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Microbial interactions shape ecosystem diversity and chemistry through production and exchange of organic compounds, but the impact of regulatory mechanisms on production and release of these exometabolites is largely unknown. We studied the extent and nature of impact of two signaling molecules, tropodithietic acid (TDA) and the quorum sensing molecule acyl homoserine lactone (AHL) on the exometabolome of the model bacterium Phaeobacter inhibens DSM 17395, a member of the ubiquitous marine Roseobacter group. Exometabolomes of the wild type, a TDA and a QS (AHL-regulator) negative mutant were analyzed via Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). Based on a total of 996 reproducibly detected molecular masses, exometabolomes of the TDA and QS negative mutant were ∼70% dissimilar to each other, and ∼90 and ∼60% dissimilar, respectively, to that of the wild type. Moreover, at any sampled growth phase, 40–60% of masses detected in any individual exometabolome were unique to that strain, while only 10–12% constituted a shared “core exometabolome.” Putative annotation revealed exometabolites of ecological relevance such as vitamins, amino acids, auxins, siderophore components and signaling compounds with different occurrence patterns in the exometabolomes of the three strains. Thus, this study demonstrates that signaling molecules, such as AHL and TDA, extensively impact the composition of bacterial exometabolomes with potential consequences for species interactions in microbial communities.

In the efforts to mitigate the ongoing humanitarian crisis at the European sea borders, this work builds detection capabilities to help find refugee boats in distress. For this paper, we collected dual-pol and quad-pol synthetic aperture radar (SAR) data over a 12 m rubber inflatable in a test-bed lake near Berlin, Germany. To consider a real scenario, we prepared the vessel so that its backscattering emulated that of a vessel fully occupied with people. Further, we collected SAR imagery over the ocean with different sea states, categorized by incidence angle and by polarization. These were used to emulate the conditions for a vessel located in ocean waters. This setup enabled us to test nine well-known vessel-detection systems (VDS), to explore the capabilities of new detection algorithms and to benchmark different combinations of detectors (detector fusion) with respect to different sensor and scene parameters (e.g., the polarization, wind speed, wind direction and boat orientation). This analysis culminated in designing a system that is specifically tailored to accommodate different situations and sea states.

Abstract Understanding broad trends in the distribution and composition of wetlands is essential for making evidence‐based management decisions. Determining temporal change in the extent of inundation in wetlands using remote sensing remains challenging and requires on‐ground verification to determine accuracy and precision. Therefore, optimization and validation of remote sensing methods in threatened wetlands is a high priority for their conservation. Despite their ecological importance in the landscape, we have little knowledge of the variation in the spatial extent of inundation in upland lagoons, a threatened ecological community in New South Wales, Australia. Our project developed locally trained algorithms to predict the extent of water and emergent vegetation using imagery from the Landsat‐5, ‐7, and ‐8 satellites. The best model for upland lagoons used shortwave infrared reflectance (performing better than normalized difference spectral indices), with model accuracy against validation transects greater than 95%. We applied the model to images from 1988 to 2020 across 58 lagoons to generate a dataset that demonstrates the variable water regime and vegetation change in response to local rainfall over 32 years such as in the lagoons. Our results reduce threats to a dynamic threatened ecological community by filling an important knowledge gap and demonstrate a valuable method to understand historical and current changes in the hydrology of dynamic wetland systems more broadly.

I read with interest the article “The Emergence of Japanese Encephalitis Virus in Australia in 2022: Existing Knowledge of Mosquito Vectors” [...]

Leisingera nanhaiensis DSM 24252(T) is a Gram-negative, motile, rod-shaped marine Alphaproteobacterium, isolated from sandy marine sediments. Here we present the non-contiguous genome sequence and annotation together with a summary of the organism's phenotypic features. The 4,948,550 bp long genome with its 4,832 protein-coding and 64 RNA genes consists of one chromosome and six extrachromosomal elements with lengths of 236 kb, 92 kb, 61 kb, 58 kb, 56 kb, and 35 kb, respectively. The analysis of the genome showed that DSM 24252(T) possesses all genes necessary for dissimilatory nitrite reduction, and the strain was shown to be facultatively anaerobic, a deviation from the original description that calls for an emendation of the species. Also present in the genome are genes coding for a putative prophage, for gene-transfer agents and for the utilization of methylated amines. Phylogenetic analysis and intergenomic distances indicate that L. nanhaiensis might not belong to the genus Leisingera.

TheraBracelet is a peripheral vibrotactile stimulation applied to affected upper extremities via a wristwatch-like wearable device during daily activities and therapy to improve upper limb function. The objective of this study was to examine the feasibility of using TheraBracelet for a child with hemiplegic cerebral palsy. Methods: A nine-year-old male with cerebral palsy was provided with TheraBracelet to use during daily activities in the home and community settings for 1.5 years while receiving standard care physical/occupational therapy. Results: The child used TheraBracelet independently and consistently, except during summer vacations and elbow-to-wrist orthotic use from growth spurt-related contracture. The use of TheraBracelet did not impede or prevent participation in daily activities. No study-related adverse events were reported by the therapist, child, or parent. Future research is warranted to investigate TheraBracelet as a propitious therapeutic device with a focus on the potential impact of use to improve the affected upper limb function in daily activities in children with hemiplegic cerebral palsy. [ABSTRACT FROM AUTHOR]

Abstract Strain U95T (= DSM 24752T = LMG 26464T) is the type strain of Epibacterium ulvae, which is the type species of the genus Epibacterium. This genus belongs to the marine Roseobacter group. E. ulvae Strain U95T was isolated from the macroalga Ulva australis, is Gram-negative, rod-shaped and motile. Here we describe the permanent draft genome sequence and annotation of E. ulvae U95T with a focus on secondary metabolite production and interaction with its host. The genome contains 4,092,893 bp, 3977 protein-coding genes and 60 RNA genes. The genome encodes a gene cluster for synthesis of the blue-pigmented secondary metabolite indigoidine and contains several genes for adhesion mechanisms, putative bacteriocin, siderophores, a type VI secretion system, and enzymes that confer oxidative stress resistance. Combined, these features may aid in the successful colonization and persistence of E. ulvae on host surfaces and in competition with the surrounding microbial consortium.

The ability to accurately and systematically monitor avocado crop phenology offers significant benefits for the optimization of farm management activities, improvement of crop productivity, yield estimation, and evaluation crops’ resilience to extreme weather conditions and future climate change. In this study, Sentinel-2-derived enhanced vegetation indices (EVIs) from 2017 to 2021 were used to retrieve canopy reflectance information that coincided with crop phenological stages, such as flowering (F), vegetative growth (V), fruit maturity (M), and harvest (H), in commercial avocado orchards in Bundaberg, Queensland and Renmark, South Australia. Tukey’s honestly significant difference (Tukey-HSD) test after one-way analysis of variance (ANOVA) with EVI metrics (EVImean and EVIslope) showed statistically significant differences between the four phenological stages. From a Pearson correlation analysis, a distinctive seasonal trend of EVIs was observed (R = 0.68 to 0.95 for Bundaberg and R = 0.8 to 0.96 for Renmark) in all 5 years, with the peak EVIs being observed at the M stage and the trough being observed at the F stage. However, a Tukey-HSD test showed significant variability in mean EVI values between seasons for both the Bundaberg and Renmark farms. The variability of the mean EVIs between the two farms was also evident with a p-value < 0.001. This novel study highlights the applicability of remote sensing for the monitoring of avocado phenological stages retrospectively and near-real time. This information not only supports the ‘benchmarking’ of seasonal orchard performance to identify potential impacts of seasonal weather variation and pest and disease incursions, but when seasonal growth profiles are aligned with the corresponding annual production, it can also be used to develop phenology-based yield prediction models.

Secondary metabolites are key components in microbial ecology by mediating interactions between bacteria and their environment, neighboring species or host organisms. Bioactivities can be beneficial for both interaction partners or provide a competitive advantage only for the producer. Colonizers of confined habitats such as biofilms are known as prolific producers of a great number of bioactive secondary metabolites and are a potential source for novel compounds. We investigated the strain Paracoccus marcusii CP157, which originates from the biofilm on the carapace of a shell disease-affected Cancer pagurus specimen, for its potential to produce bioactive secondary metabolites. Its closed genome contains 22 extrachromosomal elements and several gene clusters potentially involved in biosynthesis of bioactive polyketides, bacteriocins, and non-ribosomal peptides. Culture extracts of CP157 showed antagonistic activities against bacteria from different phyla, but also against microalgae and crustacean larvae. Different HPLC-fractions of CP157 culture extracts had antibacterial properties, indicating that several bioactive compounds are produced by CP157. The bioactive extract contains several small, antibacterial compounds that partially withstand elevated temperatures, extreme pH values and exposure to proteolytic enzymes, providing high stability toward environmental conditions in the natural habitat of CP157. Further, screening of 17 Paracoccus spp. revealed that antimicrobial activity, hemolysis and production of N-acyl homoserine lactones are common features within the genus. Taking into account the large habitat diversity and phylogenetic distance of the tested strains, we hypothesize that bioactive secondary metabolites play a central role in the ecology of Paracoccus spp. in their natural environments.

The fermentation of medicinal plants has been studied very little, as compared to the fermentation of food and beverages. One approach applies fermentation by single bacterial or fungal strains and targets the production of specific compounds or preservation of the fermented material. Spontaneous fermentation by an autochthonous starter community may lead to a more diverse blend of fermentation products because co-occurring microbes may activate the biosynthetic potentials and formation of compounds not produced in single strain approaches. We applied the community approach and studied the fermentation of four medicinal plants (Achillea millefolium, Taraxacum officinale, Mercurialis perennis, and Euphrasia officinalis), according to a standardized pharmaceutical fermentation method. It is based on the spontaneous fermentation by plant-specific bacterial and fungal communities under a distinct temperature regime, with a recurrent cooling during the first week and further fermentation for at least six months. The results revealed both general and plant-specific patterns in the composition and succession of microbial communities during fermentation. Lactic acid bacteria increasingly dominated in all preparations, whereas the fungal communities retained more plant-specific features. Three distinct fermentation phases with characteristic bacterial communities were identified, i.e., early, middle, and late phases. Co-occurrence network analyses revealed the plant-specific features of the microbial communities.

Strain T5(T) is the type strain of the species Phaeobacter inhibens Martens et al. 2006, a secondary metabolite producing bacterium affiliated to the Roseobacter clade. Strain T5(T) was isolated from a water sample taken at the German Wadden Sea, southern North Sea. Here we describe the complete genome sequence and annotation of this bacterium with a special focus on the secondary metabolism and compare it with the genomes of the Phaeobacter inhibens strains DSM 17395 and DSM 24588 (2.10), selected because of the close phylogenetic relationship based on the 16S rRNA gene sequences of these three strains. The genome of strain T5(T) comprises 4,130,897 bp with 3.923 protein-coding genes and shows high similarities in genetic and genomic characteristics compared to P. inhibens DSM 17395 and DSM 24588 (2.10). Besides the chromosome, strain T5(T) possesses four plasmids, three of which show a high similarity to the plasmids of the strains DSM 17395 and DSM 24588 (2.10). Analysis of the fourth plasmid suggested horizontal gene transfer. Most of the genes on this plasmid are not present in the strains DSM 17395 and DSM 24588 (2.10) including a nitrous oxide reductase, which allows strain T5(T) a facultative anaerobic lifestyle. The G+C content was calculated from the genome sequence and differs significantly from the previously published value, thus warranting an emendation of the species description.

Bacteria of the Roseobacter group (Rhodobacteraceae) are important members of many marine ecosystems. Similar to other Gram-negative bacteria many roseobacters produce N-acylhomoserine lactones (AHLs) for communication by quorum sensing systems. AHLs regulate different traits like cell differentiation or antibiotic production. Related N-acylalanine methyl esters (NAMEs) have been reported as well, but so far only from Roseovarius tolerans EL-164. While screening various roseobacters isolated from macroalgae we encountered four strains, Roseovarius sp. D12_1.68, Loktanella sp. F13, F14 and D3 that produced new derivatives and analogs of NAMEs, namely N-acyl-2-aminobutyric acid methyl esters (NABME), N-acylglycine methyl esters (NAGME), N-acylvaline methyl esters (NAVME), as well as for the first time a methyl-branched NAME, N-(13-methyltetradecanoyl)alanine methyl ester. These compounds were detected by GC–MS analysis, and structural proposals were derived from the mass spectra and by derivatization. Verification of compound structures was performed by synthesis. NABMEs, NAVMEs and NAGMEs are produced in low amounts only, making mass spectrometry the method of choice for their detection. The analysis of both EI and ESI mass spectra revealed fragmentation patterns helpful for the detection of similar compounds derived from other amino acids. Some of these compounds showed antimicrobial activity. The structural similarity of N-acylated amino acid methyl esters and similar lipophilicity to AHLs might indicate a yet unknown function as signalling compounds in the ecology of these bacteria, although their singular occurrence is in strong contrast to the common occurrence of AHLs. Obviously the structural motif is not restricted to Roseovarius spp. and occurs also in other genera.

Abstract Planktotalea frisia SH6-1T Hahnke et al. (Int J Syst Evol Microbiol 62:1619–24, 2012) is a planktonic marine bacterium isolated during a phytoplankton bloom from the southern North Sea. It belongs to the Roseobacter group within the alphaproteobacterial family Rhodobacteraceae. Here we describe the draft genome sequence and annotation of the type strain SH6-1T. The genome comprises 4,106,736 bp and contains 4128 protein-coding and 38 RNA genes. The draft genome sequence provides evidence for at least three extrachromosomal elements, encodes genes for DMSP utilization, quorum sensing, photoheterotrophy and a type IV secretion system. This indicates not only adaptation to a free-living lifestyle of P. frisia but points also to interactions with prokaryotic or eukaryotic organisms.

In 2020, mango (Mangifera indica) exports contributed over 40 million tons, worth around US$20 billion, to the global economy. Only 10% of this contribution was made from African countries including Ghana, largely due to lower investment in the sector and general paucity of research into the mango value chain, especially production, quality and volume. Considering the global economic importance of mango coupled with the gap in the use of the remote sensing technology in the sector, this study tested the hypothesis that phenological stages of mango can be retrieved from Sentinel-2 (S2) derived time series vegetation indices (VIs) data. The study was conducted on four mango farms in the Yilo Krobo Municipal Area of Ghana. Seasonal (temporal) growth curves using four VIs (NDVI, GNDVI, EVI and SAVI) for the period from 2017 to 2020 were derived for each of the selected orchards and then aligned with five known phenology stages: Flowering/Fruitset (F/FS), Fruit Development (FRD), Maturity/Harvesting (M/H), Flushing (FLU) and Dormancy (D). The significance of the variation “within” and “between” farms obtained from the VI metrics of the S2 data were tested using single-factor and two-factor analysis of variance (ANOVA). Furthermore, to identify which specific variable pairs (phenology stages) were significantly different, a Tukey honest significant difference (HSD) post-hoc test was conducted, following the results of the ANOVA. Whilst it was possible to differentiate the phenological stages using all the four VIs, EVI was found to be the best related with p < 0.05 for most of the studied farms. A distinct annual trend was identified with a peak in June/July and troughs in December/January. The derivation of remote sensing based ‘time series’ growth profiles for commercial mango orchards supports the ‘benchmarking’ of annual and seasonal orchard performance and therefore offers a near ‘real time’ technology for identifying significant variations resulting from pest and disease incursions and the potential impacts of seasonal weather variations.

Crop phenology modeling often involves determining variety‐specific growing degree day thresholds, or parameterizing mechanistic crop models. In this work, we used machine learning methods to develop models that provide daily predictions of the probability that rice (Oryza sativa) crops had reached the panicle initiation and flowering growth stages. These per‐date classifications were summarized into per‐paddock growth stage transition dates, which were then compared with field‐sampled reference data, encompassing 15 rice varieties, 10 years, and 380 sites. Leave‐one‐year‐out cross validation was used to provide realistic estimates of model errors. Compared with more complex and computationally intensive algorithms, logistic regression produced competitive results (mean cross‐season validation RMSE 3.9 and 5.2 days for panicle initiation and flowering, respectively). Logistic regression had additional advantages: providing confidence of growth stage predictions at each date (as it is a probabilistic algorithm), and straightforward explainability (as model parameters directly indicated how the various input variables contributed to growth stage predictions). Input variables included accumulated weather, rice variety, and sowing methods. The models were applied to forecasting phenology transition dates of the rice crops planted throughout the Murray and Murrumbidgee valleys. In addition, recommendations for optimal sowing dates were developed, using simulations involving more than 40 years of weather data, with the goal of minimizing the risk of cold‐temperatures during the microspore growth phase, which can severely degrade yield in temperate rice growing regions. Core Ideas: Crop phenology predictions aid timely interventions such as water and fertilizer application.Machine learning models predict growth stages of rice crops at each date in a time series.Input variables include weather, rice variety, and sowing method.Logistic regression yields competitive results, providing probabilistic predictions and explainability.Models enable climate‐based simulations of optimal sowing dates for rice crops in temperate regions. [ABSTRACT FROM AUTHOR]

Abstract Antibiotics are typically regarded as microbial weapons, but whereas their function at concentrations lethal for bacteria is often well characterized, the role of antibiotics at much lower concentrations as possibly found under natural conditions remains poorly understood. By using whole-transcriptome analyses and phenotypic screenings of the marine bacterium Phaeobacter inhibens we found that the broad-spectrum antibiotic tropodithietic acid (TDA) causes the same regulatory effects in quorum sensing (QS) as the common signaling molecule N-acyl-homoserine lactone (AHL) at concentrations 100-fold lower than the minimal inhibitory concentration against bacteria. Our results show that TDA has a significant impact on the expression of ~10% of the total genes of P. inhibens, in the same manner as the AHL. Furthermore, TDA needs the AHL associated LuxR-type transcriptional regulator, just as the AHL molecule. Low concentrations of antibiotics can obviously have a strong influence on the global gene expression of the bacterium that produces it and drastically change the metabolism and behaviour of the bacterium. For P. inhibens this includes motility, biofilm formation and antibiotic production, all important for settlement on new host-associated surfaces. Our results demonstrate that bacteria can produce antibiotics not only to antagonise other bacteria, but also to mediate QS like endogenous AHL molecules.

Objectives: The activation and inhibition of T-cells has been well-studied under physiological conditions. Co-inhibition is an important mechanism to keep effector T-cells in check. Co-inhibitors mediate peripheral self-tolerance and limit the immune response. Dysfunctional co-inhibition is associated with loss of T-cell regulation and induction of autoimmunity. Therefore, we investigated the co-inhibitor B- and T-Lymphocyte attenuator (BTLA) in ANCA-associated vasculitis (AAV).Methods: Fifty-six AAV patients and 32 healthy controls (HC) were recruited. Flow cytometry was performed to investigate the expression of BTLA on T-cells. Double negative T-cells were defined as CD3+CD4−CD8−. To assess the functionality of BTLA, CFSE-labeled T-cells were stimulated in presence or absence of an agonistic anti-BTLA antibody. In addition, impact of BTLA-mediated co-inhibition on Th17 cells was studied.Results: AAV patients in remission had a decreased expression of BTLA on double negative T-cells (CD3+CD4−CD8−). On all other subtypes of T-cells, expression of BTLA was comparable to healthy controls. TCR-independent stimulation of T-cells resulted in down-regulation of BTLA on Th cells in AAV and HC, being significantly lower in HC. Co-inhibition via BTLA led to suppression of T-cell proliferation in AAV as well as in HC. As a result of BTLA mediated co-inhibition, Th17 cells were suppressed to the same extent in AAV and HC.Conclusion: BTLA expression is altered on double negative T-cells but not on other T-cell subsets in quiescent AAV. BTLA-induced co-inhibition has the capacity to suppress Th17 cells and is functional in AAV. Thus, BTLA-mediated co-inhibition might be exploited for future targeted therapies in AAV.

Marine sponges (Phylum Porifera) are globally distributed within marine and freshwater ecosystems. In addition, sponges host dense and diverse prokaryotic communities, which are potential sources of novel bioactive metabolites and other complex compounds. Those sponge-derived natural products can span a broad spectrum of bioactivities, from antibacterial and antifungal to antitumor and antiviral compounds. However, most analyses concerning sponge-associated prokaryotes have mainly focused on conveniently accessible relatively shallow sampling locations for sponges. Hence, knowledge of community composition, host-relatedness and biotechnological potential of prokaryotic associations in temperate and cold-water sponges from greater depths (mesophotic to mesopelagic zones) is still scarce. Therefore, we analyzed the prokaryotic community diversity of four phylogenetically divergent sponge taxa from mesophotic to mesopelagic depths of Antarctic shelf at different depths and locations in the region of the South Shetland Islands using 16S rRNA gene amplicon-based sequencing. In addition, we predicted functional profiles applying Tax4Fun from metagenomic 16S rRNA gene data to estimate their biotechnological capability and possible roles as sources of novel bioactive compounds. We found indications that cold and deep-water sponges exhibit host-specific prokaryotic communities, despite different sampling sites and depths. Functional prediction analysis suggests that the associated prokaryotes may enhance the roles of sponges in biodegradation processes of xenobiotics and their involvement in the biosynthesis of secondary metabolites.