scholarly journals Shotgun Metagenomic Analysis Reveals New Insights into Bacterial Community Profiles in Tempeh

2020 ◽  
Author(s):  
Adi Yulandi ◽  
Antonius Suwanto ◽  
Diana Elizabeth Waturangi ◽  
Aris Tri Wahyudi
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Iron Complex ◽  
Metagenomic Analysis ◽  
Whole Genome Sequence ◽  
Sequencing Analysis ◽  
16S Rrna Analysis ◽  
Functional Profiling

Abstract Objective: Amplicon sequencing targeting 16S ribosomal RNA (rRNA) has been widely used for the profile analysis of the microbial community from fermented food samples. Previous results of 16S rRNA analysis metagenome showed that Firmicutes was the dominant phylum in tempeh. However, polymerase chain reaction (PCR) steps on amplicon sequencing analysis and intragenomic heterogeneity within 16S rRNA are believed to contribute to bias in the estimation of microbial community composition. An alternative approach known as shotgun metagenomic might be able to avoid this limitation. In this study, we employed total metagenomic DNA fragments that were sequenced directly for taxonomic dan functional profiling analysis.Results: Taxonomic profiling showed that Proteobacteria, Firmicutes, and Bacteroidetes were the dominant phyla from the direct shotgun metagenomic analysis in all tempeh samples. In terms of composition, this shotgun metagenomic study revealed that Proteobacteria was the most abundant phylum. Functional profiling showed that iron complex outer-membrane recepter protein (KEGG ID: K02014) was the most transcribed genes based in this metagenomic analysis. The binning pipeline could reveal almost complete whole genome sequence of Lactobacillus fermentum, Enterococcus cecorum, Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii.

scholarly journals Shotgun Metagenomic Analysis Reveals New Insights on Bacterial Community Profiles in Tempeh

2020 ◽  
Author(s):  
Adi Yulandi ◽  
Diana Elizabeth Waturangi ◽  
Aris Tri Wahyudi ◽  
Antonius Suwanto
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Iron Complex ◽  
Fermented Food ◽  
Metagenomic Analysis ◽  
Sequencing Analysis ◽  
16S Rrna Analysis ◽  
Functional Profiling

AbstractObjectiveAmplicon sequencing targeted 16S ribosomal RNA (rRNA) has been widely used for the analysis profile of the microbial community from fermented food samples. Previous results of 16S rRNA analysis metagenome showed that Firmicutes was the dominant phylum in tempeh. However, polymerase chain reaction (PCR) steps on amplicon sequencing analysis and intragenomic heterogeneity within 16S rRNA are believed to contribute to bias in the estimation of microbial community composition. An alternative approach known as shotgun metagenomic might be able to avoid this limitation. In this study, we employed total metagenomic DNA fragments sequenced directly for taxonomic dan functional profiling analysis.ResultTaxonomic profiling showed that Proteobacteria, Firmicutes, and Bacteroidetes were the dominant phyla from direct shotgun metagenomic analysis in all tempeh samples. In terms of composition, the shotgun metagenomic study revealed that Proteobacteria was the most relatively abundant phylum. Functional profiling showed that iron complex outer-membrane recepter protein (KEGG ID: K02014) was the most transcribed genes based on metagenome from tempeh samples.

scholarly journals Shotgun Metagenomic Analysis Reveals New Insights into Bacterial Community Profiles in Tempeh

2020 ◽  
Author(s):  
Adi Yulandi ◽  
Antonius Suwanto ◽  
Diana Elizabeth Waturangi ◽  
Aris Tri Wahyudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Food Samples ◽  
Iron Complex ◽  
Fermented Food ◽  
Metagenomic Analysis ◽  
Whole Genome Sequence ◽  
Sequencing Analysis ◽  
Functional Profiling

Abstract Objective: Amplicon sequencing targeting 16S ribosomal RNA (rRNA) has been widely used to profile the microbial community from fermented food samples. However, polymerase chain reaction (PCR) steps on amplicon sequencing analysis and intragenomic heterogeneity within 16S rRNA are believed to contribute to bias in estimating microbial community composition. As potential paraprobiotics sources, a comprehensive profiling study of tempeh microbial ecology could contribute to tempeh product development. This study employed a shotgun metagenomic approach, where metagenome fragments from tempeh samples were sequenced directly for taxonomic and functional profiling analysis.Results: Taxonomic profiling showed that Proteobacteria, Firmicutes, and Bacteroidetes were the dominant phyla from the shotgun metagenomic analysis in all tempeh samples. In terms of composition, this shotgun metagenomic study revealed that Proteobacteria was the most abundant phylum. Functional profiling showed that iron complex outer-membrane recepter protein (KEGG ID: K02014) was the most transcribed gene based on this metagenomic analysis. The metagenome-assembled genomes (MAGs) results from the binning pipeline could reveal almost complete whole genome sequence of Lactobacillus fermentum, Enterococcus cecorum, Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii.

scholarly journals Shotgun Metagenomic Analysis Reveals New Insights into Bacterial Community Profiles in Tempeh

2020 ◽  
Author(s):  
Adi Yulandi ◽  
Antonius Suwanto ◽  
Diana Elizabeth Waturangi ◽  
Aris Tri Wahyudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Food Samples ◽  
Iron Complex ◽  
Fermented Food ◽  
Metagenomic Analysis ◽  
Whole Genome Sequence ◽  
Sequencing Analysis ◽  
Functional Profiling

Abstract Objective: Amplicon sequencing targeting 16S ribosomal RNA (rRNA) has been widely used to profile the microbial community from fermented food samples. However, polymerase chain reaction (PCR) steps on amplicon sequencing analysis and intragenomic heterogeneity within 16S rRNA are believed to contribute to bias in estimating microbial community composition. As potential paraprobiotics sources, a comprehensive profiling study of tempeh microbial ecology could contribute to tempeh product development. This study employed a shotgun metagenomic approach, where metagenome fragments from tempeh samples were sequenced directly for taxonomic and functional profiling analysis.Results: Taxonomic profiling showed that Proteobacteria, Firmicutes, and Bacteroidetes were the dominant phyla from the shotgun metagenomic analysis in all tempeh samples. In terms of composition, this shotgun metagenomic study revealed that Proteobacteria was the most abundant phylum. Functional profiling showed that iron complex outer-membrane recepter protein (KEGG ID: K02014) was the most transcribed gene based on this metagenomic analysis. The metagenome-assembled genomes (MAGs) results from the binning pipeline could reveal almost complete whole genome sequence of Lactobacillus fermentum, Enterococcus cecorum, Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii.

scholarly journals Shotgun metagenomic analysis reveals new insights into bacterial community profiles in tempeh

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Adi Yulandi ◽  
Antonius Suwanto ◽  
Diana Elizabeth Waturangi ◽  
Aris Tri Wahyudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Food Samples ◽  
Iron Complex ◽  
Fermented Food ◽  
Metagenomic Analysis ◽  
Whole Genome Sequence ◽  
Sequencing Analysis ◽  
Functional Profiling

Abstract Objective Amplicon sequencing targeting 16S ribosomal RNA (rRNA) has been widely used to profile the microbial community from fermented food samples. However, polymerase chain reaction (PCR) steps on amplicon sequencing analysis and intragenomic heterogeneity within 16S rRNA are believed to contribute to bias in estimating microbial community composition. As potential paraprobiotics sources, a comprehensive profiling study of tempeh microbial ecology could contribute to tempeh product development. This study employed a shotgun metagenomic approach, where metagenome fragments from tempeh samples were sequenced directly for taxonomic and functional profiling analysis. Results Taxonomic profiling showed that Proteobacteria, Firmicutes, and Bacteroidetes were the dominant phyla from the shotgun metagenomic analysis in all tempeh samples. In terms of composition, this shotgun metagenomic study revealed that Proteobacteria was the most abundant phylum. Functional profiling showed that iron complex outer-membrane recepter protein (KEGG ID: K02014) was the most transcribed gene based on this metagenomic analysis. The metagenome-assembled genomes (MAGs) results from the binning pipeline could reveal almost complete whole genome sequence of Lactobacillus fermentum, Enterococcus cecorum, Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii.

scholarly journals Evaluation of the microbial community structure of potable water samples from occupied and unoccupied buildings using16S rRNA amplicon sequencing

2020 ◽  
Author(s):  
Kimothy L Smith ◽  
Howard A Shuman ◽  
Douglas Findeisen
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
Water Samples ◽  
Ad Hoc ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
The Other ◽  
Water Usage ◽  
16S Rrna Amplicon Sequencing ◽  
Oxford Nanopore

AbstractWe conducted two studies of water samples from buildings with normal occupancy and water usage compared to water from buildings that were unoccupied with little or no water usage due to the COVID-19 shutdown. Study 1 had 52 water samples obtained ad hoc from buildings in four metropolitan locations in different states in the US and a range of building types. Study 2 had 36 water samples obtained from two buildings in one metropolitan location with matched water sample types. One of the buildings had been continuously occupied, and the other substantially vacant for approximately 3 months. All water samples were analyzed using 16S rRNA amplicon sequencing with a MinION from Oxford Nanopore Technologies. More than 127 genera of bacteria were identified, including genera with members that are known to include more than 50 putative frank and opportunistic pathogens. While specific results varied among sample locations, 16S rRNA amplicon abundance and the diversity of bacteria were higher in water samples from unoccupied buildings than normally occupied buildings as was the abundance of sequenced amplicons of genera known to include pathogenic bacterial members. In both studies Legionella amplicon abundance was relatively small compared to the abundance of the other bacteria in the samples. Indeed, when present, the relative abundance of Legionella amplicons was lower in samples from unoccupied buildings. Legionella did not predominate in any of the water samples and were found, on average, in 9.6% of samples in Study 1 and 8.3% of samples in Study 2.SynopsisComparison of microbial community composition in the plumbing of occupied and unoccupied buildings during the COVID-19 pandemic shutdown.

scholarly journals Comparative Analysis of Chicken Cecal Microbial Diversity and Taxonomic Composition in Response to Dietary Variation using 16S rRNA Amplicon Sequencing

2021 ◽  
Author(s):  
Zubia Rashid ◽  
Muhammad Zubair Yousaf ◽  
Syed Muddassar Hussain Gilani ◽  
Sitwat Zehra ◽  
Ashaq Ali ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
Organic Acids ◽  
Microbial Diversity ◽  
Relative Abundance ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Feed Additives ◽  
Poultry Feed ◽  
16S Rrna Amplicon Sequencing

Abstract Antibiotic resistance poses a serious threat to human and animal health. As a consequence, their use in conventional poultry feed may be replaced by non-antibiotic additives (alternatives to antibiotics, ATAs). Phytogenic feed additives and organic acids have been gaining considerable attention that could abate the proliferation of pathogenic bacteria and strengthen gut function in broiler chickens. The aim of this study was to evaluate the effects of phytogenic feed additives and organic acids on cecal microbial diversity using 16S rRNA amplicon sequencing of the V3-V4 region. In this study, 240 chicks were divided into five treatments comprising: a controlled basal diet (CON), antibiotic group (AB), phytogenic feed additives (PHY), organic acids (ORG) and a combination of PHY + ORG (COM). A distinctive microbial community structure was observed amongst different treatments with an increased microbial diversity in AB, ORG and COM (p < 0.05). The synergistic effects of PHY and ORG increased the population of beneficial bacteria that belonged to the phyla: Firmicutes, Bacteroides and Proteobacteria in the cecum. The presence of the species Akkermansia muciniphila (involved in mucin degradation) and Bacillus safensis (a probiotic bacterium) were noticed in COM and PHY, respectively. Clustering analysis revealed a higher relative abundance of similar microbial community composition between AB and ORG groups. In conclusion, treatments with PHY and ORG modified the relative abundance and presence/absence of specific microbiota in the chicken cecum. Hence, cecal microbiota modulation through diet is a promising strategy to reduce cross-contamination of zoonotic poultry pathogens.

scholarly journals Interpretations of microbial community studies are biased by the selected 16S rRNA gene amplicon sequencing pipeline

2019 ◽  
Author(s):  
Daniel Straub ◽  
Nia Blackwell ◽  
Adrian Langarica Fuentes ◽  
Alexander Peltzer ◽  
Sven Nahnsen ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Environmental Samples ◽  
16S Rrna Gene Sequencing ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Sequencing Analysis ◽  
Rrna Gene Sequencing ◽  
Diversity Estimates

AbstractOne of the major methods to identify microbial community composition, to unravel microbial population dynamics, and to explore microbial diversity in environmental samples is DNA- or RNA-based 16S rRNA (gene) amplicon sequencing. Subsequent bioinformatics analyses are required to extract valuable information from the high-throughput sequencing approach. However, manifold bioinformatics tools complicate their choice and might cause differences in data interpretation, making the selection of the pipeline a crucial step.Here, we compared the performance of most widely used 16S rRNA gene amplicon sequencing analysis tools (i.e. Mothur, QIIME1, QIIME2, and MEGAN) using mock datasets and environmental samples from contrasting terrestrial and freshwater sites. Our results showed that QIIME2 outcompeted all other investigated tools in sequence recovery (>10 times less false positives), taxonomic assignments (>22% better F-score) and diversity estimates (>5% better assessment), while there was still room for improvement e.g. imperfect sequence recovery (recall up to 87%) or detection of additional false sequences (precision up to 72%). Furthermore, we found that microbial diversity estimates and highest abundant taxa varied among analysis pipelines (i.e. only one in five genera was shared among all analysis tools) when analyzing environmental samples, which might skew biological conclusions.Our findings were subsequently implemented in a high-performance computing conformant workflow following the FAIR (Findable, Accessible, Interoperable, and Re-usable) principle, allowing reproducible 16S rRNA gene amplicon sequence analysis starting from raw sequence files. Our presented workflow can be utilized for future studies, thereby facilitating the analysis of high-throughput DNA- or RNA-based 16S rRNA (gene) sequencing data substantially.ImportanceMicroorganisms play an essential role in biogeochemical cycling events across the globe. Phylogenetic marker gene analysis is a widely used method to explore microbial community dynamics in space and time, to predict the ecological relevance of microbial populations, or to identify microbial key players in biogeochemical cycles. Several computational analysis methods were developed to aid 16S rRNA gene analysis but choosing the best method is not trivial. In this study, we compared popular analysis methods (i.e. Mothur, QIIME1 and 2, and MEGAN) using samples with known microbial composition (i.e. mock community samples) and environmental samples from contrasting habitats (i.e. groundwater, soil, sediment, and river water). Our findings provide guidance for choosing the currently optimal 16S rRNA gene sequencing analysis method and we implemented our recommended pipeline into a reproducible workflow, which follows highest bioinformatics standards and is open source and free to use.

scholarly journals Ultra-accurate microbial amplicon sequencing with synthetic long reads

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Benjamin J. Callahan ◽  
Dmitry Grinevich ◽  
Siddhartha Thakur ◽  
Michael A. Balamotis ◽  
Tuval Ben Yehezkel
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
Amplicon Sequencing ◽  
Species Level ◽  
Full Length ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Strain Identification ◽  
Long Reads ◽  
Long Read

Abstract Background Out of the many pathogenic bacterial species that are known, only a fraction are readily identifiable directly from a complex microbial community using standard next generation DNA sequencing. Long-read sequencing offers the potential to identify a wider range of species and to differentiate between strains within a species, but attaining sufficient accuracy in complex metagenomes remains a challenge. Methods Here, we describe and analytically validate LoopSeq, a commercially available synthetic long-read (SLR) sequencing technology that generates highly accurate long reads from standard short reads. Results LoopSeq reads are sufficiently long and accurate to identify microbial genes and species directly from complex samples. LoopSeq perfectly recovered the full diversity of 16S rRNA genes from known strains in a synthetic microbial community. Full-length LoopSeq reads had a per-base error rate of 0.005%, which exceeds the accuracy reported for other long-read sequencing technologies. 18S-ITS and genomic sequencing of fungal and bacterial isolates confirmed that LoopSeq sequencing maintains that accuracy for reads up to 6 kb in length. LoopSeq full-length 16S rRNA reads could accurately classify organisms down to the species level in rinsate from retail meat samples, and could differentiate strains within species identified by the CDC as potential foodborne pathogens. Conclusions The order-of-magnitude improvement in length and accuracy over standard Illumina amplicon sequencing achieved with LoopSeq enables accurate species-level and strain identification from complex- to low-biomass microbiome samples. The ability to generate accurate and long microbiome sequencing reads using standard short read sequencers will accelerate the building of quality microbial sequence databases and removes a significant hurdle on the path to precision microbial genomics.

scholarly journals Reduced metagenome sequencing for strain-resolution taxonomic profiles

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Lars Snipen ◽  
Inga-Leena Angell ◽  
Torbjørn Rognes ◽  
Knut Rudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Good Alternative ◽  
Shotgun Sequencing ◽  
Least Square ◽  
Full Potential ◽  
Shotgun Metagenomics ◽  
Metagenome Sequencing ◽  
Reference Genomes

Abstract Background Studies of shifts in microbial community composition has many applications. For studies at species or subspecies levels, the 16S amplicon sequencing lacks resolution and is often replaced by full shotgun sequencing. Due to higher costs, this restricts the number of samples sequenced. As an alternative to a full shotgun sequencing we have investigated the use of Reduced Metagenome Sequencing (RMS) to estimate the composition of a microbial community. This involves the use of double-digested restriction-associated DNA sequencing, which means only a smaller fraction of the genomes are sequenced. The read sets obtained by this approach have properties different from both amplicon and shotgun data, and analysis pipelines for both can either not be used at all or not explore the full potential of RMS data. Results We suggest a procedure for analyzing such data, based on fragment clustering and the use of a constrained ordinary least square de-convolution for estimating the relative abundance of all community members. Mock community datasets show the potential to clearly separate strains even when the 16S is 100% identical, and genome-wide differences is < 0.02, indicating RMS has a very high resolution. From a simulation study, we compare RMS to shotgun sequencing and show that we get improved abundance estimates when the community has many very closely related genomes. From a real dataset of infant guts, we show that RMS is capable of detecting a strain diversity gradient for Escherichia coli across time. Conclusion We find that RMS is a good alternative to either metabarcoding or shotgun sequencing when it comes to resolving microbial communities at the strain level. Like shotgun metagenomics, it requires a good database of reference genomes and is well suited for studies of the human gut or other communities where many reference genomes exist. A data analysis pipeline is offered, as an R package at https://github.com/larssnip/microRMS.

scholarly journals Do initial concentration and activated sludge seasonality affect pharmaceutical biotransformation rate constants?

2021 ◽  
Author(s):  
Tamara J. H. M. van Bergen ◽  
Ana B. Rios-Miguel ◽  
Tom M. Nolte ◽  
Ad M. J. Ragas ◽  
Rosalie van Zelm ◽  
...  
Keyword(s):  
Microbial Community ◽  
Activated Sludge ◽  
Community Composition ◽  
Rate Constants ◽  
Wastewater Treatment Plants ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Initial Concentration ◽  
Different Seasons

Abstract Pharmaceuticals find their way to the aquatic environment via wastewater treatment plants (WWTPs). Biotransformation plays an important role in mitigating environmental risks; however, a mechanistic understanding of involved processes is limited. The aim of this study was to evaluate potential relationships between first-order biotransformation rate constants (kb) of nine pharmaceuticals and initial concentration of the selected compounds, and sampling season of the used activated sludge inocula. Four-day bottle experiments were performed with activated sludge from WWTP Groesbeek (The Netherlands) of two different seasons, summer and winter, spiked with two environmentally relevant concentrations (3 and 30 nM) of pharmaceuticals. Concentrations of the compounds were measured by LC–MS/MS, microbial community composition was assessed by 16S rRNA gene amplicon sequencing, and kb values were calculated. The biodegradable pharmaceuticals were acetaminophen, metformin, metoprolol, terbutaline, and phenazone (ranked from high to low biotransformation rates). Carbamazepine, diatrizoic acid, diclofenac, and fluoxetine were not converted. Summer and winter inocula did not show significant differences in microbial community composition, but resulted in a slightly different kb for some pharmaceuticals. Likely microbial activity was responsible instead of community composition. In the same inoculum, different kb values were measured, depending on initial concentration. In general, biodegradable compounds had a higher kb when the initial concentration was higher. This demonstrates that Michealis-Menten kinetic theory has shortcomings for some pharmaceuticals at low, environmentally relevant concentrations and that the pharmaceutical concentration should be taken into account when measuring the kb in order to reliably predict the fate of pharmaceuticals in the WWTP. Key points • Biotransformation and sorption of pharmaceuticals were assessed in activated sludge. • Higher initial concentrations resulted in higher biotransformation rate constants for biodegradable pharmaceuticals. • Summer and winter inocula produced slightly different biotransformation rate constants although microbial community composition did not significantly change. Graphical abstract

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