How to Elucidate the Structure of Peptide Monolayers on Gold Nanoparticles?

I have recently submitted my PhD thesis and we have now pre-printed on bioRxiv the work constituting its major chapter. Together with the pre-print, the data have been made publicly available in an online repository of the University of Liverpool. Well isn’t it perfect timing that this week is open access week? 😉

This work has been conducted nearly entirely during the 2 years of my PhD spent at the A*STAR Institute of Materials Research and Engineering (IMRE) and at the A*STAR Institute of High Performance Computing (IHPC) in Singapore.

In this study, peptide-capped gold nanoparticles are considered, which offer the possibility of combining the optical properties of the gold core and the biochemical properties of the peptides.

In the past, short peptides have been specifically designed to form self-assembled monolayers on gold nanoparticles. Thus, such approach was described as constituting a potential route towards the preparation of protein-like nanosystems. In other words, peptide-capped gold nanoparticles can be depicted as building-blocks which could potentially be assembled to form artificial protein-like objects using a “bottom-up” approach.

However, the structural characterization of the peptide monolayer at the gold nanoparticles’ surface, essential to envision the design of building-blocks with well-defined secondary structure motifs and properties, is poorly investigated and remains challenging to assess experimentally.

In the pre-printed manuscript, we present a molecular dynamics computational model for peptide-capped gold nanoparticles, which was developed using systems characterized by mean of IR spectroscopy as a benchmark. In particular, we investigated the effect of the peptide capping density and the gold nanoparticle size on the structure of self-assembled monolayers constituted of either CALNN or CFGAILSS peptide.

The computational results were found not only to well-reproduce the experimental ones, but also to provide insights at the molecular level into the monolayer’s structure and organization, e.g., the peptides’ arrangement within secondary structure domains on the gold nanoparticle, which could not have been assessed with experimental techniques.

Overall, we believe that the proposed computational model will not only be used to predict the structure of peptide monolayers on gold nanoparticles, thus helping in the design of bio-nanomaterials with well-defined structural properties, but will also be combined to experimental findings, in order to obtain a compelling understanding of the monolayer’s structure and organization.

In this sense, we would like to stress that, in order to improve data reproducibility, enable further analysis and the use of the proposed computational model for peptide-capped gold nanoparticles, we are making the data and the custom-written software to assemble and analyse the systems publicly available.


Snapshots of the final structure of the simulated 5 (left) and 10 (right) nm CFGAILSS-capped gold nanoparticle, illustrating different content and organization of secondary structure motifs.

Is targeting your target?

Warren Chan’s group published in June a perspective in Nature Reviews Materials entitled “Analysis of nanoparticle delivery to tumours” (Wilhelm et al). A key finding of their analysis of the literature is the absence of increase in the (very small) amount of nanoparticles delivered to tumours in the past 10 years. In a welcome departure from the usually overly diplomatic and confused style that is the trademark of most scientific writing, Wilhelm et al write the following:

 “These advantages [of nanoparticles] have been dampened by the lack of translation to patient care, despite the large investment (more than $1 billion in North America in the past 10 years) and success in imaging and treating tumours in mouse models. As a result, nanomedicine has acquired a reputation of being “hype” that cannot deliver and has not transformed patient care as it promised 15 years ago”


“We must admit that our current approach is broken, and that is why we have not observed significant clinical translation of cancer nanomedicines. Many academic studies focused on the potential of nanoparticles for in vivo applications and showed that nanoparticles may be delivered to tumours by the EPR effect. However, publishing ‘proof of concept’ studies will only lead to curing mice and will unlikely translate to cancer care, irrespective of the number of nanoparticle design permutations used for cancer targeting studies.”

Recognising the magnitude of the challenge, Wilhelm et al propose a thirty year strategy for nanomedicine.

Not surprisingly the publication sparked a debate; see for example Derek Lowe’s blog “Nanoparticles Mix It Up With Reality” and the comments therein, and the article by Michael Torrice for Chemical and Engineering News “Does nanomedicine have a delivery problem?” which features a number of quotes by various nanomedicine players, some of whom contesting Wilhelm et al’s findings, or their relevance to the development of nanomedicine. The debate has also continued in the scientific literature with a comment by McNeil “Evaluation of nanomedicines: stick to the basics” and a response by Chan.

Another comment by Lammers et al has been published 10 days ago “Cancer Nanomedicine: Is targeting our target?”. The implicit answer of the authors is no, targeting is not our target and therefore the absence of progress noted by Wilhelm et al matters little. Lammers et al’s argument is first that the percentage of the injected dose reaching the tumour is not a good indicator of the potential of a therapy, and second, that nanomedicine has in fact had some successes even without targeting. To illustrate this latter point, their first example is Doxil, a liposomal formulation of the anti-cancer drug Doxurubicin.

It is rather unconvincing that Lammers et al would use Doxil as an indication of the success of nanomedicine given that it was developed in the 80s and 90s, i.e. one or two decades before the “nanomedicine” word had been coined and Clinton had announced the $500M National Nanotechnology Initiative (January 2000). A bibliography search for the word “nanomedicine” suggests that it started to be used in the year 2000, with this MIT Technology Review being one of the very first examples:

Nanomedicine Nears the Clinic

Minuscule “smart bombs” that find cancer cells, kill them with the help of lasers and report the kills. Sound crazy? Guess again. That treatment scenario may be less than a decade away.

by David Voss
January 1, 2000

Since this infamous MIT technology review, we have seen so many similar promises and so little translation that Chan’s review and the debate that it provoked are indeed an incredibly positive and much needed development.

There is another amusing thing about Lammers et al’s review. The title suggesting that targeting is not our target is further echoed in the conclusion as follows:

“Patients do not benefit from targeting as such, and a reported tumour accumulation of 0.7%ID does not mean that nanomedicines do not work. We have to think beyond targeting, and beyond numbers, and focus on carrier-dependent drugs, combination therapies, protocols for patient selection and ways to enable rapid and more efficient clinical translation.”

Yet targeting as such seems very much to have been the target of these authors as the (non-exhaustive) list of articles below illustrate.

  1. Blume, G.; Cevc, G.; Crommelin, M.; Bakkerwoudenberg, I.; Kluft, C.;Storm, G.,Specific targeting with poly(ethylene glycol)-modified liposomes – coupling of homing devices to the ends of the polymeric chains combines effective target binding with long circulation times. Biochimica Et Biophysica Acta 1993, 1149 (1), 180-184.
  2. Vingerhoeds, M. H.; Steerenberg, P. A.; Hendriks, J.; Dekker, L. C.; vanHoesel, Q.;Crommelin, D. J. A.; Storm, G., Immunoliposome-mediated targeting of doxorubicin to human ovarian carcinoma in vitro and in vivo. British Journal of Cancer 1996, 74 (7), 1023-1029.
    3. Storm, G.; Crommelin, D. J. A., Colloidal systems for tumor targeting. Hybridoma 1997, 16 (1), 119-125.
    4. Mastrobattista, E.; Koning, G. A.; Storm, G., Immunoliposomes for the targeted delivery of antitumor drugs. Advanced Drug Delivery Reviews 1999, 40 (1-2), 103-127.
    5. Mastrobattista, E.; Kapel, R. H. G.; Eggenhuisen, M. H.; Roholl, P. J. M.; Crommelin, D. J. A.; Hennink, W. E.; Storm, G., Lipid-coated polyplexes for targeted gene delivery to ovarian carcinoma cells. Cancer Gene Therapy 2001, 8 (6), 405-413.
    6. Mastrobattista, E.; Crommelin, D. J. A.; Wilschut, J.; Storm, G., Targeted liposomes for delivery of protein-based drugs into the cytoplasm of tumor cells. Journal of Liposome Research 2002, 12 (1-2), 57-65.
    7. Metselaar, J. M.; Bruin, P.; de Boer, L. W. T.; de Vringer, T.; Snel, C.; Oussoren, C.; Wauben, M. H. M.; Crommelin, D. J. A.; Storm, G.; Hennink, W. E., A novel family of L-amino acid-based biodegradable polymer-lipid conjugates for the development of long-circulating liposomes with effective drug-targeting capacity. Bioconjugate Chemistry 2003, 14 (6), 1156-1164.
    8. Metselaar, J. M.; Wauben, M. H. M.; Wagenaar-Hilbers, J. P. A.; Boerman, O. C.; Storm, G., Complete remission of experimental arthritis by joint targeting of glucocorticoids with long-circulating liposomes. Arthritis and Rheumatism 2003, 48 (7), 2059-2066.
    9. Schiffelers, R. M.; Koning, G. A.; ten Hagen, T. L. M.; Fens, M.; Schraa, A. J.; Janssen, A.; Kok, R. J.; Molema, G.; Storm, G., Anti-tumor efficacy of tumor vasculature-targeted liposomal doxorubicin. Journal of Controlled Release 2003, 91 (1-2), 115-122.
    10. Schmidt, J.; Metselaar, J. M.; Wauben, M. H. M.; Toyka, K. V.; Storm, G.; Gold, R., Drug targeting by long-circulating liposomal glucocorticosteroids increases therapeutic efficacy in a model of multiple sclerosis. Brain 2003, 126, 1895-1904.
    11. van Steenis, J. H.; van Maarseveen, E. M.; Verbaan, F. J.; Verrijk, R.; Crommelin, D. J. A.; Storm, G.; Hennink, W. E., Preparation and characterization of folate-targeted pEG-coated pDMAEMA-based polyplexes. Journal of Controlled Release 2003, 87 (1-3), 167-176.
    12. Mulder, W. J. M.; Strijkers, G. J.; Griffioen, A. W.; van Bloois, L.; Molema, G.; Storm, G.; Koning, G. A.; Nicolay, K., A liposomal system for contrast-enhanced magnetic resonance imaging of molecular targets. Bioconjugate Chemistry 2004, 15 (4), 799-806.
    13. Schiffelers, R. M.; Ansari, A.; Xu, J.; Zhou, Q.; Tang, Q. Q.; Storm, G.; Molema, G.; Lu, P. Y.; Scaria, P. V.; Woodle, M. C., Cancer siRNA therapy by tumor selective delivery with ligand-targeted sterically stabilized nanoparticle. Nucleic Acids Research 2004, 32 (19).
    14. Verbaan, F. J.; Oussoren, C.; Snel, C. J.; Crommelin, D. J. A.; Hennink, W. E.Storm, G., Steric stabilization of poly(2-(dimethylamino)ethyt methacrytate)-based polyplexes mediates prolonged circulation and tumor targeting in mice. Journal of Gene Medicine 2004, 6 (1), 64-75.
    15. Visser, C. C.; Stevanovic, S.; Voorwinden, L. H.; van Bloois, L.; Gaillard, P. J.; Danhof, M.; Crommelin, D. J. A.; de Boer, A. G., Targeting liposomes with protein drugs to the blood-brain barrier in vitro. European Journal of Pharmaceutical Sciences 2005, 25 (2-3), 299-305.
    16. Zhang, C. F.; Jugold, M.; Woenne, E. C.; Lammers, T.; Morgenstern, B.; Mueller, M. M.; Zentgraf, H.; Bock, M.; Eisenhut, M.; Semmler, W.; Kiessling, F., Specific targeting of tumor angiogenesis by RGD-conjugated ultrasmall superparamagnetic iron oxide particles using a clinical 1.5-T magnetic resonance scanner. Cancer Research 2007, 67 (4), 1555-1562.
    17. Dolman, M. E. M.; Fretz, M. M.; Segers, G. W.; Lacombe, M.; Prakash, J.; Storm, G.; Hennink, W. E.; Kok, R. J., Renal targeting of kinase inhibitors. International Journal of Pharmaceutics 2008, 364 (2), 249-257.
    18. Lammers, T.; Hennink, W. E.; Storm, G., Tumour-targeted nanomedicines: principles and practice. British Journal of Cancer 2008, 99 (3), 392-397.
    19. Lammers, T.; Subr, V.; Peschke, P.; Kuhnlein, P.; Hennink, W. E.; Ulbrich, K.; Kiessling, F.; Heilmann, M.; Debus, J.; Huber, P. E.; Storm, G., Image-guided and passively tumour-targeted polymeric nanomedicines for radiochemotherapy. British Journal of Cancer 2008, 99 (6), 900-910.
    20. Rijcken, C. J. F.; Schiffelers, R. M.; van Nostrum, C. F.; Hennink, W. E., Long circulating biodegradable polymeric micelles: Towards targeted drug delivery. Journal of Controlled Release 2008, 132 (3), E33-E35.
    21. Crommelin, D. J. A., Nanotechnological approaches for targeted drug delivery: hype or hope? New Biotechnology 2009, 25, S34-S34.
    22. Mulder, W. J. M.; Castermans, K.; van Beijnum, J. R.; Egbrink, M.; Chin, P. T. K.; Fayad, Z. A.; Lowik, C.; Kaijzel, E. L.; Que, I.; Storm, G.; Strijkers, G. J.; Griffioen, A. W.; Nicolay, K., Molecular imaging of tumor angiogenesis using alpha v beta 3-integrin targeted multimodal quantum dots. Angiogenesis 2009, 12 (1), 17-24.
    23. Talelli, M.; Rijcken, C. J. F.; Lammers, T.; Seevinck, P. R.; Storm, G.; van Nostrum, C. F.; Hennink, W. E., Superparamagnetic Iron Oxide Nanoparticles Encapsulated in Biodegradable Thermosensitive Polymeric Micelles: Toward a Targeted Nanomedicine Suitable for Image-Guided Drug Delivery. Langmuir 2009, 25 (4), 2060-2067.
    24. Dolman, M. E. M.; Harmsen, S.; Storm, G.; Hennink, W. E.; Kok, R. J., Drug targeting to the kidney: Advances in the active targeting of therapeutics to proximal tubular cells. Advanced Drug Delivery Reviews 2010, 62 (14), 1344-1357.
    25. Lammers, T.; Subr, V.; Ulbrich, K.; Hennink, W. E.; Storm, G.; Kiessling, F., Polymeric nanomedicines for image-guided drug delivery and tumor-targeted combination therapy. Nano Today 2010, 5 (3), 197-212.
    26. Lammers, T.; Subr, V.; Ulbrich, K.; Peschke, P.; Huber, P. E.; Hennink, W. E.; Storm, G.; Kiessling, F., Long-Circulating and Passively Tumor-Targeted Polymer-Drug Conjugates Improve the Efficacy and Reduce the Toxicity of Radiochemotherapy. Advanced Engineering Materials 2010, 12 (9), B413-B421.
    27. Oerlemans, C.; Bult, W.; Bos, M.; Storm, G.; Nijsen, J. F. W.; Hennink, W. E., Polymeric Micelles in Anticancer Therapy: Targeting, Imaging and Triggered Release. Pharmaceutical Research 2010, 27 (12), 2569-2589.
    28. Talelli, M.; Iman, M.; Rijcken, C. J. F.; van Nostrum, C. F.; Hennink, W. E., Targeted core-crosslinked polymeric micelles with controlled release of covalently entrapped doxorubicin. Journal of Controlled Release 2010, 148 (1), E121-E122.
    29. van Rooy, I.; Cakir-Tascioglu, S.; Couraud, P. O.; Romero, I. A.; Weksler, B.; Storm, G.; Hennink, W. E.; Schiffelers, R. M.; Mastrobattista, E., Identification of Peptide Ligands for Targeting to the Blood-Brain Barrier. Pharmaceutical Research 2010, 27 (4), 673-682.
    30. Talelli, M.; Hennink, W. E., Thermosensitive polymeric micelles for targeted drug delivery. Nanomedicine 2011, 6 (7), 1245-1255.
    31. Talelli, M.; Rijcken, C. J. F.; Oliveira, S.; van der Meel, R.; Henegouwen, P.; Lammers, T.; van Nostrum, C. F.; Storm, G.; Hennink, W. E., Nanobody – Shell functionalized thermosensitive core-crosslinked polymeric micelles for active drug targeting. Journal of Controlled Release 2011, 151 (2), 183-192.
    32. van Rooy, I.; Mastrobattista, E.; Storm, G.; Hennink, W. E.; Schiffelers, R. M., Comparison of five different targeting ligands to enhance accumulation of liposomes into the brain. Journal of Controlled Release 2011, 150 (1), 30-36.
    33. Crielaard, B. J.; Lammers, T.; Schiffelers, R. M.; Storm, G., Drug targeting systems for inflammatory disease: One for all, all for one. Journal of Controlled Release 2012, 161 (2), 225-234.
    34. Crielaard, B. J.; Rijcken, C. J. F.; Quan, L. D.; van der Wal, S.; Altintas, I.; van der Pot, M.; Kruijtzer, J. A. W.; Liskamp, R. M. J.; Schiffelers, R. M.; van Nostrum, C. F.; Hennink, W. E.; Wang, D.; Lammers, T.; Storm, G., Glucocorticoid-Loaded Core-Cross-Linked Polymeric Micelles with Tailorable Release Kinetics for Targeted Therapy of Rheumatoid Arthritis. Angewandte Chemie-International Edition 2012, 51 (29), 7254-7258.
    35. Dolman, M. E. M.; Harmsen, S.; Pieters, E. H. E.; Sparidans, R. W.; Lacombe, M.; Szokol, B.; Orfi, L.; Keri, G.; Storm, G.; Hennink, W. E.; Kok, R. J., Targeting of a platinum-bound sunitinib analog to renal proximal tubular cells. International Journal of Nanomedicine 2012, 7, 417-433.
    36. Joshi, M. D.; Unger, W. J.; Storm, G.; van Kooyk, Y.; Mastrobattista, E., Targeting tumor antigens to dendritic cells using particulate carriers. Journal of Controlled Release 2012, 161 (1), 25-37.
    37. Kunjachan, S.; Jayapaul, J.; Mertens, M. E.; Storm, G.; Kiessling, F.; Lammers, T., Theranostic Systems and Strategies for Monitoring Nanomedicine-Mediated Drug Targeting. Current Pharmaceutical Biotechnology 2012, 13 (4), 609-622.
    38. Lammers, T.; Kiessling, F.; Hennink, W. E.; Storm, G., Drug targeting to tumors: Principles, pitfalls and (pre-) clinical progress. Journal of Controlled Release 2012, 161 (2), 175-187.
    39. van der Meel, R.; Oliveira, S.; Altintas, I.; Haselberg, R.; van der Veeken, J.; Roovers, R. C.; Henegouwen, P.; Storm, G.; Hennink, W. E.; Schiffelers, R. M.; Kok, R. J., Tumor-targeted Nanobullets: Anti-EGFR nanobody-liposomes loaded with anti-IGF-1R kinase inhibitor for cancer treatment. Journal of Controlled Release 2012, 159 (2), 281-289.
    40. Talelli, M.; Oliveira, S.; Rijcken, C. J. F.; Pieters, E. H. E.; Etrych, T.; Ulbrich, K.; van Nostrum, R. C. F.; Storm, G.; Hennink, W. E.Lammers, T., Intrinsically active nanobody-modified polymeric micelles for tumor-targeted combination therapy. Biomaterials 2013, 34 (4), 1255-1260.
    41. van der Meel, R.; Vehmeijer, L. J. C.; Kok, R. J.; Storm, G.; van Gaal, E. V. B., Ligand-targeted particulate nanomedicines undergoing clinical evaluation: Current status. Advanced Drug Delivery Reviews 2013, 65 (10), 1284-1298.
    42. Heukers, R.; Altintas, I.; Raghoenath, S.; De Zan, E.; Pepermans, R.; Roovers, R. C.; Haselberg, R.; Hennink, W. E.; Schiffelers, R. M.; Kok, R. J.; Henegouwen, P., Targeting hepatocyte growth factor receptor (Met) positive tumor cells using internalizing nanobody-decorated albumin nanoparticles. Biomaterials 2014, 35 (1), 601-610.
    43. Kunjachan, S.; Pola, R.; Gremse, F.; Theek, B.; Ehling, J.; Moeckel, D.; Hermanns-Sachweh, B.; Pechar, M.; Ulbrich, K.; Hennink, W. E.; Storm, G.; Lederle, W.; Kiessling, F.; Lammers, T., Passive versus Active Tumor Targeting Using RGD- and NGR-Modified Polymeric Nanomedicines. Nano Letters 2014, 14 (2), 972-981.
    44. Novo, L.; Mastrobattista, E.; van Nostrum, C. F.; Hennink, W. E., Targeted Decationized Polyplexes for Cell Specific Gene Delivery. Bioconjugate Chemistry 2014, 25 (4), 802-812.
    45. Theek, B.; Gremse, F.; Kunjachan, S.; Fokong, S.; Pola, R.; Pechar, M.; Deckers, R.; Storm, G.; Ehling, J.; Kiessling, F.; Lammers, T., Characterizing EPR-mediated passive drug targeting using contrast-enhanced functional ultrasound imaging. Journal of Controlled Release 2014, 182, 83-89.
    46. Liu, J.; Jiang, X. L.; Hennink, W. E.; Zhuo, R. X., A modular approach toward multifunctional supramolecular nanopolyplexes for targeting gene delivery. Journal of Controlled Release 2015, 213, E123-E124.
    47. Novo, L.; Takeda, K. M.; Petteta, T.; Dakwar, G. R.; van den Dikkenberg, J. B.; Remaut, K.; Braeckmans, K.; van Nostrum, C. F.; Mastrobattista, E.; Hennink, W. E., Targeted Decationized Polyplexes for siRNA Delivery. Molecular Pharmaceutics 2015, 12 (1), 150-161.
    48. Shi, Y.; Lammers, T.; van Nostrum, C.; Hennink, W. E., Long circulating and stable polymeric micelles for targeted delivery of paclitaxel. Journal of Controlled Release 2015, 213, E127-E128.
    49. Shi, Y.; van der Meel, R.; Theek, B.; Blenke, E. O.; Pieters, E. H. E.; Fens, M.; Ehling, J.; Schiffelers, R. M.; Storm, G.; van Nostrum, C. F.; Lammers, T.; Hennink, W. E., Complete Regression of Xenograft Tumors upon Targeted Delivery of Paclitaxel via Pi-Pi Stacking Stabilized Polymeric Micelles. Acs Nano 2015, 9 (4), 3740-3752.
    50. Ashton, S.; Song, Y. H.; Nolan, J.; Cadogan, E.; Murray, J.; Odedra, R.; Foster, J.; Hall, P. A.; Low, S.; Taylor, P.; Ellston, R.; Polanska, U. M.; Wilson, J.; Howes, C.; Smith, A.; Goodwin, R. J. A.; Swales, J. G.; Strittmatter, N.; Takats, Z.; Nilsson, A.; Andren, P.; Trueman, D.; Walker, M.; Reimer, C. L.; Troiano, G.; Parsons, D.; De Witt, D.; Ashford, M.; Hrkach, J.; Zale, S.; Jewsbury, P. J.; Barry, S. T., Aurora kinase inhibitor nanoparticles target tumors with favorable therapeutic index in vivo. Science Translational Medicine 2016, 8 (325).


A welcome Nature Editorial

I reproduce below a comment I have left on this Nature editorial entitled “Go forth and replicate!“.

Nature Publishing Group encouragement of replications and discussions of their own published studies is a very welcome move. Seven years ago, I wrote a letter (accompanying a submission) to the Editor of Nature Materials. The last paragraph of that letter read: “The possibility of refuting existing data and theories is an important condition of progress of scientific knowledge. The high-impact publication of wrong results can have a real impact on research activities and funding priorities. There is no doubt that the series of papers revisited in this Report contribute to shape the current scientific landscape in this area of science and that their refutation will have a large impact.” [1]

The submission was “Stripy Nanoparticles Revisited” and it took three more years to publish it… in another journal; meanwhile Nature Materials continued to publish findings based on the original flawed paper [2]. The ensuing, finally public (after three years in the secret of peer review), discussions on blogs, news commentary and follow up articles were certainly very informative on the absolute necessity of changing the ways we do science to ensure a more rapid discussion of research results [3].

One of the lessons I draw from this adventure is that the traditional publishing system is, at best ill suited (e.g. Small: three years delay), or at worst (e.g. Nature Materials) completely reluctant at considering replications or challenges to their published findings. Therefore, I am now using PrePrints (e.g. to publish a letter PNAS won’t share with their readers [4]), PubPeer and journals such as ScienceOpen where publication happens immediately and peer review follows [5].

So whilst I warmly welcome this editorial, it will need a little more to convince me that it is not a complete waste of time to use the traditional channels to open discussions of published results.

[1] The rest of letter can be found at
[2] The article was eventually published in Small (DOI:10.1002/smll.201001465

2 comments on PubPeer

); timeline:

Nanoparticles for imaging and sensing in biology

This is the title of a 3x1H45 course which I will give early September at the European School On Nanosciences and Nanotechnologies (ESONN) in Grenoble. The focus is on inorganic nanoparticles, e.g. gold, silver, iron oxide, quantum dots for biological applications. It will be the third year I give this course. It is a small class format with 21 students coming from all over the world, from New Zealand to South Africa, Denmark, Italy, India and France.

I have opted for a mostly discussion-based format centered around selected publications. I am asking readers of this blog (optional but very much welcome!) as well as students registered for the track B of ESONN15 (mandatory) to suggest at least one article for discussion. To suggest a paper, simply add a comment to this post with a reference (link to the paper would be even better).

Papers can be selected because they are historic landmarks in the field; or because they are recent ground breaking discoveries; or because they raise important questions that we need to discuss to move forward. Please provide one or two lines of justification for why you think we should discuss this paper.

Over to you!

Gold nanorods to shine light on the fate of implanted stem cells


Joan Comenge

This is a guest post by Joan Comenge

Our work regarding the use of gold nanorods as contrast agents for photoacoustic tracking of stem cells has been just published (or here*). You can find all the technical details of the work there, so I will try to explain here the work for the readers who are not very familiar with our field.

It is important to have the appropriate tools to evaluate safety and efficacy of regenerative medicine therapies in preclinical models before they can be translated to the clinics. This is why there is an interest in developing new imaging technologies that enable real time cell tracking with improved sensitivity and/or resolution. This work is our contribution to this field.

To distinguish therapeutic cells from the patient’s own cells (or here from the mouse’s own cell),  the therapeutic cells have to be labelled before they are implanted. It is well known, that biological tissue is more transparent to some regions of the light spectrum than others. This fact is very easy to try at home (or at your favourite club): if you put your hand under a green light, no light will go through it, whilst doing the same under a red light the result will be very different. That means that red light is less absorbed by our body. Near infrared light is even less absorbed and this is why this region of the spectrum is ideal for in vivo imaging. Therefore, we made our cells to absorb strongly in the near infrared so we can easily distinguish them.

Gold nanoparticles of different sizes and shapes (synthesis and picture by Joan Comenge).

Gold nanoparticles of different sizes and shapes (synthesis and picture by Joan Comenge).

To do this, we labelled cells with gold nanoparticles. Interestingly, the way gold nanoparticles interact with light depends on how their electrons oscillate. That means that size and shape of the nanoparticles determine their optical properties, and this is one of the reasons why we love to make different shapes of nanoparticles. In particular, gold nanorods strongly absorb in the near infrared and they are ideal contrast agents for in vivo imaging.


Figure reproduced from: The production of sound by radiant energy; Science 28 May 1881; DOI: 10.1126/science.os-2.49.242

We have now cells that interact with light in a different way than the tissue. The problem is that light is scattered by tissue, so resolution is rapidly lost as soon as you try to image depths beyond 1 mm. Obviously, this is not the best for in vivo imaging. Luckily for us, Alexander Graham Bell realised 130 years ago that matter emits sounds when is irradiated by a pulsed light. This is known as the photoacoustic effect and it has been exploited recently for bioimaging. Photoacoustic imaging combines the advantages of optical imaging (sensitivity, real-time acquisition, molecular imaging) and the good resolution of ultrasound imaging because ultrasounds (or phonons), contrarily to photons, are not scattered by biological tissue.
GNR-35.2Si3 in cells_16

Silica-coated gold nanorods inside cells

To optimise the performance of our gold nanorods, we coated them with silica. Silica is glass and therefore it protects the gold core without interfering with its optical properties. This protection is required to maintain gold nanorods isolated inside cells since nanorods are entrapped in intracellular vesicles, where they are very packed. The absence of a protective coating ultimately would result in a broader and less intense absorbance band, which would be translated to a less intense photoacoustic signal and consequently a lower sensitivity in cell detection. This of special importance in our system, a photoacoustic imaging system developed by iThera Medical which uses a  multiwavelength excitation to later deconvolute the spectral information of the image to find your components of interest. Thus, narrow absorption bands helps to improve the detection sensitivity even further. With this we demonstrated that we were able to monitor a few thousand nanorods labelled-cells with a very good 3D spatial resolution for 15 days. This allowed for example to see how a cell cluster changed with time, see how it grows or which regions of the cell cluster shows the highest cell density. In addition, this work opens the door to new opportunities such as  multilabelling using gold nanorods of different sizes and consequently different optical properties to observe simultaneously different type of cells. We also believe that not only stem cell therapies, but also other fields that are interested in monitoring cells such as cancer biology or immunology can benefit from the advances described in our work.

You can find the original publication here (or here*).
All the datasets are available via Figshare.

This work was supported by the UK Regenerative Medicine Platform Safety and efficacy, focusing on imaging technologies. Joan Comenge was funded by the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme. The in vivo imaging was done in the Centre for Preclinical Imaging, the Electron Microscopy in the Biomedical EM unit and the Optical Microscopy in the Centre for Cell Imaging.

* the alternative link is to 50 free e-prints; the link will be removed once the paper is fully open access (in a couple of days).


Cluster of gold nanorod-labelled cells imaged by photoacoustic imaging three days after implantation in mice.

More hype than hope? #Biomaterials16

Congratulations to the organisers of the World Biomaterials Congress for having a high profile debate on the following proposition:

Nanotechnology is more hype than hope

I wish I could have attended as it is a topic I have given some thought… Thankfully, one of the attendees, Professor Laura Poole-Warren has done some live tweeting from the floor. So here is a storify.

SmartFlare Maths

SmartFlare are nanoparticle sensors which are sold by Merck and are supposed to detect mRNA inside live cells. The technology has been developed by Chad Mirkin. In his papers, the nanoparticles are called Nano-Flares or Spherical Nucleic Acids. I am saying “supposed to” because the central question of how those sensors could possibly reach the target that they are supposed to detect has not been addressed by Mirkin nor by Merck.

After evaluating the SmartFlare, we published recently our conclusions at ScienceOpen. We ran this research as an open science project, sharing our experimental results, analyses and conclusions in quasi real time using an open science notebook. All of the imaging data can also be consulted via our online Open Microscopy Environment repository.

Gal Haimovich, who reviewed our paper, first on his blog and then at ScienceOpen, suggested we should do some SmartFlare Maths (point 4 of his list of comments). This had been at the back of my mind for some time. There are various ways to look at this problem, but all those I have tried lead to the same conclusion that the protocols, results and conclusion published do not add up. Here is what I believe the simplest way to think of the SmartFlare Maths problem. As usual, comments and corrections would be very much appreciated.

Estimation of the number of SmartFlares per cell

SF-figure adapted from Giljohann

Adapted from Giljohan et al, Figure 1b

Estimate 1. SmartFlares are added to cells at a final concentration of 0.1 nM (following Merck’s protocol). For 400,000 cells and 20 μL (following Merck’s protocol), this would result in 150,000 SmartFlares per cell, assuming that all nanoparticles are uptaken.


Estimate 2. Giljohann et al  (Mirkin’s group) published a quantitative study of uptake of SmartFlares in various cell lines in 2007. From their Figure 1b, we can see that in the lower concentration range tested, there is a linear correlation between SmartFlare concentration in the medium and number of particles per cell. For cells exposed to a medium concentration of 0.1 nM, this would result in an uptake of 75 000 SmartFlares per cell. In the following discussion, we will use this lower estimate. With ~50 oligo probes per SmartFlare, this would give 3,750,000 oligo probes per cell.

Oligo probes per cell versus mRNA per cell

The copy number of any specific mRNA per cell depends on sequence, cell types, signalling events etc, but typically it ranges from a few copies to a few thousands of copies. Our estimate above indicates an excess of oligo probes of at least three orders of magnitude over the most abundant mRNA.

If just 0.1% of these probes would bind their target, it would block 3,750 mRNA resulting in silencing. However, Merck and Mirkin both report that there is no silencing effect in the conditions of these experiments. It follows that more than 99.9% of the SmartFlares do not bind their target mRNA.

Fluorescence background


Reproduced from Seferos et al, Figure 1.

Seferos et al (2007, Mirkin’s group) show that in the absence of release of the probe, fluorescence value of ~30% of the total value after release is observed (in ideal test-tube conditions, i.e. in the absence of nucleases). This is presumably due to a non-complete quenching of the fluorescence. For the SmartFlares to work, we would therefore have to detect a variation of less than 0.1% over a background of ~30%.