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At least 55 records · Page 3

How cells (might) sense microgravity

This article is a summary of a lecture presented at an ESA/NASA Workshop on Cell and Molecular Biology Research in Space that convened in Leuven, Belgium, in June 1998. Recent studies are reviewed which suggest that cells may sense mechanical stresses, including those due to gravity, through changes in the balance of forces that are transmitted across transmembrane adhesion receptors that link the cytoskeleton to the extracellular matrix and to other cells (e.g., integrins, cadherins, selectins). The mechanism by which these mechanical signals are transduced and converted into a biochemical response appears to be based, in part, on the finding that living cells use a tension-dependent form of architecture, known as tensegrity, to organize and stabilize their cytoskeleton. Because of tensegrity, the cellular response to stress differs depending on the level of pre-stress (pre-existing tension) in the cytoskeleton and it involves all three cytoskeletal filament systems as well as nuclear scaffolds. Recent studies confirm that alterations in the cellular force balance can influence intracellular biochemistry within focal adhesion complexes that form at the site of integrin binding as well as gene expression in the nucleus. These results suggest that gravity sensation may not result from direct activation of any single gravioreceptor molecule. Instead, gravitational forces may be experienced by individual cells in the living organism as a result of stress-dependent changes in cell, tissue, or organ structure that, in turn, alter extracellular matrix mechanics, cell shape, cytoskeletal organization, or internal pre-stress in the cell-tissue matrix.--Ingber, D. How cells (might) sense microgravity.

NASA Discipline Cell Biology↗

Spectroscopic Probe Molecule Selection Using Quantum Theory, First-Principles Calculations, and Machine Learning

Probe molecule vibrational spectra have a long history of being used to characterize materials including metals, oxides, metal-organic frameworks, and even human proteins. Furthermore, recent advances in machine learning have enabled computationally generated spectra to aid in detailed characterization of complex surfaces with probe molecules. Despite widespread use of probe molecules, the science of probe molecule selection is underdeveloped. Here, we develop physical concepts, including orbital interaction energy and the energy overlap integral, to explain and predict the ability of probe molecules to discriminate structural descriptors. We resolve the crystal orbital overlap population (COOP) to specific molecular orbitals and quantify their bonding character, which directly influences vibrational frequencies. Using only a single adsorbate calculation from density function theory (DFT), we compute the interaction energy of individual adsorbate molecular orbitals with adsorption site atomic orbitals across many different sites. Combining the molecular orbital resolved COOP and changes in orbital interaction energy enables probe molecule selection for improved discrimination of various sites. We demonstrate these concepts by comparing the predicted effectiveness of carbon monoxide (CO), nitric oxide (NO), and ethylene (C 2 H 4 ) to probe Pt adsorption sites. Finally, using a previously developed machine learning framework, we show that models trained on hundreds of thousand C 2 H 4 spectra, computed from DFT, which regress surface binding-type and generalized coordination number (GCN), outperform those trained using CO and NO spectra. Lastly, a python package, pDOS_overlap, for implementing the electron density based analysis on any combination of adsorbates and materials, is also made available.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Fully synthetic platform to rapidly generate tetravalent bispecific nanobody–based immunoglobulins

Nanobodies bind a target antigen with a kinetic profile similar to a conventional antibody, but exist as a single heavy chain domain that can be readily multimerized to engage antigen via multiple interactions. Presently, most nanobodies are produced by immunizing camelids; however, platforms for animal-free production are growing in popularity. Here, we describe the development of a fully synthetic nanobody library based on an engineered human V H 3-23 variable gene and a multispecific antibody-like format designed for biparatopic target engagement. To validate our library, we selected nanobodies against the SARS-CoV-2 receptor–binding domain and employed an on-yeast epitope binning strategy to rapidly map the specificities of the selected nanobodies. We then generated antibody-like molecules by replacing the V H and V L domains of a conventional antibody with two different nanobodies, designed as a molecular clamp to engage the receptor-binding domain biparatopically. The resulting bispecific tetra-nanobody immunoglobulins neutralized diverse SARS-CoV-2 variants with potencies similar to antibodies isolated from convalescent donors. Subsequent biochemical analyses confirmed the accuracy of the on-yeast epitope binning and structures of both individual nanobodies, and a tetra-nanobody immunoglobulin revealed that the intended mode of interaction had been achieved. This overall workflow is applicable to nearly any protein target and provides a blueprint for a modular workflow for the development of multispecific molecules.

60 APPLIED LIFE SCIENCES↗

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗

Microencapsulated Bioactive Agents and Method of Making

Microcapsules prepared by encapsulating an aqueous solution of a protein, drug or other bioactive substance inside a semi-permeable membrane by are disclosed. The microcapsules are formed by interfacial coacervation under conditions where the shear forces are limited to 0- 100 dynes per sq cm at the interface. By placing the microcapsules in a high osmotic watering solution, the protein solution is gradually made saturated and then supersaturated, and the controlled nucleation and crystallization of the protein is achieved. The crystal-filled microcapsules prepared by this method can be conveniently harvested and stored while keeping the encapsulated crystals in essentially pristine condition due to the rugged, protective membrane. Because the membrane components themselves are x-ray transparent, large crystal-containing microcapsules can be individually selected. mounted in x-ray capillary tubes and subjected to high energy x-ray diffraction studies to determine the 3-D structure of the protein molecules. Certain embodiments of the microcapsules of the invention have composite polymeric outer membranes which are somewhat elastic, water insoluble, permeable only to water, salts, and low molecular weight molecules and are structurally stable in fluid shear forces typically encountered in the human vascular system.

Dennis R Morrison↗

Method for determining the three-dimensional structure of a protein

Microcapsules prepared by encapsulating an aqueous solution of a protein, drug or other bioactive substance inside a semi-permeable membrane by are disclosed. The microcapsules are formed by interfacial coacervation under conditions where the shear forces are limited to 0-100 dynes/cm.sup.2 at the interface. By placing the microcapsules in a high osmotic dewatering solution, the protein solution is gradually made saturated and then supersaturated, and the controlled nucleation and crystallization of the protein is achieved. The crystal-filled microcapsules prepared by this method can be conveniently harvested and stored while keeping the encapsulated crystals in essentially pristine condition due to the rugged, protective membrane. Because the membrane components themselves are x-ray transparent, large crystal-containing microcapsules can be individually selected, mounted in x-ray capillary tubes and subjected to high energy x-ray diffraction studies to determine the 3-D structure of the protein molecules. Certain embodiments of the microcapsules of the invention have composite polymeric outer membranes which are somewhat elastic, water insoluble, permeable only to water, salts, and low molecular weight molecules and are structurally stable in fluid shear forces typically encountered in the human vascular system.

Morrison, Dennis R.↗

Exploiting correlations in multi-coincidence Coulomb explosion patterns for differentiating molecular structures using machine learning

Coulomb explosion imaging (CEI) is a powerful technique for capturing the real-time motion of individual atoms during ultrafast photochemical reactions. CEI generates high-dimensional data with naturally embedded correlations that allow mapping the coordinated motion of nuclei in molecules. This enables reliable separation of competing reaction pathways and makes this approach uniquely suited for characterizing weak reaction channels. However, rich information contained in experimental CEI patterns remains largely underexploited due to challenges in visualizing correlations between multiple observables in multi-dimensional parameter space. Here we present a new approach to CEI of intermediate-sized polyatomic molecules, detecting up to eight ionic fragments in coincidence and leveraging machine-learning-based analysis to identify patterns and correlations in the resulting high-dimensional momentum-space data, enabling robust molecular structure identification and differentiation. Our approach provides high-dimensional background-free data encoding exceptionally rich structural information and establishes an automated, scalable framework for extracting insightful information from the data. As a demonstration, we apply this method to image and distinguish dichloroethylene isomers, showcasing its potential for broader applications in molecular imaging. Our results pave the way for channel-specific analysis of ultrafast structural dynamics in chemically relevant systems, particularly for disentangling mixed reaction pathways and detecting contributions from weak channels and minority species.

Chemical Physics (physics.chem-ph)↗

Defining the S-Glutathionylation Proteome by Biochemical and Mass Spectrometric Approaches

Protein S-glutathionylation (SSG) is a reversible post-translational modification (PTM) featuring the conjugation of glutathione to a protein cysteine thiol. SSG can alter protein structure, activity, subcellular localization, and interaction with small molecules and other proteins. Thus, it plays a critical role in redox signaling and regulation in various physiological activities and pathological events. In this review, we summarize current biochemical and analytical approaches for characterizing SSG at both the proteome level and at individual protein levels. To illustrate the mechanism underlying SSG-mediated redox regulation, we highlight recent examples of functional and structural consequences of SSG modifications. Finally, we discuss the analytical challenges in characterizing SSG and the thiol PTM landscape, future directions for understanding of the role of SSG in redox signaling and regulation and its interplay with other PTMs, and the potential role of computational approaches to accelerate functional discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Leveraging Topological Events in Tracking Graphs for Understanding Particle Diffusion

Abstract Single particle tracking (SPT) of fluorescent molecules provides significant insights into the diffusion and relative motion of tagged proteins and other structures of interest in biology. However, despite the latest advances in high‐resolution microscopy, individual particles are typically not distinguished from clusters of particles. This lack of resolution obscures potential evidence for how merging and splitting of particles affect their diffusion and any implications on the biological environment. The particle tracks are typically decomposed into individual segments at observed merge and split events, and analysis is performed without knowing the true count of particles in the resulting segments. Here, we address the challenges in analyzing particle tracks in the context of cancer biology. In particular, we study the tracks of KRAS protein, which is implicated in nearly 20% of all human cancers, and whose clustering and aggregation have been linked to the signaling pathway leading to uncontrolled cell growth. We present a new analysis approach for particle tracks by representing them as tracking graphs and using topological events – merging and splitting, to disambiguate the tracks. Using this analysis, we infer a lower bound on the count of particles as they cluster and create conditional distributions of diffusion speeds before and after merge and split events. Using thousands of time‐steps of simulated and in‐vitro SPT data, we demonstrate the efficacy of our method, as it offers the biologists a new, detailed look into the relationship between KRAS clustering and diffusion speeds.

McDonald, T.↗

Structures of a synthetic antibody selected against and bound to the C‐terminal domain of Clostridium perfringens enterotoxin

Abstract Clostridium perfringensenterotoxin (CpE) causes cytotoxic gastrointestinal disease in mammalian epithelium by binding membrane protein receptors called claudins. Claudins direct the formation of cell/cell tight junctions through oligomerization and govern the transport of molecules between individual cells. CpE binds claudins through its C‐terminal domain (cCpE) and induces cytotoxicity through its N‐terminal domain. The non‐toxic cCpE is a useful tool to study claudins, tight junctions, and for translational applications, such as increasing the permeability of restrictive tissues like the blood–brain barrier or selective targeting of claudin overexpressing cancers. Conversely, there are no specialized molecular tools to study CpE or cCpE, or to modulate or inhibit their functions. We previously reported the development of synthetic antigen‐binding fragments (sFabs) that bind cCpE, and low‐resolution structures of them bound to claudin/cCpE complexes. Here, we determine high‐resolution structures of sFab COP‐2 bound to cCpE using X‐ray crystallography and cryogenic electron microscopy. The structures and biophysical findings provide the mechanism of COP‐2 binding to cCpE and the molecular determinants driving their interactions. These insights can advance the design of new antibody‐based tools from our COP‐2 scaffold to study or alter cCpE function and give rise to a “Trojan horse” strategy that exploits cCpE's tight junction barrier disrupting function to selectively deliver conjugated therapeutics through normally impermeable tissues.

Biochemistry & Molecular Biology↗

Kinetic and structural evidence for specific DMSO interference with reversible binding of uncharged bis-oximes to hAChE and their reactivation kinetics of OP-hAChE

The structural basis of inhibitory effect of organic solvent dimethyl sulfoxide (DMSO) on human acetylcholinesterase (EC 3.1.1.7; hAChE) was inferred from the effect of DMSO on kinetics of reversible inhibition of uncharged, heterocyclic bis-oximes to hAChE, from DMSO effect on rates of reactivation of inactive organophosphate (OP)-hAChE conjugates by bis-oximes and by X-ray structures of bis-oxime and DMSO binding to hAChE. Here, the reversible inhibition constant of DMSO for hAChE in 0.1 M phosphate buffer pH 7.4 at 22 °C, was K i = (0.32 ± 0.04) % (or 45 ± 5 mM). The K i of the bis-oxime LG-703 for hAChE was 3.2-fold larger in 1 % DMSO, consistent with direct competition between LG-703 and DMSO. The X-ray structure of the LG-703∗hAChE complex (PDB ID: 6U3P) shows DMSO and LG-703 bound to individual hAChE monomers, LG-703 in the chain A and DMSO in the chain B. In the co-crystallization both small molecules were present at a similar excess over their corresponding K i values for hAChE (7.8-fold for DMSO and 6.5-fold for LG-703) and formation of two different complexes (DMSO∗hAChE and LG-703∗hAChE), in the same crystal, appears consistent with inhibition kinetics. Furthermore, rates of reactivation of paraoxon-inhibited hAChE (POX-hAChE) and of VX-hAChE by LG-703 and by a novel heterocyclic bis-oxime LG-1922 were reduced 2 – 3-fold in DMSO, consistent with observation of the active-center-bound DMSO molecules in the newly solved structure of the LG-1922∗POX-hAChE complex presented here and in our POX-hAChE structure (PDB ID: 8DT2) showing obstruction of the reactivator access to the conjugated P atom.

Acetylcholinesterase inhibition↗

Making Macroscopic Assemblies of Aligned Carbon Nanotubes

A method of aligning and assembling single-wall carbon nanotubes (SWNTs) to fabricate macroscopic structures has been invented. The method entails suspending SWNTs in a fluid, orienting the SWNTs by use of a magnetic and/or electric field, and then removing the aligned SWNTs from suspension in such a way as to assemble them while maintaining the alignment. SWNTs are essentially tubular extensions of fullerene molecules. It is desirable to assemble aligned SWNTs into macroscopic structures because the common alignment of the SWNTs in such a structure makes it possible to exploit, on a macroscopic scale, the unique mechanical, chemical, and electrical properties that individual oriented SWNTs exhibit at the molecular level. Because of their small size and high electrical conductivity, carbon nanotubes, and especially SWNTs, are useful for making electrical connectors in integrated circuits. Carbon nanotubes can be used as antennas at optical frequencies, and as probes in scanning tunneling microscopes, atomic-force microscopes, and the like. Carbon nanotubes can be used with or instead of carbon black in tires. Carbon nanotubes are useful as supports for catalysts. Ropes of SWNTs are metallic and, as such, are potentially useful in some applications in which electrical conductors are needed - for example, they could be used as additives in formulating electrically conductive paints. Finally, macroscopic assemblies of aligned SWNTs can serve as templates for the growth of more and larger structures of the same type. The great variety of tubular fullerene molecules and of the structures that could be formed by assembling them in various ways precludes a complete description of the present method within the limits of this article. It must suffice to present a typical example of the use of one of many possible variants of the method to form a membrane comprising SWNTs aligned substantially parallel to each other in the membrane plane. The apparatus used in this variant of the method (see figure) includes a reservoir containing SWNTs dispersed in a suspending agent (for example, dimethylformamide) and a reservoir containing a suitable solvent (for example, water mixed with a surfactant). By use of either pressurized gas supplied from upstream or suction from downstream, the suspension of SWNTs and the solvent are forced to mix and flow into a tank. A filter inside the tank contains pores small enough to prevent the passage of most SWNTs, but large enough to allow the passage of molecules of the solvent and suspending agent. The filter is oriented perpendicular to the flow path. A magnetic field parallel to the plane of the filter is applied. The success of the method is based on the tendency of SWNTs to become aligned with their longitudinal axes parallel to an applied magnetic field. The alignment energy of an SWNT increases with the length of the SWNT and the magnetic-field strength. In order to obtain an acceptably small degree of statistical deviation of SWNTs of a given length from alignment with a magnetic field, one must make the field strong enough so that the thermal energy associated with rotation of an SWNT away from alignment is less than the alignment energy.

Smalley, Richard E.↗

A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs

One often observes small but measurable differences in the diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and may reveal the natural dynamism of the molecule in solution. Partitioning these mixed-state data into single-state clusters is a critical step that could extract information about the dynamic behavior of proteins from hundreds or thousands of single-crystal data sets. Mixed-state data can be obtained deliberately (through intentional perturbation) or inadvertently (while attempting to measure highly redundant single-crystal data). To the extent that different states adopt different molecular structures, one expects to observe differences in the crystals; each of the polystates will create a polymorph of the crystals. After mixed-state diffraction data have been measured, deliberately or inadvertently, the challenge is to sort the data into clusters that may represent relevant biological polystates. Here, this problem is addressed using a simple multi-factor clustering approach that classifies each data set using independent observables, thereby assigning each data set to the correct location in conformational space. This procedure is illustrated using two independent observables, unit-cell parameters and intensities, to cluster mixed-state data from chymotrypsinogen (ChTg) crystals. It is observed that the data populate an arc of the reaction trajectory as ChTg is converted into chymotrypsin.

36 MATERIALS SCIENCE↗

Structural mechanism of allosteric activation of TRPML1 by PI(3,5)P 2 and rapamycin

Transient receptor potential mucolipin 1 (TRPML1) is a Ca 2+ -permeable, nonselective cation channel ubiquitously expressed in the endolysosomes of mammalian cells and its loss-of-function mutations are the direct cause of type IV mucolipidosis (MLIV), an autosomal recessive lysosomal storage disease. TRPML1 is a ligand-gated channel that can be activated by phosphatidylinositol 3,5-bisphosphate [PI(3,5)P 2 ] as well as some synthetic small-molecule agonists. Recently, rapamycin has also been shown to directly bind and activate TRPML1. Interestingly, both PI(3,5)P 2 and rapamycin have low efficacy in channel activation individually but together they work cooperatively and activate the channel with high potency. To reveal the structural basis underlying the synergistic activation of TRPML1 by PI(3,5)P 2 and rapamycin, we determined the high-resolution cryoelectron microscopy (cryo-EM) structures of the mouse TRPML1 channel in various states, including apo closed, PI(3,5)P 2 -bound closed, and PI(3,5)P 2 /temsirolimus (a rapamycin analog)-bound open states. These structures, combined with electrophysiology, elucidate the molecular details of ligand binding and provide structural insight into how the TRPML1 channel integrates two distantly bound ligand stimuli and facilitates channel opening.

59 BASIC BIOLOGICAL SCIENCES↗

Self-sorting in supramolecular assemblies

Supramolecular self-assembly enables living organisms to form highly functional hierarchical structures with individual components self-organized across multiple length scales. This has inspired work on multicomponent supramolecular materials to understand factors behind co-assembly versus self-sorting of molecules. We report here on a supramolecular system comprised of negatively charged peptide amphiphile (PA) molecules, in which only a tiny fraction of the molecules (0.7 mol%) were covalently conjugated to one of two different fluorophores, half to fluorescein isothiocyanate (FTIC) and the other half to tetramethylrhodamine (TAMRA). Confocal microscopy of the system revealed self-sorting of the two different fluorescent PA molecules, where TAMRA PA is concentrated in micron-scale domains while FITC PA remains dispersed throughout the sample. From Förster resonance energy transfer and fluorescence recovery experiments, we conclude that conjugation of the negatively charged FITC to PA significantly disrupts its co-assembly with the 99.3 mol% of unlabeled molecules, which are responsible for formation of micron-scale domains. Conversely, conjugation of the zwitterionic TAMRA causes no such disruption. Interestingly, this dissimilar behavior between FITC and TAMRA PA causes them to self-sort at large length scales in the supramolecular system, mediated not by specific interactions among the individual fluorophores but instead by their different propensities to co-assemble with the majority component. We also found that greater ionic strength in the aqueous environment of the system promotes mixing by lowering the electrostatic barriers involved in self-sorting. Furthermore, our results demonstrate great thermodynamic subtlety in the driving forces that mediate self-sorting versus co-assembly in supramolecular peptide assemblies.

36 MATERIALS SCIENCE↗

Structure-based development of a subtype-selective orexin 1 receptor antagonist

Orexin receptors belong to the superfamily of G-protein–coupled receptors (GPCRs) which represent the largest class of drug targets in humans. Despite the recent progress in structural biology, the development of subtype-selective orexin receptor and GPCR ligands in general remains challenging, due to the high sequence similarity among individual receptor subtypes. However, subtype-selective molecules are key to discerning the individual contributions of receptor subtypes to (patho-)physiology. Starting from the clinically used, non–subtype-selective orexin receptor antagonist suvorexant, we demonstrate how docking, crystallography, medicinal chemistry, and in vitro pharmacology can be combined to exploit single amino acid sequence differences for the discovery of subtype-selective probes. Such compounds will help to better understand orexin receptor pharmacology and develop promising drug candidates.

59 BASIC BIOLOGICAL SCIENCES↗

Fundamental Studies of the Vibrational, Electronic, and Photophysical Properties of Tetrapyrrolic Architectures

The ability to capture and utilize light in the near-ultraviolet (NUV), visible and near-infrared (NIR-I and NIR-II) spectral regions (i.e., 320–400, 400–700, 700–1000, 1000–1700 nm) is essential for any solar-energy conversion scheme. Nature employs chlorophylls and bacteriochlorophylls in light-harvesting architectures to absorb light in the blue and red/NIR regions. Accessory pigments (carotenoids, bilins) augment absorption of the (bacterio)chlorophylls in the green region. The harvested energy is funneled to a reaction center protein, where charge separation occurs. Subsequent migration of the electron and the hole stabilizes and stores the energy from light via redox chemistry. The long-term objective of the Bocian/Holten&Kirmaier/Lindsey research program under this DOE grant has been to develop tetrapyrrole-based molecular architectures that absorb sunlight, funnel energy and separate charge with high efficiency. Integral to the program has been iterative cycles of design, synthesis and characterization that provided deep insights into the relationships between chemical composition, electronic structure, and key static and dynamic properties (vibrational, redox, photophysical, energy/charge transfer) of tetrapyrrolic systems. Such architectures included monomers, dyads, larger arrays, and complexes with accessory components. The objective was to develop molecular designs and guiding principles to enhance current and future energy-conversion schemes. Molecular arrays targeted to address one or more fundamental questions concerning light harvesting and energy/charge transfer were constructed from analogues of the naturally occurring hemes, chlorophylls and bacteriochlorophylls. Diverse, tunable synthetic building blocks were prepared that spanned the three respective tetrapyrrole families, which are the porphyrins, chlorins and bacteriochlorins. Thus, the research focused on porphyrins as well as synthetic surrogates for chlorophylls (chlorins, 13 1 -oxophorbines and chlorin-imides) and bacteriochlorophylls (bacteriochlorins, bacterio-13 1 -oxophorbines and bacteriochlorin-imides), generically termed hydroporphyrins. Although the three tetrapyrrole classes (porphyrins, chlorins and bacteriochlorins) absorb light strongly in the violet-blue spectral region, the long-wavelength absorption band typically lies in the green-orange, red, and NIR regions, respectively, with increasing intensity. Understanding the spectra, electronic structure, and energy/charge-transfer properties of such tetrapyrrolic macrocycles is of central importance for the rational design of molecular architectures for solar-energy conversion. Our integrated program of molecular design and synthesis coupled with a variety of spectroscopic, electrochemical, and computational studies have probed from first principles how structural and electronic properties of tetrapyrrolic macrocycles dictate spectral properties as well as the rates of ground-state hole/electron transfer and excited-state energy flow in multicomponent architectures. Individual molecules and multicomponent architectures were designed to test ideas of fundamental importance, often requiring the development of new synthetic methodology. The members of the collaborative team had almost daily discussions by phone and/or e-mail concerning design of molecules, flow of compounds between the labs, planning of physical characterization studies, discussing results and analysis and integrating into design of next generation architectures, and the preparation of manuscripts. Furthermore, students and postdocs in the different labs routinely communicated with one another to facilitate the advancement of the research activities. In short, a highly integrated and collaborative research program was well established among the groups. The research effort involved molecular design and synthesis of synthetic molecular architectures by the Lindsey group integrated with physicochemical and photophysical characterization by the Bocian group and the Holten&Kirmaier group (Figure 2). The Bocian group carried out electrochemical, electron paramagnetic resonance (EPR), resonance Raman (RR), and Fourier-transform infrared (FT-IR) studies, as well as density functional theory (DFT) calculations and the time-dependent extension (TDDFT) to gain insight into excited-state properties. The Holten&Kirmaier group carried out static and time-resolved absorption and fluorescence spectroscopy studies and simulated absorption spectra using molecular orbital (MO) energies from DFT as input to the four-orbital model to complement the TDDFT calculations. The combined measurements provided understanding of the vibrational/electronic properties of the individual molecules and the changes that occur upon incorporation into multicomponent architectures. This information underpinned elucidating the mechanisms and timescales of ground-state hole/electron transfer and excited-state energy and charge transfer.

14 SOLAR ENERGY↗

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts’ opinion on the development and application of multi-omic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular and functional aberrations within the lesion and within individual cells. Additionally, single-cell proteomic data will be essential for the establishment of new tools that with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included: • The best way/s to analyze single-cells from fresh and preserved tissue • Detection and analysis of secreted molecules and from single cells, especially from a tissue slice • Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment • Multi-omic integration of data to support and inform proteomic measurements • Subcellular organelles – identifying abnormal structure, function, distribution and location within individual premalignant and malignant cells • How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post translational modifications (PTM) • The depth of coverage measured concurrently using single-cell techniques • Quantitation - absolute or semiquantitative? • Single methodology or multiplexed combinations? • Application of analytical methods for identification of biologically significant subsets • Data visualization of N-dimensional datasets • How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME) • Associations between intrinsic cellular processes and extrinsic stimuli • How to predict cellular responses to stress inducing stimuli • Identification of new markers for prediction of progression from precursor, benign and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells • Identification of new targets for immunoprevention or immunotherapy – identification of neoantigens and surfactome of individual cells within a lesion

59 BASIC BIOLOGICAL SCIENCES↗