Solid-Phase Extraction at High pH as a Promising Tool for Targeted Isolation of Biologically Active Fractions of Humic Acids.

A search for novel sources of biologically active compounds is at the top of the agenda for biomedical technologies. Natural humic substances (HSs) contain a large variety of different chemotypes, such as condensed tannins, hydrolyzable tannins, terpenoids, lignins, etc. The goal of this work was to develop an efficient separation technique based on solid-phase extraction (SPE) for the isolation of narrow fractions of HS with higher biological activity compared to the initial material. We used lignite humic acid as the parent humic material, which showed moderate inhibition activity toward beta-lactamase TEM 1 and antioxidant activity. We applied two different SPE techniques: the first one was based on a gradient elution with water/methanol mixtures of the humic material sorbed at pH 2, and the second one implied separation by a difference in the pKa value by the use of sequential sorption of HS at pH from 8 to 3. SPE cartridges Bond Elute PPL (Agilent) were used in the fractionation experiments. The first and second techniques yielded 9 and 7 fractions, respectively. All fractions were characterized using high-resolution mass spectrometry and biological assays, including the determination of beta-lactamase (TEM 1) inhibition activity and antioxidant activity. The acidity-based separation technique demonstrated substantial advantages: it enabled the isolation of components, outcompeting the initial material at the first step of separation (sorption at pH 8). It showed moderate orthogonality in separation with regard to the polarity-based technique. Good perspectives are shown for developing a 2D separation scheme using a combination of polarity and acidity-based approaches to reduce structural heterogeneity of the narrow fractions of HS.

NOMspectra: An Open-Source Python Package for Processing High Resolution Mass Spectrometry Data on Natural Organic Matter.

The present study introduces NOMspectra, a Python package for processing high resolution mass spectrometry data on complex systems of natural organic matter (NOM). NOM is characterized by multicomponent composition reflected as thousands of signals producing very complex patterns in high resolution mass spectra. This complexity sets special demands on the methods of data processing used for analysis. The developed NOMspectra package offers a comprehensive workflow for processing, analyzing, and visualizing information-rich mass spectra of NOM and HS including algorithms for filtering spectra, recalibrating, and assigning elemental compositions to molecular ions. Additionally, the package includes functions for calculating various molecular descriptors and methods for data visualization. A graphical user interface (GUI) has been developed to make a user-friendly interface for the proposed package.

Hepatoprotective Activity of Lignin-Derived Polyphenols Dereplicated Using High-Resolution Mass Spectrometry, In Vivo Experiments, and Deep Learning.

Chronic liver diseases affect more than 1 billion people worldwide and represent one of the main public health issues. Nonalcoholic fatty liver disease (NAFLD) accounts for the majority of mortal cases, while there is no currently approved therapeutics for its treatment. One of the prospective approaches to NAFLD therapy is to use a mixture of natural compounds. They showed effectiveness in alleviating NAFLD-related conditions including steatosis, fibrosis, etc. However, understanding the mechanism of action of such mixtures is important for their rational application. In this work, we propose a new dereplication workflow for deciphering the mechanism of action of the lignin-derived natural compound mixture. The workflow combines the analysis of molecular components with high-resolution mass spectrometry, selective chemical tagging and deuterium labeling, liver tissue penetration examination, assessment of biological activity in vitro, and computational chemistry tools used to generate putative structural candidates. Molecular docking was used to propose the potential mechanism of action of these structures, which was assessed by a proteomic experiment.

Spatial genomics maps the structure, nature and evolution of cancer clones.

Genome sequencing of cancers often reveals mosaics of different subclones present in the same tumour1-3. Although these are believed to arise according to the principles of somatic evolution, the exact spatial growth patterns and underlying mechanisms remain elusive4,5. Here, to address this need, we developed a workflow that generates detailed quantitative maps of genetic subclone composition across whole-tumour sections. These provide the basis for studying clonal growth patterns, and the histological characteristics, microanatomy and microenvironmental composition of each clone. The approach rests on whole-genome sequencing, followed by highly multiplexed base-specific in situ sequencing, single-cell resolved transcriptomics and dedicated algorithms to link these layers. Applying the base-specific in situ sequencing workflow to eight tissue sections from two multifocal primary breast cancers revealed intricate subclonal growth patterns that were validated by microdissection. In a case of ductal carcinoma in situ, polyclonal neoplastic expansions occurred at the macroscopic scale but segregated within microanatomical structures. Across the stages of ductal carcinoma in situ, invasive cancer and lymph node metastasis, subclone territories are shown to exhibit distinct transcriptional and histological features and cellular microenvironments. These results provide examples of the benefits afforded by spatial genomics for deciphering the mechanisms underlying cancer evolution and microenvironmental ecology.

Aromaticity Index with Improved Estimation of Carboxyl Group Contribution for Biogeochemical Studies.

Natural organic matter (NOM) components measured with ultrahigh-resolution mass spectrometry (UHRMS) are often assessed by molecular formula-based indices, particularly related to their aromaticity, which are further used as proxies to explain biogeochemical reactivity. An aromaticity index (AI) is calculated mostly with respect to carboxylic groups abundant in NOM. Here, we propose a new constrained AIcon based on the measured distribution of carboxylic groups among individual NOM components obtained by deuteromethylation and UHRMS. Applied to samples from diverse sources (coal, marine, peat, permafrost, blackwater river, and soil), the method revealed that the most probable number of carboxylic groups was two, which enabled to set a reference point n = 2 for carboxyl-accounted AIcon calculation. The examination of the proposed AIcon showed the smallest deviation to the experimentally determined index for all NOM samples under study as well as for individual natural compounds obtained from the Coconut database. In particular, AIcon performed better than AImod for all compound classes in which aromatic moieties are expected: aromatics, condensed aromatics, and unsaturated compounds. Therefore, AIcon referenced with two carboxyl groups is preferred over conventional AI and AImod for biogeochemical studies where the aromaticity of compounds is important to understand the transformations and fate of NOM compounds.

Inhibition of Class A ß-Lactamase (TEM-1) by Narrow Fractions of Humic Substances.

Antimicrobial resistance is a global threat. The use of biologically active natural products alone or in combination with the clinically proven antimicrobial agents might be a useful strategy to fight the resistance. The scientific hypotheses of this study were twofold: (1) the natural humic substances rich in dicarboxyl, phenolic, heteroaryl, and other fragments might possess inhibitory activity against ß-lactamases, and (2) this inhibitory activity might be linked to the molecular composition of the humic ensemble. To test these hypotheses, we used humic substances (HS) from different sources (coal, peat, and soil) and of different fractional compositions (humic acids, hymatomelanic acids, and narrow fractions from solid-phase extraction) for inhibiting serine ß-lactamase TEM-1. Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) was used to characterize the molecular composition of all humic materials used in this study. The kinetic assay with chromogenic substrate CENTA was used for assessment of inhibitory activity. The inhibition data have shown that among all humic materials tested, a distinct activity was observed within apolar fractions of hymatomelanic acid isolated from lignite. The decrease in the hydrolysis rate in the presence of most active fractions was 42% (with sulbactam-87%). Of particular importance is that these very fractions caused a synergistic effect (2-fold) for the combinations with sulbactam. Linking the observed inhibition effects to molecular composition revealed the preferential contribution of low-oxidized aromatic and acyclic components such as flavonoid-, lignin, and terpenoid-like molecules. The binding of single low-molecular-weight components to the cryptic allosteric site along with supramolecular interactions of humic aggregates with the protein surface could be considered as a major contributor to the observed inhibition. We believe that fine fractionation of hydrophobic humic materials along with molecular modeling studies on the interaction between humic molecules and ß-lactamases might contribute to the development of novel ß-lactamase inhibitors of humic nature.

Fourier transform ion cyclotron resonance mass spectrometry for the analysis of molecular composition and batch-to-batch consistency of plant-derived polyphenolic ligands developed for biomedical application.

Complex plant-derived polyphenols are promising for biomedical application. Their high complexity prevents the use of conventional pharmacopoeia techniques to perform quality control. The goal of this study was to apply ultra-high-resolution mass spectrometry to evaluate the batch-to-batch consistency of the molecular composition of a polyphenolic ligand using appropriate statistical metrics. METHODS: Polyphenols were obtained by hydrolyzed-lignin oxidation. Manufacturing was performed under a range of reaction conditions: heating cycles, oxygen flows, purification. Direct-injection Fourier transform ion cyclotron resonance mass spectrometry (DI FTICR-MS) was applied to analyze reaction products. For pairwise comparison Jaccard and Tanimoto similarities calculations were proposed. In addition, principal component analysis (PCA) was applied for sample grouping based on the molecular class contributions. RESULTS: FTICR-MS analysis revealed moderate Jaccard similarity of products synthesized under the same conditions, which shared about 50% of the formulae calculated in each sample. The intensity-based Tanimoto index indicated high similarity of major components distribution of samples synthesized under standard conditions, while products obtained with variations in synthetic conditions were significantly different. PCA of molecular class contributions showed similar grouping with a high cumulative score. CONCLUSIONS: FTICR-MS provides robust metrics for the examination of batch-to-batch consistency of synthetic polyphenol materials. This approach can be proposed for the analysis of reference samples and for development of complementary methods for quality control of medicinal agents based on various biologically active matrices.