All organisms, fundamentally, are made from the same raw material, namely the elements of the periodic table. Biochemical diversity is achieved by how these elements are utilized, for what purpose, and in which physical location. Determining elemental distributions, especially those of trace elements that facilitate metabolism as cofactors in the active centers of essential enzymes, can determine the state of metabolism, the nutritional status, or the developmental stage of an organism. Photosynthetic eukaryotes, especially algae, are excellent subjects for quantitative analysis of elemental distribution. These microbes utilize unique metabolic pathways that require various trace nutrients at their core to enable their operation. Photosynthetic microbes also have important environmental roles as primary producers in habitats with limited nutrient supplies or toxin contaminations. Accordingly, photosynthetic eukaryotes are of great interest for biotechnological exploitation, carbon sequestration, and bioremediation, with many of the applications involving various trace elements and consequently affecting their quota and intracellular distribution. A number of diverse applications were developed for elemental imaging, allowing subcellular resolution, with X-ray fluorescence microscopy (XFM, XRF) being at the forefront, enabling quantitative descriptions of intact cells in a non-destructive method. This Tutorial Review summarizes the workflow of a quantitative, single-cell elemental distribution analysis of a eukaryotic alga using XFM.

This study presents a novel computational approach to study molecular recognition and binding kinetics for drug-like compounds dissociating from a flexible protein system. The intermediates and their free energy profile during ligand association and dissociation processes control ligand-protein binding kinetics and bring a more complete picture of ligand-protein binding. The method applied the milestoning theory to extract kinetics and thermodynamics information from running short classical molecular dynamics (MD) simulations for frames from a given dissociation path. High-dimensional ligand-protein motions (3N-6 degrees of freedom) during ligand dissociation were reduced by use of principal component modes for assigning more than 100 milestones, and classical MD runs were allowed to travel multiple milestones to efficiently obtain ensemble distribution of initial structures for MD simulations and estimate the transition time and rate during ligand traveling between milestones. We used five pyrazolourea ligands and cyclin-dependent kinase 8 with cyclin C (CDK8/CycC) as our model system as well as metadynamics and a pathway search method to sample dissociation pathways. With our strategy, we constructed the free energy profile for highly mobile biomolecular systems. The computed binding free energy and residence time correctly ranked the pyrazolourea ligand series, in agreement with experimental data. Guided by a barrier of a ligand passing an αC helix and activation loop, we introduced one hydroxyl group to parent compounds to design our ligands with increased residence time and validated our prediction by experiments. This work provides a novel and robust approach to investigate dissociation kinetics of large and flexible systems for understanding unbinding mechanisms and designing new small-molecule drugs with desired binding kinetics.

This study presents a novel computational approach to study molecular recognition and binding kinetics for drug-like compounds dissociating from a flexible protein system. The intermediates and their free energy profile during ligand association and dissociation processes control ligand-protein binding kinetics and bring a more complete picture of ligand-protein binding. The method applied the milestoning theory to extract kinetics and thermodynamics information from running short classical molecular dynamics (MD) simulations for frames from a given dissociation path. High-dimensional ligand-protein motions (3N-6 degrees of freedom) during ligand dissociation were reduced by use of principal component modes for assigning more than 100 milestones, and classical MD runs were allowed to travel multiple milestones to efficiently obtain ensemble distribution of initial structures for MD simulations and estimate the transition time and rate during ligand traveling between milestones. We used five pyrazolourea ligands and cyclin-dependent kinase 8 with cyclin C (CDK8/CycC) as our model system as well as metadynamics and a pathway search method to sample dissociation pathways. With our strategy, we constructed the free energy profile for highly mobile biomolecular systems. The computed binding free energy and residence time correctly ranked the pyrazolourea ligand series, in agreement with experimental data. Guided by a barrier of a ligand passing an αC helix and activation loop, we introduced one hydroxyl group to parent compounds to design our ligands with increased residence time and validated our prediction by experiments. This work provides a novel and robust approach to investigate dissociation kinetics of large and flexible systems for understanding unbinding mechanisms and designing new small-molecule drugs with desired binding kinetics.

The acidocalcisome is an acidic organelle in the cytosol of eukaryotes, defined by its low pH and high calcium and polyphosphate content. It is visualized as an electron-dense object by transmission electron microscopy (TEM) or described with mass spectrometry (MS)-based imaging techniques or multimodal X-ray fluorescence microscopy (XFM) based on its unique elemental composition. Compared with MS-based imaging techniques, XFM offers the additional advantage of absolute quantification of trace metal content, since sectioning of the cell is not required and metabolic states can be preserved rapidly by either vitrification or chemical fixation. We employed XFM in Chlamydomonas reinhardtii to determine single-cell and organelle trace metal quotas within algal cells in situations of trace metal overaccumulation (Fe and Cu). We found up to 70% of the cellular Cu and 80% of Fe sequestered in acidocalcisomes in these conditions and identified two distinct populations of acidocalcisomes, defined by their unique trace elemental makeup. We utilized the vtc1 mutant, defective in polyphosphate synthesis and failing to accumulate Ca, to show that Fe sequestration is not dependent on either. Finally, quantitation of the Fe and Cu contents of individual cells and compartments via XFM, over a range of cellular metal quotas created by nutritional and genetic perturbations, indicated excellent correlation with bulk data from corresponding cell cultures, establishing a framework to distinguish the nutritional status of single cells.

The acidocalcisome is an acidic organelle in the cytosol of eukaryotes, defined by its low pH and high calcium and polyphosphate content. It is visualized as an electron-dense object by transmission electron microscopy (TEM) or described with mass-spectrometry (MS)-based imaging techniques or multimodal X-ray fluorescence microscopy (XFM) based on its unique elemental composition. Compared to MS-based imaging techniques, XFM offers the advantage of absolute quantification of trace metal content, since sectioning of the cell is not required and metabolic states can be preserved rapidly by either vitrification or chemical fixation. We employed XFM in Chlamydomonas reinhardtii , to determine single-cell and organelle trace metal quotas within algal cells in situations of trace metal over-accumulation (Fe, Cu). We found up to 70% of the cellular Cu and 80% of Fe sequestered in acidocalcisomes in these conditions, and identified two distinct populations of acidocalcisomes, defined by their unique trace elemental makeup. We utilized the vtc1 mutant, defective in polyphosphate synthesis and failing to accumulate Ca to show that Fe sequestration is not dependent on either. Finally, quantitation of the Fe and Cu contents of individual cells and compartments via XFM, over a range of cellular metal quotas created by nutritional and genetic perturbations, indicated excellent correlation with bulk data from corresponding cell cultures, establishing a framework to distinguish the nutritional status of single cells.

Significance statement

Transition metals are of crucial importance for primary productivity; their scarcity limits crop yield in agriculture and carbon sequestration at global scale. Copper (Cu), iron (Fe) and manganese (Mn) are among the most important trace elements that enable the redox chemistry in oxygenic photosynthesis. The single-celled, eukaryotic green alga Chlamydomonas reinhardtii is a choice experimental system for studying trace metal homeostasis in the context of phototrophy, offering all the advantages of a classical microbial system with a well-characterized photosystem and trace metal metabolism machinery of relevance to plants. This project identifies and differentiates different trace metal storage sites in Chlamydomonas and uncovers the dynamics of trace metal storage and mobilization in situations of fluctuating resources.

We have examined the gypsum (CaSO4·2H2O) scaling phenomena on membranes with different physicochemical properties in forward osmosis (FO) processes. Three hollow fiber membranes made of (1) cellulose acetate (CA), (2) polybenzimidazole (PBI)/polyethersulfone (PES) and (3) PBI-polyhedral oligomeric silsesquioxane (POSS)/polyacrylonitrile (PAN) were studied. For the first time in FO processes, we have found that surface ionic interactions dominate gypsum scaling on the membrane surface. A 70% flux reduction was observed on negatively charged CA and PBI membrane surfaces, due to strong attractive forces. The PBI membrane surface also showed a slightly positive charge at a low pH value of 3 and exhibited a 30% flux reduction. The atomic force microscopy (AFM) force measurements confirmed a strong repulsive force between gypsum and PBI at a pH value of 3. The newly developed PBI-POSS/PAN membrane had ridge morphology and a contact angle of 51.42° ± 14.85° after the addition of hydrophilic POSS nanoparticles and 3 min thermal treatment at 95 °C. Minimal scaling and an only 1.3% flux reduction were observed at a pH value of 3. Such a ridge structure may reduce scaling by not providing a locally flat surface to the crystallite at a pH value of 3; thus, gypsum would be easily washed away from the surface.

X-ray fluorescence tomography is based on the detection of fluorescence x-ray photons produced following x-ray absorption while a specimen is rotated; it provides information on the 3D distribution of selected elements within a sample. One limitation in the quality of sample recovery is the separation of elemental signals due to the finite energy resolution of the detector. Another limitation is the effect of self-absorption, which can lead to inaccurate results with dense samples. To recover a higher quality elemental map, we combine x-ray fluorescence detection with a second data modality: conventional x-ray transmission tomography using absorption. By using these combined signals in a nonlinear optimization-based approach, we demonstrate the benefit of our algorithm on real experimental data and obtain an improved quantitative reconstruction of the spatial distribution of dominant elements in the sample. Compared with single-modality inversion based on x-ray fluorescence alone, this joint inversion approach reduces ill-posedness and should result in improved elemental quantification and better correction of self-absorption.

Understanding ligand binding kinetics and thermodynamics, which involves investigating the free, transient, and final complex conformations, is important in fundamental studies and applications for chemical and biomedical systems. Examining the important but transient ligand-protein-bound conformations, in addition to experimentally determined structures, also provides a more accurate estimation for drug efficacy and selectivity. Moreover, obtaining the entire picture of the free energy landscape during ligand binding/unbinding processes is critical in understanding binding mechanisms. Here, we present a Binding Kinetics Toolkit (BKiT) that includes several utilities to analyze trajectories and compute a free energy and kinetics profile. BKiT uses principal component space to generate approximated unbinding or conformational transition coordinates for accurately describing and easily visualizing the molecular motions. We implemented a new partitioning approach to assign indexes along the approximated coordinates that can be used as milestones or microstates. The program can generate input files to run many short classical molecular dynamics simulations and uses milestoning theory to construct the free energy profile and estimate binding residence time. We first validated the method with a host-guest system, aspirin unbinding from β-cyclodextrin, and then applied the protocol to pyrazolourea compounds and cyclin-dependent kinase 8 and cyclin C complexes, a kinase system of pharmacological interest. Overall, our approaches yielded good agreement with published results and suggest ligand design strategies. The computed unbinding free energy landscape also provides a more complete picture of ligand-receptor binding barriers and stable local minima for deepening our understanding of molecular recognition. BKiT is easy to use and has extensible features for future expansion of utilities for postanalysis and calculations.

Acetoclastic methanogenesis is a key metabolic process in anaerobic digestion, a technology with broad applications in biogas production and waste treatment. Acetoclastic methanogenesis is known to be performed by two archaeal genera, Methanosaeta and Methanosarcina. The conventional model posits that Methanosaeta populations are more competitive at low acetate levels (<1 mM) than Methanosarcina and vice versa at higher acetate concentrations. While this model is supported by an extensive body of studies, reports of inconsistency have grown that Methanosaeta were observed to outnumber Methanosarcina at elevated acetate levels. In this study, monitoring of anaerobic digesters treating animal wastewater unexpectedly identified Methanosaeta as the dominant acetoclastic methanogen population at both low and high acetate levels during organic overloading. The surprising competitiveness of Methanosaeta at elevated acetate was further supported by the enrichment of Methanosaeta with high concentrations of acetate (20 mM). The dominance of Methanosaeta in the methanogen community could be reproduced in anaerobic digesters with the direct addition of acetate to above 20 mM, again supporting the competitiveness of Methanosaeta over Methanosarcina at elevated acetate levels. This study for the first time systematically demonstrated that the dominance of Methanosaeta populations in anaerobic digestion could be linked to the competitiveness of Methanosaeta at elevated acetate concentrations. Given the importance of acetoclastic methanogenesis in biological methane production, findings from this study could have major implications for developing strategies for more effective control of methanogenic treatment processes.