Hi everyone, welcome to BGI’s webinar. The title of today’s webinar is Proteomics &
Metabolomics for Biomarker Discovery Research. The webinar will last 30 minutes.
My name is Yalan Wang, the Global Product Manager for Proteomics and Metabolomics
at BGI. It is my pleasure to be here today. I’ve helped our customers with hundreds of
proteomics and metabolomics projects. During the course of the presentation, you can type
in any questions you have using the Q&A section. At the end of the webinar, I will answer
any questions there are.
Here is the structure of today’s webinar. First I will present the basic concept of proteomics
and metabolomics, then I will give you a practical guidance for biomarker discovery design
and sample considerations followed by real-world case studies, and finally I will present an
introduction to BGI’s mass spectrometry service and platform advantages.
After viewing this webinar I hope you will first have a comprehensive understanding of the
different proteomics and metabolomics techniques available and when to use them, and
also understand best practice for setting up an effective biomarker discovery research
project and finally have new insight from some real cases studies.
Ok, let’s go to the first part. An introduction to proteomics.
Ok, So What is the Proteome? It means all the proteins expressed by a cell、tissue or an
organism.
And Proteomics is to identify and quantify all the proteins, including their modifications.
But Why apply Proteomics?
There are usually four omics techniques to do biological research. The genomics and
transcriptomics studies are done through sequencing platforms. And they tell us what can
happen in an organism. Since the protein is the real executor of life activities and are
involved in almost all life activities, so the proteomics study tells us what is happening and
is done through mass spectrometry platform. The other reason is that The correlation
between mRNA and protein is poor, so we can obtain a panorama of gene expression by
proteomics and transcriptomics. and Finally, The vast majority of drug targets are proteins.
There are about 10,000 kinds of drug target proteins in the human body, however, only
about 500 kinds of drug targets have been found to date. So we need to discover more
therapeutic target proteins for precise treatment of disease.
Proteomics can be applied to many research areas. They are mainly divided into two types
of applications. In medical research, proteomics can be used to study, such as, biomarkers.
In plant and animal research, proteomics can be used to study, such as, animal special
behavior mechanisms. As the concept of proteomics is accepted by more and more
researchers, the area is becoming more popular and publications have increased year by
year.
The proteomics studies are divided into four sections. Protein identification, Protein
Quantification, Protein Modification and Protein-protein Interaction. Protein identification
and quantification studies give you an idea of the protein composition and expression level,
protein modification research gives you an insight on how the proteins are modified and
then activated or inactivated, and finally interactions studies tell you which proteins can
bind to each other under specific conditions.
The most common approach to identifying proteins using MS is bottom-up/shotgun
proteomics.
For the workflow, we extract the protein mixture from cells, tissue or biofluids and then
digest them into peptides mixture and separate them by LC. Next, Peptides are analyzed
by MS. We could obtain MS1 spectra containing molecular weight of intact peptide;
And also obtain MS2 and tandem MS2 spectra representing molecular weight of peptide
fragment ions.
Finally, we identify the Proteins using database searching.
Ok Generally, Proteomics is mainly used in protein identification, protein quantification and
protein modification.
Now that we have understood the proteomics, let’s have a look at Metabolomics.
So What are Metabolites? It means small molecules with molecular weight less than 1500
Da, such as Lipids and Amino acids.
And Metabolomics is to identify and quantify all the metabolites in your samples.
But Why We apply Metabolomics?
The genomics and transcriptomics studies are done through sequencing platforms. And
they tell us what can happen in an organism. The proteomics study tells us what is
happening. But The Metabolomics is directly associated with phenotypic changes and tells
us what has happened and is done through mass spectrometry platform. What’s more, The
used techniques in metabolomics are more common in all fields and more acceptable. So
It can apply to all the sample types.
Metabolomics can be applied to many research areas. They are mainly divided into three
types of applications. In human health research, Metabolomics can be used to study, such
as, biomarkers from your body fluids or tissue samples. In plant and animal research,
Metabolomics can be used to study, such as, growth and development from your Rice
samples. In microbe research, Metabolomics can be used to study, such as, microbial
metabolite change from your feces samples. As the concept of Metabolomics is accepted
by more and more researchers, the area is becoming more popular and publications have
increased year by year.
Generally, there are two types of metabolomics study, untargeted metabolomics and
targeted metabolomics.
Untargeted Metabolomics is an important branch of metabolomics and is to detect all the
metabolites and screen for differentially-expressed molecules in the sample.
While targeted metabolomics is aimed at several target compounds, or some metabolites
involved in a certain pathway. So if you are interested in a targeted class of metabolites,
you can choose targeted metabolomics.
For the workflow of untargeted metabolomics, it includes experimental design, sample
collection, sample preparation, data acquisition, statistical analysis, and metabolite
identification stages.
Now that we have understood the proteomics and Metabolomics, let’s have a look at how
they apply to Biomarker Discovery.
Generally, there are four application scenarios of biomarkers.
Firstly, Predictive markers. It can predict the risk of future disease.
Secondly, Diagostic markers. It can tell us what kind of disease is.
Thirdly, Prognostic markers. It can tell us how the disease progressing is.
Fourthly, Drug targets. It can tell us how to personalize medication.
Here I want to show you a protocol of biomarker screening process. You can see there are
different phases and features.
At the beginning, the main task is to scan for differentially expressed proteins or
metabolites, so the untargeted methods can be used. Such as DIA proteomics and
UNTARGETED metabolomics.
Then after the discovery experiment, you need to further verify these potential candidates
and narrow down the scope, so now you can choose the targeted MRM/PRM analysis and
expand the sample group a little bit.
The third step is to precisely validate the candidate for the clinical assessment. At this
stage, the ideal technique to use is ELISA or Western Blot.
Finally, you can provide some supplymentary validation with your clinical data, such as
biochemical indicators and genome data.
Now we will move to the real practice of protein marker discovery research. You might
think the process of discovery and verification is easy, but in reality, there are many
challenges before you design a strict and precise scientific research project. Common
questions we get here at BGI and which you might also be asking yourself include what is
the protein/metabolite composition in my sample? what is the proteome/metabolome
difference between the two samples?
So there are two choices.
If you just want to know the compound composition in your simple specimens, such as gel
band, you can choose qualitative analysis just for identification.
But if you want to know the content difference and your samples are complex, SUCH as
plasma, tissue, we recommend you to choose quantification products, such as DIA
proteomics and Untargeted metabolomics. To obtain the content information.
Well you may ask “How many biological replicates should I set per group?”
For proteomics, the Recommended biological replicates for Plant、Cell and Microorganism
samples are three, and thirty for human samples.
For metabolomics, the Recommended biological replicates for Plant 、 Cell and
Microorganism samples are six, and ten for animal samples, thirty for human samples.
But What will happen to the results of the experiment if the number of replicates is not
reached?
Ok The essence of analysis is to conduct statistical analysis based on data. Generally
speaking, the more the replicates, the better the performance of analysis results. The
recommended number is the most suitable number based on experience. If the number is
lower than the recommended number, the experimental results will be poorer. If the
number of samples is lower than three, it can not explain biological phenomena very well.
Before collecting samples, it is necessary to consider whether the data can explain
biological phenomena, so it is best to conduct reasonable experimental design.
You may also ask “What are the differential proteins/metabolites, how should I find out?”
Ok Relative quantification or comparative quantification measures the relative change in
protein/metabolite expression levels. It determines the changes between control and test
groups. So if you want to find the differential compounds, you can get the content in control
and test groups, and usually, Two filtration criteria (that is, Fold change more than 2 and
P-value less than zero point zero five) were used to get significant differential
proteins/metabolites.
Then You may ask “Is there any difference between the quantitative technologies?:
Untargeted proteomic study is usually the first step for a protein marker discovery. Here
we compare the different protein quantification technologies, we can see that even for the
sample type, some methods have their own limitations. And compared with the labeling
method, the biggest advantage of label-free quantification seems to be the high throughput,
because no more limitations on the label number anymore. From other perspectives like
protein ID number, dynamic range, and accuracy, different methods may vary a little bit but
overall in my opinion, DIA seems to be the one with all the combined advantages and is a
quite promising technology, especially for large comparison group.
So, for anyone actively planning a proteomics research project, I would like to share some
general sample requirements. Again, please don’t hesitate to reach out if you need more
information and I or someone from BGI can follow up with you afterwards.
We can process a lot of different sample types, cells, blood, tissue, body fluid etc. For each
sample type, the identified protein number is listed here. For example, 4000-9000 proteins
can be expected in cell and tissue sample, while 600-1500 can be identified in the blood
sample with our optimized DIA technology. We can also take ultra-low sample amount, for
a nanoproteomic study. Basically you only need to prepare at least 100 cells for a
quantitative proteomic experiment.
For untargeted metabolomics, 1000-2000 metabolites can be identified in serum plasma
urine and tissue.
While 5000-10,000 metabolites can be identified in feces.
Now I’d like to present a real case to explain the discovery and validation process of protein
biomarker.
Let’s learn about how BGI proteomics contributes to COVID-19 studies:
Biomarker research mainly includes three phases.
Phase I: Discovery--use DIA Proteomics technology to screen the differential proteins;
Phase II: Verification—use PRM Proteomics technology to verify results;
Phase III: Validation—use ELISA technology for further validation.
Finally, BGI and our partners successfully identified DDT, OAF, and MB as a panel of
predictive factors of potential severe COVID-19 patients, which is not only critical to the
lifesaving of patients with COVID-19 but also beneficial to relief of COVID-19 pandemic in
most countries.
The second study was conducted by BGI and the aim of this study is to identify the
metabolite biomarkers for the diagnosis of chronic kidney disease and potential therapeutic
targets.
The experimental design of this study is very perfect. Untargeted screening was performed
in a cohort study and 5 different metabolites were identified as potential biomarkers.
These 5 metabolites were then verified by targeted metabolomics.
Finally, at validation stage, animal model and cell model were used to find a potential target
for the treatment of the disease.
Now that we have understood the how proteomics and metabolomics apply to Biomarker
Discovery, let’s have a look at BGI’s mass spectrometry service and platform advantages.
The proteomics solutions at BGI are divided into four sections. Protein identification,
Protein Quantification, Protein Modification and Protein-protein Interaction. Generally,
there are two types of protein quantification study, untargeted and targeted quantification.
the untargeted protein quantification method can also be divided into two types, labeling
and label-free method.
Labeling method includes ITRAQ、IBT、TMT and label free method includes DDA DIA.
Targeted quantification includes MRM/PRM
Protein interaction include Phosphorylation Glycosylation Acetylation
Particularly worth mentioning is the DIA Quantitative Proteomics. Data-independent
acquisition (DIA) is a relatively new approach to acquisition in
MS but one which has already been applied in many National Precision Medical Projects,
such as the "Cancer Moonshot". Our DIA proteomics service quality has recently been
recognised in two international performance assessment and standardization studies
recently published in Nature communication and therefore BGI is able to accurately and
stably identify and quantify the proteome.
Also BGI helps human proteome research to a new stage. We participated in the Human
Proteome Project, and so far have 18 relevant articles.
For example, BGI participated in the proteome analysis and our proteomics service quality
has been recognised in an international proteome study published in Nature
communications named “A high-stringency blueprint of the human proteome”.
While The Metabolomics solutions at BGI are divided into four sections. Untargeted
metabolomics, Lipidomics, Targeted metabolomics and Multi-Omics Correlation Analysis.
Untargeted metabolomics is divided into Untargeted medical metabolomics and
Untargeted plant metabolomics.
BGI’s lipidomics is to detect all the lipids.
Also, BGI offers nine kinds of targeting options, such as short-chain fatty acids detection,
bile acids detection, amino acids detection, TMAO and relevant metabolites detection,
vitamins detection and neurotransmitter detection.
Lastly, BGI offers multi-omics services LIKE Metagenomics + metabolomics correlation
analysis, Proteome + metabolome correlation analysis.
Here are the detailed advantages of Metabolomics.
1 we have cutting-edge LC-MS/MS systems.
2 we have 10 years rich large sample experience and expert support in metabolomics with
over 2000 projects
3 we have self-built standard metabolite library and thermos standard mzcloud database
which cover over forty thousand endogenous metabolites
4 we have strict protocols and double quality control systems
With these advantages, We aim to bring researchers the most competitive and reliable
results.
So I’ll conclude with an overview of BGI’s MS capacity. BGI MS platform is now wellequipped with more that 30 types of MS and LC instruments. With our cutting-edge
platforms, such as high resolution Orbitrap Exploris 480, timsTOF, Thermo QE series, and
FUSION LUMOS mass spectrometers, we've now supported over three thousand projects
globally. We aim to bring researchers the most competitive and reliable results.
With over 10+ years of experience, an average volume of twenty-two thousand samples
per year, and over two hundred and forty publications, BGI is one of the world’s most
experienced providers of multi-omics based mass spec services and bioinformatics
solutions. With our extensive experiences, we have provided services for more than 3000
projects. We also participated in the Human Proteome Project, and so far have 18 relevant
articles.
Thank you for listening to today’s webinar and I will now review any questions that have
been posted in the portal.