Metagenome sequencing to unveil microbial community composition and prevalence of antibiotic and metal resistance genes in hypersaline and hyperalkaline Lonar Lake, India

2020 ◽  
Vol 110 ◽  
pp. 105827 ◽  
Author(s):  
Jaya Chakraborty ◽  
Vibhavari Sapkale ◽  
Manan Shah ◽  
Vinay Rajput ◽  
Gajanan Mehetre ◽  
...  
Keyword(s):  
Microbial Community ◽  
Community Composition ◽  
Resistance Genes ◽  
Microbial Community Composition ◽  
Metal Resistance ◽  
Lonar Lake ◽  
Metagenome Sequencing

scholarly journals Host-associated microbe PCR (hamPCR): accessing new biology through convenient measurement of both microbial load and community composition

2020 ◽  
Author(s):  
Derek S. Lundberg ◽  
Pratchaya Pramoj Na Ayutthaya ◽  
Annett Strauß ◽  
Gautam Shirsekar ◽  
Wen-Sui Lo ◽  
...  
Keyword(s):  
Microbial Community ◽  
Community Composition ◽  
Compositional Data ◽  
Microbial Community Composition ◽  
Cost Effective ◽  
Amplicon Sequencing ◽  
Microbial Load ◽  
Rrna Gene ◽  
Metagenome Sequencing ◽  
Transformative Approach

AbstractThe ratio of microbial population size relative to the amount of host tissue, or “microbial load”, is a fundamental metric of colonization and infection, but it cannot be directly deduced from microbial amplicon data such as 16S rRNA gene counts. Because conventional methods to determine load, such as serial dilution plating or quantitative PCR, add substantial experimental burden, they are only rarely paired with amplicon sequencing. Alternatively, whole metagenome sequencing of DNA contributed by host and microbes both reveals microbial community composition and enables determination of microbial load, but host DNA typically greatly outweighs microbial DNA, severely limiting the cost-effectiveness and scalability of this approach. We introduce host-associated microbe PCR (hamPCR), a robust amplicon sequencing strategy to quantify microbial load and describe interkingdom microbial community composition in a single, cost-effective library. We demonstrate its accuracy and flexibility across multiple host and microbe systems, including nematodes and major crops. We further present a technique that can be used, prior to sequencing, to optimize the host representation in a batch of libraries without loss of information. Because of its simplicity, and the fact that it provides an experimental solution to the well-known statistical challenges provided by compositional data, hamPCR will become a transformative approach throughout culture-independent microbiology.

Microbial Community Composition During Artificial Frosting of Dried Persimmon Fruits

LWT ◽  
2021 ◽  
pp. 111694
Author(s):  
Xiaoxi Chen ◽  
Qin Chen ◽  
Yaxin Liu ◽  
Bin Liu ◽  
Xubo Zhao ◽  
...  
Keyword(s):  
Microbial Community ◽  
Community Composition ◽  
Microbial Community Composition

scholarly journals Benchmarking laboratory processes to characterise low-biomass respiratory microbiota

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Raiza Hasrat ◽  
Jolanda Kool ◽  
Wouter A. A. de Steenhuijsen Piters ◽  
Mei Ling J. N. Chu ◽  
Sjoerd Kuiling ◽  
...  
Keyword(s):  
Microbial Community ◽  
Community Composition ◽  
Microbial Community Composition ◽  
Positive Control ◽  
Rrna Gene ◽  
Elution Buffer ◽  
Community Profile ◽  
Microbial Community Profile ◽  
Microbial Dna ◽  
Pcr Conditions

AbstractThe low biomass of respiratory samples makes it difficult to accurately characterise the microbial community composition. PCR conditions and contaminating microbial DNA can alter the biological profile. The objective of this study was to benchmark the currently available laboratory protocols to accurately analyse the microbial community of low biomass samples. To study the effect of PCR conditions on the microbial community profile, we amplified the 16S rRNA gene of respiratory samples using various bacterial loads and different number of PCR cycles. Libraries were purified by gel electrophoresis or AMPure XP and sequenced by V2 or V3 MiSeq reagent kits by Illumina sequencing. The positive control was diluted in different solvents. PCR conditions had no significant influence on the microbial community profile of low biomass samples. Purification methods and MiSeq reagent kits provided nearly similar microbiota profiles (paired Bray–Curtis dissimilarity median: 0.03 and 0.05, respectively). While profiles of positive controls were significantly influenced by the type of dilution solvent, the theoretical profile of the Zymo mock was most accurately analysed when the Zymo mock was diluted in elution buffer (difference compared to the theoretical Zymo mock: 21.6% for elution buffer, 29.2% for Milli-Q, and 79.6% for DNA/RNA shield). Microbiota profiles of DNA blanks formed a distinct cluster compared to low biomass samples, demonstrating that low biomass samples can accurately be distinguished from DNA blanks. In summary, to accurately characterise the microbial community composition we recommend 1. amplification of the obtained microbial DNA with 30 PCR cycles, 2. purifying amplicon pools by two consecutive AMPure XP steps and 3. sequence the pooled amplicons by V3 MiSeq reagent kit. The benchmarked standardized laboratory workflow presented here ensures comparability of results within and between low biomass microbiome studies.

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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