BioTechniquesVol. 62, No. 5 Tech NewsOpen AccessGoing with the flowNathan BlowNathan BlowPublished Online:16 Mar 2018https://doi.org/10.2144/000114543AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit AbstractFrom bacteria to circulating tumor cells, advances in flow cytometry technology are pushing the boundaries of cell biology research. The human gut is an amazing environment containing millions upon millions of bacteria interacting with one another. We are now learning that these microscopic inhabitants also interact with our own cells in a myriad of ways. Recent studies have revealed that intestinal bacteria play essential roles in human health, and alterations in the relative abundances of different bacterial species can lead to significant health changes or even cause disease.Understanding the ways in which these different microbes interact and the roles that they play in shaping human gut functions has become a cornerstone of many research efforts, leading to new insights in our understanding of the microbiome. But sorting through this vast array of bacteria requires technologies capable of isolating and sorting specific subpopulations based on certain characteristics. This is the reason that flow cytometry has emerged in recent years as a crucial technology platform in the field of microbiomics.Sensing a changeAs gut microbes go about their basic functions, they produce a variety of signaling molecules that are used to communicate with other bacteria and human cells. The timing of when these signaling molecules are released and exactly how other cells respond to specific microbial signaling cues are largely unanswered questions that many researchers would like to study in greater detail.The strategy of using modified bacteria possessing engineered sensors to "eavesdrop" on communications between the inhabitants of microbial environments got its start nearly a decade ago. Recently, researchers from Rice University and Baylor University in Texas took advantage of this idea to engineer a novel strain of bacteria that could report on the intracellular levels of two key metabolites in a mouse model of colitis (1). Even though mounting data show mammalian gut function is regulated through cross-talk between host cells and resident bacteria, deciphering this cross-talk and the signaling molecules involved has proven to be quite a challenge.The Rice and Baylor groups, led by bioengineering professor Jeffrey Tabor, were curious about the role sulfur-reducing bacteria present in the gut might be playing in the emergence of colitis. The researchers identified two sensors, one for the metabolite thiosulfate and the other for the metabolite tetrathionate, which they were then able to engineer into gut-adapted E. coli strains possessing fluorescent markers. Tabor's team was particularly interested in assessing changes in thiosulfate and tetrathionate levels since these metabolites can be used as a measure of the levels of sulfur metabolism in the gut. By attaching green fluorescent protein (GFP) to each of their engineered sensors, the researchers could measure changes in fluorescence levels as a proxy for sulfur metabolism status in the mouse gut. To quantify the numbers of the engineered fluorescent bacteria responding to the metabolites during the experiment, the research team turned to a flow cytometry workflow.Researchers used flow cytometry to sort circulating tumor cell (CTC) populations in blood to better understand the mechanisms underlying tumor metastasis.Credit: D. Marchetti.Flow cytometry data showed that when it came to inflammation in the colon, output from the thiosulfate sensor was elevated, implying that sulfur metabolism was indeed involved in the colitis seen in the mouse model. Based on this result, Tabor and his co-authors suggested that thiosulfate might be a useful biomarker for inflammation and colitis in the future.In their study, Tabor and his colleagues were able to specifically engineer thiosulfate and tetrathionate bacterial sensors that could in turn be isolated using flow cytometry. But the approach they took in developing their sensors is actually more robust, and could be applied to generate other bacterial metabolite sensors in the future, opening up microbiome studies for a greater range of biological processes and phenotypes in the gut.Multiple colors, multiple differencesFlow cytometry technology can be used to quickly detect and isolate specific cell types within a sample, especially if the cells are labeled with GFP or another suitable visual marker. But that's only the start of what flow cytometry is capable of doing these days when it comes to cell selection. In fact, many researchers and methods developers would argue that the true value of the technology lies in its multidimensional capabilities—where more colors mean more data.The development of multi-parametric flow cytometry instrumentation and technology has proceeded at a rapid pace in recent years. Back in 1970s and early 1980s, only two fluorescence parameters could be sorted during a flow cytometry experiment. It was not until later in the 1980s, following the discovery and development of new fluorochromes along with enhancements in laser technologies and new software for experimental analysis, that flow cytometry entered its next phase of evolution—a period where the number of fluorescence parameters that could be sorted during a flow cytometry experiment grew on a nearly annual basis.Flow cytometry systems, such as the one above from ACEA Biosciences, are now capable of sorting and analyzing multiple cell parameters in a single experiment.Credit: ACEA Biosciences.Today, most commercially available flow cytometry instruments have the capacity to sort cells based on 8 to 13 different parameters, with the current state-of-the-art being able to take advantage of 18 different colors for cell sorting. Moving beyond 18 colors is not possible at the moment due to the current number of different fluorophores that can be spectrally resolved by available lasers. However, developers have found some ways to get around this limitation. Mass cytometry is a technique that combines flow cytometry with mass spectrometry to analyze more than 40 parameters in a single experiment without the need for fluorophores. Still, even given the current color limits, these latest advances in flow cytometry technology have made it possible for researchers to isolate and study very specific cell types, and even subsets of cell populations, to glean unique information on cell composition and abundance for fields as diverse as immunology and cancer research.Singling out cellsCirculating tumor cells (CTCs) are found in the bloodstream and have been implicated to play roles as "seeds" of fatal cancer metastasis. As such, identifying these cells and understanding their roles in metastatic onset could prove critical for detecting the presence of cancer as well as for monitoring disease progression in those patients being treated with specific therapies.In 2015, Dario Marchetti from the Houston Methodist Research Institute in Texas and his colleagues reported on the use of flow cytometry to isolate CTC subsets possessing properties related to breast cancer dormancy (2). The idea was to compare CTC populations from patients with breast cancer metastasis to those without metastasis in an effort to identify difference in their circulating tumor cell profiles. The use of multi-parametric flow cytometry made it possible for Marchetti's team to identify different CTC cells by their unique phenotypic properties, including adhesion, proliferation, and invasion, using reagents that targeted the expression of specific cell-surface markers."Multi-parametric flow cytometry offered us an excellent tool with which to both isolate and interrogate CTC populations," explains Marchetti, who also directs the Biomarker Research Program Center at Houston Methodist. It's important to note that developing robust assays to interrogate numerous cellular parameters during a flow cytometry experiment requires time and effort for optimization. But it turns out that Marchetti's lab has actually been using flow cytometry to explore CTC biology for a number of years now. "Flow cytometry experiments have allowed us to isolate rare cells, including CTCs, that often cannot be captured with the same high level of rigor using other methods."CTC discoveriesTwo years earlier, Marchetti's lab was already applying flow cytometry in cancer studies. At the time, it was known that breast cancer was one of the most common cancers to metastasize to the brain, and Marchetti wanted to understand the mechanisms causing this outcome.Applying a multi-parametric flow cytometry approach, Marchetti's group uncovered CTCs in patients that were not expressing the common carcinoma epithelial cell adhesion molecule (these are classified as EpCAM-negative cells) and possessed a gene signature important for brain cancer metastasis (3). Further work revealed that these cells promoted breast cancer brain metastasis when injected in xenografts.Marchetti suspected that most of the other commercially available approaches being used at the time to isolate and characterize CTCs would not have been able to capture specific CTC subpopulations found to be associated with brain cancer brain metastasis."We needed alternative methods to the established approaches for CTC enumeration, such as CellSearch, and we realized then that a flow cytometry workflow would provide the ideal solution here," Marchetti recalls.Spurred by their EpCAM-negative CTC capture, Marchetti's team became increasingly curious about the roles that other CTCs might be playing in breast cancer metastasis, cells that he refers to as "flying under the radar" of detection for many technologies in the way that EpCAM-negative CTCs had previously.It's critical to note that CTCs are exceedingly rare in blood samples, making their isolation that much more challenging. Add to this the fact that Marchetti was now focused on further subdividing CTCs by tumor origin and proliferative capacity, and it's clear he needed to develop a robust multi-parametric flow cytometry strategy for narrowing down any CTC associations with breast cancer brain metastasis.For his most recent study on breast cancer, Marchetti employed a multistep approach for hunting unique CTCs. First, the team isolated CTCs based on EpCAM agnostic status and epithelial versus stem-cell-like properties. From there, a combination of six different surface expression markers were assayed to classify the functions of the various CTC subsets found. Finally, isolated CTC subsets were investigated to determine gene expression profiles and biomarker pathways, similar to how EpCAM-negative CTCs had been studied 2 years earlier. When all was done, Marchetti's team was able to use the data from their CTC isolation and characterization efforts to start dissecting apart the molecular pathways and mechanisms involved in CTC brain organ-homing and, thus, better understand breast cancer CTC characteristics in relation to brain metastasis onset (i.e., detectable by MRI as accepted standard of care compared to tumor progression). The next step, according to Marchetti, will be to identify biomarkers associated with breast cancer CTCs that can be used in the detection and monitoring of cancer progression along with therapy decisions and evaluation of therapy efficacy.Dario Marchetti from Houston Methodist Research Institute has been using flow cytometry in his breast cancer research studies.Credit: D. Marchetti.In many ways, flow cytometry can be thought of as a re-emerging technology. While the basic technique is well-established, its use in the lab today is moving beyond simply separating and sorting cell populations. And as flow cytometry technology continues to advance in the years to come, with more researchers seeking to dissect cell populations and their interactions, our understanding of the cellular world will only continue to grow.References1. Daeffler, K. et al.. 2017. Engineering bacterial thiosulfate and tetrathionate sensors for detecting gut inflammation. Molecular Systems Biology 13:923.Crossref, Medline, Google Scholar2. Vishoi, M. et al.. 2015. The isolation and characterization of CTC subsets related to breast cancer dormancy. Scientific Reports 5:17533.Crossref, Medline, Google Scholar3. Zhang, L. et al.. 2013. The identification and characterization of breast cancer CTCs competent for brain metastasis. Science Translational Medicine 5:180ra48.Crossref, Medline, Google ScholarFiguresReferencesRelatedDetailsCited ByThe role of automated cytometry in the new�era of cancer immunotherapy (Review)20 August 2018 | Molecular and Clinical Oncology, Vol. 8 Vol. 62, No. 5 Follow us on social media for the latest updates Metrics History Published online 16 March 2018 Published in print May 2017 Information© 2017 Author(s)PDF download

At many research institutions, lab space is more valuable than gold. Developers are taking note by designing smaller instruments with enhanced capabilities. Nathan Blow looks inside today's tiny lab.

Technology developments are leading to rapid advances in ancient DNA analysis. Nathan Blow talks to researchers peering into the past through ancient DNA.

Nathan Blow looks at how efforts to create guidelines and scoring systems could change the way you buy antibodies.

New genome-editing approaches always receive widespread attention. But in the case of a novel Argonaute-based technique published last spring, attention has been particularly intense.

From lampreys to human stem cells, the CRISPR/Cas9 system is challenging our notions of what is possible with genome editing. Nathan Blow talks to researchers pushing the boundaries of CRISPR/Cas9 technology to expand our understanding of biology.

BioTechniquesVol. 56, No. 3 From the EditorOpen AccessShould we eliminate the Impact Factor?Nathan S. BlowNathan S. BlowBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000114139AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail The growing number of debates on the value of article and journal metrics got me thinking: Do we really need a metric such as the Impact Factor in this day and age? I mean, everyone knows that there are ways to "game" the citation numbers, right? Not to mention that such metrics are fairly simplistic, only taking into account citations received in a two- or five-year period.But, what are the alternatives? Here are a couple of ideas I have heard thrown around recently.1. Use the number of downloads and tweets, or other online metrics, in addition to citations. At first glance, this might seem a good way to go in the internet age. However, such calculations would simply generate another metric equivalent to today's Impact Factor—only on steroids. Similar to concerns raised about the current citation-based Impact Factor, online metrics would say little about the quality or influence of an article or a journal. What happens if there is a flaw in a research article that garners hundreds of thousands of downloads in the first week after publication? Can a download metric be adjusted in such a case? Another major issue is the timing of assessment. Downloads and tweets peak very quickly—most likely within the first month or two after publication and usually within a much shorter period than the two-year window used in a citation-based Impact Factor calculation. So, how could you account for someone who downloads an article once, but cites it in 10 subsequent papers over the next 5 years? Downloads might be a good measure of immediate interest—but they do not speak to quality or impact and therefore do not address the concerns of those advocating for the elimination of citation counts and Impact Factors.2. Articles should be judged on their own merit: Eliminate Impact Factors and ignore citations. Although an obvious and wonderful thought, pushing young researchers to focus on the true scientific value of an article does not mean all other publication metrics need to, or will be, eliminated. If journal Impact Factors and other citation metrics were eliminated, article downloads would likely take over as a de facto measure of quality in the face of nothing else. And if that were to go away, numbers of tweets and re-tweets would take over. And if that were gone…then, well, you get the point. There will always be a need to judge an article and discuss the importance of its findings in a public forum. But as noted above, there is not much value gained in these other, "trendier" measures.3. Use something different: Citations and Impact Factors do not reflect journal quality. Yes and no. Don't you find it interesting that journals, for the most part, do not fluctuate in Impact Factor/number of overall citations for published articles beyond their first five years? There are exceptions, but most journals settle into a particular Impact Factor range and then don't move much. Why? The most likely reason for this lies in the fact that scientists need some system for determining where to publish in an expanding sea of journals. Like it or not, Impact Factors and citation counts establish a journal "pecking order" that scientists themselves have created and continue adhering to, no matter how many open access start-up titles hang out a shingle on the internet. I strongly suspect that if we eliminated formal citation databases and Impact Factor calculations, nothing would change when it comes to this pecking order amongst established journals.So, do we need citation metrics and Impact Factors? I think we do, since it appears scientists need something on which to based their publishing decisions. However, we need to change the way scientists view such metrics: While it might be good to publish in a top tier journal with an Impact Factor of 30—if your article only gets 2 citations, what does this mean? And the opposite is also true—if the journal has an Impact Factor of 2, but your article receives 500 citations in 2 years, should you be penalized for where you publish? And fundamentally, what does it mean to get 2 versus 500 citations? The validity of any statistic or analysis tool depends on careful and appropriate application by an informed user. Maybe scientists need to look beyond sheer numbers towards the "community" impact of their studies. Here, network analysis showing the reach of an article based on a deeper citation analysis might provide stronger insights into its impact. Tenure committee members also need to look beyond the simple "30-versus-2" Impact Factor debate and use their experience and knowledge to see the true contribution that a scientist is making to their field and beyond—you cannot ask a young scientist to do something that you are not willing to do yourself! In the end, measures such as the Impact Factor are only "lazy" statistics because we make them lazy.FiguresReferencesRelatedDetails Vol. 56, No. 3 STAY CONNECTED Metrics History Published online 3 April 2018 Published in print March 2014 Information© 2014 Author(s)PDF download

BioTechniquesVol. 56, No. 2 From the EditorOpen AccessA Practical Perspective on MethodsNathan BlowNathan BlowBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000114127AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail This month, we are introducing a slightly new article format at BioTechniques, something that we will be calling a Practical Guide. The genesis of this article type was born out of discussions amongst the editorial staff on new ways to provide readers with additional insights and information on the latest techniques and methods, given the explosion of methods articles and new technology developments in recent years.The reason I say this is a "slightly" new article format is that Practical Guide articles are intended to be part review, part analysis, and part personal research experience with case study examples, all blended together to provide readers with a unique perspective on a specific area of methods development. For me, it is this last part, the personal research experience/case study discussion, that makes this Practical Guide format so important for the scientific community at this moment in time.Today, publishing "negative" results, reporting unsuccessful experiments, or documenting the challenges in implementing new techniques in the lab is not a common practice. It is well known that most journal articles report only the success stories. This leaving researchers with important cautionary tales on the limitations and potential drawbacks of a particular technique or protocol without an outlet to share their findings in a meaningful way. And what about all the trial-and-error effort that is invested in obtaining those new results? Shouldn't it be communicated to other researchers? Surely there is value to be gained from informing the scientific community of the steps that did not work in addition to those steps that produced a successful experiment.What the editors at BioTechniques came to realize was that by bringing some of that trial-and-error information to the readers, new solutions to experimental problems can be found, accelerating the speed of scientific discovery. Clearly, there is no need to repeat optimizations if another lab has gone through the process already. The Practical Guide format is designed to provide that extra guidance and insight into a particular methodology—from highly experienced and qualified methods developers who have used a variety of approaches in their own research— to hopefully prevent unnecessary repetition.The month, we are excited to launch our very first Practical Guide article. Authored by Steven Head and colleagues at The Scripps Research Institute, this article explores the latest methods and techniques in next-generation sequencing (NGS) library construction. Interest in NGS has expanded greatly in recent years, creating a truly important area for methods development. Focusing on sample preparation, an essential part of the NGS workflow, Head et al. discuss a wide array of techniques, protocols, and applications involved in optimal NGS library preparation. The article also documents the possible pitfalls and challenges one can encounter when constructing an optimized library for NGS from either DNA or RNA, based on the authors— own experiences working with a variety of sample types and sequencing applications.Our challenge when it comes to publishing Practical Guide articles is identifying authors who have extensive experience with different techniques and can provide unique insights into methodology. Fortunately, many developers have responded enthusiastically to this new format, so in the coming months you will see other Practical Guide articles in these pages focusing on NGS bioinformatics tools, super-resolution imaging, qPCR, and other important research methods. In addition, we would like to encourage potential authors who might be interested in writing a Practical Guide in the future to contact the editorial team to discuss suitable topics and how to submit an article proposal.It is our expectation that the Practical Guide format will provide a unique mechanism for researchers to discuss best practices in the lab and assist others interested in using a new technique or choosing the best technical approaches to meet their research goals.As always, we welcome your feedback, comments and opinions on this new article format at bioeditor@biotechniques.com.FiguresReferencesRelatedDetails Vol. 56, No. 2 Follow us on social media for the latest updates Metrics History Published online 3 April 2018 Published in print February 2014 Information© 2014 Author(s)PDF download

BioTechniquesVol. 56, No. 1 From the EditorOpen AccessA Simple Question of ReproducibilityNathan S. BlowNathan S. BlowBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000114117AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Embracing the dark sideOne of the things that we pride ourselves on at BioTechniques is providing simple methods developments that can be implemented in the lab immediately. Maybe this makes us throwbacks—"old school" so to speak. But it seems that life science research is becoming so complex at the moment that it is now difficult to reproduce major scientific results between labs. At least this is better than the alternative explanation, that fabricating or "massaging" data have become common practices amoung researchers. Either way, the lack of reproducibility is a serious problem at the moment that needs to be addressed by life scientists.The troubling trend of irreproducibility, which has been brewing for some time now, came to a head for many with the publication of a commentary in the journal Nature by Begley and Ellis finding that the results of 47 out of 53 studies could not be replicated. These preclinical studies formed the basis for other research studies and in some instances were the starting points for costly drug studies. Begley and Ellis are not alone in their findings— other reports have surfaced in recent months highlighting the problem of irreproducible studies.Recently, a group called the Global Biological Standards Institute (GBSI) presented a report making a case for biological standards. In interviews with 60 key figures in the life science community, nearly 75% of those interviewed described having to deal with irreproducible data and/or results. The conclusion of the GBSI was that there is a need for more well-defined and consistently used standards, both material (reference reagents and chemicals) and written (optimal practices and methodologies).The Begley and Ellis commentary also brings to light another fundamental problem in life science today: researchers tackling projects beyond their fields of expertise. Preclinical and translational research have become the buzz-words of the moment, leading many investigators to search out ways in which to focus their grants on these types of studies. But what is the impact of this trend? Are these researchers sufficiently trained and equipped to perform the necessary experiments and analyze their findings in a meaningful way when it comes to clinical significance? Or are attempts to include the "right" buzzwords in grant applications in order to obtain funding dictating experimental design?The impact of irreproducible studies is particularly troubling for me as the editor of a methods-oriented journal. The manner in which methods are reported and detailed is critical to reproducing the findings of an article— researchers need to be able to replicate experiments 1, 10, or even 20 years after an article has been published. While it is a great to be able to go to another lab or exchange reagents to verify an experiment or study in the short-term, what happens over time? Researchers need to understand the methods they are using and document the manner in which they are being performed so that future generations can build upon the work that is being done today.In the end, science continues to grow more complex and more interdisciplinary. This is an exciting development, but it creates the need to modify traditional ways of thinking about grants, peer review, publishing, and experimental design. Specific steps, chemicals, and processes need to be documented. At BioTechniques, we will be taking additional steps during the peer review process to ensure that all of the information needed to replicate a method is presented in every report. In addition, we encourage authors to submit articles identifying "challenging" reagents—including the robust characterization of antibodies and or cell lines— as well as other potential roadblocks standing in the way of reproducibility.The creation of new standards in life science research is an important endeavor that requires care and thought. Researchers need to be cautious in designing their experiments and also report full experimental procedures and results. Journals should require complete methods descriptions, even if they appear as online Supplementary Materials, as this will provide a great first step towards reproducibility.It is interesting to note that at this moment of greater irreproducibility in life science, journals continue to minimize the space given to Materials and Methods sections in articles. Reporting the way in which experiments are performed should not be an afterthought. While the goal is simple—eliminating irreproducibility—getting on the right path could prove tough.FiguresReferencesRelatedDetailsCited ByRecommendations and requirements for reporting on applications of electric pulse delivery for electroporation of biological samplesBioelectrochemistry, Vol. 122Ten Simple Rules for Experiments' Provenance20 October 2015 | PLOS Computational Biology, Vol. 11, No. 10Polyalkoxyflavonoids as inhibitors of cell division4 March 2015 | Russian Chemical Reviews, Vol. 84, No. 2 Vol. 56, No. 1 Follow us on social media for the latest updates Metrics History Published online 3 April 2018 Published in print January 2014 Information© 2014 Author(s)PDF download

BioTechniquesVol. 54, No. 2 From the EditorOpen AccessCat's In the CradleNathan S. BlowNathan S. Blow*E-mail Address: nathan.blow@informausa.comBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000113984AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail "Dad, what is science?""Science? Well, science is the search for the truth. It's all about trying to understanding what surrounds us in our world.""Can I be a scientist?""Of course you can. In some ways, you already are: when you look out at the world, ask questions, and seek answers.""Science sounds fun. Let's make up some good questions right now!""Well, it's not so simple. First you have to observe. When you see something you think is strange, then you can ask questions like: why is this strange, or how did this become strange.""Like when we saw that platypus at the zoo?""Exactly.""So no making things up in science?""Right. Unless—""Unless what?""Well, say you observe something interesting, like that platypus. But maybe the next step in answering your question—say, how the platypus got its bill—is a little beyond your reach; you don't have enough information at the moment. But you know that your idea on how this occurred is correct. Even if you can't prove your idea, you can say that it's highly possible.""Possible?""Yes. When we know something is going to happen, we can say that there is a strong probability it will occur.""But, is that correct?""Of course it's correct. Sometimes, things are implied even if they are not known. It's okay to assume in some instances.""So, science can assume.""Sure. But, you need to realize that scientific inquiry can be tough; proving your idea can take a long time. Still, you need to make sure you get your ideas out to the scientific community as quickly as possible.""So, science is quick.""There will always be someone else doing the same work as you, so you also have to find a special angle to make your results stand out.""So, science stands out.""Of course, you'll need money to do your research, and that comes through grants. Grants today are impossible to get: NIH is only putting out $31 billion each year. So, you might have to say you have done an experiment when you haven't yet, or you might not do an experiment when you already know the result in order to get funding…you know, a little fibbing to get those much-needed dollars.""So, science can fib.""And sometimes, you might have to fight with your colleagues for proper attribution in an article: for example, to make sure you are the lead author. Proper credit is important.""So, science has fights.""Don't forget, you must publish your findings in only the highest-profile journals with the best impact factors, so that your work is seen and cited.""So, science is high-profile.""But always claim that doesn't matter. Say that you 'believe in open access' but keep publishing in the high-impact journals, of course. And be sure to disparage the impact factor as statistically inaccurate—that sounds popular and hip.""So, science is popularity.""And finally, when all is said and done and your career is well launched, make sure you stand on the shoulders of everyone who helped you better understand that world around you. After all, you are the one who spent years suffering for your love of science.""So, science is suffering.""You've got it. Any questions?""Dad—what happened to the truth?"As always, please share your thoughts with us by posting at our Molecular Biology Forums under "To the Editor" (http://molecularbiology.forums.biotechniques.com) or sending an email directly to the editors (bioeditor@biotechniques.com).FiguresReferencesRelatedDetails Vol. 54, No. 2 Follow us on social media for the latest updates Metrics History Published online 3 April 2018 Published in print February 2013 Information© 2013 Author(s)PDF download

BioTechniquesVol. 54, No. 4 From the EditorOpen AccessHistory LessonsNathan BlowNathan BlowBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000114003AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit Another new large-scale biology project is in the offing. The Brain Activity Map (BAM) initiative has gained the support of the Obama administration along with endorsements from several key scientists in recent weeks. However, doubts regarding the feasibility of mapping the human brain have been raised by prominent neuroscientists who argue that the technology to achieve this grand mission is currently lacking.As supporters and skeptics write perspective articles and blog posts about the potential of the BAM project and government officials figure out a way to fund it, this might be a good time to reflect on past large-scale projects for inspiration and direction. The Human Genome Project (HGP) is considered by many to be the high water mark for large-scale, collaborative efforts in biological research. Mapping the genome took more than a decade at a cost of nearly $3 billion dollars, which is very similar to the BAM time and cost projections. The HGP raced across the finish line in 2001 to great public and scientific fanfare. But how did scientists get to that finish line? It is crucial to insert the name J. Craig Venter here. Venter initiated a privately funded effort to complete a draft sequence of the human genome, employing a different mapping approach than used by the government funded project. That nudge likely led to a more rapid completion of the HGP and the combination of public and private data, produced a better initial reference sequence. In many ways, the HGP was similar to the two-team approach used by physicists in their quest to find the Higgs particle. This highlights the importance of pushing forward with large-scale projects.Venter approached the genome from a more commercial perspective. Such a viewpoint could be critically important when formulating large-scale biology projects. Involvement of biotechnology and pharmaceutical companies in these projects from the outset, although potentially tricky due to intellectual property issues, adds significantly to the potential future impact. Academics design experiments looking for basic biological insights, while pharmaceutical companies look for direct routes to healthcare applications' both of these approaches are very much needed and should be considered when planning a project the size of BAM.Another lesson for those scientists working on the BAM initiative can be seen in the recently completed phase of the ENCODE project. This massive effort by hundreds of academic scientists is reshaping how we look at genome structure and function. The amount of data is immense and will fuel discovery for years to come. But the presentation of results in the numerous ENCODE articles published at the end of 2012 also cast a shadow over how the project will be perceived in the coming years. Suggestions by the ENCODE authors that the majority of the genome is 'functional— are questionable, perhaps even over reaching, a point raised by non-ENCODE scientists in a number of recent articles. This is the trap of the large-scale project—large volumes of data lead to the desire to make big conclusions. This is not necessary—the data, methods and potential future importance speak for themselves. The HGP and ENCODE provide investigative frameworks and datasets that other researchers can build upon to advance science—empowering generations of scientists is the reason we fund these efforts in the first place.While the tools needed to complete the BAM might not be in place yet, that should not be a major concern; there are many great methods and instrument developers in the world who will rise to the challenge as others did for the HGP and ENCODE efforts. The potential of the BAM project is extraordinary—a map of brain activity would greatly enhance our understanding of what it is that makes us human. What is worrisome is that we might fail to build on our previous experience to make the impact of the BAM even greater. Project leaders would be well-advised to engage the pharmaceutical community in order to understand what aspects of the project could be directly translated for healthcare benefits. The data from the BAM effort should be presented rapidly and without over interpretation in an attempt to justify the expense and effort. In the end, it is important to realize that the HGP and ENCODE are the great biology initiatives for this generation of scientists—let's make sure BAM reaches its full potential and becomes part of the strong legacy we leave to the next generation of scientists.Please share your thoughts with us by posting at our Molecular Biology Forums under "To the Editor" (http://molecularbiology.forums.biotechniques.com) or sending an email directly to the editors (bioeditor@biotechniques.com).FiguresReferencesRelatedDetails Vol. 54, No. 4 Follow us on social media for the latest updates Metrics History Published online 3 April 2018 Published in print April 2013 Information© 2013 Author(s)PDF download

BioTechniquesVol. 55, No. 1 From the EditorOpen AccessCould the NIH payline be too high?Nathan S. BlowNathan S. BlowBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000114045AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail The paylines at the various institutes making up the NIH are near historical lows, making it increasingly competitive to obtain funding. This is partially due to the recent budget sequesteration, but is also a result of flat government funding levels coming on the heels of years of double digit growth, as well as an unexpected funding "bump" from the fiscal stimulus package.There have been many media reports, editorials, and even rallies bemoaning the 2013 cuts and the lack of funding increases in recent years. A major concern is the possible impact that the current constraints on grants will have on young scientists as they start their careers. Even with new investigator initiatives and suggested caps on the number of grants for established scientists, there is concern that important research efforts will go under-funded, or even unfunded, due to the current budget woes. So, the question of the day would seem to be whether or not the payline needs to be moved to improve the probability of grant success for all researchers and, even more critically, how this might be accomplished.Eight percent funding (ten for new investigators) at some institutes does seem very small indeed. But in the end, could we be thinking about this in the wrong way? Might that number in fact be too high, at least for established investigators? The payline, and subsequently the number of funded scientists, comes down to a question of resource allocation and, to an extent, a question of whether or not the NIH should be setting stricter rules on the number of grants or the amount of money any single investigator can receive. Here, I argue that it is important to more closely examine cost-benefit ratios for all awards.If we look at a small, random sampling of NIH grant awardees during 2013 (excluding program projects and small business grants) and compare these awards to production as measured by article output, an interesting trend can be observed. Averaging the awards and output for 3 randomly selected investigators whose 2013 grants total over $1 million dollars, we find an average dollar amount of $1.65 million and an average article production output of 30 for 2013 thus far. When looking at 3 random grantees awarded less than $1 million, we find an average funding amount of $573,000 and an average of 3 articles published in 2013, thus far. The numbers (although obviously my data set does not include the most robust sample size) would seem to indicate that more funding produces more articles.Now, before you say this is obvious, the more interesting point here is that more funding would in fact appear to produce disproportionately more articles, implying that labs with more funding are significantly more productive than their smaller counterparts. This could be attributed to sheer resources. On the other hand, maybe study sections are doing the right thing—identifying investigators with the ability to rapidly shape scientific progress and awarding them appropriately. While a larger sampling of grants and a more detailed analysis of productivity now or in the coming years could alter these conclusions, it is important to start thinking about grants in this fashion—especially if funding continues to lag behind the rate of inflation.So, is it fair to place restrictions on investigators making such significant contributions to science? Unfortunately, I think the answer is clear—restrictions could only serve to further reduce scientific output and therefore run against the needs and desire of the NIH. However, such a lack of restrictions on grant awards would also create more competitive conditions for all established investigators.Obviously, it is important to support young researchers as they start their careers, and this should be accomplished by raising paylines significantly when it comes to first time submissions and awards. But beyond that point, grants should be made on the basis of merit alone, without regard for the amount of money awarded to any one investigator. This will prove challenging to many, but could ultimately produce the necessary change and accountability needed to push life science research forward.Please share your thoughts and comments by posting at our Molecular Biology Forums under "To the Editor" (http://molecularbiology.forums.biotechniques.com) or sending an email directly to the editor (bioeditor@biotechniques.com).FiguresReferencesRelatedDetails Vol. 55, No. 1 STAY CONNECTED Metrics History Published online 3 April 2018 Published in print July 2013 Information© 2013 Author(s)PDF download

BioTechniquesVol. 55, No. 3 From the EditorOpen AccessPushing the envelope on cost/benefit analysisNathan BlowNathan BlowBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000114068AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Today, whether we like it or not, there is a constant need to justify funding for cutting-edge research. Grant money is scarce, and thanks to the internet, journalists are reporting the latest discoveries faster than ever before, raising questions among the general public about the possible impact of these studies. It is with this in mind that I think we are reaching a crossroads in public perception—with research on the avian influenza virus H7N9 likely to take center stage.H7N9 has caused more than 130 human infections in China. Although the virus is not currently transmissible among humans, a team of researchers is suggesting that creating mutant viruses with different degrees of transmissibility in mammals will help us understand the potential for human-to-human transmission.In a letter published this August in both Science and Nature, 22 researchers from 12 universities in the the US, Europe, and Asia present a case for performing gain-of-function [GOF] experiments in H7N9 to examine immunogenicity, adaptation, drug resistance, transmission, and pathogenicity (1,2). The authors argue that "classical epidemiological tracking does not give public health authorities the time they need to mount an effective response to mitigate the effects of a pandemic virus. To provide information that can assist surveillance activities—thus enabling appropriate public health preparations to be initiated before a pandemic—experiments that may result in GOF are critical."Such experiments could provide new insights into virus function and possible paths of future evolution resulting in increased transmissibility to humans. The challenge, though, is to monitor and report that progress as a growing range of mutations are engineered in the lab. Prior work by the same researchers examined the H5N1 virus and its capacity for airborne transmission between ferrets in the lab (3). This work was controversial, leading to several public discussions amongst government officials, researchers, and journal editors before that work was finally published.The rationale behind new GOF studies in H7N9 is curious. While planning ahead for a potential pandemic is important, are vaccine developers willing to design vaccines against "hypothetical" viruses based on GOF mutations? Actually, work has already begun on an H7N9 vaccine, so it is not clear what impact new GOF studies would have.While surveillance should be done, are GOF experiments really necessary given our current knowledge of the potential mechanisms by which viruses can acquire the ability to broaden their host range? Next-generation sequencing can decode a whole genome in a day, and airborne transmission can be determined quickly based on information from patients. Sequencing might not be a viable option in the developing world, so does the knowledge gained through GOF studies improve surveillance options? I'm not suggesting these questions could not be answered, rather I am echoing the need for greater transparency, as many have suggested.Researchers must go to extra lengths to accurately explain the rationale behind experiments that might create more transmissible viruses and how they will be safely conducted. A nice article in Nature Biotechnology suggesting a new safeguard mechanism for GOF studies was recently published (3). Here, the authors took advantage of endogenous miRNAs in human cells to prevent transmission of viruses. The technique appears effective and provides a degree of possible containment when working with GOF viruses. Such techniques and approaches need to be highlighted as widely as the letters suggesting these experiments in the first place.Hyperbole aside, this is a moment where scientists need to consider the psychological impact of their work on the general public. Fears about scientific experiments should not be used as a tool to get an experiment done or to stop such research altogether. There should not be any perception that scientists are simply creating a series of "monster viruses" that will be locked away in labs around the world; this only feeds public fears and future Hollywood movies. Providing clear explanations for the potential of such research, as well as the safeguards built into these studies, will help to reduce concerns and provide a stronger framework for experimental success.The H5N1 studies led to lengthy discussions on the cost/benefits of engineering influenza viruses. In the end, it was decided that the benefits outweighed the potential risks. Now, as researchers push the envelope once again, it is important to revisit that cost/benefit question. Share your thoughts with us at bioeditor@biotechniques.com.References1. Fouchier, R.A., et al.. 2013. Gain-of-function experiments on H7N9. Science 341:612–613.Crossref, Medline, CAS, Google Scholar2. Fouchier, R.A., et al.. 2013. Avian flu: Gain-of-function experiments on H7N9. Nature 500:150–151.Crossref, Medline, CAS, Google Scholar3. Herfst, S., et al.. 2012. Airborne transmission of influenza A/H5N1 virus between ferrets. Science 336:1534–1541.Crossref, Medline, CAS, Google ScholarFiguresReferencesRelatedDetails Vol. 55, No. 3 Follow us on social media for the latest updates Metrics History Published online 3 April 2018 Published in print September 2013 Information© 2013 Author(s)PDF download

BioTechniquesVol. 54, No. 1 From the EditorOpen Access30 years of methodsNathan S. BlowNathan S. BlowBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000113970AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Thinking back over my scientific career, BioTechniques has always been there. When I was an undergraduate at the University of Vermont doing population genetics research, I can fondly remember late nights spent reading the journal while I waited for my gels to run. Then, moving on to work in another lab prior to graduate school, I recall looking at issues with labmates the moment they arrived and betting on which technique would be featured that month. BioTechniques was also the first journal I ever subscribed to (of course it was a huge help that it was free). And after completing my degree and a fellowship, BioTechniques was the first place I worked as an editor.Many of you might also have stories about this journal. Several friends of mine published their first articles in these pages, and many more have methods and techniques from the journal clipped into their lab notebooks for regular use. If you really stop to think about it, BioTechniques has been there for an amazing number of young researchers as they start their careers. How many journals can say that? Although, I might have drifted to different journals throughout my years in the lab (from population genetics-oriented publications to infectious diseases journals), a few publications stayed on my reading list ' BioTechniques being one. And while some might just chalk this up to the fact that BioTechniques provides general methods and protocols directed at improving experiments at the bench, I would argue that there is more to the impact of this journal. For many researchers, BioTechniques represents a first exposure to reading and writing scientific articles. When you begin graduate school, everything is new and learning your field takes time. But most everyone starts working in a lab during that first year ' using different techniques and methods to get some initial data. Here is where BioTechniques fills an important need in the scientific community ' helping young researchers gain access to new methods and techniques, introducing future leaders of science to how research works. This is what makes BioTechniques special, and this is what has kept this magazine growing for the past 30 years.In 2013, BioTechniques will mark its 30th year influencing the way science is conducted in labs around the globe. While the journal has changed over the years, as has the way in which readers receive their issues (e.g., digital versions on iPads and smartphones), the heart and soul remains the same ' speaking to researchers at the bench and assisting everyone in becoming better scientists.With this in mind, I'm pleased to announce that during the coming year we will have a number of special 30th anniversary events. From celebrations at major conferences to special focus sections exploring the methods that this journal helped advance (PCR methodologies in the 1990s for example), our goal is to honor all of the exceptional effort put in by the journal's founders, staff, supporters, authors, and readers over the past three decades.I would be remiss if I did not mention one of the most amazing aspect of BioTechniques ' the journal remains free to subscribers. Despite a difficult economy and challenges in the publishing world, BioTechniques continues to be free to all scientists, both in print and online. The advertiser-supported model upon which the journal was founded is simple, but has stood the test of time. And while open-access might be all the rage at the moment, I think it is important to acknowledge that BioTechniques represents one of the first truly open-access journals; a journal where neither authors nor subscribers pay. It is through the efforts of our advertisers that we have been able to bring science to the masses these past three decades, and for this we should all be thankful.Finally, I would also like take this opportunity to thank the wide range of scientists who have given their time over the past 30 years to serve as reviewers for our manuscripts. This service is critical to the publication of rigorous and informative methods articles, and for many, the feedback provided through peer-review leads to both a substantially improved manuscript as well as an education in how to become a better scientist.I'm looking forward to this coming year and our celebration. I ask that you do us one favor though for our birthday, please send your favorite memories of BioTechniques, or maybe a note on one of your favorite methods from the pages of BioTechniques, to bioeditor@biotechniques.com. We will highlight some of your memories and comments during the coming year.FiguresReferencesRelatedDetails Vol. 54, No. 1 Follow us on social media for the latest updates Metrics History Published online 3 April 2018 Published in print January 2013 Information© 2013 Author(s)PDF download

BioTechniquesVol. 55, No. 6 From the EditorOpen AccessA sequencer in every labNathan BlowNathan BlowBioTechniquesSearch for more papers by this authorPublished Online:3 Apr 2018https://doi.org/10.2144/000114107AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Where has the time gone? It seems like only yesterday we were in the early days of 2013, and now the year is drawing to a close. Traditionally, December editorials are about looking back at the year that was and forward to the year that will be. Some years it is easy to identify a “hot topic” while in other years it takes a little digging and thinking to uncover important trends. Turns out, 2013 was easy.While 2013 definitely saw a variety of interesting new methods being published in BioTechniques and other journals, developments in DNA sequencing methodologies stood out from the pack. For years, sequencing has been the domain of large centers, core facilities, and researchers with deep pockets. Instrument and reagent costs were high, and for most, output outpaced the needs of individual researchers. But all this might be changing as DNA sequencing appears to be reaching a unique tipping point where costs are down, while innovative methods and techniques aimed at maximizing output and applications for “lower-throughput” users abound.In January, Lazinski and Camilli reported on a modified DNA cloning and library construction approach for next-generation sequencing (NGS). Modifications and enhancements for library construction have been appearing more often in the literature. For me, the impact of such articles is two-fold: First, these methods serve to (in most instances) speed up and/or lower the cost of the upstream steps in DNA sequencing, enhancing possibilities for smaller labs. Secondly, they serve as foundations to educate new users on different approaches through comparisons with existing methods. These are the next steps towards wider adoption—decreasing costs, increasing speed, simplifying methodologies, and inspiring future users. The end result here is a deeper understanding and, eventually, a better informed usage of NGS.In February, Okoniewski et al. presented a technique for localizing large genomic deletions using the Pacific Biosciences and Illumina NGS platforms. Copy number variation (CNV) analysis is a growing area of interest for geneticists as it is becoming clear that these genomic modifications can play critical roles in some human diseases. However, localizing the breakpoints where a deletion or duplication has occurred can be a challenge. Applications such as those presented by Okoniewski and colleagues pave the way for others to use NGS platforms for more than standard whole genome or whole exome sequencing studies. And these new applications are creating unique opportunities, another trend of sequencing development in 2013. In the long run, it will be applications, maybe even more so than education and cost reduction, that will lead to the greater use of NGS by all researchers.Localizing deletions wasn't the only target sequencing application we saw during 2013' in one case, targeting was also a target. In June, Li et al. demonstrated a new methodology to capture protein-coding genes among highly divergent species. The technique adds to a growing toolkit that has slowly been developed for evolutionary biologists and other life scientists interested in studying gene families from species where little or no reference sequence is available.August brought two more novel approaches for massively paral lel sequencing—a high-plex PCR method for sequencing large numbers of amplified products and a new assessment tool for quantification and size characterization of sequencing libraries. These articles by Nguyen-Dumont et al. and Laurie et al., respectively, further demonstrate the growing interest of researchers in developing new tools and techniques to enhance NGS adoption.In the end, I suspect 2013 will be remembered for the new methods, techniques, and applications that are finally taking advantage of the maturing NGS platforms currently available—the starting point for a democratization of the technology. But with new systems and approaches set to debut in the coming months, the full impact that massively parallel sequencing will have on biological research remains to be seen.FiguresReferencesRelatedDetailsCited ByPixel: a content management platform for quantitative omics data27 March 2019 | PeerJ, Vol. 7Application of Molecular Methods for Traceability of Foodborne Pathogens in Food Safety Systems Vol. 55, No. 6 Follow us on social media for the latest updates Metrics History Published online 3 April 2018 Published in print December 2013 Information© 2013 Author(s)PDF download

BioTechniquesVol. 55, No. 5 From the EditorOpen AccessMore than the fonts have changedNathan S. BlowNathan S. BlowBioTechniquesPublished Online:3 Apr 2018https://doi.org/10.2144/000114095AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Leafing through this issue of BioTechniques, some of you might feel a ting of nostalgia, while others might just wonder what the heck is going on. Ahh, the different perspectives of age. Our younger readers will likely be the ones wondering about the "old" look this month, since they will not have been in the lab in the early 1990s, when BioTechniques articles appeared in this style and format. But for those of us who can recall those days, this special issue of BioTechniques should be a throwback to a bygone era, in more ways than one.Back in the early 1990s, I was finishing my undergraduate education and BioTechniques was the first journal to which I subscribed. Being free (and remaining free to this day), it presented me the opportunity to have my very own copy of a scientific journal. As corny as this might sound, I was proud each time an issue arrived in the lab, because I was part of a much larger group of scientists and researchers reading this journal every month. In those days, articles were not published as quickly as today, but I think there was a stronger sense of journal identity that is missing now. I was able to start my own scientific mini-library, keeping those issues that would help me as my career progressed. It was solid, tangible, physical proof that I was a part of something. Today, I can get any article I need in an instant, but I receive very few journals in print. My job is to keep up with new methods and techniques, but that is increasingly difficult with more journals coming online each day. I tend not to read journals cover to cover anymore. Instead I skim tables of contents and abstracts, usually online, to find relevant information.Back then, each month BioTechniques would come with a number of PCR, sequencing, cloning, or microscopy techniques/methods articles. There would also be "card decks", index-sized cards that featured new products or technologies and often contained offers for free samples or other items. I cannot tell you how many times I sent for a free spin column, extraction buffer, or enzyme to trial. As for the cards I did not send in—someone else in the lab would take a couple and use them. My copy of BioTechniques always saw more than one pair of hands.The journal content was different too. There were not that many news features; instead, the journal focused on publishing a larger number of peer-reviewed methods and technique articles than today. I'm not saying there isn't a place for news—in fact we know many readers enjoy our monthly columns. But at that time, with fewer publishing outlets, the focus was on distributing research to a large community of scientists. There were no flashy fonts or styles, simply clean and direct articles.While I might be sounding old (which I guess I am now), this editorial is not about yearning for the past. Being able to publish articles quickly and in new formats is a very good thing. Rather, my nostalgia is about how journals promote science by giving authors a voice and a forum to present their research, building a community of readers who actively engage and communicate discoveries beyond the confines of their labs. For me, this is a time to reflect on what we can do in the future to preserve these traditions in an era of fast publishing and decreased oversight, often led by publishers focused on nothing more than the bottom line. Many of today's newer journals exist merely as collections of articles on a website—they lack identity and have simply been put in place to collect author or subscriber fees, which is a sad reflection on the state of scientific publishing.So, take a look at this special "retro" issue of BioTechniques, and while reflecting on the "old school" look, think about that bygone era where journals existed only in print, submissions were sent by post, and editors called authors with questions. A time where predatory journals did not exist for the most part and publishing was less business and more science. And then ask yourself if speed and convenience are worth losing the feeling of being a part of a community or of creating your own mini-library. Being more connected to information without much context ultimately could make us less connected as scientists.FiguresReferencesRelatedDetails Vol. 55, No. 5 STAY CONNECTED Metrics History Published online 3 April 2018 Published in print November 2013 Information© 2013 Author(s)PDF download