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.

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.

Principles of Visualization in Radiation Oncology.

BACKGROUND: Medical visualization employs elements from computer graphics to create meaningful, interactive visual representations of medical data, and it has become an influential field of research for many advanced applications like radiation oncology, among others. Visual representations employ the user's cognitive capabilities to support and accelerate diagnostic, planning, and quality assurance workflows based on involved patient data. SUMMARY: This article discusses the basic underlying principles of visualization in the application domain of radiation oncology. The main visualization strategies, such as slice-based representations and surface and volume rendering are presented. Interaction topics, i.e., the combination of visualization and automated analysis methods, are also discussed. Key Messages: Slice-based representations are a common approach in radiation oncology, while volume visualization also has a long-standing history in the field. Perception within both representations can benefit further from advanced approaches, such as image fusion and multivolume or hybrid rendering. While traditional slice-based and volume representations keep evolving, the dimensionality and complexity of medical data are also increasing. To address this, visual analytics strategies are valuable, particularly for cohort or uncertainty visualization. Interactive visual analytics approaches represent a new opportunity to integrate knowledgeable experts and their cognitive abilities in exploratory processes which cannot be conducted by solely automatized methods.

Ten simple rules to create biological network figures for communication.

Biological network figures are ubiquitous in the biology and medical literature. On the one hand, a good network figure can quickly provide information about the nature and degree of interactions between items and enable inferences about the reason for those interactions. On the other hand, good network figures are difficult to create. In this paper, we outline 10 simple rules for creating biological network figures for communication, from choosing layouts, to applying color or other channels to show attributes, to the use of layering and separation. These rules are accompanied by illustrative examples. We also provide a concise set of references and additional resources for each rule.

Cellular physiology controls photoautotrophic production of 1,2-propanediol from pools of CO2 and glycogen.

Synechocystis sp. PCC 6803 PG is a cyanobacterial strain capable of synthesizing 1,2-propanediol from carbon dioxide (CO2 ) via a heterologous three-step pathway and a methylglyoxal synthase (MGS) originating from Escherichia coli as an initial enzyme. The production window is restricted to the late growth and stationary phase and is apparently coupled to glycogen turnover. To understand the underlying principle of the carbon partitioning between the Calvin-Benson-Bassham (CBB) cycle and glycogen in the context of 1,2-propanediol production, experiments utilizing 13 C labeled CO2 have been conducted. Carbon fluxes and partitioning between biomass, storage compounds, and product have been monitored under permanent illumination as well as under dark conditions. About one-quarter of the carbon incorporated into 1,2-propanediol originated from glycogen, while the rest was derived from CO2 fixed in the CBB cycle during product formation. Furthermore, 1,2-propanediol synthesis was depending on the availability of photosynthetic active radiation and glycogen catabolism. We postulate that the regulation of the MGS from E. coli conflicts with the heterologous reactions leading to 1,2-propanediol in Synechocystis sp. PCC 6803 PG. Additionally, homology comparison of the genomic sequence to genes encoding for the methylglyoxal bypass in E. coli suggested the existence of such a pathway also in Synechocystis sp. PCC 6803. These findings are critical for all heterologous pathways coupled to the CBB cycle intermediate dihydroxyacetone phosphate via a MGS and reveal possible engineering targets for rational strain optimization.

Predicting functional neuroanatomical maps from fusing brain networks with genetic information.

Functional neuroanatomical maps provide a mesoscale reference framework for studies from molecular to systems neuroscience and psychiatry. The underlying structure-function relationships are typically derived from functional manipulations or imaging approaches. Although highly informative, these are experimentally costly. The increasing amount of publicly available brain and genetic data offers a rich source that could be mined to address this problem computationally. Here, we developed an algorithm that fuses gene expression and connectivity data with functional genetic meta data and exploits cumulative effects to derive neuroanatomical maps related to multi-genic functions. We validated the approach by using public available mouse and human data. The generated neuroanatomical maps recapture known functional anatomical annotations from literature and functional MRI data. When applied to multi-genic meta data from mouse quantitative trait loci (QTL) studies and human neuropsychiatric databases, this method predicted known functional maps underlying behavioral or psychiatric traits. Taken together, genetically weighted connectivity analysis (GWCA) allows for high throughput functional exploration of brain anatomy in silico. It maps functional genetic associations onto brain circuitry for refining functional neuroanatomy, or identifying trait-associated brain circuitry, from genetic data.

Production of 1,2-propanediol in photoautotrophic Synechocystis is linked to glycogen turn-over.

We utilized a photoautotrophic organism to synthesize 1,2-propanediol from carbon dioxide and water fueled by light. A synthetic pathway comprising mgsA (methylglyoxal synthase), yqhD (aldehyde reductase), and adh (alcohol dehydrogenase) was inserted into Synechocystis sp. PCC6803 to convert dihydroxyacetone phosphate to methylglyoxal, which is subsequently reduced to acetol and then to 1,2-propanediol. 1,2-propanediol could be successfully produced by Synechocystis, at an approximate rate of 55 µmol h-1 gCDW-1 . Surprisingly, maximal productivity was observed in the stationary phase. The production of 1,2-propanediol was clearly coupled to the turn-over of intracellular glycogen. Upon depletion of the glycogen pool, product formation stopped. Reducing the carbon flux to glycogen significantly decreased final product titers. Optimization of cultivation conditions allowed final product titers of almost 1 g L-1 (12 mM), which belongs to the highest values published so far for photoautotrophic production of this compound.

Visualization of 4D multimodal imaging data and its applications in radiotherapy planning.

PURPOSE: To explore the benefit of using 4D multimodal visualization and interaction techniques for defined radiotherapy planning tasks over a treatment planning system used in clinical routine (C-TPS) without dedicated 4D visualization. METHODS: We developed a 4D visualization system (4D-VS) with dedicated rendering and fusion of 4D multimodal imaging data based on a list of requirements developed in collaboration with radiation oncologists. We conducted a user evaluation in which the benefits of our approach were evaluated in comparison to C-TPS for three specific tasks: assessment of internal target volume (ITV) delineation, classification of tumor location in peripheral or central, and assessment of dose distribution. For all three tasks, we presented test cases for which we measured correctness, certainty, consistency followed by an additional survey regarding specific visualization features. RESULTS: Lower quality of the test ITVs (ground truth quality was available) was more likely to be detected using 4D-VS. ITV ratings were more consistent in 4D-VS and the classification of tumor location had a higher accuracy. Overall evaluation of the survey indicates 4D-VS provides better spatial comprehensibility and simplifies the tasks which were performed during testing. CONCLUSIONS: The use of 4D-VS has improved the assessment of ITV delineations and classification of tumor location. The visualization features of 4D-VS have been identified as helpful for the assessment of dose distribution during user testing.

Stabilization of single species Synechocystis biofilms by cultivation under segmented flow.

The application of segmented flow on a Synechocystis sp. PCC 6803 biofilm prevented excessive biomass formation and clogging by fundamentally changing the structure of the microbial community. It was possible to continuously operate a capillary microreactor for 5 weeks, before the experiment was actively terminated. The biofilm developed up to a thickness of 70-120 µm. Surprisingly, the biofilm stopped growing at this thickness and stayed constant without any detachment events occurring afterwards. The substrates CO2 and light were supplied in a counter-current fashion. Confocal microscopy revealed a throughout photosynthetically active biofilm, indicated by the red fluorescence of photo pigments. This control concept and biofilm reaction setup may enable continuous light driven synthesis of value added compounds in future.

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.

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource.

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

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.

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.

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.

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.

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.

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.

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.

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.

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.