SEARCH · bioRxiv Science

Results for “Bioengineering”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19Linked to original sources

bioRxiv2022

Integrative Teaching of Metabolic Modeling and Flux Analysis with Interactive Python Modules

The modeling of rates of biochemical reactions - fluxes - in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint-based (Metabolic Flux Analysis and Flux Balance Analysis) approaches. Although different resources exist for teaching these methods individually, to-date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, Metabolic Control Analysis, l3C-Metabolic Flux Analysis and Flux Balance Analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands-on computer laboratory component of a four-day metabolic modeling workshop and participant survey results showed improvements in learners self-assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

scientific communication and education↗

bioRxiv2022

Sequence Controlled Secondary Structure Determines Site-selectivity of Lanthipeptides

Lanthipeptides are ribosomally synthesized and post-translationally modified peptides that are generated from precursor peptides through a dehydration and cyclization process in the biosynthetic pathways. In contrast to most other lanthipeptide synthetases, ProcM, a class II lanthipeptide synthetase, demonstrates high substrate tolerance. It is enigmatic that a single enzyme can catalyze the cyclization process of a diverse range of substrates with high fidelity. Previous studies suggested that the site-selectivity of lanthionine formation is determined by substrate sequence rather than by the enzyme. However, exactly how substrate sequence contributes to site-selective lanthipeptide biosynthesis is not clear. In this study, we performed molecular dynamic simulations for ProcA3.3 core peptide variants to explore how the predicted solution structure of the substrate without enzyme correlates to final product formation. Our simulation results support a model in which the secondary structure of the core peptide controls the ring pattern of the final product. We also demonstrate that the dehydration step in the biosynthesis pathway does not influence the site-selectivity of ring formation. In addition, we performed simulation for the core peptides of ProcA1.1 and 2.8, which are well-suited candidates to investigate the connection between order of ring formation and solution structure. Simulation results indicate that in both cases, C-terminal ring formation is more likely which was supported by experimental results. Our findings indicate that the substrate sequence and its solution structure can be used to predict the site-selectivity and order of ring formation, and that secondary structure is a crucial factor influencing the site-selectivity. Taken together, these findings will facilitate our understanding of the lanthipeptide biosynthetic mechanism and accelerate bioengineering efforts for lanthipeptide-derived products.

biophysics↗

bioRxiv2022

Dystrophin is a mechanical tension modulator

Duchenne muscular dystrophy (DMD) represents the most common inherited muscular disease, where progressing muscle weakness leads to loss of ambulation and premature death. DMD is caused by mutations in the dystrophin gene, and is known to reduce the contractile capacity of muscle tissue both in vivo, and in reconstituted systems in vitro. However, these observations are based on mechanical studies that focused on stimulated contractions of skeletal muscle tissue. Seemingly paradoxical, upon evaluating bioengineered skeletal muscles produced from DMD patient derived myoblasts we observe an increase in myosin motor mediated homeostatic tissue tension that strongly correlates with decreased stimulated tissue strength, suggesting the involvement of dystrophin in regulating the baseline homeostatic tension level of tissue. This was confirmed by three independent pairs of isogenic cell lines, one of each lacking dystrophin compared to the isogenic dystrophin-expressing control. From this we speculate that the protective function of dystrophin also supports cellular fitness via active participation in the mechanosensation to achieve and sustain an ideal level of tissue tension. Hence, this study reveals fundamental novel insights into skeletal muscle biomechanics and into a new key mechanical aspect of DMD pathogenesis, provided by increased homeostatic tissue tension.

biophysics↗

bioRxiv2022

Structural basis for the ligand promiscuity of the neofunctionalized, carotenoid-binding fasciclin domain protein AstaP

Fasciclins (FAS1) are ancient adhesion protein domains found across different phyla from bacteria to humans, with no common small ligand binding function reported. A unique FAS1-containing astaxanthin-binding protein (AstaP) from green algae can efficiently bind an unusually broad repertoire of carotenoids (astaxanthin, zeaxanthin, canthaxanthin, {beta}-carotene), but the underlying mechanism is largely unknown. Here we dissect the structural basis for the ligand binding promiscuity of AstaP-orange1 (AstaPo1) by determining its solution NMR structure in complex with its natural ligand, astaxanthin (AXT), and validate this structure by SAXS, calorimetry, optical spectroscopy and mutagenesis data. While the unstructured tails of AstaPo1 are not essential for carotenoid binding, they enhance protein solubility. The a1-a2 helices of the AstaPo1 FAS1 domain embrace the carotenoid polyene like a jaw, organizing a conserved hydrophobic tunnel, too short to prevent the AXT {beta}-ionone rings from protruding on both sides of the tunnel, thereby not imposing specificity restrictions. The only specific protein-AXT interactions involve H-bonds between the oxygenated groups on AXT and a peripheral Gln56 residue. Remarkably, mapping of this and other AXT-contacting AstaPo1 residues revealed their different conservation in AstaP orthologs with the tentative carotenoid-binding function and in FAS1 proteins in general, supporting neofunctionalization of AstaPs within green algae. Correspondingly, a cyanobacterial homolog with a similar domain structure cannot bind carotenoids due to subtle differences in residues decorating the tunnel. These structure-activity relationships inform the sequence-based prediction of the carotenoid-binding FAS1 members. SIGNIFICANCEA water-soluble astaxanthin-binding protein (AstaP) is a photoprotective protein in green algae helping them to tolerate stress conditions. While belonging to a ubiquitous protein family sharing an ancient structural domain, fasciclin, involved in cell adhesion, AstaP possesses an outstanding ability to bind carotenoid pigments of a different type, which are potent antioxidants. To understand the molecular basis for such carotenoid-binding promiscuity of AstaP, here we determined its spatial structure - the first structure of a carotenoid-protein complex solved by nuclear magnetic resonance spectroscopy. Together with biochemical and sequence conservation analyses, our data illustrate a remarkable case of neofunctionalization of the ancient protein domain and pave the way for its bioengineering and practical use as antioxidant transporter for biomedical applications.

biochemistry↗

bioRxiv2023

Information integration during bioelectric regulation of morphogenesis in the embryonic frog brain

Spatiotemporal bioelectric states regulate multiple aspects of embryogenesis. A key open question concerns how specific multicellular voltage potential patterns differentially activate distinct downstream genes required for organogenesis. To understand the information processing mechanisms underlying the relationship between spatial bioelectric patterns, genetics, and morphology, we focused on a specific spatiotemporal bioelectric pattern in the Xenopus ectoderm that regulates embryonic brain patterning. We used machine learning to design a minimal but scalable bioelectric-genetic dynamical network model of embryonic brain morphogenesis that qualitatively recapitulated previous experimental observations. A causal integration analysis of the model revealed a simple higher-order spatiotemporal information integration mechanism relating the spatial bioelectric and gene activity patterns, where the latter is expressed as a function of the causal influence of the voltages of groups of cells. Specific aspects of this mechanism include causal apportioning (certain cell positions are more important for collective decision making), informational asymmetry (depolarized cells are more influential than hyperpolarized cells), long distance influence (genes in a cell are variably sensitive to voltage of faraway cells), and division of labor (different genes are sensitive to different aspects of voltage pattern). The asymmetric information-processing character of the mechanism led the model to predict an unexpected degree of plasticity and robustness in the bioelectric prepattern that regulates normal embryonic brain development. Our in vivo experiments verified these predictions via molecular manipulations in Xenopus embryos. This work shows the power of using a minimal in silico approach to drastically reduce the parameter space in vivo, making hard biological questions tractable. These results provide insight into the collective decision-making process of cells in interpreting bioelectric pattens that guide large-scale morphogenesis, suggesting novel applications for biomedical interventions and new tools for synthetic bioengineering.

developmental biology↗

bioRxiv2023

At-home, cell-free synthetic biology education modules for transcriptional regulation and environmental water quality monitoring

As the field of synthetic biology expands, the need to grow and train science, technology, engineering, and math (STEM) practitioners is essential. However, the lack of access to hands-on demonstrations has led to inequalities of opportunity and practice. In addition, there is a gap in providing content that enables students to make their own bioengineered systems. To address these challenges, we develop four shelf-stable cell-free biosensing educational modules that work by just-adding-water and DNA to freeze-dried crude extracts of Escherichia coli. We introduce activities and supporting curricula to teach the structure and function of the lac operon, dose-responsive behavior, considerations for biosensor outputs, and a build-your-own activity for monitoring environmental contaminants in water. We piloted these modules with K-12 teachers and 130 high school students in their classrooms - and at home - without professional laboratory equipment or researcher oversight. This work promises to catalyze access to interactive synthetic biology education opportunities.

synthetic biology↗

bioRxiv2023

FLInt: Single Shot Safe Harbor Transgene Integration via Fluorescent Landmark Interference

The stable incorporation of transgenes and recombinant DNA material into the host genome is a bottleneck in many bioengineering applications. Due to the low efficiency, identifying the transgenic animals is often a needle in the haystack. Thus, optimal conditions require efficient screening procedures, but also known and safe landing sites that do not interfere with host expression, low input material and strong expression from the new locus. Here, we leverage an existing library of{approx} 300 different loci coding for fluorescent markers that are distributed over all 6 chromosomes in Caenorhabditis elegans as safe harbors for versatile transgene integration sites using CRISPR/Cas9. We demonstrated that a single crRNA was sufficient for cleavage of the target region and integration of the transgene of interest, which can be easily followed by loss of the fluorescent marker. The same loci can also be used for extrachromosomal landing sites and as co-CRISPR markers without affecting body morphology or animal behavior. Thus, our method overcomes the uncertainty of transgene location during random mutagenesis, facilitates easy screening through fluorescence interference and can be used as co-CRISPR markers without further influence in phenotypes.

genetics↗

bioRxiv2023

Assessing the functional impact of protein binding site definition

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data this approach generates, it also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also provides guidance on the minimum expected accuracy of interface definition that is required to capture the biological function of a protein. AUTHOR SUMMARYThe residue level description or prediction of protein interfaces is a critical input for protein engineering and classification of function. However, different parametrizations of the same methods and especially alternative methods used to define the interface of a protein can return substantially different sets of residues. Typical experimental or computational methods employ mutational studies to verify interface definitions, but all these approaches inherently suffer from the problem that in order to probe the importance of any one position of an interface, an unknown amount of alteration is introduced into the very interface being studied. In this work, we employ a pharmacophore-based approach to computationally explore the consequences of defining alternative binding sites. The pharmacophore generates a hypothesis for the complementary protein binding interface, which then can be used in a search to identify the corresponding ligand from a library of candidates. The accurate ranking of cognate ligands can inform us about the biological accuracy of the interface definition. This study also provides a guideline about the minimum required accuracy of protein interface definitions that still provides a statistically significant recognition of cognate ligands above random expectation, which in turn sets a minimum expectation for interface prediction methods.

bioinformatics↗

bioRxiv2023

Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate

Loss of muscle stem cell (MuSC) self-renewal with aging reflects a combination of influences from the intracellular (e.g., post-transcriptional modifications) and extracellular (e.g., matrix stiffness) environment. Whereas conventional single cell analyses have revealed valuable insights into factors contributing to impaired self-renewal with age, most are limited by static measurements that fail to capture nonlinear dynamics. Using bioengineered matrices mimicking the stiffness of young and old muscle, we showed that while young MuSCs were unaffected by aged matrices, old MuSCs were phenotypically rejuvenated by young matrices. Dynamical modeling of RNA velocity vector fields in silico revealed that soft matrices promoted a self-renewing state in old MuSCs by attenuating RNA decay. Vector field perturbations demonstrated that the effects of matrix stiffness on MuSC self-renewal could be circumvented by fine-tuning the expression of the RNA decay machinery. These results demonstrate that post-transcriptional dynamics dictate the negative effect of aged matrices on MuSC self-renewal. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/529950v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1a840corg.highwire.dtl.DTLVardef@d354cforg.highwire.dtl.DTLVardef@650556org.highwire.dtl.DTLVardef@41587c_HPS_FORMAT_FIGEXP M_FIG Graphical abstract description: The balance of self-renewal and differentiation in young muscle stem cells (MuSCs) is robust to perturbations of the biophysical microenvironment. In contrast, aged MuSCs are highly sensitive to extrinsic perturbations, and exposure to a youthful microenvironment rejuvenates the self-renewing potential of aged MuSCs by modulating post-transcriptional RNA dynamics. C_FIG

cell biology↗

bioRxiv2023

Label-free Quantification of Host-Cell Protein Impurity in a Recombinant Hemoglobin Reference Material

Quantitative analysis depends on pure-substance primary calibrators with known mass fractions of impurity. Here, label-free quantification (LFQ) is being evaluated as a readily available, reliable method for determining the mass fraction of host-cell proteins (HCPs) in bioengineered proteins. For example, hemoglobin-A2 (HbA2) is being used as obtained through overexpression in E.coli. Two different materials had been produced: natural, and U-15N-labeled HbA2. For quantification of impurity, precursorion (MSl-) intensities were integrated over all E.coli -proteins identified, and divided by the intensities obtained for HbA2. This ratio was calibrated against the corresponding results for E.coli-cell lysate, which had been spiked at known mass-ratios to pure HbA2. To demonstrate the universal applicability of LFQ, further proteomes (yeast and human K562) were then alternatively used for calibration and found to produce comparable results. Valid results could also be obtained when the complexity of the calibrator is reduced to a mix of nine proteins, and a minimum of five proteins is estimated to be sufficient to keep the sampling error below l5%. For the studied materials, HbA2-mass fractions of 916{+/-}15 mg/g and 922{+/-}11 mg/g were found. Value assignment by LFQ thus contributes 1-2% to the overall uncertainty of HbA2-quantification when these materials are used as calibrators. Further purification of the natural HbA2 yielded 999.1{+/-} 0.15 mg/g, corresponding to {approx} 0.2% of uncertainty contribution, though at a significant loss of material. If an overall-uncertainty of 5% is acceptable for protein-quantification, working with the original materials would definitely be viable, therefore.

biochemistry↗

bioRxiv2023

ATP-induced crosslinking of a biomolecular condensate

DEAD-box helicases are important regulators of biomolecular condensates. However, the mechanisms through which these enzymes affect the dynamics of biomolecular condensates have not been systematically explored. Here, we demonstrate the mechanism by which mutation of a DEAD-box helicases catalytic core alters ribonucleoprotein condensate dynamics in the presence of ATP. Through altering RNA length within the system, we are able to attribute the altered biomolecular dynamics and material properties to physical crosslinking of RNA facilitated by the mutant helicase. These results suggest the mutant condensates approach a gel transition when RNA length is increased to lengths comparable to eukaryotic mRNA. Lastly, we show that this crosslinking effect is tunable with ATP concentration, uncovering a system whose RNA mobility and material properties vary with enzyme activity. More generally, these findings point to a fundamental mechanism for modulating condensate dynamics and emergent material properties through nonequilibrium, molecular-scale interactions. SignificanceBiomolecular condensates are membraneless organelles which organize cellular biochemistry. These structures have a diversity of material properties and dynamics which are crucial to their function. How condensate properties are determined by biomolecular interactions and enzyme activity remain open questions. DEAD-box helicases have been identified as central regulators of many protein-RNA condensates, though their specific mechanistic roles are ill-defined. In this work, we demonstrate that a DEAD-box helicase mutation crosslinks condensate RNA in an ATP-dependent fashion via protein-RNA clamping. Protein and RNA diffusion can be tuned with ATP concentration, corresponding to an order of magnitude change in condensate viscosity. These findings expand our understanding of control points for cellular biomolecular condensates that have implications for medicine and bioengineering.

biophysics↗

bioRxiv2023

Engineering genetic circuits in receiver cells for diffusion-based molecular data communications

Developments in bioengineering and nanotechnology have ignited the research on biological and molecular communication systems. Despite potential benefits, engineering communication systems to carry data signals using biological messenger molecules is challenging. Diffusing molecules may fall behind their schedule to arrive at a receiver, interfering with symbols of subsequent time slots and distorting the signal. Theoretical molecular communication models often focus solely on the characteristics of the communication channel and fail to provide an end-to-end system response, since they assume a simple thresholding process for a receiver cell and overlook how the receiver can detect the incoming distorted molecular signal. There is a need to develop viable end-to-end communication models. In this paper, we present a model-based framework for designing diffusion-based molecular communication systems coupled with synthetic genetic circuits. We describe a novel approach to encode information as a sequence of bits, each transmitted from a sender as a burst of specific number of molecules, control cellular behavior, and minimize cellular signal interference by employing equalization techniques from communication theory. This approach allows the encoding and de-coding of data bits efficiently using two different types of molecules that act as the data carrier and the antagonist to cancel out the heavy tail of the former. We also present Period Finder, as a tool to optimize communication parameters, including the number of molecules and symbol duration. This tool facilitates automating the choice of communication parameters and identifying the best communication scenarios that can produce efficient cellular signals.

synthetic biology↗

bioRxiv2023

Growth balance analysis models of cyanobacteria for understanding resource allocation strategies

Cyanobacteria have emerged as attractive microbial cell factories, as they can convert atmospheric CO2 and sunlight into valuable chemicals. To increase their growth and productivity, one should aim to optimize the allocation of limited cellular resources across different metabolic processes. Here, we developed two growth balance analysis (GBA) models for the cyanobacterium Synechocystis sp. PCC 6803. In its biological assumptions, the models closely related to an existing coarse-grained model, while its mathematical formulation is heavily streamlined. We show that the GBA models provide virtually identical predictions about cellular resource allocation among photosynthesis, carbon metabolism, and the protein translation machinery under different environmental conditions as the previous, mathematically more involved model. Our model also captures the effects of photodamage on proteome allocation and the resulting growth rates. We further show how the GBA model can be easily extended to include more reactions, leading to a second GBA model capable of new predictions about the cellular resource allocation. Balanced growth models of the type presented here can easily expanded to include more biological details, providing a useful toolbox for the understanding of the physiological capabilities of cyanobacteria, their allocation of cellular resources, and the potential of their bioengineering for optimized biomass production.

systems biology↗

bioRxiv2023

Mass spectrometry imaging of natural carbonyl products directly from agar-based microbial interactions using 4-APEBA derivatization

Aliphatic carboxylic acids, aldehydes, and ketones play diverse roles in microbial adaptation to their microenvironment, from excretion as toxins to adaptive metabolites for membrane fluidity. However, the spatial distribution of these molecules throughout biofilms, and how microbes in these environments exchange these molecules remains elusive for many of these bioactive species due to inefficient molecular imaging strategies. Herein, we apply on-tissue chemical derivatization (OTCD) using 4-(2-((4-bromophenethyl)dimethylammonio)ethoxy)benzenaminium bromide (4-APEBA) on a co-culture of a soil bacterium (Bacillus subtilis NCIB 3610) and fungus (Fusarium sp. DS 682) grown on agar as our model system. Using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), we spatially resolved more than 300 different metabolites containing carbonyl-groups within this model system. Various spatial patterns are observable of these species, which indicate possible extracellular or intercellular processes of the metabolites, and their up or down regulation during microbial interaction. The unique chemistry of our approach allowed us to bring additional confidence in accurate carbonyl identification, especially when multiple isomeric candidates were possible, and this provided the ability to generate hypotheses about the potential role of some aliphatic carbonyls in this B. subtilis/Fusarium sp. interaction. The results shown here demonstrate the utility of 4-ABEBA-based OCTD MALDI-MSI in probing interkingdom interactions directly from microbial co-cultures, and these methods will enable future microbial interactions studies with expanded metabolic coverage. IMPORTANCEThe metabolic profiles within microbial biofilms and interkingdom interactions are extremely complex and serve a variety of functions, which include promoting colonization, growth, and survival within competitive and symbiotic environments. However, measuring and differentiating many of these molecules, especially in an in-situ fashion, remains a significant analytical challenge. We demonstrate a chemical derivatization strategy that enabled highly sensitive, multiplexed mass spectrometry imaging of over 300 metabolites from a model microbial co-culture. Notably, this approach afforded us to visualize over two dozen classes of ketone-, aldehyde-, and carboxyl-containing molecules, which were previously undetectable from colonies grown on agar. We also demonstrate that this chemical derivatization strategy can enable discrimination of isobaric and isomeric metabolites, without the need for orthogonal separation (e.g., online chromatography or ion mobility). We anticipate this approach will further enhance our knowledge of metabolic regulation within microbiomes and microbial systems used in bioengineering applications.

biochemistry↗

bioRxiv2023

Cytosolic iron-sulfur protein assembly system identifies clients by a C-terminal tripeptide

The eukaryotic cytosolic Fe-S protein assembly (CIA) machinery inserts iron-sulfur (Fe-S) clusters into cytosolic and nuclear proteins. In the final maturation step, the Fe-S cluster is transferred to the apo-proteins by the CIA-targeting complex (CTC). However, the molecular recognition determinants of client proteins are unknown. We show that a conserved [LIM]-[DES]-[WF]-COO- tripeptide present at the C-terminus of clients is necessary and sufficient for binding to the CTC in vitro and directing Fe-S cluster delivery in vivo. Remarkably, fusion of this TCR (target complex recognition) signal enables engineering of cluster maturation on a non-native protein via recruitment of the CIA machinery. Our study significantly advances our understanding of Fe-S protein maturation and paves the way for bioengineering applications. One-Sentence SummaryA C-terminal tripeptide guides eukaryotic iron-sulfur cluster insertion into cytosolic and nuclear proteins.

biochemistry↗

bioRxiv2023

Discovery of new deaminase functions by structure-based protein clustering

The elucidation of protein function and its exploitation in bioengineering have greatly contributed to the development of the life sciences. Existing protein mining efforts generally rely on amino acid sequences rather than protein structures due to technical difficulties in structural elucidation. We describe here for the use of AlphaFold2 to predict and subsequently cluster an entire protein family based on predicted structure similarities. We selected the deaminase family of proteins to analyze and through this approach identified many previously unknown deaminase properties. We applied these new deaminases to the development of new cytosine base editors with distinct features. Although we found many new double-stranded DNA deaminases from the DddA-like protein clade, we were surprised to find that most of the proteins in this family were not actually double-stranded DNA cytidine deaminases. From this protein clade, we engineered the smallest single-strand specific cytidine deaminase, which facilitates the first efficient cytosine base editor to be packaged into a single AAV vector. Importantly, we also profiled a deaminase from this clade that edits robustly in soybean plants, which previously suffered from poor editing by cytosine base editors. These newly discovered deaminases based on AI-assisted structural predictions greatly expand the utility of base editors for therapeutic and agricultural applications.

molecular biology↗

bioRxiv2023

Meta-omics analyses of dual substrate enrichment culturing of nitrous oxide respiring bacteria suggest that attachment and complex polysaccharide utilisation contributed to the ability of Cloacibacterium strains to reach dominance

Bioengineering soil metabolism by inoculation is an emerging approach to enhance plant growth and strengthen specific functions such as N2O reduction in order to reduce climate forcing. The use of organic wastes as substrates and carriers of microbial biomass has proven to be a viable approach to improving effectiveness and economic viability. A key factor in the success of this approach lies in selection of microbes capable of growth and survival in both organic wastes as well as soils, and which are tolerant of the rapid environmental fluctuations such fertilisations involve. A dual substrate, N2O-enrichment experiment, switching between soil and organic waste as substrates has yielded Cloacibacterium isolates which grow well in organic wastes and retain significant N2O reduction capacity when applied to soils. However, an understanding of the genetic and phenotypic characteristics utilised by these enrichment winners to dominate under such conditions remains unexplored. Here we have performed a multi-omics examination of the enrichment cultures, using both metagenomics and metaproteomics to probe the genetic basis and expressed proteins which may contribute to the success of Cloacibacterium in the enrichments, and their survival in soil. These omics results show an increase in complex carbohydrate metabolism, chemotaxis and motility genes throughout the enrichment as well as the expression of gliding motility proteins and polysaccharide utilization loci proteins by Cloacibacterium organisms. Taken together this suggests that attachment and complex polysaccharide utilisation may be key processes allowing Cloacibacterium to tolerate the stresses of a changing environment during transfers between digestate and soil.

microbiology↗

bioRxiv2023

Engineering cell and nuclear morphology on nano topography by contact-free protein micropatterning

Platforms with nanoscale topography have recently become powerful tools in cellular biophysics and bioengineering. Recent studies have shown that nanotopography affects various cellular processes like adhesion and endocytosis, as well as physical properties such as cell shape. To engineer nanopillars more effectively for biomedical applications, it is crucial to gain better control and understanding of how nanopillars affect cell and nuclear physical properties, such as shape and spreading area, and impact cellular processes like endocytosis and adhesion. In this study, we utilized a laser-assisted micropatterning technique to manipulate the 2D architectures of cells on 3D nanopillar platforms. We performed a comprehensive analysis of cellular and nuclear morphology and deformation on both nanopillar and flat substrates. Our findings demonstrate precise engineering of cellular architectures through 2D micropatterning on nanopillar platforms. We show that the coupling between nuclear and cell shape is disrupted on nanopillar surfaces compared to flat surfaces. Furthermore, we discovered that cell elongation on nanopillars enhances nanopillar-induced endocytosis. These results have significant implications for various biomedical applications of nanopillars, including drug delivery, drug screening, intracellular electrophysiology, and biosensing. We believe our platform serves as a versatile tool for further explorations, facilitating investigations into the interplay between cell physical properties and alterations in cellular processes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/543791v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1b3a13dorg.highwire.dtl.DTLVardef@1edbdaorg.highwire.dtl.DTLVardef@1f3e40corg.highwire.dtl.DTLVardef@100d6fc_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗