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Microbial Ecology - Science topic

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Evolution runs in perpetuity for billions of years, with innumerable remarkable
innovations inspired and catalyzed by both cooperation and conflict. Bacteria in nature are categorized into beneficial and harmful ones. They have evolved the capacity to communicate chemically to coordinate attacks on others, and a willingness to commit suicide for the greater good of the community. At the very early stage of biological evolution Mother Nature conducted a great experiment: Bacteria and Archaea came together in a fusion event to
synthesize a whole new domain of life, the Eukarya. Over the past 600 million years the Bacteria, Archaea and microbial Eukarya have continued to evolve into brand new niches. In the process thet have created new substances for bacteria to exploit and new environments to inhabit. What conditions detemine the nature of interactions? Do such interactions offer some clues? How such interactions could be exploited to solve the environmental problems humanity is facing today?
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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.
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I am currently doing a PCA on microbial data. After running a Parallel Analysis to determine the number of factors to retain from the PCA, the answer is 12. Since my idea is to save the factor scores and use them as independent variables for a GLM together with other variables, I was wondering:
  • Should I definitely save the factor scores of all 12 factors (which would become too many variables) or I can save only a few of them (e.g., the first 3 which together explain a 50% of the variance) for the GLM?
  • If I can save a lower number, should I re-run the PCA retaining only that lower number (e.g. 3) or just use the factor scores already obtained when retaining the 12 ones?
Thank you all for your time and help!
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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.
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Hi, can anyone recommend any papers exploring the relationship between microbial biomass and microbial diversity? Some papers I have looked at just say there’s a moderately positive correlation in their introductions but it’s not the focus of the study or the studies cited.
I also would love if anyone could share papers expounding on the Fungal:Bacteria and G+:G- bacterial ratios and their link to ecosystem functioning/soil health. I have tried searching for studies that go deeper into why these ratios are the objects of many experiments‘ focii, but I still feel I am missing some gaps in their connection with soil health (and soil biodiversity/biomass).Thanks!
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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.
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I am working on an iron inducible promoter screen and would like to perform it on solid media. However, using agar may contaminate my control media with iron and I would like to use some method to deplete the usable iron to the bacteria. I have seen a few papers that use 2,2'-dipyridyl to do so, but I am skeptical because I have never heard of this method and am having trouble finding literature pertaining to this topic. If anyone has experience or can steer me to an article discussing the use of the substance in this way I would appreciate it.
THANKS!
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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
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Dear Friends and Colleagues,
To date very few journals are available to accept video articles for submission/publication in our field, although these types of articles are of paramount importance in microbial ecology in order to share new techniques and approaches.
For this reason, I decided to open a Collection titled “Multi-targeted approaches to evaluate microbial interactions and ecosystem assemblages in diverse environments” on the Journal of Visualized Experiments (JoVE): https://www.jove.com/methods-collections/919.
The purpose of the Collection is to offer a comprehensive overview of wet- and dry-labs perspectives in the field of microbial ecology.
The most recent Impact Factor for JoVE (ISSN 1940-087X) is 1.163, according to the 2019 Journal Citation Reports released by Clarivate Analytics in 2020, and the Journal is currently indexed in the major databases, including PubMed, EMBASE, Scopus and Web of Science.
After submission, each manuscript will be editorially and peer reviewed, which is typically a 1-2 month process. Once a text article passes review, a script will be generated. Generally, a filming date will be scheduled within 4-8 weeks after acceptance. A videographer will be sent to the authors’ site to film the procedure.
If you are interested, either message me or submit an abstract here:(https://www.jove.com/methods-collections/submit-an-abstract?collection_id=919).
Best Regards,
Prof. Elaine CP De Martinis, Ph.D – Full Professor, University of São Paulo, Brazil
Otávio GG Almeida, B.Sc. – Ph.D. candidate, University of São Paulo, Brazil
Guest editors.
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Thanks for sharing!
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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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We will be happy to collaborate. Mechanism has to be developed between the partnership.
Dr Diwan
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The content obtained for the C & N in the soil samples of the forest floors is increased this time and in 2020 is 5 times more than that of the C & N obtained in 2008, simultaneously the same forest stands in four districts is increased by areas observed in the India State of Forest Report 2019, not only that the forest canopy is much lush green in comparison to 2008, is this change be considered as the evidence of the climate change, though the time span of only 12 years is very short for interpretation of the evidence of the climate change.
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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.
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Gut microbiota play significant roles in human health. With the help of Next-gen sequencing, we know much about the compositions of bacteria in the gut but little is known about their activities. What is the default state of bacteria in the gut? Are most bacteria living in the gut at near stationary phase with basal metabolic activity? Do they become more active after a meal? Or they are always active? For example, what will a probiotic species do in the gut after they are taken by people? How many and how long will they colonize and grow in the gut?
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Yes, we need approaches to study their activity in vivo.
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1. There are several database containing nifH sequences like fungene (19500 seq), arb database (32,954 seq), zehr (72000 seq) and farnelid (5,00,000 seq). what is the difference between these databases ?
2. Can fungene pipeline be used for taxonomic classification of nifH functional gene ?
3. Any other pipeline/tool available for taxonomic classification of nifH gene ?
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In addition to the pipeline mentioned above ( ), you can also have a look at this one:
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I would like to find a tool (if it exist ...), to predict the porportion of r vs K strategist in samples from a metabarcoding study.
For example, the tool I need (R package or equivalent) could work similarly to functional predictive tools such as Tax4Fun, FAPROTAX or PICRUST, but instead of predicting functions, it investigate ecological strategy such as r vs K as explained by the "r and K selection theory".
Benoît.
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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
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Does the material of the 96-well plate (PVC or Polystyrene) make a difference on the attachment of the biofilm to the surface? I am able to grow a mature Mycobacterium biofilm on the air-media interface, just need a better way of quantifying, as most of the bacteria is washed away when rinsed with saline. Plate counts works fine, but need a more high throughput method. Also, what stain will work the best to use for mycobacterial EPS?
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I am processing a 16s RNA next gen sequencing data set and trying to compare between my samples the effects on organisms involved in the nitrogen cycle. I am just wondering if there is some sort of database or even a good paper that goes over all of the known organisms in the nitrogen cycle. The more detail the better but i would settle for just a simple list
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Thanks Shan Thomas i will check it out, looks like a more convenient solution than trolling through papers
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I am working on a project aimed to determine the influence of long-term fertilization on soil microbial communities.  I am sampling both the rhizosphere and the bulk soil and hope to use the current best choice of primers for targeting bacterial and archaeal 16S rRNA genes. Initially I planned to use the primer pair 341F/785R, which targets the V3-V4 region of 16S and is reported to have good domain coverage for both bacteria and archaea. However, I now also have the option to use separate, archaea (956F/1401R)- or bacteria (969F/1406R) -specific primers, which target the V6-V8 region of 16S. The benefits of the separate primers are better coverage for archaea, and less eukaryotic sequence contamination, but the V3-V4 primers are the standard tool typically used in similar research. I am confused with which set should I proceed with or if there are any other primer sets I should be considering?
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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
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I have two treatment groups of sample plus a group control. Each treatment and control have own three replicates. I am using Qiime2 for data analysis. I am in dilemma to the following ways below. My question is here:
For normalization prior to statistical analysis, do I need to get an arrange value of three replicates then normalize my data or without calculation the average?
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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.
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I have atmospheric microbiome data and want to know how I should be analyzing alpha diversity. I used unweighted unifrac for beta diversity and thought that I should use Fath's PD but don't really understand the difference between Faith and Chao1.
I don't think Shannon is going to be good because my data has the presence of many low abundant taxa and is zero inflated.
Any help is greatly appreciated!
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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
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Has such a question been answered in a paper? Or does anyone have experience with that?
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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?
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Is there a possibility that bacteria show low solubilization index on PVK agar medium but show quite a high solubilization efficiency in PVK broth when quantified? If so, Kindly share some literature.
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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.
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I am currently investigating Archaeal and Fungal populations in a micro biome dataset, and while digging in the literature I came across the linked paper below in which they utilized Permanovas to dissect their data. Can someone (in laymen's terms) explain what this test does and why it is useful in this situation?
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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.
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In a fermentor reactor, I have detected several "Uncultured bacterial clone (Prevotella)" with >95% of identity which were dominant and appeared to inhibit the fermentation process under certain operational conditions where the main fatty acids were acetate and butyrate. However, they were also present in the microbiome under other operational conditions where the reactor performance was different.
I have read that some Prevotella species can produce bacteriocins but I am wondering if this has only been determined for a few well known species or is it a more general feature for the genus Prevotella?
And what (pH, substrate availability, redox) might trigger bacteriocin production in this or other genera?
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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.
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Hey! Dear colleagues,
I am designing my experiment. I want to know which nuclease can cut linear dsDNA but don't cut circular dsDNA?
To be more specific. I am looking for a nuclease that cut the extracted genomic DNA but don't cut the plasmid DNA. 
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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.
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I'm quite confused about using DESeq2 to find the differential abundant taxa in microbiome studies, especially when there are more than two groups of the factor. I know DESeq2 was initially used for RNA-seq to detect the regulation of gene expressions. It's easy to understand when there are only two groups, e.g. treated vs. untreated. We can easily say which taxa was up-regulated by looking at the log2fold change (positive or negative).
BUT what about when there are three groups, control vs. treat1 vs. treat2? The DESeq2 can still handle this situation, but then I have no idea how to interpret the log2fold change. If we detected some taxa that were significantly different, how can we know in which group these taxa were up-regulated?
Although some people suggest to do the pairwise comparison, it's still unclear to me how to do it and how to interpret it. Does anyone have very good recommendation or idea about this?
Thanks in advance.
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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!
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For a dark root that doesn't clear with 10% KOH in autoclave for 1 hour, 24 and also 48 hours at room temperature, would it be possible and time effective to directly clear it with 0.5%NH4OH+0.5% H2O2?
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Dr. Brian R Murphy perfect
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Hi fellow researchers,
I have recently begun a PhD in an interdisciplinary team that involves some microbial ecology in field experiments on my part.
Correspondingly I am looking for a way to determine especially prokaryote diversity from soil and water samples (types of species and relative abundance basically) in a mobile setup.
It should be relatively quick and especially not too expensive to buy up-front.
I am not sure about FISH as the technique seems to be more about looking at the occurence of specific strains that you already know before-hand (and thus know the complementary DNA).
PCR techniques use quite a lot of rather costly equipment and is pretty lab-bound to my experience.
The abundance itself could be achieved by DAPI/Hoechst staining and fluorescent microscopy.
Any way to get a sense of types of prokaryotes involved / general diversity in the field though?
May alternatively look at fungi in the field aswell so if that would work in a similar fashion that would also be great.
Any ideas would be much appreciated.
Thanks
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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/)!
  • "I am not sure about FISH as the technique seems to be more about looking at the occurrence of specific strains that you already know before-hand (and thus know the complementary DNA)."
Exactly, if you want to assess total microbial community composition FISH technique is not the way to do it.
  • "The abundance itself could be achieved by DAPI/Hoechst staining and fluorescent microscopy."
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
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I always have some problems with the formula while doing PERMANOVA. For example, adonis(distance.bray ~ x+y, sample.data, permutations = 999) and adonis(distance.bray ~ y+x, sample.data, permutations = 999) gave me the different results of the R square values for factor x and y. So what are the difference between these two formula? And which one should I trust?
Also, I once did the analysis with three factors. When I did adonis(distance.bray ~ x+y+z, sample.data, permutations = 999), z was significant. But when I do adonis(distance.bray ~ z, sample.data, permutations = 999), z was not significant. Can someone explain what happened in these analyses?
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Hi,
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.
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In parallel with a project I am currently working on ("BiodiverCité", the inventory and characterization of the wetlands of the urban area of Bordeaux in France), partners will have to opportunity to collect samples of water over a few dozen streams carefully selected. While they are interested in the hydrological and chemical characteristics of these rivers and their associated fauna, I had the idea to take advantage of this sampling campaign to focus on the microflora and, later, possibily establish a link between the different data produced.
I am interested in two types of microflora : on the one hand, bacteria, archaea and other unicellular organisms (but mainly bacteria I must admit) and, on the other hand, the viral microflora.
Concerning the bacterial flora, I will unfortunately exclude any pasteurian approach, because of lack of time and lack of means.
I started with the idea of centrifuging the collected water samples and carrying out a DNA extraction which would join a DNA library to be analyzed once the financial means have been collected.
For the viral flora, I thought to carry out a precipitation of 1M NaCl, PEG6000 10% on the supernatant to concentrate the viruses in a volume easily handled and storable to have a phagolibrary in which to possibly find phages directed against bacterial species of interest (eg F. psychrophilum or other pathogenic species in aquaculture) and secondly, carry out a phage nucleic acid extraction to constitute a phagoDNAlibrary exploitable in the longer term.
My questions are:
1) What volume of sample should be collected to have enough bacterial DNA to make metabarcoding ? For the soil, the specialists of Genosol (INRA, France) urge me to extract from at least 500 mg of soil for bacterial and 1 g for fungal. But for water ?
2) Is the NaCl / PEG6000 precipitation suitable for a long-term phago-library ? I fear that this step is too brutal for some phages and that even if I concentrate theoretically in number of viral particles, I lose in infectivity (due to damage to viral fibrils). If this technique is suitable, is the use of PEG8000 better recommended to ensure a wider enrichment spectrum (for podoviridae for example, more difficult to precipitate if I understand my literature) ?
3) I know there are publications on viromics but I have not looked into detail: what minimum sample volume (before precipitation) is desirable to have enough DNA for metagenomics (or just qPCR detection of well known virus) ? 200 ml ? 1L ? 10L ??? (2 ml :) ?)
Thank you for your attention.
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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,
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While checking the effect of inhibitors on protease enzyme it was found that iodoacetate instead of inhibiting the protease activity it has enhanced the protease activity. I searched alot but could't find the possible reason for this. Can anyone explain what could be the possible reason for the same. Thank you.
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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.
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Is there a definitive method for typing Streptomyces strains apart from whole genome sequencing ?           
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Thank you Gerry for the answer.
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What are the criteria or procedure to define a new phyla form culture independent processes?
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This is some good background information:
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If you want to do taxonomic profiling of your ngs data, mainly comprising the variable regions of 16S (v3-v4), which database you will prefer and why ?
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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!
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Dear All,
not only in all known to me textbooks, but also in my academic environment, plants are only discussed as carbon sinks and therefore planting forests is said to be one of the main strategies to reverse or reduce some effects of climate change.
But: About 10 years ago a german team from MPI published - and that seemed to be a shock for some climate researchers - that plants (especially forests) are able to produce tremendous amounts of methane under "normal" aerobic conditions autonomously (1). There were even attempts to link the ending phase of the ice ages with forest growth in the way that besides volcanic or solar activity forests were responsible for the warm up (and not vice versa).
Still in any lectures at my institution only common methane sources (microbes, anaerobic environments as bogs and swamps, cattles, humans,...) are discussed with students while - as said - plants are only considered as carbon sinks.
How so? Do you know something about the latest discoveries in this field (maybe i missed some relevant publications)? Are plants excluded as methane sources because of new investigations? Or is it an open (and not well known) problem that is not recognized broadly by environmental scientists?
Thank you
(1) Keppler F, Hamilton JTG, Brass M et al (2006) Methane emissions from terrestrial plants under aerobic conditions. Nature 439, 187-191.
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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
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We are running 1.5% agarose gels (using 1x TBE as a buffer), for 8 hours at 120 watts.
Gels have continuously been very smeary and bands are in the shape of an upside down 'u'. Due to the strange nature of the bands, we have run the same samples multiple times and the number of bands and band lengths also vary every time (The two attached pictures represent different samples, though).
In addition the current when running the gel seems to be uneven.
We have already tried altering the amount of sample that we load into the gel, and altering PCR conditions.
Has anyone ever seen this issue before and know what could be the cause?
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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.
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Best practical way to quantify the microbial population in soil samples?
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The practical way to quantify the microbial population in soil samples would be as described by Ricker (1972) using "bean-sampler method".
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I want to do an elastase production test. How can I do it?
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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)
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I want to compare bacterial communities using 16s rRNA sequences. I used Illumina Miseq and I has big differences in the number of OTUs and reads in all the samples. I use Primer-6 software to get diversity indexes and comparative analysis (ie. MDS, CAP). The question is: Is it necessary to normalize the total number of reads for these analyses and comparisons? If it is true, Which methodology is recommended?
Thanks!
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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.
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I have to prepare biological samples (natural fibrous material like luffa sponge) for SEM analysis to understand the colonization of Methanogenic Archea in biofilms. after fixation in glutaraldehyde followed by dehydration in graded series of ethanol solutions it require to be completely dried by Critical point drying or lyophilization. as i have no facility of these two, is there any alternative or shall i simple dry it in drying oven?
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Yes. Go a head.
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I am analysing microbial communities from different sources regarding cheesemaking (milk, starter culture, cheeses) and I would like to know which is the best way to correlate these microbial communities with environmental samples such as latitude, longitude, altitude, etc.
I am currently using Qiime and phyloseq, but I want to give a try with Vegan. Anyone could help me with some functions from this software regarding my main question?
Thanks a lot!
Cheers,
Felipe
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you may also find in the link below some information on the multivariate analyses; hope it may help~
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DNA isoalation of microbial community for DGGE. I m looking for an explanation and recent papers in support.
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How many samples should be included for the authenticity of  16S metagenomic data for human gut microbiota?
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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.
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Dear Everyone,
I'm looking for some papers on using selective media to identify and enumerate certain soil based probiotics. May you know any papers, please advise. Thanks
Arthrobacter agilis,
Arthrobacter citreus,
Arthrobacter globiformis,
Arthrobacter luteus,
Arthrobacter simplex,
Acinetobacter calcoaceticus,
Azotobacter chroococcum,
Azotobacter paspali,
Azospirillum brasiliense,
Azospirillum lipoferum,
Bacillus brevis,
Bacillus marcerans,
Bacillus pumilus,
Bacillus polymyxa,
Bacillus subtilis,
Bacteroides lipolyticum,
Bacteriodes succinogenes,
Brevibacterium lipolyticum,
Brevibacterium stationis,
Kurthia zopfii,
Myrothecium verrucaria,
Pseudomonas calcis,
Pseudomonas dentrificans,
Pseudomonas fluorescens,
Pseudomonas glathei,
Phanerochaete chrysosporium,
Streptomyces fradiae,
Streptomyces cellulosae,
Streptomyces griseoflavus.
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Does anybody know which is the best way of calculating alpha and beta diversity from molecular fingerprint techniques? I have done DGGE with environmental samples in order to determine the diversity of microalgae, I have the band patterns with the number of species in each sample, but I'm not sure how to calculate diversity, taking into account that I don't have abundance data, only number of species.
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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.
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I want to find out if ITS sequence can be used to study diversity of Phytophthora population in a region?
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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.
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Hi, I am approaching to the identification of nano and microplankton using an inverted microscope with epifluorescence. 
I would like to differentiate the organisms in 7 classes:
Autotrophic dinoflagellates, autotrophic flagellates, cryptophytes, diatoms, prymnesiophytes, heterotrophic dinoflagellates and
heterotrophic flagellates.
This type of classification has been used by Landry et al. 2014 (http://dx.doi.org/10.1016/j.dsr2.2014.02.006).
Using the epifluorescence I can distinguish heterotrophs from autotrophs, but I do not now how to identify the organisms for each class.
Do you know how to do it? 
Thank you, any help will be more than welcome,
Luca
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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
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We are looking for the stool standard with known bacterial abundance which we can use as a control to find if any differences between two stool DNA extraction method.
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Hi Elizabeth,
Thank you for your detail explanation. Your option 1 totally make sense but it won't be easy to prepare.
Thanks
Deep 
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Hi,
I am analyzing my 18sRNA Soil samples for Eukaryota classification with Mother pipeline. I used Silva.nr_v123.align database and silva.nr_v123.tax in alignment. In result, as i see in taxonomy file there are classification up-to class level of species but not classification up-to species name.
Please let me know how to get classification upto species names.
Example Result
#########################
OTU Size Taxonomy
Otu000001 27283 Eukaryota(100);Opisthokonta(100);Nucletmycea(100);Fungi(100);Zygomycota(100);Mucoromycotina(100);
Otu000002 24765 Eukaryota(100);SAR(100);Alveolata(100);Ciliophora(100);Intramacronucleata(100);Spirotrichea(100);
Otu000003 18535 Eukaryota(100);Opisthokonta(100);Holozoa(100);Metazoa_(Animalia)(100);Eumetazoa(100);Bilateria(100);
Otu000004 15052 Eukaryota(100);Opisthokonta(100);Holozoa(100);Metazoa_(Animalia)(100);Eumetazoa(100);Bilateria(100);
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Dear Manoj
Maybe i can help you. My email : parziarati@gmail.com
Please  report it in email.
Best wishes
Parisa ziarati
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Horizontal gene transfer is the primary mechanism for the spread of antibiotic resistance in bacteria. How to detect when there is HGT between bacteria and their hosts?
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Hello,
I am analysing microbial assemblages attached to marine microplastics using 16S metagenomics, and I have a query about maximising the quantity of DNA I can extract from the substrate?
I have been using the DNeasy Kit, Qiagen (Formerly PowerSoil, MoBio) to remove the attached assemblage from the plastic (recommended by Harrison et al, 2014), but I am struggling to extract any DNA - according to PCR amplification and 0.8% agarose gel electrophoresis. I am aware that the associated biomass, ergo DNA yield, is typically very low.
One paper (Debeljak et al, 2017) suggests that I should incorporate an additional lysis step using ReadyLyse solution (Epicentre) to maximise cell lysis. However, I was wondering if there was a cheaper alternative? For example, I was thinking of creating a Lysozyme:TE Buffer solution to the desired molarity, although I'm aware that the enzymes are derived from different sources and have different efficiencies.
If anyone has any feedback/recommendations, that would be very useful!
Thanks in advance.
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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 :-)
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I have some river DNA samples (i.e., biofilm, water, sediment) for which I would like to know about the amounts (or relative proportion) of eukaryotic and prokaryotic DNAs before metagenomic sequencing.
Any comments or insights would be greatly appreciated!
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 Hi Dr. Vogel,
Thanks for the answer. Can you recommend a primer set? or a literature that address this.
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Besides, how many cells should be collected at least to realize a good RNA extraction?
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Thanks, Brijesh! I will try out your method.
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I have recently come across some papers that suggest 16S RNA sequencing as a technique to know the active microbial population in metagenome and require some views about it. Also if this experiment is effective, I would like to know how to specifically isolate rRNA as most kits offer specific isolations of mRNA only.  
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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. 
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I isolate bacteria from jhum soil and get may Burkholderia species, can you suggest any reason for their abundance and an article for reference in this respect.
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I would like to know if there is a detailed biological classification of autotrophic or facultative autotrophic microorganisms.
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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.
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How to increase the production of certain molecules from certain bacteria in communities of microbiome without changing these community profiles?
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Pyrosequencing in gene diversity
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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.
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anyn one have any idea what the yellow coccoid species are?
sample was from a stream in west Georgia.
cond-32.9 DO- 8 ppm pH-6.5
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According to my opinion it is not possible to make identification using a pic only.
 Best regards Vit 
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Can fastidious or even unculturable marine bacteria be grown in situ? If so, what are the current methodologies for doing so?
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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).
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Looking for a pipeline for taxonomical assignments of large batches using the RDP classifier. Any help?
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You can use rdp_classifier standalone 
And after use the files in MEGAN
If you are using biolinux rdp_classfier is already installed
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I have two groups of fecal samples and want to compare α-diversity between the groups. I already know the Shannon index for the microbial community of each sample, and I know I can compare one sample with another sample in terms of α-diversity, but I would like to know a way to compare groups of samples, not one sample to another. I am thinking it more like a comparison of a group of ecosystems against a different group of ecosystems, always in terms of α-diversity. The attached paper from Nature seems to have calculated something like a mean relative inverse Simpson's index (Figure 1a).
Thank you in advance.
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Thanks for your answer, I hope your paper is accepted!
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Some possible species used are E. coli and S. aureus 
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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.
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Municipal and industrial wastewater often contains a cocktail of a multitude of heavy metals and nutrients. Bacteria present in such wastewater may develop multiple heavy metals resistance to cope with such heavy metal stress as an adaptive strategy. These bacteria with multimetal resistance property have the potential for remediating the wastewater or soil contaminated with multiple heavy metals. I expect some enlightening   and enriching inputs from RG friends and researchers.
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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?
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I want to  isolate microbes from fermented  fish but confused  which type  of microorganisms  should be targeted and what media can be used to isolate  them.
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 Thank-you  Lith Al- Ani.I will definitely look into your recommended papers and books.
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I want to screen soil samples for azotobacter and azospirillium, so is there any plate or chemical assay to quickly screen samples, after that when I identify it as any one above them, then please suggest any molecular or other method to identify the strain of the same..
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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.
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Can any one tell the CGR can only be used for whole genome or it can be used for 16S rRNA gene sequence (from cultivable microbes). 
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I would say that it can be used for whole genome and in fact it can not be used with 16rRNA.
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Hi, I am looking for sequencing my soil samples. My objective to study bacterial diversity in the response of nitrogen fixation. Could you suggest me the good target gene and primers. I am wondering to go with MiSeq (2*250) technique. Thanks..  
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Good Luck
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Which method is more suitable for the isolation and concentration of parasites isolated form sand?
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Yes just to visualize by microscope
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Please suggest me the best and precise methodology to extract the microbial biomass N in soil samples. Thank u.
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I want to analyse the biomass, abundance and functional diversity of different flora and fauna in my experimental samples. Please suggests me precise and standard methods for this purpose.
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Thanks Dear Dr Pegman
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Actually how to Identify the siderophore from bacteria? after screened through CAS test
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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!
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Hello , everyone. I measured the rhizospheric fungal community by ITS2 sequencing and found greater within site dissimilarity in rhizospheric compartment than thoes in bulk soil. I wonder of  priority effects could be operating in rhizospheric compartment? How can I directly test the priority effects? Can I take the bulk soil as the initial state and the rhizospheric as the final state and then compare the difference between these two state? Thank you for your consideration!
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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
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Hi,
I'm working on degradation studies. The sample I have, is a consortia of unknown microorganisms. I want to study diversity of microorganisms on gene basis particularly functional gene community, which are taking part in degradation. Can anyone help me out in this.
Thanks
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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
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Hi all, 
Can you suggest me a method to create a heat map based on actual data and not the relative percentages? I need it because I have different treatments with increasing the overall population! For example, in one treatment, I have a species A with number 30, and species B with number 70. On the other hand, in second treatment, I have species A with number 300 and species B as 700. So, the heat created on relative percentages will say that there is no difference however there is a major difference in the expression of each species population. I have such a dataset for which I want a descriptive illustration. Can anyone help me to figure out a way for such a problem. Thanks in advance!
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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.
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Does anyone know of a consolidated, easy-to-access resource for identification/growth conditions of culturable bacteria?
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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. 
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According to metagenomics, DNA is extracted from a mixture of microbial community in soil, cloned into a vector and later on a metagenomic library is constructed. the ability of the community to produce a specific protein or antibiotic is also tested. However my doubt is that how the specific organism of interest can be isolated from the metagenome library which has hundreds of microbial community. there also exists a possibility that we may not know the primer sequence for a novel microorganism not yet studied which may be producing the specific antibiotic.Can somebody make this point clear to me
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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. 
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Hi All, I am working on denitrifying bacteria (nosZ genes) in soil, I would like to ask you that what is the best database for reference sequences for BLAST? I would appreciate any kind of help………….Thanks.
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You're welcome
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I am currently working on microcystis which is a very toxic algae. We are near to having a monoculture and would like to get a whole genome sequencing done when that has been achieved. What are some reliable companies that do genome sequencing and how much does it usually cost? Or is this something that you would have to purchase instruments for?
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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.
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I am trying to grow cultures of either Microcystis or Anabaena but I am having trouble getting them to take off. Right now I am using a modified version of COMBO with limited to no results. Any help or advice would be appreciated! Thank you!
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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