Global NMR Discussion Meetings

Biological NMR

  • Effects of Membrane Composition on Kindlin-2 Binding to Phosphatidyl Inositol Phosphates in Lipid Bilayers

    Zainab Mustapha (Rutgers University, United States)

    Abstract: Kindlin-2, K2, is a peripheral membrane protein and co-activator of integrin signaling in the cell, which is implicated in cell migration, adhesion, and cancer. K2 contains a pleckstrin homology (PH) domain, which, like many PH domains, binds to the phosphoinositide components of the cell membrane, specifically phosphatidylinositol-3,4,5-trisphosphate (PIP3), to enhance integrin activation. However, the mechanism of PIP3 recognition and binding is not fully understood, as no structural studies to date use full-length PIP3 in lipid bilayers, focusing instead on the soluble inositol headgroup.
    In this study, we use a combination of solid-state and solution NMR to investigate the structure and dynamics of PIP3-bound K2-PH in a model membrane containing PIP3, phosphatidylcholine, phosphatidylserine, and cholesterol. We study changes in the bound state with respect to the model membrane and the unbound protein. Using proton detection and very fast MAS, ssNMR results show chemical shift perturbations in the backbone of the bound protein compared to the unbound form. These perturbations confirm interactions in areas predicted to interact with the membrane (in our MD simulations). We also describe how additional membrane components, such as cholesterol, can stabilize the binding of the protein.
    Together, these results suggest that PIP3 binding induces structural changes in membrane-interacting regions of K2-PH, and that additional membrane components may help stabilize this interaction. Our findings help explain the mechanism of K2-PH binding to PIP3s in the context of a full-length lipid bilayer, which has broad implications for the PIP-based regulation of numerous important cellular processes.

    1. Nicolas Bolik-Coulon Avatar
      Nicolas Bolik-Coulon

      Nice presentation!

      I have a few questions:
      1) Are the bilayers preserving their structural integrity upon spinning in MAS?
      2) T398 seem to split into two. Would you have an explanation for this?
      3) Can you quantify the fraction of PH bound to the bilayers?

      cheers

      Reply
    2. Zainab Mustapha Avatar
      Zainab Mustapha

      Thank you! Very good questions and observation
      1) Usually, we spin the rotors containing liposomes only at 15 kHz, because they preserve their structural integrity and give good linewidth at this MAS rate. However, the 31P 1D data of the bound sample was spun at 40 kHz and the 31P static spectra taken before and after shows that the bilayer structure is preserved. So yes, the bilayers preserve their structural integrity

      2) Very nice observation, I am still trying to make sense of all the changes we see.

      3) Yes, so we start out with solution NMR titration, which of course renders the membrane-associated protein invisible as the titration progresses. When we pellet the complex, we collect the supernatant and take 15N-HSQC to estimate how much of it is left in solution. We use this as a measure of what is bound to the bilayer.

      I hope this answers your question. Please let me know if you have any suggestions or input. I’ll be happy to take them. Thank you again.

      Reply
    3. KSHAMA SHARMA Avatar
      KSHAMA SHARMA

      Dear Zainab,
      Thank you for your presentation.

      1. I was wondering if you were able to determine the binding constants from your titration studies. If so, could you share the binding affinity you observed between the PH domain and PIP3?
      2. Looking at your static 31P spectra, I noticed slight differences between the bound and unbound forms. Could you please elaborate on what might be causing these differences?

      Thank you!

      Reply
    4. Zainab Mustapha Avatar
      Zainab Mustapha

      Hi KSHAMA,

      Very good questions.

      1. We didn’t determine binding affinity from our solution NMR titrations. However, in a pioneering work with the soluble headgroup of PIP3, the Kd was measured to be about 2.12 uM. It’s worth thinking about if the presence of the tails would give a different measurement.

      2. The presence of the protein may be inducing some sort of membrane curvature on the bound sample compared to the unbound. It can be that some of phosphates in the bilayer now have a different orientation as a result of protein binding. Overall, even though there are subtle differences between the two spectra, we think the bilayer may not be completely destroyed because at a different protein:lipid ratio (data not shown), the static spectra completely shows a different powder pattern.

      Thanks for engaging with my research and I hope this answers your questions. Happy to take any suggestions or further questions.

      Reply

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  • What happens when a 1H of a methyl group is substituted by a 19F?

    Gottfried Otting (The Australian National University, Australia)

    Abstract: Fluorine is bigger than hydrogen and the C-F bond is longer than a C-H bond, but not by much. CF groups prefer hydrophobic environments (think of Teflon). 19F-spins provide site-specific probes easy to detect by 1D 19F-NMR. Using cell-free protein synthesis, we replaced all valine residues in the protein GB1 by fluorinated analogues with a 19F spin in either the CG1 methyl group, the CG2 methyl group or both. The 19F NMR signals were distributed over a large chemical shift range. The protein structure remains unchanged. While CH3 groups rotate rapidly, the CH2F groups preferentially populate different staggered rotamers. Transient contacts between different fluorinated valine residues are manifested by through-space 19F-19F couplings that are observed more easily than 19F-19F NOEs.

    1. Marco Schiavina Avatar
      Marco Schiavina

      Hello! An amazing work! Thanks for sharing.

      I have a couple of questions.
      1) this might be a bit naif but I was wondering: I can clearly appreciate 3 distinct peaks for the 19F-G1 spectrum as well as 4 peaks in the 19F-G2 spectrum. Thus I was expecting 8 peaks in the G1-G2 spectrum. Could you comment on the minor forms and on the relative intensities of the major form of this latter spectrum?
      2) You mentioned you were decoupling 1H during 19F acquisitions thus I am assuming you are using a QCI-19F probe (or something similar). If this is the case, did you try any 19F-1H correlation experiment?
      3) In the abstract you mention that the protein structure is unchanged upon incorporation of the 19F moiety. How did you prove it? Do you think this would be true even for a putative CF3 group?

      Thanks again!

      Reply
    2. Gottfried Otting Avatar
      Gottfried Otting

      good questions!
      1) Difluorovaline is not as easily accepted by the E. coli valyl-tRNA synthetase as monofluorovaline. Therefore, the tiny amounts of canonical valine present in the cell-free reaction mixture get used preferentially and some of the protein ends up with 3 difluorovalines and 1 valine. This species produces different 19F chemical shifts. Statistically, ~20% of each site contains valine instead of difluorovaline.
      2) We use a 400, where 19F is on the X-channel like all other non-1H nuclei. Indeed, to assign the 19F-NMR spectrum, we used 1H-19F correlation spectra.
      3) We assigned the 1H NMR spectra. The 1H chemical shifts and NOEs are conserved. Circular dichroism indicates that the melting temperature dropped by ~10 degrees. A CF3 group would perturb the structure more. More critically, it could be quite a challenge for the valyl-tRNA synthetase.

      Reply
    3. Nicolas Bolik-Coulon Avatar
      Nicolas Bolik-Coulon

      Hello,
      Very interesting and very nice presentation!
      Just a few questions:
      1) the g1,g2 1D spectrum looks quite different from a ‘visual sum’ of the g1 and g2 1D spectra. Are the CSPs arising from the presence of more 19F in the g1,g2 sample?
      2) Did you measure some proton relaxation rates? Relaxation in CH3 (and even more in CF3) methyl groups is quite tricky to analyze, but maybe just the magnitude of the decay would be quite informative on the increased rigidity of the CF3.

      Cheers

      Reply
    4. Gottfried Otting Avatar
      Gottfried Otting

      1) Indeed, the 19F chemical shifts depend very much on whether there is another fluorine nearby, either in the same amino acid residue or simply in another residue nearby! Based on 1H-1H NOEs and the appearance of Halpha-Hbeta COSY-cross-peaks (reflecting large or small 3J(Alpha,Hbeta) coupling constants), the fluorovaline side chains feature the same Chi1 angles as the valine residues in the wild-type protein. Using a 1H,19F-HOESY spectrum, we obtained stereospecific resonance assignments of the 19F spins in the difluorovaline residues. In 3 of the 4 difluorovaline residues, the relative 19F-chemical shifts (high-field or low-field) proved to be conserved between the samples made with singly fluorinated valines and the sample made with difluorovaline. (Subscripts in the FF-TOCSY spectrum indicate the stereospecific resonance assignments.)

      2) Interesting idea! No, we haven’t measured the 1H relaxation of the CH2F groups. (We worked only with CH2F groups, not with CF3 groups, in order to minimise structural perturbations.) Obviously, the 1H relaxation of CH2 groups is difficult to compare with the 1H relaxation of CH3 groups. In an attempt to find evidence for minor rotamer species of the CH2F groups that may be in slow exchange with other rotamers, we performed 19F-CPMG experiments. In the protein made with difluorovaline, only the gamma2-fluorine of residue 54 showed significantly slower relaxation (36 s-1) when we applied 180 degree pulses rapidly as opposed to applying a single refocusing 180 degree pulse (26 s-1). The CH2F group associated with this fluorine atom is right in the hydrophobic core of the protein and more solidly immobilized than the other CH2F groups, which is also demonstrated by a large 3J(1H,19F) coupling. None of the other 19F spins relaxed as quickly.

      Reply
    5. Gottfried Otting Avatar
      Gottfried Otting

      Oops, correction: 26 s-1 with CPMG, 36 s-1 with a single 180(19F) refocussing pulse.

      Reply
    6. Zainab Amin Avatar
      Zainab Amin

      Very nice presentation and really fascinating work. I have a somewhat naive question!
      Since the CH₂F groups preferentially populate distinct staggered rotamers and exhibit through-space ¹⁹F–¹⁹F couplings, have you explored whether these interactions might also reflect transient conformational states of the protein backbone, rather than being driven purely by side-chain rotamer preferences? And do you think this strategy could be extended to detect low-population backbone conformers that are often invisible to other NMR probes?

      Reply
    7. Gottfried Otting Avatar
      Gottfried Otting

      Good thought!
      GB1 is a very stable protein and the backbone atoms would not easily deviate far from their average conformations. Nonetheless, in previous work, we found that a through-space scalar 19F-19F coupling can be detected between the CF3 groups of two residues of N6-trifluoroacetyl-L-lysine (TFAK) installed 33 residues apart (one of the TFAK residues being at the C-terminus of a solvent-exposed, flexible polypeptide segment). This observation is interesting because, in this case, the fluorine-fluorine contacts would certainly be transient and infrequent: https://doi.org/10.1021/jacs.1c10104
      The big question is, whether a scheme can be designed that uses this effect to detect non-random conformational changes of backbone conformations? I fear that the chemistry may become prohibitive. For example, the alpha-hydrogen would be difficult to replace by fluorine. Furthermore, there would be no detectable scalar coupling, unless the fluorine atoms definitely (and repeatedly) make a contact with some orbital overlap.

      Reply

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  • HSQC/F1-PSYCHE TOCSY NOAH Supersequence for the Analysis of Biofluids

    Aditi Pandey (Centre of BioMedical Research, India)

    Abstract: Accurate metabolite assignment is essential for effective metabolomics research. 2D NMR spectroscopy such as 1H-13C HSQC and 1H-1H TOCSY plays vital role in the identification of metabolites when combined with spectral databases. However, collecting high quality HSQC data from biofluids at natural 13C abundance requires large number of scans and hence NMR time typically of the order of 12-24 hours even at high fields (600-800MHz) with cryogenic probes. Performing further COSY and TOCSY in high resolution mode can result in additional hours. While NOAH (NMR by Ordered Acquisition using 1 H detection) supersequences offer
    time-efficient acquisition by combining multiple experiments in a single pulse sequence using a single recovery delay without sacrificing sensitivity. This is achieved by reusing unused magnetization from one experiment (e.g. HSQC) for subsequent ones (e.g. TOCSY). However due to high complexity of biofluids standard TOCSY spectra often suffers from peak overlap.
    The PSYCHE-TOCSY experiment helps resolve this by generating one sharp peak per resonance, thus minimizing overlap. Thus we want to introduce a novel HSQC+PSYCHE-TOCSY NOAH2 supersequence that combines HSQC with PSYCHE-TOCSY to provide fasterand clearer analysis of complex metabolite mixtures in biofluids.

    1. Marco Schiavina Avatar
      Marco Schiavina

      Hello! Very nice work congratulations!
      I was wondering, in your NOAH-based sequence, how much sensitivity is lost (if any) compared to the two experiments acquired separately? How much time is then saved?
      Thank you very much!

      Reply
      1. Aditi Pandey Avatar
        Aditi Pandey

        Hello Marco, very insightful query indeed!
        Actually when we record a PSYCHE-TOCSY separately at all the same acquisition parameters, there is negligible loss in the sensitivity. Here we have compared it with a regular TOCSY, which is although more sensitive but we are often not able to make full use of it due to the crowded peaks.
        I hope you understand. You can further ask any more queries.
        Thank you!

        Reply
    2. Nicolas Bolik-Coulon Avatar
      Nicolas Bolik-Coulon

      That’s quite impressive!
      How does the resolution of the NOAH sequence compares to the a PSYCHE-TOCSY, as opposed to a regular TOCSY?
      The NOAH TOCSY (pannel D in the 1D and 2D NMR Spectra assignment pannel) seems to show some artifacts at 5ppm in F1. Can you comment on that? Also water suppression seems a lot better, what is the reason?
      How does the signal-to-noise ratio compare between the experiments?

      Thanks!

      Reply
    3. Aditi Pandey Avatar
      Aditi Pandey

      Hello Nicolas, thanks for your kind appreciation.
      The resolution in PSYCHE-TOCSY from NOAH sequence is same as standalone PSYCHE-TOCSY. The artefact is due to some phase problem.
      For water suppression we have used presaturation block before the start of TOCSY sequence and excitation sculpting, placed just before the acquisition in homonuclear module.
      The SNR of the two experiments is very similar.
      I hope this resolves your query. Thank you!

      Reply

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  • High-resolution ssNMR study of Collagen Protein in Native Bone under Fast Magic Angle Spinning

    Bijaylaxmi Patra (Centre of Biomedical Research, India)

    LinkedIn: @Bijaylaxmi Patra; X: @BijaylaxmiNMR; Bluesky: @bijaylaxmi.bsky.social‬

    Abstract: Fast magic angle spinning (MAS) is a powerful technique in solid-state nuclear magnetic resonance (ssNMR) spectroscopy that effectively decreases line broadening and enables high-resolution structural study of biological systems. Nevertheless, its utility in probing complex and heterogeneous biomaterials in their native form has been constrained. In this study, we leveraged fast MAS (70KHz) to perform 2D ¹H-detected ¹³C–¹H double cross-polarization (CP) heteronuclear correlation experiments on native bone. This high-resolution method enabled the detection of previously unobserved inter-residue correlations within the aliphatic region of collagen. Additionally, our findings suggest potential π-interactions between aromatic amino acids and spatially proximal anionic or imino acids within the collagen triple helix. Our study paves the way for advanced ¹H-detected heteronuclear correlation experiments under fast MAS to more effectively elucidate the complex and heterogeneous structural organization of other native collagen-rich biological systems.

    1. Marco Schiavina Avatar
      Marco Schiavina

      Hello Patra, nice presentation!
      I was wondering if you can observe the same inter-residue correlation also exploiting other SS-NMR experiments such as the C-C DARR or similar.

      Reply
      1. Bijaylaxmi Patra Avatar
        Bijaylaxmi Patra

        Hi Marco, thanks for showing interest in my work.

        Yes, we may observe the same inter-residue correlations using other ssNMR experiments as well, and our future plans include performing such experiments to obtain ¹³C–¹³C correlations.
        However, as an initial study, we preferred ¹H-detected ¹³C–¹H experiments because they require significantly less experimental time compared to ¹³C–¹³C correlation experiments, especially since the experiments are conducted at natural isotopic abundance.

        Fast MAS techniques have not been widely used to study collagen in native bone due to concerns about friction-induced sample instability during long experimental durations. In our previous study (https://doi.org/10.1002/mrc.5508), we demonstrated the feasibility of acquiring ¹H–¹H correlations. Building on that, we now report ¹³C–¹H correlations, and we believe that ¹³C–¹³C experiments will be even more interesting in future studies.

        Reply
    2. Bijaylaxmi Patra Avatar
      Bijaylaxmi Patra

      Hi Marco, thanks for showing interest in my work.

      Yes, we may observe the same inter-residue correlations using other ssNMR experiments as well, and our future plans include performing such experiments to obtain ¹³C–¹³C correlations.
      However, as an initial study, we preferred ¹H-detected ¹³C–¹H experiments because they require significantly less experimental time compared to ¹³C–¹³C correlation experiments, especially since the experiments are conducted at natural isotopic abundance.

      Fast MAS techniques have not been widely used to study collagen in native bone due to concerns about friction-induced sample instability during long experimental durations. In our previous study (https://doi.org/10.1002/mrc.5508), we demonstrated the feasibility of acquiring ¹H–¹H correlations. Building on that, we now report ¹³C–¹H correlations, and we believe that ¹³C–¹³C experiments will be even more interesting in future studies.

      Reply
    3. Zainab Mustapha Avatar
      Zainab Mustapha

      Very nice presentation. I was just wondering if it would be interesting to study other components of the bone and how they are structured within the bone e.g the lipids.

      Reply
      1. Bijaylaxmi Patra Avatar
        Bijaylaxmi Patra

        Yes, it is indeed very interesting to study other components in bone, as it is rich in various types of molecules within its extracellular matrix.

        Bone is a fascinating biomaterial that my lab has been working on for many years. My seniors have already explored water–lipid interactions (https://doi.org/10.1016/j.ssnmr.2020.101666), water–mineral interactions (https://doi.org/10.1021/acsomega.2c01133), and citrate–collagen interactions within the bone matrix (https://doi.org/10.1021/acs.jpcb.1c01431).

        Specifically, regarding lipids in bone, the major type found in the matrix is triglycerides. Nidhi et al. studied lipids in hydrated, dehydrated, and H₂O–D₂O exchanged bone samples. They found that dehydration and H/D exchange significantly affect the transverse relaxation times (T₂) of triglycerides. These changes reflect alterations in the hydrogen bonding network and the local conformational dynamics of the lipid environment. Dehydration increased the mobility of triglycerides, indicating greater freedom of motion when water is removed. For further insights into other components, I recommend reading this book chapter: https://doi.org/10.1039/9781839165702-00614

        Thank you for your curiosity and engagement with our research.

        Reply
    4. KSHAMA SHARMA Avatar
      KSHAMA SHARMA

      Hi Bijaylakshmi, Thank you for the presentation.

      So if I understood correctly, you just ground the native bone and packed it directly into the rotor? Were there any other steps involved in preparing the sample for the fast MAS experiments?

      Reply
      1. Bijaylaxmi Patra Avatar
        Bijaylaxmi Patra

        Studies have shown that cryogenic grinding can alter the structure and hydration of bone. Therefore, we avoided both cryogenic and mechanical grinding. Instead, we carefully prepared small bone flakes (tiny pieces) using a scalpel and directly packed them into the rotor without any further processing. These flakes retained the structural and morphological features of the native intact bone.

        For further queries, you can refer to our published article: https://doi.org/10.1002/mrc.5508.

        I’m grateful for your interest and curiosity about my work.

        Reply

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  • Expanding Solid-State NMR Frontiers: The 1.2 GHz MAS System at CERM

    Rebecca Calamandrei (CERM, Italy)

    Abstract: The ITACA.SB project (https://www.itaca-sb.it/about/) is dedicated to potentiate the Italian Instruct-ERIC center, CERM/CIRMMP (https://www.cerm.unifi.it/) and significantly enhance structural biology (SB) services at selected laboratories of CNR. By enhancing service capacity and overcoming key access barriers, the project supports high-level life sciences research in Italy, boosts international visibility, and fosters stronger integration with European research infrastructures.
    Within this embodiment, a significant enhancement of the instrumentation at CERM/CIRMMP has enabled the expansion of both solution and solid-state NMR research as well as the biotechnologies instrumentation ranging a broad spectrum of experiment set-up and characterization techniques.
    As part of the infrastructure upgrades supported by ITACA.SB, the 1.2 GHz NMR spectrometer at CERM has been equipped with a 0.7 mm solid-state MAS probe. This high-field system offers exceptional performance for the investigation of solid-phase materials, including protein crystals and, more critically, non-crystalline systems such as amyloid fibrils, membrane proteins, and complex sediments. The implementation of ultra-fast magic angle spinning at 1.2 GHz enables the acquisition of high-resolution, proton-detected spectra, comparable in quality to those obtained in solution-state NMR. This advancement significantly expands the capabilities of solid-state NMR for probing molecular dynamics and intermolecular interactions in challenging biological and material samples.
    As the result of the synergic integration of upgraded infrastructure, targeted user support, and strategic collaboration, ITACA.SB not only strengthens Italy’s contribution to the structural biology landscape but also ensures that CERM/CIRMMP operates as a competitive hub for research, facilitating the alignment within the European Research area.

    1. Marco Schiavina Avatar
      Marco Schiavina

      Hello Rebecca! Nice presentation!
      Among all these beautiful instruments and applications presented here, I was intrigued by the performances of the 1.2 GHz equipped with the 0.7 mm MAS probe.
      Could you please comment about the resolution that can be obtained? How fast can you spin and what nuclear spins can be detected?

      Reply
    2. Zainab Mustapha Avatar
      Zainab Mustapha

      Nice presentation. I am curious about the NEO console. Does this mean one can set up two different experiments and both run simultaneously instead of queuing experiments?

      Reply
    3. Nicolas Bolik-Coulon Avatar
      Nicolas Bolik-Coulon

      Nice presentation of the facility!
      Is there any plans to use the 1.2 GHz with a liquid state probe?
      Smaller rotor means less materials. How does the sensitivity of the 0.7mm rotor compares with 1.3/1.9 mm rotors on a GHz for example?

      Reply

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  • Folding, Stability, and Oligomerization of HSPB8: An NMR-Based Investigation of Its α-Crystallin Domain

    Zainab Amin (IISER Pune, India)

    LinkedIn: @Zainab Khan; X: @ZAINAB_KHAN_7

    Abstract: HSPB8 (Heat Shock Protein B8) is an important chaperone that acts independently of ATP. Perturbations in HSPB8 function have thus been implicated in various protein aggregation disorders. Despite its biological importance, the structural and dynamic behaviour of HSPB8 under different stress conditions remains poorly understood. Understanding these perturbations is a key to elucidating the role of HSPB8 in protein quality control mechanisms. In this study, we performed a biophysical characterization of the α-crystallin domain (ACD) of HSPB8, involved in dimer formation, using solution-state nuclear magnetic resonance spectroscopy under different environmental perturbations. The effect on the structural integrity was characterized by monitoring changes in chemical shifts and linewidths of ACD in response to stressors. The results suggest that the ACD domain of HSPB8 is highly sensitive to environmental perturbations. In parallel, an initial investigation into the folding process of the protein has been carried out using multidimensional NMR spectroscopy. The backbone amide resonances of the unfolded protein were assigned through a combination of 3D NMR experiments, allowing mapping of amino acid residues to their respective peaks in the 2D 15N-1H HSQC spectrum. With the unfolded state characterized, this study aims to further elucidate the conformational landscape of the protein during refolding by gradually reducing the denaturant concentration and monitoring changes using the dynamic NMR techniques. These experiments are expected to yield mechanistic insights into the folding pathway of HSPB8, including the identification of transient, low-population intermediate states that may play critical roles in its chaperone activity and cellular function under stress.

    1. Chandan Singh Avatar
      Chandan Singh

      Thanks for a nice presentation. I have following questions regarding the same:
      What happens if you go in reverse order i.e. If the protein is denatured slowly with the help of urea and HSQC is recorded?

      Reply
    2. Zainab Amin Avatar
      Zainab Amin

      Thanks for asking! We have not tried that as it is difficult to assign the protein its folded monomeric form as of now. I think the protein may or may not follow the same folding pathway as we slowly unfold the protein from the folded form. To have an exact answer ,we may need to perform the experiments.

      Reply
    3. Nicolas Bolik-Coulon Avatar
      Nicolas Bolik-Coulon

      Thank you for this nice presentation!
      Your CEST profiles are quite pretty. I was wondering though if you had any information about the intermediate state, i.e. what is its nature? I thought that if it is was a folding intermediate, its chemical shift would be closer to the folded state but it seems like the major peak is moving away as you decrease the urea concentration.
      In addition, as you progress toward folding, do you expect to form oligomeric species? How do the R2 of the ground and excited states compare?

      Reply
      1. Zainab Amin Avatar
        Zainab Amin

        The observation that the chemical shifts of the minor (excited) state are distinct from both the unfolded and native conformations suggests that the intermediate represents a unique conformational ensemble. While it may involve local structure formation, it remains structurally distinct from the final folded state, a point further supported by our HSQC spectra. Although the fully folded state has not yet been assigned, overlay analysis shows that the intermediate does not fully converge with it, particularly at 2 M urea, where the HSQC profile deviates from the native-like pattern. The minor-state chemical shifts remain relatively consistent across decreasing urea concentrations, which indicates that the intermediate is structurally persistent. Regarding oligomerization, our concentration-dependent HSQC experiments for the folded construct showed only subtle line shape changes, consistent with weak self-association. This suggests a tendency towards dimer formation, though not strong enough to classify as higher-order oligomerization under the conditions tested. At 2 M urea, we do observe increased R₂ values and modest peak broadening, yet not to the extent typically seen with large oligomeric assemblies. Further validation is required to confirm this behavior.
        I hope this helps clarify some of your questions!
        Thank you!

        Reply
    4. Zainab Amin Avatar
      Zainab Amin

      The observation that the chemical shifts of the minor (excited) state are distinct from both the unfolded and native conformations suggests that the intermediate represents a unique conformational ensemble. While it may involve local structure formation, it remains structurally distinct from the final folded state, a point further supported by our HSQC spectra. Although the fully folded state has not yet been assigned, overlay analysis shows that the intermediate does not fully converge with it, particularly at 2 M urea, where the HSQC profile deviates from the native-like pattern. The minor-state chemical shifts remain relatively consistent across decreasing urea concentrations, which indicates that the intermediate is structurally persistent. Regarding oligomerization, our concentration-dependent HSQC experiments for the folded construct showed only subtle line shape changes, consistent with weak self-association. This suggests a tendency towards dimer formation, though not strong enough to classify as higher-order oligomerization under the conditions tested. At 2 M urea, we do observe increased R₂ values and modest peak broadening, yet not to the extent typically seen with large oligomeric assemblies. Further validation is required to confirm this behavior.
      I hope this helps clarify some of your questions!
      Thank you!

      Reply
    5. Raj Chaklashiya Avatar
      Raj Chaklashiya

      Hi Zainab, nice talk! I am curious about how you can use this technique to distinguish between different possible outcomes–like for example, if there were 2 or 3 intermediate states, how would that look like as compared to having one (which is what is shown)? I ask because I can imagine this method could be applied also to other proteins as well, which may have more than one intermediate state. Thanks!

      Reply

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  • Advancing GHz-class NMR: High sensitivity through larger volume cryoprobe and optimal control sequences

    David Joseph (Max Planck Institute for Multidisciplinary Sciences, Germany)

    X: @DaJo_1729

    Abstract: Improving the sensitivity of nuclear magnetic resonance (NMR) spectroscopy requires advancements in both instrument technology and experimental methodology. In this study, we introduce the first proton-detected large volume cryoprobe designed for 1.2 GHz instruments, leveraging optimal control pulse sequences to enhance performance (Sci. Adv. 9,eadj1133, 2023). Our results demonstrate up to a 56% increase in sensitivity and more than a twofold reduction in experimental time compared to the small volume cryoprobes in use at the moment. Additionally, we systematically optimized the experimental conditions to fully exploit the capabilities of GHz-class magnets. To further extend the benefits of our approach, we developed a library of optimal control triple resonance experiments, enabling boosted sensitivity for advanced NMR applications.

    1. Cory Widdifield Avatar
      Cory Widdifield

      When comparing the results from the 5 mm TCI probe at 1.2 GHz with the 5 mm TCI probe at 950 MHz, what is the most surprising/interesting/useful insight that you have personally encountered? In the future, what do you think might be the most useful/interesting insights enabled by performing experiments at 1.2 GHz?

      Reply
      1. David Joseph Avatar
        David Joseph

        The most useful insight is that bio-NMR experiments perform much better using optimal control pulses. A 5 mm TCI at 950 MHz approaches the power availability limit for broadband pulses, particularly for the 13C and 15N channels. At 1.2 GHz, a 5 mm TCI can only be used with optimal control pulses. However, using optimal control pulses with fields starting from 800 MHz would provide free signal enhancement and save valuable experimental time.

        The most interesting insights would come from performing experiments at 1.2 GHz to study biomolecular dynamics. All B₀-dependent parameters, such as CSA and alignment, reach their maximum values at this frequency, enabling access to data on motions that would otherwise be impossible to observe with lower field magnets. Increased resolution at 1.2 GHz would also be useful for studying larger proteins and intrinsically disordered proteins.

        Reply
        1. Cory Widdifield Avatar
          Cory Widdifield

          Thank you for your response, David.

          Reply
    2. Gottfried Otting Avatar
      Gottfried Otting

      These are important reference data.
      1) Wouldn’t one expect that the sensitivity obtained with a Shigemi tube is either the same or less than that obtained with a conventional 5 mm tube?
      2) Which compound and signal did you use to measure the sensitivities in the presence of different salt concentrations – ubiquitin or sucrose?
      3) Does CSA relaxation of ubiquitin amide protons broaden their 1H NMR signals noticeably more than at, say, 950 MHz?

      Reply
      1. David Joseph Avatar
        David Joseph

        1) The sensitivity of a Shigemi depends on the amount of sample available. It is especially sensitive when a lower volume of sample is available. There is also an optimal height that provides the best signal-to-noise ratio when using a Shigemi tube. Our concern here was B_1 inhomogeneity, which is lower with a Shigemi tube. However, since the pulses also compensate for ±20% inhomogeneity, we only see only a slight improvement in sensitivity when using a Shigemi tube.

        2) It was p53 1-73, a disordered protein, in a Tris-Bis buffer, using optimal control HNCA sequence.

        3) Thanks for the question! I just looked it up, and for an HNCO experiment, the difference is around 3 Hz, while for an HSQC, it’s around 1 Hz (along the proton dimension). It is broader at 1.2 GHz.

        Reply
    3. David Joseph Avatar
      David Joseph

      1) The sensitivity of a Shigemi depends on the amount of sample available. It is especially sensitive when a lower volume of sample is available. There is also an optimal height that provides the best signal-to-noise ratio when using a Shigemi tube. Our concern here was B_1 inhomogeneity, which is lower with a Shigemi tube. However, since the pulses also compensate for ±20% inhomogeneity, we only see only a slight improvement in sensitivity when using a Shigemi tube.

      2) It was p53 1-73, a disordered protein, in a Tris-Bis buffer, using optimal control HNCA sequence.

      3) Thanks for the question! I just looked it up, and for an HNCO experiment, the difference is around 3 Hz, while for an HSQC, it’s around 1 Hz (along the proton dimension). It is broader at 1.2 GHz.

      Reply
    4. Bijaylaxmi Patra Avatar
      Bijaylaxmi Patra

      Hi David, brilliant presentation. Clear, concise, and insightful.
      You mentioned a useful tip about using buffers with lower conductivity and larger ions. Could you please elaborate on why this is beneficial and how exactly it helps in practice?

      Reply
      1. David Joseph Avatar
        David Joseph

        Hi, thank you! This has to do with noise contribution from the sample, which is especially problematic for the cryoprobe. The noise from the sample is proportional to its conductivity and dielectric properties. Using a buffer with larger ions will lower the mobility, thus lowering the conductivity of the buffer and reducing the noise from the sample. This increases the signal-to-noise ratio of the spectrum.

        Reply
    5. David Joseph Avatar
      David Joseph

      Hi, thank you! This has to do with noise contribution from the sample, which is especially problematic for the cryoprobe. The noise from the sample is proportional to its conductivity and dielectric properties. Using a buffer with larger ions will lower the mobility, thus lowering the conductivity of the buffer and reducing the noise from the sample. This increases the signal-to-noise ratio of the spectrum.

      Reply

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  • Understanding the differential RNA-binding of HuD isoforms through conformational dynamics using solution NMR spectroscopy

    Nikhil Sunny (IISER Pune, India)

    LinkedIn: @Nikhil Sunny; X: @Nikhil__Sunny__

    Abstract: HuD is an RNA-binding protein (RBP) essential for neuronal development and glucose homeostasis. It has tandemly arranged three RNA recognition motifs (RRMs). Multiple isoforms, namely, HuD A, HuD B, and HuD D—have been reported that are differentially expressed in various tissues. The A and B isoforms both feature an unstructured N-terminal region; however, the A isoform has five additional amino acids when compared to the B isoform. This difference significantly impacts the RNA-binding and translation of insulin 2 mRNA. While the structure of HuD RRM12 is known, it does not include the unstructured N-terminal region, creating a gap in understanding its role in RNA targeting. In this study, we focus on understanding the role of the unstructured N-terminal region of A and B isoforms in the RNA-binding activity of the RRM1 domain by using NMR-based dynamics experiments and other biophysical techniques. FOur preliminary results show that the presence of the N-terminal leads to line-broadening and the disappearance of peaks in the 2D 15N-1H HSQC spectra. The disappeared peaks are mainly from the N-terminal region and the possible site of intra- and/or intermolecular interactions. In the presence of the N-terminal region, CSP is found in or near the RNP motifs of RRM1, which are the sites for RNA binding. We believe that this study will provide insights into how intrinsically disordered regions affect the intrinsic dynamics and RNA-binding activity of the RRM.

    1. Nicolas Bolik-Coulon Avatar
      Nicolas Bolik-Coulon

      Interesting!
      Although I believe you are planning on further experiments to confirm the interaction of the N-ter with the folded domain, can you comment on the effect it could have on the binding to RNA?
      Also, how do the R1 and R2 of the N-ter tail evolve as a function of residue number?

      Reply
      1. Nikhil Sunny Avatar
        Nikhil Sunny

        1) The RNA-binding region can either be masked, reducing overall binding affinity, or it can function as an auxiliary region that enhances binding affinity. Since this RNA recognition motif (RRM) is a weak binder, we are working on optimizing the experimental parameters for the binding studies. I suspect it will act as an auxiliary region facilitating RNA binding, as shown from EMSA studies on Isoforms of HuD (full-length)(https://doi.org/10.1371/journal.pone.0194482)
        2) “R1 and R2 of the N-ter tail evolve as a function of residue number.” I haven’t done those experiments. That’s the next part of my project.

        Reply
    2. Chandan Singh Avatar
      Chandan Singh

      Interesting work:

      What type of experiments you are planning to look for exact functional role of this protein?

      Reply
      1. Nikhil Sunny Avatar
        Nikhil Sunny

        I will be doing in vitro studies only; majorly binding studies with RNA using ITC, NMR, fluorescence, etc.

        Reply

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  • Characterizing Metabolic Dysregulation in Early-Stage Chronic Kidney Disease for Diagnostic Insight

    Upasna Gupta (Centre of Biomedical Research (CBMR) & Lucknow and Academy of Scientific and Innovative Research(AcSIR), India)

    LinkedIn: @Upasna Gupta; X: @Upasnagupta30

    Abstract: The progressive illness known as chronic kidney disease (CKD) can often be challenging to diagnose in its early stages with conventional diagnostic approaches such as serum creatinine and albumin assessment. Identifying possible biomarkers for early detection and personalized treatment, as well as physiological changes linked to early CKD—an area that hasn’t been fully investigated before—is the goal of this study to address this gap.
    We performed a metabolomic analysis using ¹H NMR on 115 human serum samples (24 healthy controls, 91 patients with early-stage CKD). MetaboAnalyst 6.0 was used for data pre-processing and statistical analyses (PCA, PLS-DA, OPLS-DA, ANOVA, and Wilcoxon Mann-Whitney test). Strong differentiation between CKD stages was shown by random forest modelling. The KEGG database was used to perform pathway enrichment, and ROC analysis evaluated the diagnostic value of important metabolites.
    Across CKD stages, significant changes in ten different metabolites: myo-inositol, glycerol, pyruvate, carnitine, phenylalanine, tyrosine, histidine, TMAO, 2-hydroxyisobutyrate, and 3-hydroxyisobutyrate (p 1). AUC values > 0.7 from ROC curves demonstrated its potential for diagnosis. Pathway analysis revealed significant dysregulation in metabolism of inositol phosphate, tyrosine, histidine, pyruvate, and biosynthesis of phenylalanine, tryptophan and tyrosine.
    This comprehensive metabolomics investigation identified potential early-stage CKD biomarkers in addition to significant metabolic abnormalities. These findings could help provide individualized care for CKD early management.

    1. Chandan Singh Avatar
      Chandan Singh

      Thanks for a nice presentation. I have following questions regarding the same:
      1. In the stack plot showing the 1D NMR spectra shown gradual variation of creatinine and format in different groups but these two do not show up in the contributing metabolic factors of group deafferentation. What can be possible explanation?

      2. Similarly, my-inositol does not seem to vary much in the 1D plots but its there in contributing factors of group differentiations. What can be the reason?
      Thanks again.

      Reply
      1. Upasna Gupta Avatar
        Upasna Gupta

        Thank you, sir.
        1. Although creatinine was found to be significantly altered when comparing G3a and G3b groups, indicating that its changes become more prominent in later stages of CKD. However, since our primary aim was to identify early-stage biomarkers beyond conventional markers like creatinine, we did not include it in the final list of contributing factors for group deafferentation, though detailed results are provided in the manuscript.

        Formate, on the other hand, showed significant differences when comparing early-stage CKD patients to controls. However, it may not have contributed strongly to the variance specifically within the deafferentation group, and thus was not highlighted in the final metabolic signature for that group.

        2. Great observation, sir, although myo-inositol does not display a marked shift in the 1D NMR stack plots, it was identified as a significant contributor in the multivariate analysis. This suggests that its variation across groups is subtle yet consistent, not readily apparent to the eye but statistically relevant when analysed in the context of the full metabolic profile.

        Reply
    2. Marco Schiavina Avatar
      Marco Schiavina

      Hey, very interesting work, I was wondering how did you handle the large lipo protein signals arising from the blood samples. Did you filter them out? what kind of NMR pulse sequences did you use? Is there any evidence of these proteins to be a biomarker of the disease?

      Reply
      1. Upasna Gupta Avatar
        Upasna Gupta

        Thank You, Dr. Marco Schiavina
        Yes, we filtered the serum samples using a 3 kDa Amicon filter to remove larger proteins and lipoproteins. However, as reported in earlier studies, small lipid fragments can still appear in the aliphatic region (δ 0.75–2.5 ppm) due to aggregation or interactions with other macromolecules. To suppress these broad signals and focus on low-molecular-weight metabolites, we used the CPMG pulse sequence, which attenuates macromolecular signals. This approach enhanced the spectral resolution and improved our ability to reliably detect metabolites associated with CKD-related metabolic dysregulation.
        While we didn’t focus on lipoproteins as biomarkers in this study, there’s growing evidence supporting their relevance, and it’s a great direction for future research.

        Reply
    3. Upasna Gupta Avatar
      Upasna Gupta

      Thank you, sir.
      1. Although creatinine was found to be significantly altered when comparing G3a and G3b groups, indicating that its changes become more prominent in later stages of CKD. However, since our primary aim was to identify early-stage biomarkers beyond conventional markers like creatinine, we did not include it in the final list of contributing factors for group deafferentation, though detailed results are provided in the manuscript.

      Formate, on the other hand, showed significant differences when comparing early-stage CKD patients to controls. However, it may not have contributed strongly to the variance specifically within the deafferentation group, and thus was not highlighted in the final metabolic signature for that group.

      2. Great observation, sir, although myo-inositol does not display a marked shift in the 1D NMR stack plots, it was identified as a significant contributor in the multivariate analysis. This suggests that its variation across groups is subtle yet consistent, not readily apparent to the eye but statistically relevant when analysed in the context of the full metabolic profile.

      Reply
    4. Upasna Gupta Avatar
      Upasna Gupta

      Thank You, Dr. Marco Schiavina
      Yes, we filtered the serum samples using a 3 kDa Amicon filter to remove larger proteins and lipoproteins. However, as reported in earlier studies, small lipid fragments can still appear in the aliphatic region (δ 0.75–2.5 ppm) due to aggregation or interactions with other macromolecules. To suppress these broad signals and focus on low-molecular-weight metabolites, we used the CPMG pulse sequence, which attenuates macromolecular signals. This approach enhanced the spectral resolution and improved our ability to reliably detect metabolites associated with CKD-related metabolic dysregulation.
      While we didn’t focus on lipoproteins as biomarkers in this study, there’s growing evidence supporting their relevance, and it’s a great direction for future research.

      Reply

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  • Fibrosis Under the Lens: NMR Metabolomics and Machine Learning Illuminate Hidden Pathways and Offer a Non-Invasive Alternative to Liver Biopsy”

    Shreya Pandey (Centre of Biomedical Research, India)

    LinkedIn: Shreya Pandey; X: @shreyapandey171

    Abstract: The landscape of chronic liver disease has changed significantly, with metabolic dysfunction-associated steatotic liver disease(MASLD) now emerging as the most widespread form worldwide. In Asia, particularly in India, the prevalence of MASLD is increasing, largely driven by poor dietary habits and a sedentary way of life. MASLD spans from fat deposition to inflammation and fibrosis. Fibrosis stands out as the most critical indicator of liver-related complications and overall risk of death in MASLD. Early identification of fibrosis is critical, but current tests are often invasive or unreliable. While studies have explored metabolic changes in MASLD, few have focused on distinguishing early-stage fibrosis from steatosis.
    In this study, we used NMR-based metabolomics to analyse serum samples from n = 103 MASLD patients, divided into fibrosis (n = 44) and non-fibrosis (n = 59) groups based on standard non-invasive scoring systems. We identified seven metabolites—arginine, glycerol, aspartate, glucose, phenylalanine, histidine, and citrate—that significantly differed between the two groups and showed good diagnostic potential (AUROC> 0.70). Pathway analysis revealed disruptions in arginine and nitrogen metabolism, associated with liver scarring processes, and in energy and lipid metabolism, pointing to mitochondrial dysfunction and lipotoxic stress. Reduced aspartate levels also suggested loss of natural protection against fibrosis.
    This is the first study of MASLD cohort to differentiate early-stage fibrosis from steatosis using metabolomics. Our findings highlight the potential of a simple NMR based blood test to aid early diagnosis, guide treatment decisions, and personalize care—offering a non-invasive alternative to improve MASLD management.

    1. Chandan Singh Avatar
      Chandan Singh

      Thanks for the nice presentation. I have following questions related to the presentation:

      1. As per the study enhanced level of arginine leads to increased proline synthesis. Is this enhanced proline level reflected in metabolic profile?
      2. How is the lipid profile? Are there specific lipids which are changing?
      3. How does enhanced level of collagen synthesis lead to fibrosis?
      4. What portion of the result was used in machine learning?

      Thanks again

      Reply
      1. Shreya Pandey Avatar
        Shreya Pandey

        Thank you sir.
        1- Yes sir, even the proline level was enhanced in the NMR profiling , however it didnot match the criteria to be considered as significant metabolite ( despite having p value 1 , the AUC value was 0.65 so we had to exclude it).
        2- The few lipids that we obtained using diffusion edited pulse program also profile had significant difference. -CO-CH2-CH2- (corresponding to cholesterol and FA{TAG and Phospholipids}) was found to be increased in fibrotic cohort, similarly PUFA was found to be decreased in fibrotic cohort. As we did using NMR we have limited data corresponding to lipids. Once we use LC we might get broader insights which we will be starting soon
        3- When there is continuous injury or inflammation to liver , Hepatic stellate cells gets activated due to cascade of events. These HSCs are major contributers for collagen. When the level of collagen increases , it starts accumulating in the liver , distorting the normal structure and function and liver and eventually forming scarred tissue. This condition is called fibrosis.
        4- Only the data from bins of significant metabolites was used. We excluded the water region and the regions that were not significant

        Reply
    2. Chandan Singh Avatar
      Chandan Singh

      Thanks for a nice presentation. I have following questions:

      1. As shown in the presentation the enhanced level of arginine leads to increased collagen production via increased proline level. Is increased proline reflected in the NMR profiling?
      2. How is does lipid profile look? Any specific lipids which are enhanced?
      3. How does increased collagen lead to liver fibrosis?
      4. What exact data was used in machine learning?

      Thanks again

      Reply
      1. Shreya Pandey Avatar
        Shreya Pandey

        Thank you sir.
        1- Yes sir, even the proline level was enhanced in the NMR profiling , however it didnot match the criteria to be considered as significant metabolite ( despite having p value 1 , the AUC value was 0.65 so we had to exclude it).
        2- The few lipids that we obtained using diffusion edited pulse program also profile had significant difference. -CO-CH2-CH2- (corresponding to cholesterol and FA{TAG and Phospholipids}) was found to be increased in fibrotic cohort, similarly PUFA was found to be decreased in fibrotic cohort. As we did using NMR we have limited data corresponding to lipids. Once we use LC we might get broader insights which we will be starting soon
        3- When there is continuous injury or inflammation to liver , Hepatic stellate cells gets activated due to cascade of events. These HSCs are major contributers for collagen. When the level of collagen increases , it starts accumulating in the liver , distorting the normal structure and function and liver and eventually forming scarred tissue. This condition is called fibrosis.
        4- Sir, the data from the binned sheet that we obtained from chenomx was used in machine learning learning.

        Reply
    3. Daniel Vincent Avatar
      Daniel Vincent

      Interesting work! Could you tell the pulse program used? What data did you use for building the model ? Is NMETA available online

      Reply
      1. Shreya Pandey Avatar
        Shreya Pandey

        Thank you Daniel, we have used CPMG pulse program which is basically used to suppress large molecules. We have used the binned sheet generated using chenomx for creating model. As far as NMETA is concerned, it is not available online we are still working on it.

        Reply
    4. Ch s karthik Avatar
      Ch s karthik

      The presentation looks very informative but can you answer me the following question: What is NMeta? What all information does it require?

      Reply
      1. Shreya Pandey Avatar
        Shreya Pandey

        Thank you, Karthik,
        NMETA is a web-based application we are currently working on as part of our effort to develop a non-invasive alternative to liver biopsy.
        The process is simple: perform a 1D NMR experiment on a serum sample and upload the resulting spectrum to our webpage. The tool will then provide the probability of the individual having liver fibrosis.

        Reply
    5. Marco Schiavina Avatar
      Marco Schiavina

      Hello Shreya!
      Interesting work, I was wondering how did you handle the large lipo protein signals arising from the blood samples. Did you filter them out? Is there any evidence of these proteins to be a biomarker of the disease?

      Reply
      1. Shreya Pandey Avatar
        Shreya Pandey

        Thank you, Dr. Schiavina,
        We have not filtered the serum as we had to perform diffusion edited experiment on the same serum sample. Instead, we have used the CPMG pulse sequence to suppress signals from large molecules, particularly lipoproteins and lipid fragments, thereby minimizing their interference.
        While previous studies have compared MASLD (formerly NAFLD) with hepatocellular carcinoma (reference: ref:-https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(21)00455-2/fulltext), none have specifically examined non-fibrotic MASH versus early fibrotic MASH within the MASLD cohort. We are currently investigating this comparison and expect to share promising results soon.

        Reply

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