Biological Systems Research Articles

Luminescence Probes in Bio-Applications: From Principle to Practice

Bioanalysis based on optical imaging has gained significant progress in the last few decades. Luminescence probes are capable of detecting, monitoring, and tracing particular biomolecules in complex biological systems to figure out the roles of these molecules in organisms. Considering the rapid development of luminescence probes for bio-applications and their promising future, we have attempted to explore the working principles and recent advances in bio-applications of luminescence probes, in the hope of helping readers gain a detailed understanding of luminescence probes developed in recent years. In this review, we first focus on the current widely used luminescence probes, including fluorescence probes, bioluminescence probes, chemiluminescence probes, afterglow probes, photoacoustic probes, and Cerenkov luminescence probes. The working principles for each type of luminescence probe are concisely described and the bio-application of the luminescence probes is summarized by category, including metal ions detection, secretion detection, imaging, and therapy.

Split Luciferase Molecular Tension Sensors for Bioluminescent Readout of Mechanical Forces in Biological Systems.

The ability of proteins to sense and transmit mechanical forces underlies many biological processes, but characterizing these forces in biological systems remains a challenge. Existing genetically encoded force sensors typically rely on fluorescence or bioluminescence resonance energy transfer (FRET or BRET) to visualize tension. However, these force sensing modules are relatively large, and interpreting measurements requires specialized image analysis and careful control experiments. Here, we report a compact molecular tension sensor that generates a bioluminescent signal in response to tension. This sensor (termed PILATeS) makes use of the split NanoLuc luciferase and consists of the H. sapiens titin I10 domain with the insertion of a 10-15 amino acid tag derived from the C-terminal β-strand of NanoLuc. Mechanical load across PILATeS mediates exposure of this tag to recruit the complementary split NanoLuc fragment, resulting in force-dependent bioluminescence. We demonstrate the ability of PILATeS to report biologically meaningful forces by visualizing forces at the interface between integrins and extracellular matrix substrates. We further use PILATeS as a genetically encoded sensor of tension experienced by the mechanosensing protein vinculin. We anticipate that PILATeS will provide an accessible means of visualizing molecular-scale forces in biological systems.

Optical Halo: A Proof of Concept for a New Broadband Microrheology Tool

Microrheology, the study of material flow at micron scales, has advanced significantly since Robert Brown’s discovery of Brownian motion in 1827. Mason and Weitz’s seminal work in 1995 established the foundation for microrheology techniques, enabling the measurement of viscoelastic properties of complex fluids using light-scattering particles. However, existing techniques face limitations in exploring very slow dynamics, crucial for understanding biological systems. Here, we present a proof of concept for a novel microrheology technique called “Optical Halo”, which utilises a ring-shaped Bessel beam created by optical tweezers to overcome existing limitations. Through numerical simulations and theoretical analysis, we demonstrate the efficacy of the Optical Halo in probing viscoelastic properties across a wide frequency range, including low-frequency regimes inaccessible to conventional methods. This innovative approach holds promise for elucidating the mechanical behaviour of complex biological fluids.

Optical Halo: A Proof of Concept for a New Broadband Microrheology Tool

Microrheology, the study of material flow at micron scales, has advanced significantly since Robert Brown’s discovery of Brownian motion in 1827. Mason and Weitz’s seminal work in 1995 established the foundation for microrheology techniques, enabling the measurement of viscoelastic properties of complex fluids using light-scattering particles. However, existing techniques face limitations in exploring very slow dynamics, crucial for understanding biological systems. Here, we present a proof of concept for a novel microrheology technique called “Optical Halo”, which utilises a ring-shaped Bessel beam created by optical tweezers to overcome existing limitations. Through numerical simulations and theoretical analysis, we demonstrate the efficacy of the Optical Halo in probing viscoelastic properties across a wide frequency range, including low-frequency regimes inaccessible to conventional methods. This innovative approach holds promise for elucidating the mechanical behaviour of complex biological fluids.

Laser Ablating Biomimetic Periodic Array Fish Scale Surface for Drag Reduction

Reducing resistance to surface friction is challenging in the field of engineering. Natural biological systems have evolved unique functional surfaces or special physiological functions to adapt to their complex environments over centuries. Among these biological wonders, fish, one of the oldest in the vertebrate group, have garnered attention due to their exceptional fluid dynamics capabilities. Fish skin has inspired innovation in reducing surface friction due to its unique structures and material properties. Herein, drawing inspiration from the unique properties of fish scales, a periodic array of fish scales was fabricated by laser ablation on a polished aluminum template. The morphology of the biomimetic fish scale surface was characterized using scanning electron microscopy and a white-light interfering profilometer. Drag reduction performance was measured in a closed circulating water tunnel. The maximum drag reduction was 10.26% at a Reynolds number of 39,532, and the drag reduction performance gradually decreased with an increase in the distance between fish scales. The mechanism of the biomimetic drag reduction surface was analyzed using computational fluid dynamics. Streamwise vortices were generated at the valley of the biomimetic fish scale, replacing sliding friction with rolling friction. These results are expected to provide a foundation for in-depth analysis of the hydrodynamic performance of fish and serve as new inspiration for drag reduction and antifouling.

Laser Ablating Biomimetic Periodic Array Fish Scale Surface for Drag Reduction

Reducing resistance to surface friction is challenging in the field of engineering. Natural biological systems have evolved unique functional surfaces or special physiological functions to adapt to their complex environments over centuries. Among these biological wonders, fish, one of the oldest in the vertebrate group, have garnered attention due to their exceptional fluid dynamics capabilities. Fish skin has inspired innovation in reducing surface friction due to its unique structures and material properties. Herein, drawing inspiration from the unique properties of fish scales, a periodic array of fish scales was fabricated by laser ablation on a polished aluminum template. The morphology of the biomimetic fish scale surface was characterized using scanning electron microscopy and a white-light interfering profilometer. Drag reduction performance was measured in a closed circulating water tunnel. The maximum drag reduction was 10.26% at a Reynolds number of 39,532, and the drag reduction performance gradually decreased with an increase in the distance between fish scales. The mechanism of the biomimetic drag reduction surface was analyzed using computational fluid dynamics. Streamwise vortices were generated at the valley of the biomimetic fish scale, replacing sliding friction with rolling friction. These results are expected to provide a foundation for in-depth analysis of the hydrodynamic performance of fish and serve as new inspiration for drag reduction and antifouling.

Molecular mechanisms of precise timing in cell lysis

Many biological systems exhibit precise timing of events, and one of the most known examples is cell lysis, which is a process of breaking bacterial host cells in the virus infection cycle. However, the underlying microscopic picture of precise timing remains not well understood. We present a novel theoretical approach to explain the molecular mechanisms of effectively deterministic dynamics in biological systems. Our hypothesis is based on the idea of stochastic coupling between relevant underlying biophysical and biochemical processes that lead to noise cancellation. To test this hypothesis, we introduced a minimal discrete-state stochastic model to investigate how holin proteins produced by bacteriophages break the inner membranes of gram-negative bacteria. By explicitly solving this model, the dynamic properties of cell lysis are fully evaluated, and theoretical predictions quantitatively agree with available experimental data for both wild-type and holin mutants. It is found that the observed threshold-like behavior is a result of the balance between holin proteins entering the membrane and leaving the membrane during the lysis. Theoretical analysis suggests that the cell lysis achieves precise timing for wild-type species by maximizing the number of holins in the membrane and narrowing their spatial distribution. In contrast, for mutated species, these conditions are not satisfied. Our theoretical approach presents a possible molecular picture of precise dynamic regulation in intrinsically random biological processes.

A Delayed Spiking Neural Membrane System for Adaptive Nearest Neighbor-Based Density Peak Clustering.

Although the density peak clustering (DPC) algorithm can effectively distribute samples and quickly identify noise points, it lacks adaptability and cannot consider the local data structure. In addition, clustering algorithms generally suffer from high time complexity. Prior research suggests that clustering algorithms grounded in P systems can mitigate time complexity concerns. Within the realm of membrane systems (P systems), spiking neural P systems (SN P systems), inspired by biological nervous systems, are third-generation neural networks that possess intricate structures and offer substantial parallelism advantages. Thus, this study first improved the DPC by introducing the maximum nearest neighbor distance and K-nearest neighbors (KNN). Moreover, a method based on delayed spiking neural P systems (DSN P systems) was proposed to improve the performance of the algorithm. Subsequently, the DSNP-ANDPC algorithm was proposed. The effectiveness of DSNP-ANDPC was evaluated through comprehensive evaluations across four synthetic datasets and 10 real-world datasets. The proposed method outperformed the other comparison methods in most cases.

An insight of heart-like systems with percolation

We study the signal percolation through heart-like biological system. Starting from an initial distribution of waiting and inactive cells with probabilities p and (1−p) respectively, the signal propagation is observed in terms of active cells. As the signal enters the system from one end, the number of arrival of active sites at the other end is studied and analysis of the system behaviour is made by varying a few important parameters of the system like pswitch (switching probability from inactive to waiting) and pact (switching probability from waiting to active). In this connection, the non-regular heart rhythms are discussed. Fraction of paths percolating through the system shows a transition from 0 to 1 near p=pc. Some other important quantities like tortuosity and cluster distribution are discussed. Several critical exponents have been obtained and compared the exponents of standard percolation.

Enantioselective Carbon Isotope Exchange.

The synthesis of isotopically labeled organic molecules is vital for drug and agrochemical discovery and development. Carbon isotope exchange is emerging as a leading method to generate carbon-labeled targets, which are sought over hydrogen-based labels due to their enhanced stability in biological systems. While many bioactive small molecules bear carbon-containing stereocenters, direct enantioselective carbon isotope exchange reactions have not been established. We describe the first example of an enantioselective carbon isotope exchange reaction, where (radio)labeled α-amino acids can be generated from their unlabeled precursors using a stoichiometric chiral aldehyde receptor with isotopically labeled CO2 followed by imine hydrolysis. Many proteinogenic and non-natural derivatives undergo enantioselective labeling, including the late-stage radiolabeling of complex drug targets.

Neurobehavioral, neurotransmitter and redox modifications in Nauphoeta cinerea under mixed heavy metal (silver and mercury) exposure

Heavy metals are encountered in nature, and are used in several human endeavors, including in dental fillings. It is well known that the safety of metals depends on their chemical form, as well as the dose and route through which biological systems are exposed to them. Here, we used the Nauphoeta cinerea model to examine the mechanism by which salts of the heavy metals used in dental fillings – silver and mercury – exert their neurotoxicity. Nymphs exposed to heavy metals presented with reduced motor and exploratory abilities as they spent more time immobile, especially in the periphery of a novel object, and covered less distance compared with control nymphs. Exposure to AgNO3 and HgCl2 also exacerbated levels of oxidative stress markers (MDA & ROS) and the neurotransmitter regulators – AChE and MAO, while reducing antioxidant activity markers, both in biochemical (thiol & GST) and RT-qPCR (TRX, GST, SOD, Catalase) examinations, in neural tissues of the cockroach. The observed disruptions in neurolocomotor control, synaptic transmission and redox balance explain how heavy metal salts may predispose organisms to neurological disorders.

Possible detection of atmospheric bioaerosol via LiDAR: a wavelength-based simulation study

This study explores potential of LiDAR technology to rapidly detect aerosolized biological terror agents in the atmosphere. It assesses the application by simulating extinction coefficients and the Ångström exponent at various wavelengths (266, 1064, 1571, and 2000 nm), focusing on differentiating bioaerosols from typical atmospheric particles. The simulation analysis evaluates changes in aerosol distributions and related extinction coefficient and Ångström exponent shifts under clean, normal, and bad atmospheric conditions. The findings indicate that the 1064 nm wavelength effectively detects bioaerosol presence, with a combination of 1064 nm and 1571 nm providing optimal Ångström exponent use for particle size differentiation. This dual-wavelength approach is highlighted as a practical method for bioaerosol detection, showcasing a significant sensitivity to variations in particle quantity and size, which are critical in biological threat scenarios. In conclusion, the study offers guidance for selecting LiDAR wavelengths for biological agent detection systems. While providing a theoretical framework for practical applications, it also underlines the need for further experimental work to confirm findings and fine-tune technology for real-world monitoring and threat management. This research contributes to the development of effective monitoring strategies against the backdrop of biological terror threats.Graphical

Unveiling the molecular insights of 2-(carboxymethyl) benzoic acid: A density functional theory approach towards structural and biological attributes

Nowadays density functional theory (DFT) is one of the best methods to explore the vibrational modes and structure of the biological system. Quantum mechanical calculations are performed using gas phase and different solvents (DMSO, methanol and water). The derived global reactive parameters, structural and topological study provides the clear insight of the 2-(Carboxymethyl) benzoic acid. Depth studies of DFT proves the existence of hydrogen bonds between donor and acceptor in the compound, which is supportive for the biological applications. In this paper, different experimental and computational simulated FT-IR, FT-Raman, UV–Vis spectral studies are used to explicate vibration assignments of the 2-(Carboxymethyl) benzoic acid. Experimentally observed vibrational frequency is compared with theoretically simulated spectrum. B3LYP method with 6–311++G (d, p) basis set is used in DFT to optimize the 2-(Carboxymethyl)benzoic acid structure. The most stable lower energy conformer is identified using potential energy surface (PES) analysis using Gaussian 16 W software. ESP, HOMO-LUMO, NBO, and QTAIM calculations have evinced an adequate electronic characterization of 2-(Carboxymethyl) benzoic acid. Further, van der Waals and steric interactions among 2-(Carboxymethyl) benzoic acid have been discussed with the help of RDG study. Hirshfeld surface studies establish the existing various interaction among molecules and total packing arrangement of the crystal structure. Due to the high biological activity score, 2-(Carboxymethyl) benzoic acid is a good therapeutic candidate. Lipophilicity analysis of 2-(Carboxymethyl)benzoic acid clearly explicates the bioactivity properties and its effective drug applications. Further, molecular docking investigates that the compound can be used as anticancer medication. The detailed DFT study of the 2-(Carboxymethyl) benzoic acid justified its biological applications of the present communication. The calculated NLO parameters of 2-(Carboxymethyl)benzoic acid evidenced for good efficacy in diverse filed application has been discussed.

Fe(III)-Based Fluorescent Probe for High-Performance Recognition, Test Strip Analysis, and Cell Imaging of Carbon Monoxide.

Fluorescence sensing and imaging techniques are being widely studied for detecting carbon monoxide (CO) in living organisms due to their speed, sensitivity, and ease of use to biological systems. Most fluorescent probes used for this purpose are based on heavy metal ions like Pd, with a few using elements like Ru, Rh, Ir, Os, Tb, and Eu. However, these metals can be expensive and toxic to cells. There is a need for more affordable and biologically safe fluorescent probes for CO detection. Drawing inspiration from the robust affinity exhibited by heme iron toward CO, in this work, a rhodamine derivative called RBF was developed for imaging CO in living cells by binding to Fe(III) and could be used for CO sensing. A Fe(III)-based fluorescent probe for CO imaging in living cells offers advantages of cost effectiveness, low toxicity, and ease of use. The fluorescence detection using the RBF-Fe system showed a direct correlation with increasing levels of CORM-3 (LOD = 146 nM) or the exposure time of CO gas, displaying reduced fluorescence. A CO test paper based on RBF-Fe was created for simple on-site CO detection, where fluorescence would diminish in response to CO exposure, allowing rapid (2 min) visual identification. Imaging of CO in living cells was successfully conducted using the probe system, showing a decrease in fluorescence intensity as CORM-3 concentrations increased, indicating its effectiveness in monitoring CO levels accurately within living cells.

Extreme dependence of dynamics on concentration in highly crowded polyelectrolyte solutions.

Charge-carrying species, such as polyelectrolytes, are vital to natural and synthetic processes that rely on their dynamic behavior. Through single-particle tracking techniques, the diffusivity of individual polyelectrolyte chains and overall system viscosity are determined for concentrated polylysine solutions. These studies show scaling dependences of D ~ c-6.1 and η ~ c7.2, much stronger than theoretical predictions, drawing the applicability of power law fits into question. Similar trends are observed in concentrated solutions prepared at various pH and counterion conditions. These hindered system dynamics appear universal to polyelectrolyte systems and are attributed to the large effective excluded volumes of polyelectrolyte chains inducing glassy dynamics. The framework of the Vrentas-Duda free-volume theory is used to compare polyelectrolyte and neutral systems. Supported by this theory, excluding counterion mass from total polymer mass results in all environmental conditions collapsing onto a common trendline. These results are applicable to crowded biological systems, such as intracellular environments where protein mobility is strongly inhibited.

Integrating host and microbiome biology using holo-omics.

Holo-omics is the use of omics data to study a host and its inherent microbiomes - a biological system known as a "holobiont". A microbiome that exists in such a space often encounters habitat stability and in return provides metabolic capacities that can benefit their host. Here we present an overview of beneficial host-microbiome systems and propose and discuss several methodological frameworks that can be used to investigate the intricacies of the many as yet undefined host-microbiome interactions that influence holobiont homeostasis. While this is an emerging field, we anticipate that ongoing methodological advancements will enhance the biological resolution that is necessary to improve our understanding of host-microbiome interplay to make meaningful interpretations and biotechnological applications.

Treatment appraisal and fate of HMs in up-flow anaerobic sludge blanket and trickling filter-based sewage treatment process: The case of a kaliti Centralized Wastewater Treatment Plant, Addis Ababa, Ethiopia

Heavy metals (HMs) in wastewater could pose a significant challenge to biological treatment systems such as in an Up-flow Anaerobic Sludge Blanket Reactor (UASBr) as well as Trickling Filter (TF) performances. These HMs are associated with retention and accumulation of solid precipitates, limitting solid-liquid separation, disrupting biochemical processes, which ultimately brings environmental risks, such as soil contamination and public health issues, dominantly due to the inhibited activities of degrading microorganisms. A cross-sectional study was applied to investigate the levels of HMs in sewage using composite and grab sampling taken from Kaliti Wastewater Treatment Plant and the samples were analyzed using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). The HMs concentrations in mean±(SD) were, Ag ranges from below detection level (BDL) to 63.5 (13.5) mg/kg; Ba 60 (4.47) μg/l to 1291(58.5) mg/kg; Al, BDL to 2358.5(662.5) mg/kg; Cd 0 μg/l to 0.35(0.15) mg/kg; Cr 0 μg/l to 10.5(0.7) mg/kg; Cu 0 μg/l to 23.9(1.2) mg/kg; Zn 5.45 (12.3) to 165(5.4) mg/kg, and Mn 165 (49.5) μg/l to 92.5(3.8) mg/kg. Results indicated that Kaliti Wastewater Treatment Plant was effective in removing pollutants and thereby meeting local and international discharge limits. The plant was also found to be effective in removing Al, Cd, Cu, and Cr, but not in removing Ba and Zn. However, a real time data collection and monitoring of seasonal physicochemical parameters and HM levels in the wastewater treatment plant is suggested useful.

Ultra-selective pyrene-based fluorescent sensor for detection of Fe+3 in neat aqueous medium

Transition metals, particularly Fe+3, play vital roles in biological and environmental systems, yet their chronic elevation can lead to severe diseases. Early detection of Fe+3 is crucial for diagnosing associated ailments. While traditional detection methods have drawbacks, fluorescent sensors offer promising alternatives due to their ease of use, cost-effectiveness, and real-time monitoring capability. Pyrene-based sensors have demonstrated notable sensitivity and selectivity for Fe+3, but challenges remain in achieving applicability in neat aqueous systems. We present two novel turn-off pyrene-based sensors, APTS (sodium 8-aminopyrene-1,3,6-trisulfonate) and APSS (sodium (E)-4-hydroxy-3-((pyren-1-ylimino)methyl)benzenesulfonate), incorporating sulfonate groups to enable their use in pure water samples and achieve nanomolar-level detection limits. Through meticulous experimental and characterization efforts, we elucidate the significance of the imine linkage in enhancing selectivity towards Fe+3 ions. Our sensors exhibit exceptional selectivity and sensitivity, with LODs of 45.6 nM and 45.9 nM for APTS and APSS, respectively, surpassing environmental protection guidelines. Additionally, binding stoichiometry studies reveal insights into the interaction mechanisms, supported by fluorescence lifetime analysis and DFT studies. APSS particularly stands out for its lack of interference from other metal ions, notably Cu2+ as well as Fe2+, offering promising potential for real-time applications and development of paper strip tests. The practical applicability of our sensors is demonstrated through successful Fe+3 detection in various water samples with recoveries ranging from 94 % to 104 %. Overall, our study highlights the effectiveness of APTS and APSS as robust fluorescent probes, with implications for environmental monitoring and biomedical diagnostics.

Low microbial diversity, yeast prevalence, and nematode-trapping fungal presence in fungal colonization and leaf microbiome of Serjania erecta

Medicinal plant microbiomes undergo selection due to secondary metabolite presence. Resident endophytic/epiphytic microorganisms directly influence plant’s bioactive compound synthesis. Hypothesizing low microbial diversity in Serjania erecta leaves, we assessed leaf colonization by epiphytic and endophytic fungi. Given its traditional medicinal importance, we estimated diversity in the endophytic fungal microbiome. Analyses included scanning electron microscopy (SEM), isolation of cultivable species, and metagenomics. Epiphytic fungi interacted with S. erecta leaf tissues, horizontally transmitted via stomata/trichome bases, expressing traits for nematode trapping. Cultivable endophytic fungi, known for phytopathogenic habits, didn’t induce dysbiosis symptoms. This study confirms low leaf microbiome diversity in S. erecta, with a tendency towards more fungal species, likely due to antibacterial secondary metabolite selection. The classification of Halicephalobus sp. sequence corroborated the presence of nematode eggs on the epidermal surface of S. erecta by SEM. In addition, we confirmed the presence of methanogenic archaea and a considerable number of methanotrophs of the genus Methylobacterium. The metagenomic study of endophytic fungi highlighted plant growth-promoting yeasts, mainly Malassezia, Leucosporidium, Meyerozyma, and Hannaella. Studying endophytic fungi and S. erecta microbiomes can elucidate their impact on beneficial bioactive compound production, on the other hand, it is possible that the bioactive compounds produced by this plant can recruit specific microorganisms, impacting the biological system.

Quantifying superimposed protein flow dynamics in live cells using spatial filtering and spatiotemporal image correlation spectroscopy.

Flow or collective movement is a frequently observed phenomenon for many cellular components including the cytoskeletal proteins actin and myosin. To study protein flow in living cells, we and others have previously used spatiotemporal image correlation spectroscopy (STICS) analysis on fluorescence microscopy image time series. Yet, in cells, multiple protein flows often occur simultaneously on different scales resulting in superimposed fluorescence intensity fluctuations that are challenging to separate using STICS. Here, we exploited the characteristic that distinct protein flows often occur at different spatial scales present in the image series to disentangle superimposed protein flow dynamics. We employed a newly developed and an established spatial filtering algorithm to alternatively accentuate or attenuate local image intensity heterogeneity across different spatial scales. Subsequently, we analysed the spatially filtered time series with STICS, allowing the quantification of two distinct superimposed flows within the image time series. As a proof of principle of our analysis approach, we used simulated fluorescence intensity fluctuations as well as time series of nonmuscle myosin II in endothelial cells and actin-based podosomes in dendritic cells and revealed simultaneously occurring contiguous and noncontiguous flow dynamics in each of these systems. Altogether, this work extends the application of STICS for the quantification of multiple protein flow dynamics in complex biological systems including the actomyosin cytoskeleton.