Individual Molecular Components Research Articles

Understanding the nervous system: lessons from Frontiers in Neurophotonics.

The Frontiers in Neurophotonics Symposium is a biennial event that brings together neurobiologists and physicists/engineers who share interest in the development of leading-edge photonics-based approaches to understand and manipulate the nervous system, from its individual molecular components to complex networks in the intact brain. In this Community paper, we highlight several topics that have been featured at the symposium that took place in October 2022 in Québec City, Canada.

Specific molecular peak analysis by ion mobility spectrometry of volatile organic compounds in urine of COVID-19 patients: A novel diagnostic approach

IntroductionSARS-CoV-2 is usually diagnosed from naso-/oropharyngeal swabs which are uncomfortable and prone to false results. This study investigated a novel diagnostic approach to Covid-19 measuring volatile organic compounds (VOC) from patients’ urine. MethodsBetween June 2020 and February 2021, 84 patients with positive RT-PCR for SARS-CoV-2 were recruited as well as 54 symptomatic individuals with negative RT-PCR. Midstream urine samples were obtained for VOC analysis using ion mobility spectrometry (IMS) which detects individual molecular components of a gas sample based on their size, configuration, and charge after ionization. ResultsPeak analysis of the 84 Covid and 54 control samples showed good group separation. In total, 37 individual specific peaks were identified, 5 of which (P134, 198, 135, 75, 136) accounted for significant differences between groups, resulting in sensitivities of 89–94% and specificities of 82–94%. A decision tree was generated from the relevant peaks, leading to a combined sensitivity and specificity of 98% each. DiscussionVOC-based diagnosis can establish a reliable separation between urine samples of Covid-19 patients and negative controls. Molecular peaks which apparently are disease-specific were identified. IMS is an additional non-invasive and cheap device for the diagnosis of this ongoing endemic infection. Further studies are needed to validate sensitivity and specificity.

Probing Atmospheric Aerosols by Multimodal Mass Spectrometry Techniques: Revealing Aging Characteristics of Its Individual Molecular Components

Probing Atmospheric Aerosols by Multimodal Mass Spectrometry Techniques: Revealing Aging Characteristics of Its Individual Molecular Components

Functional decomposition of metabolism allows a system-level quantification of fluxes and protein allocation towards specific metabolic functions

Quantifying the contribution of individual molecular components to complex cellular processes is a grand challenge in systems biology. Here we establish a general theoretical framework (Functional Decomposition of Metabolism, FDM) to quantify the contribution of every metabolic reaction to metabolic functions, e.g. the synthesis of biomass building blocks. FDM allowed for a detailed quantification of the energy and biosynthesis budget for growing Escherichia coli cells. Surprisingly, the ATP generated during the biosynthesis of building blocks from glucose almost balances the demand from protein synthesis, the largest energy expenditure known for growing cells. This leaves the bulk of the energy generated by fermentation and respiration unaccounted for, thus challenging the common notion that energy is a key growth-limiting resource. Moreover, FDM together with proteomics enables the quantification of enzymes contributing towards each metabolic function, allowing for a first-principle formulation of a coarse-grained model of global protein allocation based on the structure of the metabolic network.

Modeling contractility kit-mediated cytoskeletal network assembly.

The proper function of the cytoskeleton enables mechanoresponsiveness, the ability of cells to sense and respond to mechanical cues. Myosin II, cortexillin I and IQGAP proteins preassemble in the cytoplasm of Dictyostelium cells into contractility kits (CKs). These CKs are thought to play a pivotal role in the regulation and delivery of contractile proteins to sites of mechanical stress. The IQGAPs complementarily regulate the mechanoresponsiveness of cortexillin I-myosin II elements within CKs. Whereas cells that have only IQGAP2 are highly mechanoresponsive, those that have only IQGAP1 are not. Moreover, double mutants lacking both IQGAPs are also mechanoresponsive, suggesting that IQGAP1 serves as an inhibitor of cortexillin I and myosin II, and part of the role of IQGAP2 is to alleviate IQGAP1's inhibition. To investigate the mechanism of CK self-assembly and the possible molecular means for IQGAP regulation, we developed in SpringSaLaD a coarse-grained excluded-volume molecular model in which all protein polymers are represented by nm-sized spheres connected by spring-like links. The model is parameterized using experimentally measured values acquired through fluorescence cross-correlation spectroscopy (FCCS) and fluorescence correlation spectroscopy (FCS), which describe the interaction affinities and diffusion coefficients for individual molecular components. Simulations of the model provided cluster diffusion coefficients, distributions of cluster sizes, cluster component distributions, and IQGAP ratios in the clusters. Simulations of wild-type and null-mutant conditions revealed that the temporal order of assembly of these kits is dominated by myosin II dimer formation and that IQGAP proteins mediate cluster growth. Additionally, our simulations predicted, and FCCS experiments confirmed, the existence of CKs that incorporate both IQGAP1 and IQGAP2. This molecular model serves to describe the formation of CKs and how their assembly enables and regulates mechanoresponsiveness.

Impact of individual molecular components in determining primary sensitization to latex

Allergy to natural rubber latex emerged as one of the main allergies at the beginning among some professional groups and the general population. Sensitization and development of latex allergy have been attributed to exposure to products containing residual latex proteins. The prevailing cross-reactivity of latex proteins with other food allergens is of great concern. Numerous purified allergens are currently available, which greatly help in patient management, thus determining their specific profile. We conducted a multicenter study to investigate changes, from the ROC analysis, in the characteristics of patients with latex allergy by measuring its major protein components. Sensitization to latex proteins is crucial because it highlights the cross reactivity to inhalants (pollen) and food (fruit). It is very essential in an accurate and specific clinical setting.

Particle-based model of mechanosensory contractility kit assembly

Cell shape change processes, such as proliferation, polarization, migration, and cancer metastasis, rely on a dynamic network of macromolecules. The proper function of this network enables mechanosensation, the ability of cells to sense and respond to mechanical cues. Myosin II and cortexillin I, critical elements of the cellular mechanosensory machinery, preassemble in the cytoplasm of Dictyostelium cells into complexes that we have termed contractility kits (CKs). Two IQGAP proteins then differentially regulate the mechanoresponsiveness of the cortexillin I-myosin II elements within CKs. To investigate the mechanism of CK self-assembly and gain insight into possible molecular means for IQGAP regulation, we developed a coarse-grained excluded volume molecular model in which all protein polymers are represented by nm-sized spheres connected by spring-like links. The model is parameterized using experimentally measured parameters acquired through fluorescence cross-correlation spectroscopy and fluorescence correlation spectroscopy, which describe the interaction affinities and diffusion coefficients for individual molecular components, and which have also been validated via several orthogonal methods. Simulations of wild-type and null-mutant conditions implied that the temporal order of assembly of these kits is dominated by myosin II dimer formation and that IQGAP proteins mediate cluster growth. In addition, our simulations predicted the existence of “ambiguous” CKs that incorporate both classes of IQGAPs, and we confirmed this experimentally using fluorescence cross-correlation spectroscopy. The model serves to describe the formation of the CKs and how their assembly enables and regulates mechanosensation at the molecular level.

Nanoscopic dopamine transporter distribution and conformation are inversely regulated by excitatory drive and D2 autoreceptor activity.

SUMMARYThe nanoscopic organization and regulation of individual molecular components in presynaptic varicosities of neurons releasing modulatory volume neurotransmitters like dopamine (DA) remain largely elusive. Here we show, by application of several super-resolution microscopy techniques to cultured neurons and mouse striatal slices, that the DA transporter (DAT), a key protein in varicosities of dopaminergic neurons, exists in the membrane in dynamic equilibrium between an inward-facing nanodomain-localized and outward-facing unclustered configuration. The balance between these configurations is inversely regulated by excitatory drive and DA D2 autoreceptor activation in a manner dependent on Ca2+ influx via N-type voltage-gated Ca2+ channels. The DAT nanodomains contain tens of transporters molecules and overlap with nanodomains of PIP2 (phosphatidylinositol-4,5-bisphosphate) but show little overlap with D2 autoreceptor, syntaxin-1, and clathrin nanodomains. The data reveal a mechanism for rapid alterations of nanoscopic DAT distribution and show a striking link of this to the conformational state of the transporter.

Label-free laser spectroscopy for respiratory virus detection: A review.

Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real-time, low cost and label-free detection. There are two groups of methods for molecular biomarkers' detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.

Multimodal method of tissue differentiation in neurooncology using Raman spectroscopy, fluorescence and diffuse reflectance spectroscopy

There is a need to expand the possibilities of urgent analysis of intracranial tumor type during resection. These measures are necessary to improve resection quality with preservation of intact tissues and avoiding recurrence and neurological impairment in postoperative period. To create optical-spectral method for differentiating the intracranial tumor types. We used a combination of certain methods such as fluorescence spectroscopy to analyze the content of endogenous and exogenous fluorophores in samples, diffuse reflectance spectroscopy to analyze structural integrity of tissues according to light scattering and blood filling according to hemoglobin spectrum absorption, as well as spontaneous Raman spectroscopy detecting individual molecular components of tissues. The study was conducted at the Laboratory of Neurosurgical Anatomy and Conservation of Biological Materials of the Burdenko Neurosurgical Center and included 93 tissue samples from 60 patients diagnosed with glioblastoma (n=28), meningioma (n=12), astrocytoma (n=9), oligodendroglioma (n=5), and metastasis (n=6). Different types of intracranial tumors that cannot be differentiated using one of the considered spectroscopy modes can be distinguished in another one. Thus, we can conclude possible advantages of combined optical-spectral approach.

Multimodal method of tissue differentiation in neurooncology using Raman spectroscopy, fluorescence and diffuse reflectance spectroscopy

There is a need to expand the possibilities of urgent analysis of intracranial tumor type during resection. These measures are necessary to improve resection quality with preservation of intact tissues and avoiding recurrence and neurological impairment in postoperative period. To create optical-spectral method for differentiating the intracranial tumor types. We used a combination of certain methods such as fluorescence spectroscopy to analyze the content of endogenous and exogenous fluorophores in samples, diffuse reflectance spectroscopy to analyze structural integrity of tissues according to light scattering and blood filling according to hemoglobin spectrum absorption, as well as spontaneous Raman spectroscopy detecting individual molecular components of tissues. The study was conducted at the Laboratory of Neurosurgical Anatomy and Conservation of Biological Materials of the Burdenko Neurosurgical Center and included 93 tissue samples from 60 patients diagnosed with glioblastoma (n=28), meningioma (n=12), astrocytoma (n=9), oligodendroglioma (n=5), and metastasis (n=6). Different types of intracranial tumors that cannot be differentiated using one of the considered spectroscopy modes can be distinguished in another one. Thus, we can conclude possible advantages of combined optical-spectral approach.

Systems biology of angiogenesis signaling: Computational models and omics.

Angiogenesis is a highly regulated multiscale process that involves a plethora of cells, their cellular signal transduction, activation, proliferation, differentiation, as well as their intercellular communication. The coordinated execution and integration of such complex signaling programs is critical for physiological angiogenesis to take place in normal growth, development, exercise, and wound healing, while its dysregulation is critically linked to many major human diseases such as cancer, cardiovascular diseases, and ocular disorders; it is also crucial in regenerative medicine. Although huge efforts have been devoted to drug development for these diseases by investigation of angiogenesis-targeted therapies, only a few therapeutics and targets have proved effective in humans due to the innate multiscale complexity and nonlinearity in the process of angiogenic signaling. As a promising approach that can help better address this challenge, systems biology modeling allows the integration of knowledge across studies and scales and provides a powerful means to mechanistically elucidate and connect the individual molecular and cellular signaling components that function in concert to regulate angiogenesis. In this review, we summarize and discuss how systems biology modeling studies, at the pathway-, cell-, tissue-, and whole body-levels, have advanced our understanding of signaling in angiogenesis and thereby delivered new translational insights for human diseases.This article is categorized under:Cardiovascular Diseases > Computational Models Cancer > Computational Models

Dual detection of chromatin accessibility and DNA methylation using ATAC-Me.

The epigenome is multidimensional, with individual molecular components operating on different levels to control transcriptional output. Techniques that combine measurements of these features can reveal their precise correspondence in genomic space, or temporal connectivity, to better understand how they jointly regulate genes. ATAC-Me is an integrated method to probe DNA methylation and chromatin accessibility from a single DNA fragment library. Intact nuclei undergo Tn5 transposition to isolate DNA fragments within nucleosome-free regions. Isolated fragments are exposed to sodium bisulfite before library amplification and sequencing. A typical ATAC-Me experiment detects ~60,000-75,000 peak regions (P < 0.05), covering ~3-4 million CpG sites with at least 5× coverage. These sites display a range of methylation values depending on the cellular and genomic context. The approach is well suited for time course studies that aim to capture chromatin and DNA methylation dynamics in tandem during cellular differentiation. The protocol is completed in 2 d with standard molecular biology equipment and expertise. Analysis of resulting data uses publicly available software requiring basic bioinformatics skills to interpret results.

Systems-Level Chemical Biology to Accelerate Antibiotic Drug Discovery.

Drug-resistant bacterial infections pose an imminent and growing threat to public health. The discovery and development of new antibiotics of novel chemical class and mode of action that are unsusceptible to existing resistance mechanisms is imperative for tackling this threat. Modern industrial drug discovery, however, has failed to provide new drugs of this description, as it is dependent largely on a reductionist genes-to-drugs research paradigm. We posit that the lack of success in new antibiotic drug discovery is due in part to a lack of understanding of the bacterial cell system as whole. A fundamental understanding of the architecture and function of bacterial systems has been elusive but is of critical importance to design strategies to tackle drug-resistant bacterial pathogens.Increasingly, systems-level approaches are rewriting our understanding of the cell, defining a dense network of redundant and interacting components that resist perturbations of all kinds, including by antibiotics. Understanding the network properties of bacterial cells requires integrative, systematic, and genome-scale approaches. These methods strive to understand how the phenotypic behavior of bacteria emerges from the many interactions of individual molecular components that constitute the system. With the ability to examine genomic, transcriptomic, proteomic, and metabolomic consequences of, for example, genetic or chemical perturbations, researchers are increasingly moving away from one-gene-at-a-time studies to consider the system-wide response of the cell. Such measurements are demonstrating promise as quantitative tools, powerful discovery engines, and robust hypothesis generators with great value to antibiotic drug discovery.In this Account, we describe our thinking and findings using systems-level studies aimed at understanding bacterial physiology broadly and in uncovering new antibacterial chemical matter of novel mechanism. We share our systems-level toolkit and detail recent technological developments that have enabled unprecedented acquisition of genome-wide interaction data. We focus on three types of interactions: gene-gene, chemical-gene, and chemical-chemical. We provide examples of their use in understanding cell networks and how these insights might be harnessed for new antibiotic discovery. By example, we show the application of these principles in mapping genetic networks that underpin phenotypes of interest, characterizing genes of unknown function, validating small-molecule screening platforms, uncovering novel chemical probes and antibacterial leads, and delineating the mode of action of antibacterial chemicals. We also discuss the importance of computation to these approaches and its probable dominance as a tool for systems approaches in the future. In all, we advocate for the use of systems-based approaches as discovery engines in antibacterial research, both as powerful tools and to stimulate innovation.

Supramolecular Relay-Control of Organocatalysis with a Hemithioindigo-Based Molecular Motor.

Integration of individual molecular components such as molecular motors or switches into larger meta-functional systems represents a current challenge at the forefront of molecular machine research. Here we present a modular supramolecular approach to relay the photoinduced geometry changes of a hemithioindigo based molecular motor into catalytic efficiency of a chemical reaction. Using the intrinsic chemical nature of the motor for recognition of different hydrogen-bonding organocatalysts a greater than 10-fold modulation in binding affinity is achieved upon photoisomerization. This change in affinity is then translated effectively into control of catalytic competence of the organocatalysts without direct interference by the motor. As an example the organocatalysed Michael addition reaction between nitrostyrene and 3-methoxy-dimethyl aniline was modulated in situ by visible light irradiation. Thus, dynamic and reversible remote control of catalytic processes by the switching capacity of a hemithioindigo molecular motor is established in a multicomponent chemical system. The high intrinsic modularity of this approach presents further advantages, e.g., for easy tailoring of conditions or facile exchange of catalysts and reactions. These results represent a first stepping stone into integrated chemical networks regulated by molecular machines in a fully dynamic way.

Imaging layers in thin-film molecular devices by transmission electron microscopy, using milling by focused ion beams and deposition on NaCl and Si

The performance of molecule-based thin-film devices such as organic light-emitting diodes, photovoltaic cells, and thin-film transistors depends on the electronic properties of the individual molecular components, as well as on their association to form complex morphologies. Transmission electron microscopy (TEM) can be used to image the morphologies and help reveal how the devices work and can be improved. We have examined the suitability of various ways to prepare samples of thin molecular films for imaging by TEM. Specifically, we have used focused ion beams to mill cross sections of complete devices that have been glued together with epoxy adhesives. In addition, thin films of the type used as active layers in molecule-based devices can be deposited on disks of NaCl, which can then be dissolved in water to release free-standing films that can be imaged by TEM, without loss of nanostructural details. Films of this type can also be deposited on Si wafers, which can then be fractured to expose sections of film that overhang edges of fragments and can be imaged conveniently by TEM. This allows TEM to be used as a quick method for screening samples and monitoring the purification of active materials.

Computational models to explore the complexity of the epithelial to mesenchymal transition in cancer.

Epithelial to mesenchymal transition (EMT) is a complex biological process that plays a key role in cancer progression and metastasis formation. Its activation results in epithelial cells losing adhesion and polarity and becoming capable of migrating from their site of origin. At this step the disease is generally considered incurable. As EMT execution involves several individual molecular components, connected by nontrivial relations, in vitro techniques are often inadequate to capture its complexity. Computational models can be used to complement experiments and provide additional knowledge difficult to build up in a wetlab. Indeed in silico analysis gives the user total control on the system, allowing to identify the contribution of each independent element. In the following, two kinds of approaches to the computational study of EMT will be presented. The first relies on signal transduction networks description and details how changes in gene expression could influence this process, both focusing on specific aspects of the EMT and providing a general frame for this phenomenon easily comparable with experimental data. The second integrates single cell and population level descriptions in a multiscale model that can be considered a more accurate representation of the EMT. The advantages and disadvantages of each approach will be highlighted, together with the importance of coupling computational and experimental results. Finally, the main challenges that need to be addressed to improve our knowledge of the role of EMT in the neoplastic disease and the scientific and translational value of computational models in this respect will be presented. This article is categorized under: Analytical and Computational Methods > Computational Methods.

Single-Molecule Imaging and Labelling with DNA-Based Superresolution Microscopy

Recent advances in localisation-based super-resolution microscopy have enabled researchers to visualise single molecular features down to individual molecular components (∼5 nm), but do not yet allow manipulation of single-molecule targets in a user-prescribed, context-dependent manner. Here we report an “Action-PAINT” strategy for super-resolution labelling upon visualisation on single molecules. This approach monitors and localises DNA binding events in real-time with DNA-PAINT, and upon visualisation of binding to a desired location, photo-crosslinks the DNA to affix the molecular label. We showed the efficiency of 3-cyanovinylcarbazole nucleoside (CNVK) photo-inducible crosslinking on single molecular targets and developed a software package for real-time super-resolution imaging and crosslinking control. We then benchmarked our super-resolution labelling method on synthetic DNA nanostructures and demonstrated targeted multi-point labelling on various complex patterns with 30 nm selectivity. Finally, we performed targeted in situ labelling on fixed microtubule samples with 40 nm target size and custom-controlled, sub-diffraction spacing.

Exploring the dynamics of flagellar dynein within the axoneme with Fluctuating Finite Element Analysis.

Flagellar dyneins are the molecular motors responsible for producing the propagating bending motions of cilia and flagella. They are located within a densely packed and highly organised super-macromolecular cytoskeletal structure known as the axoneme. Using the mesoscale simulation technique Fluctuating Finite Element Analysis (FFEA), which represents proteins as viscoelastic continuum objects subject to explicit thermal noise, we have quantified the constraints on the range of molecular conformations that can be explored by dynein-c within the crowded architecture of the axoneme. We subsequently assess the influence of crowding on the 3D exploration of microtubule-binding sites, and specifically on the axial step length. Our calculations combine experimental information on the shape, flexibility and environment of dynein-c from three distinct sources; negative stain electron microscopy, cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET). Our FFEA simulations show that the super-macromolecular organisation of multiple protein complexes into higher-order structures can have a significant influence on the effective flexibility of the individual molecular components, and may, therefore, play an important role in the physical mechanisms underlying their biological function.

Super-resolution labelling with Action-PAINT.

Recent advances in localisation-based super-resolution microscopy have enabled researchers to visualise single molecular features down to individual molecular components (~5 nm), but do not yet allow manipulation of single-molecule targets in a user-prescribed, context-dependent manner. Here we report an “Action-PAINT” strategy for super-resolution labelling upon visualisation on single molecules. This approach monitors and localises DNA binding events in real-time with DNA-PAINT, and upon visualisation of binding to a desired location, photo-crosslinks the DNA to affix the molecular label. We showed the efficiency of 3-cyanovinylcarbazole nucleoside (CNVK) photo-inducible crosslinking on single molecular targets and developed a software package for real-time super-resolution imaging and crosslinking control. We then benchmarked our super-resolution labelling method on synthetic DNA nanostructures and demonstrated targeted multi-point labelling on various complex patterns with 30 nm selectivity. Finally, we performed targeted in situ labelling on fixed microtubule samples with 40 nm target size and custom-controlled, sub-diffraction spacing.