Microbial Ecology - Science topic

Microbes frequently interact with each other within or upon their animal host, and a rapidly increasing number of studies now shows that these interactions can have substantial effects on host. The following link includes the diversity of microbial interactions, and the variation in their nature and impact on the animal host that have been determined by differences in symbiont diversity.

Hello Abdulmuhsin S. Shihab. The Preacher & MacCallum (2003) article I referred to in my earlier post explains (among many other things) why eigenvalues > 1 is a very poor way to determine the number of factors (or components) to retain:

HTH.

These two recent publications published in 2021 hopefully fits the discussed issue; describing the potential relationships between microbial biomass and diversity and the impacts in the case of soil agronomic management practices.

You can use 2,2'-dipyridyl to deplete labile iron pools. However, you need to establish the right concentration- a threshold where the bacteria is still able to grow. 2,2'-dipyridyl is a strong iron chelator, when sued used at high concentrations could inhibit growth. But, typically, 100uM could be the [starting]. Best wishes

Thanks for sharing!

We will be happy to collaborate. Mechanism has to be developed between the partnership.

Dr Diwan

I totally agree with Fazel Mohammadi-Moghadam that we need more studies to be done around the world to repeat the idea and evidence. It is a very interesting discussion we are countering here. During my PhD study, I have done a long-term research investigating the effects of 20 years climate influence on soil fauna and vegetation. I think 12 years can also be considered as a long-term research and these discussed obtained results maybe show the effect of higher temperatures on increasing the decomposition rates. Although this is a perception and it really needs to be studied in detail.

Dilip Kumar Pal

Zahid Fazal

Yes, we need approaches to study their activity in vivo.

In addition to the pipeline mentioned above ( ), you can also have a look at this one:

Hi Benoît,

No program that I am aware of. I reckon that differentiate life-strategist from mere amplicon seqs can be, at best, unreliable if considering problems such as uncomplete reference datasets.

A good paper describing this but trying to list taxa that behaves as copio-oligotrophs:

Please let me know if you come across with a relevant program though

Cheers

Ben

Vanessa Baldin

Thanks Shan Thomas i will check it out, looks like a more convenient solution than trolling through papers

Thanks all for your comments. Haitao Wang I agree with your suggestion but I guess the 515F/806R are shown to be biased against both the Crenarchaeota/Thaumarchaeota (https://msystems.asm.org/content/1/1/e00009-15) so after going through some articles I found that the V4-V5 primers 515F/926R performs well and can reduce bias and can detect more environmentally important taxa including archaea. I just posted here as I thought it might be helpful.

Best,

Sandipan

I would definitely leave each replicate as a separate data point and normalize them individually. More discrete data points will generally give a more statistically robust result. I would suggest testing for normality before you go ahead and normalize the dataset, though. You'll want to be able to explain why you chose to normalize. While most biological data needs some form of normalization, it's not a bad idea to take a look first.

Hi Justin,

It really depends on your questions you are asking.

Since Alfa diversity is used to evaluate within sample's indices, the important parameters are Richness (number of OTUs, Chao1 as Benoit mentioned), Evenness, total diversity (such as Shannon but not only ) which basically takes into consideration both richness and evenness,

and the total number of cells in the sample.

Other indices such as dominance and more are also acceptable, again depends on your questions.

Nir

While doing leaf litter decomposition experiment following Olsen (1963) we got k value (per year) 0.18 and half life 3.85. However, 54.01% weight has already lost at the end of first year. How can we interprete the value of half life and weight loss?

One of the reasons is that, solid PVK media, consist on testing a single fixed bacterial colony, while in liquid media, the bacterial densities are much higher with better access to the nutients, which makes the solubilization more efficient and important.

As stated earlier PERMANOVA is a permutational multivariate anova. But maybe it would help to understand how the test is most often used in microbial ecology. Say you have an ordination–like a PCA, NMDS, PCoA, whatever–and in this ordination you are showing gut microbiome samples from a sick host and a well host. The samples from either host overlap a little, but don't totally overlap. You want to know if folks that are sick have a different gut microbial assemblage than the folks that are healthy. A PERMANOVA lets you statistically determine if the centers (centroids) of the cluster of samples for the sick person differs from the center of the samples for the healthy person. Just like an ANOVA lets one tell if the mean value differs among treatment groups, so the PERMANOVA lets one determine if centroids differ in ordinations. In other words, the PERMANOVA tells you the chances of observing the ordination you observed, or one with even less overlap, given no difference between the gut microbes of the healthy and sick people. Note that the PERMANOVA is not done on the actual ordination but is done on the underlying distance matrices. You can perform a PERMANOVA on other multivariate data, but I think every time I have seen somebody use a PERMANOVA in ecology it is to test if centroids of distance matrices differ. Note that PERMANOVAs can miss a lot, so they shouldn't be the only analytical technique used. Whenever possible, doing some species-specific analyses can provide extra insight. Hope this helps.

Hello, paper about enhancement of bacteriocin production is attached.

The best source for bacteriocines is Lactic acid bacteria.

Bacteriocin should be protease, bile resistant to have opportunity for future use.

Hope this info will help you.

Good luck.

Jai Ghosh Zhaowei Wu

I think every one could ask any research related questions here, no matter what. You may or may not answer any question but better not to comment the question itself as silly or smart.

Thanks.

Hi Haitao Wang,

This is definitely confusing, and the meaning of the fold-change returned automatically is a bit convoluted. Ultimately, the reported fold-change depends on the models (full vs. reduced) you provide DESeq2 when performing the likelyhood ratio test (LRT), since the LRT goodness-of-fit tests the hypothesis that the data are _-times more likely to fit the full model (~treat1 + treat2) than the reduced (~1) model. This result has little biological meaning when examining multiple variables (though it is essentially the same as fold-change with Wald when comparing between two).

It is therefore more useful, once you have computed the p-value statistic, to report the fold-changes of treat1-vs-control and treat2-vs-control using the following to examine the possible iterations: resultsNames(dds). It will give you something like: "Intercept" "Treatment_treat1_vs_control" etc... You can then select the appropriate fold-change when you generate the data table:

resdf<-as.data.frame(DESeq2::results(dds, format = "DataFrame", name = "Treatment_treat1_vs_control")).

I hope this helps!

Dr. Brian R Murphy perfect

Hi Sebastian,

I would have immediately suggested analysis of 16S rRNA from environmental DNA by employing NGS, e.g. Illumina MiSeq. However, this is a PCR based technique. Nevertheless, any sequencing laboratory will do downstream operation after DNA has been isolated from the sample. I think you could even send a raw sample to them and they would do DNA isolation and the rest. In the end you would get a qualitative and quantitative report on the microbiome of interest. Of course, this kind of complete workflow and analysis comes with a price, you should ask for a quote to calculate your expenses and to check whether is it in line with your budget. Alternatively, you can perform part of the workflow alone to lower the costs, e.g. isolate DNA, and analyse sequences coming from he sequencing laboratory.

Another method that you could use for a rapid quantitative and qualitative analysis of your microbiota are the microarray techniques, which don't require PCR at all. Does a Phylochip ring a bell? If not, check it out (https://ipo.lbl.gov/lbnl2229/)!

Exactly, if you want to assess total microbial community composition FISH technique is not the way to do it.

Again correct, but you will lack compositional information.

To obtain both, qualitative and quantitative information of total microbial community in certain environment, in my opinion, your best bets are molecular techniques mentioned previously. I would refrain myself from staining approach in this instance.

Hope this helps.

Deni

Hi,

Please take a look at this question and the answer: https://stats.stackexchange.com/questions/312302/adonis-in-vegan-order-of-variables-non-nested-with-one-degree-of-freedom-for

In short, the output of `adonis` says: "Terms added sequentially (first to last)". That means that the order matters. And from the answer:

> This occurs because A1 and Moisture are not uncorrelated; as there is some linear dependency, which ones goes into the model first determines how much variation is left to be explained by the second of the pair of covariates.

Please, take a look at the link. Here you can find what you can do in such cases.

Hi Thomas,

Maybe you can consider sampling sediments, as well.

Sediments from the bottom of the streams are suitable places for microbiota sticking.

In water and in sediments, you need to consider a mixed sample, with at least eight sampling sites for every stream reach. How are you defining the stream reaches? How long are they? Fluvial geomorphologists use 10 to 12 times stream-width to determine a stream reach for sampling.

Please tell us about the results and sampling design.

Best,

Yes it can as it can alter or stabilizes the active site residues (probably SNH). Once active site residues of protease stabilizes definitely prtease activity could enhance.

Thank you Gerry for the answer.

This is some good background information:

Hi Saurav, That seems pretty high at the phylum level. Although they are 30% of the reads, how many different taxa do they represent? I am suspicious that mitochondrial or plastid DNA from a eukaryote might be being amplified and seen as bacterial, but not classified further. If its relatively few taxa I would try blasting the sequence in genbank(s) to see if it provides any insight. Good Luck!

Dear Aleksander,

I did a PhD on the ethylene production of Phaseolus Vulgaris L. and Marchantia Polymorpha L.

With the technique I used, I could measure methane, ethylene, ethane and propane as low molecular weight hydrocarbons at the sub-ppb level using a cryogenic pre-concentration technique. The plants were monitored in an open flow system, with very low backgrounds of the chemical species mentioned. The only hydrocarbon which was measurable with this system is ethylene, no methane, ethane or propane which were below the detection level of the measuring system (0.01 ppbv). It should be mentioned that I always removed the soil when I measured the plants in this system whereby the plants were watered with a glassfiber sheet substrate. If the soil was not removed some other of the hydrocarbons popped up above their detection limits.

It is my conviction that a large majority of plants do not emit methane, but when the soils wherein they grow are measured along with the plants growing on them, methane is bound to be measured as well.

Hence, methane is emitted by soils and not by the plants growing in these soils. Only the separate measurement of soil and plant has corroborated this finding, as I did in my PhD.

Hence, the measuring method has to be critically evaluated on the presence of soil in the measurement protocol or not!

Best regards,

Frank

It is not an issue that seems to be related with the PCR product. It is usually related with uneven or too high salt concentration in the sample loaded on the wells, or left overs from the combs dried with buffer, then concentrating salts that are contaminating the wells when casting them. Also, very important is to wash with buffer (pipetting several times) the wells before loading the samples. This helps to clean accumulated salt as I see that this is also happening with the MWM, reason why I think is not an issue of the PCR product salt concentration. DNA loading buffer replacement is recommended (i.e. Glycerol 30%, Bromophenol Blue-Xylene Cyanol 0,2%) (be sure you are not using a loading buffer having a denaturing agent such as loading buffer for protein gels). Finally, there are several tricks to improve how the samples are entering the gel in a more even and horizontal pattern, this is varying the voltage to have a faster entrance after loading, to run the gel for some minutes before loading the samples to distribute homogeneously cations, etc.

The practical way to quantify the microbial population in soil samples would be as described by Ricker (1972) using "bean-sampler method".

cf.: https://www.researchgate.net/post/Elastase_assay_using_Elastin-Congo_Red_assay_principle_i_needed  

Reply by 

Adam B Shapiro · 690.36   ResearchGate SCORE · Entasis therapeutics

" The premise of the assay is that digestion of elastin by elastase allows the Congo Red dye to be released from the dye-elastin complex. The original reference for this assay is Biochemical Journal volume 78 page 156 (1961) by none other than Fred Sanger. Another useful reference for elastase methods is Methods in Enzymology volume 19 pages 113-140 (1970).

Any absorbance value that is greater than the background value by a statistically significant amount should be considered as positive. The initial rate of absorbance increase should be directly proportional to the amount of elastase present.

Jun 14, 2016          " (End of text citation for convenience)

I can't understand why people here is recommending rarefying while at the same time suggesting an article that state in its very title that that procedure is inadmissible. That article in fact was referenced previously here by Adam Šťovíček in his first answer. The complete reference is:

McMurdie, Paul J., and Susan Holmes. "Waste not, want not: why rarefying microbiome data is inadmissible." PLoS computational biology 10.4 (2014): e1003531.

And indeed it's a must-read for everyone working in microbial ecology. Here the authors, demonstrate that rarefying (subsetting samples to even size, as previously called here) is the worst option (they regard it as 'inadmissible'!) since it requires loss of potentially valuable information in the analyses (loss of statistical power). However, normalization by sample size (use of proportions), only has the drawback of not addressing heteroscedasticity, which is the differential dispersion or variance that the counted features (e.g. species) may display across the samples. This condition is normally found in RNA-seq data, because gene expression is a highly dynamical process -- way more than the dynamics of microbial communities, and some genes can vary a lot their expression patterns while others can simply not. Thus, it is unclear that the presence of species can have such characteristic in every experiment. So, for starting with something simple, or exploratory, I still recommend proportions (dividing counts by sample size) rather than rarefied counts (one may ask why the authors rather did not entitle the article ...normalize by sample size is inadmissible). Then, of course, if one suspects the data may have the heteroscedasticity problem, the statistical solutions given in that article must be considered.

EDITED: so much controversy still exists for this normalization process... a more recent article lend support to rarefying in some cases, and I am updating this here because I've being suggesting naive proportions instead. The article also suggests another method called ANCOM. In summary, it does not exists a single best normalization method, and exploring all the possibilities is currently the best way to go.

Weiss, Sophie, et al. "Normalization and microbial differential abundance strategies depend upon data characteristics." Microbiome 5.1 (2017): 27.

you may also find in the link below some information on the multivariate analyses; hope it may help~

g

Hi Muhammad, 

For illumine Miseq, it is the most commercial source for 16S sequencing. Generally people use V3-V4 region of 16S. However, you should look up some papers to check which region they use to identify human gut microbiota. Different region of 16S rRNA gene would have different resolutions.

Dear Catalina,

If you have densiotometric data that comes along with your fingerprint data. You can quantify your bands from a molecular marker with known concentrations. Your software will do that part. The below mentioned papers will tell you how to extract fingerprint data to a matrix format with frequency/quantity. Then you will have to go to vegan package in R to calculate distance matrix and further stuff.

Thanks Dr. Gaetano,

I appreciate your response to my question, actually I am aware of the paper. They have used SSR markers, and I know, several different workers have used other nuclear, mitochondrial gene along with ITS region to differentiate. My question though was, if ITS region alone can be used.

Hello,

I did my PhD looking at the different phytoplanktonic group and differentiate autotrophs to heterotrophs. For each samples, I was doing two observations: 1 with the traditional light to identify the species and then switching on the epifluorescence to observe if the organism is auto- or heterotrophic.   I have checked the article you mentioned, and they don't provide a lot information "Each cell was manually identified ".  I am almost sure that they should have a picture  of the organisms without fluoresecence for identification.

Today I work in a company where we do viability count for Ballast Water using epifluorescence, and identification is done by switching off the fluorescence

Bye

Aurore

Hi Elizabeth,

Thank you for your detail explanation. Your option 1 totally make sense but it won't be easy to prepare.

Thanks

Deep 

Dear Manoj

Maybe i can help you. My email : parziarati@gmail.com

Please  report it in email.

Best wishes

Parisa ziarati

Ok this link will be very helpful  for you:

Ok, sounds challenging - I also found early sampling intervals (6hrs - 2 days) more difficult to deal with. In the BMC Microbiology paper, some samples were excluded for this reason. If PCR fails, you could also consider multiple displacement amplification (MDA) or FISH (if you know which taxa you're looking for).

As a side note: This also depends on temperature... during some pilot experiments, I found that the plastic surfaces were colonised a lot quicker when incubated at RT rather than 4 degrees Celsius :-)

 Hi Dr. Vogel,

Thanks for the answer. Can you recommend a primer set? or a literature that address this.

Thanks, Brijesh! I will try out your method.

Any extraction protocol to extract total RNA, if no specific treatment is included to avoid rRNA, will actually extract mainly rRNA (over 90% of total RNA) and minor amounts of mRNA. RNA strands is in general a very fragile and unstable molecules, so I recommend you to proceed to produce cDNA as soon as you obtain the RNA. There are many possibilities with bacterial RNA but one is to use random hexamers or external primers comprising the targeted region for the PCR amplicon generation (like nested PCR fragments). As example you can use for reverse transcription primers of the outer conserved regions of 16S (like 17F and 1492R) and then for PCR, use on this cDNA template, primers targeting regions inside those fragments (such as V4). Or you can use for the RT reaction random hexamers (NNNNN) and use that cDNA produced as template for PCR amplification of region V4. 

11

Facultative autotroph is  an organism, especially a bacterium, having a metabolism that is either autotrophic or heterotrophic and thus is capable of growth on either inorganic or organic media.

Based on the definition most of the (viable and culturable) bacteria are facultative autotrophs. The ability makes it possible for us to study them under defined  conditions. Concerning the bacterial  classification, it falls to the same challenges as  general bacterial classification.

Please let me know if this was useful and if you would like to hear more about the classification.

hi

Dear Jackson, the method book entitled "Pyrosequencing, Methods and Protocols, Second Edition, 2015" describes a chapter related to BACTERIAL TYPING AND IDENTIFICATION. Maybe it is helpfull for your studies.

Best regards.

According to my opinion it is not possible to make identification using a pic only.

 Best regards Vit 

Hoping this will be helpful to your project, good luck

The main 'classic' method is just leaving a glass slide in the water and let it colonise by the bugs.

For more advanced methods I would recommend take a look on some of the work of Belinda Ferrari at UNSW (Australia).

You can use rdp_classifier standalone 

And after use the files in MEGAN

If you are using biolinux rdp_classfier is already installed

Thanks for your answer, I hope your paper is accepted!

See EPA consideration of the opportunistic pathogen Burkholderia cepacia - https://archive.epa.gov/scipoly/sap/meetings/web/pdf/bc_bkgrnd.pdf.

As James mentioned, except for a few strains, Escherichia coli is normal flora and not a pathogen.  Think Staph aureus would represent too much risk.

The case of bacterial multimetal resistance  is a bit different from resistance to single metal but is more worthy as a tool for bioremediation. I am particularly interested to tolerance and resistance strategy and the cellular, biochemical and molecular mechanism involved there. How does escape mechanism and tolerance in course of time evolves as an adaptive  strategy and means of detoxification and/or removal?

 Thank-you  Lith Al- Ani.I will definitely look into your recommended papers and books.

Characterization of Azotobacter

Direct microscopy investigates was used for pure isolates of Azotobacter. It was found that the microbe is gram negative, large in size, oval or cocci, single or in pairs according to Bergy's Manual (1974) and Becking (1981). Identifying testes were carried out including (IMViC) tests, it was positive in indole test and negative in methyl red , voges proskauer , citrate , gelatin hydrolysis catalase , cellulase , pectinase and amylase activities .Nitrite formation and denitrification tests were carried out by the method described by Neyra et al., (1977) in addition to nitrogenase activity according to (Hardy et al., 1973) and litmus as described by Drews (1983) and Sussmulh et al. (1987)

Characterization of Azospirillum

Pure isolates being short rods of spinning motility gram negative, producing alkalinity in growth culture .The ability of Azospirilla to use glucose a sole carbon source for growth was described by Tarrand et al. (1978), positive in production of acid and gas, requirement of biotin for growth , catalase production and reduction NO3 to NO2.

I would say that it can be used for whole genome and in fact it can not be used with 16rRNA.

Good Luck

Yes just to visualize by microscope

Please go through the PDF attachments.

Thanks Dear Dr Pegman

Couple of ideas re: HPLC. You can collect fractions and test them for CAS reactivity (probably the easiest method). You could take your extract and use EDDHA or another chelator to strip the iron from your siderophore and compare with-chelator extracts to without-chelator extracts (you may see a migration of your siderophore peak once it's released the iron). I would monitor at a couple of wavelengths: one for aromatics such as the DHBA mentioned by Dr. Jameel (although that's just one of three common structures used to coordinate iron ; hydroxamates and alphaketo acids work without using DHBA derivatives) and one for standard peptide bonds (220nm). To increase titer of your siderophore pre-separation, you can add 2,2'-dipyridyl to your media. It restricts the bioavailable iron and results in enhanced siderophore production (typically through fur regulation). Good luck!

Dear Apple,

 You can compare the bulk soil and the rhizosphere zones. They are two different environments.

-The dynamic of the soil zone is under several biochemical reactions driven by the organic matter decomposition by soil microorganisms.

-The dynamic of the rhizosphere zone is governed by the presence of living roots with soluble and available exudates. You can even subdivide the rhizosphere into the inner and outer rhizosphere (adjacent soil).

Have a look to some pictures of the root colonization process over time (ex. : Beauchamp and Kloepper, 2003). This process depends of the plant species and age.

May be you should determine which fungi are there? Try a rapid identification of your fungi (using your ITS2). Are they mycorhizes? Are they plant pathogens? Then you could examine priority effects.

 Sincerely,

Chantal Beauchamp

Depends of the kind of contamination, functional gene families that are possibly involved, and the approach, detection of genes by PCR targeting or in total metagenomic sequencing datasets or by functional metagenomics. I published some articles about it and can be found in my researchgate profile. One review  we wrote on this interest at: https://www.researchgate.net/publication/46402778_Metabolic_networks_microbial_ecology_and_'omics'_technologies_Towards_understanding_in_situ_biodegradation_processes

Hi Muhammad,

I think a log fold change is what you need. Calculate log(A1/A2) where A1 is the raw count of A at time T1 and A2, the raw count of A at time T2. This way, you'll be able to visualize positive and negative changes in abundance.

Agree. Searching any approved bacterial species/strain deposited in DSMZ, there are the conditions for culturing conditions https://www.dsmz.de/catalogues/catalogue-microorganisms.html and the references of the articles reporting the identification of the strain. 

Dear Kamesh

I feel that you are trying to "search a needle from a hay stack". If your microbial community is very highly biodiverse, it would be next to impossible to find the answer. 

remember that metagenomics library itself is very complex and trying to get a microorganism from it requires a lot of patience. 

You're welcome

As Frederick said, the cost will depend on teh required completeness of the draft genome. We typically sequence E. coli on our Miseq/Miniseq for a cost of $100 per draft genome at 50x coverage which is sufficient for epidemiological typing puropses. So expect to pay no more than a few hundred dollars if you have it done by a commercial lab . Buying the cheapest equipment (Miniseq) will easily cost 100 times that amount and the learning curve is very steep if you have never done sequencing.

Dear Patrick,

This is the procedure we used for cultivating Microcystis in our lab:

'Microcystis cultures were established by picking individual colonies from live samples with a sterile micropipette under a binocular microscope. They were transferred to 24-well Repli dishes and later to 250 ml Falcon culture flasks. All strains were grown in freshwater WC medium (Guillard and Lorenzen, 1972) without pH adjustment and vitamin addition, at 24 °C, a photon flux density of ca. 120 µE m-2 s-1 and a 12h/12h light/dark regime. For long-term maintenance, the culture flasks were incubated at 18 °C, under a photon flux density of ca. 30 µE m-2 s-1 and a 12h/12 h light/dark regime, and re-inoculated approximately every month.'

We obtained good results with this method and were able to keep our cultures stable for many years.

Good luck!

Jeroen