Science topics: ChemistryGeneral BiochemistryMetabolismMetabolomics
Metabolomics - Science topic
Metabolomics are the systematic identification and quantitation of all the metabolic products of a cell, tissue, organ, or organism under varying conditions. The METABOLOME of a cell or organism is a dynamic collection of metabolites which represent its net response to current conditions.
Questions related to Metabolomics
Metabolomics has emerged as an invaluable tool for prognostic and diagnostic purposes, last in the cascade of others OMICS -genomics, transcriptomics, and proteomics. Omics training usually covers experiment design, data generation, and collection, data preparation, data analysis, and the last but not the least - data interpretation.
At the end of this meticulous energy, time, and financial-consuming path, it might be totally none sense to fail to put your results into the broader biological context.
For those like me that have never been trained to interpret metabolomics data, how can we make sure to not miss important points? Is Basic knowledge in Biochemistry, Physiology, or physiopathology of the disease of your interest, enough to harness the full potential of metabolomics technologies for biomarker screening u.a?
I would like to discuss with experts out there, the most important assets for a right and successful data interpretation of metabolomics data.
Thank you for sharing your experience in the Metabolomics journey as well.
as my question already indicates I would like to do some multivariate analysis of my proteomics data as I have multiple characteristics in my samples. I have successfully used MetaboAnalyst for multivariate analysis in metabolomics approaches. Do I have to expect some drawbacks by using MetaboAnalyst for proteomics data or is there an easy tool such metaboAnalyst for proteomics data?
Thank you for your help!
Heavy metals stress and their responses in plants through metabolomics approaches
What are the widely used methods to study intracellular metabolomics of E coli ? Are there any softwares available to exclusively analyze E coli Metabolomics data?
I'm looking to find molecular weights from mass spec experiments to identify compounds. Is there a database aside from Human Metabolome Database HMDB)? I am coming across molecular weights that don't appear in HMDB.
I used LCMS to detect metabolites and after a PCA plot was generated, I noticed that there were some sample outliers. What could be the cause of this?
I have some raw data in mzML form. Can someone please share with me a step-by-step guide on how I can use the MetaboAnalyst 5.0 platform to do my metabolomics analysis?
More so on how to run PCA analysis, PLS-DA, fold change comparisons, pathway analysis and comparisons etc
Dear colleagues, I'm currently writing my thesis on metabolomic differences of root development using algae-based biostimulants and I just ran into something weird.
I've grown modified strains of Arabidopsis using YFP and GFP to be able to measure simultaneous differences of expression of two different genes.
Everything went smooth up to the point of measuring of fluorescence. GFP was measured just fine, but YFP showed very fast declining brightness as the photos were being taken. It took about a minute from the moment the light was turned on to the moment the first picture was taken, and maybe 10-20 seconds in between each photo. I see the light diminishing with each picture and my result are not (and obviously cannot, until I sort this thing up) conclusive.
I've searched everywhere for evidence of reduced half life of the protein but it actually should be performing better than GFP, according to evidence.
Is there something very obvious i'm missing? or could this be related to something very specific like small changes in structure?
Thank you very much for your help.
I have full access to several metabolomic (metabolite concentrations) and transcriptomic databases (FC and pvalues). I would like to integrate all these info in one to obtain not only DEGs and metabolite boxplots but pathways and tissue/cell type information. I'm stuck searching for free software or friendly R packages other than mixOmics. Any idea?
Actually, I analyze my metabolomics data from LC-MS source (mzXML) and get a list of compounds with their mass, retention time, and polarity but no names or identifiers for many of them. Please, what tools can I use based on this information to find metabolites expressed here?
Hi, I am wondering whether I should purchase the pure substance or the salt (sodium or chloride) as standard for my LC-MS analysis in metabolomics. Any recommendations would be greatly appreciated!
I just started to use GCMS (8890gc 5977b gcmsd). I want to study human serum metabolomics. But I couldn't get good peaks so far. I keep changing GC and MS parameters but can't get good peaks. Could somebody help me with the oven temperature? I don't know which temperatures I should use for my method.
I did a metabolomic study, where some of my compounds are novel and have high production in one of my mutants. I have its m/z ratio. Can I identify this compound solely based on this ratio? I understand the ratio could be the same for other similar compounds. How do I determine what this compound is? Any help or path would be greatly appreciated.
I run the samples same group in two batches with quality control samples so it is showing batch effect. How to correct the batch effect?
How to prepare the sperm for metabolomic analysis in LCMS/MS
How can you say leaves are fresh in terms of its moisture content? Is a 100% moisture content possible? Does it mean that plant leaves that were harvested and subjected right away to IR moisture balance will give us a result of somewhere near 100%?
On the other hand, does "dried leaves" have specific moisture content values to be regarded as "dried" e.g. moisture content should be below a certain percent (10%).
For reference, I am studying Cymbopogon citratus leaves.
I am a graduate student at UC Davis trying to submit samples for complex lipidomics. Our metabolomics core facility does offer this but the turn-around time is 4-5 months, so I am looking for options with a shorter turn-around time. Any advice would be greatly appreciated.
in ordre to An Explorative Study of Vinegar Metabolomics Using GC-MS, I have not find the same column (Zebron ZB-1701 (Phenomenex, Torrance, CA, USA), 30 m ˆ 250 µm (internal diameter) ˆ 0.15 µm (film thickness), with a 5-m guard column),
but the supplier offered me other columns
their description is on the attachments to this message
I want to use AMDIS, the software needs msp to operate, can someone help me?
Say you are measuring the concentration of metabolite of interest (MOI) using fluorescence detection. The MOI concentration the one and only sample is unknown, say, u mg/L.
By adding extra MOI at defined concentrations to the same sample, you have a series of fluorescence readings as follow:
Concentrations -- Fluorescence readings
n mg/L -- Reading 1
(n + 15) mg/L -- Reading 2
(n + 30) mg/L -- Reading 3
(n + 60) mg/L -- Reading 4
(n + 120) mg/L -- Reading 5
As MOI concentration increases, fluorescence increases.
What would you do to obtain the value of n?
I am new to metabolomics and have never used GC-MS. I am analyzing the common compounds (nothing specific) present in the cell-free supernatant of Lactobacillus, and I do not know if I can submit my sample without further processing. Thank you for any help!
Hi, am new to metabolomics, can i use GC-MS to characterize volatile of milk? or there is a better methodology.
I have a very small knowledge in bioinformatics, and part of my research project is based on analysis of proteomics and metabolomics data. However, I am struggling to find some resources (webinars, courses, websites, ...) to help me get started with understanding and analyzing my data. I would appreciate it if anyone can give me some suggestions.
Once the metabolite concentrations are known which program(s) may be useful to interpret data in terms of metabolic pathways?
We are currently conducting a research project that focuses on organ rejection. For this purpose, we have taken blood samples of various patients, who have received an organ transplant pre- and postOP, although here we only consider postOP. Some of these patients have received an organ biopsy to diagnose a suspected organ rejection reaction. Blood samples were also taken during these times.
We want to compare the non-rejection (samples taken postOP when no biopsy was taken or samples corresponding to a negative biopsy result) to the rejection samples (samples corresponding to a positive biopsy result).
The problem we now face is the following: Not all patients have received a biopsy.
This means that some but not all of the patients in the non-rejection group have dependent (paired) samples in the rejection group.
How do we statistically account for the fact that some of the samples are paired? Any help is greatly appreciated!
I am currently using UHPLC-Q-Exactive-MS system for metabolomics analysis. Initially, I have normalized the extracted data (processed by Compound Discoverer software) using the internal standards (ISs) peak area but the data was not satisfactory.
Therefore, I wanted to try other normalisation techniques to compare my data. In many articles, researchers are using total ion count and total spectral area appraches for normalising their metabolomics data. However, I don't know how to evalute the total ion count or the total spectral area. Therefore, I need your kind valuable suggestion and guidace to evaluate it. I would appreciate anykind of assistance. Thank you.
I want to statistically analyse my metabolomics data (18 metabolites). I have two species and four levels of drought. I analysed each species individually by CRD and for mean comparison I used Fisher's LSD (0.05%) by adjusted P-value (FDR). Is this procedure correct or I must use another statistical method?
Thank you all.
Looking for a high-reliability lab that can run plant samples for metabolomic analysis using untargeted approaches byeither NMR or LC-MS with follow up with data analysis (PCA/PLSDA).
If possible ideally also annotate discriminatory compounds
Already came across a few amongst which creative-proteomics/metabolomics in USA although many focus more on biomedical sciences (BioAnalytix Inc, Charles River Laboratories, or KBI Biopharma).
Is it possible to eliminate only the bulky fructose and glucose (F/G) content from the matrix of interest simultaneously and selectively?
I should get rid of the F/G composition but not the other various mono and oligosaccharides along with similar structure polar metabolites. To find out a convenient polar marker at HILIC condition, removal of F/G is crucial since bulk concentration is suppressing ionization at mass spec. and contaminating the ionization chamber/sampling capillary. Totally, this issue is hampering the marker determination capability of the metabolomic approach.
I look for any advice other than molecularly imprinted polymer (MIP) usage and immunoaffinity-capturing methodology. I have tested lectin affinity resin which unfortunately not selective fructose and MIP showed non-specific binding causing the loss of information.
Any suggestion will be appreciated, thanks in advance...
I will perform multiple omic analyses in a sample, but for redox proteomics an akylating agent needs to added in the lysis solution (iodoacetamide or NEM). The problem is that the sample will be splitted in two parts, half for redox proteomics, and half for metabolomics and lipidomics.
The aqueous phase of half of the sample will be used used for metabolomics (and it will be contaminated with iodoacetamide). So I have to remove it befor metabolomics, and the workflow includes HILIC separation. So, I would like to know if by using the HILIC column it will be enough to remove iodoacetamide, or if iodoacetamide will interact with the column and disturb the analisys.
Or still, if anyone can think in another way to remove this iodoacetamide from the aqueous phase that will be used for metabolomics. Remembering that for metabolomics small MW molecules are analyzed.
I need to use the same sample for all analyses, because this is the type of approach that we intend with this project.
Thank you all in advances!
I am trying to assess the activity of PFK enzyme in mESC lines. Recently in the metabolomics analysis, I discovered that although the cells show an increased uptake of glucose 6-P and fructose 6-P, there is a major drop in the levels of downstream metabolites starting from fructose-1,6-bisP all the way up to pyruvate. (except glyceraldehyde-3-P, 1,3-bisPglycerate and 2-phosphoglycerate)
There is also an increase in the levels of glucosamine-6-P, mannose, mannose-6-P and of 6-P gluconate and ribose 5-P. These levels could be increased as G 6-P and F 6-P could be shunted into the pentoseP pathways.
Therefore, I am planning to check if there is a blockage between the F 6-P and fructose 1,6-P by detecting the activity of the PFKinase enzyme.
So far the kits I've found to do this, are based on the calorimetric assay where PFK activity is determined by a coupled enzyme assay, in which fructose-6-phosphate and ATP is converted to fructose1,6-diphosphate and ADP by PFK. The ADP is converted by the enzyme mix to AMP and NADH. The resulting NADH reduces a colorless probe resulting in a colorimetric (450 nm) product proportional to the PFK activity present. One unit of PFK is the amount of enzyme that will generate 1.0 mmole of NADH per minute at pH 7.4 at 37 °C.
I was wondering if there is an in cell method, more precise for cell extracts.. I am not sure how sensitive or specific this calorimetric assay would be.. Any comments/ suggestions would be much appreciated.
As I'm a newcomer to metabolomic data processing from the very raw data, I was wondering how to combine pos and neg mode data together, especially in the condition of acquiring from separate two-year samples.
I have two separate data acquired from two years in the same untargeted LC/MS method but different samples involved, and I want to combine them. Things turned difficult for me when I found there are some metabolites detected in different mode between the two years and not consistent in the two modes. For example, compound A was detected in year 1's pos mode but in year 2's neg mode , not in pos mode.
I'm not sure whether I can combine such compounds directly into one column and then normalize.
Our metabolomics data showed accumulation of UDP in mutants strains of Staphylococcus aureus when compared to the wild type
Hi everybody. I have been in metabolomics 10 years and proteomics 20 years. However I feel confuse today that I am not going anywhere. It is endless questions and endless work to do? Is it good or bad for my future? Have I going wrong direction on the beginning? Today, every manuscript you read it has something to do with programming. Is it future? Should change my career as soon as possible?
To understand how glucose is being metabolized in our cell conditions, 13C Glucose was used as a tracer. To determine the carbon contribution from tracer glucose in each metabolite, the MPE was calculated. However, some MPEs came out as negative. I am relatively new to metabolomics so I am hoping someone can help explain what a negative MPE means in terms of glucose carbon contribution to these metabolites. Or if you can point me to literature that provide an explanation and examples, if will be greatly appreciated.
I am going to work on untargeted metabolomics with Agilent QToF. Please suggest to me the best software for untargeted metabolomics.
I need to know what types of metabolites are present in the FCS.
I have raw data for global/untargeted mass spectrometry metabolomic data. I have processed that data and now have with me the peak intensities of all the m/z values. I had also spiked the samples with an internal standard. Can anyone tell me how can I normalize my data using the internal standard?
I need to know the optimum temperature and duration for the storage of stool samples if I want to perform untargeted metabolomics. Specifically, some evidence or references where metabolomics has been done on stool samples stored in -20 instead of -80.
We do not have GC/MS available in our Lab, therefore I need to send Tissue samples to the company for metabolomic analysis. The out source Lab has to perform derivatization and extraction and analysis itself. But I am looking for sample storage method, because I want to store tissue samples up to one month and later I would like to transport all sample together. For this reason, I am afraid If long storage might impact samples.
Can you Please Suggest me any better method for tissue sample storage or suggest me any related articles or source I should apply to manage sample storage properly..?
Thanks in advance :)
I plan to conduct a non-targeted metabolomic study. I wonder which solvent gives the best extraction for a wide range of metabolites.
It says in the manual that for metabolomic analyses, we should use biological replicates instead of the regular replicates. I am just concerned if even though i already have 3 biological replicates, do I still need test or analyze each biological replicate in certain number of replicates too? For example I have 3 biological replicates, if I test each biological replicates in triplicates again, I have a total of 9 replications ?
Or are those biological replicates good to go and I can just get the mean as is?
If you are an expert in GC-MS metabolomics I need some help here!
I am doing a metabolomic analysis of a pure bacterial culture using derivatization with MTSFA using Fiehn´s protocol.
I am not very clear about how to prepare the cells for extraction and derivatization. I have a nutritive broth with a high cell count, then I have to somehow "clean it" so I can make the metabolite chemical extraction? or how do you account for the contents of the media on the sample?
In the protocol, it says I need to have a blank with only the media both treated as the samples. But is it not better to clean the sample first somehow?. I am confused.
Using non-targeted Liquid-Chromatography Mass Spectrometry I found highly-correlated compounds (r>0.95) with a difference in m/z ~1 (ex: 451.3069 and 452.3102) and very close retention time (<0.01 min). Would this difference be due to the presence of one C13? How to deal with them? Remove? Average? Sum?
Also, when the m/z is very similar (ex: 451.3069 and 451.3078) and highly correlated, but retention time is not so close (ex: 3.70 and 3.88), can they be considered the same compound? How to deal with them?
I am using metaboanalyst for pathway analysis and such.
The y-axis is of course the p value, but the x-axis are the actual pathway impact values ranging from 0-0.5
How do we comment on which pathways are actually significant features?
For example, some pathways are significant (p value, y axis) but are less than 0.2 on the impact analysis (x-axis)
I've read around and most people say "significant features are on the top right" which makes sense, but where exactly is the cut off for the x-axis.
Hope this makes sense
The VIP is usually used in screening biomarkers in metabolomics. I have calculated the VIP from the principle components. But which of them should be used, the most representative component or average of VIP from every components?
I am comparing Mass Spec data from 4 sample groups using MetaboAnalyst. I performed PCA and PLSDA analysis and the 2D scores plots are the exact same.
Does this mean PCA had the best possible separation already? Permutation analysis and cross validation showed that the PLSDA results were valid.
Any certificate course or institution where I can learn the basics and advanced level of metabolomics and metagenomics data analysis?
I have worked on metabolomics data and I am not sure the principle of analysis. First is to conduct a PCA. Literature review says it is to test the overall stability of the system. I do not understand it. Then PLS-DA could select some metabolites. Permutation for cross-validation is to check if over-fitting exists or not. I really do not understand the last bit. Why R2 less than 0 means no over-fitting? What if R2 is over 0 on the figure after permutation? I also do not understand how this permutation is done to cross-validate. Could anyone explain it to me? Many thanks.
I wanted to carry out some metabolomic experiments using E.coli grown on galactose as the sole carbon source as a control. However, the typical expression strains such as BL21 are engineered to be deficient in galactose metabolising genes. I need a strain of E.coli that is capable of protein expression but that grow on galactose. Short of reintroducing the genes (I haven't got much time left in my PhD) is there a strain capable of this?
In the field of Lipidomics or Metabolomics, how is the accurate method to achieve the comprehensive metabolite of a sample using LC-MS/MS?
MRM method might be sensitive enough to achieve the goal, however, in the MRM method, we decide the Q1 and Q3 intentionally based on the available database.
If we use pre-cursor ion scan or natural loss mode, we may lose several metabolites which shows low peak intensity.
For your information, in this case, a Triple Quadrupole with maximum 2 m/z decimal place (ex: 365.45) is used.
I analyzed 20 tissue samples of oral leukoplakia (OL - an oral potentially malignant disease) through untargeted metabolomics to compare the metabolic profile of those OL who had malignant transformation (5) and those who did not (15). I know that the small sample size is one important limitation of the study, but OL is a rare disease and I have to deal with it.
Well, when I use my complete dataset (around 4k compounds) to perform multivariate analysis such as PLS-DA, my model is overfitted, exhibiting a negative q2. However, when I use the 72 compounds considered statistically significant by the univariate methods (hypothesis tests) as the input data, my q2 rises to 0.6. The improvement also occurs when I use this small dataset to build the heatmap that clearly distinguishes the malignant transformed from the non-transformed OL. Interestingly most of the compounds classified on the PLS-DA VIP list are the same, both using my whole data and using the 72 discriminant features as the input.
I recently presented my thesis to a metabolomics specialist and she told me that my analysis is curious and that she cannot tell me whether it is right or wrong.
Would anyone here help me with this question?
Hi, guys, I plan to do an untargeted metabolomics assay in Germany.
My lab is in Bonn, Germany.
My sample is in vitro cultured/stimulated cells.
However, our core facility just offers proteomic service these days. Also, core facilities in Koln and Max Planck Institute are fully booked.
Could anyone can recommend metabolomics core facility that would like to cooperate with or service provider (company) in Germany? My professor would like to pay for good service and accurate analysis. Also, it can be a cooperation that we share authorships.
I am currently studying a proteolytically stable peptide that transiently increases blood brain barrier permeability. While the results suggest that it could facilitate drug delivery to the brain, we are interested in assessing the potential downside of such a strategy.
Primarily, we are worried about neuroinflammation. My lab does not have the facilities to properly detect neuroinflammation. Does anyone know of any lab, core facility, or private company that offers services that can determine whether or not the peptide we are testing can lead to neuroinflammation?
I just need to know the emerging applications of metabolomics in the field of agriculture.
I am working with metabolite data from an experiment that looked at the exometabolome in filtrate of bacteria grown in a medium made with natural seawater. Because natural seawater is a complex mixture, the data also includes analysis of a sample of the medium as a "blank". I was planning on subtracting the value from this medium blank for each metabolite identified in the filtrate to correct for background presence of that metabolite in the medium, but many of the values for metabolites in the medium are below the specified limit of detection. Should I subtract the blank anyway even if its value is below the LOD?
How to analysis LC-MS data without any internal or external standards in metabolomics study?
How to analysis LC-MS data without any internal or external standards in metabolomics study?
I am a layman in metabolomics or LC-MS. And I am confused that which is the suitable internal standards for metabolomics study, like in urine、fecies or plasma samples, if I don't use isotape label metabolites as internal standards. Or, how to do normalization of peak intensities without any standards. Sorry for the stupid questions. Thank you all!
I have one question about compatibility with pyridine as a solvent and GC Capillary Column (such, HP-5MS or RTx-5MS or similar). I am trying to use derivatization by the MeOX in pyridine for dry samples and then I'm going to use MSTFA (metabolomics plant profile) and then inject all.
However I hear, that pyridine can have a negative effect on the stationary phase of the column. The column might get older (bleeding) quickly than usual. So, I have a question: Do you evaporate pyridine before add MSTFA, or impact of the pyridine on the stationary phase not so scary? Might be to using pyridine in the mix with MSTFA not so dangerous too.
Please share with me your opinions and suggestions.
I am thinking about a side experiment where I need to free mouse bone from flesh. Basically to have the skeleton in the end.
The best would be to have a solution which dissolves flesh but not bones. I want to observe bone structure and maybe analyze minerals in the bones.
If you have any solution or a better one than the one I am portraying it would be very nice to hear from you.
Any recommendation on FREE online Webserver/ Software For metabolomic approaches and toxicity prediction for dermal ?
Is better if enclosed with guidance on how to interpret the results generated from the webserver.
This is because I would like to generate a report and have to do interpretation on it.
I want to check the metabolomic profile of my sample. The results seem like only the chemical structures. Is there any software or tools available to analyze the chemical structures to a compound? For example, I got the data as Benzamine, 2,4 dimethyl..... But I want to check the exact metabolites... like glucose, fructose....
I want to extract metabolites from placental tissue for my study. We are using biphasic method and LC-MS platform. The tissue we have is stored in RNAlater. I was wondering if it can be used for the metabolomics or not!! Does RNAlater has any effect on the metabolites of the tissue??!!
Thanks a lot!
I am looking for unanalyzed and unpublished GC-MS datasets from diverse mass spectrometer vendors ? Such as ToFs, single/ triple Quads, Orbitraps etc. that have been acquired from human, plant, or microbial samples for "metabolomics" or "phytochemistry" ?
Happy to collaborate and explain further. Do message for further details.
For each tissue type, targeted LC-MS/MS and untargeted GC-TOF-MS data are available on the same control and experimental groups. Biological replicates per group: n≥18. Would prefer tools that allow the use of effect size values (Cohen’s D) rather than fold change.
I want to ask how to properly collect and store exosomes just after their isolation from conditioned culture media, for subsequent proteomic and/or metabolomic profiling ?? Should we make snap freezing in liquid nitrogen then store in -80 ??? or just store in -80 (without snap freezing)?? or are there any specific precautions that should be taken in consideration while sample collection and storage?? Many thanks in advance for sharing your experience.
I’m using saliva sample of cancer patients for the metabolomic profiling to biomarker discovery. In connection with that I have some doubt in storage of saliva sample.
1. I want to know that the how long I can store the whole saliva in -80oC for the untargeted metabolomic study using LC-MS method?
2. Is the saliva more stable as whole ?
3. After sample preparation for the metabolomic studies how long it can be store in -80oC?
Is the chromatographic peak a valid measure of a compounds` (relative) abundance in LC-MS data? We have recorded three MS/MS spectra; their retention time falls into a specific chromatographic peak (see attached document). Is this peak area an accurate measurement of abundance for the compound described by the three MS/MS spectra? If not, what would be a more accurate measure?
I'm working with NanoLC/MS for both Metabolomics and Proteomics.
We usually make our nano columns using emitters from NewObjective. Unfortunately New Objective, due to the pandemic, is now able to provide them anymore and it is not taking orders.
I've tried with many others company, but all of them are collaborating with NewObjective.
Do you know a different company which provides these products?
I am currently analyzing lipidomic profiles in a cohort study. I have seen some papers adjusting for total HDL and LDL concentrations, but others do not. I am wondering if there are any particularly strong reasons to either adjust or not adjust for them?
When adjusting for it, does this mean you find the effect of unbound lipids or is it more similar to a clustering correction?
I am relatively new to this field, so I would appreciate to hear your opinion about this!
I have metabolite concentrations from mammalian cells, and also total protein concentration in each replicate. I do not have an internal standard.
Please could someone describe or provide a literature reference/software method etc. of the best statistical method to normalize metabolite concentrations to total protein?
Dear to whom it may concern,
I would like to ask you about the normalization methods used to remove non-biological variations from the metabolomics data.
Because there have been many normalization methods reported until now, I am so confused about based on what criteria to select the best normalization method for a particular metabolomics data? Also, what is the meaning of each normalization method?
I hope that you may spend your little time clearing my questions and if convenient for you, may you show me the documents or tips in this case, please?
Thank you so much,
Pham Quynh Khoa.
In metabolomic research, it's important to doing derivatization to your extract before GC-MS analysis to get sugar and amino acid peaks in the results.
Previously, i found on a publication related to metabolomic research that your samples must be immediately analyze with GC-MS equipment after derivatization process.
But, i didn't have any idea about how long we can keep our samples prior to GC-MS analysis.
I am using Orbitrap Q-Exactive plus for metabolomics analysis. I would like to ask about the differences between dd MS/dd-MS2 vs targeted SIM/dd-MS2 mode. When I ran the full MS/dd-MS2 (without a inclusion list) I can get the MS/MS fragmentation however, when I tried to run it with targeted SIM/dd-MS2 mode (with a list of 400 precursor ions), I couldn't get any peaks from the analysis.
So I wonder if the targeted SIM/dd-MS2 mode has a limitation in terms of number of compounds included in the inclusion list? Additionally, whether specifying the retention time for each compound will be a better idea in this case?
Beside, will full MS/dd-MS2 with inclusion list would be another option for targeted large number of compounds? If so, is there any limitation for the number of analytes inputted?
Thank you for your help!
Happy new year to everyone!
Any suggestions, any comments highly appreciated! We mostly use speedvac/lyophilizer system for our metabolomics samples however its not compatible with the organic solvents.