iNClusive: a database collecting useful information on non-canonical amino acids and their incorporation into proteins for easier genetic code expansion implementation.

The incorporation of non-canonical amino acids (ncAAs) into proteins is a powerful technique used in various research fields. Genetic code expansion (GCE) is the most common way to achieve this: a specific codon is selected to be decoded by a dedicated tRNA orthogonal to the endogenous ones. In the past 30 years, great progress has been made to obtain novel tRNA synthetases (aaRSs) accepting a variety of ncAAs with distinct physicochemical properties, to develop robust in vitro assays or approaches for codon reassignment. This sparked the use of the technique, leading to the accumulation of publications, from which gathering all relevant information can appear daunting. Here we present iNClusive (https://non-canonical-aas.biologie.uni-freiburg.de/), a manually curated, extensive repository using standardized nomenclature that provides organized information on ncAAs successfully incorporated into target proteins as verified by mass spectrometry. Since we focused on tRNA synthetase-based tRNA loading, we provide the sequence of the tRNA and aaRS used for the incorporation. Derived from more than 687 peer-reviewed publications, it currently contains 2432 entries about 466 ncAAs, 569 protein targets, 500 aaRSs and 144 tRNAs. We foresee iNClusive will encourage more researchers to experiment with ncAA incorporation thus contributing to the further development of this exciting technique.

Requirements for mammalian promoters to decode transcription factor dynamics.

In response to different stimuli many transcription factors (TFs) display different activation dynamics that trigger the expression of specific sets of target genes, suggesting that promoters have a way to decode dynamics. Here, we use optogenetics to directly manipulate the nuclear localization of a synthetic TF in mammalian cells without affecting other processes. We generate pulsatile or sustained TF dynamics and employ live cell microscopy and mathematical modelling to analyse the behaviour of a library of reporter constructs. We find decoding of TF dynamics occurs only when the coupling between TF binding and transcription pre-initiation complex formation is inefficient and that the ability of a promoter to decode TF dynamics gets amplified by inefficient translation initiation. Using the knowledge acquired, we build a synthetic circuit that allows obtaining two gene expression programs depending solely on TF dynamics. Finally, we show that some of the promoter features identified in our study can be used to distinguish natural promoters that have previously been experimentally characterized as responsive to either sustained or pulsatile p53 and NF-κB signals. These results help elucidate how gene expression is regulated in mammalian cells and open up the possibility to build complex synthetic circuits steered by TF dynamics.

patcHwork: a user-friendly pH sensitivity analysis web server for protein sequences and structures.

pH regulates protein function and interactions by altering the charge of individual residues causing loss or gain of intramolecular noncovalent bonds, which may lead to structural rearrangements. While tools to analyze residue-specific charge distribution of proteins at a given pH exist, currently no tool is available to investigate noncovalent bond changes at two different pH values. To make protein pH sensitivity analysis more accessible, we developed patcHwork, a web server that combines the identification of amino acids undergoing a charge shift with the determination of affected noncovalent bonds at two user-defined pH values. At the sequence-only level, patcHwork applies the Henderson-Hasselbalch equation to determine pH-sensitive residues. When the 3D protein structure is available, patcHwork can be employed to gain mechanistic understanding of the effect of pH. This is achieved using the PDB2PQR and PROPKA tools and noncovalent bond determination algorithms. A user-friendly interface allows visualizing pH-sensitive residues, affected salt bridges, hydrogen bonds and aromatic (pi-pi and cation-pi) interactions. patcHwork can be used to identify patches, a new concept we propose of pH-sensitive residues in close proximity on the protein, which may have a major impact on function. We demonstrate the attractiveness of patcHwork studying experimentally investigated pH-sensitive proteins (https://patchwork.biologie.uni-freiburg.de/).

Engineering AraC to make it responsive to light instead of arabinose.

The L-arabinose-responsive AraC and its cognate PBAD promoter underlie one of the most often used chemically inducible prokaryotic gene expression systems in microbiology and synthetic biology. Here, we change the sensing capability of AraC from L-arabinose to blue light, making its dimerization and the resulting PBAD activation light-inducible. We engineer an entire family of blue light-inducible AraC dimers in Escherichia coli (BLADE) to control gene expression in space and time. We show that BLADE can be used with pre-existing L-arabinose-responsive plasmids and strains, enabling optogenetic experiments without the need to clone. Furthermore, we apply BLADE to control, with light, the catabolism of L-arabinose, thus externally steering bacterial growth with a simple transformation step. Our work establishes BLADE as a highly practical and effective optogenetic tool with plug-and-play functionality-features that we hope will accelerate the broader adoption of optogenetics and the realization of its vast potential in microbiology, synthetic biology and biotechnology.

The active repertoire of Escherichia coli peptidoglycan amidases varies with physiochemical environment.

Nearly all bacteria are encased in peptidoglycan, an extracytoplasmic matrix of polysaccharide strands crosslinked through short peptide stems. In the Gram-negative model organism Escherichia coli, more than 40 synthases and autolysins coordinate the growth and division of the peptidoglycan sacculus in the periplasm. The precise contribution of many of these enzymes to peptidoglycan metabolism remains unclear due to significant apparent redundancy, particularly among the autolysins. E. coli produces three major LytC-type-N-acetylmuramoyl-L-alanine amidases, which share a role in separating the newly formed daughter cells during cytokinesis. Here, we reveal two of the three amidases that exhibit growth medium-dependent changes in activity. Specifically, we report acidic growth conditions stimulate AmiB-and to a lesser extent, AmiC-amidase activity. Combining genetic, biochemical, and computational analyses, we demonstrate that low pH-dependent stimulation of AmiB is mediated through the periplasmic amidase activators NlpD, EnvC, and ActS (formerly known as YgeR). Although NlpD and EnvC promote amidase activity across pH environments, ActS preferentially stimulates AmiB activity in acidic conditions. Altogether, our findings support partially overlapping roles for E. coli amidases and their regulators in cell separation and illuminate the physiochemical environment as an important mediator of cell wall enzyme activity.

Switchable inteins for conditional protein splicing.

Synthetic biologists aim at engineering controllable biological parts such as DNA, RNA and proteins in order to steer biological activities using external inputs. Proteins can be controlled in several ways, for instance by regulating the expression of their encoding genes with small molecules or light. However, post-translationally modifying pre-existing proteins to regulate their function or localization leads to faster responses. Conditional splicing of internal protein domains, termed inteins, is an attractive methodology for this purpose. Here we discuss methods to control intein activity with a focus on those compatible with applications in living cells.

Chromosome segregation by the Escherichia coli Min system.

The mechanisms underlying chromosome segregation in prokaryotes remain a subject of debate and no unifying view has yet emerged. Given that the initial disentanglement of duplicated chromosomes could be achieved by purely entropic forces, even the requirement of an active prokaryotic segregation machinery has been questioned. Using computer simulations, we show that entropic forces alone are not sufficient to achieve and maintain full separation of chromosomes. This is, however, possible by assuming repeated binding of chromosomes along a gradient of membrane-associated tethering sites toward the poles. We propose that, in Escherichia coli, such a gradient of membrane tethering sites may be provided by the oscillatory Min system, otherwise known for its role in selecting the cell division site. Consistent with this hypothesis, we demonstrate that MinD binds to DNA and tethers it to the membrane in an ATP-dependent manner. Taken together, our combined theoretical and experimental results suggest the existence of a novel mechanism of chromosome segregation based on the Min system, further highlighting the importance of active segregation of chromosomes in prokaryotic cell biology.

Int&in: A machine learning-based web server for active split site identification in inteins.

Inteins are proteins that excise themselves out of host proteins and ligate the flanking polypeptides in an auto-catalytic process called protein splicing. In nature, inteins are either contiguous or split. In the case of split inteins, the two fragments must first form a complex for the splicing to occur. Contiguous inteins have previously been artificially split in two fragments because split inteins allow for distinct applications than contiguous ones. Even naturally split inteins have been split at unnatural split sites to obtain fragments with reduced affinity for one another, which are useful to create conditional inteins or to study protein-protein interactions. So far, split sites in inteins have been heuristically identified. We developed Int&in, a web server freely available for academic research (https://intein.biologie.uni-freiburg.de) that runs a machine learning model using logistic regression to predict active and inactive split sites in inteins with high accuracy. The model was trained on a dataset of 126 split sites generated using the gp41-1, Npu DnaE and CL inteins and validated using 97 split sites extracted from the literature. Despite the limited data size, the model, which uses various protein structural features, as well as sequence conservation information, achieves an accuracy of 0.79 and 0.78 for the training and testing sets, respectively. We envision Int&in will facilitate the engineering of novel split inteins for applications in synthetic and cell biology.

ReverseDock: a web server for blind docking of a single ligand to multiple protein targets using AutoDock Vina.

Several platforms exist to perform molecular docking to computationally predict binders to a specific protein target from a library of ligands. The reverse, that is, docking a single ligand to various protein targets, can currently be done by very few web servers, which limits the search to a small set of pre-selected human proteins. However, the possibility to in silico predict which targets a compound identified in a high-throughput drug screen bind would help optimize and reduce the costs of the experimental workflow needed to reveal the molecular mechanism of action of a ligand. Here, we present ReverseDock, a blind docking web server based on AutoDock Vina specifically designed to allow users with no computational expertise to dock a ligand to 100 protein structures of their choice. ReverseDock increases the number and type of proteins a ligand can be docked to, making the task of in silico docking of a ligand to entire families of proteins straightforward. We envision ReverseDock will support researchers by providing the possibility to apply inverse docking computations using web browser. ReverseDock is available at: https://reversedock.biologie.uni-freiburg.de/.

Self-organized partitioning of dynamically localized proteins in bacterial cell division.

How cells manage to get equal distribution of their structures and molecules at cell division is a crucial issue in biology. In principle, a feedback mechanism could always ensure equality by measuring and correcting the distribution in the progeny. However, an elegant alternative could be a mechanism relying on self-organization, with the interplay between system properties and cell geometry leading to the emergence of equal partitioning. The problem is exemplified by the bacterial Min system that defines the division site by oscillating from pole to pole. Unequal partitioning of Min proteins at division could negatively impact system performance and cell growth because of loss of Min oscillations and imprecise mid-cell determination. In this study, we combine live cell and computational analyses to show that known properties of the Min system together with the gradual reduction of protein exchange through the constricting septum are sufficient to explain the observed highly precise spontaneous protein partitioning. Our findings reveal a novel and effective mechanism of protein partitioning in dividing cells and emphasize the importance of self-organization in basic cellular processes.

From in vivo to in silico biology and back.

The massive acquisition of data in molecular and cellular biology has led to the renaissance of an old topic: simulations of biological systems. Simulations, increasingly paired with experiments, are being successfully and routinely used by computational biologists to understand and predict the quantitative behaviour of complex systems, and to drive new experiments. Nevertheless, many experimentalists still consider simulations an esoteric discipline only for initiates. Suspicion towards simulations should dissipate as the limitations and advantages of their application are better appreciated, opening the door to their permanent adoption in everyday research.

Synthetic microbiology applications powered by light.

Synthetic biology is a field of research in which molecular parts (mostly nucleic acids and proteins) are de novo created or modified and then used either alone or in combination to achieve new functions that can help solve the problems of our modern society. In synthetic microbiology, microbes are employed rather than other organisms or cell-free systems. Optogenetics, a relatively recently established technology that relies on the use of genetically encoded photosensitive proteins to control biological processes with high spatiotemporal precision, offers the possibility to empower synthetic (micro)biology applications due to the many positive features that light has as an external trigger. In this review, we describe recent synthetic microbiology applications that made use of optogenetics after briefly introducing the molecular mechanism behind some of the most employed optogenetic tools. We highlight the power and versatility of this technique, which opens up new horizons for both research and industry.

Experimental Characterization of In Silico Red-Shift-Predicted iLOVL470T/Q489K and iLOVV392K/F410V/A426S Mutants.

iLOV is a flavin mononucleotide-binding fluorescent protein used for in vivo cellular imaging similar to the green fluorescent protein. To expand the range of applications of iLOV, spectrally tuned red-shifted variants are desirable to reduce phototoxicity and allow for better tissue penetration. In this report, we experimentally tested two iLOV mutants, iLOVL470T/Q489K and iLOVV392K/F410V/A426S, which were previously computationally proposed by (KhrenovaJ. Phys. Chem. B2017, 121 ( (43), ), pp 10018-10025) to have red-shifted excitation and emission spectra. While iLOVL470T/Q489K is about 20% brighter compared to the WT in vitro, it exhibits a blue shift in contrast to quantum mechanics/molecular mechanics (QM/MM) predictions. Additional optical characterization of an iLOVV392K mutant revealed that V392 is essential for cofactor binding and, accordingly, variants with V392K mutation are unable to bind to FMN. iLOVL470T/Q489K and iLOVV392K/F410V/A426S are expressed at low levels and have no detectable fluorescence in living cells, preventing their utilization in imaging applications.

Deterministic Lateral Displacement Microfluidic Chip for Minicell Purification.

Deterministic lateral displacement (DLD) is a well-known microfluidic technique for particle separation with high potential for integration into bioreactors for therapeutic applications. Separation is based on the interaction of suspended particles in a liquid flowing through an array of microposts under low Reynolds conditions. This technique has been used previously to separate living cells of different sizes but similar shapes. Here, we present a DLD microchip to separate rod-shaped bacterial cells up to 10 µm from submicron spherical minicells. We designed two microchips with 50 and 25 µm cylindrical posts and spacing of 15 and 2.5 µm, respectively. Soft lithography was used to fabricate polydimethylsiloxane (PDMS) chips, which were assessed at different flow rates for their separation potential. The results showed negligible shear effect on the separation efficiency for both designs. However, the higher flow rates resulted in faster separation. We optimized the geometrical parameters including the shape, size, angle and critical radii of the posts and the width and depth of the channel as well as the number of arrays to achieve separation efficiency as high as 75.5% on a single-stage separation. These results pave the way for high-throughput separation and purification modules with the potential of direct integration into bioreactors.

Analysis of Slow-Cycling Variants of the Light-Inducible Nuclear Protein Export System LEXY in Mammalian Cells.

The optogenetic tool LEXY consists of the second light oxygen voltage (LOV) domain of Avena sativa phototropin 1 mutated to contain a nuclear export signal. It allows exporting from the nucleus with blue light proteins of interest (POIs) genetically fused to it. Mutations slowing the dark recovery rate of the LOV domain within LEXY were recently shown to allow for better depletion of some POIs from the nucleus in Drosophila embryos and for the usage of low light illumination regimes. We investigated these variants in mammalian cells and found they increase the cytoplasmic localization of the proteins we tested after illumination, but also during the dark phases, which corresponds to higher leakiness of the system. These data suggest that, when aiming to sequester into the nucleus a protein with a cytoplasmic function, the original LEXY is preferable. The iLEXY variants are, instead, advantageous when wanting to deplete the nucleus of the POI as much as possible.

Temporal control of the integrated stress response by a stochastic molecular switch.

Stress granules (SGs) are formed in the cytosol as an acute response to environmental cues and activation of the integrated stress response (ISR), a central signaling pathway controlling protein synthesis. Using chronic virus infection as stress model, we previously uncovered a unique temporal control of the ISR resulting in recurrent phases of SG assembly and disassembly. Here, we elucidate the molecular network generating this fluctuating stress response by integrating quantitative experiments with mathematical modeling and find that the ISR operates as a stochastic switch. Key elements controlling this switch are the cooperative activation of the stress-sensing kinase PKR, the ultrasensitive response of SG formation to the phosphorylation of the translation initiation factor eIF2α, and negative feedback via GADD34, a stress-induced subunit of protein phosphatase 1. We identify GADD34 messenger RNA levels as the molecular memory of the ISR that plays a central role in cell adaptation to acute and chronic stress.

A light way for nuclear cell biologists.

The nucleus is a very complex organelle present in eukaryotic cells. Having the crucial task to safeguard, organize and manage the genetic information, it must tightly control its molecular constituents, its shape and its internal architecture at any given time. Despite our vast knowledge of nuclear cell biology, much is yet to be unravelled. For instance, only recently we came to appreciate the existence of a dynamic nuclear cytoskeleton made of actin filaments that regulates processes such as gene expression, DNA repair and nuclear expansion. This suggests further exciting discoveries ahead of us. Modern cell biologists embrace a new methodology relying on precise perturbations of cellular processes that require a reversible, highly spatially confinable, rapid, inexpensive and tunEable external stimulus: light. In this review, we discuss how optogenetics, the state-of-the-art technology that uses genetically encoded light-sensitive proteins to steer biological processes, can be adopted to specifically investigate nuclear cell biology.

Expanding the SiMPl Plasmid Toolbox for Use with Spectinomycin/Streptomycin.

We recently developed the SiMPl plasmid toolbox, which is constituted by pairs of plasmids, generically indicated as pSiMPlx_N and pSiMPlx_C, which can be stably maintained in Escherichia coli with a single antibiotic x. The method exploits the split intein gp41-1 to reconstitute the enzyme conferring resistance toward the antibiotic x, whereby each enzyme fragment is expressed from one of the plasmids in the pair. pSiMPl plasmids are currently available for use with ampicillin, kanamycin, chloramphenicol, hygromycin, and puromycin. Here, we introduce another pair for use with spectinomycin/streptomycin, broadening the application spectrum of the SiMPl toolbox. To find functional splice sites in aminoglycoside adenylyltransferase, we apply a streamlined strategy looking exclusively at the flexibility of native cysteine and serine residues, which we first validated splitting the enzymes conferring resistance toward ampicillin, kanamycin, chloramphenicol, and hygromycin. This strategy could be used in the future to split other enzymes conferring resistance toward antibiotics.

A Novel Nanobody Precisely Visualizes Phosphorylated Histone H2AX in Living Cancer Cells under Drug-Induced Replication Stress.

Histone H2AX phosphorylated at serine 139 (γ-H2AX) is a hallmark of DNA damage, signaling the presence of DNA double-strand breaks and global replication stress in mammalian cells. While γ-H2AX can be visualized with antibodies in fixed cells, its detection in living cells was so far not possible. Here, we used immune libraries and phage display to isolate nanobodies that specifically bind to γ-H2AX. We solved the crystal structure of the most soluble nanobody in complex with the phosphopeptide corresponding to the C-terminus of γ-H2AX and show the atomic constituents behind its specificity. We engineered a bivalent version of this nanobody and show that bivalency is essential to quantitatively visualize γ-H2AX in fixed drug-treated cells. After labelling with a chemical fluorophore, we were able to detect γ-H2AX in a single-step assay with the same sensitivity as with validated antibodies. Moreover, we produced fluorescent nanobody-dTomato fusion proteins and applied a transduction strategy to visualize with precision γ-H2AX foci present in intact living cells following drug treatment. Together, this novel tool allows performing fast screenings of genotoxic drugs and enables to study the dynamics of this particular chromatin modification in individual cancer cells under a variety of conditions.

finDr: A web server for in silico D-peptide ligand identification.

In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation, resulting in a favourable pharmacokinetic profile. To experimentally identify D-peptide binders to interesting therapeutic targets, so-called mirror-image phage display is typically performed, whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage display. This technique is extremely powerful, but it requires the synthesis of the target in D-form, which is challenging for large proteins. Here we present finDr, a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure (https://findr.biologie.uni-freiburg.de/). finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank (PDB) for their ability to bind to the target. In a separate, heuristic approach to search the chemical space of 12-mer peptides, finDr executes a customizable evolutionary algorithm (EA) for the de novo identification or optimization of D-peptide ligands. As a proof of principle, we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3 (PSMα3), a toxin of methicillin-resistant Staphylococcus aureus (MRSA). We validate the predictions using in vitro binding assays, supporting the success of this approach. Compared to conventional methods, finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size limitation. We believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.