Combining Field and Imaging Spectroscopy to Map Soil Organic Carbon in a Semiarid Environment

Semiarid regions are especially vulnerable to climate change and human-induced land-use changes and are of major importance in the context of necessary carbon sequestration and ongoing land degradation. Topsoil properties, such as soil carbon content, provide valuable indicators to these processes, and can be mapped using imaging spectroscopy (IS). In semiarid regions, this poses difficulties because models are needed that can cope with varying land surface and soil conditions, consider a partial vegetation coverage, and deal with usually low soil organic carbon (SOC) contents. We present an approach that aims at addressing these difficulties by using a combination of field and IS to map SOC in an extensively used semiarid ecosystem. In hyperspectral imagery of the HyMap sensor, the influence of nonsoil materials, i.e., vegetation, on the spectral signature of soil dominated image pixels was reduced and a residual soil signature was calculated. The proposed approach allowed this procedure up to a vegetation coverage of 40% clearly extending the mapping capability. SOC quantities are predicted by applying a spectral feature-based SOC prediction model to image data of residual soil spectra. With this approach, we could significantly increase the spatial extent for which SOC could be predicted with a minimal influence of a vegetation signal compared to previous approaches where the considered area was limited to a maximum of, e.g., 10% vegetation coverage. As a regional example, the approach was applied to a 320 km2 area in the Albany Thicket Biome, South Africa, where land cover and landuse changes have occurred due to decades of unsustainable land management. In the generated maps, spatial SOC patterns were interpreted and linked to geomorphic features and land surface processes, i.e., areas of soil erosion. It was found that the chosen approach supported the extraction of soil-related spectral image information in the semiarid region with highly varying land cover. However, the quantitative prediction of SOC contents revealed a lack in absolute accuracy

Combining Field and Imaging Spectroscopy to Map Soil Organic Carbon in a Semiarid Environment

Semiarid regions are especially vulnerable to climate change and human-induced land-use changes and are of major importance in the context of necessary carbon sequestration and ongoing land degradation. Topsoil properties, such as soil carbon content, provide valuable indicators to these processes, and can be mapped using imaging spectroscopy (IS). In semiarid regions, this poses difficulties because models are needed that can cope with varying land surface and soil conditions, consider a partial vegetation coverage, and deal with usually low soil organic carbon (SOC) contents. We present an approach that aims at addressing these difficulties by using a combination of field and IS to map SOC in an extensively used semiarid ecosystem. In hyperspectral imagery of the HyMap sensor, the influence of nonsoil materials, i.e., vegetation, on the spectral signature of soil dominated image pixels was reduced and a residual soil signature was calculated. The proposed approach allowed this procedure up to a vegetation coverage of 40% clearly extending the mapping capability. SOC quantities are predicted by applying a spectral feature-based SOC prediction model to image data of residual soil spectra. With this approach, we could significantly increase the spatial extent for which SOC could be predicted with a minimal influence of a vegetation signal compared to previous approaches where the considered area was limited to a maximum of, e.g., 10% vegetation coverage. As a regional example, the approach was applied to a 320 km2 area in the Albany Thicket Biome, South Africa, where land cover and landuse changes have occurred due to decades of unsustainable land management. In the generated maps, spatial SOC patterns were interpreted and linked to geomorphic features and land surface processes, i.e., areas of soil erosion. It was found that the chosen approach supported the extraction of soil-related spectral image information in the semiarid region with highly varying land cover. However, the quantitative prediction of SOC contents revealed a lack in absolute accuracy

Mechanical Stability of a High-Affinity Toxin Anchor from the Pathogen Clostridium perfringens

The opportunistic pathogen Clostridium perfringens assembles its toxins and carbohydrate-active enzymes by the high-affinity cohesin-dockerin (Coh-Doc) interaction. Coh-Doc interactions characterized previously have shown considerable resilience towards mechanical stress. Here, we aimed to determine the mechanics of this interaction from C. perfringens in the context of a pathogen. Using atomic force microscopy based single-molecule force spectroscopy (AFM-SMFS) we probed the mechanical properties of the interaction of a dockerin from the $mu$-toxin with the GH84C X82 cohesin domain of C. perfringens. Most probable complex rupture forces were found to be approximately 60 pN. An estimate of the binding potential width was performed using two different methods of loading rate determination. The dockerin was expressed with its adjacent FIVAR (Found in Various Architectures) domain, whose mechanostability we determined to be very similar to the complex. Additionally, fast refolding of this domain was observed. The Coh-Doc interaction from C. perfringens is the mechanically weakest observed to date. Our results establish the relevant force range of toxin assembly mechanics in pathogenic Clostridia

Mechanisms of Nanonewton Mechanostability in a Protein Complex Revealed by Molecular Dynamics Simulations and Single-Molecule Force Spectroscopy

Can molecular dynamics simulations predict the mechanical behavior of protein complexes? Can simulations decipher the role of protein domains of unknown function in large macromolecular complexes? Here, we employ a wide-sampling computational approach to demonstrate that molecular dynamics simulations, when carefully performed and combined with single-molecule atomic force spectroscopy experiments, can predict and explain the behavior of highly mechanostable protein complexes. As a test case, we studied a previously unreported homologue from; Ruminococcus flavefaciens; called X-module-Dockerin (XDoc) bound to its partner Cohesin (Coh). By performing dozens of short simulation replicas near the rupture event, and analyzing dynamic network fluctuations, we were able to generate large simulation statistics and directly compare them with experiments to uncover the mechanisms involved in mechanical stabilization. Our single-molecule force spectroscopy experiments show that the XDoc-Coh homologue complex withstands forces up to 1 nN at loading rates of 10; 5; pN/s. Our simulation results reveal that this remarkable mechanical stability is achieved by a protein architecture that directs molecular deformation along paths that run perpendicular to the pulling axis. The X-module was found to play a crucial role in shielding the adjacent protein complex from mechanical rupture. These mechanisms of protein mechanical stabilization have potential applications in biotechnology for the development of systems exhibiting shear enhanced adhesion or tunable mechanics

Castelnuovo-Mumford regularity of deficiency modules

Let $d \in \N$ and let $M$ be a finitely generated graded module of dimension $\leq d$ over a Noetherian homogeneous ring $R$ with local Artinian base ring $R_0$. Let \beg(M), \gendeg(M) and \reg(M) respectively denote the beginning, the generating degree and the Castelnuovo-Mumford regularity of $M$. If $i \in \N_0$ and $n \in Z$, let $d^i_M(n)$ denote the $R_0$-length of the $n$-th graded component of the $i$-th $R_+$-transform module $D^i_{R_+}(M)$ of $M$ and let $K^i(M)$ denote the $i$-th deficiency module of $M$. Our main result says, that \reg(K^i(M)) is bounded in terms of \beg(M) and the "diagonal values" $d^j_M(-j)$ with $j = 0,..., d-1$. As an application of this we get a number of further bounding results for \reg(K^i(M)).Comment: 25 pages, the previous version divided in two part

Design of small molecule-responsive microRNAs based on structural requirements for Drosha processing

MicroRNAs (miRNAs) are prevalent regulatory RNAs that mediate gene silencing and play key roles in diverse cellular processes. While synthetic RNA-based regulatory systems that integrate regulatory and sensing functions have been demonstrated, the lack of detail on miRNA structure–function relationships has limited the development of integrated control systems based on miRNA silencing. Using an elucidated relationship between Drosha processing and the single-stranded nature of the miRNA basal segments, we developed a strategy for designing ligand-responsive miRNAs. We demonstrate that ligand binding to an aptamer integrated into the miRNA basal segments inhibits Drosha processing, resulting in titratable control over gene silencing. The generality of this control strategy was shown for three aptamer–small molecule ligand pairs. The platform can be extended to the design of synthetic miRNAs clusters, cis-acting miRNAs and self-targeting miRNAs that act both in cis and trans, enabling fine-tuning of the regulatory strength and dynamics. The ability of our ligand-responsive miRNA platform to respond to user-defined inputs, undergo regulatory performance tuning and display scalable combinatorial control schemes will help advance applications in biological research and applied medicine

Ultrastable cellulosome-adhesion complex tightens under load

Challenging environments have guided nature in the development of ultrastable protein complexes. Specialized bacteria produce discrete multi-component protein networks called cellulosomes to effectively digest lignocellulosic biomass. While network assembly is enabled by protein interactions with commonplace affinities, we show that certain cellulosomal ligand-receptor interactions exhibit extreme resistance to applied force. Here, we characterize the ligand-receptor complex responsible for substrate anchoring in the Ruminococcus flavefaciens cellulosome using single-molecule force spectroscopy and steered molecular dynamics simulations. The complex withstands forces of 600-750 pN, making it one of the strongest bimolecular interactions reported, equivalent to half the mechanical strength of a covalent bond. Our findings demonstrate force activation and inter-domain stabilization of the complex, and suggest that certain network components serve as mechanical effectors for maintaining network integrity. This detailed understanding of cellulosomal network components may help in the development of biocatalysts for production of fuels and chemicals from renewable plant-derived biomass

Cowpox Virus Transmission from Pet Rats to Humans, Germany

We describe a cluster of cowpox virus (CPXV) infections in humans that occurred near Munich, Germany, around the beginning of 2009. Previously, only sporadic reports of CPXV infections in humans after direct contact with various animals had been published. This outbreak involved pet rats from the same litter

Engineering naturally occurring trans-acting non-coding RNAs to sense molecular signals

Non-coding RNAs (ncRNAs) are versatile regulators in cellular networks. While most trans-acting ncRNAs possess well-defined mechanisms that can regulate transcription or translation, they generally lack the ability to directly sense cellular signals. In this work, we describe a set of design principles for fusing ncRNAs to RNA aptamers to engineer allosteric RNA fusion molecules that modulate the activity of ncRNAs in a ligand-inducible way in Escherichia coli. We apply these principles to ncRNA regulators that can regulate translation (IS10 ncRNA) and transcription (pT181 ncRNA), and demonstrate that our design strategy exhibits high modularity between the aptamer ligand-sensing motif and the ncRNA target-recognition motif, which allows us to reconfigure these two motifs to engineer orthogonally acting fusion molecules that respond to different ligands and regulate different targets in the same cell. Finally, we show that the same ncRNA fused with different sensing domains results in a sensory-level NOR gate that integrates multiple input signals to perform genetic logic. These ligand-sensing ncRNA regulators provide useful tools to modulate the activity of structurally related families of ncRNAs, and building upon the growing body of RNA synthetic biology, our ability to design aptamer–ncRNA fusion molecules offers new ways to engineer ligand-sensing regulatory circuits