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Microbial Diversity - Science topic

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What kind of soil is rich with microorganisms and impact of introducing new microorganisms to soil microbial diversity?
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Dr Souvik Bag thank you for your contribution to the discussion
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Hello,
I recently received metagenomic 16S rRNA gene sequence data from a company, which includes both raw reads, and clean data with barcodes removed. My goal is to analyze these sequences and obtain information on the taxonomic diversity and abundance of the species present in the sample.
Since I use a Windows system and cannot utilize Mac or Linux, I would greatly appreciate guidance on how to proceed with this analysis. Are there any web server-based applications available that can assist with this task?
Furthermore, if there are any researchers or experts interested in this project, I would be grateful to explore potential collaborations. Please feel free to reach out to me if you are interested or have any recommendations.
Thank you in advance for your assistance.
Best regards
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SilvaNGS - simple and win-based. https://ngs.arb-silva.de/silvangs/ It is probably less flexible than all nice approaches mentioned above but it is quite useful for first look or for someone who needs an established reliable pipeline
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Why is microbial diversity important in the ecosystem and relationship between soil microbial diversity and ecosystem function?
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I agree with Negin Naghibi that the diversity of microorganisms is critical to the functioning of the ecosystem, because there is the need to maintain ecological processes such as decomposition of organic matter, nutrient cycling, soil aggregation and controlling pathogens within the ecosystem. Microbial diversity in the soil is always crucial for any ecosystem as they play vital role in improving soil health, plant growth and yield, and maintaining the sustainability of that ecosystem, as well as reducing the use of chemical fertilizers. The diversity and biomass of soil microbial communities are the major regulators of fundamental ecosystem processes, such as organic matter decomposition, nutrient cycling, and gaseous fluxes. Soil contains all major groups of microorganisms-bacteria, fungi, algae, protozoa, and virus, but bacteria are the most numerous usually the topsoil contains the greatest number of microorganisms due to the sufficient supply of oxygen and nutrients. Microbial bioremediation strategies are based on the consortia of diverse organisms that are indigenous to the polluted sites and possess immense metabolic potential. Isolating and purifying such indigenous microorganisms gives some knowledge of the microbial metabolites and the degradation processes. The diversity and biomass of soil microbial communities are the major regulators of fundamental ecosystem processes, such as organic matter decomposition, nutrient cycling, and gaseous fluxes. Increasing species diversity can influence ecosystem functions — such as productivity — by increasing the likelihood that species will use complementary resources and can also increase the likelihood that a particularly productive or efficient species is present in the community.Thus, by having a greater diversity of microbes there is a greater opportunity for different microbes to perform specific functions associated with the different stages of litter decomposition; nutrient and carbon cycling that together maintain the broad ecosystem functions of plant productivity and diversity. Ecosystem Diversity can be the variety of different habitats, communities and ecological processes. A biological community is defined by the species that occupy a particular area and the interactions between those species. Microbes live in every kind of habitat (terrestrial, aquatic, atmospheric, or living host) and their presence invariably affects the environment in which they grow. Their diversity enables them to thrive in extremely cold or extremely hot environments.
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What is the role of microbes in maintaining temperature and microbial diversity changing with climate change?
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Warmer temperatures affect the densities of airborne microbes and can accelerate their long-distance transport. Higher temperatures and environmental stresses can also alter human and animal physiologies and defenses against pathogens. Skin and gut micro biomes may become less protective. Temperature also impacts microbial growth. Most microbes grow optimally within a certain temperature range dictated by the ability of proteins within the cell to function. In general, at low temperatures, microbes grow slower. At higher temperatures, microbes grow more quickly. The most significant effect of the microbes on earth is their ability to recycle the primary elements that make up all living systems, especially carbon, oxygen, and nitrogen. Primary production involves photosynthetic organisms which take up CO2 from the atmosphere and convert it to organic material. Microbes play an important role in climate because they release carbon dioxide into the atmosphere when they eat. Bacteria and their main predators, protests, account for more than 40 times the biomass of all animals on Earth. As a result, they have a huge effect on carbon dioxide emissions. Microbes are involved in many processes, including the carbon and nitrogen cycles, and are responsible for both using and producing greenhouse gases such as carbon dioxide and methane. Microbes can have positive and negative responses to temperature, making them an important component of climate change models.Increased levels of CO2 also induce the reproduction of microbes, resulting in excessive consumption of the nutrient, as well as iron and phosphorus, which are not abundantly found in the oceans. Carbon dioxide can also affect the biodiversity of keystone microbial species of the ocean ecosystem. Microbial population in soil are determined by various factor such as soil depth, organic matter, porosity, oxygen and carbon dioxide concentration, soil PH, etc. Factors that influence microorganism role in nutrient building and cycling in soil and organic matter decomposition are of unique interest.
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How does microbial diversity help the environment and potential impacts of climate change on microbial communities?
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The diversity of microorganisms is critical to the functioning of the ecosystem, because there is the need to maintain ecological processes such as decomposition of organic matter, nutrient cycling, soil aggregation and controlling pathogens within the ecosystem. Warming and physical changes to soil can affect nutrient availability and cycling by microbes, which will have unknown cascading effects on the environment. Microorganisms consume and produce the key greenhouse gases CO2, CH4, and N2O, which contribute to global warming. Microbial diversity in the soil is always crucial for any ecosystem as they play vital role in improving soil health, plant growth and yield, and maintaining the sustainability of that ecosystem, as well as reducing the use of chemical fertilizers. Microbial functional diversity is a constituent of biodiversity that includes wide range of metabolic activities that can influence numerous aspects of ecosystem functioning like ecosystem stability, nutrient availability, ecosystem dynamics, etc.
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My undergraduate thesis partner and I will be identifying and characterizing the microbial diversity in 3 sample sites from an urban river. We were thinking of using Sanger sequencing since we would just like to identify what is in the river, but NGS yields a lot of data to really characterize the bacteria present. Our main issue with NGS however would be cost. We are planning to apply for subsidies but our budget is around PHP 20,000 or USD 360. If we will be sending 3 samples, which institution has the most affordable NGS sequencing service? What are possible alternatives to NGS that are more cost-friendly to undergraduate students?
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For Sanger, you need a purified PCR product. I am not sure what you mean by as much data as possible - you will get a single consensus sequence for each direction up to ~800 base. I would recommend talking to a sequencing lab or whoever has a sequencing machine at your university to discuss your options.
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I am studying microbial diversity and wants to know which culture media should I use to get a better understanding of microbial diversity
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Primary media which can be used to access the microbial diversity present in the sample are Nutrient Agar Media or Luria Bertani Agar Media, Peptone water, Nutrient Broth and Luria Bertani broth.
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Actually I am writing a review on Microbial diversity of a medicinal plant and want my article to be published in Reviews in Microbiology of Natures. I have gone through previously published articles and also guide to author section of the journal but still have few confusions regarding the formatting of article. I want to ask that should we have to give the details of frequently used words into separate boxes/sections? as I have seen it is provided into separate boxes in previously published articles. Please try to help me regarding this.
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Every journal format followed according to own system in following rsearch item history ,writing researcher name and literature review
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Dear researchers, I am conducting an experiment with five treatments, out of which four treatments are used as a rotation, while the 5th one is used as a control (bare plot).
How can I take a soil sample from these plots for soil microbial diversity analysis? In rotation plots, rhizosphere samples can be taken but in the bare fallow plots, which method do I use to take samples. If I take rhizosphere samples in vegetable plots, then fallow plot soil would be considered as bulk soil. How can I compare the bulk soil with rhizosphere soil?
I appreciate any help you can provide.
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Dear Andrew Paul McKenzie Pegman thank you very much for your valuable suggestions.
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I am interested in doing microbial diversity analysis associated with a plant. I was looking for PNA clamps suppliers who can provide me mitochondrial PNA and plastid PNAs. Let me know if anyone has used it in their experiments or if someone can provide me as a courtesy.
Thanks in advance.
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I have been using them many times when working with grapevine-associated microbiome. As a rule of thumb I would check before-hand if they match the specific target you want to prevent and then they should work quite well. Only recently I had problems with wheat mitochondrial DNA and so far I have not had any luck using mPNA
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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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extensive exploitation of soil by following un-scientific practices of agriculture and introducing new Micro-Organisms (Beneficial Microorganisms for Agriculture ) to local soil microbial diversity. Are we altering the ecosystem of such microbial diversity of the respective soil?
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One school of though considers not to introduce any new microbe in already existing local soil microbial diversity , it could disturb the existing microbial synergisms...and in the process, introduction of new microbe could disturb the functional microbial diversity of a soil..
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I want to determine the effect of paddy farming on microbial biodiversity without using molecular methods since they are expensive and I don't have access to it.
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The points/methods suggested by
Utpal Mallick
are only applicable if one is working with any known candidate as growing the whole microbial community together or in a predefined medium is not practical. Microscopic methods or biochemical methods are primarily used for particular isolates and never used for a soil communities. I agree with Phil Geis that you most certainly can not determine the microbial diversity without molecular methods. Just to let you know, even molecular methods are not capable to fully determine the complete diversity in any natural environments. So, you can either ask for the assistance from your colleagues in same institute (as they have good lab for molecular analysis), hire commercial service for simpler methods like T-RFLP etc. or just drop the idea to study of microbial diversity. You can instead focus on any particular organism.
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Can anyone point to any studies (other than the one below) that suggest a loss of microbial diversity in a given habitat exacerbates the spread of ARGs, or that increasing microbial diversity (e.g. via inoculation) reduces ARGs?
And/or if you have any general thoughts on this, please leave comments.
Thanks,
Jake
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Dear colleague,
Please see this study:
We discuss aspects of how the loss of microbial diversity impacts ecosystem functions, with a focus on the degradation of organic pollutants.
To date, I only know the work Chen et al. (2019) on this theme. Being that for 7 years I am inserted in the field of study microbial diversity and degradation of organic pollutants in the soil.
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I am comparing the gut microbial diversity of 2 groups of individuals. I found that the alpha diversity is significantly different but the beta diversity is not significantly different. Can I still assume that the groups are different in their microbial population?
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Alpha diversity indices are most influenced by the abundance of local communities. When looking for beta diversities, the index you are using is crucial to understand if these abundances are taken into account or not. Bray-Curtis and Sorensen, for example, are based on the same equation. The only difference is the assumption of abundance-based (Bray-Curtis) or presence/absence (Sorensen). You can normalize alpha diversity matrices before running beta diversity tests by using Raupp-Crick correction, for example. It decreases the bias that different abundances would cause in beta diversity inferences. I would rather use beta Bray balanced.
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The fact that fewer birds from each replicate will be used for sampling leaving more than half from each experiment unused is the problem, which in effect is related to cost.
DR. Kan asked for more datails about the study. (please see below).
Experimental Procedure Experiment 1.
Effects of dietary supplementation of a phytobiotic or synbiotic on the growth performance, immune status, and cecal microbiota of pasture-based broilers. A total of 180 one-day-old, male Cornish Cross broiler chicks will be purchased from a local commercial hatchery. All birds will be fed a corn-soy meal starter diet containing 23% CP. After two weeks, the birds will be blocked by weight and randomly allocated in triplicate (20 birds per replicate) to one of three dietary treatments. For six weeks, birds will be fed the control diet (CON), the control diet supplemented with thymol and carvadiol or the control diet supplemented with symbiotic. All birds will have free access to pasture from sunrise to sunset.
On 28 and 42 days of age, six birds from each treatment (two birds from each replicated pen) will be randomly selected, individually weighed and samples taken.
Objective 2:
Effects of dietary supplementation of thymol or synbiotic on laying performance, egg quality, and cecal microbial diversity of pasture-based laying hens. A total of 90 Rhode Island Red hens at point-of-lay will be used in this study. The birds will be randomly allocated in triplicate (10 birds per replicate) to one of three dietary treatments. For 12 weeks, the birds will be fed control diet (CON), the control diet supplemented with thymol and carvadiol or the control diet supplemented with symbiotic. Birds will be placed on commercial layer diet (16% CP) with free access to pasture from sunrise to sunset.
On week 10, samples will be collected from one bird from each replicate.
Statistical Analysis:
Data will be analyzed using the GLIMMIX procedure of SAS. Each replicate will be considered the experimental unit and the model will include the fixed effect of treatment. Effects will be declared significant at P ≤ 0.05 and tendencies will be considered when 0.05 < P ≤ 0.10.
NOTE: In Expt. 1, 36 birds will be sampled out of a total of 180 (144 birds will not be used)
In Expt. 2, 9 birds will be sampled out of a total of 90 (81 birds will not be used)
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I following the best answer.
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How to go about the microbial diversity of sediment creek
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Hello, if you need find out total biodiversity of river water the better way is DNA Pyrosequencing. By culture cultivation on different nutrient media will show only cultivable forms of microorganisms.
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Different taxonomic levels are used in mono-gastric animal feeding experiments which report changes in intestinal microbial diversity indexes and relative abundance caused by dietary treatments. For example, paper report changes in diversity indexes and relative abundance of fecal microbiol in phylum level, family level or genus level for studying effects of buytric acid (a feed additive) supplementation. And sometimes researchers relate the changes in intestinal microbial diversity indexes and relative abundance to the improvements in growth performance and incidence of diarrhea of experimental animals. Can someone experienced in this field explain the criteria for choosing the correct taxonomic level for comparing microbial diversity following dietary treatments? What factors should be considered? Thank you.
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Wakita et al. showed that family-, genus-, and species-level analyses are appropriate to correlate the fecal microbiome and the fecal metabolome ( ). Even though the amplification of short 16S rDNA variable regions can result in the inability to determine the species-level with a high level of confidence, genus- and family-levels are still reachable and valid.
Meanwhile, due to the easiness of classifying sequences to phylum-level, the Firmicutes/Bacteroidetes ratio is frequently used in the scientific literature. However, the biological meaning of this is limited, especially if you are interested in the metabolome changes induced by diet. The popular index, Firmicutes/Bacteroidetes ratio, is based on the phylum level and was initially associated with obesity and certain health states. Interestingly, new data refute its validity (reviewed by Magne et al., ).
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Hi you all,
I'm looking for a not very expensive journal to submit our work related to microbial diversity in a beverage drink using an amplicon perspective. Any suggestion is welcome because I am lost!
Thank you in advance
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Food Microbiology, International Journal of Food Microbiology
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Want to construct the following type of phylogenetic tree to show the microbial diversity.
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Making a phylogentic tree is task 1 and annotating it is task 2.
It is not automatic and you have to do manual preparation for annotating the tree.
qiime and mothur are replaced by improved pipeline. Do not miss the chance to get look at the alternatives.
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What are the suitable software to analyze the raw DNA sequences (16S rRNA data ) for microbial diversity analysis ?
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please read about DADA2, QIIME2, Mothur, MG-RAST, Galaxy server, Unipro Ugene, BioEdit and choose according your need/expertise
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i would like to analysis/identify the microbial diversity at the ripening of passion fruit, and want to anlysis about which fugus, bacteria or microbe are present and which species.s
so which analysi should recommend ? as 16s, 18s and ITS ?
which one is suitable ?
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Definitely the 16S rRNA sequencing for detecting the diversity among the bacterial strains. For the determination of fungal diversity, ITS gene sequencing should be conducted as recommended earlier.
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First, how to isolate DNA from effective microorganisms? is it the more to genomic DNA isolation or metagenomic DNA isolation protocol?
Second, is the Bacterial 16s rRNA Amplicon Sequencing with Illumina 250 PE/ 300 PE strategy, suitable to study their microbial diversity?
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1. You can use either CTAB method or phenol-chloroform method for isolation of DNA from individual bacterial or archaeal strains and different kits, such as FastPrep DNA, DNeasy Power etc. are available commercially for extraction of metagenomic DNA from environmental samples.
2. To study microbial diversity, 16S rRNA based Illumina sequencing 300 PE is better option as compared to llumina sequencing 2500 PE
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I have sampled the roots of specific crop along with soil from four different areas of Sindh Province of Pakistan. Can you suggest me the technique to determine the microbial diversity in these samples please?
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Very important question
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I woultd like to study the microbial diversity of hypersaline water by PCR-DGEE followed by sequencing. Before this step I have sequenced the 16s rRNA gene of some isolated strains from this sample by using the following archaea specif pair of primers
A20F (TCC GGT TGA TCC TGC CG)
A1540R (GGA GGT GAT CCA GCC G)
Do I have to use this pair of primers in DGGE?
For the DGGE analysis of bacterial diversity I will use another pair of primers.
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Salma Mukhtar your answer is great
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Dear Members,
I am pursuing my PhD degree from vit university, india. I wish to apply for short term visiting fellowship (3-9 months) in different countries (except USA,UK, FRANCE, KOREA). My domain of research includes the study of microbial diversity in high background radiation area and their adaptive strategy. I passionately want to work in the field of radio ecology and bioremediation of radioactive waste which are similar to my research interest.
I look forward to any suggestion of research laboratory/ institutes/ universities related to my field of research.
Thank you all in advance.
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Greetings!
You have a wide scope of opportunities around the globe. I had come across some labs in Germany,
*DLR-Germany (You can apply for DAAD-overseas fellowship)
*European Molecular Biology Laboratory (EMBL) research centers (You can opt funding option from EMBL schemes)
I would suggest you to consider USA and France for short term internship programs since they have more funding options and has active research in the topics you are interested in. I shall be glad to give you further details.
Cheers!
Manobala
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Microbial profiling
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Thanks a million Simon and Bhaskar. That's an excellent breakdown of number of samples vs reads. I want to start with about 40 samples and not too sure about the diversity. Its seems like 5-6 million read is a good place to start with.
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I am in the process of a microbial diversity study of soil samples through 16S rRNA sequencing and overall microbiome analysis. Through this analysis, I have identified one single microbe that is of particular interest in the Chloroflexi phyla, and I would like to isolate this microbe from leftover soil samples and culture it for further study.
What would be the best method(s) to isolate the specific microbe from the overall soil sample, and then culture the microbe from there?
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Chloroflexi are rarely isolated and usually hard to work with. You can directly plate the soil on R2A agar plates or a dilute Mineral Medium supplemented with CMcellulose or make an enrichment broth (MM+CMC) and plate it on the same medium and R2A agar. Then look for small white rhizoid colonies. You might want to include some antifungals and anti-bacillus agents (those tend to spread a lot). This is a long shot, not much is known about this genus (or the whole phylum for that matter) so designing a medium specific for a particular genus is difficult.
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What are the classic papers about interaction effect of extreme drought and plant composition(diversity) in the grassland ?
Hello everyone! I'm looking for information about interaction effect of extreme drought and plant composition(diversity) in the steppe and I want to start reading the papers about this topic, especially its influence on the carbon exchange and soil microbial diversity.
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Dear Hui,
the publications of György Kröel-Dulay (https://www.researchgate.net/profile/Gyorgy_Kroel-Dulay) and his research group may be of interests.
HTH,
Ákos
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I would like to study the metagenomic diversity of actinobacteria associated with the marine sponges. In this context, I would like to use actinospecific primers to capture the complete actinobacteria phylum rather than using universal primers. Especially, would like to explore the rare actinobacteria like Salinispora.
I am aware the actinospecific primers given by Stach et al. 2003 ( SC-Act-235aS20, SC-Act-878aA19) may be useful in my case. However, as the primer read length is 640 bp it can not be used for Illumina.
Illumina can deliver less than 400 bp.
Blackwood et al., 2005 has also proposed Phyla specific primers. He has reported that the Actinobacteria Phyla specific primer "Act1159R" captures most of the actinobacteria they tested. Can it be useful in my case? Whether the Reverse primer alone sufficient to explore the actinobacterial Phyla?
Kindly, some one can provide me the write primer that will be helpful for me.
Thanks in Advance.
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They made a first Actinobacteria-specific PCR with a1.2 kb amplicon length, and then another PCR with universal primers to amplify the V3-V4 region of the 16SrRNA.
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To explore the soil microbial diversity, usually we analyse the alpha and beta-diversity of microbes. what is the significance of both indicators, what these indices explicit the true microbial picture? If only analysed alpha-diversity by 454-pyrosequencing, is that enough in data. If beta-diversity appear with no significant difference with treatments and control, can we exclude it from data ? If Only alpha-diversity has significant different between treatments, is that enough for data?
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Hi! Also, for the a-diversity you can do t-test and check the p value for evaluating the significanc.
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To explore the microbial diversity through High sequencing approach like 454- Pyrosequencing or Mi seq Illumina sequence, sometime the terms microbial community and microbial diversity may confuse, or look similar in meanings. Kindly precisely differentiate that...
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I think it should not confuse as they are pretty different in meaning. Fungal community is the presence of many types of fungi as a whole in a community/society. Fungal diversity is the extent of different species or subspecies present in that community. If the diversity is low, there are only few taxonomic categories present or if it is high diversity there are more number of taxonomic classes present. The broadness or narrowness of diversity means how closely or distantly the fungal taxa are related. If you think same concept in human population (just for example) a community is the people together, and diversity (lets say gender) on a category level is low if we consider sex of people as there will be only three functional categories. And if we consider (age groups of 5 years) age group as a functional unit, there will be 20 classes (if age is 100 years), in this case this is highly diverse community.
In case of microbiology, the genus level is commonly taken as functional class to evaluate the diversity in fungal or bacterial community.
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Hiya
I have around 30 samples of sequenced plant microbiomes from one location. I would like to find out if there is any correlation between how far the samples are away from each other and their overall similarity.
An idea is to create pairwise distance measurements between samples and plot them against similarity values.
1) Is it possible to get a similarity values (say between 0-1) for samples?
2) Does anyone know of a better/existing method for such comparisons?
Thanks a lot
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Additionally, if you are using phyloseq for the sequences data visualisation, you can have the physical distance information in the metadata file. While you plot PCoA or NMDS plots, you can have the physical distance factor in the plot command and it will consider the physical distance too. For better understanding, you can also add the arrows in the graphs which will elaborate the effect of physical distance on the samples and overall community.
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Hi,
I'm working on soil microbiology and I want to check the microbial diversity in the soil. so, I have 2 options,PE illumina or 454-Pyrosequencing. I want to ask that which technique is better to use and why is this so?
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Ralstonia solanacearum, a harmful plant pathogen of warm climate zone, worldwide plant quarantine organism is often found in irrigation water at more cold areas (Turkey, Poland, Russia) without causing plant diseases in fields around the isolation site. It is long-surviving in soil bacterium in tropical area. I see the only possible explanation - association between Rs and some soil/fresh water algae (like done by Pseudomonas syringae).
So, can Rs go to North with its potential host under progress of the Global warming? Any other ideas?
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Rs has been recently reported in glasshouses on ornamentals and vegetables (hydroponics) in European countries. Can it be a source for field infection? Drainage water from greenhouses often runs strait to local rivers...
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I have a rarefaction curve of two samples no of tags observed vs OTUs observed
Can any one explain or suggest some literature for further reading?
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Hi Vijay,
Rarefaction curves can give you an ideia of microbial diversity looking to the form of the curve. Traditionally they have been used to know if the throughput of your samples was high enough to sample all the richness(=microorganisms) present in the your samples. Therefore, as it was said before, they are more suitable to richness estimation. Although there are more proper metrics, such as Chao1 and Faith's PD (alpha diversity), unweighted UniFrac (beta diversity). Nevertheless, image that you have two samples with the same number of OTUs sampled at some depth (let's say 40,000 reads). You can look to the form that the two curves take in order to get some insights about the diversity (weighted richness). For instance image this scenario, if curve A has the same number of OTUs (=richness) as curve B at 40,000 reads (subsampling depth), sample A has a community more evenly distributed than B. Why? Because it requires to subsample fewer number of reads to get higher number of OTUs/taxa/microorganisms meaning that these have, probably, equal or similar frequencies.
I hope this helps.
Cheers,
António
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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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I am working on microbial diversity and planing to send samples for Next Generation Sequencing (NGS); Which hypervariable region of 16S rRNA gene will appropriate to target most of bacterial taxa present in seawater.
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Hi Rajeev,
This depends a bit on what you need from the study. The V4 region has (probably) the closest to universal primer set and it has the advantage that you can completely sequence through in both directions (on a MiSeq) the amplified region of 254 base and perform sequencing error correction (I do this in the Mother pipeline). I haven't used it, but there seems to be a lot of positive talk about the use of DADA4 in the Qiime package for helping go deal with the issue of sequence error. You might want to check out the recommended protocol from the earth microbiome project, http://press.igsb.anl.gov/earthmicrobiome/protocols-and-standards/16s/
I use this for a variety of sample types. Again I have to stess that there is no perfect primer set/target region, but V4 has worked well for many, including me.
Good luck,
Frank
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Good evening respected teachers/scholar/researcher, I hope you are fine and doing well, I am Ph. D student in china, working on current project "Sustainable vegetable production in china" in College of Horticulture, Northwest A&F University, China. I analysed soil microbial diversity by Illumina MiSeq platform. i have data in figure form, some of them i couldn't understand How to interpret it well especially "Heat map analysis" ? my capabilities are very limited in soil bio diversity and microbial ecology. So i need assistance belong to bioinformatic or soil microbial ecology experts for my figure illustration? Details about these figures are in attached file. I really thankful if someone help me in this regard.
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The colors suggest a positive or negative relation between the environmental parameters and the abundance of the different classes/genera. 
The top dendrogram shows which environmental parameters have the most similar responses. The side dendrogram shows which classes/genera are behaving most similar.
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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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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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Year 2015 is being celebrated as International year of Soil.As we are  all aware soil is foundation to agroecosystems and base for agricultural production.Soil is living system ,store house for carbon and microbial diversity, biochemical laboratory, filter, decontaminant. By providing ecosystem services, food security, climate resilience,supporting animal and human health,soils are serving the humanity.So,what can be done for safe ,secure  and sustainable use of soil in future.
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Dr. Ewald Schnughas good and justified concerns about urbanization agri lands. But to de-urbanize may be not a cost-effective and time saving option. Rather take care in future may be more practical option to save agri lands for sustainable food production.
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Is there an effect of altitude on soil microbial biodiversity ?
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temperature and pressure will be gradually depleted in line with increase of altitude.  it will directly impact to the metabolism of microbes.  microbes are sensitive to environment changing.  indirectly, low temperature will inhibit decomposition of organic compound then will deplete population of heteretrophic microbes as well.  
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I am looking for microbial  diversity pattern in soil samples from different altitudes through DGGE. I used FastDNA™ SPIN Kit for Soil DNA extraction but I am getting lot of brownish color in the final eluted DNA. Can anyone suggest me a method to get rid of this problem, as this is hampering further downstream process.
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possibly the colour is caused by humins  which often purify with dna. You could try ethanol precipitation ( with glycogen added if you do not have very much dna as a co precipitant then do an OD260/280 to ascertain dna purity Dusan makes a good point that when you do have interfering substances sometimes using less samples allows a PCR to work rather than using more and having more interference. Having said that any substance that absorbs at 260 will make you think that you have more dna than you actuallu do have
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There are so many microbial diversity investigations using high-throughput sequencing on variety of natural environments, e.g. land soil, fresh and salt water, sediment etc. Some of them sampling their samples in a site, and then mixed them for one sample to do the next study. I want to know if this kind of sampling method are scientific and rigorous? And how to do a scientific and rigorous sampling when we do microbial diversity investigation in natural environments?
Thank you!
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Hi Wei
Your sampling should reflect the research question you want to ask,  As you know, soil is full of microsites, each with is own microbial diversity. So depending on what you wish to know you have to sample accordingly. It is alo necessary to validate your experimental methods to ensure that they are giving you a true representation.
Best wishes
Chris
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I would like to calculate diversity index from DGGE banding patterns.
Can the DGGE band strength/intensity actually be estimated visually as described by Gafan et al. (2005)?
Anyone knows any papers that make use of the same approach?
Reference:
Gafan, G. P., Lucas, V. S., Roberts, G. J., Petrie, A., Wilson, M., & Spratt, D. A. (2005). Statistical analyses of complex denaturing gradient gel electrophoresis profiles. Journal of clinical microbiology, 43(8), 3971-3978.
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 Hi Muhammad,
I think the authors chose visually estimation maybe because they had no better methods at that time. The software, such as Quantity One, should be not such popular like today.  In my private opinion, I think the software-based analysis would be much more sensitive and  accurate than our eyes. So I recommend that you should better use software (e.g. Quantity One) to analyze your DGGE bands.
regards,
Guangshan
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Literature findings are contrasting and published cytograms are not convincing.
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Stefano, 
As you have found the literature has contrasting reports. I think it will depend on what you are trying to do, if you have a large virus that is clonal then it probably possible to optimize conditions for accurate counting. For a population of viruses of different sizes and genome sizes such as in natural seawater samples , I am skeptical that you can accurately count all viruses within a sample.  
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Are there any latest molecular tools beside DGGE, TRFLP and Illumina to assess microbial diversity of environmental samples with ease? If yes kindly suggest..otherwise which among three is better suited for the same?
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Hi Upendra,
In my opinion, other than these three, you can also construct clone library to study the microbial diversity.
Among these four techniques, TRFLP requests least efforts in terms of both experimental part and data analysis part. It gives quantitative data on the community structure but it is hard to tell who are the key players in the community.
DGGE is a bit complicate when doing the experiment, while the data analysis is easy. The data is not very quantitative as you are comparing the brightness of the bands. You can then cut the bands out for the sequencing which shows you the key players in the community.
Construct clone library is easy in terms of doing experiment. The data analysis part is straight forward. The data will not be quantitative but you will know the species in the community. The whole process may be a bit costly too depends on how many colonies you plan to sequence.
Illumina is easy in terms of experimental part then you need more efforts to analyze the data. Illumina would give the most information. The data will be quantitative and tell you the taxa information. 
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Hi,
I´m studying microbial community development in time (using 16S sequencing) and would like to tell what taxa are changing in time and in what way (significantly increase, decrease...). I have an OTU table, what analysis is advisable?
Thx!
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This is difficult to address in such general terms. The answer really depends on the exact structure of your data, the experiment, the specific research question and probably more. Get your data into R, familiarize yourself a bit with ecological statistics, and packages like phyloseq & vegan that offer many useful tools. Assuming you have a relatively large, Next-Gen Sequencing dataset, a useful first stop could be to work on an ordination (e.g. Non Metric Dimensional Scaling, NMDS). (There will be data cleaning and normalization steps to go through before you can do this though). This will give you an overview over the overall change of the community with time and you can create biplots including the correlation of the OTUs with this overall trend. This will allow you to determine a set of candidate OTUs that are associated with the community change. You can then extract the timeseries of abundance data for these OTUs and study them in greater detail. If this is still a large number of OTUs you can subject this subset to e.g. cluster analysis, to see if there are different types of "typical" time dependet patterns (e.g. increase, decrease, spike at a certain time, etc.). You can also plot OTUs individually against time. You can then test for linear trends (regression), or significant changes between defined periods (e.g. all early against all late timepoints, using a T-test) or any of the more elaborate techniques of time series analysis. You can also sort the list for the most abundant types, or the largest differences over time, to find particularly interesting OTUs. Take some time to explore but always keep your research question in mind.
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I am growing TG1 cells on 2XYT media without any antibiotic and getting two types of colonies, one is opaque and another one is transparent . i dont know which one is actually TG1. Can anyone help me ?
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I have streaked my stocks and there is only mucoid colonies.
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Dear all, this is a 40X magnification field of view. Never seen something like that before, so couldn't recognize. Any ideas? Thanks!
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It seems like a microalgae.
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I have extracted genomic DNA from 4 single lesions derived from one rust isolate. By PCR amplifying elongation factor gene, I saw different band pattern on the gel. Can anybody let me know whether even spores derived from Single Spore Isolation are still genetically different?
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Hi Peng
Which rust are you working with, and at which stageof its life cycle? If you work with teliospores, these should be all different as they derive from sexual reporoduction. Other stages ( like uredia) are derived from asexual multiplication, so you can assume greater genetic homogeneity.
Best regards
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Unknown microorganism surviving 80 degrees of heat treatment
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You can go for 16S - however you will only end up at genus level with Bacilli of the cereus group - their 16S is virtually completely identical and therefor a species level identification will not be achieved by most molecular standard techniques
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According to the latest list, how many species are recognised under the genus Vibrio??
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The best place to look for such information is "The List of Prokaryotic Names with Standing in Nomenclature" (also known  as Euzeby's list). For Vibrio see http://www.bacterio.net/vibrio.html.
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I would like to know what is common practice in countries outside The Netherlands. Do you use a name like Dolichospermum for planktic Anabaena?
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Hello Maria. My main reference is Komarek's Süßwasserflora von Mitteleuropa, book 3. I have been working for many years in the US but was trained on algae taxonomy in France. I do use new genus names such as Dolichospermum and Cuspidothrix.
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Is there a website,database or a manual where the CDMs are listed?  I have been digging through various papers from 1960s, but may be there is an easier way. Thanks.
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Thank you Robert. Those are good ideas !
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I am looking into the relationship of Actinomycetes in different habitats.
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Soil rich in organic matter is most suitable habitat for the isolation of Actinomycetes
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I want to study the molecular diversity and homogeneity of bla-CTX-M genes in E. coli isolates from different localities in relation to their phenotypic characteristics, such as antibiotic resistance to various drugs, based on some molecular techniques. As, I am not a molecular biologist, therefore, I need guidance in this context. Thank you very much.
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Dear Tariq Ali,
For study of molecular diversity of a gene in different E. coli isolates, you can go through PFGE or MLST (Multi locus sequence typing). We already studied on diversity of blaCCTX-M-15 in E. coli.  the article was published in Microbial Drug Resistance (Impact Factor: 2.49) and I have attached herewith. Hope it will be use full to use.
Good Luck.
Regards,
Dr Anand
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I would like to study on spatial distribution of soil organic matter fractions [such as dissolved organic carbon (DOC), dissolved organic nitrogen (DON), particulate organic carbon (POC) and particulate organic nitrogen (PON)] and also microbial respiration, microbial biomass C and N in mono-species 20-year old plantations of alder (A. subcordata C. A. M.) and oak (Q. castaneifolia C. A. M.), planted at a spacing of 2×2 m, located in northern Iran. The stands were never fertilized. The study areas show very similar climatic conditions and management practices. The experimental plots were located at an altitude of 300 m above sea level. The area is on flat and uniform terrain with low slope (0–3%).
Unfortunately I didn’t find any reference about soil sampling design. I have two questions about this project:
Question 1: How many soil samples (the minimum) are enough for study on spatial distribution of soil organic matter fractions and microbial features for each of these stands?
Question 2: Which sampling design is the best for soil sampling?
May you please help me about these questions? Do you have any references about these to present?
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The number of samples depends on your experimental design and the heterogenity of your area. Usually the number of samples required is  if the carbon content is high and there is not a really good answer. 
We have been usually taken 10 samples per plot. This is too much if you have a well replicate experimental design (many blocks and plots) and might not be enough if you have a high carbon soil (not very probable in Iran I think). 
In sampling it might be good to go for a standard depth below the humus layer and take the humus and litter layer separately. The reason is that humus accumulates on the mineral soil and will falsify your samples.  Random sampling within a plot might be avisable. But you might also go for different distances from the trees.  
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What possibles outcomes or conclusion can be drawn from comparative taxonomic/functional diversity analysis of different hot springs on the basis of pH, Temperature and locations?
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What kind of metagenomic approach you are using? structural/functional?
in functional-comparative analysis you may prospect that what kind of genes were more active in stress(high temperature) conditions; moreover you may link the diversity to presence of various metals abundant at that particular region...
pH of most hot springs(as much as i know) lie in acidic region but here are few with pH in alkaline region; you may compare these 2 for difference in structure and dynamics of 2 sites...which specific genra were dominating 2 niches..
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When I studied the microbial diversity, I wanted to choose a good method for the relationships between microbial diversity and environmental factors. So I found some relatives. I thought db-RDA and CAP are good methods for my study, but I don't know the difference between them. Can you give me some advices. Thanks!
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Have a look on the article from Ramette 2007 which should help you to understand more about db-RDA and CAP which both correspond overall to a RDA and CA respectively. Below are citations from this article about db-RDA:
db-RDA: “When the data set consists of a matrix of distances between objects, distance-based RDA (db-RDA; Legendre & Anderson, 1999) can be applied to determine how well additional environmental parameters can explain the variation among objects in the matrix. The technique first applies a PCoA on the distance matrix to convert it back to a rectangular table containing rows of objects by columns of PCoA coordinates. Those new, uncorrelated coordinates thus correspond to synthetic ‘species’ variables that are then related to additional environmental parameters using a
classical RDA. For instance, db-RDA was successfully used to determine how the variation in matrices of genomic distances among environmental strains could be explained by factors such as soil parameters, host plant species, and spatial scale, each factor being taken alone or in combination”
CAP: is a canonical analysis on the principal coordinates for any resemblance matrix, including a permutation test. CAP takes into consideration the structure of the data. So, it is more likely to separate your different levels if there is no strong difference and is good to show the interaction between factors.
db-RDA “can be applied to determine how well additional environmental parameters can explain the variation among objects in the matrix”. In contrast, CAP do not try to increase the explanation of the variance with other parameters, but only perform correlations. I think this is the major difference. Overall, the choice of the “best” method depends on what you want to do and show, and there is not necessarily a unique answer but better to try different options. See this RG question
Reference:
A. Ramette (2007) Multivariate analyses in microbial ecology, FEMS Microbiology Ecology, 62, 142-160
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Hello,
I am working on exploration of hidden microbial diversity using shotgun sequencing approach.
I need to analyze my data using PAST.
I installed PAST in my PC drive, I read the manual also, but I'm still facing problem for transfer MG-RAST tsv. file from excel into PAST. Help me.
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Hello coleague
Well, I always have transfered Excel sheets into PAST without problems merely using Ctrl+C/Ctrl+V. I particularly don't know how MG-RAST tsv files looks like, because I don't work with this kind of analysis, so that is my question: do you put the information you need in an ordinary Excel sheet, I mean, rows and columnsl or the arrangement of data is different from that?
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The effects of nitrogen addition, and more widely fertilizer, on soil microbial (bacteria, archaea and fungi) diversity and activity have been investigated, but the understanding of the effect of potassium alone (e.g. in the form of potassium sulphate) on soil microbial communities seems to be more limited. Are we expecting a negative/positive direct or indirect effect (or no effect?) on soil microorganisms, due for example to a change in soil pH or in plant growth (reduction in N uptake, decrease in roots exudate)?
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Aimeric , very intelligently framed question . Having given a soil without any micronutrient constraint, application of  K  will induce an improvement in uptake efficiency of both N and P , and this  will  impose cascading effect on proliferation  of soil microbes by and large . however , certain K-solubilizers or silicate solubuilizers could further expand their number by metabolizing the additional K released from microbial action . Needless to say ,  effective microbes are biggest sink for nutrients N, P, and to a lesser extent  K  . Such solubilizers  will display much better resilience either under salinity or under any other abiotic stress,  as rightly opined by Alii.
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G+C ratio role in novel taxa identification.
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Dear Krishna,
Have a look at the following papers.
1.On the molecular mechanism of GC content variation among eubacterial genomes
Hao Wu, Zhang Zhang, Songnian Hu and Jun Yu,TRENDS IN ECOLOGY & EVOLUTION · MAY 2005
2.Taxonomy of Lactobacilli and Bifidobacteria by Giovanna E. Felis and Franco Dellaglio,http://www.biology-direct.com/content/7/1/2
Good luck!
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Dual/multiple inoculation of rhizo-competent microbes  is now almost a common practice, irrespective of crop and soil type. In the process , there has been growing concerns about exploiting the rhizosphere microbial diversity , in order to develop the crop specific microbial consortium . We have developed a microbial consortium for citrus . The developed microbial consortium  consists of five microbes viz., Bacillus polymyxa, Pseudomonas flourescens, Trichoderma harzianum, Azotobacter chroococcum, and Bacillus mycoides , isolated from rhizosphere of  citrus grown on  smectite  rich  alkaline black clay soils . Their complementarity test ,  shelf life , response in nursary , and in field ( Under INM mode ) have comprehensively established the excellent performance of developed microbial consortium .   I call upon my esteemed colleagues to express their opinion as how to further improve the efficacy of microbial consortium . We now intend to carry out further studies with respect to following:
# There has been some antagonistic effect of Pseudomonas on the population of Trichoderma   during the complentarity test , what shall be our strategy to overcome such relation  in the context of long shelf life of microbial consortium ?.  
# What  could be the probable options to use cheaper growing media  to lessen the cost of the microbial consortium ?.
# Is it possible to  improve the nutrient value of microbial consortium by supply some additional nutrients into the growing medium ?  .
# How can we extend the shelf life of microbial consortium ?.  
# Do we need to develop a different  microbial consortium for citrus,  if  grown on a different soil type ?.
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Dr Singh , few days back , in some of  RG questions , I responded by saying do we have some indicator microbes specific to specific soil conditions in order to judge the general health of the soil microbiologically . Likewise we have probably yet not attempted to analyse the AMs diversity of different crop rhizopshere , annual versus perennial  fro example. Rhizosphere of one crop to another crop . Can we sythesize a consortium of rhizocompetent microbes including AMs using a process called rhizosphere  hybridization .
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Microbial abundance of soil is normally  considered  synonymous to higher bio-availability of nutrients , and hence soils are biologically more responsive to any management input(s). The soil microbial diversity in a given soil is claimed to undergo transformation in response to metabolic requirement of any crop being grown on a specific soil. In this background , I call upon my esteemed colleagues to throw some valuable comments  on the following issues:
# How does a stable microbial diversity  in a given soil undergo reorientation in response to heavy metal accumulation/contamination/.
# Do we expect a definite change in structural and functional composition of microbial diversity in the light of contaminated soil vis-a-vis uncontaminated/normal soil ?.
# Which group of microbes is  considered more sensitive ( Prevalence of one species over other ) to such disturbances in soil microbial environment?.
# What kind of implications of contaminants  , do you anticipate in the context of bioavailability  of nutrients in soil ?.
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There will be surely two microbial niche , one for contaminated soil and another for normal soil depending upon the type of heavy metals. But , from such contaminated soils , there is a possibility to isolate some microbes well adjusted to such adverse conditions as a part of microbial remediation of contaminated soils.
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I want to quantify the microbial diversity in the rhizospheric soil of paddy field. kindly provide me the standard protocol with references.
Thank you
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Please read the textbook, "Practical Biotechnology" by Sadashivan
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EcoSim software can be used to calculate the checkboard score with species absence/presence pattern in order to evaluate species interaction. However, in a community, speices density is going to be an important factor that affects the interactions between species, especially in microbial systems.  Is there any robust tool (null models) to handle microbial abundence data to indicate the direction and extent of the interacting process? 
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You can calculate the Probability of Interspecific Encounter (PIE), which is an alternative measure to compositional dissimilarity (Hurlbert 1971):
Other useful references:
PIE is a simple, probabilistic measure, of the –potential– interaction between species. It is not spatially explicit, meaning that PIE is calculated WITHIN a given sample or inventory. However, you can calculate co-dominance (F), which is the probability that two individuals from two samples belong to the same species (Chave and Leigh 2002): http://chave.ups-tlse.fr/chave/chave-tpb02.PDF
Note that F = 1 – PIE at the inter-sample level, i.e., in a triangular association matrix between each pair of plots.
Chave and Leigh 2002 include a neutral model with 'null' expectations. You can develop your own null models under different scenarios of species aggregation and diversity.
I do not think that beta-diversity measures that take into account the species' abundances are the same thing as a measure of the (potential) interaction between species, or the most direct approach to species' density.
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I am looking for good an most of all recent estimates of bacterial diversity in different ecosystems, i.e seawater, freshwater and soil. 
The two numbers that are cited everywhere are 20 000 species per litter of seawater and 10 000 species per gram of soil. The first number comes from Sogin et al (2006) and is based on an extrapolation with the Chao1 index. They observed about 6000 OTUs clustered at the 3% level. The second number come from Gans et al (2006) who cites Torsvik et al from 1990!
Given the development of NGS sequencing, there must be better estimates around than these 9 to 25 years old paper. 
Do you know of any?
Sogin, M. L., Morrison, H. G., Huber, J. A., Mark Welch, D., Huse, S. M., Neal, P. R., et al. (2006). Microbial diversity in the deep sea and the underexplored “rare biosphere.” Proceedings of the National Academy of Sciences of the United States of America, 103(32), 12115–12120. 
Torsvik, Vigdis, Jostein Goksøyr, and FRIDA LISE Daae. "High diversity in DNA of soil bacteria." Applied and environmental microbiology 56.3 (1990): 782-787.
Gans, J., Wolinsky, M., & Dunbar, J. (2005). Computational improvements reveal great bacterial diversity and high metal toxicity in soil. Science, 309(5739), 1387–1390. http://doi.org/10.1126/science.1112665
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Despite the advances in NGS, we remain a long way off to know the bacterial diversity in soil, and surprisingly there is not many studies that try to tackle this difficult (still impossible at the moment?) question. Roesch et al., (2007) estimated between 2000 to 10,000 OTU per gram of soil, similar values than Torsvik et al (1990), but lower than Gans et al (2005) 10^7. Schloss and Handelsman, (2006) give the number of 2000-5000 of OTU.
 The recent Opinion article from Prosser (2015) give the following values: “Molecular studies (those that describe microbial taxonomy on the basis of the 16S rRNA gene) indicate that up to 1 million different bacterial and archaeal species are present in 10 g of soil, in the context of approximately 1 billion microbial cells”, citing most previous studies. It should be kept in mind that despite the advances of NGS, nobody has yet sequenced all the bacteria in a gram of soil. Again, Prosser (2015) remind us this fact: “so complete coverage of a soil metagenome is not usually obtained; for example, in one study, it was shown that deep coverage of the majority of a soil community was not achieved, even with 300 Gbp of sequence data”, citing the study from Howe et al. (2014).
 If you are interested in reading more about this debate of bacterial diversity in soil you can read Delmont et al. (2011) and several articles from Curtis (Curtis et al., 2002; Curtis and Sloan, 2004, 2005)…
Keep in mind 1) the diversity of soils, 2) the heterogeneity of soil at the microscale, 3) the changes in soil properties with soil depths 4) and over time. All these characteristics will influence the richness of bacterial community (and other microorganisms) in soil and their estimation.
Sorry I do not have numbers for sea or freshwater, although Zhou et al. (2015) mentioned some studies for diverse ecosystems.
Looking forward any point of view and articles on this subject!
References:
Curtis, T.P., Sloan, W.T., 2005. MICROBIOLOGY: Exploring microbial diversity--a vast below. Science 309, 1331–1333. doi:10.1126/science.1118176
Curtis, T.P., Sloan, W.T., 2004. Prokaryotic diversity and its limits: microbial community structure in nature and implications for microbial ecology. Current Opinion in Microbiology 7, 221–226. doi:10.1016/j.mib.2004.04.010
Curtis, T.P., Sloan, W.T., Scannell, J.W., 2002. Estimating prokaryotic diversity and its limits. Proceedings of the National Academy of Sciences of the United States of America 99, 10494 –10499. doi:10.1073/pnas.142680199
Delmont, T.O., Robe, P., Cecillon, S., Clark, I.M., Constancias, F., Simonet, P., Hirsch, P.R., Vogel, T.M., 2011. Accessing the soil metagenome for studies of microbial diversity. Applied and Environmental Microbiology 77, 1315–1324. doi:10.1128/AEM.01526-10
Howe, A.C., Jansson, J.K., Malfatti, S.A., Tringe, S.G., Tiedje, J.M., Brown, C.T., 2014. Tackling soil diversity with the assembly of large, complex metagenomes. Proceedings of the National Academy of Sciences 111, 4904–4909. doi:10.1073/pnas.1402564111
Prosser, J.I., 2015. Dispersing misconceptions and identifying opportunities for the use of “omics” in soil microbial ecology. Nature Reviews Microbiology advance online publication. doi:10.1038/nrmicro3468
Roesch, L.F.W., Fulthorpe, R.R., Riva, A., Casella, G., Hadwin, A.K.M., Kent, A.D., Daroub, S.H., Camargo, F.A.O., Farmerie, W.G., Triplett, E.W., 2007. Pyrosequencing enumerates and contrasts soil microbial diversity. The ISME Journal 1, 283–290.
Schloss, P.D., Handelsman, J., 2006. Toward a Census of Bacteria in Soil. PLoS Comput Biol 2, e92. doi:10.1371/journal.pcbi.0020092
Zhou, J., He, Z., Yang, Y., Deng, Y., Tringe, S.G., Alvarez-Cohen, L., 2015. High-throughput metagenomic technologies for complex microbial community analysis: open and closed formats. mBio 6, e02288–14. doi:10.1128/mBio.02288-14
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Currently, the co-occurrence network were built base on correlation, regression, or other statistical methods. However, these results are ambiguous for understand the interactions. Is there some other method to identify the interactions in microbial network? 
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You pose a good question - because co-occurrence networks are just that - and the assumption that co-occurrence translates to a a real ecological relationship is not necessarily strong. Clues (but not proof) can come from the phylogenetic assignments (e.g., a positive co-occurrence with a dominant phylotype with a known physiology such as N-fixation could be inferred as a positive trophic interaction), but real proof would only come with experimental studies (good, old-fashioned co-culturing experiments, for example).
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Normally for pure bacteria culture isolation people refer to do 16s RNA sequencing and they get phylogenetic tree, in my case i have mixed of microorganisma in a solution, I want to know the microbial diversity with phylogentic tree in my solution. For that what kind of DNA sequencing i have to refer.
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If you need to identify the prokaryotic microbial diversity in a sample for sure you will get much more information using NGS techniques, after extracting DNA and amplyfying 16S rRNA genes using different primers that are suitable for bacteria and archaea. Illumina is nowadays the most used technology, although the choosen sequecing technology would depend on the type of results you need and the budget you have (now NGS sequencing is getting cheaper and cheaper). Most sequencing companies also offer the bioinformatics work to a certain extent, but further you will profit more the data if later you do your own bioinformatics work for refinement and search of specific issues.
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I am studying microbial diversity from environmental samples. I am using v4 of 16S rRNA gene sequenced with Illumina MiSeq (paired-end). Quality control and statistics were done using Mothur package from which BIOM file was generated and imported in MEGAN5 for visualization. From my OTU file, Proteinclasticum is the most abundant, BUT when get bar plots from MEGAN5 I can not see them most abundant OTU? What could be wrong?. Thanks
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Not much to go on but I would suggest having a go at visualisation in QIIME or phyloseq to see if you get a similar result. If you still have the problem you can have a look at the Mothur forum, particularly if it is a problem with how you generated the Biom table.
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I have Isolated and identified many enteric, bacillus and nonfermenters from Bovine manure during decomposition process on the basis of morphological and biochemical characteristics. Now I would like to go for clostridium, how it can be possible? and what protocols should be followed? 
Thanks in advance!
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You can use Robertson's cooked meet medium or Thioglycolate broth for anaerobic organisms growth. Cooked meet medium contains heart or liver chopped pieces which inhibits the growth of aerobes and make condition anaerobic like clostridiums. Thioglycolate do the same thing, makes the condition anaerobic and enhances anaerobes growth conditions.
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I have isolated some bacteria and I want to identify them at stain level. I have determined their 16s RNA sequences and after BLAST they showed the similarities  with many bacillus bacteria. The results are in attached picture. So what I need to do next to find the name of these bacteria at strain level?
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Hi Jamil,
Just before you continue, ensure that your sequencing data is clean and there is no errors in your sequencing data. Looking at the image you have uploaded, your sequence is ~99% similar to the nearest phylogenetic neighbour according to blast. Chances are that your isolate is most likely the organism blast is suggesting. Note however that anyone can upload sequences to blast, including partial sequences, new strains, etc. and as such blast is not always the best website to use. Might I suggest that if you want to search type strains, obtain sequences, etc. for phylogeny you could try the Ribosomal Database Project: http://rdp.cme.msu.edu/seqmatch/seqmatch_intro.jsp
Simply paste your sequence, and change the options to the following..>
Strain: Type
Source: Isolate
Leave the rest as default. 
This should load a screen with the nearest closest type relative, and from there click "View selectable matches"
This will bring up the type strains, which will provide you with less cumbersome information. You can also take the sequences and generate trees with the data. Feel free to message me if you require additional help.
Hope this helps :) 
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I am currently analysing 16S amplicon data of microbial populations from environmental samples, and trying to apply network analysis to explore OTU-OTU and OTU-environmental properties relationships. At the moment I have successfully created OTU co-occurrance networks using the Cytoscape plugin CoNet, and I am now trying to move forward to the ecological interpretation of the networks. Since I wasn't able to find some good references regarding ecological interpretation of the networks shape, and interpretation and use of network properties, Can anybody suggests some review/articles/books or other resources type covering the use of network analysis in (microbial) population studies?
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