Beneficial applications of biofilms.

Many microorganisms live in the form of a biofilm. Although they are feared in the medical sector, biofilms that are composed of non-pathogenic organisms can be highly beneficial in many applications, including the production of bulk and fine chemicals. Biofilm systems are natural retentostats in which the biocatalysts can adapt and optimize their metabolism to different conditions over time. The adherent nature of biofilms allows them to be used in continuous systems in which the hydraulic retention time is much shorter than the doubling time of the biocatalysts. Moreover, the resilience of organisms growing in biofilms, together with the potential of uncoupling growth from catalytic activity, offers a wide range of opportunities. The ability to work with continuous systems using a potentially self-advancing whole-cell biocatalyst is attracting interest from a range of disciplines, from applied microbiology to materials science and from bioengineering to process engineering. The field of beneficial biofilms is rapidly evolving, with an increasing number of applications being explored, and the surge in demand for sustainable and biobased solutions and processes is accelerating advances in the field. This Review provides an overview of the research topics, challenges, applications and future directions in beneficial and applied biofilm research.

Exploration of overlap volumes for radiotherapy plan evaluation with the aim of healthy tissue sparing.

PURPOSE: Development of a novel interactive visualization approach for the exploration of radiotherapy treatment plans with a focus on overlap volumes with the aim of healthy tissue sparing. METHODS: We propose a visualization approach to include overlap volumes in the radiotherapy treatment plan evaluation process. Quantitative properties can be interactively explored to identify critical regions and used to steer the visualization for a detailed inspection of candidates. We evaluated our approach with a user study covering the individual visualizations and their interactions regarding helpfulness, comprehensibility, intuitiveness, decision-making and speed. RESULTS: A user study with three domain experts was conducted using our software and evaluating five data sets each representing a different type of cancer and location by performing a set of tasks and filling out a questionnaire. The results show that the visualizations and interactions help to identify and evaluate overlap volumes according to their physical and dose properties. Furthermore, the task of finding dose hot spots can also benefit from our approach. CONCLUSIONS: The results indicate the potential to enhance the current treatment plan evaluation process in terms of healthy tissue sparing.

Evaluating scaling of capillary photo-biofilm reactors for high cell density cultivation of mixed trophies artificial microbial consortia.

Capillary biofilm reactors (CBRs) are attractive for growing photoautotrophic bacteria as they allow high cell-density cultivation. Here, we evaluated the CBR system's suitability to grow an artificial consortium composed of Synechocystis sp. PCC 6803 and Pseudomonas sp. VBL120. The impact of reactor material, flow rate, pH, O2, and medium composition on biomass development and long-term biofilm stability at different reactor scales was studied. Silicone was superior over other materials like glass or PVC due to its excellent O2 permeability. High flow rates of 520 µL min-1 prevented biofilm sloughing in 1 m capillary reactors, leading to a 54% higher biomass dry weight combined with the lowest O2 concentration inside the reactor compared to standard operating conditions. Further increase in reactor length to 5 m revealed a limitation in trace elements. Increasing trace elements by a factor of five allowed for complete surface coverage with a biomass dry weight of 36.8 g m-2 and, thus, a successful CBR scale-up by a factor of 25. Practical application: Cyanobacteria use light energy to upgrade CO2, thereby holding the potential for carbon-neutral production processes. One of the persisting challenges is low cell density due to light limitations and O2 accumulation often occurring in established flat panel or tubular photobioreactors. Compared to planktonic cultures, much higher cell densities (factor 10 to 100) can be obtained in cyanobacterial biofilms. The capillary biofilm reactor (CBR) offers good growth conditions for cyanobacterial biofilms, but its applicability has been shown only on the laboratory scale. Here, a first scale-up study based on sizing up was performed, testing the feasibility of this system for large-scale applications. We demonstrate that by optimizing nutrient supply and flow conditions, the system could be enlarged by factor 25 by enhancing the length of the reactor. This reactor concept, combined with cyanobacterial biofilms and numbering up, holds the potential to be applied as a flexible, carbon-neutral production platform for value-added compounds.

Spatial organization and proteome of a dual-species cyanobacterial biofilm alter among N2-fixing and non-fixing conditions.

Many disciplines have become increasingly interested in cyanobacteria, due to their ability to fix CO2 while using water and sunlight as electron and energy sources. Further, several species of cyanobacteria are also capable of fixing molecular nitrogen, making them independent of the addition of nitrate or ammonia. Thereby they hold huge potential as sustainable biocatalysts. Here, we look into a dual-species biofilm consisting of filamentous diazotrophic cyanobacteria Tolypothrix sp. PCC 7712 and heterotrophic bacteria Pseudomonas taiwanensis VLB 120 growing in a capillary biofilm reactor. Such systems have been reported to enable high cell densities continuous process operation. By combining confocal laser scanning and helium-ion microscopy with a proteomics approach, we examined these organisms' interactions under two nitrogen-feeding strategies: N2-fixing and nitrate assimilation. Not only did Pseudomonas facilitate the biofilm formation by forming a carpet layer on the surface area but also did N2-fixing biofilms show greater attachment to the surface. Pseudomonas proteins related to surface and cell attachments were observed in N2-fixing biofilms in particular. Furthermore, co-localized biofilm cells displayed a resilient response to extra shear forces induced by segmented media/air flows. This study highlights the role of Pseudomonas in the initial attachment process, as well as the effects of different nitrogen-feeding strategies and operation regimes on biofilm composition and growth. IMPORTANCE Cyanobacteria are highly interesting microorganisms due to their ability to synthesize sugars from CO2 while using water and sunlight as electron and energy sources. Further, many species are also capable of utilizing molecular nitrogen, making them independent of artificial fertilizers. In this study, such organisms are cultivated in a technical system, which enables them to attach to the reactor surface, and form three-dimensional structures termed biofilms. Biofilms achieve extraordinarily high cell densities. Furthermore, this growth format allows for continuous processing, both being essential features in biotechnological process development. Understanding biofilm growth and the influence technical settings and media composition have on biofilm maturation and stability are crucial for reaction and reactor design. These findings will help to open up these fascinating organisms for applications as sustainable, resource-efficient industrial workhorses.

Introduction to Cyanobacteria.

Cyanobacteria are highly interesting microbes with the capacity for oxygenic photosynthesis. They fulfill an important purpose in nature but are also potent biocatalysts. This chapter gives a brief overview of this diverse phylum and shortly addresses the functions these organisms have in the natural ecosystems. Further, it introduces the main topics covered in this volume, which is dealing with the development and application of cyanobacteria as solar cell factories for the production of chemicals including potential fuels. We discuss cyanobacteria as industrial workhorses, present established chassis strains, and give an overview of the current target products. Genetic engineering strategies aiming at the photosynthetic efficiency as well as approaches to optimize carbon fluxes are summarized. Finally, main cultivation strategies are sketched.

On the Importance of Domain Awareness in Classifier Interpretations in Medical Imaging.

Translating the success of deep learning-based computer-assisted classification into clinical adaptation hinges on the ability to explain a prediction's causality. Post-hoc interpretability approaches, especially counterfactual techniques, have shown both technical and psychological potential. Nevertheless, currently dominant approaches utilize heuristic, unvalidated methodology. Thereby, they potentially operate the underlying networks outside their validated domain, adding doubt in the predictor's abilities instead of generating knowledge and trust. In this work, we investigate this out-of-distribution problem for medical image pathology classifiers and propose marginalization techniques and evaluation procedures to overcome it. Furthermore, we propose a complete domain-aware pipeline for radiology environments. Its validity is demonstrated on a synthetic and two publicly available image datasets. Specifically, we evaluate using the CBIS-DDSM/DDSM mammography collection and the Chest X-ray14 radiographs. Our solution shows, both quantitatively and qualitatively, a significant reduction of localization ambiguity and clearer conveying results.

Photosynthesis driven continuous hydrogen production by diazotrophic cyanobacteria in high cell density capillary photobiofilm reactors.

Hydrogen (H2) is a promising fuel in the context of climate neutral energy carriers and photosynthesis-driven H2-production is an interesting option relying mainly on sunlight and water as resources. However, this approach depends on suitable biocatalysts and innovative photobioreactor designs to maximize cell performance and H2 titers. Cyanobacteria were used as biocatalysts in capillary biofilm photobioreactors (CBRs). We show that biofilm formation/stability depend on light and CO2 availabilityH2 production rates correlate with these parameters but differ between Anabaena and Nostoc. We demonstrate that high light and corresponding O2 levels influence biofilm stability in CBR. By adjusting these parameters, biofilm formation/stability could be enhanced, and H2 formation was stable for weeks. Final biocatalyst titers reached up to 100 g l-1 for N. punctiforme atcc 29133 NHM5 and Anabaena sp. pcc 7120 AMC 414. H2 production rates were up to 300 µmol H2 l-1h-1 and 3 µmol H2 gcdw-1h-1 in biofilms.

Employing similarity to highlight differences: On the impact of anatomical assumptions in chest X-ray registration methods.

To facilitate both the detection and the interpretation of findings in chest X-rays, comparison with a previous image of the same patient is very valuable to radiologists. Today, the most common approach for deep learning methods to automatically inspect chest X-rays disregards the patient history and classifies only single images as normal or abnormal. Nevertheless, several methods for assisting in the task of comparison through image registration have been proposed in the past. However, as we illustrate, they tend to miss specific types of pathological changes like cardiomegaly and effusion. Due to assumptions on fixed anatomical structures or their measurements of registration quality, they produce unnaturally deformed warp fields impacting visualization of differences between moving and fixed images. We aim to overcome these limitations, through a new paradigm based on individual rib pair segmentation for anatomy penalized registration. Our method proves to be a natural way to limit the folding percentage of the warp field to 1/6 of the state of the art while increasing the overlap of ribs by more than 25%, implying difference images showing pathological changes overlooked by other methods. We develop an anatomically penalized convolutional multi-stage solution on the National Institutes of Health (NIH) data set, starting from less than 25 fully and 50 partly labeled training images, employing sequential instance memory segmentation with hole dropout, weak labeling, coarse-to-fine refinement and Gaussian mixture model histogram matching. We statistically evaluate the benefits of our method and highlight the limits of currently used metrics for registration of chest X-rays.

Whole-genome sequence of the filamentous diazotrophic cyanobacterium Tolypothrix sp. PCC 7712 and its comparison with non-diazotrophic Tolypothrix sp. PCC 7601.

Cyanobacteria are highly promising microorganisms in forthcoming biotechnologies. Besides the systematic development of molecular tools for genetic engineering, the design of chassis strains and novel reactor concepts are in focus. The latter includes capillary biofilm reactors (CBR), which offer a high surface area-to-volume ratio and very high cell densities. In this context, Tolypothrix sp. PCC 7712 was found to be highly suited for this reactor system due to maximal surface coverage, extraordinarily strong biofilm attachment, and high biomass formation. Here, we provide the genome sequence of Tolypothrix sp. PCC 7712 to potentially allow targeted strain engineering. Surprisingly, it was almost identical to an available incomplete genome draft of Tolypothrix sp. PCC 7601. Thus, we completely sequenced this strain as well and compared it in detail to strain PCC 7712. Comparative genome analysis revealed 257 and 80 unique protein-coding sequences for strains PCC 7601 and PCC 7712, respectively. Clustering genomes based on average nucleotide identity (ANI) and 16S rRNA homology showed 99.98% similarity and only minor distance, respectively, between the two strains in contrast to 21 other cyanobacterial genomes. Despite these high similarities, both strains differ in the ability to fix atmospheric nitrogen and show specific sequence variations, which are discussed in the paper.

Molecular archaeology of human cognitive traits.

The brains and minds of our human ancestors remain inaccessible for experimental exploration. Therefore, we reconstructed human cognitive evolution by projecting nonsynonymous/synonymous rate ratios (ω values) in mammalian phylogeny onto the anatomically modern human (AMH) brain. This atlas retraces human neurogenetic selection and allows imputation of ancestral evolution in task-related functional networks (FNs). Adaptive evolution (high ω values) is associated with excitatory neurons and synaptic function. It shifted from FNs for motor control in anthropoid ancestry (60-41 mya) to attention in ancient hominoids (26-19 mya) and hominids (19-7.4 mya). Selection in FNs for language emerged with an early hominin ancestor (7.4-1.7 mya) and was later accompanied by adaptive evolution in FNs for strategic thinking during recent (0.8 mya-present) speciation of AMHs. This pattern mirrors increasingly complex cognitive demands and suggests that co-selection for language alongside strategic thinking may have separated AMHs from their archaic Denisovan and Neanderthal relatives.

Evaluation of self-sustaining cyanobacterial biofilms for technical applications.

Cyanobacteria are potent microorganisms for sustainable photo-biotechnological production processes, as they are depending mainly on water, light, and carbon dioxide. Persisting challenges preventing their application include low biomass, as well as insufficient process stability and productivity. Here, we evaluate different cyanobacteria to be applied in a novel capillary biofilm reactor. Cultivated as biofilms, the organisms self-immobilize to the reactor walls, reach high biomass and enable long and robust production processes. As 'best performer' Tolypothrix sp. PCC 7712 emerged from this study. It reached the highest biomass in the reactors with 62.6 ± 6.34 gBDWL-1, produced 0.14 µmole H2 mgChl a -1h-1 under N2-fixing conditions, showed optimal surface coverage of the available growth surface, and only minor detachment in contrast to other tested species, highlighting its potential for photobiotechnology in the near future.

Rational orthologous pathway and biochemical process engineering for adipic acid production using Pseudomonas taiwanensis VLB120.

Microbial bioprocessing based on orthologous pathways constitutes a promising approach to replace traditional greenhouse gas- and energy-intensive production processes, e.g., for adipic acid (AA). We report the construction of a Pseudomonas taiwanensis strain able to efficiently convert cyclohexane to AA. For this purpose, a recently developed 6-hydroxyhexanoic acid (6HA) synthesis pathway was amended with alcohol and aldehyde dehydrogenases, for which different expression systems were tested. Thereby, genes originating from Acidovorax sp. CHX100 and the XylS/Pm regulatory system proved most efficient for the conversion of 6HA to AA as well as the overall cascade enabling an AA formation activity of up to 48.6 ± 0.2 U gCDW-1. The optimization of biotransformation conditions enabled 96% conversion of 10 mM cyclohexane with 100% AA yield. During recombinant gene expression, the avoidance of glucose limitation was found to be crucial to enable stable AA formation. The biotransformation was then scaled from shaking flask to a 1 L bioreactor scale, at which a maximal activity of 22.6 ± 0.2 U gCDW-1 and an AA titer of 10.2 g L-1 were achieved. The principal feasibility of product isolation was shown by the purification of 3.4 g AA to a purity of 96.1%. This study presents the efficient bioconversion of cyclohexane to AA by means of a single strain and thereby sets the basis for an environmentally benign production of AA and related polymers such as nylon 6,6.

Multi-Task Fusion for Improving Mammography Screening Data Classification.

Machine learning and deep learning methods have become essential for computer-assisted prediction in medicine, with a growing number of applications also in the field of mammography. Typically these algorithms are trained for a specific task, e.g., the classification of lesions or the prediction of a mammogram's pathology status. To obtain a comprehensive view of a patient, models which were all trained for the same task(s) are subsequently ensembled or combined. In this work, we propose a pipeline approach, where we first train a set of individual, task-specific models and subsequently investigate the fusion thereof, which is in contrast to the standard model ensembling strategy. We fuse model predictions and high-level features from deep learning models with hybrid patient models to build stronger predictors on patient level. To this end, we propose a multi-branch deep learning model which efficiently fuses features across different tasks and mammograms to obtain a comprehensive patient-level prediction. We train and evaluate our full pipeline on public mammography data, i.e., DDSM and its curated version CBIS-DDSM, and report an AUC score of 0.962 for predicting the presence of any lesion and 0.791 for predicting the presence of malignant lesions on patient level. Overall, our fusion approaches improve AUC scores significantly by up to 0.04 compared to standard model ensembling. Moreover, by providing not only global patient-level predictions but also task-specific model results that are related to radiological features, our pipeline aims to closely support the reading workflow of radiologists.

Thickness and roughness of transparent gold-palladium anodes have no impact on growth kinetics and yield coefficients of early-stage Geobacter sulfurreducens biofilms.

Geobacter sulfurreducens is the model organism for electroactive microorganisms performing direct extracellular electron transfer and forming thick mature biofilm electrodes. Although numerous physiological properties of mature biofilm electrodes are deciphered, there is an extensive gap of knowledge on the early-stage biofilm formation. We have shown recently that transparent gold-palladium (AuPd) electrodes allow for analysis of early-stage biofilm formation using confocal laser scanning microscopy. Here we analysed the influence of thickness (ranging from 12.5 to 200 nm) and roughness of AuPd electrodes on physiological parameters of G. sulfurreducens early-stage biofilms. We show that when grown potentiostatically at -200 mV vs. Ag/ AgCl sat. KCl neither maximum current density (jmax of âˆ¼ 80-150 µA cm-2) nor lag time (lag t of âˆ¼ 0.2-0.4 days) or single cell yield coefficients (YNe of 1.43 × 1012 cells mole--1) of the biofilms are influenced by the electrode preparation. This confirms the robustness of the experimental approach, which is an inevitable prerequisite for obtaining reliable results in follow-up experiments.

Cross-Modality Imaging of Murine Tumor Vasculature-a Feasibility Study.

Tumor vasculature and angiogenesis play a crucial role in tumor progression. Their visualization is therefore of utmost importance to the community. In this proof-of-principle study, we have established a novel cross-modality imaging (CMI) pipeline to characterize exactly the same murine tumors across scales and penetration depths, using orthotopic models of melanoma cancer. This allowed the acquisition of a comprehensive set of vascular parameters for a single tumor. The workflow visualizes capillaries at different length scales, puts them into the context of the overall tumor vessel network and allows quantification and comparison of vessel densities and morphologies by different modalities. The workflow adds information about hypoxia and blood flow rates. The CMI approach includes well-established technologies such as magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), and ultrasound (US), and modalities that are recent entrants into preclinical discovery such as optical coherence tomography (OCT) and high-resolution episcopic microscopy (HREM). This novel CMI platform establishes the feasibility of combining these technologies using an extensive image processing pipeline. Despite the challenges pertaining to the integration of microscopic and macroscopic data across spatial resolutions, we also established an open-source pipeline for the semi-automated co-registration of the diverse multiscale datasets, which enables truly correlative vascular imaging. Although focused on tumor vasculature, our CMI platform can be used to tackle a multitude of research questions in cancer biology.

[Quality of primary care and quality of life from the point of view of older patients with dizziness. Results oft the cohort study MobilE-TRA]. / Hausärztliche Versorgungsqualität und Lebensqualität aus der Sicht älterer Patienten mit Schwindel : Ergebnisse der Kohortenstudie MobilE-TRA.

BACKGROUND: The treatment of elderly patients with dizziness/vertigo/balance disorders (VDB) can be challenging for their general practitioner. Patient-centered care with a focus on self-management support could be a possible approach. Primary objective of this study was to investigate the correlations between quality of primary care and health-related quality of life (HRQOL) from the patient's perspective. METHOD: Data had been collected in the area of Munich and in the area of Dresden between 2017 and 2019. Questionnaires of n = 157 elderly patients from primary care practices in Munich and Dresden were evaluated. Multiple linear regression was used to analyse quality of care, physical activity, depression, and their correlations with HRQOL. RESULTS: In this cohort of patients aged 65 to 94 no significant correlation between quality of care and HRQOL could be detected. Depression correlated negatively with HRQOL, whereas physical activity showed a positive correlation with HRQOL. CONCLUSIONS: Physical activity can be beneficial for elderly dizzy patients' HRQOL. Additionally, a potential depression should be taken into account when treating patients with dizziness to improve their HRQOL. The results can be well transferred to elderly patients with VDB. Analysing more patients however, could increase the significance of the results.

Characterization of different biocatalyst formats for BVMO-catalyzed cyclohexanone oxidation.

Cyclohexanone monooxygenase (CHMO), a member of the Baeyer-Villiger monooxygenase family, is a versatile biocatalyst that efficiently catalyzes the conversion of cyclic ketones to lactones. In this study, an Acidovorax-derived CHMO gene was expressed in Pseudomonas taiwanensis VLB120. Upon purification, the enzyme was characterized in vitro and shown to feature a broad substrate spectrum and up to 100% conversion in 6 h. Furthermore, we determined and compared the cyclohexanone conversion kinetics for different CHMO-biocatalyst formats, that is, isolated enzyme, suspended whole cells, and biofilms, the latter two based on recombinant CHMO-containing P. taiwanensis VLB120. Biofilms showed less favorable values for KS (9.3-fold higher) and kcat (4.8-fold lower) compared with corresponding KM and kcat values of isolated CHMO, but a favorable KI for cyclohexanone (5.3-fold higher). The unfavorable KS and kcat values are related to mass transfer- and possibly heterogeneity issues and deserve further investigation and engineering, to exploit the high potential of biofilms regarding process stability. Suspended cells showed only 1.8-fold higher KS , but 1.3- and 4.2-fold higher kcat and KI values than isolated CHMO. This together with the efficient NADPH regeneration via glucose metabolism makes this format highly promising from a kinetics perspective.

Pseudomonas taiwanensis biofilms for continuous conversion of cyclohexanone in drip flow and rotating bed reactors.

In this study, the biocatalytic performance of a Baeyer-Villiger monooxygenase (BVMO) catalyzing the reaction of cyclohexanone to ε-caprolactone was investigated in Pseudomonas biofilms. Biofilm growth and development of two Pseudomonas taiwanensis VLB120 variants, Ps_BVMO and Ps_BVMO_DGC, were evaluated in drip flow reactors (DFRs) and rotating bed reactors (RBRs). Engineering a hyperactive diguanylate cyclase (DGC) from Caulobacter crescentus into Ps_BVMO resulted in faster biofilm growth compared to the control Ps_BVMO strain in the DFRs. The maximum product formation rates of 92 and 87 g m-2 d-1 were observed for mature Ps_BVMO and Ps_ BVMO_DGC biofilms, respectively. The application of the engineered variants in the RBR was challenged by low biofilm surface coverage (50-60%) of rotating bed cassettes, side-products formation, oxygen limitation, and a severe drop in production rates with time. By implementing an active oxygen supply mode and a twin capillary spray feed, the biofilm surface coverage was maximized to 70-80%. BVMO activity was severely inhibited by cyclohexanol formation, resulting in a decrease in product formation rates. By controlling the cyclohexanone feed concentration at 4 mM, a stable product formation rate of 14 g m-2 d-1 and a substrate conversion of 60% was achieved in the RBR.

The electrode potential determines the yield coefficients of early-stage Geobacter sulfurreducens biofilm anodes.

Geobacter sulfurreducens is the model for electroactive microorganisms (EAM). EAM can use solid state terminal electron acceptors (TEA) including anodes via extracellular electron transfer (EET). Yield coefficients relate the produced cell number or biomass to the oxidized substrate or the reduced TEA. These data are not yet sufficiently available for EAM growing at anodes. Thus, this study provides information about kinetics as well as yield coefficients of early-stage G. sulfurreducens biofilms using anodes as TEA at the potentials of -200 mV, 0 mV and +200 mV (vs. Ag/AgCl sat. KCl). The selected microorganism was therefore cultivated in single and double chamber batch reactors on graphite or AuPd anodes. Interestingly, whereas the lag time and maximum current density within 12 days of growth differed, the anode potential does not influence the coulombic efficiency and the formal potential of the EET, which remains constant for all the experiments at ~ -300 to -350 mV. We demonstrated for the first time that the anode potential has a strong influence on single cell yield coefficients which ranged from 2.69 × 1012 cells mole--1 at -200 mV and 1.48 × 1012 cells mole--1 at 0 mV to 2.58 × 1011 cells mole--1 at +200 mV in single chamber reactors and from 1.15 × 1012 cells mole--1 at -200 mV to 8.98× 1011 cells mole--1 at 0 mV in double chamber reactors. This data can be useful for optimization and scaling-up of primary microbial electrochemical technologies.