were added to raw milk and their distribution between different milk fractions was examined by cultivation on selective agar plates. Quantitative real‐time PCR (qPCR) assays and Illumina amplicon sequencing were conducted after DNA extraction of whole milk and skimmed milk. In addition, fluorescent microscopy was used to visualize the distribution of Lactobacillus reuteri R2LC mCherry in milk samples with different fat contents. Depending on spike‐in bacterial species, recovery rates of 7·4–26·5% of added bacteria were obtained in the fat fraction in culture‐based enumeration. qPCR showed a 7‐9 fold increase in recovery of spike‐in bacteria when the milk fat fraction was combined with the pellet during the DNA extraction step. In the Illumina 16S amplicon approach, relative abundance of six of the top 11 operational taxonomic units identified differed significantly when comparing skimmed milk and whole milk as starting material. Fluorescent microscopy images demonstrated that L. reuteri R2LC mCherry was associated with fat globules in whole milk samples.
Conclusions
This study demonstrates that milk fat harbours bacterial species that might be underestimated when skimmed milk, rather than whole milk, is used for DNA extraction.
Significance and Impact of the Study
This study emphasizes the importance of using whole instead of skimmed milk for DNA extraction. A protocol for extracting DNA from whole milk is suggested.
“…summarised those approaches that are used to discover novel enzymes. More recently, Quantitative Polymerase Chain Reaction (Q-PCR), and sequencing methods were applied to determine the abundance of genes that are coding for GH families (Pereyra et al, 2010;Sun et al, 2013). Although these approaches showed the diversity of GH 48 families, the interpretation of these results should be carefully considered since the amplicon size of the targeted genes are relatively small and the diversity of GH 48 enzyme family is very large for designing successful primers.…”
Section: Chitinase and Lichanase Activitymentioning
In recent years, biogas production from complex biomass has received great interest. Therefore, many studies have been conducted to understand the anaerobic digestion process and to characterise responsible microbes for the biochemical conversions. Although our knowledge about biogas production in general is rapidly increasing, less information is available about hydrolytic microbes within anaerobic bioreactors. Here, we pinpoint the urgent need for solid fundamental knowledge about hydrolytic bacteria within biogas plants. In this review, current knowledge about anaerobic hydrolytic microbes is presented, including their abundance in biogas plants, and the factors impacting their activity.
“…Fungi, such as Trichodermo spp., can also be used to break down lignin before the biomass is added to the digester increasing biogas yields by up to 400% (Muthangya et al 2009; Wagner et al 2013). The bacteria used as inoculum in anaerobic digesters can also be optimized to break down lignin (Sun et al 2013). For example, Clostridium thermocellum, Comamonas testosteroni , and Pseudonocardia autotrophica contain endoglucanases, exoglucanases, xylanases, and lignolitic enzymes highly effective in degrading plant cell walls (Himmel et al 2007; Liao et al 2016).…”
Bioenergy may be one of the ‘ecosystem services of the future’ for grasslands managed for conservation as the concept of bio-based economies is embraced worldwide. Although the idea of producing biogas and bioethanol from lignocellulosic material is not new, there are currently few regional-level comparisons of the bioenergy potential of high-diversity grasslands that would establish whether this could be a competitive bioenergy feedstock for farmers. Comparing the chemical composition and biogas yields of biomass samples from 13 grasslands in England and 73 other bioenergy feedstocks reveals that the lignin content of biomass from grasslands managed for conservation was up to 50% less than other bioenergy crops. Grasslands managed for conservation yielded up to 160% more biogas per ton dry matter than cereals or crop waste and only slightly less than Miscanthus. GIS modeling of the estimated biogas yields of grasslands managed for conservation and fields currently sown with Miscanthus show that grasslands are larger (20.57 ha) than Miscanthus fields (5.95 ha) and are projected to produce up to 117% more biogas per average field. Future incorporation of high-diversity grasslands into local and nation-wide energy plans may help reduce global fossil-fuel use in the 21st century.
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