SpyDirect: A Novel Biofunctionalization Method for High Stability and Longevity of Electronic Biosensors

Electronic immunosensors are indispensable tools for diagnostics, particularly in scenarios demanding immediate results. Conventionally, these sensors rely on the chemical immobilization of antibodies onto electrodes. However, globular proteins tend to adsorb and unfold on these surfaces. Therefore, self-assembled monolayers (SAMs) of thiolated alkyl molecules are commonly used for indirect gold-antibody coupling. Here, a limitation associated with SAMs is revealed, wherein they curtail the longevity of protein sensors, particularly when integrated into the state-of-the-art transducer of organic bioelectronics-the organic electrochemical transistor. The SpyDirect method is introduced, generating an ultrahigh-density array of oriented nanobody receptors stably linked to the gold electrode without any SAMs. It is accomplished by directly coupling cysteine-terminated and orientation-optimized spyTag peptides, onto which nanobody-spyCatcher fusion proteins are autocatalytically attached, yielding a dense and uniform biorecognition layer. The structure-guided design optimizes the conformation and packing of flexibly tethered nanobodies. This biolayer enhances shelf-life and reduces background noise in various complex media. SpyDirect functionalization is faster and easier than SAM-based methods and does not necessitate organic solvents, rendering the sensors eco-friendly, accessible, and amenable to scalability. SpyDirect represents a broadly applicable biofunctionalization method for enhancing the cost-effectiveness, sustainability, and longevity of electronic biosensors, all without compromising sensitivity.

An open-source, automated, and cost-effective platform for COVID-19 diagnosis and rapid portable genomic surveillance using nanopore sequencing

The COVID-19 pandemic, caused by SARS-CoV-2, has emphasized the necessity for scalable diagnostic workflows using locally produced reagents and basic laboratory equipment with minimal dependence on global supply chains. We introduce an open-source automated platform for high-throughput RNA extraction and pathogen diagnosis, which uses reagents almost entirely produced in-house. This platform integrates our methods for self-manufacturing magnetic nanoparticles and qRT-PCR reagents-both of which have received regulatory approval for clinical use-with an in-house, open-source robotic extraction protocol. It also incorporates our "Nanopore Sequencing of Isothermal Rapid Viral Amplification for Near Real-time Analysis" (NIRVANA) technology, designed for tracking SARS-CoV-2 mutations and variants. The platform exhibits high reproducibility and consistency without cross-contamination, and its limit of detection, sensitivity, and specificity are comparable to commercial assays. Automated NIRVANA effectively identifies circulating SARS-CoV-2 variants. Our in-house, cost-effective reagents, automated diagnostic workflows, and portable genomic surveillance strategies provide a scalable and rapid solution for COVID-19 diagnosis and variant tracking, essential for current and future pandemic responses.

Synthetic biology open language (SBOL) version 3.1.0

Synthetic biology builds upon genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. When designing a synthetic system, synthetic biologists need to exchange information about multiple types of molecules, the intended behavior of the system, and actual experimental measurements. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, following an open community process involving both bench scientists and scientific modelers and software developers, across academia, industry, and other institutions. This document describes SBOL 3.1.0, which improves on version 3.0.0 by including a number of corrections and clarifications as well as several other updates and enhancements. First, this version includes a complete set of validation rules for checking whether documents are valid SBOL 3. Second, the best practices section has been moved to an online repository that allows for more rapid and interactive of sharing these conventions. Third, it includes updates based upon six community approved enhancement proposals. Two enhancement proposals are related to the representation of an object’s namespace. In particular, the Namespace class has been removed and replaced with a namespace property on each class. Another enhancement is the generalization of the CombinatorialDeriviation class to allow direct use of Features and Measures . Next, the Participation class now allow Interactions to be participants to describe higher-order interactions. Another change is the use of Sequence Ontology terms for Feature orientation . Finally, this version of SBOL has generalized from using Unique Reference Identifiers (URIs) to Internationalized Resource Identifiers (IRIs) to support international character sets.

Convection Driven Ultrarapid Protein Detection via Nanobody-Functionalized Organic Electrochemical Transistors

Conventional biosensors rely on the diffusion-dominated transport of the target analyte to the sensor surface. Consequently, they require an incubation step that may take several hours to allow for the capture of analyte molecules by sensor biorecognition sites. This incubation step is a primary cause of long sample-to-result times. Here, alternating current electrothermal flow (ACET) is integrated in an organic electrochemical transistor (OECT)-based sensor to accelerate the device operation. ACET is applied to the gate electrode functionalized with nanobody-SpyCatcher fusion proteins. Using the SARS-CoV-2 spike protein in human saliva as an example target, it is shown that ACET enables protein recognition within only 2 min of sample exposure, supporting its use in clinical practice. The ACET integrated sensor exhibits better selectivity, higher sensitivity, and lower limit of detection than the equivalent sensor with diffusion-dominated operation. The performance of ACET integrated sensors is compared with two types of organic semiconductors in the channel and grounds for device-to-device variations are investigated. The results provide guidelines for the channel material choice in OECT-based biochemical sensors, and demonstrate that ACET integration substantially decreases the detection speed while increasing the sensitivity and selectivity of transistor-based sensors.

The exceptionally efficient quorum quenching enzyme LrsL suppresses Pseudomonas aeruginosa biofilm production

Quorum quenching (QQ) is the enzymatic degradation of molecules used by bacteria for synchronizing their behavior within communities. QQ has attracted wide attention due to its potential to inhibit biofilm formation and suppress the production of virulence factors. Through its capacity to limit biofouling and infections, QQ has applications in water treatment, aquaculture, and healthcare. Several different QQ enzymes have been described; however, they often lack the high stability and catalytic efficiency required for industrial applications. Previously, we identified genes from genome sequences of Red Sea sediment bacteria encoding potential QQ enzymes. In this study, we report that one of them, named LrsL, is a metallo-β-lactamase superfamily QQ enzyme with outstanding catalytic features. X-ray crystallography shows that LrsL is a zinc-binding dimer. LrsL has an unusually hydrophobic substrate binding pocket that can accommodate a broad range of acyl-homoserine lactones (AHLs) with exceptionally high affinity. In vitro, LrsL achieves the highest catalytic efficiency reported thus far for any QQ enzyme with a K_cat/K_M of 3 × 10⁷. LrsL effectively inhibited Pseudomonas aeruginosa biofilm formation without affecting bacterial growth. Furthermore, LrsL suppressed the production of exopolysaccharides required for biofilm production. These features, and its capacity to regain its function after prolonged heat denaturation, identify LrsL as a robust and unusually efficient QQ enzyme for clinical and industrial applications.

Efficient multi-gene expression in cell-free droplet microreactors

Cell-free transcription and translation systems promise to accelerate and simplify the engineering of proteins, biological circuits and metabolic pathways. Their encapsulation on microfluidic platforms can generate millions of cell-free reactions in picoliter volume droplets. However, current methods struggle to create DNA diversity between droplets while also reaching sufficient protein expression levels. In particular, efficient multi-gene expression has remained elusive. We here demonstrate that co-encapsulation of DNA-coated beads with a defined cell-free system allows high protein expression while also supporting genetic diversity between individual droplets. We optimize DNA loading on commercially available microbeads through direct binding as well as through the sequential coupling of up to three genes via a solid-phase Golden Gate assembly or BxB1 integrase-based recombineering. Encapsulation with an off-the-shelf microfluidics device allows for single or multiple protein expression from a single DNA-coated bead per 14 pL droplet. We envision that this approach will help to scale up and parallelize the rapid prototyping of more complex biological systems.

How to Find the Right RNA-Sensing CRISPR-Cas System for an In Vitro Application

CRISPR-Cas systems have a great and still largely untapped potential for in vitro applications, in particular, for RNA biosensing. However, there is currently no systematic guide on selecting the most appropriate RNA-targeting CRISPR-Cas system for a given application among thousands of potential candidates. We provide an overview of the currently described Cas effector systems and review existing Cas-based RNA detection methods. We then propose a set of systematic selection criteria for selecting CRISPR-Cas candidates for new applications. Using this approach, we identify four candidates for in vitro RNA.

The Synthetic Biology Open Language (SBOL) Version 3: Simplified Data Exchange for Bioengineering

The Synthetic Biology Open Language (SBOL) is a community-developed data standard that allows knowledge about biological designs to be captured using a machine-tractable, ontology-backed representation that is built using Semantic Web technologies. While early versions of SBOL focused only on the description of DNA-based components and their sub-components, SBOL can now be used to represent knowledge across multiple scales and throughout the entire synthetic biology workflow, from the specification of a single molecule or DNA fragment through to multicellular systems containing multiple interacting genetic circuits. The third major iteration of the SBOL standard, SBOL3, is an effort to streamline and simplify the underlying data model with a focus on real-world applications, based on experience from the deployment of SBOL in a variety of scientific and industrial settings. Here, we introduce the SBOL3 specification both in comparison to previous versions of SBOL and through practical examples of its use.

Synthetic biology open language (SBOL) version 3.0.0

Synthetic biology builds upon genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. When designing a synthetic system, synthetic biologists need to exchange information about multiple types of molecules, the intended behavior of the system, and actual experimental measurements. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, following an open community process involving both wet bench scientists and dry scientific modelers and software developers, across academia, industry, and other institutions. This document describes SBOL 3.0.0, which condenses and simplifies previous versions of SBOL based on experiences in deployment across a variety of scientific and industrial settings. In particular, SBOL 3.0.0, (1) separates sequence features from part/sub-part relationships, (2) renames Component Definition/Component to Component/Sub-Component, (3) merges Component and Module classes, (4) ensures consistency between data model and ontology terms, (5) extends the means to define and reference Sub-Components, (6) refines requirements on object URIs, (7) enables graph-based serialization, (8) moves Systems Biology Ontology (SBO) for Component types, (9) makes all sequence associations explicit, (10) makes interfaces explicit, (11) generalizes Sequence Constraints into a general structural Constraint class, and (12) expands the set of allowed constraints.

Synthetic Biology Open Language (SBOL) Version 2.3

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems is to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.3.0 of SBOL, which builds upon version 2.2.0 published in last year’s JIB Standards in Systems Biology special issue. In particular, SBOL 2.3.0 includes means of succinctly representing sequence modifications, such as insertion, deletion, and replacement, an extension to support organization and attachment of experimental data derived from designs, and an extension for describing numerical parameters of design elements. The new version also includes specifying types of synthetic biology activities, unambiguous locations for sequences with multiple encodings, refinement of a number of validation rules, improved figures and examples, and clarification on a number of issues related to the use of external ontology terms.

Synthetic Biology Open Language (SBOL) Version 2.2.0

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year’s JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.

Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.0 of SBOL Visual, which builds on the prior SBOL Visual 1.0 standard by expanding diagram syntax to include functional interactions and molecular species, making the relationship between diagrams and the SBOL data model explicit, supporting families of symbol variants, clarifying a number of requirements and best practices, and significantly expanding the collection of diagram glyphs.

A Visual Language for Protein Design

As protein engineering becomes more sophisticated, practitioners increasingly need to share diagrams for communicating protein designs. To this end, we present a draft visual language, Protein Language, that describes the high-level architecture of an engineered protein with easy-to-draw glyphs, intended to be compatible with other biological diagram languages such as SBOL Visual and SBGN. Protein Language consists of glyphs for representing important features (e.g., globular domains, recognition and localization sequences, sites of covalent modification, cleavage and catalysis), rules for composing these glyphs to represent complex architectures, and rules constraining the scaling and styling of diagrams. To support Protein Language we have implemented an extensible web-based software diagram tool, Protein Designer, that uses Protein Language in a "drag and drop" interface for visualization and computer-aided-design of engineered proteins, as well as conversion of annotated protein sequences to Protein Language diagrams and figure export. Protein Designer can be accessed at http://biocad.ncl.ac.uk/protein-designer/ .

SBOLme: a Repository of SBOL Parts for Metabolic Engineering

The Synthetic Biology Open Language (SBOL) is a community-driven open language to promote standardization in synthetic biology. To support the use of SBOL in metabolic engineering, we developed SBOLme, the first open-access repository of SBOL 2-compliant biochemical parts for a wide range of metabolic engineering applications. The URL of our repository is http://www.cbrc.kaust.edu.sa/sbolme .

Synthetic Biology Open Language (SBOL) Version 2.1.0

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.1 of SBOL that builds upon version 2.0 published in last year’s JIB special issue. In particular, SBOL 2.1 includes improved rules for what constitutes a valid SBOL document, new role fields to simplify the expression of sequence features and how components are used in context, and new best practices descriptions to improve the exchange of basic sequence topology information and the description of genetic design provenance, as well as miscellaneous other minor improvements.

Sharing Structure and Function in Biological Design with SBOL 2.0

The Synthetic Biology Open Language (SBOL) is a standard that enables collaborative engineering of biological systems across different institutions and tools. SBOL is developed through careful consideration of recent synthetic biology trends, real use cases, and consensus among leading researchers in the field and members of commercial biotechnology enterprises. We demonstrate and discuss how a set of SBOL-enabled software tools can form an integrated, cross-organizational workflow to recapitulate the design of one of the largest published genetic circuits to date, a 4-input AND sensor. This design encompasses the structural components of the system, such as its DNA, RNA, small molecules, and proteins, as well as the interactions between these components that determine the system's behavior/function. The demonstrated workflow and resulting circuit design illustrate the utility of SBOL 2.0 in automating the exchange of structural and functional specifications for genetic parts, devices, and the biological systems in which they operate.

Gesetzmäßigkeiten von Funkenentladungen im Nanosekundenbereich

In the experimental section of this paper it is shown how the shape of the electrical spark discharge pulse (in air) depends on the discharged capacitor C, the initial field strength E0, and the inductance of the electrodes and of the spark L0. In order to get nanosecond pulses, the time constant C must be some nanoseconds and the circuit has almost to be damped critically. The experiments confirm that this can be achieved for each capacitor C by choosing a suitable spark length l (or field strength E0). In the theoretical section the current is calculated for a discharge circuit with a time-dependent spark resistance R(t)=g/t. Under certain assumptions a solution for a “hard” discharge can be calculated according to the theory of WEIZEL and ROMPE. Thus formulae for imax, (di/dt)max, the spark resistance constant g0 and the risetime τan are obtained, and these prove to be in fair agreement with experimental results. The half-width of the light pulse exceeds that of the envelope of the electrical pulse approximately 1 ... 2 nanoseconds. Thus the design of nanosecond light sources can be based on this theory.

Messungen der Elektronenbeweglichkeit bei hohen Gasdrucken in Ar, He, N2 und H2

By means of a time of flight method the electron drift velocity ν _ in argon, helium, nitrogen, and hydrogen was determined as function of E/p [V/Torr cm] at room temperature and for high pressure up to 42 at, at which no measurements were as yet available. In He and H2 E/p was decreased to that range where the electrons are in thermal equilibrium with thet gas. In N2 measurements were extended nearly to this range, and in Ar measurements were carried out for E/p well above this range of thermal equilibrium.

The accuracy from 1% to 1.5% in the available pressure range enabled an examination of the similarity rule. For the diatomic gases N2 and H2 the measurements show that for constant E/p, in the range E/p < 1, the drift velocities decrease with increasing pressure. This effect was not found in Ar. In He no effect was found in the pressure range up to 8400 Torr (or it lies within the limits of error).

Engineering of weak helper interactions for high-efficiency FRET probes

Fluorescence resonance energy transfer (FRET)-based detection of protein interactions is limited by the very narrow range of FRET-permitting distances. We show two different strategies for the rational design of weak helper interactions that co-recruit donor and acceptor fluorophores for a more robust detection of bimolecular FRET: (i) in silico design of electrostatically driven encounter complexes and (ii) fusion of tunable domain-peptide interaction modules based on WW or SH3 domains. We tested each strategy for optimization of FRET between (m)Citrine and mCherry, which do not natively interact. Both approaches yielded comparable and large increases in FRET efficiencies with little or no background. Helper-interaction modules can be fused to any pair of fluorescent proteins and could, we found, enhance FRET between mTFP1 and mCherry as well as between mTurquoise2 and mCitrine. We applied enhanced helper-interaction FRET (hiFRET) probes to study the binding between full-length H-Ras and Raf1 as well as the drug-induced interaction between Raf1 and B-Raf.

SynBioWave--a real-time communication platform for molecular and synthetic biology

SUMMARY

Synthetic Biology is advanced by many users and relies on the assembly of genetic elements to devices, systems and finally genomes. SynBioWave is a software suite that enables multiple distributed users to analyze and construct genetic parts in real-time collaboration. It builds on Google Wave and provides an extensible robot-robot-user communication framework, a menu driven user interface, biological data handling including DAS and an internal database communication. We demonstrate its use by implementing robots for gene-data retrieval, manipulation and display. The initial development of SynBioWave demonstrates the power of the underlying Google Wave protocol for Synthetic Biology and lays the foundation for continuous and user-friendly extensions. Specialized wave-robots with a manageable set of capabilities will divide and conquer the complex task of creating a genome in silico.

AVAILABILITY

The robot is available at SynBioWave@appspot.com, the source code at http://synbiowave.sourceforge.net

Strategies for protein synthetic biology

Proteins are the most versatile among the various biological building blocks and a mature field of protein engineering has lead to many industrial and biomedical applications. But the strength of proteins—their versatility, dynamics and interactions—also complicates and hinders systems engineering. Therefore, the design of more sophisticated, multi-component protein systems appears to lag behind, in particular, when compared to the engineering of gene regulatory networks. Yet, synthetic biologists have started to tinker with the information flow through natural signaling networks or integrated protein switches. A successful strategy common to most of these experiments is their focus on modular interactions between protein domains or domains and peptide motifs. Such modular interaction swapping has rewired signaling in yeast, put mammalian cell morphology under the control of light, or increased the flux through a synthetic metabolic pathway. Based on this experience, we outline an engineering framework for the connection of reusable protein interaction devices into self-sufficient circuits. Such a framework should help to ‘refacture’ protein complexity into well-defined exchangeable devices for predictive engineering. We review the foundations and initial success stories of protein synthetic biology and discuss the challenges and promises on the way from protein- to protein systems design.

Building blocks for protein interaction devices

Here, we propose a framework for the design of synthetic protein networks from modular protein–protein or protein–peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part–based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors controlling protein expression in Escherichia coli: obstruction of translation initiation by mRNA secondary structure or toxicity of individual domains. Eventually, 13 proteins were purified for further characterization. Starting from well-established biotechnological tools, two general–purpose interaction input and two readout devices were built and characterized in vitro. Constitutive interaction input was achieved with a pair of synthetic leucine zippers. The second interaction was drug-controlled utilizing the rapamycin-induced binding of FRB(T2098L) to FKBP12. The interaction kinetics of both devices were analyzed by surface plasmon resonance. Readout was based on Förster resonance energy transfer between fluorescent proteins and was quantified for various combinations of input and output devices. Our results demonstrate the feasibility of parts-based protein synthetic biology. Additionally, we identify future challenges and limitations of modular design along with approaches to address them.

Biskit A software platform for structural bioinformatics

Biskit is a modular, object-oriented python library that provides intuitive classes for many typical tasks of structural bioinformatics research. It facilitates the manipulation and analysis of macromolecular structures, protein complexes and molecular dynamics trajectories. At the same time, Biskit offers a software platform for the rapid integration of external programs and new algorithms into complex structural bioinformatics workflows. Calculations are thus often delegated to established programs like Xplor, Amber, Hex, Prosa, Hmmer and Modeller; interfaces to further software can be easily added. Moreover, Biskit simplifies the parallelization of time consuming calculations via PVM (Parallel Virtual Machine).

AVAILABILITY

The latest snapshot of Biskit, documentation and examples are freely available under the GNU General Public License at http://biskit.sf.net (alternate url http://biskit.pasteur.fr).

Flexibility and Conformational Entropy in Protein-Protein Binding

To better understand the interplay between protein-protein binding and protein dynamics, we analyzed molecular dynamics simulations of 17 protein-protein complexes and their unbound components. Complex formation does not restrict the conformational freedom of the partner proteins as a whole, but, rather, it leads to a redistribution of dynamics. We calculate the change in conformational entropy for seven complexes with quasiharmonic analysis. We see significant loss, but also increased or unchanged conformational entropy. Where comparison is possible, the results are consistent with experimental data. However, stringent error estimates based on multiple independent simulations reveal large uncertainties that are usually overlooked. We observe substantial gains of pseudo entropy in individual partner proteins, and we observe that all complexes retain residual stabilizing intermolecular motions. Consequently, protein flexibility has an important influence on the thermodynamics of binding and may disfavor as well as favor association. These results support a recently proposed unified model for flexible protein-protein association.

Complementarity of structure ensembles in protein-protein binding

Protein-protein association is often accompanied by changes in receptor and ligand structure. This interplay between protein flexibility and protein-protein recognition is currently the largest obstacle both to our understanding of and to the reliable prediction of protein complexes. We performed two sets of molecular dynamics simulations for the unbound receptor and ligand structures of 17 protein complexes and applied shape-driven rigid body docking to all combinations of representative snapshots. The crossdocking of structure ensembles increased the likelihood of finding near-native solutions. The free ensembles appeared to contain multiple complementary conformations. These were in general not related to the bound structure. We suggest that protein-protein binding follows a three-step mechanism of diffusion, free conformer selection, and refolding. This model combines previously conflicting ideas and is in better agreement with the current data on interaction forces, time scales, and kinetics.

Peptide bond formation mediated by substrate mimetics. Structure-guidedoptimization of trypsin for synthesis

Substrate mimetics are excellent tools for protease-mediated peptide synthesis that enable the coupling of peptides independently of the primary specificity of the enzyme without undesired cleavages of the newly formed peptide bonds. However, the synthetic utility of this beneficial approach is limited to reactions with nonspecific amino-acid-containing peptides while the coupling of specific ones leads to unwanted cleavages due to the native proteolytic activity of the biocatalyst. This paper reports on the use of site-directed mutagenesis to design trypsin variants with decreased cleavage activity. Starting from the variant D189S, which is known for its low proteolytic potential, Ser189 and Ser190 were exchanged for Ala to further repress the inherent amidase activity of trypsin D189S. The effect of mutations was analysed by model synthesis reactions using specific amino-acid-containing peptides and substrate mimetics as the reactants. Finally, computer-assisted protein-ligand docking studies were performed to get closer insight into the molecular basis of the experimental results.

Spo0A directly controls the switch from acid to solvent production in solvent-forming clostridia

The spo0A genes of Clostridium beijerinckii NCIMB 8052 and Clostridium cellulolyticum ATCC 35319 were isolated and characterized. The C-terminal DNA-binding domains of the predicted products of spo0A from these two organisms, as well as 16 other taxonomically diverse species of Bacillus and Clostridium, show extensive amino acid sequence conservation (56% identity, 65% similarity over 104 residues). A 12-amino-acid motif (SRVERAIRHAIE) that forms the putative DNA recognition helix is particularly highly conserved, suggesting a common DNA target. Insertional inactivation of spo0A in C. beijerinckii blocked the formation of solvents (as well as spores and granulose). Sequences resembling Spo0A-binding motifs (TGNCGAA) are found in the promoter regions of several of the genes whose expression is modulated at the onset of solventogenesis in Clostridium acetobutylicum and C. beijerinckii. These include the upregulated adc gene, encoding acetoacetate decarboxylase (EC 4.1.1. 4), and the downregulated ptb gene, encoding phosphotransbutyrylase (EC 2.3.1.c). In vitro gel retardation experiments using C. acetobutylicum adc and C. beijerinckii ptb promoter fragments and recombinant Bacillus subtilis and C. beijerinckii Spo0A suggested that adc and ptb are directly controlled by Spo0A. The binding affinity was reduced when the 0A boxes were destroyed, and enhanced when they were modified to conform precisely to the consensus sequence. In vivo analysis of wild-type and mutagenized promoters transcriptionally fused to the gusA reporter gene in C. beijerinckii validated this hypothesis. Post-exponential phase expression from the mutagenized adc promoter was substantially reduced, whereas expression from the mutagenized ptb promoter was not shut down at the end of exponential growth.

Messungen des Anlagerungskoeffizienten von Elektronen in Sauerstoff

The attachment coefficient η for the formation of negative ions in low energy electron swarms was measured over an E/p-range of 0.1 ... 30 V/Torr cm by a new and accurate method. Thus earlier measurements up to 54 Torr of other authors could be extended to 880 Torr.

The shape of the minimum in the η/p-curves between the three-body process (e+2O2 → O2- + O2) and the dissociative process (e + O2 → O- + O) and its shift to higher E/p with increasing pressure was measured. Behind the minimum a maximum at E/p = 14 was found. Between the minimum and this maximum the dissociative process is predominant but the three-body process is still of influence. For E/p > 14 the η/p-values are slowly decreasing with increasing E/p.

For the higher pressures above 44 Torr deviations from the relation η proportional to p2 were found for the three-body process. These deviations are discussed.