We, Constantin and Dominik, the newest members of OPIG (SABS rotation students, as usual) were lucky to have a conference suitable to our research within our rotation period and, granted an allowance from the powers that be, were able to visit this year’s Prague Protein Spring with the topic ‘Proteins at Work’. There, we spent four busy but very inspirational days with about 50 participants in a little palace, the Vila Lanna.

The general topic of this meeting led to a broad variety of talks representing a multitude of fields of protein research: from origins of life, over fuzzy intrinsically disordered proteins and crowded cells to metagenomics and functional sequence alignment annotation.

We picked four thought engaging talks to present at the group meeting on 08/05/2018; here are their summaries:

Protein engineering and in vitro evolution studies for the origins of life

Kosuke Fujishima from Tokyo Institute of Technology presented several examples of the research he conducts in the area of origins of life. Research on the origins of life are generally based around the questions how prebiotic monomers were created, how they condensed into polymers and how functionality emerged within these polymers.

The first example of his research deals with the condensation of prebiotic monomers on the ocean-earth crust-interface. Water cycling between the ocean and the outer layers of the earth’s core provided an environment of high pressure and high temperatures (80 – 200 °C) which is necessary for amino acid polymerisation. The mineral Olivine was found to attract amino acids to its surface and the serpentinisation reaction happening with Olivine might provide the necessary wet/dry cycle. Therefore, the researchers built a reactor aiming to investigate this potential polymerisation mechanism. They found that with providing six prebiotic amino acids, 28 out of 36 possible dipeptides could be found in the reactor. Furthermore, up to 10-mer linear polypeptides could be detected as well, providing evidence for a mechanism of early earth’s generation of polypeptides [unpublished].

The second project showed that both enzymes, CysE/CysK, responsible for the current production of cysteine from serine, could be re-engineered to contain no cysteine in their sequence. Interestingly, cysteine-free CysE showed higher reaction rates than the wild type. Additional reduction to cysteine- and methionine-free enzyme sequences only worked for CysE but not for CysK.[Fujishima et al. (2018)] Still, the experiments indicate that an enzyme world could have existed with a reduced number of amino acids compared to the 20(+) amino acids that we know today.

The third project we wanted to point out used a type of mRNA display that not only links the genotype (mRNA) with its corresponding phenotype (translated protein) but also allows the translated protein to interact with a randomised, non-translated part of the mRNA. This provided a framework for investigating the evolution of ribonucleotide-binding (RNP) proteins. When selecting for ATP-binding, it was observed that protein together with RNA had the best fitness landscape compared to protein selection or RNA selection alone. Further analysis revealed that most binding affinity of the ribonucleotide protein stemmed from its RNA part.[unpublished] These results give rise to the suggestion that RNA and proteins co-evolved, opposing the idea of a pure RNA world.

RNA-protein interactions and the structure of the genetic code

The next speaker added more to the research area of RNA-protein interaction and evolution. Bojan Zagrovic from the University of Vienna presented his research around the finding that pyrimidine (PYR) density of RNA regions is correlated with the corresponding protein region’s affinity to pyrimidine-containing bases (running means of 21 amino acids or 63 bases were used), with the highest correlation between mRNA PYR density and guanine affinity, having an average ‘typical’ Pearson correlation coefficient of 0.80.[Polyansky & Zagrovic (2013)]

This correlation is specific for the current genetic code, shown by random generation of genetic codes which could not reproduce such a correlated behaviour and by looking into three organisms with very different codon usage bias (homo sapiens, E. coli, M. jannaschii). Even though the three averages of codon usage were very different, the highest correlating pairs of mRNA and cognate proteins clustered together, having very similar codon usage. This was also true for the worst correlating pairs.[Hlevnjak & Zagrovic (2015)]

But the big question being: what does this correlation imply functionally?

Annotation analysis revealed that the highest correlating pairs were enriched in nucleotide-binding functions and intrinsically disordered proteins. Without claiming generalisability, Professor Zagrovic pointed out a case study done on RNA polymerase II which has a long disordered C-terminus build up by 26 repeats of a 7 amino acid motif. 248 RNAs were found to interact with RNA polymerase II and in all three reading frames of the interacting RNAs, amino acid codons of the polymerase’s C-terminus were enriched.[unpublished]

This indicates some regulation over gene expression but also several other hypotheses were made: the correlation between the protein regions’ affinity for their cognate mRNA regions might be relevant in virus assembly, since coding RNA and translated proteins have to be in close proximity with each other. The same could be true for some non-membrane-bound compartments, e.g. P-bodies. Or is this correlation characteristic a hint to mRNAs acting as chaperones for their respective proteins? The functional implications of this correlation, while highly speculative, nevertheless suggest exciting research to come in the future.

Fuzziness in protein assemblies

Research from a different, but equally thought provoking field was presented by Mónika Fuxreiter from the University of Debrecen. Her talk on the concept of fuzziness in protein complexes, which she introduced 10 years ago [Tompa & Fuxreiter (2008)], shed light on some more recent developments in the field as well as explaining the underlying concept for those of us (ourselves included) who have not encountered the concept as such before.

Fuzziness in the context of protein complexes describes a phenomenon in which intrinsically disordered proteins, instead of folding upon binding as one would usually observe, can sample several conformational states with different propensities, leading to the sampled states contributing with different strengths to the function of the protein complex and further leading to varying degrees of disorder in the bound state.

This observation has several implications for the understanding of the functionality of disordered proteins, since the relative propensity for different ensemble states in the bound form is thought to be highly susceptible to milieu influences, such as tissue specific splicing and post-translational modifications. Fuzziness (a term that was borrowed from the mathematical theory of fuzzy sets) could thus be a driver of functional adaptability of disordered proteins to cell-cycle stage, environmental influences or tissue type.

Evidence for fuzziness has been curated by the Fuxreiter group since 2015 [Miskei et al. 2017] in the FuzDB database and recently been used to develop a prediction algorithm [unpublished], that according to Professor Fuxreiter achieves highly accurate predictions of fuzziness on a comprehensive validation dataset.

Both the implications of fuzziness for the understanding of the mode of action for disordered proteins (and disordered regions in otherwise ordered proteins) certainly spiked our interest, not least due to the potential importance of a clear understanding of these mode of actions for drug development.

Investigation of mutually exclusive splicing events using the CATH FunFam framework

The last of the 4 talks we would like to single out in this blogpost highlighted recent progress in using structure-based databases for the investigation of complex cellular events.

Christine Orengo from UCL presented her group’s work on mutually exclusive splicing, which employed the FunFam framework of the CATH database to probe the structural and functional implications of these splicing events [Lam et al. (2018), under review].

The FunFams are a subcategory of CATH’s homologous superfamilies, which further divides the superfamilies based on clusters of residue conservation within each family, thus creating groupings of functionally related proteins [Rentzsch & Orengo (2013)].

Mutually exclusive splicing that were investigated using this framework are a group of splicing events in which only one of several specific exons is present in the spliced mRNA. These exons usually show a high level of sequence similarity, leading to a low disruption of the protein structure by the splicing event. It is thought that this feature is a reason for the relative enrichment of mutually exclusive exons amongst alternative splicing events in the proteome.

This high degree of sequence similarity further enabled the mapping of the mutually exclusive exons to FunFams in the CATH database and thus further onto protein structures. This allowed the Orengo group to conduct a ‘large scale systematic study of the structural/functional effects of MXE splicing’.

Their analysis found that variable residues between the exons are significantly enriched at the protein surface, both compared to other stretches of the protein sequence and compared to non-variable residues in the exons, and in close proximity (< 6 Angstroms) to functional sites of the protein.

The main conclusion drawn from these findings was that, as previously hypothesised, mutually exclusive exons are likely functional switches, since changes in the surface exposed area close to functional sites are likely to affect the protein function without strongly disrupting its structure.

In the eyes of the Orengo group, this makes these splicing events good candidates for drug targeting, particularly in cases where a tissue specific isoform can be drugged, since in that case off-target effects could potentially be significantly reduced.

Sources:

Fujishima et al. (2018). Reconstruction of cysteine biosynthesis using engineered cysteine-free enzymes. Scientific Reports

Hlevnjak & Zagrovic (2015). Malleable nature of mRNA-protein compositional complementarity and its functional significance. Nucleic Acids Res

Lam, S. D., Orengo, C., & Lees, J. (2018). Protein structure and function analyses to understand the implication of mutually exclusive splicing. BioRxiv

Miskei, M. et al (2017). FuzDB: Database of fuzzy complexes, a tool to develop stochastic structure-function relationships for protein complexes and higher-order assemblies. Nucleic Acids Research

Polyansky & Zagrovic (2013). Evidence of direct complementary interactions between messenger RNAs and their cognate proteins. Nucleic Acids Res

Rentzsch, R., & Orengo, C. A. (2013). Protein function prediction using domain families. BMC Bioinformatics

Tompa, P., & Fuxreiter, M. (2008). Fuzzy complexes: polymorphism and structural disorder in protein-protein interactions. Trends in Biochemical Sciences

 

In February I was very fortunate to attend the Biophysical Society 62nd Annual Meeting, which was held in San Francisco – my first real conference and my first trip to North America. Despite arriving with the flu, I had a great time! The conference took place over five days, during which there were manageable 15-minute talks covering a huge range of Biophysics-related topics, and a few thousand more posters on display (including mine). With almost 6,500 attendees, it was also large enough to slip across the road to the excellent SF Museum of Modern Art without anyone noticing.

The best presentation of the conference was, of course, Saulo’s talk on integrating biological folding features into protein structure prediction [1]. Aside from that, here are a few more of my favourites:

Folding proteins from one end to the other
Micayla A. Bowman, Patricia L. Clark [2]

Here in the COFFEE (COtranslational Folding Family of Expert Enthusiasts) office, we love to talk about the vectorial nature of cotranslational folding and how it contributes to the efficiency of protein folding in vivo. Micayla Bowman and Patricia Clark have created a novel technique that will allow the effects of this vectorial folding to be investigated specifically in vitro.

ClpX is an A+++ molecular motor that grabs proteins and translocates them through its pore. In vivo, its role is to denature substrates and feed them to an associated protease (ClpP) [3]. Bowman & Clark have used protein tags to initiate translocation of the target protein through ClpX, resulting in either N-C or C-N vectorial refolding.

They demonstrate the effect using YKB, a construct with two mutually exclusive native states: YK-B (fluoresces yellow) and Y-KB (fluoresces blue) [4]. In vitro refolding results in an equal proportion of yellow and blue states. Cotranslational folding, which proceeds in the N-C direction, biases towards the yellow (YK-B) state. C-N refolding in the presence of ClpX and ATP biases towards the blue (Y-KB) state. With this neat assay, they demonstrate that ClpX can mediate vectorial folding in vitro, and they plan to use the assay to investigate its effect on protein folding pathways and yields.

An ambiguous view of protein architecture
Guillaume Postic, Charlotte Perin, Yassine Ghouzam, Jean-Christope Gelly [Poster abstract: 5, Paper: 6]

This work addresses the ambiguity of domain definition by assigning multiple possible domain boundaries to protein structures. Their automated method, SWORD (Swift and Optimised Recognition of Domains), performs protein partitioning via the hierarchical clustering of protein units (PUs) [7], which are smaller than domains and larger than secondary structures. The structure is first decomposed into protein units, which are then merged depending on the resulting “separation criterion” (relative contact probabilities) and “compactness” (contact density).

Their method is able to reproduce the multiple conflicting definitions that often exist between domain databases such as SCOP and CATH. Additionally, they present a number of cases for which the alternative domain definitions have interesting implications, such as highlighting early folding regions or functional subdomains within “single-domain” structures.

Dual function of the trigger factor chaperone in nascent protein folding
Kaixian Liu, Kevin Maciuba, Christian M. Kaiser [8]

The authors of this work used optical tweezers to study the cotranslational folding of the first two domains of 5-domain protein elongation factor G.

In agreement with a number of other presentations at the conference, they report that interactions with the ribosome surface during the early stages of translation slows folding by stabilising disordered states, preventing both native and misfolded conformations. They found that the N-terminal domain (G domain) folds independently, while the subsequent folding of the second domain (Domain II) requires the presence of the folded G domain. Furthermore, while partially extruded, unfolded domain II destabilises the native G domain conformation and leads to misfolding. This is prevented in the presence of the chaperone Trigger factor, which protects the G domain from unproductive interactions and unfolding by stabilising the native conformation. This work demonstrates interesting mechanisms by which Trigger factor and the ribosome can influence the cotranslational folding pathway.

Predicting protein contact maps directly from primary sequence without the need for homologs
Thrasyvoulos Karydis, Joseph M. Jacobson [10]

The prediction of protein contacts from primary sequence is an enormously powerful tool, particularly for predicting protein structures. A major limitation is that current methods using coevolution inference require a large multiple sequence alignment, which is not possible for targets without many known homologous sequences.

In this talk, Thrasyvoulos Karydis presented CoMET (Convolutional Motif Embeddings Tool), a tool to predict protein contact maps without a multiple sequence alignment or coevolution data. They extract structural and sequence motifs from known sequence-structure pairs, and use a Deep Convolutional Neural Network to associate sequence and structure motif embeddings. The method was trained on 137,000 sequence-structure pairs with a maximum of 256 residues, and is able to recreate contact map patterns with low resolution from primary sequence alone. There is no paper on this yet, but we’ll be looking out for it!

1. de Oliveira, S.H. and Deane, C.M., 2018. Exploring Folding Features in Protein Structure Prediction. Biophysical Journal, 114(3), p.36a.
2. Bowman, M.A. and Clark, P.L., 2018. Folding Proteins From One End to the Other. Biophysical Journal, 114(3), p.200a.
3. Baker, T.A. and Sauer, R.T., 2012. ClpXP, an ATP-powered unfolding and protein-degradation machine. Biochimica et Biophysica Acta (BBA)-Molecular Cell Research, 1823(1), pp.15-28.
Acta (BBA) – Molecular Cell Research, 2012, 1823 (1), 15-28
4. Sander, I.M., Chaney, J.L. and Clark, P.L., 2014. Expanding Anfinsen’s principle: contributions of synonymous codon selection to rational protein design. Journal of the American Chemical Society, 136(3), pp.858-861.
5. Postic, G., Périn, C., Ghouzam, Y. and Gelly, J.C., 2018. An Ambiguous View of Protein Architecture. Biophysical Journal, 114(3), p.46a.
6. Postic, G., Ghouzam, Y., Chebrek, R. and Gelly, J.C., 2017. An ambiguity principle for assigning protein structural domains. Science advances, 3(1), p.e1600552.
7. Gelly, J.C. and de Brevern, A.G., 2010. Protein Peeling 3D: new tools for analyzing protein structures. Bioinformatics, 27(1), pp.132-133.
8. Liu, K., Maciuba, K. and Kaiser, C.M., 2018. Dual Function of the Trigger Factor Chaperone in Nascent Protein Folding. Biophysical Journal, 114(3), p.552a.
9. Liu, K., Rehfus, J.E., Mattson, E. and Kaiser, C., 2017. The ribosome destabilizes native and non‐native structures in a nascent multi‐domain protein. Protein Science.
10. Karydis, T. and Jacobson, J.M., 2018. Predicting Protein Contact Maps Directly from Primary Sequence without the Need for Homologs. Biophysical Journal, 114(3), p.36a.

As the sole representative of OPIG attending Biophys 2017 in New Orleans, I had to bear the heavy burden of a long and lonely flight and the fear of missing out on a week of the very grey Oxford winter. Having successfully crossed the border into the US, which was thankfully easier for me than it was for some of our scientific colleagues from around the world, I found my first time attending the conference to be full of very interesting and relevant science. While also covering a wide variety of experimental techniques and non-protein topics, the conference is so large and broad that there was more than enough to keep me busy over the five days, featuring folding, structure prediction, docking, networks, and molecular dynamics.

There were several excellent talks on the subject of folding pathways, misfolding and aggregation. A common theme was the importance of the kinetic stability of the native state, and the mechanisms by which it may be prevented from reaching a non-native global thermodynamic minimum. This is particularly important for serpins, large protease inhibitors which inactivate proteases by a suicide mechanism. The native and active state can be transformed into a lower energy conformation over long timescales. However, this also occurs by cleavage near the C-terminal end, which allows insertion of the C-terminal tail into a beta sheet, holding the cleaving protease inactive and therefore the stored energy is very important for function. Anne Gershenson described recent simulations and experiments to elucidate the order in which substructures of the complete fold assemble. There are many cooperative substructures in this case, and N-terminal helices form at an early stage. The overall topology appears to be consistent with a cotranslational folding mechanism inside the ER, but requires significant rearrangements after translation for adoption of the full native fold.

Cotranslational folding was also discussed by several others including the following: Patricia Clark is now using the YKB system of alternately folding fluorescent protein to find new translation stalling sequences; Anais Cassaignau described NMR experiments to show the interactions taking place between nascent chains and the ribosome at different stalled positions during translation; and Daniel Nissley presented a model to predict a shift in folding mechanism from post-translational to cotranslational due to specific designed synonymous codon changes, which agreed very well with experimental data.

To look more deeply into the evolution of folding mechanisms and protein stability, Susan Marqusee presented a study of the kinetics of folding of RNases, comparing the properties of inferred ancestral sequences to a present day thermophile and mesophilic E. coli. A number of reconstructed sequences were expressed, and it was found that moving along either evolutionary branch from the ancestor to modern day, folding and unfolding rates had both decreased, but the same three-state folding pathway via an intermediate is conserved for all ancestors. However, the energy transition between the intermediate and the unfolded state has evolved in opposite directions even while the kinetic stability remains similar. This has led to the greater thermodynamic stability seen in the modern day thermophile compared to the mesophile at higher temperatures and concentrations of denaturant.

There were plenty of talks discussing the problems and mechanisms of protein aggregation, with two focussing on light chain amyloidosis. Marina Ramirez-Alvarado was investigating how fibrils begin to grow and showed using microscopy that both soluble light chains and fibrils (more slowly) are internalised by heart muscle cells. They can then be exposed at the cell surface and become a seed to recruit other soluble light chains to form fibrils. Shannon Esswein presented work on the enhancement of VL-VL dimerisation to prevent amyloid formation. The variable domain of the light chain (VL) can pair with itself in a similar orientation to its pairing with VH domains in normal antibodies, or in a non-canonical orientation. Adding disulphide bonds to stabilise these dimers prevented fibril formation, therefore they carried out a small scale screen of 27 aromatic and hydrophobic ligands to find those which would favour dimer formation by binding at the interface. Sulfasalazine was detected in this screen and was also shown to significantly reduce fibril formation and could therefore be used as a template for future drug design.

Among the posters, Alan Perez-Rathke presented loop modelling by DiSGro in beta barrel membrane proteins which showed that the population of structures generated and scored favourably after relaxation at a pH 7 led to an open pore more often than at pH 5, consistent with experimental observations. There were two posters on the topic of prediction of membrane protein expression in bacteria and yeast presented by students of Bill Clemons, who also gave a great talk. Shyam Saladi has carefully curated datasets of successes and failures in expression in E. coli and trained a linear SVM on features such as RNA secondary structure and transmembrane segment hydrophobicity to predict the outcome for unknown proteins. This simple approach (preprint available here) achieved area under ROC curve of around 0.6 on a separate test set, and using more complex machine learning techniques is likely to improve this. Samuel Schulte is adapting the same method for prediction of expression in yeast.

Overall, it was a great conference and it was nice to hear about plenty of experimental work alongside the more familiar computational work. I would also highly recommend New Orleans as an excellent place to find great food, jazz and sunshine!