This course will focus on developing integrative skills through directed reading and analysis of the current primary literature to enable the student to develop the capstone project as the overall final exam for the specialization in systems biology.
Lecture 2A - Introduction to Research Article 1- Part 1
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En provenance du cours de Icahn School of Medicine at Mount Sinai
Integrated Analysis in Systems Biology
44 notes
Icahn School of Medicine at Mount Sinai
44 notes
Cours 5 sur 6 dans Specialization Systems Biology and Biotechnology
À partir de la leçon
General Features of Systems Biology Studies
Rencontrer les enseignants
Susana Neves, PhDAssistant Professor
Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY)
Welcome to lecture 2 in the Integrated Analysis in Systems Biology course.
This lecture will cover the first research article.
One of the goals of this course is to expose you to how experimental and
computational approaches are applied in systems biology problems.
We will use original research articles to illustrate how these concepts and
approaches that you've learned in other courses
are utilized to answer biological questions.
We also will have to test your understanding of these approaches.
Today we're covering a research article title, A systems approach identifies
HIPK2 as a key regulator of kidney fibrosis.
We chose this article because it was a good example how to utilize network and
graph theory methods to analyze unique expression data to predict noble,
experimentally, testable targets.
Today we will cover a brief introduction of biology of the kidney in the process
of fibrosis and how HIV infection of the kidney can lead to kidney fibrosis.
We will also go over the goal of the study and the experimental hypothesis.
Most of the experimental and computational approaches used in this study.
And some of the methods, and
a selected number of the figures from the result section.
And we will start with some kidney physiology.
As it is common knowledge,
the function of the kidney is to filtrate waste from blood to produce urine.
The kidney has an essential role not only waste management but
also in maintaining the proper fluid and electrolyte balance of the body.
Each kidney is made up of many filtration units called nephrons.
And each nephron consists of a glomerulus,
which is the site of filtration, and a tubule.
That's where ions and water gets recycled and
waste gets expelled.
And if we were to blow up a diagram of the glomerulus,
we would see a diagram like this, where you have
a multitude of cells making up the filtration unit.
So you have capillaries where blood comes in.
These capillaries are made of fenestrated endothelial cells.
So they are cells that have small pores, and
surrounding the endothelial cells is the glomerular basement membrane.
The glomerular basement membrane provides support.
It's made up of many supportive proteins that creates a rigidity.
And on top of the glomerular basement membrane, are podocytes.
Podocytes are the cells that actually
maintained ingegrity of the filtration unit.
A healthy intact glomerulus.
What you will have is fluid that comes in as blood and
gets filtrated so that all the red blood cells and
most of the proteins remain and everything else gets expelled in,
into the bow, Bowman's space and eventually, come out as a, as urine.
There are many types of injuries that can be detrimental to the functioning of
a kidney.
One of them is fibrosis.
It is known that chronic injury and inflammation can result in fibrosis.
Fibrosis occurs when a process that normally happens as,
as part of the healing process is dis-regulated.
So the normal healing process, if there's injury to the epithelial cells
of the kidney, and that results in an increase in signaling,
specifically of the TGF beta transforming growth factor beta.
And that activates, fibroblast, that facilitate wound healing and repair.
But when the injury is extensive or chronic in nature,
the response becomes disregulated.
So that there is a magnified increase in TGF beta signaling
that leads to proliferation of the fibroblast and
the positions of extracellular matrix like collagen that becomes disrupted and
becomes almost like a, a, a scar type of repair.
And that is called fibrotic repair.
Kidney fibrosis results in many cellular events that eventually
lead to renal failure.
For instance, there is the thickening of the basement membrane, so that
in a process called glomerulosclerosis, there is infiltration of immune cells.
There is proliferation of epithelial cells.
There is an enlargement of Bowman's space, and
this is partly due to a loss of podocytes and capillaries.
There is also an accumulation of protein.
And the atrophy of the tubules eventually
that is also seen with the death of the epithelial cells of the tubules.
All these pathological cellular events will eventually lead to renal failure and
that means that the filtration capability of the kidney is compromised,
and the kidney is no longer able to retain most of the,
the protein in the blood, and basically, there will be protein in the urine.
Kidney fibrosis can occur to a number of pathologies.
One of them is HIV.
HIV infection of a kidney can lead to kidney fibrosis, and
histology data shows some of the key features of HIV-associated nephropathy.
So you have again, the enlarged Bowman space that we described before,
the proliferation of epithelial cells, the tubular atrophy.
The cysts with proteins, and
the glomenrulosclerosis, or the thickening of the basement membrane.
There have been a number of signaling pathways that have been associated with
HIVAN but there was a need for a comprehensive study to look at
all the signaling that occurs during HIVAN in order to identify therapeutic targets.
So, the goal of the study was to evaluate the signaling
pathways that are altered in HIVAN in an unbiased and
systems-wide manner to identify upstream kinases that can be drug targeted.
The hypothesis was that targeting potential
upstream kinases responsible for the transcriptional changes in
HIVAN could protect against the progression of kidney fibrosis.
The approach was to use an animal model of HIV infection in the kidney.
So, the animal use was a T, called Tg26.
And is an HIV transgenic mouse
that expresses the HIV provirus only in the kidney.
This animal develops proteinuria,
or protein in the urine a sign of renal failure.
And what is compelling about this is that the histological findings show that
the human HIVAN resembles very closely this Tg26 type induced HIVAN.
The approach was to compare the mRNA expression profile from
kidneys from Tg26 mice to wild-type mice.
And then use experimental and computational methods to identify
transcriptional factors and upstream kinases that are responsible for
the observed transcriptional changes in HIVAN.
And then go back and determine whether the predicted
kinase is indeed regulated during HIVAN and
can be targeted to prevent the progression of HIVAN.
One of the first experiments done was a microarray based analysis
of the MRA expression from the kidneys of the Tg26 mice versus the wild type mice.
There was also a transcription factor activation array.
These are protein DNA arrays to determine subscription factors that were activated,
preferentially in the Tg26 mice.
>> So and now we're going to talk a little bit in detail about the tools
that were used to analyze the micro array data.
The first things is Chia which is a ChiP-seq/chip enrichment
analysis that contains a database of chip-seq or
chip, chip experiments from a 157 publications.
And that provides a database of over
a 160 transcription factors, and their corresponding DNA targets.
They also have used TRANSFAC, which is a, a promoter analysis tool.
They use Position Weight Matrices data.
Basically they have putative target chains for
each transcription factors based on consensus binding sites, and
by scanning a certain distance from the transcription start site,
they can determine whether the gene
is potentially regulated by a transcription factor or not.
They use the genes2network software also to connect
the seed nodes, which were the transcription factors that were predicted
from the microarray data and from the transcription factor activation arrays
to upstream regulatory signaling,
and they did this using a background
protein interaction network that is made up from 18 different data
sets containing over 24,000 proteins and
Genes2Network uses the shortest path between all pairs of signals based
on a specified maximum path length that is determined.
And finally is KEA, the Kinases enrichment analysis, that basically predicts kinases
that regulate the activated transcription factors that are,
been predicted based on the micro aid and the transcription factor array data.
And this is based on a database of kinasis and
substrates and their substrate.
>> Experimentally validated their predictions.
Most of the computational methods that I'm describing here, have already
been covered by Doctor Ma'ayan, network analysis and systems biology.
Also, some of the experimental methods that
such as the microarray based technologies.
And more recently the RNA-seq technology that are used look at gene expression
have also been described in detail by Doctor Mark Burtwhistles in his course,
experimental methods in systems biology.
We have included PDF files of the lectures
in the supplemental file section, for those of you that would like a refresher.
The pipeline is shown in this figure,
that is actually from the original paper that described
the expression to network pipeline which is a combination of these tools.
The chip enrichment analysis tool, the Genes2Network tool and
the kinase enrichment analysis tool.
So you have a set of differentially expressed genes that then you're
able to identify transcription factors that could be upstream of these genes,
connect them to a protein protein interactions, sub network.
And then able to identify kinases that could modulate them.
>> One of the experimental approaches that was not covered in Dr. Burtwhistles class,
was this protein DNA array, so I'll briefly go over them.
These DNA protein arrays are commercially available and
they consist of labeled DNA probes
that are based on the consensus binding site of activated transcription factors.
So, you incubate these probes with nuclear extracts from kidneys of Tg26 or
wild-type mice.
Then you allow for the DNA active transcription factor complex to form.
And after a series of washes,
is removal of any probes that are not bound to proteins.
Then only the DNA protein complex are recovered.
The protein is denatured, and the DNA probe is released, and
this free DNA probe is hybridized to a membrane net process.
And the results of these membranes look like this, where each of these
spots represents a consensus binding site for a transcription factor.
And they have some control spots to show even hybridization,
and these are, these side dots here, but as you can see,
and these are labeled in, with different red circles,
some of the transcription factor binding sites appear to
increase in the Tg26 mice to increase significantly.
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