This document summarizes a proposed method for segmenting epithelial cells in high-throughput RNAi screens using image analysis. The method uses a pipeline that includes pre-processing images using filters to reduce noise and enhance cell structures, segmenting nuclei, generating an edge map of cell-cell contacts, and performing an adaptive watershed segmentation to extract three structures: cell-cell contacts, nuclei, and cell walls. The method is shown to accurately segment these structures and provide reliable quantification of markers in different experimental conditions, distinguishing effects of depleting different actin-binding proteins on cell-cell adhesion receptors and the cytoskeleton.
Raman microscopy and x ray diffraction a combined study of fibrillin-rich mic...John Clarkson
J.L. Haston, S.B. Engelsen, M. Roessle, J. Clarkson, E.W. Blanch, C. Baldock, C.M. Kielty & T.J. Wess, “Raman microscopy and X-ray diffraction: A combined study of fibrillin-rich microfibillar elasticity”, J. Biol. Chem., 278(42), 41189-41197, 2003.
Perturbing The Interactome: Multi-Omics And Personalized Methods For Network ...Marc Santolini
In this talk, I will describe several recently developed methods to study disease perturbations through the lens of network science. First I will present evidence that one can accurately predict perturbation patterns from the topology of biological networks, even when lacking measurements on the kinetic parameters governing the dynamics of these interactions. Using 87 biochemical networks with experimentally measured kinetic parameters, we show that a knowledge of the network topology offers 65% to 80% accuracy in predicting the impact of perturbations. In other words, we can use the increasingly accurate topological models to approximate perturbation patterns, bypassing expensive kinetic constant measurement. These results open new avenues in modeling drug action, and in identifying drug targets relying on the human interactome only.
Then, I will present a novel approach to identify the collective impact of miRNAs in disease. Instead of focusing on the magnitude of miRNA differential expression, here we address the secondary consequences for the interactome. We developed the Impact of Differential Expression Across Layers (IDEAL), a network-based algorithm to prioritize disease-relevant miRNAs based on the central role of their targets in the molecular interactome. This method was used in the context of asthmatic Th2 inflammation and identified five Th2-related miRNAs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. This result offers novel approaches for therapeutic interventions.
Finally, I will present an investigation of the personalized gene expression responses when inducing hypertrophy and heart failure in 100+ strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). I will show that genes whose expression change significantly correlates with the severity of the disease are either up- or down-regulated across strains, and therefore missed by traditional population-wide analyses of differential gene expression. These uncovered personalised genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome, the set of molecular interactions in the cell. We validate our approach by showing that the knockdown of Hes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80-90% in neonatal rat ventricular myocytes, demonstrating that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies.
Micro and nanoengineering approaches to developing gradient biomaterials sui...Dr. Sitansu Sekhar Nanda
Interface tissue found between soft and hard tissue regions such as cartilage-bone, tendon-bone, ligament-bone and other tissues. (e.g. dentin-enamel). Conventional Biomaterials are monophasic or composite materials are inefficient facilitating tissue formation. So, gradient materials are required for interface tissue engineering.
Raman microscopy and x ray diffraction a combined study of fibrillin-rich mic...John Clarkson
J.L. Haston, S.B. Engelsen, M. Roessle, J. Clarkson, E.W. Blanch, C. Baldock, C.M. Kielty & T.J. Wess, “Raman microscopy and X-ray diffraction: A combined study of fibrillin-rich microfibillar elasticity”, J. Biol. Chem., 278(42), 41189-41197, 2003.
Perturbing The Interactome: Multi-Omics And Personalized Methods For Network ...Marc Santolini
In this talk, I will describe several recently developed methods to study disease perturbations through the lens of network science. First I will present evidence that one can accurately predict perturbation patterns from the topology of biological networks, even when lacking measurements on the kinetic parameters governing the dynamics of these interactions. Using 87 biochemical networks with experimentally measured kinetic parameters, we show that a knowledge of the network topology offers 65% to 80% accuracy in predicting the impact of perturbations. In other words, we can use the increasingly accurate topological models to approximate perturbation patterns, bypassing expensive kinetic constant measurement. These results open new avenues in modeling drug action, and in identifying drug targets relying on the human interactome only.
Then, I will present a novel approach to identify the collective impact of miRNAs in disease. Instead of focusing on the magnitude of miRNA differential expression, here we address the secondary consequences for the interactome. We developed the Impact of Differential Expression Across Layers (IDEAL), a network-based algorithm to prioritize disease-relevant miRNAs based on the central role of their targets in the molecular interactome. This method was used in the context of asthmatic Th2 inflammation and identified five Th2-related miRNAs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. This result offers novel approaches for therapeutic interventions.
Finally, I will present an investigation of the personalized gene expression responses when inducing hypertrophy and heart failure in 100+ strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). I will show that genes whose expression change significantly correlates with the severity of the disease are either up- or down-regulated across strains, and therefore missed by traditional population-wide analyses of differential gene expression. These uncovered personalised genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome, the set of molecular interactions in the cell. We validate our approach by showing that the knockdown of Hes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80-90% in neonatal rat ventricular myocytes, demonstrating that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies.
Micro and nanoengineering approaches to developing gradient biomaterials sui...Dr. Sitansu Sekhar Nanda
Interface tissue found between soft and hard tissue regions such as cartilage-bone, tendon-bone, ligament-bone and other tissues. (e.g. dentin-enamel). Conventional Biomaterials are monophasic or composite materials are inefficient facilitating tissue formation. So, gradient materials are required for interface tissue engineering.
DNA IMAGE SEGMENTATION – A COMPARISON OF EDGE DETECTION TECHNIQUESijbbjournal
Bioinformatics is a computer-assisted interface discipline dealing with the acquisition, storage,
management, access and processing of molecular biology data. It is an interdisciplinary scientific tool
without barriers among various disciplines of science like biology, mathematics, computer science and
information technology. Bioinformatics has become an important part of many areas of biology.
Bioinformatics tools aid in the comparison of genetic and genomic data and more generally in the
understanding of evolutionary aspects of molecular biology. In structural biology, it aids in the simulation
and modelling of DNA, RNA and Protein structures as well as molecular interactions. The most important
feature of DNA is that it is usually composed of two polynucleotide chains twisted around each other in the
form of a double helix. In this paper we have easily identified the complicated structure of DNA images for
using several techniques of edge detection in image processing .we consider various well known Algorithms
and metrics used in image processing applied to DNA images in this comparison .
A Multiset Rule Based Petri net Algorithm for the Synthesis and Secretary Pat...ijsc
Membrane computing is a branch of Natural computing aiming to abstract computing models from the structure and functioning of the living cell. A comprehensive introduction to membrane computing is meant to offer both computer scientists and non-computer scientists an up-to date overview of the field. In
this paper, we consider a uniform way of treating objects and rules in P Systems with the help of Multiset rewriting rules. Here the synthesis and secretary pathway of glycoprotein in epithelial cells of small intestine is considered as an example. A natural and finite link is explored between Petri nets and membrane Computing. A Petri net (PN) algorithm combined with P Systems is implemented for the synthesis and secretary pathway of Glycoprotein. To capture the compartmentalization of P Systems, the Petri net is extended with localities and to show how to adopt the notion of a Petri net process accordingly.
The algorithm uses symbolic representations of multisets of rules to efficiently generate all the regions associated with the membrane. In essence, this algorithm is built from transport route sharing a set of places modeling the availability of system resources. The algorithm when simulated shows a significant
pathway of safe Petri nets.
Talk given to the Emory Cancer Control and Population Science Program 2/17/2011 Describing Biomedical Informatics, Integrative Cancer Research, caBIG and CTSA
SeedEZ 3D cell culture application notes - gel and drug embeddingLena Biosciences
SeedEZ 3D cell culture application notes - gel and drug embedding. Many inert polymers used as scaffolds for 3D cell cultures and colony formation are also used in drug delivery systems both in vitro and in vivo. Read this practical guide to learn how SeedEZ lets you merge these two worlds in order to integrate 3D cell cultures into standard drug delivery and testing applications.
By incorporating or adding drugs to SeedEZ, or in polymer matrices embedded in SeedEZ, dosage forms which release a drug over a period of time may be prepared in a desired shape and size. More importantly, all SeedEZ-based dosage forms may be tested in situ, with cells in a 3D cell culture. SeedEZ wicks most sol-state hydrogels, hydrogel precursors, semisolid media, excipient formulations, pharmaceuticals and test compounds. As a result, SeedEZ offers a novel 3D framework for (A) development of sustained release drug delivery systems that are simple to make and convenient to use in vitro; (B) localized or distributed drug delivery into 3D cell cultures using spot-a-culture and spot-a-drug approach, wick, dip or SeedEZ-stack method; (C) gradient formation and testing of drug combination strategies; (D) quality control testing and assurance; and (E) development of test platforms for quasi-steady drug release.
Notably, in most diffusion-driven drug delivery systems, a drug release rate declines in time. A degradable polymer matrix embedded in SeedEZ may enable quasi-steady drug release from a defined volume, defined by SeedEZ, when the matrix degradation rate is adjusted to compensate for this decline via increased drug permeability from the SeedEZ/polymer matrix system.
The application note covers use of common biomaterials, including extracellular matrix hydrogels (Collagen and Matrigel), gels from natural sources for spheroid cultures and controlled drug release (Agarose, Alginate, Methylcellulose, Gelatin), and synthetic materials such as Poloxamers (Pluronic - used for cell encapsulation, drug delivery and pharmaceutical formulations), and Carbomers used in ocular, transdermal, oral and nasal delivery systems.
Cornea is the outermost anterior layer of the eye ball which
has unique optical and physio-mechanical properties to maintain
good vision. A stratified squamous epithelium is continued with the conjunctival epithelium in the limbal area and create a protective stratum on the ocular surface to defend internal structure from environmental threats
DNA IMAGE SEGMENTATION – A COMPARISON OF EDGE DETECTION TECHNIQUESijbbjournal
Bioinformatics is a computer-assisted interface discipline dealing with the acquisition, storage,
management, access and processing of molecular biology data. It is an interdisciplinary scientific tool
without barriers among various disciplines of science like biology, mathematics, computer science and
information technology. Bioinformatics has become an important part of many areas of biology.
Bioinformatics tools aid in the comparison of genetic and genomic data and more generally in the
understanding of evolutionary aspects of molecular biology. In structural biology, it aids in the simulation
and modelling of DNA, RNA and Protein structures as well as molecular interactions. The most important
feature of DNA is that it is usually composed of two polynucleotide chains twisted around each other in the
form of a double helix. In this paper we have easily identified the complicated structure of DNA images for
using several techniques of edge detection in image processing .we consider various well known Algorithms
and metrics used in image processing applied to DNA images in this comparison .
A Multiset Rule Based Petri net Algorithm for the Synthesis and Secretary Pat...ijsc
Membrane computing is a branch of Natural computing aiming to abstract computing models from the structure and functioning of the living cell. A comprehensive introduction to membrane computing is meant to offer both computer scientists and non-computer scientists an up-to date overview of the field. In
this paper, we consider a uniform way of treating objects and rules in P Systems with the help of Multiset rewriting rules. Here the synthesis and secretary pathway of glycoprotein in epithelial cells of small intestine is considered as an example. A natural and finite link is explored between Petri nets and membrane Computing. A Petri net (PN) algorithm combined with P Systems is implemented for the synthesis and secretary pathway of Glycoprotein. To capture the compartmentalization of P Systems, the Petri net is extended with localities and to show how to adopt the notion of a Petri net process accordingly.
The algorithm uses symbolic representations of multisets of rules to efficiently generate all the regions associated with the membrane. In essence, this algorithm is built from transport route sharing a set of places modeling the availability of system resources. The algorithm when simulated shows a significant
pathway of safe Petri nets.
Talk given to the Emory Cancer Control and Population Science Program 2/17/2011 Describing Biomedical Informatics, Integrative Cancer Research, caBIG and CTSA
SeedEZ 3D cell culture application notes - gel and drug embeddingLena Biosciences
SeedEZ 3D cell culture application notes - gel and drug embedding. Many inert polymers used as scaffolds for 3D cell cultures and colony formation are also used in drug delivery systems both in vitro and in vivo. Read this practical guide to learn how SeedEZ lets you merge these two worlds in order to integrate 3D cell cultures into standard drug delivery and testing applications.
By incorporating or adding drugs to SeedEZ, or in polymer matrices embedded in SeedEZ, dosage forms which release a drug over a period of time may be prepared in a desired shape and size. More importantly, all SeedEZ-based dosage forms may be tested in situ, with cells in a 3D cell culture. SeedEZ wicks most sol-state hydrogels, hydrogel precursors, semisolid media, excipient formulations, pharmaceuticals and test compounds. As a result, SeedEZ offers a novel 3D framework for (A) development of sustained release drug delivery systems that are simple to make and convenient to use in vitro; (B) localized or distributed drug delivery into 3D cell cultures using spot-a-culture and spot-a-drug approach, wick, dip or SeedEZ-stack method; (C) gradient formation and testing of drug combination strategies; (D) quality control testing and assurance; and (E) development of test platforms for quasi-steady drug release.
Notably, in most diffusion-driven drug delivery systems, a drug release rate declines in time. A degradable polymer matrix embedded in SeedEZ may enable quasi-steady drug release from a defined volume, defined by SeedEZ, when the matrix degradation rate is adjusted to compensate for this decline via increased drug permeability from the SeedEZ/polymer matrix system.
The application note covers use of common biomaterials, including extracellular matrix hydrogels (Collagen and Matrigel), gels from natural sources for spheroid cultures and controlled drug release (Agarose, Alginate, Methylcellulose, Gelatin), and synthetic materials such as Poloxamers (Pluronic - used for cell encapsulation, drug delivery and pharmaceutical formulations), and Carbomers used in ocular, transdermal, oral and nasal delivery systems.
Cornea is the outermost anterior layer of the eye ball which
has unique optical and physio-mechanical properties to maintain
good vision. A stratified squamous epithelium is continued with the conjunctival epithelium in the limbal area and create a protective stratum on the ocular surface to defend internal structure from environmental threats
The paradigm shift in the way we are treating periodontal disease necessitates the use of modifiable and non-modifiable risk factors. This presentation reviews the most recent evidence regarding periodontal disease diagnosis and maintenance.
Large scale cell tracking using an approximated Sinkhorn algorithmParth Nandedkar
Cell tracking for a large scale (of over 1 million cells) has not yet been achievable within reasonable a time scope with current NN/RNN/Bi-RNN based methods. This individual research conducted by me at Osaka University, ISIR seeks to solve this problem using the Sinkhorn algorithm, and taking inspiration from the MPM method (Hayashida, 2020)
New foreground markers for Drosophila cell segmentation using marker-controll...IJECEIAES
Image segmentation consists of partitioning the image into different objects of interest. For a biological image, the segmentation step is important to understand the biological process. However, it is a challenging task due to the presence of different dimensions for cells, intensity inhomogeneity, and clustered cells. The marker-controlled watershed (MCW) is proposed for segmentation, outperforming the classical watershed. Besides, the choice of markers for this algorithm is important and impacts the results. For this work, two foreground markers are proposed: kernels, constructed with the software Fiji and Obj.MPP markers, constructed with the framework Obj.MPP. The new proposed algorithms are compared to the basic MCW. Furthermore, we prove that Obj.MPP markers are better than kernels. Indeed, the Obj.MPP framework takes into account cell properties such as shape, radiometry, and local contrast. Segmentation results, using new markers and illustrated on real Drosophila dataset, confirm the good performance quality in terms of quantitative and qualitative evaluation.
A Multiset Rule Based Petri net Algorithm for the Synthesis and Secretary Pat...ijsc
Membrane computing is a branch of Natural computing aiming to abstract computing models from the structure and functioning of the living cell. A comprehensive introduction to membrane computing is meant to offer both computer scientists and non-computer scientists an up-to date overview of the field. In this paper, we consider a uniform way of treating objects and rules in P Systems with the help of Multiset rewriting rules. Here the synthesis and secretary pathway of glycoprotein in epithelial cells of small intestine is considered as an example. A natural and finite link is explored between Petri nets and membrane Computing. A Petri net (PN) algorithm combined with P Systems is implemented for the synthesis and secretary pathway of Glycoprotein. To capture the compartmentalization of P Systems, the Petri net is extended with localities and to show how to adopt the notion of a Petri net process accordingly. The algorithm uses symbolic representations of multisets of rules to efficiently generate all the regions associated with the membrane. In essence, this algorithm is built from transport route sharing a set of places modeling the availability of system resources. The algorithm when simulated shows a significant pathway of safe Petri nets.
ADAPTIVE SEGMENTATION OF CELLS AND PARTICLES IN FLUORESCENT MICROSCOPE IMAGEJournal For Research
Understanding the mechanisms of cell motility and their regulation is an important challenge in biomedical research. The ability of cells to exert forces on their environment and alter their shape as they move is essential to various biological processes such as the immune response, embryonic development, or tumor genesis .Recent technological advances in con-focal fluorescence microscopy have given researchers the opportunity to investigate these complex processes in vivo. However, they also lead to a tremendous increase in the amount of image data acquired during the studies. Therefore, the analysis of time-lapse experiments relies increasingly on automated image processing techniques. Namely, there is a high demand for fast and robust methods to help biologists to quantitatively analyze time-lapse image data. The potential of the proposed tracking scheme and the advantages and disadvantages of both frameworks are demonstrated on 2-D and 3-D time-lapse series of rat adipose-derived mesenchymal stem cells and human lung squamous cell carcinoma cells, respectively. The crucial tasks are, in particular, segmenting, tracking, and evaluating movement tracks and morphological changes of cells, sub-cellular components and other particles.
Detection of DNA Damage Using Comet Assay Image AnalysisIJRST Journal
Reactive species such as free radicals are constantly produced in vivo and DNA is the very important target of oxidative stress. Oxidative DNA damage is considered as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for specifying oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. The comet assay, also known as single-cell gel electrophoresis (SCGE), is a simple, sensitive and reliable method for studying DNA damage caused by physical and chemical agents. So the comet assay is a well-established, simple, versatile, visual, rapid, and sensitive method used extensively to assess DNA damage quantitatively and qualitatively at single cell level. The comet assay is most frequently used to analyze white blood cells or lymphocytes in human bio monitoring studies. So through the analysis of comet assay image we can detect edge of damaged DNA comet isolating it from undamaged DNA.
Genome folding by loop extrusion and compartmentalization Leonid Mirny
2018-03-27 Leonid Mirny (MIT) and Nezar Abdennur, Sameer Abraham, Ed Banigan, Hugo Brandao, Martin Falk, Geoff Fudenberg (UCSF), Anton Goloborodko, Max Imakaev, Carolyn Lu, Johannes Nuebler, Aafke van den Berg; talk at the Keystone Symposium
I elaborated these slides for an introductory class on Network Medicine given at UPV (Valencia) in October 2017. The fundamental principle behind Network Medicine is that disease phenotypes emerge from genotypes via the network properties of interactions between the underlying biological components. These phenotypes are best conceptualized as consequences of perturbations to disease modules of the biological networks in the cell, whether at the node level (disease genes) or the link level (disease edgotypes). With the further analysis of drug-disease association and drug-target association data, one can investigate the effects - therapeutic and undesired - of the associated medication. Understanding the molecular level networks allows to understand the connections between different diseases and the effects of drugs designed to target them, paving the way for personalized treatments based on one's own interactome.
An Efficient VLSI Design for Extracting Local Binary PatternIJTET Journal
Abstract— The nonspecific nature of the signs and symptoms of Acute Myelogenous leukaemia typically results in wrong designation. Diagnostic confusion is additionally display because of imitation of comparable signs by alternative disorders. Careful microscopic examination of stained blood smear or bone marrow aspirate is that the solely thanks to effective designation of leukaemia. Now a days, a statistic approach to texture analysis has been developed, during which the distributions of straightforward texture measures supported native ternary patterns (LTP) are used for texture details. This paper shows that a selected set of patterns encoded in LTP forms together with wavelets transform primarily based frequency domain parameters extraction is an economical and sturdy texture description which may bring higher classification rates compared with the prevailing ways.
Tracking of leukocytes in vivo and recording their dynamics with intravital microscopy is an effective
technique for further understanding of the mechanism of inflammation and the influence of drug delivery in
microcirculation. Though the technique is well established, automated quantitative analysis of the captured
video frames is lacking in the literature. In this paper we adopt a duality based TV-L1 optical flow to
analyze leukocyte behavior using in vivo video microscopy. Typically, we exploit the ability of this
approach to conserve discontinuities in the flow field through the regularization of the Total Variation
(TV). On the other hand, the L1 norm overcomes the sensitivity to outliers. In the proposed framework, we
submit the input images to a structure-texture decomposition in order to overcome the illumination changes
causing violations in the optical flow constraint. Moreover, to further reduce the sensitivity to sampling
artifacts in the image data, we apply a median filter into the numerical scheme. Using this technique, it is
possible to directly compute the trajectories of leukocytes and their physical interaction parameters directly
from the video frames. We have compared the obtained hydrodynamic fields with those obtained via
simulation and have found that duality based TV-L1 optical flow approach is computationally less costly
and reveals promising results.
Stem cells and nanotechnology in regenerative medicine and tissue engineeringDr. Sitansu Sekhar Nanda
Alexis Carrel, winner of the Nobel Prize in Physiology or Medicine in 1912 and the father of whole-organ transplant, was the first to develop a successful technique for end to end arteriovenous anastomosis in transplantation.
71st ICREA Colloquium "Intrinsically disordered proteins (id ps) the challeng...ICREA
The unbearable lightness of being (a protein)
Proteins adopt beautiful shapes that enable them to perform an incredible array of tasks. But these wiggly little creatures cannot stay still. Is this a nuisance or a blessing?
After a basic introduction to proteins, Xavier Barril focuses on the implications of protein flexibility for drug discovery. Showing that a rigid representation has been, and continues to be, extremely useful. He will present some of the failures and challenges in introducing a more realistic view, but also how the dynamic perspective is gaining ground thanks to the advances in structural biology and computational chemistry.
Xavier Salvatella discusses where the limit is: can proteins be completely disorganised? Can we study and understand intrinsically disordered proteins from a structural point of view? How can this class proteins perform functions if they have no structure? Why have they evolved? Is it ever going to be possible to modify the function of this class of proteins with small molecules, as we have learned to do with proteins that fold?
Proteins adopt beautiful shapes that enable them to perform an incredible array of tasks. But these wiggly little creatures cannot stay still. Is this a nuisance or a blessing?
Xavier Salvatella discusses where the limit is: can proteins be completely disorganised? Can we study and understand intrinsically disordered proteins from a structural point of view? How can this class proteins perform functions if they have no structure? Why have they evolved? Is it ever going to be possible to modify the function of this class of proteins with small molecules, as we have learned to do with proteins that fold?
The ECIS is a turnkey system that provides researchers with an advanced, automated, non-invasive means to monitor cell behavior in real-time and without the use of labels.
Similar to Segmenting Epithelial Cells in High-Throughput RNAi Screens (Miaab 2011) (20)
Sparsity Based Spectral Embedding: Application to Multi-Atlas Echocardiograph...Kevin Keraudren
Slides from Ozan Oktay at the MICCAI workshop on Sparsity Techniques in Medical Imaging (STMI2014), presenting one of the methods we used in the CETUS challenge (http://www.creatis.insa-lyon.fr/Challenge/CETUS/index.html).
Faceccrumbs: Manifold Learning on 1M Face Images, MSc group projectKevin Keraudren
MSc group project (March 2011) at Imperial College which emulated Google's People Hopper:
http://googleresearch.blogspot.co.uk/2010/03/hopping-on-face-manifold-via-people.html
Slides presented at the Steiner Unit, Hammersmith Hospital, 08/06/2012Kevin Keraudren
These slides present my work during my first year of PhD. The Steiner Unit used to be the MRI Research unit before the whole team moved to St Thomas (King's College).
Slides from the reading group presentation where I introduced a new Python interface for IRTK.
See http://kevin-keraudren.blogspot.co.uk/2013/12/irtk-python.html for more details and the iPython notebook demo.
Segmenting Epithelial Cells in High-Throughput RNAi Screens (MIAAB 2011)Kevin Keraudren
Slides presented at the workshop in Microscopic Image Analysis with Applications in Biology, Heidelberg, September 2011. The associated paper can be found here: http://www.doc.ic.ac.uk/~kpk09/publications/MIAAB-2011.pdf
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
The ASGCT Annual Meeting was packed with exciting progress in the field advan...
Segmenting Epithelial Cells in High-Throughput RNAi Screens (Miaab 2011)
1. 1
Segmenting Epithelial Cells in High-Throughput RNAi Screens
Kevin Keraudren1, Martin Spitaler2, Vania M.M. Braga2, Daniel Rueckert1, Luis Pizarro1
1Department of Computing, Imperial College London, UK
2National Heart and Lung Institute, Imperial College London, UK
Abstract— Epithelial cells are present in many different
organs and are essential for physiology. Understanding the
molecular mechanisms via which cell-cell contacts are stabilised
has important implications for a variety of diseases and
cancers. To elaborate on such studies, we develop an automatic
approach to cell segmentation for image-based high-throughput
RNAi screens. Our method is based on a simple but effective
combination of well-established image filters, morphological
operations and watershed segmentation. Aiming at preserving
the localisation of the different cell structures, we are able
to extract nuclei, cell walls and cell-cell contacts with high
accuracy. These turned out to be very important for masking the
image readouts of cadherin receptors and actin reorganisation to
distinguish between junctional and cytoplasmic cell phenotypes.
Although we focus on epithelial cells, our approach has general
applicability to other cell-based screens in confocal microscopy.
Index Terms— Cell segmentation, epithelial cells, high-content,
high-throughput screening, biological image analysis
I. INTRODUCTION
Image-based RNA interference (RNAi) screening has
become a widely used technique to knock-down targeted
genes to analyse their effect on specific cellular functions.
The identification of phenotypes corresponding to distinct
phases of the cell cycle in cells of different health status is
the first step to a better understanding of cellular function
in disease and in response to treatment. Large-scale high-
throughput, high-content screens produce thousands of images
and time-lapse videos capturing particular instants of these
cellular processes. Recent studies have emphasised the need
of robust and efficient computational tools to analyse this
overwhelming amount of data, which is the real bottleneck in
terms of data interpretation [1], [2], [3].
We are interested in studying the biological processes that
regulate cell-cell adhesion signalling. Cell-cell adhesion is
essential for the life of many different cell types and for
their organisation into higher ordered structures (tissues and
organs). Epithelial cells attach strongly to neighbouring cells
via specialised adhesive molecules. Sheets of tightly packed
epithelial cells play a key role in absorption, secretion and
as protective layers. Perturbation of their ability to interact
tightly is found in different pathologies such as detachment
of malignant tumour cells or pathogen infection [4], [5].
One of the master regulators of epithelial adhesion are
members of the cadherin family of receptors. Establishment
of E-cadherin cell-cell contacts is a multifactorial event;
signalling and structural actin-binding proteins contribute to
receptor clustering and stabilisation at adhesive sites. Clearly,
Corresponding author: Luis Pizarro, email: luis.pizarro@imperial.ac.uk.
disruption of actin cytoskeleton severely prevents stable
cell-cell adhesion, indicating the important role cytoskeletal
attachment for junction morphology and function. RNAi
screens have successfully mapped important regulators of cell
attachment to substratum [6], [7] and potential diagnostic tools
for diseases and cancer [8]. Yet, in spite of many previous
studies, a comprehensive knowledge of the molecules and
processes required for stable cadherin adhesion and junction
morphology is not available.
Towards a better understanding of the adhesion properties of
epithelial cells, we performed a RNAi actin screen to identify
specific actin-binding proteins required for assembly of cell-
cell contacts and actin reorganisation. The screen produced
thousands of images for about 400 proteins considered in
our study. In the following, we will consider (R, G, B) =
(IHECD1, IACT IN , IDAP I) image composites like the one
shown in Figure 1. To investigate the way epithelial cells attach
to one another, it is essential to rely on an accurate image
segmentation of the constituent parts of each cell (nucleus,
cytoplasm and membrane) so as to identify those proteins
whose depletion by RNAi perturbed levels of E-cadherin
or F-actin at junctions or in the cytoplasm. As it can be
noted in Figure 1, this is not a straightforward task since
RNAi depletion causes various cell distortions that need to
be quantified, making any automatic segmentation attempt
extremely challenging. The main challenges for automated
analysis that we observed in the acquired images are their
low signal-to-noise ratio (SNR), broken cell-cell contacts and
multiple cell overlaps.
In this paper we propose an algorithmic pipeline for the
automatic segmentation of epithelial cells in high-content,
high-throughput RNAi screens. Our method is able to segment
most cells under these challenging conditions. It is based on
a simple but effective combination of well-established filters,
morphological operations and watershed segmentation. We are
specially keen on segmenting three types of cell structures:
nuclei, cell walls and cell-cell contacts. That way, we can
aim at distinguishing different actin-binding proteins by their
image readouts.
The rest of the paper is organised as follows: Some
related work on cell segmentation is reported in Section II.
Our proposed approach is presented in detail in Section III.
Section IV demonstrates the suitability of our approach to
correctly segment junctional and cytoplasmic structures, which
allows for the characterisation of different proteins. Finally,
we discuss our contributions and sketch some future work in
Section V.
2. 2
(a) (b) (c) (d)
Fig. 1. (a) image composite (R, G, B) = (IHECD1, IACT IN , IDAP I ); (b), (c) and (d) display zoomed-up images of each channel, respectively.
II. RELATED WORK ON CELL SEGMENTATION
From the abundant literature on cell segmentation, here we
briefly report on two recent and competing methods that are
well suited for high-throughput RNAi screens.
A common approach to cell segmentation is to begin by
thresholding the nuclei and then propagating the obtained
seeds to define the cytoplasm. Jones et al. [9] proposed
a Voronoi-based segmentation approach that approximates
the Voronoi regions of each seed on a manifold with a
metric such that adjacent pixels with similar surrounds are
close to one another, while pixels whose surrounds differ
are treated as farther apart. This method has become very
popular and it is been implemented in CellProfiler [10] and in
Bioconductor [11].
The method proposed by Yan et al. [12] is based first on a
segmentation of the nuclei with the following pipeline: Otsu
thresholding, distance transform and watershed on the distance
transform. Then, for each nucleus an active contour is fitted
to the cell boundaries by minimising an energy functional that
describes both the repulsion between neighbouring cells and
the competition for segmenting pixels. The authors compared
their method to the Voronoi-based approach mentioned above,
obtaining about 10% better F-score. Nevertheless, they did not
provide the same seeds to both methods. They run a separate
nuclei segmentation, thus blaming the competing method for
over-segmenting the cells.
Later in our experiment we also compare our approach
against Jones et al.’s method, but we attempt doing it as fairly
as possible.
III. PROPOSED SEGMENTATION APPROACH
Our approach to cell segmentation utilises a couple of
components that are standard in the biological literature,
plus a few new ingredients that allow us to cope with
the challenging conditions mentioned in the introduction.
Furthermore, we will be able to define three cellular objects:
nuclei, cell-cell contacts and cell walls, which will be very
important for masking the IHECD1 and IACT IN channels to
distinguish between junctional and cytoplasmic cell-features.
The proposed pipeline for cell segmentation is outlined in
Figure 2. It consists of four main blocks: Pre-Processing,
Nuclei Processing, Edge-Map Processing, and Adaptive
Watershed, which are detailed below.
A. Pre-Processing
Screen images were acquired using a line scanning confocal
system. Four projections in the z-plane were acquired at each
experimental well, from which we computed the maximum
intensity projection for each channel. To avoid some optical
aberrations we discarded the pixels with the 2% darkest and
the 1% brightest intensities, performing then a normalisation
to the range [0, 255]. This constitutes our raw data.
The intensity variability and the low SNR observed at
the cell-cell contacts and cytoplasm hinders their proper
segmentation. We therefore opt for denoising the IHECD1 and
IDAP I channels, which are the ones we base our segmentation
approach on. We utilise the block matching 3D (BM3D) filter
of Dabov et al. [13] that is the state-of-the-art for filtering
Gaussian noise. Another issue affecting the IHECD1 channel
is the presence of broken cell-cell contacts. To partially solve
this problem we use the coherence-enhancing diffusion (CED)
filter of Weickert [14] that connects and enhances interrupted
line-like structures. It is important to mention that all these
filtering steps are only employed to help the segmentation
process. Once we have built segmentation masks for the
nuclei, the cytoplasm and the cell-cell contacts, all subsequent
phenotypic measurements are taken from the raw data.
B. Nuclei Processing
With the auto-threshold method of Li and Lee [15] we
obtain a first segmentation of the nuclei, which we then refine
with a watershed process on the grey-scale IDAP I channel to
separate the joined nuclei. As a last step, touching nuclei are
eroded in one pixel to accentuate their separation.
C. Edge-Map Processing
We obtain an approximate localisation of the cell-cell
contacts and their thickness by computing an edge map on
the IHECD1 channel with a Sobel filter, followed by the
application of a mean filter. The latter is used to fill the gaps in
the edge map. Note that a morphological closing would have
served the same purpose.
3. 3
Fig. 2. The proposed pipeline for cell segmentation consists of 4 blocks: Pre-Processing, Nuclei Processing, Edge-Map Processing, and Adaptive Watershed.
Fig. 3. Adaptive Watershed block that produces the final segmentation as a composition of three classes of structures: Cell-Contacts, Nuclei, Cell-Walls.
D. Adaptive Watershed
As shown stepwise in Figure 3, we aim at extracting
three different types of cell structures from the images: the
cell-cell contacts where two cells touch each other, the cell
walls delimiting the extent of the cytoplasm, and the nuclei
respecting such cell boundaries.
Using the input nuclei as seeds we perform a watershed on
the edge map to obtain a first segmentation of the cell-cell
contacts, which are then eroded towards the regions of high
HECD1 to obtain a first segmentation of the cell walls.
Despite the fact that the smoothed edge map provides a good
initialisation for estimating the cell boundaries, it does not
carry precise information about the regions of high cadherin.
Therefore, we optimise the cell-cell contacts by adapting
another watershed to the IHECD1 channel using the cell walls
as seeds.
Subsequently, the nuclei are segmented in such a way that
they do not cut the cell-cell contacts. That is, they need to
be intercepted with the cell walls. Finally, a last refinement
takes place at the cell walls. They are re-estimated with the
better localised cell-cell contacts. Note that the update of
the cell walls is done after the nuclei segmentation. That
way we diminish the risk of having nuclei cutting throw
the cell boundaries (although it might happen), so we can
later make junctional measurements without bias towards the
presence/absence of nuclei.
IV. RESULTS
We would first like to emphasise the importance of the
pre-processing block in our pipeline. As it was shown in
Figure 1, the IHECD1 channel is affected by a low SNR
and by incomplete cell boundaries. The joint utilisation of
the BM3D and the CED filters does help obtain smoother
and more accurate segmentations as it can be observed in
Figure 4(b)-(c).
4. 4
Another important characteristic of our segmentation
approach is its ability to accurately localise cell-cell contacts,
which is encoded in the adaptive watershed algorithm
described above. We compare the segmentation of cell-cell
contacts using our approach and the propagate method
based on Voronoi diagrams implemented in Bioconductor.
For a fair comparison, both methods were fed with the
same pre-processed data as in Figure 2. The results in
Figure 4(d)-(e) indicate that the Voronoi-based method cannot
produce as accurate segmentations of the cell-cell contacts
as our approach. The white arrows point out some of the
misalignments with respect to the IHECD1 channel obtained
via propagate. At this point it is worth noting that it should
not be difficult to implement a two-step propagate method
to mimic what we have done with the two-step watershed
algorithm.
To test the biological significance of our segmentation
pipeline, we compare the results of three images from the
cell-based high-throughput screen of actin-binding proteins.
Figure 5 shows boxplots of the intensity distribution of
three experimental parameters E-cadherin (HECD1) and actin
filaments (J-Actin) at the cell-cell contacts, as well as of the
non-junctional (cytoplasmic) Actin (NJ-Actin). In all graphs,
the first bar is the quantification of images from a positive
control (Ca2+), while the second and third bars refer to images
obtained after depletion of two proteins in cells: Tropomyosin-
2 beta (TPM2) and VAV-2 oncogene (VAV2), respectively.
TPM2 binds actin filaments and stabilise them and is thereby
predicted to play a role in cytoplasmic actin and potentially
at Junctional actin. VAV2 is an upstream regulator of the
small GTPase Rac1, a known regulator of actin remodelling
following different stimuli such as migration, growth factor
stimulation and cell-cell adhesion.
These plots confirm that the RNAi perturbation of both
TPM2 and VAV2 has a strong effect on the response of
cadherin receptors. In terms of the actin measurements, both
proteins distinguish themselves from the positive control
with higher and lower intensity levels, respectively. Thus the
new pipeline proposed here is able to identify cell borders
efficiently and provides reliable quantification. They are also
consistent with the images and predicted phenotype of the
proteins investigated (see discussion in Section V).
V. DISCUSSION AND CONCLUSIONS
We have presented a general approach to cell segmentation
for image-based high-throughput RNAi screens. The most
challenging issues were: i) to accurately extract well-localised
cell-cell contacts –which sometimes appear fuzzy– respecting
the tightly packed organisation of cell conglomerates, and ii)
to determine the thickness of the cell walls –even fuzzier.
Both issues have a huge influence on the definition of cell
phenotypes that can reliably distinguish between actin-binding
proteins inhibiting or promoting actin reorganisation and the
establishment of cadherin receptors.
(a)
(b) (c)
(d) (e)
Fig. 4. (a) raw data; segmentation (b) with and (c) without pre-processing;
localisation of cell-cell contacts (black lines) after segmentation with (d) our
approach and (e) Bioconductor. Please refer to the text for details.
Ca2+ TPM2 VAV20
20
40
60
80
100
(a)
Ca2+ TPM2 VAV20
20
40
60
80
100
120
140
(b)
Ca2+ TPM2 VAV20
20
40
60
80
100
120
(c)
Fig. 5. Boxplots of the intensity distribution of E-cadherin (HECD1),
junctional actin (J-actin) and non-junctional actin (NJ-actin) for the positive
control (Ca2+) and the proteins Tropomyosin-2 beta (TPM2) and VAV-2
oncogene (VAV2).
The method proposed here has shown its usefulness in
identifying modulation of the levels of cell-cell adhesion
receptors and changes in cytoskeleton caused by removal
of specific proteins from cells. The data suggest that, upon
5. 5
depletion of TPM2 or VAV2, cell-cell contacts are not very
stable and cadherin levels at junctions severely perturbed
as shown by a strong reduction in HECD1 levels. Potential
explanations are, in the case of TPM2, that stabilisation of
actin filaments adjacent to cell-cell contacts are an important
point to stabilise the membrane at junctions and clustered
cadherin receptors in place. Regarding VAV2, its downstream
partner Rac1 is well-known to regulate actin recruitment to
cadherin receptors engaged in adhesion. Thus by removing
VAV2, it is feasible that Rac1 cannot be activated and thus
unable to stabilise contacts by providing actin to support
adhesion. Consistent with this, VAV2 depletion lead to a partial
reduction in the actin levels in their respective images.
Once validated with further controls and other samples, the
methodology proposed here will be very useful to provide
automated quantification of large datasets and accelerate the
analysis of high-throughput screens.
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