Biological NMR

Rahul Yadav (Banaras Hindu University, India)

LinkedIn: Rahul Yadav; X: @ryadav0089

Abstract: Oral cancer, a major global health concern due to its frequent late-stage diagnosis and poor prognosis. In India, around 77,000 new cases and 52,000 deaths are reported annually, which is approximately one-fourth of global incidences. Oral Submucous Fibrosis (OSMF), is a precancerous condition that elevates the risk of Oral Squamous Cell Carcinoma (OSCC) development due to tobacco, areca nut, alcohol, HPV, and poor oral hygiene. Traditional diagnostic methods, including biopsies and advanced imaging, and not easily accessible.  Therefore, saliva-based biomarkers offer a non-invasive, affordable alternative for early disease detection and monitoring.
Recent advancements in Nuclear Magnetic Resonance (NMR)-based metabolomics combined with deep learning show promising potential for identifying metabolic alterations associated with oral cancer. NMR-based metabolomic profiling can detect distinct metabolome changes in saliva, enabling differentiation between OSCC patients, OSMF patients, and healthy individuals. Through Statistical analysis along with Machine learning and deep learning identifying metabolic patterns and potential biomarkers for Oral cancer and survivor. Our findings through NMR-based metabolomics uncovered set of metabolic signatures in saliva linked to oral cancer progression, from OSMF to OSCC and also explore Tissue metabolite in OSCC patients compare these metabolites from saliva which preferred non-invasive strategies to Early Detection of OSCC. Salivary biomarkers could revolutionize early diagnosis, facilitate personalized therapeutic interventions, and enhance prognostic evaluation in oral cancer management. Future research involving larger patient with multiple cohorts and integrated multi-omics and deep learning strategies will be crucial to validate these results and drive advancements in precision oncology.

Priya Sahu (Michigan State University, United States)

LinkedIn: Priya Sahu

Abstract: Lignin is a major structural component of plant secondary cell walls and a key determinant of biomass utilization. In grasses, both phenylalanine and tyrosine contribute to lignin biosynthesis, but their respective roles in shaping the native lignin polymer have remained unclear. Here, we combine precursor-specific 13C isotope labeling with dynamic nuclear polarization (DNP)-enhanced solid-state NMR to directly track aromatic amino acid incorporation into lignin in intact Brachypodium distachyon cell walls. Conventional solid-state NMR established tissue-specific labeling patterns, while DNP provided up to ~40-fold sensitivity enhancement, enabling multidimensional 13C-13C correlation experiments on selectively labeled samples. We found that phenylalanine is the dominant precursor for canonical guaiacyl and syringyl lignin, whereas tyrosine preferentially contributes to hydroxyphenyl lignin and ferulate moieties characteristic of grass cell walls. Analysis of a C3H knockdown mutant further revealed precursor-dependent metabolic plasticity: phenylalanine-derived lignification was strongly impaired, while tyrosine-derived lignification remained comparatively resilient through alternative metabolic routing. These results demonstrate how DNP-enhanced solid-state NMR can directly connect precursor metabolism with polymer architecture in intact plant cell walls, providing new insights into the metabolic regulation of lignin biosynthesis in grasses.

Himanshu Singh (IIT Guwahati, India)

LinkedIn: Himanshu Singh

Abstract: The four canonical DNA bases are subject to a wide range of chemical modifications that play critical roles in genome regulation. In recent years, numerous modified DNA bases and the enzymes responsible for their processing have been discovered, highlighting their importance in human diseases such as cancer and neurological disorders. Epigenetic DNA modifications enable cells with identical genomes to acquire distinct functional identities. While cytosine methylation is relatively well characterized, the biological roles of many other DNA modifications remain poorly understood, largely due to challenges in their site-specific detection.
Engineered DNA reader proteins that selectively recognize individual epigenetic marks offer a promising strategy for interrogating the genome at single-base resolution. Understanding the structural and dynamic principles governing DNA recognition by both natural and designed readers is essential for developing molecular probes to study chromatin biology and disease-associated defects in target recognition.
Using a combination of mutagenesis, NMR relaxation experiments, structural analyses, and MD simulations, we demonstrated that the selectivity of the first engineered reader for an oxidized CpG epigenetic mark depends on finely tuned conformational plasticity acquired during the directed evolution of its natural progenitor. Our findings reveal that specific dynamic features are critical for achieving both high affinity and selectivity in DNA recognition.

Aditi Pandey (Centre of BioMedical Research, India)

Abstract: Lennox-Gastaut syndrome (LGS) is an epileptic encephalopathy characterized by multiple types of seizures typically occurring between 1 and 7 years of age, cognitive impairment and characteristic electroencephalographic abnormalities. There is no definite cure for this condition; the seizures can be managed to some extent through medical, dietary and sometimes surgical interventions. LGS is also frequently refractory to anti-seizure medication (ASM).
We report NMR-based metabolomic profile in LGS and its association with clinical parameters. Children between 2-18 years were included based on clinical and EEG diagnostic criteria. Detailed neurological examinations, frequency and type of seizures, EEG changes, cranial MRI and NMR-based serum metabolomic profile were measured. Twenty-six LGS patients and 11 healthy matched controls were included. The median age of the patients was 6 (range 2-17) years, and 19 were males.
Spectra were recorded on 800 MHz NMR spectrometer and eight metabolites namely lactate, glucose, glutamate, pyruvate, glutamine, glycine, citrate and creatinine were crucial for discrimination of LGS from the controls, among which glutamate was upregulated and citrate, pyruvate, and glutamine were downregulated in LGS. Glutamate was associated with developmental quotient (r = -0.48) and pyruvate with focal seizures (r = 0.47) and cystic encephalomalacia on cranial MRI (p = 0.02).  NMR metabolomic profile including glutamate, glutamine, glycine, glucose, pyruvate, lactate, citrate and creatinine can discriminate LGS from the controls. In view of significant perturbations in glutamate, the effect of anti-glutamatergic ASM may be explored in controlling seizures and brain damage.

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.

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.

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.