Most molecular and cellular biology graduate students regularly use commercial kits to conduct experiments. There is no doubt that these experiments-in-a-box make difficult, time-consuming techniques more accessible. But many worry that the gains in efficiency come with a concomitant loss of scientific intuition.
An editorial in the December issue of Nature Methods argues that preventing this loss is the joint responsibility of vendors, mentors, and students. Vendors should supply sufficient information about how kits work and what artifacts are possible. Mentors must make sure that students understand what occurs at each step in the protocol, and encourage appropriate optimization for custom uses, and students must remember to rely on their minds (rather than just their hands) to conduct experiments.
If you have ideas about how kits can be used creatively, or how to make sure kits do not stifle scientific creativity, please post your comments here.
When using or developing experimental and observational methods it is crucial to assess the method performance in an effort to ensure that the information it provides reflects reality. For experimental biologists this often means conducting carefully chosen control experiments with alternative methods or different experimental settings. More rigorous assessment, particularly for high-throughput or large-scale methods, often requires the use of ‘ground truth’ or ‘gold standard’ data sets. But talk to different people and you will get different answers regarding what ‘ground truth’ or ‘gold standard’ data is. This often includes a nice historical explanation of where the term ‘ground truth’ comes from.
For developers of signal processing and image analysis algorithms though, the situation is clearer; the ground truth is the signal or image you start with. But add a living system into the mix and things get far more complicated. The Editorial in the November issue of Nature Methods discusses the challenges facing developers and users of algorithms for automated analysis of biological data, with a focus on image data. In short, traditional ground truth data is often insufficient. The addition of integrated-editing and change-logging capabilities to these software tools can increase the quality of the analysis, aid further algorithm development and increase the likelihood of biologists adopting the software in the first place.
Over the past 30 years the ties between academic research and commercial enterprise have increased enormously. Much of this increase has involved attempts by universities to capitalize on the intellectual property created by their research scientists using the US patent system. The Editorial in the October issue of Nature Methods discusses this change and the challenges facing academics interested in commercializing their innovations.
The America Invents Act was signed into law on September 16 by President Obama as the Nature Methods Editorial went to press. As discussed in the Editorial, this law introduces a fundamental change in US patent law that impacts how US academics and their technology transfer offices will handle their intellectual property once the law goes fully into effect a year from now.
Overall, the harmonization of US patent law with the rest of the world should greatly simplify patent claims. But it also presents challenges and fails to fix some aspects of patent law that make little sense, like forcing the same 20-year patent lifetime on classes of inventions that display huge disparities in the time and cost of moving from patent filing to commercial product and the corresponding difference in commercial lifetimes. The implementation of different patent lifetimes for different classes of inventions, for example pharmaceuticals versus computer technology and processes, would help correct severe imbalances in the current system. But given the years required to obtain passage of the America Invents Act, further significant changes are likely years away.
The links below have additional information and commentary on patent law and commercialization in academia.
US switch to first-to-file patents could cause minor shake-up Nat. Med. 17, 906 (4 Aug 2011)
New models emerge for commercializing university assets Nat. Biotechnol. 29, 774 (8 Sept 2011)
Patent reform on the brink Nat. Biotechnol. 29, 778 (8 Sept 2011)
The Effects of the America Invents Act on Technological Disclosure Patently-O Blog (8 Sept 2011)
Patent reform bill passes US Congress – September 09, 2011 Nature newsblog (9 Sept 2011)
Patents Directed to Human Organisms Patently-O Blog (9 Sept 2011)
Guest Post – To Promote Progress in Science and Job Creation Patently-O Blog (12 Sept 2011)
Patent medicine Nature 477, 249 (14 Sept 2011)
New Patent Law Could Change How Academics Commercialize Discoveries ScienceInsider (14 Sept 2011)
Patent Reform Shuffles Who Is First in Line Science 333, 1559 (16 Sept 2011)
Guest Post: Preclusive Inventor Disclosure Under Leahy-Smith Patently-O Blog (22 Sept 2011)
September’s Editorial praises the new research that more genetic rodent models will enable. However, manipulating important genes in a mouse is not enough. Experimental techniques are also needed. Perhaps nowhere is this more important—and more difficult—than using animals to assess neuropsychiatric diseases. While much can be learned on the level of brain and cell physiology, behavioral tests are important to assess which aspects of physiology are most likely to matter. It’s the behavioral symptoms, not the cell-based ones, that directly affect people’s lives. How useful would a drug be if it cleared away the telltale plaques of Alzheimer’s patients but did nothing to preserve their memories?
To make the most of the ever increasing numbers of rodent genetic models, researchers will need better assays and better ways of assessing their validity for human disease.
Please share your thoughts on how best to assess whether an animal model is relevant for studying neuropsychiatric disease.
In our August issue, we join in the celebration of the International Year of Chemistry with a special feature, including an Editorial that highlights some of the most important contributions of chemistry to method and tool development for biology research, a Technology Feature on protein engineering, a Historical Commentary on the history of mass spectrometry, a Commentary on bioorthogonal chemistry, another Commentary on small-molecule fluorescent probes, and finally, a selection of Chemistry Methods papers published in past issues of Nature Methods.
It is clear that many important insights in biology research would not have been possible without the use of methods and tools developed originally by chemists. Even today, the expertise of chemists continues to be necessary for making new discoveries and advancements in the biological sciences.
Please feel free to share your thoughts about the impact of chemistry, of methods and tools in particular, on biology research!
Many scientists (and editors) lament the proliferation of acronyms in the literature, especially for describing methods. As editors of a methods journal, we have some definite opinions about when acronyms are useful, when a new acronym is unnecessary, and what makes a good (or bad) acronym. We discuss this in depth in our July issue Editorial.
A good acronym to describe a novel method gives the research community a simple and effective way to refer to the method. However, optimizations of the method or adaptations for a different application usually do not justify the creation of a new acronym. This trivializes the original advance and the proliferation of similar-sounding acronyms creates confusion in the community. Researchers should be judicious in creating acronyms for methods and think hard about whether a new acronym is truly necessary.
Feel free to share your thoughts about the use—and misuse—of acronyms!
Obtaining research funding, particularly from the NIH, is an increasingly daunting task that requires a lot of background information in addition to presenting a stellar proposal.
Researchers need to decide which of the 25 institutes at the NIH is most likely to fund a particular line of work. A new database, linked to RePORTER, NIH’s research portfolio reporting tool, will make this decision a bit easier.
The developers of this database welcome community feedback and we encourage you to try it out.
The May Editorial in Nature Methods discusses how the overall efficiency of research can be improved by comparative analysis of research method and tool performance.
Although such analysis studies aren’t considered as ‘sexy’ as basic exploratory research, the benefits for and gratitude from the community can be profound. Large well-funded laboratories are more likely to have the resources to perform such analyses and should not discount the advantages to performing such studies and publishing the results.
Nature Methods has published several such analysis studies in the past. A (probably incomplete) selection is listed below. We will strive to publish even more in the future. Our ‘Analysis’ article type is actually dedicated to these kinds of studies. We encourage communities and labs to both contribute such analyses and suggest methodological areas that would benefit from them. The selection below may provide some inspiration.
Multiple-laboratory comparison of microarray platforms
Independence and reproducibility across microarry platforms
Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations
A guide to choosing fluorescent proteins
Reproducible isolation of distinct, overlapping segments of the phosphoproteome
Use of simulated data sets to evaluate the fidelity of metagenomic processing methods
Cost-effective strategies for completing the interactome
Cyclic nucleotide analogs as probes of signaling pathways
A HUPO test sample study reveals common problems in mass spectrometry-based proteomics
Comprehensive comparative analysis of strand-specific RNA sequencing methods
Microbial community resemblance methods differ in their ability to detect biologically relevant patterns
Validation of two ribosomal RNA removal methods for microbial metatranscriptomics
Chemically defined conditions for human iPSC derivation and culture
Two-photon absorption properties of fluorescent proteins