I am a research scientist in Gerhard Wagner’s group at Harvard Medical School, where I study protein structure and function. Our group uses a number of  biochemical and biophysical techniques, but principally we used Nuclear Magnetic Resonance (NMR) to study proteins. NMR is a powerful tool to observe protein structure, but is invaluable for studying protein dynamics and function at the atomic level. It is through these studies we are uncovering how protein-protein interactions, small molecule binding and enzymatic reactions are mediated by a protein’s ability to flex and move.

I am primarily interested in understanding how proteins adopt multiple structural states while acting as enzymes and transporters in pathogenic bacterial systems. While NMR is a powerful technique, it is often limited in the types of systems were it can be applied successfully. Part of my research efforts focus on circumventing these limitations by using advanced data acquisition techniques and novel chemical labeling schemes.


Iron Acquisition in Pathogenic Bacteria

Iron is an essential micro-nutrient for most organisms and is involved in countless biological processes. Bacteria must acquire iron from their environment and during infection the source of iron for bacteria is the host – that means humans! As such, pathogenic bacteria must compete with the host for iron – a battle that is fought at the molecular level. Hosts restrict their iron content by tightly binding iron to proteins and other molecule complexes, particularly heme. Pathogenic bacteria can steal iron from hosts by scavenging proteins bound to iron, by scavenging heme and heme binding proteins, or by direct extraction by releasing siderophores.

Siderophores are small molecules that bind to iron so tightly that they can steal it directly from host proteins. Free iron is particularly scarce in host tissues, having a concentration below 10-18 M. Many siderophores having binding constants for iron in the 10-52 M range – meaning that siderophores are also able to quickly mop up any free iron that may be available. My recent focus has been on discovering the mechanism by which bacteria synthesize their siderophores. We hope an understanding of this process will lead to novel antibiotic development.

Structure/Dynamics of Large Enzymes by NMR and Site Specific Isotopic Labeling

Enzymes are proteins that catalyze the chemistry for biology. Often times, enzymes can only do chemistry by adopting more than one structural state. Methods such as crystalography can often capture these states, but only as frozen snapshots. NMR is able to witness the movement back and forth between these states and take measurements of how fast this happens. This information is sometimes essential to understand how the chemistry takes place.

Many enzymes are in the 30+ kDa range. This size is challenging for the NMR method, so one of the primary methodological projects we work on is improving our methods for large proteins with site specific isotopic labeling.  This involves placing stable isotopes at specific locations of enzymes so we can not only determine their structures but measure enzymatic rates at these specific locations.

New Methods For Assign ing The Backbone of Large Proteins

Large proteins present a number of problems for study by NMR. Firstly, their large size means our ability to make measurements is restricted by a property called ‘relaxation’. Secondly, the large the protein the more signals we need to record in a limited amount of time and frequency space. In collaboration with Dr. Hari Arthanari at Dana Faber Cancer Institute and Dr. Paul Coote in Gerhard Wagner’s lab, we are exploring several methods that exploit the best ‘relaxation’ conditions while improving resolution of our data. These methods can be applied to regularly labeled protein samples and to a novel labeling scheme we have been developing were we use pyruvate rather than glucose as a carbon source for protein expression.

Non-Uniform Sampling And Data Analysis for NMR

Nuclear Magnetic Resonance is able to provide extensive molecular detail, however when applied to Proteins and Nucleic Acids it is a relatively insensitive and slow methodology. Improvements in instrument sensitivity and higher magnetic fields help, however to fully exploit these advances a lot of research has focused on saving time by sampling data intelligently – this is non-uniform sampling (NUS). NUS data requires special processing and we have worked to provide advances and distribute protocols for doing this. Our processing package, hmsIST, has been downloaded by over 200 labs and our sampling scheduler for Bruker spectrometers is used by over 100 labs. We continue to work to improve these methods and support users through a mailing list.

Part of my work focuses on integrating all these tools and protocols into a single package for processing and data analysis, which I call PAPUA (hence the bird of paradise image above). PAPUA is being written in python and extensively uses libraries and packages designed for doing scientific computations (numpy, sipy, scikit-learn etc). PAPUA also focuses on automatic data analysis with an emphasis on automatic assignment of backbone experiments. The philosophy is to not redo what has been done before but to act as a space where code can be written to respond to new advances in NMR experiments and technology. Users can be purely application level or since PAPUA is open source users are free to build their own tools.


Extracting Exchange Kinetic Parameters from ZZ / Nz type NMR Spectra.

This has been coded in python3 and uploaded to my GitHub site. You can find more details here.

Poisson Gap Sampling Scheduler for Topspin 3.0+

A tarball for the Poisson Gap Sampling Scheduler Macro for Bruker Topspin can be downloaded from here. Get the file, untar it and read the readme file for installation details.

Non-Uniform Sampling with hmsIST Resource Page

An extensive manual and resource page for the hmsIST reconstruction of Non-uniform Sampled data was originally placed under Gerhard Wagner’s web page. Because HMS is always changing things I moved my contributions to this location.


21) Hyberts, S. G., Robson, S. A., Wagner, G. (2017) Interpolating and extrapolating with hmsIST: seeking a tmax for optimal sensitivity, resolution and frequency accuracy. J. Biomol. NMR 68 (2), 139-154.

20) Nartey, W., Basak, S., Kamariah, N., Manimekalai, M., Robson, S., Wagner, G., Eisenhaber, B., Eisenhaber, F., Grüber, G. (2015) NMR studies reveal a novel grab and release mechanism for efficient catalysis of the bacterial 2‐Cys peroxiredoxin machinery. FEBS J. 282 (23), 4620-4638.

19) Nogueira, M. L. C., Sforça, M. L., Chin, Y. K. Y., Mobli, M., Handler, A., Gorbatyuk, YV. Y., Robson, S. A., King, G. F., ueiros-Filho, F. J., de Mattos Zeri, A. C. (2015) Backbone and side chain NMR assignments of Geobacillus stearothermophilus ZapA allow identification of residues that mediate the interaction of ZapA with FtsZ. Biomol. NMR Assign. 9 (2) 387-391.

18) Hyberts, S. G.*, Arthanari, H.*, Robson, S. A.*, Wagner, G. (2014) Perspectives in Magnetic Resonance: NMR in the Post-FFT Era. J. Magn. Reson. 241, 60-73. *Equal contribution

17) Spirig, T., Malmirchegini, G.R., Zhang, J., Robson, S.A., Sjodt, M., Liu, M., Kumar, K.K., Dickson, C. F., Gell, D. A., Lei, B., Loo, J.A., Clubb, R. T. (2013) Staphylococcus aureus uses a novel multidomain receptor to break apart human hemoglobin and steal its heme. J. Biol. Chem. 288 (2), 1065-1078.

16) Hyberts, S.G., Robson, S. A., Wagner, G. (2012) Exploring signal-to-noise ratio and sensitivity in non-uniformly sampled multi-dimensional NMR spectra. J. Biomol. NMR 55 (2), 167-178.

15) Wommack, A. J., Robson, S. A., Wanniarachchi, Y. A., Wan, A., Turner, C. J., Wagner, G., Nolan, E. M. (2012) NMR Solution Structure and Condition-Dependent Oligomerization of the Antimicrobial Peptide Human Defensin 5. Biochemistry. 51 (48), 9624–9637.

14) Robson, S.A., Jacobitz, A.W., Philips, M.L., Clubb, R.T. (2012) Solution Structure of the Sortase Required for Efficient Production of Infectious Bacillus anthracis Spores. Biochemistry. 51(40), 7953-63.

13) Villareal, V.A., Spirig, T., Robson, S.A., Liu, M., Lei, B., Clubb, R.T. (2011) Transient weak protein-protein complexes transfer heme across the cell wall of Staphylococcus aureus. J. Am. Chem. Soc. 133, 14176-9.

12) Rowland, S.L,, Wadsworth, K.D., Robson, S.A., Robichon, C., Beckwith, J., King, G.F. (2010) Evidence from artificial septal targeting and site-directed mutagenesis that residues in the extracytoplasmic β domain of DivIB mediate its interaction with the divisomal transpeptidase PBP 2B. J. Bacteriol. 192, 6116-25.

11) Weiner, E. M., Robson, S., Marohn, M., Clubb, R. T. (2010) The Sortase A Enzyme That Attaches Proteins to the Cell Wall of Bacillus anthracis Contains an Unusual Active Site Architecture. J. Biol. Chem.  285 (30), 23433-23443.

10) Robson, S.A., Peterson, R., Bouchard, L.S., Villareal, V.A., Clubb, R.T. (2010) A heteronuclear zero quantum coherence Nz-exchange experiment that resolves resonance overlap and its application to measure the rates of heme binding to the IsdC protein. J. Am. Chem. Soc. 132, 9522-3.

9) Pilpa, R.M.*, Robson, S.A.*, Villareal, V.A., Wong, M.L., Phillips, M. and Clubb, R.T. (2009) Functionally distinct NEAT (NEAr Transporter) domains within the Staphylococcus aureus IsdH/HarA protein extract heme from methemoglobin. J. Biol. Chem. 284, 1166-1176. *Equal contribution

8) Villareal, V.A., Pilpa, R.M., Robson, S.A., Fadeev, E.A. and Clubb, R.T. (2008) The IsdC protein from Staphylococcus aureus uses a flexible binding pocket to capture heme. J. Biol. Chem. 283, 31591-31600.

7) Gorbatyuk, V.Y., Nosworthy, N.J., Robson, S.A., Bains, N.P., Maciejewski, M.W., Dos Remedios, C.G., King, G.F. (2006). Mapping the phosphoinositide-binging site on chick cofilin explains how PIP2 regulates the cofilin-actin interaction. Mol. Cell. 24, 511-522.

6) Robson, S.A., and King, G.F. (2006) Domain architecture and structure of the bacterial cell division protein DivIB. PNAS 103, 6700-5.

5) Robson, S.A., and King, G.F. (2005) Backbone and side-chain 1H, 15N, and 13C assignments for the minor cis conformer of the b domain of the bacterial cell division protein DivIB. J. Biomol. NMR 33, 135.

4) Robson, S.A., Gorbatyuk, V.Y., Maciejewski, M.W., King, G.F. (2005) Backbone and side-chain 1H, 15N, and 13C assignments for the beta domain of the bacterial cell division protein DivIB. J. Biomol. NMR 31, 261-262.

3) Robson, S.A., Michie, K.A., Mackay, J.P., Harry, E., King, G.F. (2002) The Bacillus subtilis cell division proteins FtsL and DivIC are intrinsically unstable and do not interact with one another in the absence of other septasomal components. Mol. Microbiol. 44, 663-74.

2) Bains, N.P.S., Gorbatyuk, V.Y., Nosworthy, N.J., Robson, S.A., Maciejewski, M.W., dos Remedios, C.G., and King, G.F. (2002) Backbone and sidechain 1H, 15N, and 13C assignments for chick cofilin reveal an error in the reported sequence. J. Biomol. NMR 22, 193-194.

1) Blair, D.H., Robson, S., King, G., Bennett, M.R. (2001) Vesicle-associated proteins and transmitter release from sympathetic ganglionic boutons. Neuroreport. 12, 607-10.