Sulfate or Phosphate?

Some months before @robField’s tweet setting off the train that led to the Eu sensor that discriminates PAP/PAPS, Ed Yates and myself were having a curry with Dulce Papy-Garcia from UPEC, who had examined one of our PhD students. A matter we discussed at length was ‘why sulfate’. That is, why does biology use both sulfate and phosphate to modify post synthesis proteins, polysaccharides and other molecules. We didn’t come up with an answer,  but the conversation led Ed and myself to consider that the question merited exploration. 

This we thought would be a simple matter. 

It turned out to be one of the most difficult papers Ed and myself have written, to the extent that after N drafts (where N is a significantly larger number than either of us had experienced in any previous writing exercise) and too many summers we still had nothing satisfactory. So, we cunningly inveigled two colleagues, Tim Rudd from NIBSC and Marcelo Lima from Keele to join us on what we advertised as the sunny beach of sulfate and phosphate, but which in reality was a rather dank quagmire. There is though something about strength in numbers, and with very helpful input from Steve Butler in Loughborough, we arrived at what we considered a satisfactory synthesis. Happily, the reviewers concurred, and the paper is now published at Royal Society Interfaces, “Phosphorylation and sulfation share a common biosynthetic pathway, but extend biochemical and evolutionary diversity of biological macromolecules in distinct ways”.

This is by no means the last word on the matter, but along with some previous thoughtful papers we cite (if we have missed one, please let me know) it provides some ideas that may help us to understand why biology co-opted particular elements from the inorganic world to perform groups of functions vital to life as we know it now.

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FGFs in tissue repair

Our review on fibroblast growth factors (FGFs) as tissue repair and regeneration factors, which we made available as a preprint from the time of submission is now published at PeerJ.

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Of nanoparticles, cells and polyanions

Of nanoparticles, cells and polyanions

It is the end of semester 2 so it’s marking season. Since we double mark (a good thing), the final year research projects are marked by both supervisor and an assessor, a member of staff who is not involved in the project. One of the projects I marked was Gemma Carolan’s on “How do SmartFlares RNA detection probes reach the cytosol? Available are the PDF of report, and posts here and here.

I had a sense of déjà vu while reading the project – the clear endosomal location of the SmartFlares, regardless of the DNA sequences brought me back to the days when antisense was the technology of the future for medicine.

While evaluating new technology it is useful to go back and look at other high flying technology. The reality is that it takes decades before we know whether the promise (and hype) were justified; this is true for any hot topic from stem cells to nanoparticles and graphene.

Antisense effects can be mediated by RNAse H, an enzyme that specifically cleaves RNA-DNA duplexes and which protects our cells from RNA viruses. There are other mechanisms, e.g., interference with splicing or translation, but the RNAse-H mediated transcript degradation should be central to many antisense effects. There were many papers reporting specific effects (evidenced by differences between sense, antisense and scrambled oligonucleotides sequences). These certainly contributed to success of individuals and of institutions, e.g., in UK Research Assessment Exercise and grant awards.

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A milestone

Sometime last night this blog received its 50,000th page view. I write this blog because I like to. That others find the content worth reading at times is lovely, thank you.

What has been read the most and the least?

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An accidental discovery

Changye and Yong’s first paper, up as a preprint at PeerJ
in accord with my 2015 and 2014 New Year resolutions describes an accidental discovery. One of their co-authors, Sarah Taylor, was exploring HaloTag as an alternative means of labelling protein to green fluorescent protein, and I thought it would be good to be able to have a pure in vitro system to validate labelling. So Changye and Yong made some recombinant HaloTag fibroblast growth factor-2 (HT-FGF2). When they showed me the gel, they noted that HT-FGF2 did not seem terribly promising, because there was quite a lot of protein in the bacterial pellet.

It is at this point that the professor earns his keep,

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Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells

Virginie’s first paper on her thesis work, “Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells” was published yesterday at PeerJ. She first put it up as a preprint (v1 here
revised v2 here and then submitted it – my first experience of this and something I will certainly do again.

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A prize worth winning: How many extracellular proteins bind to heparan sulfate?

There are many prizes for cultural activities, of which science is one. This week has seen the announcement of the Nobel prizes, a little earlier the IgNobels were awarded. There are, of course many other prizes. I have decided to set up my own.
A question that bugs me and which loomed large while I read the excellent review by Ding Xu and Jeff Esko from UCSD on “Demystifying Heparan Sulfate–Protein Interactions” is how many extracellular proteins are there?

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Covalent conjugation of proteins and sugars to nanoparticles

Dan Nieves’ paper on an easy and accessible method to covalently conjugate proteins, sugars and indeed pretty much any biomoleucle onto nanoparticles has just come out in Chem. Commun.

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Reproducing science: there are no stripes, but FGF-1 IS the universal ligand

Gradually, the structural problems in sciences are making their way to the surface. There have been articles in newspapers, The Economist and other magazines around the world on the subject. These are stimulated by the constant dripping of information and studies that sit awkwardly with the perceived notion of how science functions.

The high profile controversies tend to catch our attention, simply because of a sense of outrage amongst the wider community that nothing has been done to fix the problem, or that the fixes have been inadequate. Despite the outrage, it remains the case that only a very few are willing to put their head above the parapet and say something. There has been an interesting discussion of this on Athene Donald’s blog here.

Not surprisingly, the “reproducibility question” has gained quite a lot of traction( e.g., here and here). This leads to a simple question: what qualifies as a reproduction?

I argue that an important aspect of reproduction is that it is not necessarily actual reproduction, but a re-examination of observations made with better methods, which includes analytical tools. I have two examples of how scientists deal with the changing landscape of data and their interpretation in these circumstances. The first example is an instance of good practice and is common (or should be). The second seems to ignore the past and the clear message provided by the new data.

Example 1
This is from an excellent 2012 paper in Journal of Biological Chemistry that we discussed (again) in a recent lab meeting. It deals with the molecular basis for one member of the fibroblast growth factor family, FGF-1, being a universal ligand. That is, FGF-1 can bind all FGF receptor isoforms, whereas other FGFs show clear restriction in their specificity. These differences must lie in the structural basis of the recognition of the FGF ligand, the FGF receptor and the heparan suflate co-receptor. The first model put forward by Moosa Mohamadi was superseded in his 2012 paper, when he and his group obtained higher resolution structures of the complexes. This is a great step forward, as FGFs are not just important to basic biology, but they also impact on a wide range of diseases, as well as tissue homeostasis and regeneration. I highlight the following from the paper:
To quote (page 3073, top right column)
“Based on our new FGF1-FGFR2b and FGF1-FGFR1c structures, we can conclude that the promiscuity of FGF1 toward FGFR isoforms cannot be attributed to the fact that FGF1 does not rely on the alternatively spliced betaC’-betaE loop of FGFR for binding as we initially proposed (31).”

This paper provides a great example of how science progresses and is how we should all deal with the normal refinement of data and the implications of such refinements.

Example 2
This is from the continued discussions on whether the ligands on the surface of gold nanoparticles can phase separate into stripes. This has been the subject of a good many posts on Raphael Lévy’s blog (from here to here), following his publication a year ago of his paper entitled “Stripy nanoparticles revisited“, as well as commentary here and elsewhere.

Some more papers from Stellacci and collaborators have been published in 2013. The entire oeuvre has been examined in detail by others, with guest posts on Raphael Lévy’s blog (most recent here) and comments on PubPeer relating to a paper on ArXiv that takes apart the entire body of evidence for stripes.

What is quite clear, even to a non-specialist, is that the basics of experimental science had not been followed in the Stellacci papers on the organisation of ligands on nanoparticles published from 2004 to 2012. These basics include the importance of signal being greater than noise and ensuring that experimental data sample at sufficient depth to avoid interpolation; note that in no cases did instrumentation limitation require interpolation. This might happen to any of us, we are, after all “enthusiasts”.

To conclude, I refer to my quote from Seneca “Errare humanum est sed perseverare diabolicum”

This excellent advice is clearly being followed by one FGF lab. It would be good if this advice was adopted more generally across science. When we see real data and analysis (the hard stuff) that challenges our previous data and interpretations, we should all be happy to change these. This is how science (should) move forward. If everyone did this, then there would be no discussion regarding reproducibility. When we see more of the same stuff, without a clear hypothesis testing experiment, we are veering towards metaphysics.

Metaphysics is not science. I note that when data are hidden, so that analysis is restricted, we again enter the realm of metaphysics – hence, for example, the call for open access to clinical trials data.

Links with some relevance to the Seneca’s advice, reproducibility and so on:
There is an excellent post at The Curious Wavefunction’s Sci Am blog
PubPeer: here and here
Neuroskeptic’s post at Discover
Chembark’s post in response to an ACS Nano editorial on reporting misconduct.

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Christmas Reads and Reproducing Science

Lots of tweets on the subject of great reads in the run up to Christmas, and, reflecting my preponderance for following science, most have been science flavoured. At the start of October this year I came across an article in the Guardian on a new translation of Herodotus’ Histories.
This is my Christmas read and I am extremely impressed. I knew of Herodotus, but had never read his work. Not without controversy in the ancient and modern world, there is no doubt that he does indeed present evidence and the source, and often weighs up the quality of the evidence. I find this refreshing, because in science now we seem to have drifted into territory where the quality of data are often ignored and the conclusion, regardless of the quality of the data is all. The truth is the opposite; data are everything, though truth remains awkward at the best of times.

This impacts directly on the growing debate on the reproducibility of science, also called the replication problem, which has recently elicited a fair amount of discussion, e.g., here and here.

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