Tularemia Clinical Manifestations, Antimicrobial Treatment, and Outcomes: An Analysis of US Surveillance Data, 2006-2021.

BACKGROUND: Tularemia, a potentially fatal zoonosis caused by Francisella tularensis, has been reported from nearly all US states. Information on relative effectiveness of various antimicrobials for treatment of tularemia is limited, particularly for newer classes such as fluoroquinolones. METHODS: Data on clinical manifestations, antimicrobial treatment, and illness outcome of patients with tularemia are provided voluntarily through case report forms to the US Centers for Disease Control and Prevention by state and local health departments. We summarized available demographic and clinical information submitted during 2006-2021 and evaluated survival according to antimicrobial treatment. We grouped administered antimicrobials into those considered effective for treatment of tularemia (aminoglycosides, fluoroquinolones, and tetracyclines) and those with limited efficacy. Logistic regression models with a bias-reduced estimation method were used to evaluate associations between antimicrobial treatment and survival. RESULTS: Case report forms were available for 1163 US patients with tularemia. Francisella tularensis was cultured from a clinical specimen (eg, blood, pleural fluid) in approximately half of patients (592; 50.9%). Nearly three-quarters (853; 73.3%) of patients were treated with a high-efficacy antimicrobial. A total of 27 patients (2.3%) died. After controlling for positive culture as a proxy for illness severity, use of aminoglycosides, fluoroquinolones, and tetracyclines was independently associated with increased odds of survival. CONCLUSIONS: Most US patients with tularemia received high-efficacy antimicrobials; their use was associated with improved odds of survival regardless of antimicrobial class. Our findings provide supportive evidence that fluoroquinolones are an effective option for treatment of tularemia.

Overcoming Symmetry Mismatch in Vaccine Nanoassembly through Spontaneous Amidation.

Matching of symmetry at interfaces is a fundamental obstacle in molecular assembly. Virus-like particles (VLPs) are important vaccine platforms against pathogenic threats, including Covid-19. However, symmetry mismatch can prohibit vaccine nanoassembly. We established an approach for coupling VLPs to diverse antigen symmetries. SpyCatcher003 enabled efficient VLP conjugation and extreme thermal resilience. Many people had pre-existing antibodies to SpyTag:SpyCatcher but less to the 003 variants. We coupled the computer-designed VLP not only to monomers (SARS-CoV-2) but also to cyclic dimers (Newcastle disease, Lyme disease), trimers (influenza hemagglutinins), and tetramers (influenza neuraminidases). Even an antigen with dihedral symmetry could be displayed. For the global challenge of influenza, SpyTag-mediated display of trimer and tetramer antigens strongly induced neutralizing antibodies. SpyCatcher003 conjugation enables nanodisplay of diverse symmetries towards generation of potent vaccines.

Quantification of circulating Mycobacterium tuberculosis antigen peptides allows rapid diagnosis of active disease and treatment monitoring.

Tuberculosis (TB) is a major global health threat, resulting in an urgent unmet need for a rapid, non-sputum-based quantitative test to detect active Mycobacterium tuberculosis (Mtb) infections in clinically diverse populations and quickly assess Mtb treatment responses for emerging drug-resistant strains. We have identified Mtb-specific peptide fragments and developed a method to rapidly quantify their serum concentrations, using antibody-labeled and energy-focusing porous discoidal silicon nanoparticles (nanodisks) and high-throughput mass spectrometry (MS) to enhance sensitivity and specificity. NanoDisk-MS diagnosed active Mtb cases with high sensitivity and specificity in a case-control study with cohorts reflecting the complexity of clinical practice. Similar robust sensitivities were obtained for cases of culture-positive pulmonary TB (PTB; 91.3%) and extrapulmonary TB (EPTB; 92.3%), and the sensitivities obtained for culture-negative PTB (82.4%) and EPTB (75.0%) in HIV-positive patients significantly outperformed those reported for other available assays. NanoDisk-MS also exhibited high specificity (87.1-100%) in both healthy and high-risk groups. Absolute quantification of serum Mtb antigen concentration was informative in assessing responses to antimycobacterial treatment. Thus, a NanoDisk-MS assay approach could significantly improve the diagnosis and management of active TB cases, and perhaps other infectious diseases as well.

The influence of heteromultivalency on lectin-glycan binding behavior.

We recently discovered that the nature of lectin multivalency and glycolipid diffusion on cell membranes could lead to the heteromultivalent binding (i.e., a single lectin simultaneously binding to different types of glycolipid ligands). This heteromultivalent binding may even govern the lectin-glycan recognition process. To investigate this, we developed a kinetic Monte Carlo simulation, which only considers the fundamental physics/chemistry principles, to model the process of lectin binding to glycans on cell surfaces. We found that the high-affinity glycan ligands could facilitate lectin binding to other low-affinity glycan ligands, even though these low-affinity ligands are barely detectable in microarrays with immobilized glycan ligands. Such heteromultivalent binding processes significantly change lectin binding behaviors. We hypothesize that living organisms probably utilize this mechanism to regulate the downstream lectin functions. Our finding not only offers a mechanism to describe the concept that lectins are pattern recognition molecules, but also suggests that the two overlooked parameters, surface diffusion of glycan ligand and lectin binding kinetics, can play important roles in glycobiology processes. In this paper, we identified the critical parameters that influence the heteromultivalent binding process. We also discussed how our discovery can impact the current lectin-glycan analysis.

Multi-functional SERS substrate: collection, separation, and identification of airborne chemical powders on a single device.

Due to its extreme sensitivity and fingerprint specificity, surface enhanced Raman spectroscopy (SERS) is a powerful tool for substance identification. Developments in portable low-cost SERS substrates and handheld Raman spectrometers enable SERS analysis at sample origin, with great potential benefit to field-work applications in numerous disciplines. This study reports a procedure which incorporates sample collection, isolation, and SERS identification of airborne solids on a single inexpensive substrate. This procedure, vacuum filtration-paper chromatography-SERS (VF-PC-SERS), utilizes a porous filter paper decorated with plasmonic nanoparticles which we call nanopaper. The porous fiber structure facilitates both the vacuum filter powder capture and the isolation of components by paper chromatography, while the nanoplasmonic coating enhances Raman signal. One potentially high-impact application of VF-PC-SERS is field analysis of hazardous or illicit materials. This study demonstrates a proof-of-concept for VF-PC-SERS using powdered rhodamine 6G (R6G) dispersed in air, resulting in 100% detection accuracy (true positive rate) at R6G levels as low as 0.6 mg/m3. Analysis of R6G contaminated with topsoil or lactose resulted in specific identification of R6G in powder mixtures containing as little as 0.1 wt. % R6G. This study demonstrates the feasibility of VF-PC-SERS as a safer procedure to identify hazardous substances at the point of sample origin.

Beneficial mutations for carotenoid production identified from laboratory-evolved Saccharomyces cerevisiae.

Adaptive laboratory evolution (ALE) is a powerful tool used to increase strain fitness in the presence of environmental stressors. If production and strain fitness can be coupled, ALE can be used to increase product formation. In earlier work, carotenoids hyperproducing mutants were obtained using an ALE strategy. Here, de novo mutations were identified in hyperproducers, and reconstructed mutants were explored to determine the exact impact of each mutation on production and tolerance. A single mutation in YMRCTy1-3 conferred increased carotenoid production, and when combined with other beneficial mutations led to further increased ß-carotene production. Findings also suggest that the ALE strategy selected for mutations that confer increased carotenoid production as primary phenotype. Raman spectroscopy analysis and total lipid quantification revealed positive correlation between increased lipid content and increased ß-carotene production. Finally, we demonstrated that the best combinations of mutations identified for ß-carotene production were also beneficial for production of lycopene.

Quantitative surface-enhanced Raman spectroscopy for kinetic analysis of aldol condensation using Ag-Au core-shell nanocubes.

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool with high potential for multiplexed detection of dilute analytes. However, quantitative SERS of kinetic assays can be difficult due to the variation in enhancement factors caused by changing reaction conditions. We report a method for quantitative SERS kinetic analysis using colloidal Ag-Au core-shell nanocubes (Ag@AuNCs) as the SERS substrate. This substrate is mass producible, possesses large SERS enhancement, and is resistant to degradation in most environments. The SERS enhancement of the Ag@AuNCs was evaluated both experimentally and computationally. Quantitation was achieved by covalently attaching a non-reactive internal standard (IS) to substrate surfaces and normalizing SERS spectra to the IS signal. We demonstrated that IS normalization corrects for temporal variations in enhancement factor and particle concentration. Quantitation was demonstrated by monitoring the base-catalyzed aldol condensation of surface-bound 4-(methylthio)benzaldehyde with free acetone. The kinetic model of this reaction was fitted to IS normalized SERS data, resulting in kinetic parameters that agreed well with published values. This SERS platform is a robust and sensitive method for quantitative analysis of kinetic assays, with potential applications in many fields.

Membrane-protein binding measured with solution-phase plasmonic nanocube sensors.

We describe a solution-phase sensor of lipid-protein binding based on localized surface plasmon resonance (LSPR) of silver nanocubes. When silica-coated nanocubes are mixed in a suspension of lipid vesicles, supported membranes spontaneously assemble on their surfaces. Using a standard laboratory spectrophotometer, we calibrated the LSPR peak shift due to protein binding to the membrane surface and then characterized the lipid-binding specificity of a pleckstrin homology domain protein.

Characterization of dynamic actin associations with T-cell receptor microclusters in primary T cells.

T cell triggering through T-cell antigen receptors (TCRs) results in spatial assembly of the receptors on multiple length scales. This assembly is mediated by the T cell actin cytoskeleton, which reorganizes in response to TCR phosphorylation and then induces the coalescence of TCRs into microclusters, followed by their unification into a micrometer-scale structure. The exact outcomes of the association of TCRs with a dynamic and fluctuating actin network across these length scales are not well characterized, but it is clear that weak and transient interactions at the single-molecule level sum to yield significant receptor rearrangements at the plasma membrane. We used the hybrid live cell-nanopatterned supported lipid bilayer system to quantitatively probe the actin-TCR interaction in primary T cells. A specialized tracking algorithm revealed that actin slows as it passes over TCR clusters in a direction-dependent manner with respect to the resistance against TCR motion. We also observed transient actin enrichments at sites corresponding to putative TCR clusters that far exceeded pure stochastic fluctuations and described an image time-autocorrelation analysis method to quantify these accumulations.

Antibody-free detection of Mycobacterium tuberculosis antigen using customized nanotraps.

Rapid screening and diagnosis of tuberculosis disease (TB) is still challenging and critically needed for global TB control efforts. In this study, we present a rapid and streamlined technology, using precisely engineered silica nanopore thin films, which are optimized for pore size, structure, capillary force, and film thickness, to isolate Mycobacterium tuberculosis (MTB) antigens in laboratory and clinical samples for rapid TB screening. This technology, referred to here as on-chip fractionation, is integrated with high-throughput matrix-assisted laser desorption/ionization time-of flight mass spectrometry to screen and identify fragments of the MTB antigen, CFP-10, from complex biological samples, without use of immunoaffinity agents. With the use of this comprehensive approach, we were able to clearly distinguish a clinical isolate of MTB from a nonTB species of the genus Mycobacterium avium grown in liquid culture media. This assay can reach a detection limit of 10 fmol and an isolation rate of 90% for the antigen CFP-10. Our strategy has significant potential to fill the conceptual and technical gaps in rapid diagnosis of active TB disease.

Nanopore film based enrichment and quantification of low abundance hepcidin from human bodily fluids.

Endogenous peptides that represent biological and pathological information of disease have attracted interest for diagnosis. However, the extraction of those low abundance peptides is still a challenge because of the complexity of human bodily fluids (HBF). Hepcidin, a peptide hormone, has been recognized as a biomarker for iron-related diseases. There is no rapid and reliable way to enrich them from HBF. Here we describe a peptide extraction approach based on nanoporous silica thin films to successfully detect hepcidin from HBF. Cooperative functions of nanopore to biomolecule, including capillary adsorption, size-exclusion and electrostatic interaction, were systematically investigated to immobilize the target peptide. To promote this new approach to clinical practices, we further applied it to successfully assay the hepcidin levels in HBF provided by healthy volunteers and patients suffering from inflammation. Our finding provides a high-throughput, rapid, label-free and cost-effective detection method for capturing and quantifying low abundance peptides from HBF. FROM THE CLINICAL EDITOR: Diagnosing diseases with low concentration peptide biomarkers remains challenging. This team of authors describes a peptide extraction approach based on nanoporous silica thin films to successfully detect low concentrations of hepcidin from human body fluids collected from 119 healthy volunteers and 19 inflammation patients.

Direct Glycan Analysis of Biological Samples and Intact Glycoproteins by Integrating Machine Learning-Driven Surface-Enhanced Raman Scattering and Boronic Acid Arrays.

Frequent monitoring of glycan patterns is a critical step in studying glycan-mediated cellular processes. However, the current glycan analysis tools are resource-intensive and less suitable for routine use in standard laboratories. We developed a novel glycan detection platform by integrating surface-enhanced Raman spectroscopy (SERS), boronic acid (BA) receptors, and machine learning tools. This sensor monitors the molecular fingerprint spectra of BA binding to cis-diol-containing glycans. Different types of BA receptors could yield different stereoselective reactions toward different glycans and exhibit unique vibrational spectra. By integration of the Raman spectra collected from different BA receptors, the structural information can be enriched, eventually improving the accuracy of glycan classification and quantification. Here, we established a SERS-based sensor incorporating multiple different BA receptors. This sensing platform could directly analyze the biological samples, including whole milk and intact glycoproteins (fetuin and asialofetuin), without tedious glycan release and purification steps. The results demonstrate the platform's ability to classify milk oligosaccharides with remarkable classification accuracy, despite the presence of other non-glycan constituents in the background. This sensor could also directly quantify sialylation levels of a fetuin/asialofetuin mixture without glycan release procedures. Moreover, by selecting appropriate BA receptors, the sensor exhibits an excellent performance of differentiating between α2,3 and α2,6 linkages of sialic acids. This low-cost, rapid, and highly accessible sensor will provide the scientific community with an invaluable tool for routine glycan screening in standard laboratories.

Factors Promoting Lipopolysaccharide Uptake by Synthetic Lipid Droplets.

Lipoproteins are essential in removing lipopolysaccharide (LPS) from blood during bacterial inflammation. The physicochemical properties of lipoproteins and environmental factors can impact LPS uptake. In this work, synthetic lipid droplets containing triglycerides, cholesterols, and phospholipids, were prepared to mimic lipoproteins. The physicochemical properties of these lipid droplets, such as charges, sizes, and lipid compositions, were altered to understand the underlying factors affecting LPS uptake. The amphiphilic LPS could spontaneously adsorb on the surface of lipid droplets without lipopolysaccharide binding protein (LBP); however, the presence of LBP can increase LPS uptake. The positively charged lipid droplets also enhance the uptake of negatively charged LPS. Most interestingly, the LPS uptake highly depends on the concentrations of Ca2+ near the physiological conditions, but the impact of Mg2+ ions was not significant. The increase of Ca2+ ions can improve LPS uptake by lipid droplets; this result suggested that Ca2+ may play an essential role in LPS clearance. Since septic shock patients typically suffer from hypocalcemia and low levels of lipoproteins, the supplementation of Ca2+ ions along with synthetic lipoproteins may be a potential treatment for severe sepsis.

Quantum-Enhanced Detection of Viral cDNA via Luminescence Resonance Energy Transfer Using Upconversion and Gold Nanoparticles.

The COVID-19 pandemic has profoundly impacted global economies and healthcare systems, revealing critical vulnerabilities in both. In response, our study introduces a groundbreaking method for the detection of SARS-CoV-2 cDNA, leveraging Luminescence resonance energy transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs) to achieve an unprecedented detection limit of 242 femtomolar (fM). This innovative sensing platform utilizes UCNPs conjugated with one primer and AuNPs with another, targeting the 5' and 3' ends of the SARS-CoV-2 cDNA, respectively, enabling precise differentiation of mismatched DNA sequences and significantly enhancing detection specificity. Through rigorous experimental analysis, we established a quenching efficiency range from 10.4\% to 73.6\%, with an optimal midpoint of 42\%, thereby demonstrating the superior sensitivity of our method. By comparing the quenching efficiency of mismatched DNAs to the target DNA, we identified an optimal DNA:UCNP:AuNP ratio that ensures accurate detection. Our comparative analysis with existing SARS-CoV-2 detection methods revealed that our approach not only provides a lower detection limit but also offers higher specificity and potential for rapid, on-site testing. This study demonstrates the superior sensitivity and specificity of using UCNPs and AuNPs for SARS-CoV-2 cDNA detection, offering a significant advancement in rapid, accessible diagnostic technologies. Our method, characterized by its low detection limit and high precision, represents a critical step forward in managing current and future viral outbreaks, contributing to the enhancement of global healthcare responsiveness and infectious disease control.

Template-assisted assembly: scanning tunneling microscopy study of solvent-dependent adlattices of alkyl-derivatized tetrathiafulvalene.

The self-assembly of an adsorbate as a function of the strength of solvent-substrate adsorption is an important yet relatively unexplored subject. In this study, how the strength of solvent-substrate adsorption and solvent-solvent attraction affects the assembly of tetrakis(octadecylthio)tetrathiafulvalene (1) is scrutinized by scanning tunneling microscopy (STM). For solvents with strong intermolecular interactions and adsorption onto graphite, such as long n-alkanes (C(n)H(2n+2), n ≥ 13), STM reveals that the solvent molecules form lamellae which become a template to direct the assembly of 1 into one-dimensional arrays. The lengths of one of the unit cell vectors for the assemblies are increased and well correlated with the solvent sizes. In situ STM monitoring of 1 introduced onto graphite with preadsorbed n-tetradecane adlattices shows that the developed assemblies of 1 have striped features aligned parallel to the underlying template. In contrast, for solvents with weak adsorption, such as short n-alkanes (C(n)H(2n+2), n ≤ 12), toluene, and 1,2,4-trichlorobenzene, the adlattice structures of 1 are solvent-independent.

Double stranded polymeric ladderphanes with 16-π-electron antiaromatic metallocycle linkers.

Three double stranded polymeric ladderphanes with 16-π-electron antiaromatic metallocycle linkers are synthesised by ring opening metathesis polymerisation of the corresponding bisnorbornene monomers. Scanning tunnelling microscopic (STM) images indicate that these polymers can assemble nicely on a graphite surface to form a highly ordered pattern which has been observed in other ladderphanes with different kinds of aromatic linkers. Little change in (1)H NMR, absorption spectra and electrochemical oxidation potential between these polymers and the corresponding monomers suggest that there would be no interactions between adjacent antiaromatic linkers in these polymeric ladderphanes. Presumably, the distance between two antiaromatic rings in these ladderphanes (5-6 Å) is far too long in comparison with that between two rings in methylene-bridged antiaromatic superphanes (2.5 Å<), where stabilisation is predicted by theoretical calculations.

Nanocube-Based Fluidic Glycan Array.

The nature of cell membrane fluidity permits glycans, which are attached to membrane proteins and lipids, to freely diffuse on cell surfaces. Through such two-dimensional motion, some weakly binding glycans can participate in lectin binding processes, eventually changing lectin binding behaviors. This chapter discusses a plasmonic nanocube sensor that allows users to detect lectin binding kinetics in a cell membrane mimicking environment. This assay only requires standard laboratory spectrometers, including microplate readers. We describe the basics of the technology in detail, including sensor fabrication, sensor calibration, data processing, a general protocol for detecting lectin-glycan interactions, and a troubleshooting guide.

Integration of surface-enhanced Raman spectroscopy (SERS) and machine learning tools for coffee beverage classification.

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for molecule identification. However, profiling complex samples remains a challenge because SERS peaks are likely to overlap, confounding features when multiple analytes are present in a single sample. In addition, SERS often suffers from high variability in signal enhancement due to nonuniform SERS substrate. The machine learning classification techniques widely used for facial recognition are excellent tools to overcome the complexity of SERS data interpretation. Herein, we reported a sensor for classifying coffee beverages by integrating SERS, feature extractions, and machine learning classifiers. A versatile and low-cost SERS substrate, called nanopaper, was used to enhance Raman signals of dilute compounds in coffee beverages. Two classic multivariate analysis techniques, Principal Component Analysis (PCA) and Discriminant Analysis of Principal Components (DAPC), were used to extract the significant spectral features, and the performance of various machine learning classifiers was evaluated. The combination of DAPC with Support Vector Machine (SVM) or K-Nearest Neighbor (KNN) shows the best performance for classifying coffee beverages. This user-friendly and versatile sensor has the potential to be a practical quality-control tool for the food industry.

Recent Developments in Drug Delivery for Treatment of Tuberculosis by Targeting Macrophages.

Tuberculosis (TB) is among the greatest public health and safety concerns in the 21st century, Mycobacterium tuberculosis, which causes TB, infects alveolar macrophages and uses these cells as one of its primary sites of replication. The current TB treatment regimen, which consist of chemotherapy involving a combination of 3-4 antimicrobials for a duration of 6-12 months, is marked with significant side effects, toxicity, and poor compliance. Targeted drug delivery offers a strategy that could overcome many of the problems of current TB treatment by specifically targeting infected macrophages. Recent advances in nanotechnology and material science have opened an avenue to explore drug carriers that actively and passively target macrophages. This approach can increase the drug penetration into macrophages by using ligands on the nanocarrier that interact with specific receptors for macrophages. This review encompasses the recent development of drug carriers specifically targeting macrophages actively and passively. Future directions and challenges associated with development of effective TB treatment is also discussed.

Quantum optical immunoassay: upconversion nanoparticle-based neutralizing assay for COVID-19.

In a viral pandemic, a few important tests are required for successful containment of the virus and reduction in severity of the infection. Among those tests, a test for the neutralizing ability of an antibody is crucial for assessment of population immunity gained through vaccination, and to test therapeutic value of antibodies made to counter the infections. Here, we report a sensitive technique to detect the relative neutralizing strength of various antibodies against the SARS-CoV-2 virus. We used bright, photostable, background-free, fluorescent upconversion nanoparticles conjugated with SARS-CoV-2 receptor binding domain as a phantom virion. A glass bottom plate coated with angiotensin-converting enzyme 2 (ACE-2) protein imitates the target cells. When no neutralizing IgG antibody was present in the sample, the particles would bind to the ACE-2 with high affinity. In contrast, a neutralizing antibody can prevent particle attachment to the ACE-2-coated substrate. A prototype system consisting of a custom-made confocal microscope was used to quantify particle attachment to the substrate. The sensitivity of this assay can reach 4.0 ng/ml and the dynamic range is from 1.0 ng/ml to 3.2 [Formula: see text]g/ml. This is to be compared to 19 ng/ml sensitivity of commercially available kits.