Amplicon sequencing based profiling of bacterial diversity from Krossfjorden, Arctic

Kachiprath, Bhavya; Puthumana, Jayesh; Gopi, Jayanath; Solomon, Solly; Krishnan, K. P.; Philip, Rosamma

doi:10.1016/j.dib.2018.11.101

Cited by 6 publications

(4 citation statements)

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“…Understanding of microbiome composition and functioning has advanced in recent years through the application of high-throughput next-generation sequencing (NGS) technologies for metagenomic analyses ( Quince et al, 2017 ). Popular NGS platforms such as the MISeq (Illumina) and MINion (Oxford Nanopore) coupled with metagenomic approaches that either target specific genes (16S rRNA) or the whole bacterial genome, are providing insights into complex microbial populations in the rumen, which are otherwise difficult to identify using culture-dependent approaches ( Zhou et al, 2015 ; Kachiprath et al, 2018 ; Gu et al, 2019 ). Additionally, the development of user-friendly computational software is enabling researchers to extrapolate more information from biological data.…”

Section: Introductionmentioning

confidence: 99%

Rumen Microbiome Composition Is Altered in Sheep Divergent in Feed Efficiency

et al. 2020

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Rumen microbiome composition and functionality is linked to animal feed efficiency, particularly for bovine ruminants. To investigate this in sheep, we compared rumen bacterial and archaeal populations (and predicted metabolic processes) of sheep divergent for the feed efficiency trait feed conversion ratio (FCR). In our study 50 Texel cross Scottish Blackface (TXSB) ram lambs were selected from an original cohort of 200 lambs. From these, 26 were further selected for experimentation based on their extreme FCR (High Feed Efficiency, HFE = 13; Low Feed Efficiency, LFE = 13). Animals were fed a 95% concentrate diet ad libitum over 36 days. 16S rRNA amplicon sequencing was used to investigate the rumen bacterial and archaeal communities in the liquid and solid rumen fractions of sheep divergent for FCR. Weighted UniFrac distances separated HFE and LFE archaea communities from the liquid rumen fraction (Permanova, P < 0.05), with greater variation observed for the LFE cohort (Permdisp, P < 0.05). LFE animals exhibited greater Shannon and Simpson diversity indices, which was significant for the liquid rumen fraction ( P < 0.05). Methanobrevibacter olleyae (in liquid and solid fractions) and Methanobrevibacter millerae (liquid fraction) were differentially abundant, and increased in the LFE cohort ( P.adj < 0.05), while Methanobrevibacter wolinii (liquid fraction) was increased in the HFE cohort ( P.adj < 0.05). This suggests that methanogenic archaea may be responsible for a potential loss of energy for the LFE cohort. Bacterial community composition (Permanova, P > 0.1) and diversity ( P > 0.1) was not affected by the FCR phenotype. Only the genus Prevotella 1 was differentially abundant between HFE and LFE cohorts. Although no major compositional shifts of bacterial populations were identified amongst the feed efficient cohorts ( FDR > 0.05), correlation analysis identified putative drivers of feed efficiency with Ruminococcaceae UCG-014 (liquid, rho = −0.53; solid, rho = −0.56) and Olsenella (solid, rho = −0.40) exhibiting significant negative association with FCR ( P < 0.05). Bifidobacterium and Megasphaera showed significant positive correlations with ADG. Major cellulolytic bacteria Fibrobacter (liquid, rho = 0.43) and Ruminococcus 1 (liquid, rho = 0.41; solid, rho = 41) correlated positively with FCR ( P < 0.05). Our study provides evidence that feed efficiency in sheep is likely influenced by co...

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Section: Introductionmentioning

confidence: 99%

Rumen Microbiome Composition Is Altered in Sheep Divergent in Feed Efficiency

et al. 2020

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“…Sequential-filter isolation techniques have been employed to improve the yield of environmental DNA by reducing the concentration of inhibitory compounds, e.g., humic acid, polysaccharides, metals, etc. [ 10 , 17 , 46 ]. Specifically, sediment samples contain high humic substances, which are the primary compounds co-extracted with DNA that inhibits enzymes (e.g., Taq polymerase) in PCR reactions [ 47 ].…”

Section: Discussionmentioning

confidence: 99%

“…Pre-processing sediment samples by multi-level or sequential membrane filtration have been reported to efficiently isolate high-quality DNA while reducing inhibitory compounds [ 10 , 17 – 19 ]. Sequential filtration has been used to concentrate microbial biomass and assess communities based on size fractions using filter membranes with different pore sizes [ 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

“…Solomon et al [ 10 ] demonstrated that community DNA with minimal shearing was obtained from pre-processing marine sediment samples against non-processed and performed PCR amplification of the 16S rRNA gene to confirm that the filtration method isolated high-quality DNA. A similar protocol was employed to process arctic sediment samples to characterize bacterial community structure by 16S rRNA amplicon sequencing [ 17 ]. However, there is no comprehensive information on sequential membrane filtration's potential biases on the retained microbial taxa than its non-processed counterpart, specifically whether sample pre-processing via sequential filtration compares to non-processed community profiles for quantitative measurements of freshwater microbial diversity and community structure.…”

Section: Introductionmentioning

confidence: 99%

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Sediment-associated microbial community profiling: sample pre-processing through sequential membrane filtration for 16S rRNA amplicon sequencing

Serrana

Watanabe

2022

BMC Microbiol

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Background Sequential membrane filtration as a pre-processing step for capturing sediment-associated microorganisms could provide good quality and integrity DNA that can be preserved and kept at ambient temperatures before community profiling through culture-independent molecular techniques. However, the effects of sample pre-processing via filtration on DNA-based profiling of sediment-associated microbial community diversity and composition are poorly understood. Specifically, the influences of pre-processing on the quality and quantity of extracted DNA, high-throughput DNA sequencing reads, and detected microbial taxa need further evaluation. Results We assessed the impact of pre-processing freshwater sediment samples by sequential membrane filtration (from 10, 5 to 0.22 μm pore size) for 16S rRNA-based community profiling of sediment-associated microorganisms. Specifically, we examined if there would be method-driven differences between non- and pre-processed sediment samples regarding the quality and quantity of extracted DNA, PCR amplicon, resulting high-throughput sequencing reads, microbial diversity, and community composition. We found no significant difference in the qualities and quantities of extracted DNA and PCR amplicons, and the read abundance after bioinformatics processing (i.e., denoising and chimeric-read filtering steps) between the two methods. Although the non- and pre-processed sediment samples had more unique than shared amplicon sequence variants (ASVs), we report that their shared ASVs accounted for 74% of both methods’ absolute read abundance. More so, at the genus level, the final collection filter identified most of the genera (95% of the reads) captured from the non-processed samples, with a total of 51 false-negative (2%) and 59 false-positive genera (3%). We demonstrate that while there were differences in shared and unique taxa, both methods revealed comparable microbial diversity and community composition. Conclusions Our observations highlight the feasibility of pre-processing sediment samples for community analysis and the need to further assess sampling strategies to help conceptualize appropriate study designs for sediment-associated microbial community profiling.

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