During heat stress in Myxococcus xanthus, the CdbS PilZ domain protein, in concert with two PilZ-DnaK chaperones, perturbs chromosome organization and accelerates cell death.

C-di-GMP is a bacterial second messenger that regulates diverse processes in response to environmental or cellular cues. The nucleoid-associated protein (NAP) CdbA in Myxococcus xanthus binds c-di-GMP and DNA in a mutually exclusive manner in vitro. CdbA is essential for viability, and CdbA depletion causes defects in chromosome organization, leading to a block in cell division and, ultimately, cell death. Most NAPs are not essential; therefore, to explore the paradoxical cdbA essentiality, we isolated suppressor mutations that restored cell viability without CdbA. Most mutations mapped to cdbS, which encodes a stand-alone c-di-GMP binding PilZ domain protein, and caused loss-of-function of cdbS. Cells lacking CdbA and CdbS or only CdbS were fully viable and had no defects in chromosome organization. CdbA depletion caused post-transcriptional upregulation of CdbS accumulation, and this CdbS over-accumulation was sufficient to disrupt chromosome organization and cause cell death. CdbA depletion also caused increased accumulation of CsdK1 and CsdK2, two unusual PilZ-DnaK chaperones. During CdbA depletion, CsdK1 and CsdK2, in turn, enabled the increased accumulation and toxicity of CdbS, likely by stabilizing CdbS. Moreover, we demonstrate that heat stress, possibly involving an increased cellular c-di-GMP concentration, induced the CdbA/CsdK1/CsdK2/CdbS system, causing a CsdK1- and CsdK2-dependent increase in CdbS accumulation. Thereby this system accelerates heat stress-induced chromosome mis-organization and cell death. Collectively, this work describes a unique system that contributes to regulated cell death in M. xanthus and suggests a link between c-di-GMP signaling and regulated cell death in bacteria.

Novel sulfur isotope analyses constrain sulfurized porewater fluxes as a minor component of marine dissolved organic matter.

Marine dissolved organic matter (DOM) is a major reservoir that links global carbon, nitrogen, and phosphorus. DOM is also important for marine sulfur biogeochemistry as the largest water column reservoir of organic sulfur. Dissolved organic sulfur (DOS) can originate from phytoplankton-derived biomolecules in the surface ocean or from abiotically "sulfurized" organic matter diffusing from sulfidic sediments. These sources differ in 34S/32S isotope ratios (δ34S values), with phytoplankton-produced DOS tracking marine sulfate (21‰) and sulfurized DOS mirroring sedimentary porewater sulfide (∼0 to -10‰). We measured the δ34S values of solid-phase extracted (SPE) DOM from marine water columns and porewater from sulfidic sediments. Marine DOMSPE δ34S values ranged from 14.9‰ to 19.9‰ and C:S ratios from 153 to 303, with lower δ34S values corresponding to higher C:S ratios. Marine DOMSPE samples showed consistent trends with depth: δ34S values decreased, C:S ratios increased, and δ13C values were constant. Porewater DOMSPE was 34S-depleted (∼-0.6‰) and sulfur-rich (C:S ∼37) compared with water column samples. We interpret these trends as reflecting at most 20% (and on average ∼8%) contribution of abiotic sulfurized sources to marine DOSSPE and conclude that sulfurized porewater is not a main component of oceanic DOS and DOM. We hypothesize that heterogeneity in δ34S values and C:S ratios reflects the combination of sulfurized porewater inputs and preferential microbial scavenging of sulfur relative to carbon without isotope fractionation. Our findings strengthen links between oceanic sulfur and carbon cycling, supporting a realization that organic sulfur, not just sulfate, is important to marine biogeochemistry.

Standard addition method for rapid, cultivation-independent quantification of Legionella pneumophila cells by qPCR in biotrickling filters.

Cultivation-independent molecular biological methods are essential to rapidly quantify pathogens like Legionella pneumophila (L. pneumophila) which is important to control aerosol-generating engineered water systems. A standard addition method was established to quantify L. pneumophila in the very complex matrix of process water and air of exhaust air purification systems in animal husbandry. Therefore, cryopreserved standards of viable L. pneumophila were spiked in air and water samples to calibrate the total bioanalytical process which includes cell lysis, DNA extraction, and qPCR. A standard addition algorithm was employed for qPCR to determine the initial concentration of L. pneumophila. In mineral water, the recovery rate of this approach (73%-134% within the concentration range of 100-5000 Legionella per mL) was in good agreement with numbers obtained from conventional genomic unit (GU) calibration with DNA standards. In air samples of biotrickling filters, in contrast, the conventional DNA standard approach resulted in a significant overestimation of up to 729%, whereas our standard addition gave a more realistic recovery of 131%. With this proof-of-principle study, we were able to show that the molecular biology-based standard addition approach is a suitable method to determine realistic concentrations of L. pneumophila in air and process water samples of biotrickling filter systems. Moreover, this quantification strategy is generally a promising method to quantify pathogens in challenging samples containing a complex microbiota and the classical GU approach used for qPCR leads to unreliable results.

Intermediate Field Coupling of Single Epitaxial Quantum Dots to Plasmonic Waveguides.

Key requirements for quantum plasmonic nanocircuits are reliable single-photon sources, high coupling efficiency to the plasmonic structures, and low propagation losses. Self-assembled epitaxially grown GaAs quantum dots are close to ideal as stable, bright, and narrowband single-photon emitters. Likewise, wet-chemically grown monocrystalline silver nanowires are among the best plasmonic waveguides. However, large propagation losses of surface plasmons on the high-index GaAs substrate prevent their direct combination. Here, we show by experiment and simulation that the best overall performance of the quantum plasmonic nanocircuit based on these building blocks is achieved in the intermediate field regime with an additional spacer layer between the quantum dot and the plasmonic waveguide. High-resolution cathodoluminescence measurements allow a precise determination of the coupling distance and support a simple analytical model to explain the overall performance. The coupling efficiency is increased up to four times by standing wave interference near the end of the waveguide.

Immunomagnetic separation coupled with flow cytometry for the analysis of Legionella pneumophila in aerosols.

Legionella pneumophila are pathogenic bacteria that can be found in high concentrations in artificial water systems like evaporative cooling towers, which have been the source of frequent outbreaks in recent years. Since inhaled L. pneumophila can lead to Legionnaires' disease, the development of suitable sampling and rapid analysis strategies for these bacteria in aerosols is therefore of great relevance. In this work, different concentrations of viable L. pneumophila Sg 1 were nebulized and sampled by the cyclone sampler Coriolis® µ under defined conditions in a bioaerosol chamber. To quantify intact Legionella cells, the collected bioaerosols were subsequently analyzed by immunomagnetic separation coupled with flow cytometry (IMS-FCM) on the platform rqmicro.COUNT. For analytical comparison, measurements with qPCR and cultivation were performed. Limits of detection (LOD) of 2.9 × 103 intact cells m-3 for IMS-FCM and 7.8 × 102 intact cells m-3 for qPCR indicating a comparable sensitivity as in culture (LOD = 1.5 × 103 culturable cells m-3). Over a working range of 103 - 106 cells mL-1, the analysis of nebulized and collected aerosol samples with IMS-FCM and qPCR provides higher recovery rates and more consistent results than by cultivation. Overall, IMS-FCM is a suitable culture-independent method for quantification of L. pneumophila in bioaerosols and is promising for field application due to its simplicity in sample preparation.

Automated detection of neutralizing SARS-CoV-2 antibodies in minutes using a competitive chemiluminescence immunoassay.

The SARS-CoV-2 pandemic has shown the importance of rapid and comprehensive diagnostic tools. While there are numerous rapid antigen tests available, rapid serological assays for the detection of neutralizing antibodies are and will be needed to determine not only the amount of antibodies formed after infection or vaccination but also their neutralizing potential, preventing the cell entry of SARS-CoV-2. Current active-virus neutralization assays require biosafety level 3 facilities, while virus-free surrogate assays are more versatile in applications, but still take typically several hours until results are available. To overcome these disadvantages, we developed a competitive chemiluminescence immunoassay that enables the detection of neutralizing SARS-CoV-2 antibodies within 7 min. The neutralizing antibodies bind to the viral receptor binding domain (RBD) and inhibit the binding to the human angiotensin-converting enzyme 2 (ACE2) receptor. This competitive binding inhibition test was characterized with a set of 80 samples, which could all be classified correctly. The assay results favorably compare to those obtained with a more time-intensive ELISA-based neutralization test and a commercial surrogate neutralization assay. Our test could further be used to detect individuals with a high total IgG antibody titer, but only a low neutralizing titer, as well as for monitoring neutralizing antibodies after vaccinations. This effective performance in SARS-CoV-2 seromonitoring delineates the potential for the test to be adapted to other diseases in the future.

Evaluation of Mid-Infrared and X-ray Fluorescence Data Fusion Approaches for Prediction of Soil Properties at the Field Scale.

Previous studies investigating multi-sensor fusion for the collection of soil information have shown variable improvements, and the underlying prediction mechanisms are not sufficiently understood for spectrally-active and -inactive properties. Our objective was to study prediction mechanisms and benefits of model fusion by measuring mid-infrared (MIR) and X-ray fluorescence (XRF) spectra, texture, total and labile organic carbon (OC) and nitrogen (N) content, pH, and cation exchange capacity (CEC) for n = 117 soils from an arable field in Germany. Partial least squares regression models underwent a three-fold training/testing procedure using MIR spectra or elemental concentrations derived from XRF spectra. Additionally, two sequential hybrid and two high-level fusion approaches were tested. For the studied field, MIR was superior for organic properties (ratio of prediction to interquartile distance of validation (RPIQV) for total OC = 7.7 and N = 5.0)), while XRF was superior for inorganic properties (RPIQV for clay = 3.4, silt = 3.0, and sand = 1.8). Even the optimal fusion approach brought little to no accuracy improvement for these properties. The high XRF accuracy for clay and silt is explained by the large number of elements with variable importance in the projection scores >1 (Fe ≈ Ni > Si ≈ Al ≈ Mg > Mn ≈ K ≈ Pb (clay only) ≈ Cr) with strong spearman correlations (±0.57 < rs < ±0.90) with clay and silt. For spectrally-inactive properties relying on indirect prediction mechanisms, the relative improvements from the optimal fusion approach compared to the best single spectrometer were marginal for pH (3.2% increase in RPIQV versus MIR alone) but more pronounced for labile OC (9.3% versus MIR) and CEC (12% versus XRF). Dominance of a suboptimal spectrometer in a fusion approach worsened performance compared to the best single spectrometer. Granger-Ramanathan averaging, which weights predictions according to accuracy in training, is therefore recommended as a robust approach to capturing the potential benefits of multiple sensors.

Macroporous Epoxy-Based Monoliths Functionalized with Anti-CD63 Nanobodies for Effective Isolation of Extracellular Vesicles in Urine.

Extracellular vesicles (EVs) have enormous potential for the implementation of liquid biopsy and as effective drug delivery means, but the fulfilment of these expectations requires overcoming at least two bottlenecks relative to their purification, namely the finalization of reliable and affordable protocols for: (i) EV sub-population selective isolation and (ii) the scalability of their production/isolation from complex biological fluids. In this work, we demonstrated that these objectives can be achieved by a conceptually new affinity chromatography platform composed of a macroporous epoxy monolith matrix functionalized with anti-CD63 nanobodies with afflux of samples and buffers regulated through a pump. Such a system successfully captured and released integral EVs from urine samples and showed negligible unspecific binding for circulating proteins. Additionally, size discrimination of eluted EVs was achieved by different elution approaches (competitive versus pH-dependent). The physical characteristics of monolith material and the inexpensive production of recombinant nanobodies make scaling-up the capture unit feasible and affordable. Additionally, the availability of nanobodies for further specific EV biomarkers will allow for the preparation of monolithic affinity filters selective for different EV subclasses.

Fully Automated Chemiluminescence Microarray Analysis Platform for Rapid and Multiplexed SARS-CoV-2 Serodiagnostics.

Lateral-flow immunoassays and laboratory diagnostic tests like enzyme-linked immunosorbent assays (ELISAs) are powerful diagnostic tools to help fight the COVID-19 pandemic using them as antigen or antibody tests. However, the need emerges for alternative bioanalytical systems that combine their favorable features─simple, rapid, and cost-efficient point-of-care (POC) analysis of lateral-flow immunoassays and higher reliability of laboratory tests─while eliminating their disadvantages (limited sensitivity and specificity of lateral-flow assays and prolonged time and work expenditure of laboratory analysis). An additional need met by only a few tests is multiplexing, allowing for the analysis of several immunorecognition patterns at the same time. We herein present a strategy to combine all desirable attributes of the different test types by means of a flow-based chemiluminescence microarray immunoassay. Laminated polycarbonate microarray chips were developed for easy production and subsequent application in the fully automated microarray analysis platform MCR-R, where a novel flow cell design minimizes the sample volume to 40 µL. This system was capable of detecting IgG antibodies to SARS-CoV-2 with 100% sensitivity and specificity using recombinant antigens for the SARS-CoV-2 spike S1 protein, nucleocapsid protein, and receptor binding domain. The analysis was accomplished within under 4 min from serum, plasma, and whole blood, making it also useful in POC settings. Additionally, we showed the possibility of serosurveillance after infection or vaccination to monitor formerly unnoticed breakthrough infections in the population as well as to detect the need for booster vaccination after the natural decline of the antibody titer below detectable levels. This will help in answering pressing questions on the importance of the antibody response to SARS-CoV-2 that so far remain open. Additionally, even the sequential detection of IgM and IgG antibodies was possible, allowing for statements on the time response of an infection. While our serodiagnostic application focuses on SARS-CoV-2, the same approach is easily adjusted to other diseases, making it a powerful tool for future serological testing.

Natural Asphalt Seeps Are Potential Sources for Recalcitrant Oceanic Dissolved Organic Sulfur and Dissolved Black Carbon.

Natural oil seepages contribute about one-half of the annual petroleum input to marine systems. Yet, environmental implications and the persistence of water-soluble hydrocarbons from these seeps are vastly unknown. We investigated the release of oil-derived dissolved organic matter (DOM) from natural deep sea asphalt seeps using laboratory incubation experiments. Fresh asphalt samples collected at the Chapopote asphalt volcano in the Southern Gulf of Mexico were incubated aerobically in artificial seawater over 4 weeks. The compositional changes in the water-soluble fraction of asphalt-derived DOM were determined with ultrahigh-resolution mass spectrometry (Fourier-transform ion cyclotron resonance mass spectrometry, FT-ICR-MS) and by excitation-emission matrix spectroscopy to characterize fluorescent DOM (FDOM) applying parallel factor (PARAFAC) analysis. Highly reduced aliphatic asphalt-derived DOM was readily biodegraded, while aromatic and sulfur-enriched DOM appeared to be less bioavailable and accumulated in the aqueous phase. A quantitative molecular tracer approach revealed the abundance of highly condensed aromatic molecules of thermogenic origin. Our results indicate that natural asphalt and potentially other petroleum seepages can be sources of recalcitrant dissolved organic sulfur and dissolved black carbon to the ocean.

Marine Dissolved Organic Matter Shares Thousands of Molecular Formulae Yet Differs Structurally across Major Water Masses.

Most oceanic dissolved organic matter (DOM) is still not fully molecularly characterized. We combined high-field nuclear magnetic resonance (NMR) and ultrahigh-resolution mass spectrometry (Fourier-transform ion cyclotron resonance mass spectrometry, FT-ICR-MS) for the structural and molecular formula-level characterization of solid-phase extracted (SPE) DOM from surface, mesopelagic, and bathypelagic Atlantic and Pacific Ocean samples. Using a MicroCryoProbe, unprecedented low amounts of SPE-DOM (∼1 mg carbon) were sufficient for two-dimensional NMR analysis. Low proportions of olefinic and aromatic relative to aliphatic and carboxylated structures (NMR) at the sea surface were likely related to photochemical transformations. This was consistent with lower molecular masses and higher degrees of saturation and oxygenation (FT-ICR-MS) compared to those of the deep sea. Carbohydrate structures in the mesopelagic North Pacific Ocean suggest export and release from sinking particles. In our sample set, the universal molecular DOM composition, as captured by FT-ICR-MS, appears to be structurally more diverse when analyzed by NMR, suggesting DOM variability across oceanic provinces to be more pronounced than previously assumed. As a proof of concept, our study takes advantage of new complementary approaches resolving thousands of structural and molecular DOM features while applying reasonable instrument times, allowing for the analysis of large oceanic data sets to increase our understanding of marine DOM biogeochemistry.

Microfluidic flow-injection aptamer-based chemiluminescence platform for sulfadimethoxine detection.

Gold nanoparticle-catalyzed chemiluminescence (CL) of luminol is an attractive alternative to strategies relying on enzymes, as their aggregation leads to significantly enhanced CL signals. Consequently, analytes disturbing such aggregation will lead to an easy-to-quantify weakening of the signal. Based on this concept, a homogeneous aptamer-based assay for the detection of sulfadimethoxine (SDM) has been developed as a microfluidic CL flow-injection platform. Here, the efficient mixing of gold nanoparticles, aptamers, and analyte in short channel distances is of utmost importance, and two-dimensional (2D) and three-dimensional (3D) mixer designs made via Xurography were investigated. In the end, since 2D designs could not provide sufficient mixing, a laminated 3D 5-layer microfluidic mixer was developed and optimized with respect to mixing capability and observation by the charge-coupled device (CCD) camera. Furthermore, the performance of standard luminol and its more hydrophilic derivative m-carboxy luminol was studied identifying the hydrophilic derivative to provide tenfold more signal enhancement and reliable results. Finally, the novel detection platform was used for the specific detection of SDM via its aptamer and yielded a stunning dynamic range over 5 orders of magnitude (0.01-1000 ng/ml) and a limit of detection of 4 pg/ml. This new detection concept not only outperforms other methods for SDM detection, but can be suggested as a new flow-injection strategy for aptamer-based rapid and cost-efficient analysis in environmental monitoring and food safety.

Flow-Based Chemiluminescence Microarrays as Screening Platform for Affinity Binders to Capture and Elute Bacteria.

Affinity describes the non-covalent but selective interaction between an affinity binder (e.g., proteins, antibiotics, or antibodies) and its counterpart (e.g., bacteria). These affinity binders can serve to detect bacteria and respond to the need for selective concentration via affinity chromatography for trace analysis. By changing the pH value or salt and protein contents, affinity bindings can be reversed, and bacteria can be recovered for characterisation. Analytical microarrays use multiple affinity binders immobilised on the surface in a distinct pattern, which immensely reduces screening time for the discovery of superior binding motifs. Here, flow-based microarray systems can inform not only about binding, but also about desorption. In this work, we pioneer a screening assay for affinity binders against both gram-positive and negative bacteria based on an automated flow-based chemiluminescence (CL) microarray. Biotinylation of model organisms E. coli and E. faecalis enabled labelling with horseradish-peroxidase-coupled streptavidin, and detection with CL. Polymyxin B, an antibiotic against gram-negative bacteria, was found to bind both E. coli and E. faecalis. Simultaneous screening for desorption methods unexpectedly revealed methyl alpha-D-mannopyranoside as a promising buffer for desorption from Polymyxin B. This proof-of-principle study shows that our new platform greatly facilitates the screening of new affinity binders against bacteria, with promise for future automation.

Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling.

Soil spectroscopy in the visible-to-near infrared (VNIR) and mid-infrared (MIR) is a cost-effective method to determine the soil organic carbon content (SOC) based on predictive spectral models calibrated to analytical-determined SOC reference data. The degree to which uncertainty in reference data and spectral measurements contributes to the estimated accuracy of VNIR and MIR predictions, however, is rarely addressed and remains unclear, in particular for current handheld MIR spectrometers. We thus evaluated the reproducibility of both the spectral reflectance measurements with portable VNIR and MIR spectrometers and the analytical dry combustion SOC reference method, with the aim to assess how varying spectral inputs and reference values impact the calibration and validation of predictive VNIR and MIR models. Soil reflectance spectra and SOC were measured in triplicate, the latter by different laboratories, for a set of 75 finely ground soil samples covering a wide range of parent materials and SOC contents. Predictive partial least-squares regression (PLSR) models were evaluated in a repeated, nested cross-validation approach with systematically varied spectral inputs and reference data, respectively. We found that SOC predictions from both VNIR and MIR spectra were equally highly reproducible on average and similar to the dry combustion method, but MIR spectra were more robust to calibration sample variation. The contributions of spectral variation (ΔRMSE < 0.4 g·kg−1) and reference SOC uncertainty (ΔRMSE < 0.3 g·kg−1) to spectral modeling errors were small compared to the difference between the VNIR and MIR spectral ranges (ΔRMSE ~1.4 g·kg−1 in favor of MIR). For reference SOC, uncertainty was limited to the case of biased reference data appearing in either the calibration or validation. Given better predictive accuracy, comparable spectral reproducibility and greater robustness against calibration sample selection, the portable MIR spectrometer was considered overall superior to the VNIR instrument for SOC analysis. Our results further indicate that random errors in SOC reference values are effectively compensated for during model calibration, while biased SOC calibration data propagates errors into model predictions. Reference data uncertainty is thus more likely to negatively impact the estimated validation accuracy in soil spectroscopy studies where archived data, e.g., from soil spectral libraries, are used for model building, but it should be negligible otherwise.

Two novel XRE-like transcriptional regulators control phenotypic heterogeneity in Photorhabdus luminescens cell populations.

BACKGROUND: The insect pathogenic bacterium Photorhabdus luminescens exists in two phenotypically different forms, designated as primary (1°) and secondary (2°) cells. Upon yet unknown environmental stimuli up to 50% of the 1° cells convert to 2° cells. Among others, one important difference between the phenotypic forms is that 2° cells are unable to live in symbiosis with their partner nematodes, and therefore are not able to re-associate with them. As 100% switching of 1° to 2° cells of the population would lead to a break-down of the bacteria's life cycle the switching process must be tightly controlled. However, the regulation mechanism of phenotypic switching is still puzzling. RESULTS: Here we describe two novel XRE family transcriptional regulators, XreR1 and XreR2, that play a major role in the phenotypic switching process of P. luminescens. Deletion of xreR1 in 1° or xreR2 in 2° cells as well as insertion of extra copies of xreR1 into 2° or xreR2 into 1° cells, respectively, induced the opposite phenotype in either 1° or 2° cells. Furthermore, both regulators specifically bind to different promoter regions putatively fulfilling a positive autoregulation. We found initial evidence that XreR1 and XreR2 constitute an epigenetic switch, whereby XreR1 represses xreR2 expression and XreR2 self-reinforces its own gene by binding to XreR1. CONCLUSION: Regulation of gene expression by the two novel XRE-type regulators XreR1 and XreR2 as well as their interplay represents a major regulatory process in phenotypic switching of P. luminescens. A fine-tuning balance between both regulators might therefore define the fate of single cells to convert from the 1° to the 2° phenotype.

A chemiluminescence-based heterogeneous asymmetric recombinase polymerase amplification assay for the molecular detection of mycotoxin producers.

The analysis of mold in indoor air is a prominent topic but it is hardly dealt with. The most affected fields of this issue are residential- and occupational safety since mold can have a number of impacts on human health. To date the most used methods for quantification of microorganism contamination in indoor air are culture- or microscopy-based and are not capable of translating the on-site situation to analytical data reliably. Here we present a chemiluminescence-based method to detect mycotoxin producers through isothermal amplification of mycotoxin biosynthesis genes using glass and polycarbonate carriers. In this proof-of-principle study, zearalenone producers were aimed to be detected by heterogeneous asymmetric recombinase polymerase amplification (haRPA). For this, an appropriate lysis method for fungal spores was developed allowing rapid access to DNA. A system calibration with spores of Fusarium culmorum as zearalenone-producing organism resulted in an LOD of 2.7 × 105 spores per ml. The system was shown to be specific for zearalenone producers. This work presents the first application of a heterogeneous isothermal amplification for rapid detection and quantification of mycotoxin producers. In the future, a multiplex detection can be possible by haRPA.

Automated, flow-based chemiluminescence microarray immunoassay for the rapid multiplex detection of IgG antibodies to SARS-CoV-2 in human serum and plasma (CoVRapid CL-MIA).

In the face of the COVID-19 pandemic, the need for rapid serological tests that allow multiplexing emerged, as antibody seropositivity can instruct about individual immunity after an infection with SARS-CoV-2 or after vaccination. As many commercial antibody tests are either time-consuming or tend to produce false negative or false positive results when only one antigen is considered, we developed an automated, flow-based chemiluminescence microarray immunoassay (CL-MIA) that allows for the detection of IgG antibodies to SARS-CoV-2 receptor-binding domain (RBD), spike protein (S1 fragment), and nucleocapsid protein (N) in human serum and plasma in less than 8 min. The CoVRapid CL-MIA was tested with a set of 65 SARS-CoV-2 serology positive or negative samples, resulting in 100% diagnostic specificity and 100% diagnostic sensitivity, thus even outcompeting commercial tests run on the same sample set. Additionally, the prospect of future quantitative assessments (i.e., quantifying the level of antibodies) was demonstrated. Due to the fully automated process, the test can easily be operated in hospitals, medical practices, or vaccination centers, offering a valuable tool for COVID-19 serosurveillance. Graphical abstract.

Integration of 3D Hydrodynamic Focused Microreactor with Microfluidic Chemiluminescence Sensing for Online Synthesis and Catalytical Characterization of Gold Nanoparticles.

Chemiluminescence assays have shown great advantages compared with other optical techniques. Gold nanoparticles have drawn much attention in chemiluminescence analysis systems as an enzyme-free catalyst. The catalytic activity of gold nanoparticles for chemiluminescence sensing depends on size, shape and the surface charge property, which is hard to characterize in batches. As there is no positive or negative correlation between chemiluminescence signals and sizes of gold nanoparticles, the best way to get optimal gold nanoparticles is to control the reaction conditions via online chemiluminescence sensing systems. Therefore, a new method was developed for online synthesis of gold nanoparticles with a three-dimension hydrodynamic focusing microreactor, directly coupled with a microfluidic chemiluminescence sensing chip, which was coupled to a charge-coupled device camera for direct catalytical characterization of gold nanoparticles. All operations were performed in an automatic way with a program controlled by Matlab. Gold nanoparticles were synthesized through a single-phase reaction using glucose as a reducing agent and stabilizer at room temperature. The property of gold nanoparticles was easily controlled with the three-dimension microreactor during synthesis. The catalyst property of synthesized gold nanoparticles was characterized in a luminol-NaOCl chemiluminescence system. After optimizing parameters of synthesis, the chemiluminescence signal was enhanced to a factor of 171. The gold nanoparticles synthesized under optimal conditions for the luminol-NaOCl system were stable for at least one month. To further investigate the catalytic activity of synthesized gold nanoparticles in various situations, two methods were used to change the property of gold nanoparticles. After adding a certain amount of salt (NaCl), gold nanoparticles aggregated with a changed surface charge property and the catalytic activity was greatly enhanced. Glutathione was used as an example of molecules with thiol groups which interact with gold nanoparticles and reduce the catalytic activity. The chemiluminescence intensity was reduced by 98.9%. Therefore, we could show that using a microreactor for gold nanoparticles synthesis and direct coupling with microfluidic chemiluminescence sensing offers a promising monitoring method to find the best synthesis condition of gold nanoparticles for catalytic activity.

ICBM-OCEAN: Processing Ultrahigh-Resolution Mass Spectrometry Data of Complex Molecular Mixtures.

Untargeted molecular analyses of complex mixtures are relevant for many fields of research, including geochemistry, pharmacology, and medicine. Ultrahigh-resolution mass spectrometry is one of the most powerful tools in this context. The availability of open scripts and online tools for specific data processing steps such as noise removal or molecular formula assignment is growing, but an integrative tool where all crucial steps are reproducibly evaluated and documented is lacking. We developed a novel, server-based tool (ICBM-OCEAN, Institute for Chemistry and Biology of the Marine Environment, Oldenburg-complex molecular mixtures, evaluation & analysis) that integrates published and novel approaches for standardized processing of ultrahigh-resolution mass spectrometry data of complex molecular mixtures. Different from published approaches, we offer diagnostic and validation tools for all relevant steps. Among other features, we included objective and reproducible reduction of noise and systematic errors, spectra recalibration and alignment, and identification of likeliest molecular formulas. With 15 chemical elements, the tool offers high flexibility in formula attribution. Alignment of mass spectra among different samples prior to molecular formula assignment improves mass error and facilitates molecular formula confirmation with the help of isotopologues. The online tool and the detailed instruction manual are freely accessible at www.icbm.de/icbm-ocean.

Controls of Land Use and the River Continuum Concept on Dissolved Organic Matter Composition in an Anthropogenically Disturbed Subtropical Watershed.

About 250 Tg of dissolved organic carbon are annually transported from inland waters to coastal systems making rivers a critical link between terrestrial and ocean carbon pools. During transport through fluvial systems, various biogeochemical processes selectively remove or transform labile material, effectively altering the composition of dissolved organic matter (DOM) exported to the ocean. The river continuum concept (RCC) has been historically used as a model to predict the fate and quality of organic matter along a river continuum. However, the conversion of natural landscapes for urban and agricultural practices can also alter the sources and quality of DOM exported from fluvial systems, and the RCC may be significantly limited in predicting DOM quality in anthropogenically impacted watersheds. Here, we studied DOM dynamics in the Altamaha River watershed in Georgia, USA, a fluvial system where headwater streams are highly impacted by anthropogenic activities. The primary goal of this study was to quantitatively assess the importance of both the RCC and land use as environmental drivers controlling DOM composition. Land use was a stronger predictor of spatial variation (∼50%) in DOM composition defined by both excitation-emission matrix-parallel factor analysis (EEM-PARAFAC) and ultrahigh-resolution mass spectrometry. This is compared to an 8% explained variability that can be attributed to the RCC. This study highlights the importance of incorporating land use among other controls into the RCC to better predict the fate and quality of DOM exported from terrestrial to coastal systems.