Congratulations and thank you for providing feedback on our Genome Sequencing Survey:
You have spoken and we have listened. ReaderFit.com has been updated to include some new features:
That is it for this update. We’ll keep you posted on our next update soon which we are already working hard on =)
-The ReaderFit Team
ReaderFit.com, our online ELISA analysis web application, has undergone a facelift with a host of new features.
Here are some of the biggest changes:
Sign up for a free account today and get started!
* Available only on the Pro Plan.
Luminex Corp. has discontinued the production of the polystyrene xTAG microspheres (formerly known as FlexMAP) for the magnetic versions which have new tags associated with them. This makes the current version of the xTAG tools for SmartNote obsolete so the MiraiBio Group has deactivated the software and will no longer support the application. We apologize for any inconvenience this may have caused.
-The MiraiBio Team
Please read this important announcement in order to avoid an interruption to your supply of the following products which are related to the Luminex 100/200, Bio-Plex 100/200, MAGPIX and FlexMAP 3D instrumentation:
We regret to inform you that Hitachi Solutions America, Ltd. (HISAL) must stop accepting orders for the above mentioned products at 12:00pm PST on December 27th, 2011**. HISAL has the most competitive prices for most of the products affected and due to the long shelf life of some of the products (up to 3 years) you may want to consider purchasing extra inventory at our competitive prices before our distribution rights end.
Please be aware that the product descriptions, part numbers and prices for the affected products will change when you source them from another supplier. You can contact HISAL at info@miraibio.com to receive a matrix that correlates HISAL product descriptions, part numbers and prices to the manufacturer’s respective descriptions, numbers and prices.
We greatly value your business and will do our very best to facilitate the transition to a new supplier of the products affected by this announcement.
Thank you again for your business and loyalty. We look forward to serving you with HISAL products and services in the future.
Regards,
The MiraiBio Group of Hitachi Solutions America, Ltd.
**After December 27th, 2011 we recommend that you purchase these products directly from the manufacturer, Luminex Corporation. In order to facilitate the transition, Luminex Corporation has assigned 2 contacts, Debra Asgari and David Mendoza, to handle any inquiries, process initial orders and communicate the ordering process for ongoing orders:
Debra Asgari – dasgari@luminexcorp.com or 512-381-4386
David Mendoza – dmendoza@luminexcorp.com or 512-381-4302
Updated: View “Reduce cost and length by 50% or more on whole-genome sequencing projects” webinar.
Although sequencing technology and price performance per base-pair-sequenced continue to advance at an impressive rate, Finished whole genome sequencing projects are still costly and lengthy endeavors. Next Gen sequencing technology (and even next-next gen technology) isn’t addressing some of the common issues faced with creating a “Finished” quality genome, namely Contig Placement, Gap Closure and Validation. Addressing these issues takes several months and a substantial amount of the budget in a sequencing project.
Consider the current workflow for generating a Finished whole genome in the figure below.
As you can see, generating the initial sequence data is no longer the bottle neck. Small genomes can be sequenced using shot gun methods in a couple of days. After the initial assembly the hard part starts: Closing gaps between your contigs, navigating regions with a high number of repeats, resequencing for validation etc. These tasks can represent over 50% of the length of a sequencing project and over 50% the cost!
I wanted to see if other researchers had found novel and/or more cost effective ways of dealing with these challenges. Especially labs that are resource constrained. I came across an interesting paper titled Finishing genomes with limited resources: lessons from an ensemble of microbial genomes that was published last year in BMC Genomics1. It discusses how using Whole Genome Mapping technology, also called Optical Mapping, can significantly reduce the length of sequencing projects. Before we get into what the paper presents let’s learn more about Whole Genome (Optical) Mapping.
Whole Genome (Optical) Mapping is a de novo process that generates whole genome, ordered, restriction maps with no requirement for previous sequence information & provides a comprehensive view of genomic architecture. An Optical Map or Whole Genome Map (WGM) is displayed in the unique MapCode™ pattern below where the vertical lines indicate the locations of restriction sites, and the distance between the lines represent the fragment size.
The WGM acts as a scaffold for your sequencing project. How? The contigs generated from your sequence assembly are converted to Optical Maps in silico and then are aligned and assembled to the de novo WGM. The WGM acts as an independent validation tool for contig placement and length of repeat regions while also helping to easily identify gaps in your assembly. By taking unordered sequence contigs and aligning them to an ordered WGM you quickly orient the contigs. When aligned, you can then identify any possible misassemblies that may have occurred in the initial assembly portion of your project.
You might be wondering how the scaffold concept as it applies to Whole Genome Mapping is different from scaffolds obtained with mate-pairs. To quote Nagarajan et al in the paper referenced above “It should be noted that unlike scaffolds obtained with mate-pairs, the scaffolds here are genome-wide and one per genome and therefore well suited for finishing efforts.”(p3) Additionally “While paired-end reads can be invaluable to scaffold contigs, they provide local order information [only] and using them to recreate a genome wide ordering of contigs is computationally challenging.”(p7) Finally “In addition, for time-critical applications in a biodefense or clinical setting, the time to construct paired-end libraries can be a limiting factor. In such settings, Optical Restriction Mapping [22], a form of ordered restriction maps (see Figure 5), can be a promising alternative as it can quickly provide genome wide restriction site information that can be used to order and orient contigs [8].”(p7)
We are starting to get a picture of how using just one single WGM can save time and reduce the need for computationally intensive bioinformatic steps thereby saving money. Let’s look in more detail about how these time savings are gained.
Contig Placement and Validation
With shotgun sequencing, genomic rearrangements, like inversions, can be missed due to incorrect reconstruction of repeats. A WGM can help you validate your whole genome and identify any possible inversions, insertions, translocations and deletions that sequencing may not have identified. In the example below the contiguous map in the middle was generated de novo using Whole Genome (Optical) Mapping technology. The contigs were generated in silico. Notice the missassemblies for example in Contig980. You can see an example of an inversion in Contig1253. You can also see examples of insertions, deletions and run of the mill gaps that will have to be spanned in resequencing efforts.
Gap Closure
Another example Nagarajan et al describe is using WGMs to reduce the number of PCR experiments needed. “Working with the original assembly (59 large contigs) could have necessitated on the order of 592 ≈ 3000 PCR experiments.” (p4) That’s a lot of PCR kits and a lot of time. Using WGMs as scaffolds, they were able to finish the genome using only 43 PCR experiments and 26 sequencing reactions to close 33 of the gaps. “From a finishing perspective, these (Optical Mapping) scaffolds are particularly useful, as for a set of n contigs, they help reduce the number of PCR experiments needed from roughly n2 to n.” (p7)
Let’s go back to our original figure describing the steps and average time to complete a sequencing project, this time comparing current methods to a workflow that uses a WGM.
As you can see, using a WGM as a scaffold reduces the time significantly by eliminating or greatly reducing the dependence and cost of generating paired-end libraries not to mention the bioinformatics muscle that is required with that approach. Plus having an accurate understanding of the gaps that need to be spanned in resequencing efforts reduces the number of PCR reactions thereby reducing the time and cost of gap closure. Finally the nature of having one whole, ordered contiguous scaffold makes validation inherently easier.
Currently there are many limitations when doing whole-genome sequencing projects. These issues include, but are not limited to: fragmented output of genomes, misassemblies of repeat regions, and limited resources to run these experiments. I’m confident that someday in the future sequencing technology will advance to address these issues. In the meantime Whole Genome (Optical) Mapping acts as a complementary technology to significantly reduce the time and cost associated with the issues discussed in this article.
Learn more about Whole Genome (Optical) Mapping and how to obtain a WGM for your sequencing project.
1 Finishing genomes with limited resources: lessons from an ensemble of microbial genomes. Nagarajan et al. BMC Genomics 2010, 11;242. Pubmed link
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The MiraiBio group of Hitachi Solutions America, Ltd. (HISAL) has partnered with ELISAlink.com to offer ReaderFit.com, a free online curve fitting tool for ELISA analysis, to ELISAlink.com users.
ELISALink.com is an online ELISA community, knowledge base and e-commerce site focused on serving the global ELISA Industry. The site will be anchored by a community-generated ELISA knowledge base and discussion platform and also feature direct access to a wide range of ELISA kits, components, equipment and services.
ReaderFit.com is a free online curve fitting application that allows users to both fit curves and optionally interpolate unknown values off the curve. Users upload response and independent values and then choose from one of 6 model equations: 4PL, 5PL, Quadratic, Log-Logit, Log-Log or Linear and one of four optional weighting algorithms: 1/Y, 1/Y2, 1/X and 1/X2. The resulting curve image and calculated results can then be easily exported from the web application.
“ELISAlink.com is an exciting concept that leverages “web 2.0” and social media features in a way that has been missing in the life science community. People in general have come to expect and rely on some of things that ELISAlink.com offers in other parts of their life. ELISA researchers now have a place to go for all of their ELISA needs. We are excited to offer ReaderFit.com as added value at ELISAlink.com,” said Robert Lynde, Deputy Director of the MiraiBio Group of HISAL.
“The team at HISAL really got it right with ReaderFit. The program is intuitive and designed from the perspective of an ELISA user, providing a streamlined and easy to use platform that is an invaluable tool to researchers and clinical users alike. The powerful Desktop Edition and the 21 CFR Part 11 compliant Security Edition were complimented earlier this year with a completely Online Edition – a natural fit for ELISAlink.com and our mission to provide the best and most powerful ELISA resources on the web,” said David Barka, Founder of ELISAlink.com
Want to be the first to know when ELISAlink.com is launched? Sign up to receive email notifications and qualify for rewards!
Are you looking for a faster and more accurate method of strain typing? Optical Mapping could be your answer.
Optical Mapping produces high coverage, ordered, restriction maps based on hundreds of markers across the entire genome. An Optical Map offers increased accuracy and provides more genomic information than strain typing with alternative methods such as PFGE.
Below you can see a comparison of Optical Mapping and PFGE. Because Optical Maps contain hundreds of markers across the entire genome researchers obtain a much higher resolution compared to other technologies. This enables better strain discrimination among other advantages.
How are researchers using Optical Mapping?
Several clusters of Salmonella Typhimurium infections appeared in Denmark in 2008 and 2009. The paper Molecular characterization of salmonella typhimurium highly successful outbreak strains published in the Foodborne Pathogens and Disease journal discusses how Optical Mapping was able to show that the strain in the largest cluster did not contain an increase content of virulence genes. However Optical Mapping did find a large insert, which was most likely a prophage, in one of the strains. The knowledge of this insert, which may confer a competitive advantage for that strain, is valuable information for epidemiologists.
In a paper titled A sustained hospital outbreak of vancomycin-resistant Enterococcus faecium bacteremia due to emergence of vanB E. faecium sequence type 203 published in the Journal of infectious Disease, researchers, with the aid of Optical Mapping, analyzed samples of Enterococcus faecium collected over a 12 year period. The results showed that over this time the strain acquired the vanB locus which resulted in an epidemic clone that exhibits vancomycin resistance.
In the figure below you can see the Optical Map similarity cluster of the German Enterohemorrhagic Escherichia coli O104:H4 outbreak of May 2011.
Figure. Optical Map similarity cluster of German EHEC O104:H4 outbreak.
Optical Mapping played a critical role in identifying and tracking strains in this outbreak. The paper Prospective Genomic Characterization of the German Enterohemorrhagic Escherichia coli O104:H4 Outbreak by Rapid Next Generation Sequencing Technology was published about this outbreak and discusses how Optical Mapping accelerated the characterization of the various strains and isolates collected.
The paper Optical genetic mapping defines regions of chromosomal variation in serovars of S. enterica subsp. enterica of concern for human and animal health published in the journal of Epidemiology and Infection discusses how optical mapping was used to establish 2 geographical lineages (based on the presence of prophage sequences) of strains of Salmonella enterica subsp. enteric.
Some of the differentiating technical advantages of Optical Mapping are:
How can you access the Optical Mapping technology?
Recently Hitachi Solutions America, Ltd. partnered with OpGen Inc. to offer the MapIt® Optical Mapping Service to its customers. Click here to learn more about Optical Mapping and the MapIt Optical Mapping Service. You can also view a webinar that describes Optical Mapping and its key application areas.
Hitachi Solutions has expanded its agreement with OpGen Inc. to offer MapIt® Optical Mapping Services to its US customer base. Hitachi Solutions has already launched the MapIt service in Japan and this move shows increased confidence in OpGen’s Optical Mapping technology.
Optical Mapping is a novel and de novo process that generates whole genome, ordered, restriction maps with no requirement for previous sequence information & provides a comprehensive view of genomic architecture.
Optical Mapping applications include:
“We are very excited to bring this new technology to our customers. We feel Optical Mapping offers great value, in terms of time and money saved in its key application areas, along with increased accuracy of results.” said Robert Lynde, Deputy Director, MiraiBio Group of Hitachi Solutions America.
Optical Mapping is currently limited to smaller bacterial, yeast and fungi genomes however OpGen is rolling out large genome support later in 2011.
Learn more Optical Mapping and the MapIt service.
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The Luminex and Bio-Plex platforms output 2 major pieces of data from an acquisition: MFI and bead count.
Let’s focus on MFI which stands for Median Fluoresence Intensity and NOT Mean Fluorescense Intensity.
Why do we use median and not mean?
Simply put, the median statistic is less sensitive to outliers where there is an inherent carryover of about 0.9% from these instruments. That is one of the reasons why Luminex recommends at least a minimum bead count of 35 to get statistically significant data but 50-100 is strongly suggested.
Here is an oversimplified example of why median is preferred over mean. Let’s say we are running a 1-plex with just 2 samples: A high control (well A1) and a low control (well A2). We have set a minimum bead count of 11. You will see in a second why I chose this odd number (no pun intended).
When we push the Acquisition button on our imaginary instrument, it begins reading well A1 with our high control and reads the following fluorescence intensities of 11 individual beads:
7833, 7609, 8335, 6900, 7354, 7234, 8120, 7777 (jackpot!), 7158, 7982, 7083
To figure out the median value, let’s place these readings in numerical order and the middle reading will be our median value.
6900, 7083, 7158, 7234, 7354, 7609, 7833, 7777 (jackpot!), 7982, 8120, 8335
Since we have an odd number of beads, the median value is simply the middle number which in this case is 7609. If this were an even count, we would have to take the average of the middle 2 readings after they are placed in order but that would just be too much work for me to do for this example. 7609 is the MFI value that this instrument would report for this particular analyte in well A1.
After the instrument reaches the minimum bead count for well A1, it moves on to well A2. (The probe actually goes back down in well A1 and spits out some of the leftover sample plus some additional sheath fluid but there is still a good chance there will be left over beads from A1.) Let’s say our imaginary instrument reports the following fluorescent intensities for A2 (our low control):
8001, 209, 7315, 199, 189, 217, 207, 186, 188, 208, 7917
Let’s place these readings in numerical order to figure out the MFI:
186, 188, 189, 199, 207, 208, 209, 217, 7315, 7917, 8001
The MFI value for the same analyte (we’re only doing a 1-plex) in well A2 is 208. Note though, that we had 3 pretty high readings (7315, 7917, 8001) that were most likely carried over from well A1. 3 out of 11 or 28% carryover is insanely high but I just wanted to illustrate this point that even though we had 28% carryover, we still have a respectable median (or MFI) value of 208 =)
If we used the mean fluorescence intensity, our value would be 2258 which is just bananas!
So in conclusion, the median statistic is preferred over the mean because the median is less sensitive to outliers or beads that are carried over from a previous well.
Thanks for tuning in!
If you have any questions or would like an explanation on other aspects of the Luminex technology feel free to comment below and we’ll try our best to address them!
