Microbiota - Science topic

Yes it is. Keep plant cover on the soil, reduce tillage, and add carbon from crop residues or manure wherever possible. It sounds simple because the soil biodiversity takes care of the complexity. Most intensive practices simplify and rely on inputs that are ultimately not sustainable—but we cannot trash them because they feed the 4 billion+ urban dwellers.

Oh, I see.

Thank you anyway!

Hi Rahaf Kaki

What are the available resources and facilities in your lab?

If it is open access I see no reason not to use it. It is however essential that you should properly cite them.

Samir Ranjan Panda , Man Kit Cheung , Phil Geis thank you very muche for your answers :)

Visit kindly the following useful RG link:

The current treatments that we have are mainly focusing on altering/causing a shift in the microbiome by the supplementation of probiotics, prebiotics, and postbiotics. Despite being popular, these treatments are not always useful and their beneficial effects are hard to detect.

Furthermore, we still don't understand fully the relationships between different bacteria and the way they interact in a complex matrix such as the gut.

Furthermore, pathogenic species of bacteria express their genes differently based on the environment they are found in. So understanding how they interact with other bacteria is key here to form a microbiome-based treatment.

Therefore, until we have a complete picture of the microbiome on a strain level and how these bacteria interact together or with their host, we won't be able to form novel microbiome-based treatments

Dr. David Wishart presented MiMeDB - Microbiome Metabolome Database (at November 2021 Nature Conference "Reshaping Microbiome through Nutrition). The release of the database was planned for January 2022: if you'll stay tuned with the Metabolomics Innovation Centre (LinkedIn), you'll know when it is launched. It is anticipated to have an integrated microbiome, metabolome and diet data.

In the meantime, HMDB database includes many subdatabases of metabolites (including microbial in origin). ECMDB, PAMDB, YMDB and FooDB may be helpful. Check https://www.metabolomicscentre.ca/software for all databases.

After the construction of OTU, I believe the QIIME2 might help you. You can find out more information at https://www.nature.com/articles/s41587-019-0209-9

at least six samples

What do you want to ask?

I'm sure dosage will have some effect but probably over a narrow range. Length of time of exposure is likely to be equally important. Remember that the antibiotic is not itself affecting or causing the spread, but rather imposing a selection on the population and letting rare events get amplified (by rare event here I mean some sort of transfer event).

Dear Luigi Marongiu Please, take a look at this paper:

Thanks Sir Khaled Elsayed

McMaster technique

Maria Jose Bellini .-. To begin with find some of the great reviews (I will try to find some to post later), but you can even begin with the basic information at https://en.wikipedia.org/wiki/Gut_flora . If you intend on culture methods, you need to find a good microbiological laboratory in your institution or a university that can process the samples. From the way you wrote the question I am assuming you might be more interested in a genomics approach (or metabolomics). For this you will need to find a lab that can process your samples (this would be too hard to set up for your own lab), and there are even commercial companies which can process your samples. I have used https://www.mrdnalab.com/ and there website will give you insight into a variety of methods.

Hi Albert

I think this article:

"Extracellular Microbial Metabolomics: The State of the Art"

Good Luck

Hello Mohsen,

In agreement with previous answer, analysis of pooled sample will provide you nice information on the response of faecal microflora to your treatment. You will only miss individual variability within a pen compared to a trial with individual faeces collection. If the microbiota determination is the main objective of your study I'll suggest individual sampling, if not, pool is clearly sufficient.

Kind regards,

following

Problem solved on using Zymo Quick DNA fecal/ soil micro kit. DNA extracted using the Zymo kit from DSS treated samples resulted in good number of reads in 16S sequencing.

It might not be a good idea to introduce more microbiota into the lung, as they are one cause for inflammation. How about using the cellular homeostasis maintenance function of autophagy/xenophagy to control the microbiota population in lungs, repair the dysfunctional epithelial cells, and decrease the overall inflammation level in the lungs:

Autophagy can e triggered by nutritional deficient stress like starvation.

Thank's a lot for sharing

DearBouthaina Hasnaoui

here are some truths in Russian

Regards, Sergey Viktorovich Pushkin

The landscape design incorporates four major elements: defining a continuous pedestrian connection the length of the corridor, developing clear and safe crossings of the roadway, creatively resolving the need for pedestrian connections in an environmentally sensitive area. In some cases, you can add your own touch in the design models that are above or based on the regular standard.

Marilia Cavalcanti Some short 16S-homologs sequences are present in bacterial genomes, and you can get non-target amplification for microbiota samples. Try to use several group-specific primers and analyse group-specific dynamics

Please also go through the following RG link.

we've alreday isolated endophytes from diverse spontaneaous plant species, we found very interesting bacterial endophytes from Urtica urens. See (Krimi et al., 2016). Good luck!

The Gratton paper also has important information on relative stability and heterogeneity of fecal samples - which is very high indeed -and is highly relevant to understanding the micro-ecological structure of the fecal samples. It also casts doubt on the ecological understanding of many microbiome/metagenomic studies which have to use quite large homogenised samples that give an averaged ecology- At some level it is always necessary to compromise in this way to get any sort of answer but it is fairly meaningless to cross correlate, for instance, metabolic data with microbiome data when the sampling heterogeneity and sample volumes are very different. If you use a large volume for metabolites then micro ecological heterogeneity information is lost. To illustrate- If we refer to the standard method of terrestrial ecological sampling using say 1 meter Square quadrats to sample species abundance (or by analogy metabolites in small samples) and throwing a series of these quadrats to statistically analyse the species composition and distribution in a field say- but if we throw a 200 m Square quadrat we could cover a much wider set of ecologies which could include a bit of oak woodland, some grassy pasture a corn field and a house with a wishing well... the average of this would mean exactly nothing! But the 200 m Square analogy is closer to what is often done in metagenomics!! This might be sidestepping the question a bit, but as one of the main aims of fecal metabolic analysis these days is to shed light on functional metagenomics the problem is worth considering. There are other big problems of course like the fact that collected fecal samples contain microbes that were functionally interacting with the host hours before and meters away (in intestinal space) under different physiological conditions= so what does that actually mean? Arguably the best place to look for microbiome related metabolites and microbe-host co-metabolites is in the urine because most absorbed compounds are made polar by host phase1 and phase 2 conjugation in the liver and then excreted by the kidneys (presence in the urine also proves they have actually been inside the body which is not true of many fecal metabolites). Hope this is of interest.

Gratton J, Phetcharaburanin J, Mullish BH, Williams HR, Thursz M, Nicholson

JK, Holmes E, Marchesi JR, Li JV. Optimized Sample Handling Strategy for

Metabolic Profiling of Human Feces. Anal Chem. 2016 May 3;88(9):4661-8. doi:

10.1021/acs.analchem.5b04159. Epub 2016 Apr 21. PubMed PMID: 27065191.

.

I suggest reading this article-

Dinan TG, Cryan JF.The Microbiome-Gut-Brain Axis in Health and Disease. Gastroenterol Clin North Am. 2017 Mar;46(1):77-89. doi: 10.1016/j.gtc.2016.09.007. Epub 2017 Jan 4

Dear Abhijeet Singh ,

Bunch of thanks for your answer. I hope it would be helpful Abhijeet Singh

Andrei Bombin I am afraid that for 2 population you get only simple similarity value for corresponding correlation coefficients.

Hi,

for me it seems like you see primer dimers. Sometimes high amounts of input can affect the melting behavior and might lead to such a behavior. You could load your samples on a gel to check this. In addition you might check it this behavior remains with lowered primer amounts. Other option would be to check another mix which was developed/ tested in microbiome applications like UCP Sybr green.

Best Sven

P.S. if you like you can send me the runs by mail. Just send me your email address via message and I will reply

Hello Shruti,

I do not have a direct answer to your question because I have never used DNA/RNA shield. But I faced a similar problem of having very low RNA yield from samples stored in RNAlater. My experience is that RNA later interferes with the extraction of RNA. However, I avoided this issue after I learned that the RNAlater needs to "pressed" out of the sample using Kimwipes. I am not sure whether you could try the same with fecal and mucus samples. But you could try to blot your samples and remove the RNAlater by putting them on kimwipes without pressing.

This should definitely improve RNA quality.

Best.

Adnan

A gap of 1 CT between two samples represent a 2-fold difference in DNA concentration. Therefore, between 20ng and 100ng you shouldn't expect anything more than a difference of 2 CT. Have you made triplicates ? My guess is that such a "small" difference is often hidden within the standart deviation of qPCR replicates.

Also, did you get a CT value for your negative control(s) ?

The microbiota in different regions of the large intestine will vary for manly reasons, including the quality of food resources left along pathway, structure of the LI, differences in crypts/microstructures, food source for the region being sampled..... One paper related to this and cancer is https://cancerpreventionresearch.aacrjournals.org/content/canprevres/11/7/393.full.pdf

Do a full pubmed or scholar.google search for variations in microbiota in the LI.

The following study reveals that fluoride also does not affect the gut microbiome.

Hello,

you can find the answer to your question in the next publication:

Emiley A. Eloe-Fadrosh1 and David A. Rasko1,2

The Human Microbiome: From Symbiosis to Pathogenesis Annu Rev Med. 2013; 64: 145–163.

doi: 10.1146/annurev-med-010312-133513. It is free

Dear Yang,

I agree with Dr. Gautier Richard answer for this question.

You can also see this manual specific for Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data analysis.

you can try potassium acetate method of DNA extraction.

some Extraction kits are also online available eg. himedia DNA extraction kit.

best wishes.

Thank you Sriram Seshadri!

Not all diseases start in the intestines.

I heard about wisdom say "Stomach is a house of sickness and fasting is a medicine"

The makeup of bacteria within our gut determines whether we are likely to have GI conditions like colitis or irritable bowel; psychological states like depression or anxiety, skin disorders like eczema or psoriasis, neurological disorders like multiple sclerosis, Parkinson’s or Alzheimer’s Disease; inflammatory conditions like rheumatoid arthritis, systemic sclerosis and ankylosing spondylitis; even susceptibility to being overweight can be mediated by the microbiome’s impact on thyroid autoimmunity and insulin resistance.

Reference ->

Dr. Ronald Hoffman

Hi Anna,

thank you very much for your detailed information!!!

It also really depends on what you want to see. If you are more interested in nerve fibers and neuron processes you might want to try PGP9.5 or have a look at beta III tubulin, which is neuron specific as well. This antibody is mainly used in enteric neuroscience, as well as HuC/D. HuC/D is very useful if you want to image neuronal cell bodies. ChAT and nNOS antibodies can be used if you want to show that different neuronal subtypes are present in the ENS. Then you could also stain for calbindin, VIP, calretinin, etc. But for a general overview of neurons and glial cells I would use HuC/D or tub bIII, and S100b or GFAP (try different combinations to see what works best for you). Sox10 will show you both neuronal precursors as well as (mature) enteric glial cells. Hope this helps!

I agree with Dr. Busi

Keep an eye to the International Human Microbiome Consortium.

You must better investigate the microbiota from the human umbilicus dermal plica, which encounters 5000 species and may be different in known 5 races or may be by every individual.

Fecal microbiota transplantation (FMT) has gained mainstream attention with its remarkable efficacy in treating recurrent Clostridium difficile infection (RCDI) when there are no other effective therapies. Methods of selecting donors and routes of administration vary among studies.

I agree with yours four points, Aida.

Antimicrobial resistance is multi-factorial. Sub-optimal exposure to antimicrobial, gene transfer (both horizontal and vertical), spontaneous mutation are among the many. When there is frequent infection, there will be exposure to broad spectrum antimicrobials which will result in selection pressure in which resistant strains are selected. These strains will constantly evolve and result in gene transfer, both horizontal and vertical. The spontaneous mutation also contribute to the emergence of resistance.

Thank you very much for your answer. I am still looking for the connections through the connective tissue, maybe with the use of fat tissue? (the remnants of the dorsal and ventral fetal mesentery?) regards SW

Our microbiome's health is a function of a balanced mixture of carbohydrates, protein, inorganic nutrients, and cellulose. Optimal balance would be a function of the needs of an individual.

Using RNAlater Tissue Collection, thermoFisher is most convenient for field trip. https://www.thermofisher.com/tw/zt/home/references/ambion-tech-support/rna-isolation/tech-notes/rnalater-preserves-bacterial-gene-expression-profiles-for-array-.html

Thank you all for your great answers !

I will take into account all of your comments, certainly for the next study, because for this one, a misunderstanding caused me to misinterpret the delta variations I had in my hands, but going back to the source, I realized that it was qPCR data. We went back in numbers and we made fold changes to respect the established statistical plan. I hope that it's correct !

However, I have other projects with sequencing data and your comments will help me to interpret the results.

Thank you!

Hi Dianne,

You can send it to Macrogen co. located in South Korea. They will receive genomic DNA of your samples or just a few amount of your samples and will go ahead will Microbial profiling according to your request.

good luck

I suggest, you observe and calculate species abundance for ith species from your data set separately. Shannon and Simpson indices represent the diversity of a community as whole.

genetic risk for IBD and microbiota or entero*

I would recommend the methodology suggested in the following article although other researchers don't use iodine but use other antiseptic washes to remove contamination from the skin which may also be very good.

The human milk microbiome changes over lactation and is shaped by maternal weight and mode of delivery1,2,3,4 Raul Cabrera-Rubio, M Carmen Collado, Kirsi Laitinen, Seppo Salminen, Erika Isolauri, and Alex MiraAm J Clin Nutr September 2012 vol. 96 no. 3 544-551

Hi Maria,

I have upload the Poster of the EGU Conference from 2015 to my profile.

Cheers,

Tina

Affirmative.  The gut microbome - liver axis is now well accepted(Compare et al. 2012) and there is significant body of evidence supporting gut microbiota plays role in nonalcoholic fatty liver disease (NAFLD) and exacerbate this to more dangerous nonalcoholic steatohepatitis (NASH) (Abu-Shanab and Quigley 2010). The overall school of thought is that the altered flora lead to dysregulation of the liver innate immunity and excessivle TLR stimulation (Miura and Ohnishi 2014). In fact E. coli mediated Small intestinal bacterial overgrowth (SIBO) is significantly increased in pediatric nonalcoholic steatohepatitis (NASH). Very interestingly Janssen et al recently reported the link between gut microbiota and bile acids(Janssen et al. 2017). In the Asian context we have observed SIBO, specially mediated by of Gram-negative pathogens result innate immune dysregulation (Ghosh 2011), insulin resistance, choline deficiency which are all signs of NAFLD, but this has not been published yet. Together, application of strategic probiotics in mitigating liver disease in high risk cohorts is increasingly suggested (Xue et al. 2017).

Suggested References

Abu-Shanab, A. and E. M. Quigley (2010). "The role of the gut microbiota in nonalcoholic fatty liver disease." Nat Rev Gastroenterol Hepatol 7(12): 691-701.

Compare, D., et al. (2012). "Gut–liver axis: the impact of gut microbiota on non alcoholic fatty liver disease." Nutrition, Metabolism and Cardiovascular Diseases 22(6): 471-476.

Ghosh, D. (2011). "Probiotics and intestinal defensins: augmenting the first line of defense in gastrointestinal immunity." probiotic foods in health and disease. Oxford& IBH Publishing Co, Delhi: 61-74.

Janssen, A. W. F., et al. (2017). "Modulation of the gut microbiota impacts nonalcoholic fatty liver disease: a potential role for bile acids." J Lipid Res 58(7): 1399-1416.

Miura, K. and H. Ohnishi (2014). "Role of gut microbiota and Toll-like receptors in nonalcoholic fatty liver disease." World J Gastroenterol 20(23): 7381-7391.

Xue, L., et al. (2017). "Probiotics may delay the progression of nonalcoholic fatty liver disease by restoring the gut microbiota structure and improving intestinal endotoxemia." Sci Rep 7: 45176.

You can use chloramphenicol to inhibit the growing of gram positive and gram negative bacteria. The usual chloramphenicol concentration is 0.05 g/L.

Thank you both for your helpful answers.

I indeed separated the contents as much from the host tissue as possible and the PCR worked just fine even for day 3 using individual mice (no pooling required). I used a forceps to carefully squeeze out the colon in one piece and the ileum in 3-4 pieces of 1 cm length each. 

 It would be helpful to know what your primers are, what your expected PCR product size should be, and what you are getting on the bench for your PCR product size. Knowing this may help to narrow down your possibilities; however, I think that there are a couple possibilities (besides the issues brought up by Sonam Mehrotra) with the most likely being that not all polymerases are created equal.  

Phusion Polymerase has high GC-Rich PCR Performance while DreamTaq is low. Depending on the consortia in the stool sample and what primers you are using you will have different GC content. This variation could affect the specificity of your primers and lead to the PCR bias giving you two different size products.

What are your primers?

I don't have an answer, but I have the same question. Do you have any clue by now?

Hi

Healthy microbes can easily turn rogue. Those in our guts are undoubtedly helpful, but if they cross the lining of the intestine and enter our bloodstream, they can trigger a debilitating immune response. The same microbes can be beneficial allies or dangerous threats, all for the difference of a few millimeters.

Conversely, “unhealthy” configurations of microbes can be normal, even necessary. Ruth E. Ley at Cornell University and colleagues demonstrated this in dramatic fashion when they found that microbiomes go through a huge upheaval by the third trimester of pregnancy. They end up looking like the microbiomes of people with metabolic syndrome — a disorder that involves obesity, high blood sugar and a higher risk of diabetes and heart disease. These communities might indicate someone on the verge of chronic disease — or merely motherhood. Packing fat and building up blood sugar makes sense when you are nourishing a growing fetus.

 another example. Common medical wisdom says that healthy vaginal microbiomes are dominated by the acid-making Lactobacillus group that creates an inhospitable environment for disease-causing microbes. But Larry J. Forney at the University of Idaho and colleagues found that a quarter of women didn’t fit this pattern, despite being perfectly healthy. They also showed that their vaginal communities can change dramatically and rapidly, even over a single day, flitting in and out of states that are supposedly conducive to disease, but with neither clear causes nor ill effects.

Please, evaluate one paper about children, and another total clinical trials.

Dear Joseph and Amir,

Sorry for the terribly late response.

Thank you Amir, for pointing out that rand was not defined.

I read Joseph's response and didn't understand what it meant at first because I didn't have enough experience using R and didn't have a clue on how to use the RandomForest package. This was my first project using R and furthermore, my first project using machine learning.

Our team eventually found out how to make it work and completed our project after much googling and a skype session with one of the authors of the paper.

After having solved the problem, I admit that replying to this post took a backseat on the list of priorities. It was quite rude of me to leave you hanging as I did. Although it's very late, I've come back to thank both of you for your help and apologize in hopes of setting things right. Again, many apologies.

We managed to replicate the microbiota-to-age model found in the Subramanian et al. paper to a satisfactory degree (although it wasn't precisely identical) and have moved on to work on other metagenomics projects. We did run into other problems after this one, (having to do with rarefaction and another part of modeling) but that is a story for a different time.

Thank you both for your time and your contribution.

Sincerely,

Isaac

By searching NIH REPORTER (with key words: microbiota, infant, multi-center), there are three projects currently active/ongoing. You might also want to loosen/modify the keyword terms to get more exhaustive search results. 

1.  5R01DK095869-03: " THE RELATIONSHIP OF FECAL MICROBIOMES AND NUTRITIONAL STATUS IN CF", Contact PI / Project Leader: HOFFMAN, LUCAS R., Awardee Organization: UNIVERSITY OF WASHINGTON

2.  1R01DK109692-01A1: " EARLY CHILDHOOD DIET, GROWTH, GUT MICROBIOME AND LUNG HEALTH IN CYSTIC FIBROSIS",  Contact PI / Project Leader: LAI, HUICHUAN J, Awardee Organization: UNIVERSITY OF WISCONSIN-MADISON

3. 1R21HD088005-01A1: "ANTIBIOTIC EFFECTS ON THE DEVELOPING MICROBIOME METABOLOME AND MORBIDITES IN PRETERM NEONATES.", Contact PI / Project Leader: NEU, JOSEF, Awardee Organization: UNIVERSITY OF FLORIDA

Hope the information would be somewhat helpful. 

Bonjour!

Maybe you can do the relative abundance of the OTU or OTUs comparing with the fly number of DNA sequences (if you have any of them in the Miseq reads), You can't use only the number or reads because the numbers of reads per sample have differences due to the methodology, it is impossible to obtain the same number of reads per sample. I mean, with Miseq reads you have relative abundance, you can't talk about total abundance.

Hi , Please look in attach file

16S rRNA sequencing (V3-V4) will be good for this type of studies. I did similar type of studies for probiotics supplemented groups versus normal food eating groups. We find the changes in the microbiome following probiotics supplementation. Now we want to find out the mechanism, for which we are going to do the metatranscriptomis and host transcriptomics.

maybe its better to freshly calculate correlation based on groups instead of calculating metrics of metrics. Maybe this gives inspiration: http://stats.stackexchange.com/questions/4040/r-compute-correlation-by-group

Using 400g, your bacteria will stay in the supernatant. You have to take care to separate the bacteria from the debris by vortexing. And then, just check your supernatant by microscopy to evaluate your samples.

Yes, it is possible. Perhaps the MALDI-TOF method is the best option, but  the challenge is how to built the matrix

I suggest you to contact Luca Mazzon from my Dept. (lmazzon@unipd.it)

best regards

Carlo Duso

Do you mean you carried out 9 cycles? If so I'm sure it will be fine and you should be checking the insert size and DNA quantity before taking the libraries any further anyway. 

You may have a higher library concentration than expected but could dilute to the correct concentration. 

Some authors mention the rectal sparing or patchy rectal involvement in UC. However biopsy and resection tissue results recommend that there is no "Absolute rectal Sparing in UC". CD has rectal sparing mostly and indeterminate colitis can have all types though. Some authors blame higher H2S concentration in rectum to explain more severe rectal involvement. However, nobody knows. Likely it can be explained by genomic variant and microbiata species in vulnerable people. Sometimes even a simple antibiotic treatment kills good bacteria and triggers sleeping IBD as it does for C diff. "Way to go!"