Monthly Archives: November 2013

Is phototoxicity compromising experimental results?

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Light-induced damage to biological samples during fluorescence imaging is known to occur but receives too little attention by researchers.

The December Technology Feature in Nature Methods asks if super-resolution microscopy is right for you and a point that comes up repeatedly from the researchers we interviewed is the danger of phototoxicity and photodamage caused by the high irradiation intensities needed for the illuminating light. This has long been a concern with these methods and many of the papers describing them mention it.

But as discussed in the December Editorial, even fluorescence microscopy with low irradiation intensities can cause dangerous levels of phototoxicity that permanently damage the sample. Microscopists are aware of these concerns but there has been little effort to implement processes intended to reduce the likelihood of it compromising research study results. Dave Piston, Director of the Biophotonics Institute at Vanderbilt University School of Medicine, laments that while phototoxicity is a big deal he has gotten zero traction with NIH reviewers on trying to build some rules for it.

There are some good resources available to researchers that highlight the dangers of phototoxicity and provide advice on how to limit it. Methods in Cell Biology Vol 114 has an excellent chapter by Magidson and Khodjakov, Circumventing Photodamage in Live-Cell Microscopy, that should be mandatory reading for all researchers using fluorescence microscopy for biological research. Also, Nikon’s MicroscopyU has a literature list with several dozen references and recommended reading on phototoxicity. It could use some updating but is still useful.

Despite the amount of microscopy literature that discusses phototoxicity, discussion of the phenomenon in research articles published in Nature Journals is conspicuously absent. This is highlighted by a simple full-text search we performed on the HTML versions of research articles published in Nature, Nature Cell Biology, Nature Immunology, Nature Methods and Nature Neuroscience. The articles retrieved were limited to original research articles.

The table below lists the number of occurrences of each of the listed words in the period from January 1, 2005 to November 3, 2013 in each of the indicated journals. The percentages represent the number fraction of articles containing ‘phototoxicity’ relative to the numbers of articles containing each of the microscopy- or fluorescence-related terms. Note that this is NOT a measure of co-occurrence, only a measure of how common the term ‘phototoxicity’ is relative to the other terms.

phototoxicity fluorescence fluorescent microscopy microscope
# # % # % # % # %
Nature 8 2120 0.4% 1925 0.4% 1995 0.4% 1918 0.4%
Nature Cell Biology 8 815 1.0% 728 1.1% 866 0.9% 822 1.0%
Nature Immunology 6 552 1.1% 574 1.0% 408 1.5% 326 1.8%
Nature Methods 27 565 4.8% 494 5.5% 441 6.1% 407 6.6%
Nature Neuroscience 18 639 2.8% 727 2.5% 587 3.1% 736 2.4%

 

The same analysis was repeated with the term ‘photodamage’ to determine if there was a substantial difference in the usage of these two similar terms.

photodamage fluorescence fluorescent microscopy microscope
# # % # % # % # %
Nature 18 2120 0.8% 1925 0.9% 1995 0.9% 1918 0.9%
Nature Cell Biology 6 815 0.7% 728 0.8% 866 0.7% 822 0.7%
Nature Immunology 2 552 0.4% 574 0.3% 408 0.5% 326 0.6%
Nature Methods 29 565 5.1% 494 5.9% 441 6.6% 407 7.1%
Nature Neuroscience 12 639 1.9% 727 1.7% 587 2.0% 736 1.6%

 

These results carry the potentially large caveat that the analysis did not include the text of the supplementary information, but the rarity with which phototoxicity or photodamage is discussed (0.4% to 7% relative to microscopy terms) suggests that researchers don’t appreciate how important it is to pay attention to artifacts that result from light irradiation. Luckily, there are exceptions to this state of affairs.

An excellent example of testing for phototoxicity and the subtle effects it can induce can be found in a manuscript from Jeff Magee’s lab at Janelia Farm Research Campus published last year in Nature. Quoting from the manuscript, “Particular care was taken to limit photodamage during imaging and uncaging. This included the use of a passive 8× pulse splitter in the uncaging path in most experiments to reduce photodamage drastically [Ji, N. et al. Nat. Methods (2008)]. Basal fluorescence of both channels was continuously monitored as an immediate indicator of damage to cellular structures. Subtle signs of damage included decreases in or loss of phasic Ca2+ signals in spine heads in response to either uncaging or current injection, small but persistent depolarization following uncaging, and changes in the kinetics of voltage responses to uncaging or current injection. Experiments were terminated if neurons exhibited any of these phenomena.”

It is easy to see how these changes in Ca2+ responses could easily have been interpreted as real biological effects caused by the uncaged glutamate, rather than the uncaging light itself.

It is unrealistic to expect that any mandates or oversight would be able to prevent or detect such consequences of phototoxicity in research studies. It is essential that investigators themselves be vigilant and implement appropriate controls to detect these effects. Na Ji, also at Janelia Farm Research Campus says, “It is not enough to only look for instant and dramatic signs of phototoxicity. Sometimes the effects may be more subtle and even unperceivable during the imaging period, but may become obvious when the same sample is imaged the next day. Care has to be taken in data collection and interpretation, especially when the biological process under investigation itself is a subtle one.”

Finally, the application is just as important as the imaging method being used. For example, light-sheet microscopy is excellent at reducing irradiation levels in volumetric imaging. But some applications of super-resolution microscopy, even on living samples, might be less susceptible to artifacts caused by phototoxicity than are sensitive long-term imaging applications of living samples by light-sheet microscopy. Nobody’s microscope earns them a free pass on the dangers of photodamage arising from phototoxicity. Everyone needs to be vigilant.

Update: A reader helpfully pointed out that the danger of phototoxicity and photodamage also applies to optogenetics, where light (often in the blue region of the spectrum) is used to control protein activity.

Stephen Quake responds to Lior Pachter

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Stephen Quake responds to a blog post by Lior Pachter that analyzes data from his recent analysis of single-cell RNA sequencing methods published in Nature Methods.

In October, we published an Analysis by Quake and colleagues that evaluated a number of single-cell RNA-seq approaches on the basis of their sensitivity, accuracy and reproducibility. In a subsequent blog post, Pachter challenged their data reporting. At issue is whether the failure rate among 96 samples sequenced using the Fluidigm C1 microfluidic instrument should have been presented differently.

We encourage animated discussion of published research and hope that this can serve as a useful forum. In this guest post, Quake responds to Pachter’s blog entry. The views expressed below are solely his and do not necessarily represent those of Nature Methods.

Stephen Quake Methagora blog postIn a recent blog post, Lior Pachter appears to question my scientific integrity and suggest that I unfairly manipulated data in a recent publication on single cell RNAseq.

Pachter has not contacted me directly with his questions nor did he give any warning before publishing his blog post. While I am happy that he is carefully scrutinizing publications and independently re-analyzing primary data, his rather sensationalistic approach to reporting his results in the absence of discussion or peer-review risks doing a disservice to science and adds more heat than light.

Pachter tries to have it both ways – based on our published data he accuses me of 1) wasting effort by sequencing lower quality samples and 2) selectively publishing data from only the better samples. It is hard to see how these accusations can simultaneously both be true. As described in the methods section of our paper, the C1 capture rate is not perfectly efficient and therefore we manually inspected all the chambers. We found 93 chambers had single cells, 1 chamber had two cells, and 2 chambers had no cells. Of the 93 chambers with single cells, 91 of the cells appeared to be alive as measured by a live/dead stain and 2 did not. Our single cell RNAseq experiments included all 91 of the “live” single cells and 1 of the “dead” single cells; the data from the latter was indistinguishable from the former and thus it was included in all further analyses. There was absolutely no selection or manipulation of the data. All of the raw data as well as our R scripts were made available for Pachter and others to download and analyze upon publication of our paper.

The sequencing library prep and workflow that we use is geared around 96 parallel samples and we decided it would be valuable to process control samples in exactly the same batch as the single cell samples. We therefore included four control samples with the single cells: amplification products from a chamber on the chip that did not have a cell (C09, which was unfortunately not given a distinguishing filename during the file upload), a single cell tube amplification, a no template control (NTC, C70) tube experiment that did not have a single cell, and a bulk control sample. Pachter correctly points out that C70 is dominated by the ERCC spike in controls and has essentially no human transcripts as expected; similarly, the other negative control C09 performs very poorly next to the actual single cell data. It is not clear to me why Pachter thinks I should be embarrassed for performing negative control experiments; indeed biochemical amplifiers are known to be so sensitive that there are many stories of contamination that occurs through aerosol dispersal from nearby benches, etc. In our own analyses C09 and the other controls were excluded from the single cell data.

Pachter also noticed that ~ 3 of the single cell RNAseq experiments have significantly lower quality than the other 89, as measured by fraction of spike in sequenced or by log-correlation coefficient. If taken at face value, this corresponds to a failure rate of 3/92, or 3%. The experiments therefore had a 97% success rate by this metric and it is hard to see where his complaint lies. We conservatively included ALL of the single cell data in our analyses and thus if one follows Pachter’s prescription to only analyze the experiments that he deems “successful”, then the results will be even better than we reported.

Finally, Pachter makes a misleading argument concerning the statistical methods used to generate figure 4a. This figure is concerned with the questions of whether an ensemble of single-cell RNAseq experiments produces similar gene expression values as a bulk experiment. The reason for sub-sampling to equal depth is worry of introducing artifacts by comparing two RNAseq experiments of dramatically differing sequencing depth (see e.g. Cai, Guoshuai, et al. “Accuracy of RNA-Seq and its dependence on sequencing depth.” BMC bioinformatics 13.Suppl 13 (2012) and Tarazona, Sonia, et al. “Differential expression in RNAseq: a matter of depth.”Genome research 21.12 (2011): 2213-2223.). This figure has little to do with estimating the quality of the individual RNAseq experiments.

Brain initiatives galore, smiles aplenty

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Vivien Marx reports on the Society for Neuroscience meeting in San Diego and the big brain projects in the EU and US.

SfN attendance sign

The Society for Neuroscience annual meeting in San Diego clocked record attendance.{credit}Vivien Marx{/credit}

The brain is hot.

Despite dismay about the recent 16-day US government shutdown, the impact of automatic budget cuts–the sequester–taking effect in light of federal budget disagreements in Washington, and the general economic malaise, there is palpable excitement. New large-scale initiatives are getting underway around the world to develop technologies to empower neuroscientists.

This year’s Society for Neuroscience (SfN) meeting in San Diego that has just ended, clocked a record attendance of over 30,000 attendees, noted society president Larry Swanson to attendees with a broad smile in one of his conference announcements. “It is an inspirational time to be a neuroscientist,” he said, with the field drawing attention, for example, across the European Union and in the White House. In a town hall meeting for the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, there was no lack of critical comments and suggestions of aspects to include in BRAIN. But smiles stayed plentiful as funders explained their plans.

The fact that the US president chose neuroscience as his multi-year, signature project is something “we should all be pretty excited about,” says Tom Insel, director of the National Institutes of Mental Health. In addition to projects in the US, such as  (BRAIN) Initiative and the EU’s Human Brain Project, large neuroscience projects are just emerging in Australia, China, Japan and Israel. “This is beginning to feel like a global movement,” he says. And projects are unfurling in the private sector, too.

The new tools, says Story Landis, director of the National Institute of Neurological Disorders and Stroke, will help neuroscientists do their work “bigger, better, faster” and expand the research strides made in recent years.

Much remains to be done. Compared to what is known about the kidney or heart, very little is known about the brain, says Insel. Adding to the neurological diseases, he noted, are the “invisible wounds of war” such as traumatic brain injury and post-traumatic stress disorder. Tools to help diagnose these illnesses are urgently needed.

Nora Volkow, director of the National Institute of Drug Abuse says that the BRAIN initiative stands to “act like a catalyst” in ways not unlike the decoding of the human genome and its successive “avalanche of discovery.”

Besides attending SfN’s hundreds of sessions and 17,000 posters, scientists had the chance to get up close and personal with representatives from the funding agencies and to hear about and discuss the new opportunities. Here is a snapshot of some of the announcements.

European Union
As Daniel Pasini from the European Commission’s programme on future and emerging technologies explained, the 10-year European Human Brain Project has invited the scientific community to present “grand ideas” for a massive effort to computationally reconstruct the human brain using supercomputers.

The model will help to study brain-related diseases, which are a major health challenge, an economic and social burden, and to pool data and expertise more effectively and translate results for treatments.

The project, which took three years of planning, involves over 250 scientists across Europe in 135 research groups in 22 countries, including groups in the US and Asia. The program began officially in October and has a budget of $1.6 billion. Half of the money will come from the EU the other will come from national funding sources, Pasini says. The first phase is slated to last 30 months and is funded with $100 million.

Six platforms are to be developed including, for example, the neuroinformatic platform as a single point of access to all neuroscience and clinical data along with software tools. The other platforms involve brain simulation, high performance computing, medical informatics, neuromorphic projects and neurorobotics. The idea is to keep improving the model as new data become available. All tools and data are set to be made available to the global scientific community. The plan is to create the ‘CERN for brain research.’ Not unlike a telescope facility or a super-collider, scientists will be able to perform experiments and use this platform to help continue to expand the model.

Deconstructing Henry

The Brain Observatory at UC San Diego is running ‘Deconstructing Henry’ an examination of the Brain of patient H.M.{credit}Vivien Marx{/credit}

US Defense Advanced Research Projects Agency (DARPA)
“Yes, we build guns and bombs, that is true,” says Colonel Geoffrey Ling of DARPA more generally. He is a neurologist who also served in Afghanistan and Iraq and currently deputy director of DARPA’s division responsible for defense sciences, which does not build bombs and guns. He and many other neuroscientists want to cure diseases ranging from Alzheimer’s to schizophrenia to post traumatic stress disorder to traumatic brain injury. DARPA is indeed “zeroed in” on the problems facing soldiers returning from the battlefield.

Speaking directly to fellow panelists from NIH, he says: “I wish they would double the budget yet again for you guys,” which was greeted by SfN attendees with vigorous applause.

Two DARPA solicitations for proposals are now open, offering “real money,” as Ling says, collecting projects that relate to memory dysfunction and psychiatric disorders. More solicitations are “in the works,” he says. “It’s not for us to decide what you’re going to build,” he says, highlighting the importance of imagination and taking a diversity of approaches.

The funding model at DARPA is shaped by use cases to assure that what is developed serves his constituency, the servicemen and women.

Multidisciplinary research, for example, is not achieved with the collaboration of a cellular neuroscientist, a neurophysiologist, and a neurologist. Rather, for DARPA interdisciplinary efforts can be a team comprised of a mathematician, a physicist and “a crazy guy in his backyard putting together some Rube Goldberg thing,” says Ling.

Unlike NIH, DARPA issues no grants but rather contracts, which are “deliverables-driven,” and may seem more rigid that NIH. But he sees strength in the synergy of the different funding approaches by NSF, NIH and DARPA. DARPA is committed to this project over the next decade, says Ling.

Data-sharing provisions are built into each contract, which DARPA takes “extremely seriously,” and breach of contracts are pursued. The DARPA solicitations issued are just the beginning, he says.

Systems based Neurotechnology for Emerging Therapies (SUBNETS)
Deadline: Dec. 17, 2013
This project seeks proposals to develop devices, perform model organism based research, or enable modeling of human neural systems, which are geared to help treat patients with neuropsychiatric and neurologic disease.

Restoring Active Memory (RAM)
Deadline: Jan. 6, 2014
This project seeks proposals in the area of analyzing and decoding neuronal signals which can be used to help patients recover memory function after injury.

SfN attendee bag

Companies in the neuroscience field may benefit from funding in the emerging large-scale projects. Here a scientst at SfN wears one company’s advertisement.{credit}Vivien Marx{/credit}

National Institutes of Health (NIH)
No grants have yet been awarded through the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. But grants are in the pipeline. True, says Insel, some see the project as a perhaps $40 billion dollar challenge, but he views the funding in 2014 as an “initial investment.”

The first report of the BRAIN initiative’s working group, says Landis, offers a guide for how the project could begin to move forward in its first year. The working group, is the advisory committee to the NIH director is chaired by Rockefeller University’s Cornelia Bargmann and Stanford University’s Bill Newsome. Landis says excitement is high in the Obama administration and across NIH. The hope is that this enthusiasm would be reflected in the budget allocations.

The NIH first year funding is “a down payment,” she says.

Insel says that the NIH’s $40 million to be allocated in 2014 is drawn from the following sources:

  • $10 million are coming from the NIH Director’s discretionary fund
  • $10 million are from the NIH Blueprint Neuroscience a program to enhance collaboration across NIH institutes
  • $20 million are split among four NIH agencies: National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Mental Health (NIMH), National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Institute of Drug Abuse (NIDA)

These monies were previously slated for initiatives of the individual institutes’ choice. As Landis explains, these four agencies agreed that the BRAIN Initiative was the one they selected for fund allocation. She says she and her colleagues are “optimistic” that the excitement, opportunities and promise of the BRAIN initiative will power the budgets of the future. Throughout sessions at SfN, she, Insel and others were quick to squelch fears that BRAIN would draw funding away from investigator-driven grants.

The first NIH Requests for Applications (RFAs) are currently begin hashed out with cross-communication happening across NIH, NSF and DARPA, says Insel.

All BRAIN Initiative projects will be peer-reviewed and perhaps unlike the more classic grants, they will have milestones and there will be expectations of data-sharing. “That’s going to be baked into everything we do in this project,” says Insel. Evaluations will accompany the projects after they are funded.

A number of awards are likely to be cooperative agreements, which are part way between a contract with deliverables and R01s, says Landis. These agreements are accompanied by milestones. If researchers do not share data and that provision is in their notice of grant award “there can be consequences,” she says.

Update: In mid-December NIH announced six funding opportunities. Approximately $44 million will finance six new funding opportunities.

Sunset at SfN

Two of the 30,000 attending scientists take a break outside the SfN conference halls.{credit}Vivien Marx{/credit}

National Science Foundation (NSF)
Cora Marrett, the acting director of the NSF says her agency will “very energetically” support the BRAIN Initiative. She says that funders need to take “the long view” to let the forces of scientific discovery play out with a long-term commitment. “I’m feeling very optimistic, too, about what the long-run prospects for additional resources will look like.”

Evidence of NSF’s engagement with neuroscience in general can be seen in the recent $25 million grant to fund the Center for Brains, Mind and Machines at the Massachusetts Institute of Technology. The intent is to blend computer science, math, robotics, neuroscience and cognitive science.

The BRAIN Initiative will require intense collaboration across disciplines and scales, she says. Neuroscience has been more devoted to small science, she says, the work of individual principal investigators and small lab groups. Marrett agrees with Alan Leshner, the executive publisher of Science, that neuroscience’s strides will benefit from a change in the culture toward larger-scale, interdisciplinary efforts.

At the same time, this shift will occur without prescriptions that all work needs to be on “the huge scale” of a particle accelerator, for example. Indeed neuroscientists will need to integrate findings across the scales of their research and link physiology, biophysical and genetic data with cognitive and behavioral findings (see Leshner Editorial in Science).

The projects will require data management plans of the grantees, she says, to explain how they will handle data-sharing, which is to the benefit of the entire enterprise.