16s rRNA sequencing for V-3-V4 hyper variable region?

Hi!
I would like to know about the specific primer or pipelines is there for seminal microbiome analysis for cattle/humans?. I got a few papers but I could not choose the right one. Kindly suggest to me a primer for the standardized method for the 16s gene microbiome profiling and may I use zymoresearch microbiome standard DNA for a mock community test?

All of this is concerning in QIIME analysis?

Thanks and regards
Srinivasan

Hello Srinivasan,

My team has been using the protocols and primers from the Earth Microbiome Projects for a number of years.
https://earthmicrobiome.org/protocols-and-standards/primer-ordering-and-resuspension/
https://earthmicrobiome.org/protocols-and-standards/16s/
This project includes many "Host-associated, Animal" samples, which sounds like the cattle/human samples you mentioned.

These primers are well cited and work well with Qiime2, but they target 16S V4, not V3-V4.

Including a mock community is very important, and I've heard good things about the one from Zymo. You could also take a look at the mock communities listed in mockrobiota.

Let us know if you have more questions!

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Hi @MSrinivasan,

I've also processed data from Zymo and it was fine. But most of the data I've processed was from the EMP protocol as outlined by @colinbrislawn. Often, primer choice is dependent upon the type of sample you are processing. For example, most researchers that process the skin microbiome like the V1V3, and those that process gut microbiome tend to go for V4 or V3V4, V4V5. The reason for this is that taxa commonly associated with different environments (e.g. skin) might be better differentiated with one primer set over another.

One thing I would like to mention is that Zymo uses proprietary primers, and will not share those sequences. This is problematic if you like using cutadapt to remove your primers, as you do not know what they are. This is fine as you can use the deblur / DADA2 trimming options to snip off the primers. Fortunately, Zymo was willing to let me know which positions to trim. I even added this information to my MIMARKS compliant metadata in the GenBank SRA here.

EDIT: I misread the part about Zymo. I thought you meant that Zymo was going to sequence the data for you. I realize now that you were discussing the Zymo mock community standards :man_facepalming:. ATCC also has some good standards too.

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I second ATCC! Our current axenic positive control is from them.

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Thank you very much, @SoilRotifer @colinbrislawn. I'd like to employ the microbiological standard. I'm curious about the similarities and differences between spike-in controls (the addition of foreign microbial DNA to a sample) and a diverse mimic community. Which of the following is a limited error in microbiome analysis? What negative and positive controls will be employed for the seminal plasma microbiome of cattle to be sufficiently comparable to the microbiome investigation?

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How to employ a bacterial mock community, spike-in control, or negative control in microbiome sequencing. Which of these is in charge of contamination control in low-biomass sequencing? I've read a lot of publications, but I'm still confused about the technique for the mock community, spike-in control, and negative control. Can I use DNA elution buffer as a negative control? Is DNA-free water the negative control? I looked for the DNA of the bacterial strains to use as standards. I've seen the ATCC Microbiome standards as well as ZymoBIOMICS' mock community DNA standards. How can it be used for seminal plasma microbiome sequencing? The seminal microbiome has less biomass but a greater diversity of microbiomes than the vaginal microbiome.
Thank you in advance for your support!

Hi, for mock community assessment maybe you can refer to this post.

Sorry it's not much, I also just learned about it.

Good luck to you!

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@SoilRotifer Thank you. Which primer set should I use if I'm studying the semen/seminal plasma microbiome?

I think the same EMP primers amplifying 16S V4 region are still a good place to start!


Thank you for your patience. Let me see if I can help answer some of your other questions.

Step number 1 is to include some or all of these on your sequencing runs. This is the easy step.
Step number 2 is to use the information you get from them to understand and contextualize what you see in the other samples on your run. This is the hard step.

You could do this with the data from your negative control / no-template-control (NTC). Your low biomass samples will contain little nucleic acid, and so it could get overwhelmed with contamination. Because your NTC should contain no biomass, everything in this sample can be attributed to contamination, and this tells you what contamination to expect in other samples.

Sure. Make sure to use the same primers and polymerase as your 'real' samples, just don't add any biomass on purpose.

Pick one and sequence it with your other samples. After running your full annotation pipeline, you can compare your results to what you expected to see in that sample. This will tell you if your pipeline is missing organisms or biased to specific groups of taxa.

We use this in clinical testing, but I have not see it used in environmental microbiome studies very often. I would recommend starting with the other controls first, because those are more common, then consider how to use an internal spike-in control.

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