Science method

Metagenomics - Science method

The genomic analysis of assemblages of organisms.
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We did surveillance of ARGs. After getting results of metagenomics, suggest the appropriate way to explore and compile results
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Prodigal is a frequently used tool to find genes from contigs by a lot of metagenomic pipeline to software. 'Gene comparison', do you mean that you want to know the function of genes? In this step, you need a proper reference database and then annotate your sequences against the database (for example CARD above mentioned), using tools like blastp, diamond, Hmmer, eggNog mapper.
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I'm planning to conduct Metagenomic analyses on DNA extracted from soil using the ITS and 16S primers. However, I'm getting bands at 2k or 3k on the gel, even though my ratios and DNA concentration are within the acceptable range.
The 260/280 ratios are approximately 1.9 and 260/230 ratios of approximately 2 and DNA concentration measures around 250-300ng/ul.
I was expecting a thicker band above 10k. I'm concerned about the quality. Should I proceed with the metagenomic analyses or should I extract the DNA again modifying my method? Do I have too much smears? I use Dneasy Pro kit for soil extraction.
Info:
Primers: Crude DNA extracted from soil with Dneasy Qiagen PRO kit
Gel %: 1% gel
Ladder full name: Lambda DNA/HindIII Marker and 1kb plus
Time and Voltage: 30 mins at 80v and 1h at 80v
Sample Volume and concentration: 1 ul of 6x DNA Loading Dye and 5ul of DNA, 1A 1:1:4
Ladder conc.: 1 ul of 6x DNA Loading Dye and 5ul of Ladder and 1:1:4. 1Kb is 1:5
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The gel picture of DNA extracts looks smearing. It is not very surprising if the sample was bead processed fiercely and a bit long. The spectral parameter looks good.
With this DNA material, you can go further for PCR to get 16S or ITS fragment. The PCR products will used for amplicon sequences. If you would like to do short-gun metagenomic sequences for the genomic DNA, you can send to sequencing company, they will check the quality and quantity of your DNA extracts with good instruments, and contact you whether the samples are good or not for sequencing.
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Hello,
I recently received metagenomic 16S rRNA gene sequence data from a company, which includes both raw reads, and clean data with barcodes removed. My goal is to analyze these sequences and obtain information on the taxonomic diversity and abundance of the species present in the sample.
Since I use a Windows system and cannot utilize Mac or Linux, I would greatly appreciate guidance on how to proceed with this analysis. Are there any web server-based applications available that can assist with this task?
Furthermore, if there are any researchers or experts interested in this project, I would be grateful to explore potential collaborations. Please feel free to reach out to me if you are interested or have any recommendations.
Thank you in advance for your assistance.
Best regards
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Hi, our lab members have used MOTHUR to analyze the amplicon data. The team members of mothur are extremely active and give you instant feedbacks on your work problems. You can check these papers for reference:
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How do scientists use metagenomics and high-throughput sequencing technologies to study microbial communities and uncover novel microbial species and functions?
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Hevar Neaz This forum is not ChatGPT. Try to figure out the basic information yourself and then ask any remaining specific questions, which only experts in the field may be able to answer.
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what's the difference between gene abundance in metagenomics and expression value in metatranscriptomics
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Metagenomics: DNA level.
Metatranscriptomics: RNA level.
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AS the title. The fecal samples were stored in the -80 ℃ refrigerator for several years. Want to know if it is suitable for 16sRNA or metagenomic sequencing to analyze the gut microbiota.
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* The Mice stool samples can be stored in -80°C for up to 2 years without significant loss of microbial diversity or composition.
References:
Thanks
Samir
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Please suggest a website, API, or other solutions to sequence similarity searches on many (all available) metagenomic libraries without downloading the metagenomic reads or assemblies.
Thank you
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You can use NCBI for that. Use project in SRA explorer.
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I have some soil samples from wheat rhizosphere. Which physical parameters may I check for a metagenomic analysis? Will approximately 20 grams of soil be enough for all tests?
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Hi Mirza, for metagenomics analysis the required edaphic properties may vary based on your specific research question as also mentioned by Pankaj Kumar Singh . Physical parameters such as soil pH, soil moisture or soil water content, bulk density, texture, porosity, water holding capacity, aggregate stability, electric conductivity etc. may be investigated. Further, Soil nutrients in terms of C (organic and inorganic carbon, dissolved organic carbon, total carbon, labile and recalcitrant carbon), N (organic and inorganic, total nitrogen), Phosphorus etc. may be determined. I also suggest to analyze soil microbial biomass carbon to understand the variabilities in the metagenomic data better.
If you want help on how to understand the correlations of these parameters with the metagenomic data please check the following article:
Thanks and all the best in exploring your research.
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which method should be more succeful and realabel in idetifing Microbiota
Metataxonomics or the shutgun ?
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Microtaxonomy is the study of classifying and identifying microorganisms based on their genetic and phenotypic characteristics, such as morphology, biochemistry, and physiology. On the other hand, metagenomics is a field that involves the study of the genetic material recovered directly from environmental samples, including the DNA of microbial communities.
In terms of identifying microbiota, both metataxonomics and shotgun metagenomics can be successful and reliable, depending on the research question and the samples being analyzed. Metataxonomics typically involves amplifying and sequencing a particular gene, such as the 16S rRNA gene, which is commonly used to identify and classify bacterial species. Shotgun metagenomics, on the other hand, involves sequencing all the DNA present in a sample, allowing for a more comprehensive analysis of the microbial community. The choice between metataxonomics and shotgun metagenomics will depend on the specific goals of the study, the complexity of the microbial community being analyzed, and the available resources. For example, metataxonomics may be preferred if the goal is to identify specific bacterial species in a relatively simple microbial community. However, shotgun metagenomics may be more appropriate if the microbial community is complex, and a more comprehensive analysis is required.
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I am working on metagenomics datasets...I have six disease datasets...i need to find disease-specific genes and proteins for comparative analysis. I would like to know that, can we find out disease-specific genes and proteins with metagenome rather than metatranscriptome...thank you in advance..
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Yes you can find gene families by using HUMAnN (https://github.com/biobakery/humann). And then you can perform differential analyses say LDA using LEfSe (https://huttenhower.sph.harvard.edu/lefse/) to identify markers.
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How abundance calculation is done for the genes which are annotated by any reference database like MegaRes, contig file generated after de novo gene assembly is aligned to the database using Blast. Is the abundance referred to the number of contigs annotated as a specific gene or is it some other way??
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The abundance calculation for genes annotated by a reference database such as MegaRes depends on the specific approach used for gene quantification. In general, the most common method involves mapping the sequencing reads to a reference database and then counting the number of reads that map to each gene.
In your case, it sounds like you are using a de novo gene assembly approach to generate contigs, which are then aligned to the MegaRes database using BLAST. To quantify the abundance of each gene, you could count the number of contigs that align to each gene in the database. However, it is important to keep in mind that the number of contigs is not necessarily directly proportional to the expression level of a gene, as different genes may have different lengths and levels of expression.
A more accurate approach to quantifying gene expression would be to use tools such as RSEM, Kallisto, or Salmon, which use a statistical model to estimate the expression level of each gene based on the mapping of the sequencing reads. These tools take into account the differences in gene length and the potential for reads to map to multiple genes, which can improve the accuracy of the abundance estimation.
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Hello to all,
I need to perform a standard curve for metagenomic analysis with qPCR, of Treponema Denticola and Pseudoramibacter Alactolyticous, using the 16S RNA copies of my DNA.
As well I must perform a standard of a monk microbial community purchased by the Zymobiomics.
Since it is the very first time that I come across this topic I am sicking for help so I asked help from another colleague and she has helped me a lot BUT, in her calculations of 16S RNA copies and bacterial population she has used the guide of applied biosystems where the Molecular wight of DNA is reported to be 660 g/mole and according her calculations the DNA mass is equal to 9,13*10^20 bp/ng.
I asked the technical team of Zymo and they replied that I should use the following formula 6,022 x 10^23/10^9/650 which equals to 9,26462E+11 bp/ng. At this point I am totally stuck and I can not proceed with my calculations.
According to your experience could you please help me?? Should I consider as the correct molecular weight of the double stranded DNA the 650 or the 660???
Why I obtain 9,26462E+11 and my colleague 9,13*10^20??
Thank you
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Thank you so much for your reply.
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I want to know if I want to apply the metagenomics test routinely to my soil throughout planting cycles to diagnose and predict harmful pathogens that might affect crop health and overall yield. How often should I take a soil sample?
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Hello, soil microbial communities are complex and susceptible to change this emphasizes the importance of establishing a baseline for the study. Controls are needed to provide such a baseline for determining whether a change in the soil microbial community is due to the treatment and use. The tests at least need to be performed before and after the metagenomic study.
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My colleague and I are planning to do a culture-independent study on identifying specific bacteria in a river system. We just have some questions before we undertake this study.
1. If we happen to sample pathogenic bacteria, do we need to work in a BSL-2 laboratory?
2. What is the general procedure for trying to identify specific bacteria? Do we need to perform DNA extraction, cultivation, etc.? We are planning to perform 16S rRNA metagenomic analysis and are scouting sequencing centers around our country.
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Ciara Maria Ines Palma Del Rosario Look at work of Gyraite G, Katarzyte M, Schernewski G. First findings of potentially human pathogenic bacteria Vibrio in the south-eastern Baltic Sea coastal and transitional bathing waters. Marine pollution bulletin. 2019 Dec 1;149:110546.
It has most of important methods regarding identification pathogenic bacteria in water
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How to analyze LEfSe and interpret the result of soil microbes obtained through metagenomic high throughput sequencing
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Thanks Mr. Milan, satisfied with your reply.
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I have microbiome sequencing data and I have analysed it to determine which taxa are up or down-regulated with my treatment, however, this doesn't really tell me much about the metabolic changes.
Is there anything I can use that is similar to the Qiagen IPA where I can place my metagenomics data and it can tell me if there are any changes in metabolic pathways?
Any links and tutorials would be greatly appreciated!
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Is there a minimal sequence depth or length of the sequence read (>xxx bp) required to use Tax4Fun2 and PICRUSt2?
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Hello, collegues,
I'm trying to estimate the distribution of a certain kind of microorganism (eg Methanobacterium) in a certain environment (permafrost) from metagenomic data presented on various online services (NCBI, MG-RAST, https://microbeatlas.org). Such an analysis can be done on MG-RAST, but data are scarce. The service https://microbeatlas.org gives good data, but they do not correspond to the entire genus, but only to selected reference genomes. The situation is complicated by the fact that my computer is not very powerful and I cannot download 10,000 metagenomes and analyze them myself. Can you please tell me if it is possible to carry out such an analysis online, at least partially, with post-processing on a computer?
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Hello Vladimir,
I agree with Dr. Abhijeet. Working with 10000 genomes requires a lot of planning and very powerful servers.
However for smaller and more modest projects you could try working with cyverse servers, or with usegalaxy servers.
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I asked a similar question before but I'm here again. I'm working on urine samples to perform shotgun metagenomics. The biggest problem is that my A260/A280 is below 1.8 (about a third of the samples are below 1.0). I cannot redo the entire procedure since I ran out of raw sample. Is there any way for me to improve A260/A280?
Someone recommended zymo kit but doesn't zymo kit require raw sample? If not which zymo kit should I use?
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Its better to ask help from someone experienced in your lab, otherwise it will be just waste of time and resources.
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Hi everyone! I hope you all are fine. I have tried many tutorials regarding the calculation of alpha and beta diversity, however, my RStudio is throwing up so many issues. Packages aren't getting installed due to some compatibility issues. That's another discussion. However, may I request you all to kindly guide me in calculating these diversity indices?
What R script should I follow to calculate the Alpha and Beta- diversity indices. People have told me to use vegan, but how to go about it?
P.S. My input taxonomic data comes from Kraken2, so I have sample_kraken_report.txt for all my samples.
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I work in the cancer research field and human disorders by using the bioinformatics approach. These projects contain the analysis of transcriptomic data such as microarray, RNA-seq analysis, TCGA, systems biology analysis, survival analysis and etc. also, the metagenomic analysis in microbiome fired are conducted. Those interested in participating in analyses and writing articles are invited to send their CV to the email below.
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How does your institute financially support the applicants?
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What would you suggest as the most efficient method for virus concentration in DNA extraction from soil for shotgun metagenomics assay? In a situation where you have soil and shoot samples for DNA extraction, targeted for metagenomics.
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There are a number of methods that can be used to concentrate viruses from soil samples for DNA extraction and shotgun metagenomics analysis. Some of the most commonly used methods include:
  1. Physical separation: Physical separation techniques, such as filtration or centrifugation, can be used to separate viruses from other contaminants in the soil sample. Filters with a small pore size (e.g. 0.2-0.45 microns) can be used to capture viruses, while larger particles such as bacteria and soil debris are retained. Centrifugation can also be used to separate viruses based on their size and density.
  2. Chemical lysis: Chemical lysis techniques involve the use of detergents or enzymes to break down cell walls and release the viral DNA from the viral particles. This can be combined with physical separation techniques to increase the efficiency of virus recovery.
  3. Enrichment culture: Enrichment culture involves the growth of viruses in the presence of specific host cells, which can be used to selectively enrich for viruses in the soil sample. This method can be combined with DNA extraction and metagenomics techniques to identify and characterize the viral communities present in the sample.
  4. Tangential flow filtration can be a useful method for virus concentration in DNA extraction, as it allows for the efficient separation of viral particles from other contaminants in the sample. This can be particularly useful for soil samples, which can contain a wide range of contaminants that can interfere with downstream analysis. By concentrating the viral particles using tangential flow filtration, it may be possible to improve the sensitivity and accuracy of DNA extraction and metagenomics techniques.
Overall, the most efficient method for virus concentration in DNA extraction from soil will depend on the specific goals of your study and the resources available to you.
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I have done 16s metagenomic analysis (16S rRNA gene targeted amplicon data )for soil samples. I have also characterized my sample for its geochemical parameters. I want to study ordination between the two data but I don't know what or which value to input from the metagenomic sequence results. In papers, they have used OTU abundance (Picture attached and the article too).
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Input all the OTU. I used excel to calculated the Relative Read Abundance.
I think you need a file with all the OTU (columns) and samples (rows). You also need another file: first column with all the samples' name and a second column with the characterization of the geochemical parameters for each sample. The NMDS plot will show points (every sample) and a centroid (mean value), and there will be as many centroids as geochemical parameters were characterized.
I used TXT files for the process.
I hope I helped you!
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The results of metagenomic analysis are a large amount of data, please tell me what is the minimum percentage value that is significant (0.1%, 0.2%, 0.3%....) at the level of phylum, class, order, family, genus?
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Oksana Kisil You should look at dinamic changes of different taxons through the season (OK, permafrost is not a case) and on taxons differentiating locations or soil levels. Even low frequency taxons (0.1-0.2%) can be important for certain biological processes.
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I'm a grad student working on metagenomics and I ran into some issues with the samples. I collected urine samples and extracted DNA using DNeasy Blood & Tissue kit. I used NanoDrop to measure DNA concentration and ran into different issues. The problem is that the A260/280 level is too low (not to mention the contamination) and I don't know how to increase the purity level. I don't think I can collect the samples again, or at least it will take a while before I can do that again. Is there a way or a kit I can use to increase the purity level of my DNA extracts without significantly lowering DNA concentration?
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Péter Gyarmati I will try again with Qubit, but regardless of contaminations, most samples have purification level that does not meet the requirement. I may have to alter the sequencing method. Thank you for the recommendations.
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Hi all,
we would like to perform metagenomics on plant tissue as well as modern soil samples. We are not experienced with these analyses neither on plant material nor on modern soil. Has anyone recommendations for sequencing depths or tips how to choose the appropriate sequencing?
Thank you very much in advance!
Cheers,
Barbara
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I would highly recommend to discuss the topic with your sequencing facility. They will understand the aim and project and can suggest the best way. Or if what you are trying to do is the best way or not.
There are many things/information missing in your question missing without which no one can suggest any logical solution.
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I'm using Kraken2 to generate a custom database to run a shotgun metagenomics (microbiome) dataset against for associated host removal (the custom database is the host). The database builds fine, but the "--unclassifed-out" .fastq files have "x"s added to them (perhaps instead of Ns) and this is not readable in my downstream applications with qiita/qiime2. Why is this happening? I can't figure it out. Interestingly, I have done this procedure before and have not had this problem. Any thoughts as to what is going on? The output in my text editor looks like this (note the "x"s in the sequence):
FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,,F:,::,,,:,FF,,:,,::FF,FF,FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF
@A00223:522:HW3NCDSXY:1:1101:8992:1000 1:N:0:GTGCACGA+GCCTATCA
AGTGCACCTCAACCCTATGTATTGTGGACCTATACCAGTCCTTATAGAATGGCAGACTGTACCTCACTCAAxCCTATGTACxGAGATCGGAAGAGCACACGTCTGAACTCCAGTCACGTGCACGAATCTCGxxTxxCxTCxTxTxxTTxxA
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This can help you
awk '/@/{ n=NR+1 } NR==n{ gsub(/x/, "N") }1' input.fq > output.fq
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Hi,
I got the shotgun sequencing data of my samples and I ran RGI for my samples to check the ARGs present in my samples using CARD database. Now I want to calculate the abundance of ARGs. May I request if I can get any help/guidance for doing the same?
Regards
Yasir
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Hi Dr. Connor!
I used RGI on assembled reads (min length of contigs was >200bp).
Awaiting your response.
Thanks and regards
Yasir
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I did DNA extraction using Power soil DNA extraction >> the yield was very low with high level of inhibitors.
I checked the publications and I found a recommendation to use one hour incubation in tissue lysis buffer and Proteinase K from Qiagen’s DNeasy Blood and Tissue kit then I complete with power soil kit however I don't know how to do this step and the amount of the enzyme I should use?
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Hello use membrane filtration method for your ground water.
Use 0.45 um filters to filtrate water if your water highly dirty first use paper filter or mechanical filter than perform membrane filtration than use pure sterile water add to filter to wash and remove all inhibitors. the amount of filtrated water depends from content of microorganisms in initial sample if it fro 10-to100 CFU/ml the 100ml is quite enough. if more you can reduce the volume. By this way you can have pure microorganisms without any inhibitors. Than you can use any method for extraction of DNA from microorganisms. For example the benzyl chloride method for DNA extraction highly recommended.
Good luck.
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I am having problem with 16S amplification on colon content DNA from DSS treated group. I have found that DSS is a polymerase inhibitors and tried to purify DNA with LICL and Glycogen-ethanol precipitation. I have also tried to dilute my stock DNA before PCR. However, there is no successful 16S amplification. I have attached a gel electrophoresis result ( tapestation report) on PCR product of my samples and E.coli as control for your reference. Only control showed 200bp band but all my samples showed no amplification. Any suggestion would be greatly appreciated.
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Hello all,
Thank you so much for your answer. Lately I have tried DNeasy PowerClean Pro Cleanup Kit for an additional clean up process of DNA samples and ran PCR. I think I saw some bands in the region of 200-300bp.
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Dear all,
I am looking for a user-friendly pipeline for metagenomics analysis using COI (Cytochrome oxidase I) as marker. I have tried some of them based on python and computed by docker but is not enough clear to be used with students. Could anyone recommend me any alternative?
Thank you in advance.
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The link posted above is useless and it does not relate what was asked in the question.
Try:
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Am a beginer in metagenomics .. Please suggest some study further can be analyzed using the fastq data of 16srRNA metagenomic data?
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I am looking for packages to predict functional profiles from metagenomic 16S rRNA data in R language, as an alternative to PICRUst in Python. I found the Tax4Fun, but there are only a few examples of how to apply it. Does anyone know other similar and well documented packages?
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You can contact me if you still need help with tax4fun2
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Hi,
I'm new to shotgun metagenomics and just realized that there are multitudes of databases available to analyze the data, however no clear way to differentiate which one is better suited for which environment..
Which one to use for human gut shallow shotgun metagenomics data? (not looking to do de novo genomes, just to map to existing curated genomes..)
Looking at taxonomy databases for now, like GTDB, Web of Life, UHGG catalog....
Thank you for any advice!
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Thanks!
It seems that HUMAnN3.0 / MetaPhlAn uses the Chocophlan database. I'll try that out :)
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Dear researchers
In my subject, I work on the characterization of the Moroccan marine microbiota by metagenomics under the discipline of microbial ecology.
During the sampling, we could not have all the in situ measurements of the Physico-chemical parameters of the studied microbiome. That's why we had recourse to the extraction of spatial data from the NASA website to complete.
my question is: do we have the right to combine our own data with those of a database to analyze them? ethical and copyright aspects. since these data are submitted to the public with open access.
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If it is open access I see no reason not to use it. It is however essential that you should properly cite them.
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I am planning to run16S metagenomic sequencing on libraries prepared from colon content of C57BL/6 mice to understand the gut microbiota diversity of control group and DSS induced colitis group. I am having problem of very low library concertation of some samples from DSS groups after quantifying by qPCR. However, the qubit showed considerable amount of library concentration. I have repeated the library preparation on same samples by increasing DNA input and cycle numbers for PCR. But the result is still same. Can I diluted the libraries based on qubit concertation for further sequencing? Can I use fecal samples instead of colon samples for those samples for preparing libraries? Any information would be greatly appreciated. I have used following kits for library preparation and quantification.
16S Library preparation kit : Ion 16S™ Metagenomics Kit, A26216
Library quantification kit : Ion Universal Library Quantitation Kit, A26217
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Man Kit Cheung is probably right. In any case, I think this article might answer your second question.
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Dear researchers
In my subject, I work on the characterization of the Moroccan marine microbiota by metagenomics under the discipline of microbial ecology.
During the sampling, we could not have all the in situ measurements of the Physico-chemical parameters of the studied microbiome. That's why we had recourse to the extraction of spatial data from the NASA website to complete.
my question is: do we have the right to combine our own data with those of a database to analyze them? ethical and copyright aspects. since these data are submitted to the public with open access.
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Samir Ranjan Panda , Man Kit Cheung , Phil Geis thank you very muche for your answers :)
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Basically, the circular plasmid is more specific to identify its completeness. However, when we gain the metagenomic sequencing result from bacterial community or whole-genome sequencing result from bacterial isolates, after assembly of contigs, it is not clearly to confirm the completeness of linear plasmid.
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Unless you have overlapping contigs at either end of the plasmid it is impossible to tell in silico and would require experimental verification. It is possible to design primers near the ends of your plasmid assembly that would amplify across the remainder of the plasmid. This amplicon can then be sequenced to identify the remainder.
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I am trying to analyze the diversity of the bacteriome at different taxonomic levels
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Rocio Parra Laca A heatmap is a graphical approach to visualizing visitor activity data as hot and cold patches using a warm-to-cool color scheme. Warm colors represent areas with the greatest visitor engagement, red areas with the most interaction, and cold colors show areas with the least contact.
Also, have a look at this:
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Hi,
I have biological replicates: they come from the same raw sample (tube of sediment) but from different DNA extraction & sequencing experiments. These are metagenomes and I used whole genome sequencing.
If I treat them separately, the abundances are consistent, some of them cluster together on a PCoA but not so well on hclust.
Question:
1) Should I concatenate the raw fastq files together beforehand?
2) Or should I treat them separately until after the alignment to a db step and then sum the counts of each replicates together?
What is the best procedure?
Thanks
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Biological replicates of environmental samples will have some variations. Additionally, the quality/quantity of the DNA, as well as the library construction method will also interfere with the sequencing outcome.
I'm assuming you extracted DNA from the biological sample using the same method and at the same time. In addition, both were sequenced using the same library preparation techniques.
The final choice to merge or not will depend on the aim of the experiment. For comparative analysis, you can merge the samples to get a single assembly and then get the gene/contig counts from non-merged biological replicate reads.
If the comparative analysis is not your aim, you can merge the biological replicates and then use the merged reads to get the gene/contig counts.
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It's about RNA viruses metagenome.
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Thank you very much, Daniel Carrera Lopez!
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I would bé gratful if you could send me a protocol to extracted metagenomic Dna from soil. The aime of work is shotgun metagenomics sequencing,so i'm looking for a good yield ans concentration. I already try with the power max kit of quiagen comptant and the concentration is very low.
Thanks
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"Comparative studies on the extraction of metagenomic DNA from various soil and sediment samples of Jammu and Kashmir region in prospect for novel biocatalysts" by R singh.
This is perhaps the best protocol that have yielded me excellent results.
The methods of Zhou et al. (1996), Volossiouk et al. (1995), Tsai and Olson (1991), Siddhapura et al. (2010), Verma and Satyanarayana (2011) are very helpful too.
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What are the best webserver/online tools for Downstream Analysis of 16S amplicon Metagenomic dataset besides Microbiomeanalyst ??
Thanks in advance...
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Hi,
EZbiocloud offers simple processing for 16S amplicon sequencing analysis, although, if I recall correctly, not much of control/information over the analysis pipeline.
dada2 + phyloseq or Qiiime2 are surely the better options if 16S sequencing analysis is a reoccuring task for you.
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as we submit genomic DNA sequences in various repositories (ex. NCBI). so is there any specific repository to submit metagenomic analysis results of 16s rDNA sequencing.
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Several platform you can prefer to submit your metagenome sequence data to NCBI-SRA(Sequence Read Archive), MG-RAST and ENA(European Nucleotide Archive)
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I am looking for future collaborators in India working in the field of microbiome and metagenomics, with focus on antimicrobial resistance. Any suggestions?
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Interested in gut resistome study
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I have completed taxonomy assignment of the assembled contig from raw data but I cannot get the relative abundance of the species present. Is there any tool that can do that?
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Hello Ishtiaque,
I have found that Kaiju (taxonomy based on sequence homology) and Metagenomic Intra-species Diversity Analysis System (MIDAS; taxonomy based on curated phylogenetic trees) work terrifically for analyzing relative abundances of taxa with WGS data. These two tools complement each other as well.
Ryan
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Hello,
I want to determine the gut microbiome composition from my mice feces by using DNA metabarcoding sequencing of V3-V4 region from 16S rRNA.
I have contacted Novogene for doing it, and they offer 150.000 reads/sample and 30K Raw Tag.
Do you have any experience in using Novogene services?
Do you think this numer of reads for sample and Raw Tag is enough for species level discrimination?
Thanks in advance
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The species level discrimination not depends of the number or reads, depends of the technical approach, and V3-V4 is risky to go to species level, but good to go to genus level.
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I have a set of metagenomic sequence data from aquatic eDNA samples, and have been able to analyze the the bacterial/16S aspects of the samples but the program I use cannot analyze eukaryotic data. Does anyone have recommendations for programs that can be used to analyze eukaryotic metagenomic data?
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As an option you can do it manually by BLASTing your reads against 18s sets like SILVA ones. Next counting the relative presence of the species by assessing number of reads (and/or proportion of reads) aligned to a specific organism.
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Hi everyone! I'm trying to figure out how to process metagenomic data (obtained using qiime2 and picrust2 for qiime) to do some network analysis using igraph or similar (do you have any recommendations?).
Now, unfortunately I can't find a good tutorial about this passage, so do any of you have something which could help me?
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If your outputs are from qiime2, you can easily extract the feature table in .biom format and extract the taxonomic information and merge the two objects. From that point you can just create a phyloseq object and use it for the network.
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which extraction kit could be used for studies on metagenomics in bees?
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Excelente information Jeferson thanks!
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Hello.
I am trying to find differentially abundant microbes between two conditions. I have the relative abundance data but not the absolute read counts.
Is there any method that considers relative abundance data as input?
or any way to transform this data before use?
Regards,
Pratyay
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ANCOM-BC (ANCOM with Bias Control). You can run it easily in R using your relative abundance data without having to transform it. Here is some documentation you may find helpful:
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I have metagenomic data of gut bacteria of tribal population of Himachal Pradesh, can anyone help me regarding analysis of same for writing a research article. we will share authorship for the same.
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Many statistical analyses can be done on metagenomic data. Adding some details to your question will help narrow down the type of analysis you can do based on your research question.
  • What is your research question?
  • What type of samples did your study use? I guess stool samples?
  • What sequencing technology was used, and what was the library prep. protocol?
You can send a private message if it's easier to chat.
Best,
Hamza
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I am currently analysing Illumina sequences for a metabarcoding project. The primers used in the process have NOT been removed from the raw data. But after exploring the data, I found that ~5% of my raw data has no primers.
What could explain this 5% ? Should I discard these primerless sequences?
PS: The data was prepared according to the following protocole : 16 Metagenomic Sequencing Library Preparation Part #15044223 Rev. B (copy paste on internet to find it)
Thank
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If you are using trimming program, use parameter which discard the sequence which will be untrimmed because it doesn't have a primer sequence.
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I work on investigating the microbiome of the grapevines Rhizosphere using Shotgun-metagenome sequencing-Illumina. DNA was extracted using PowerSoil® DNA Isolation Kit - QIAGEN and further purified by Sodium acetate. Metagenomic DNA libraries (50 ng input) were prepared using NEBNext® Ultra™ II Prep Kit for Illumina®. The readouts of Bioanalyzer, Qubit™ dsDNA HS, or 16s PCR look perfect. However, the sequencing run gets always underclustered in case of my samples. Nevertheless, it disrupts the clustering of the other samples, too.
I look forward to any help!!
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Hi Islam M. Khattab
It's hard to cluster when the diversity is very high. Here's another reference that might help you:
Deconvolute individual genomes from metagenome sequences through short read clustering
doi: 10.7717/peerj.8966
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I have done both full-length 16S metagenomic microbiome and cultured microbiome identified with sanger sequencing. The results turned out greatly different from the metagenomics and cultured one, which should be usual. However, many microbes I cultured do not have the corresponding OTUs/ASVs in the metagenomic microbiomes. Regardless of the possibility of contamination, is there any other possible factor affecting the results?
Thanks in advance!
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I wouldn't expect that the difference is because of rarity of isolates, if the samples are not novel, because people have done a lot of isolation work for various environements. One possibiliy is that Enterobacteriaceae could be super low in abudance compared to others e.g. Clostridium, and thus it can be rarely detected by amplicon sequencing. This happened to samples e.g. sewage sludge or animal manure. In contrast, under a certain culturing conditions you provided for the bacterial community, Enterobacteriacease may happen to gain competence to grow. In that case, you could obtain the Enterobacteriacease, which you don't see in amplicon sequencing.
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The key difference in data (structure and function), effectiveness for which analysis, and which one gives more clarity for gene identification.
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Genomics explores the complete genetic information of a single organism be it a microbe, plant or animal, whereas metagenomics explores a mixture of DNA or RNA from multiple organisms and organs, and environmental samples
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Good morning,
Please I have an issue with my run and I need some help.
We did a metagenomic 96 sample run on Minion Mk1B (short-read 16S 400bp amplicons). The run lasted for 72 hours. Output was 9.7 gigabases (FAST5 files are 241GB). After this base-calling was initiated.
After 24 hours, the base calling was only 17% at which we aborted the base calling to do it on our server.
After 4 days now and only less than 20% is done. Why is it taking so long? We are using guppy v5.
What is the expected output size for such runs?
Does analysis usually take this long?
Is there a time limit by which we should stop the runs?
Thank you in advance.
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In my experience, yes, it takes many days to do base-calling with the guppy base-caller. However, it depends on what guppy version you used; if you use the guppy CPU version it will be much slower compared with the GPU version. The number of threads you used also affects the base-calling process.
I think no time limit for this. You just need to wait until 100% to get all your data converted to FASTQ by the program, or, you may need to adjust the base-calling parameters or change the program version and re-run the guppy base-caller to make it faster.
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Hello, I am trying to get a metagenomic analysis and found Novogene whose prices are pretty cheap (almost 1/3 of our university core). Does anyone have any experience with this company? about the data quality or reliability?
Please let me know,
Thank you,
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Hi Alba.
I had experience with Novogene, both for whole-genome and metagenomics.
The sequencing is very good, and I had no problems at all in terms of quality.
I don´t recommend to subscribe for their bioinformatic analysis, since the analyses performed are pretty basic and can be done easily by the researcher, and many times you need more complex analysis that are not included in the price.
Let me know if you need more information.
Ricardo
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For 16s rRNA profiling/ metagenomic analysis.
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DADA2 is widely used due to its accuracy and ease of use for marker gene-based community profiling https://benjjneb.github.io/dada2/index.html
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Please suggest a tool that can provide alpha diversity and beta diversity of microbes from shotgun metagenomic data either from raw sequences or assembled contigs.
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Hi Ishtiaque Ahammad, MG-Rast (https://www.mg-rast.org/) is a good tool for analyzing metagenomics data. After submitting your data it is possible to obtain a dissimilarity matrix for beta diversity analysis. With the generated abundance table you can also calculate diversity by other programs, such as R (as mentioned in the previous answer), or PAST (if you have difficulties in using software that demands greater programming skills).
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I need to extract DNA from the vaginal flora of cows for metagenomic studies. Does anyone know any extraction technique?
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Genetic and functional analysis of the bovine uterine ...
https://www.sciencedirect.com › science › article › p
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Hi,
Has someone experience in building a custom db using Kraken2?
I have downloaded the fasta files for some taxa and build the new db but it produced an unmapped.txt file with a long list of accession numbers.
What does this file mean? How can I deal with it? Can I overcome this issue?
How can I found out which taxa have been successfully included in the db that I have created?
Thanks
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Hi thanks, do you know if Centrifuge is better than Kaiju?
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Any body working on metagenomic DNA analysis in my connections? I need some help as regards the said analysis.
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16s amplicon, ITS, shotgun which one?
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I extract environmental DNA from a soil sample and sequenced using Illumina's next-generation sequencing technology.
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DEAR Amsale Melkamu
Genovo: De Novo Assembly For Metagenomes, Journal of Computational Biology: a Journal of Computational Molecular Cell Biology 18(3):429DOI:10.1089/CMB.2010.0244.
Meta-IDBA: A de Novo assembler for metagenomic data,DOI:10.1093/bioinformatics/btr216
GOOD LUCK
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Hi,
This may not be the forum to ask this question, but we are looking for someone to analyse the raw metagenomic data. That person can become a part of the publication/s we aim to produce. All analysis will be done remotely.
I can give more specific details if anyone is interested.
Thank you.
Thilini
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Thank you for the offer. If you think me a suitable collaborator I may be involved in the analysis of your whole metagenome data. Please go through my RG profile and publications. I am available @ nazmul90@bsmrau.edu.bd
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I am planning to go for metagenomics microbiome analysis. I have selected 4 primers for the same which are:
520F: 5'- AYT GGG YDT AAA GNG -3'
802R: 5'- TAC NVG GGT ATC TAA TCC -3'
338F:  5'-CCTACGGGNGGCWGCAG-3'
806R: 5′-GACTACHVGGGTATCTAATCC-3′
However there are some ambiguous sequences like, N,H,W,V,Y in my primers. Even though I know the coding standards like N stands for any of the 4 nucleotides(A,C,T or G) but i am confused which nucleotides should i put in to replace ambiguous letter. If anybody has any information. Please help
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1. You are using 16S and that is not a metagenomics analysis
2. Not clear what do you want to do by replacing the degenerate bases in your primers, and I am not sure if you know why they are used in primers
3. No analysis require the degeneracy of bases removed from primers, and that is why the question "why do you want to do that".
4. Interpreting the question and your reply above, it appears that there is a lack of understanding the basics of molecular microbiology and I would recommend to clear the basics before moving forward.
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I am working on sequence based metagenomics analysis, and I am having difficulty choosing which tool to use for binning of the contigs.
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There is no set rules in choosing binning tool unless you are doing supervised binning or binning from long reads. For shotgun metagenomics, there are many binning tools, of which MAXBIN, METABAT2, CONCOCT and BINSANITY are widely used. Whats importent is rather than relying on one tool (unless your study goal needs) it is better to use multiple tools and then use any BIN refiner ( DASTool, Binning-refiner and MetaWRAP refinement module) to select quality bins.
Workflows/pipelines such as ANVIO, MetaWRAP,SqueezeMeta, ATLAS can do the automatic binning using multiple binners and extrecting quality bins via bin refiners. Personally, i assemble my contig via metaspades then use metawrap binning ( MAXBIN, METABAT2, CONCOCT) refinement module and later import these bins in ANVIO for manual refining and other analysiss.
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I know that Shi et al 2016 inferred hosts for novel RNA virus genomes by searching their genes across cellular genome databases, so linking them with endogenous virus elements (EVEs).
Are you aware of other methods infer hosts for RNA virus contigs?
Thank you,
Guillermo
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The answer is found in the results of this study:
Nat Commun. 2017; 8: 16054.
Published online 2017 Jun 28. doi: 10.1038/ncomms16054
PMCID: PMC5493757
PMID: 28656958
Virus-host relationships of marine single-celled eukaryotes resolved from metatranscriptomics
Mohammad Moniruzzaman,1 Louie L. Wurch,2 Harriet Alexander,3 Sonya T. Dyhrman,3 Christopher J. Gobler,4 and Steven W. Wilhelm
we examined metatranscriptomes from two highly productive sites on the east coast of USA—Quantuck Bay, New York, and Narragansett Bay, Rhode Island. Quantuck Bay experiences recurring ecosystem disruptive brown tide blooms caused by the pelagophyte A. anophagefferens16, which are shaped by a giant virus (AaV)7,17. Narragansett Bay is a highly productive system with seasonal diatom blooms, but a poorly described eukaryotic virus community. By employing selection for polyadenylation before sequencing, we were able to focus on active virus infections within eukaryotes. Using time-series data, we captured emergent relationships of putative virus–host pairings and their ecological dynamics. This approach also allowed us to characterize viruses with diverse nucleic acid genomes actively infecting eukaryotes. The results show that this approach could both confirm known virus–host infections (including the infection of Aureococcus by AaV) as well as identify novel virus–host interactions. These observations demonstrate that the depth of virus–host interaction in the global oceans is likely much deeper than previously anticipated, with viruses containing all forms of genetic material potentially infecting single-celled eukaryotes.
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16s rRNA gene sequencing/metagenomics.
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As you said in your question "16S rRNA sequencing uses PCR to amplify a specific region of DNA", that is the main difference. 16S rRNA amplicon sequencing will sequence only the 16s gene in the provided DNA sample. Whereas, metagenomic will sequence all or most of the genes within a provided DNA sample. So, with 16s sequencing, one can get only the taxonomic information (from which bacteria does the 16s sequence came) while from metagenomics, both taxonomy and functional potential of the sample can be determined.
Note: There are some algorithms like PICRUSt which can PREDICT functional genes from 16s sequencing. But this can be used only for prediction and not conformation of a particular functional gene.
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Hi everyone
I'm processing some leaf samples collected in different rivers for shotgun metagenomic sequencing (Illumina NovaSeq 6000).
The company that will sequence my DNA samples (Novogene in UK) requires a 260/280 ratio =1.8-2.0 (no degradation or RNA contamination).
(Novogene webpage:
But I've sent samples in the past (to the same company but for amplicon sequencing) with 260/280 = 1.7-1.8 and they passed the quality control and went full analysis.
Regarding the 260/230 ratio, they do not refer any requirement but my 260/230 ratios are even lower (the lowest is 0.6).
I'm using the DNeasy PowerSoil kit (Quiagen).
So my question is, how low can these ratios be for shotgun metagenomic sequencing?
What's the limit?
I know that I will probably have to clean some samples but I just want to have an idea to help me select the ones I definitely have to clean.
Thanks a lot!!!
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First you have plants sample is Wash carefully and after that extract prepared and then filter the method for the concentration of, removal and enumeration of bacteria in liquid and air to avoid contamination of microorganisms for example fungi and then used other filtration method Sach as centrifugation.
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Previously, I colllected the oral swab samples in Zymo DNA/RNA sheild solution. I would like to perform the saponin based host depletion before doing the shotgun metagenomic sequencing.
I have concerned that DNA/RNA sheild could break the bacterial cell prior to host depletion. I have no idea about the component of this reagent. Do anyone have suggestion about this concern?
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It will not break but please do not leave it long time otherwise you will lost some.
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How can I best analyze the 16s amplicon sequencing data obtained from multiple runs? Do I have to run all the sequencing files in Qiime again? Are there any tutorials available?
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The best and most correct way to proceed would be reprocessing all the raw-data from different sequencing run with same parameters and together. The OTUs will surely change. With merging two separate runs, you would be forcing the two datasets to appear similar. Reanalysis would take only a few hours anyway.
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I am performing a metagenomics based experiment, where I need to send the sample to an external facility for NGS. The transit is of approximately 7 days. What can be the extraction and transfer protocol that can be followed?
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Hi,
To get a productive amount of DNA from your environmental samples, you can use Qiagen DNeasy Powersoil Kit to extract the metagenomes. I did use this kit and got a brilliant result after sending it to my external NGS facility.
If your concerned samples are soil or sediment or any other naturally-governed origin, then you must use specific kit to remove pollutants or strong organic matters hindering the DNA isolation process. Using any simple DNA isolation kit might not gives you all the extractable DNA confined to those natural media.
For transportation, you can certainly use dry-ice in a tightly sealed container and that will roughly give you a 3-4 days of time (as in my case, it was 4 days and samples were fine in it).
Best,
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Hello all Professors
What are the kits used in 16S rRNA Metagenomic sequencing (MiSeq Illumina) after the DNA extraction from human tissues (biopsy)?
Thank you in advance
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I think you are asking about library preparation. You should use TruSeq DNA PCR-Free sample preparation kit (Illumina Inc., San Diego, USA) for library preparation.
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I was wondering which databases would be best for a scoping review on how drugs effect the microbiome. Not sure if this falls into pharmacology, microbiology or metagenomics, but I would probably want to search a database that contains all of them!
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Thank you for nice question. There are many tools to predict both microbiomes and resistomes. However, the drugs interact with microbiomes is really challenging. You can use MASI: microbiota—active substance interactions database (https://doi.org/10.1093/nar/gkaa924).
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I am interested in doing microbial diversity analysis associated with a plant. I was looking for PNA clamps suppliers who can provide me mitochondrial PNA and plastid PNAs. Let me know if anyone has used it in their experiments or if someone can provide me as a courtesy.
Thanks in advance.
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I have been using them many times when working with grapevine-associated microbiome. As a rule of thumb I would check before-hand if they match the specific target you want to prevent and then they should work quite well. Only recently I had problems with wheat mitochondrial DNA and so far I have not had any luck using mPNA
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Hello,
I made index from my reference file and run command to align my metagenomic data by bowtie2. command is
bowtie2 -x <index_referance> -1 <paired_end_read_path_1.fastq> -2 <paired_end_read_path_2.fastq> -s <outputname.sam> and i got this result on screen without getting sam file in output folder.
16190304 reads; of these: 16190304 (100.00%) were paired; of these: 16189692 (100.00%) aligned concordantly 0 times 612 (0.00%) aligned concordantly exactly 1 time
0 (0.00%) aligned concordantly >1 times ---- 16189692 pairs aligned concordantly 0 times; of these: 59 (0.00%) aligned discordantly 1 time ---- 16189633 pairs aligned 0 times concordantly or discordantly; of these: 32379266 mates make up the pairs; of these: 32379200 (100.00%) aligned 0 times 66 (0.00%) aligned exactly 1 time 0 (0.00%) aligned >1 times
0.00% overall alignment rate
Can anybody tell me what are these results and what's wrong with this??
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For your purpose i.e. to know whether a given organism or closely related representatives are present in your metagenome or not , BBMap (https://sourceforge.net/projects/bbmap/) would be very convenient. This tool requires no installation and the command-line would be something like- bbmap.sh ref=fecal_indicator_genome.fasta in1=paired_end_read_path_1.fastq in2=paired_end_read_path_2.fastq outm1=fecal_genome_mapped_1.fastq outm2=fecal_genome_mapped_2.fastq minidentity=0.95
The above command-line will output only mapped reads that are somewhat closely related to your genome of interest (you may lower the minidentity values but the number of spurious mappings may increase and the overall mapping stringency with respect to your reference may go down; use minidentity=0.98 or 1 if you want very stringent mapping). You may further re-assemble these mapped reads on Spades and then analyze if this new metagenome-assembled-genome is actually represents your ref genome or if it is closely related
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Dear professionals in arbusculer symbiosis,
Currently, I am working for the research project for the community stracture analysis of arbuscular mycorrizal fungi among with different fertilizar treated field.
For community analysis, I am planning to run NGS; platform Illumina Hiseq with eukaryotic universal primer pairs targeting 18S SSU V4 V9, ITS1/ITS2
Here my questions are;
1) Is it appropriate to use Illumina Hiseq? (Platform 454 seems to be major in other papers)
2)Is it better to use AMF specific primer pair for Hiseq or other NGS platform? If so, is there any recommendations for my research?
Thank you very much for your kindness and help.
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Also, this reference is useful
"The Influence of Bt Maize Cultivation on Communities of Arbuscular Mycorrhizal Fungi Revealed by MiSeq Sequencing"
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I'm working on ARGs analysis from shotgun metagenomic data sets. I want to learn how to analyze mobile genetic elements by using ACLAME database. Is there any guidelines ?
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You may visit this site http://aclame.ulb.ac.be/. I hope that it will help your endeavor.
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I am looking to use the Illumina DNA prep kit 96 well edition for metagenomics on stool extractions. I've heard that you can get many more samples then just 96 out of a single kit, how many can you actually get out based on the amount of buffers, beads, etc? Looking to see if anyone has empirical experience with this. Obviously the indexes will have to be on a second plate if there are more than 96. Thank you!