Intro
Hello everyone, this is my first attempt at writing a blog. I would like to dedicate this mostly to scientific discussions and focus on scientific imaging, flow Cytometry and clean room usage for biological applications. Emphasis will be laid upon discussing various options for imaging and image analysis; also various imaging platforms will be compared. The stem cell instrumentation foundry (SCIF) at University of California (UC), Merced will feature in most of the posts as it is the place of my work and most of my imaging and clean room experiences that I share will be using the instruments at SCIF. Feedback is welcome, spam not. Images and experiences from my previous work place; Dr. Alejandro Calderon Urrea’s laboratory at California State University, Fresno will also be featured in the blog. Without further ado let us delve into the first topic of interest which includes fluorescence microscopy, confocal imaging and why it is important for most of the bright field imaging applications.
Microscopy has evolved in leaps and bounds since the reconfirmation of Anton Von Leeuwenhoek’s observations using a modified version of the then existing model by Robert Hooke. Light microscopy in particular has advanced to a stage where microscopes are put into use to image nanoscale particles. Bright-field microscopes are widely employed for fluorescence studies but the major drawback of a conventional microscope is the excessive background that makes the specimen of interest look blurry. Confocal microscope gives sharper images as it eliminates most of the background as light passes through a pin-hole which blocks excess light and allows for the light to pass only through the pin-hole. Galvanized mirrors help focus light on the sample and in turn eliminate any unwanted exposure. Lasers are used for fluorescence applications as they provide a more stable source of light and also are very specific of the wavelength of light being focused on the specimen. Solid state lasers are used for Confocal applications nowadays and this provides a marked advantage as the intensity of laser remains stable for extended periods of time which makes Confocal imaging suitable even for extended time lapse applications. The beauty of a Confocal system is that it can be built around a simple microscope and customized based on the application of the user. Lasers, objectives, software modules and filters can be added based on the user’s needs. The resolution of a confocal microscope is greater by a factor of 1.4 and a confocal microscope is optimal for high speed scanning and ruggedness which makes it an ideal source for 3D imaging.
Most of the software used for confocal imaging renders 3D volume view and analysis possible and this has led for the increased usage of Confocal in developmental and neurobiological studies. Addition of temperature and growth controlled chambers to Confocal microscopes has improved live-cell imaging; in addition, advanced shutter systems and software help control laser exposure and intensity making it easy to monitor developmental processes for an extended period of time. Personally, I have worked with various live and fixed specimens for confocal imaging. A few examples include Algae, Nematodes, Zebra fish, Fungi, Drosophila, mouse and human stem cells. I will try to blog regularly and will start posting on the various techniques/modifications used for imaging different kinds of samples. Please post your views on using microscopy as a tool for your research needs and also any useful information that might be helpful for others in their research.
What Different Flow Cytometer Parts Do
Flow cytometer is an equipment used to carry out the process of flow cytometry normally shortened as FCM. It is a technique used to count and examine microscopic particles like cells and chromosomes. It is done by suspending particles to be counted in a stream of fluid and passing them over an electronic apparatus, which detects them. This technique also allows sorting, protein engineering and biomarker detection in particles.
It permits multi-parametric analysis of both chemical and physical characteristics of particles in parallel. This analysis takes a few seconds and can be applied on hundreds of particles. Cytometer equipment was invented in the United States in the late 50s and was patented by the discoverer. It has passed through several phases of refinement and modification to generate the modern day high quality version. The original name has changed a few times too.
When the equipment is in operation, wavelengths are directed on hydro-dynamically focused stream of fluids. Detectors are focused at the place where the stream of fluid passes through the ray of light. Each suspended particle whose radius is 0.2 to 150 micrometers passing through the ray scatters light beams. Fluorescent chemicals inside or on the speck could be excited to discharge longer light wave-lengths than the light source.
Detectors capture the combination of scattered and fluorescent light. Through proper analysis of fluctuations in light intensity at each detector, different kinds of data concerning physical and chemical structure of elements may be deduced. Some cytometers only apply light scatter to analyze particle properties. Others produce images of scattered light, fluorescence, and transmitted light of each particle passing on the detection appliance.
Modern equipments perform analysis of many particles in a second in real time. They can separate and isolate particles with particular attributes. They resemble microscopes only that they offer high throughput and automatic quantification of set parameters. In order to analyze a solid tissue, a suspension of a single cell has to be prepared first.
Flow cytometers have five main components. These components consist of a measuring system, flow cell, amplification system, a digital to analogue conversion system and a detector, and a computer system. A computer system is for analyzing the signal created. The amplification system may either be logarithmic or linear. The flow cell transports and aligns cells to pass as a single file through the ray of light to be sensed.
Detectors and conversion modules are used to produce FSC, fluorescence, and SSC signals from light rays into electrical signals that are capable of being analyzed by a computer. Commonly utilized measuring systems are for optical and impedance systems. Computers are normally physically connected to the device and interfaced using a software. Such software are able to adjust parameters such as compensation and voltage of whatever substance is being tested.
Normally before analysis is carried out on a flow cytometer, information needs to be gathered first. The process of gathering data is referred to as acquisition. It aids to set parameters correctly to evade mistakes. Current products have most constituents in multiples to improve speed and efficiency in operations.
If you require more information on a flow cytometer, you can access our homepage instantly on the Web. Find out all you need to know about flow cytometry by reading this post http://www.stratedigm.com today!
Tidbits of wisdom from my PI & the grad students in my lab:
(paraphrased)
By all means, you should be passionate about your work, but you shouldn’t let your work define you. In other words, don’t take successes and failures personally. It’s just science.
Also, don’t stain the FMOs when you’re doing flow cytometry.
And don’t spill precious preterm blood samples.
The Daily Dongle: Overton or SED, which to use for determining percent positive?
flowjo.typepad.comThere are a lot of ways to decide what comprises “positive” in flow data, statistically. All available methods begin by binning the data - counting the number of events that fall into discreet ranges. This can be visualized in one dimension as a histogram. The X-axis units are bins, and the Y-axis are the number of cells in each bin. FlowJo divides the data into 1024 bins of equal size by default. To compare whether two samples have a statistically different distribution, or figure out where “negative” ends and positive begins using a control for reference, one must eliminate differences caused simply by having more events in one tube than the other. This can be achieved though “normalization”.
The Overton method is one of the original methods applied to cytometric data for calculating “positive” in unimodal distributions. It is popular because it is easy to understand and works reasonably well. The process for normalization in the Overton method is to find the mode (the bin that has the most cells in it) of each tube and divide the data from that tube by that value. This puts the data on roughly the same scale (0 - 100%) while preserving features. The Overton method then subtracts the control data from the comparison tube and counts the number of events that remain per bin, labeling these “positive”.
The SED method has never been published. There is a link for a paper written by Bruce Bagwell (the person who created the SED method, among other things) at the bottom of this article that sums up the algorithms that lead to the SED method…but he never actually says specifically what the SED does differently. What we’ve put in FlowJo is essentially the Enhanced Normalization Subtraction Method (ENS) which is very similar to the SED (it lacks some correction factor). The difference between ENS and Overton is that the normalization is better - the control and test algorithms are normalized so that they have the same area. This protects the user from bad normalization due to one outlier bin having a huge number of events in it, usually due to a data artifact. One bin with a huge number of cells would cause normalize one of the tube to a huge number and would then make the scales very different, resulting in a huge number of events to be labelled positive. The ENS also estimates the probability distribution function of the positive population, and aligns it to the data using the point of maximum difference between samples. By estimating the shape of the positive population, the algorithm is less likely to create a poor fit because of noisy data.
So overall what is called the SED method in FlowJo is superior to the Overton method because it factors in some safety precautions for data artifacts. For really nice clean data, there should be almost no difference between the two methods.
Download SED paper by Bagwell.
- Bad Mo’Flow
Send comments and questions to John@treestar.com
Compensation
drmr.comGood article about Compensation method in flow cytometry
