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bioRxiv2025

Identification and characterization of host-directed therapeutics for tuberculosis using a versatile human 3D tuberculoma bioplatform

Host-directed therapies (HDT) represent a pivotal strategy in combating both drug-susceptible and drug-resistant tuberculosis (TB). Current evaluations, however, show limited success in animal models and clinical settings, emphasizing the need for more effective HDT candidates. With few druggable targets validated within granulomas, it is essential to verify the effectiveness of HDT candidates identified through traditional macrophage cultures in the context of the tuberculous granuloma milieus. Bioengineering a scalable, high-throughput screening (HTS) platform that replicates the physiological microenvironments in the hallmark tubercular lesions could significantly improve the identification of relevant HDT candidates and new treatment strategies. Here, we developed a facile, HTS-compatible bioplatform that generates tuberculoma-emulating structures, following three-dimensional (3D) co-cultures of human cells and pathogenic mycobacteria. Employing high-content imaging alongside immunological and transcriptomic approaches, we demonstrated that these 3D structures exhibit classic tuberculoma attributes and develop crucial transformations. Utilizing this system, we screened antibody biosimilars and potential HDT compounds. Our findings demonstrate the systems versatility in discovering antimicrobials and HDT candidates that effectively reduce mycobacterial burdens and granuloma lesions, while elucidating their immune mechanisms within 3D milieus. Many compounds effective in two-dimensional (2D) cultures were ineffective once granulomas formed in our 3D model. Notably, several promising compounds were found to induce rapid autophagy flux, and we validated the effectiveness of one such compound, the multi-kinase inhibitor AT9283, in a mouse model. Our findings highlight several HDT candidates for potential repurposing in TB treatment, offering a robust tool for accelerating therapeutic discoveries and advancing translational research for TB and other granulomatous diseases. SummarySafer and shorter treatment regimens for tuberculosis (TB) are urgently needed. Host-directed therapies (HDT) are being explored to enhance antibiotic regimens and address antimicrobial resistance. To expedite the discovery of HDT candidates and the development of new treatment strategies, scalable in vitro systems are needed that can replicate the critical features and microenvironments of TB lesions in a format compatible with high-throughput screening (HTS). We developed an HTS-compatible bioplatform using 3D co-cultures of human cells and fluorescent mycobacteria, creating tuberculoma-like structures with classic solid, necrotic, and cavitary transformations that exhibit crucial microenvironments. This facile system enabled us to screen antibody biosimilars and HDT compounds in 3D human in vitro tuberculomas, identifying candidates that inhibited mycobacterial growth and granuloma lesions while revealing potential innate immune mechanisms. The study revealed several promising HDT candidates that could be repurposed for TB treatment, introducing a versatile tool for screening therapeutic libraries. Additionally, it presents a framework for enhancing human in-vitro granuloma models, as advances in tissue-like systems emerge to recapitulate the architecture and multilineage differentiation in the lungs.

immunology↗

bioRxiv2025

Simulating C3-to-CAM transition under ancient atmospheric conditions

Crassulacean Acid Metabolism (CAM) plants have very low water demand and can survive in arid environment. It is hypothesized to evolve from C3 metabolism about 20 to 30 million years ago (MYA) when the Earth faced declining atmospheric CO2 concentration ([CO2]a), increasing aridity and decreasing temperature. Understanding whether and how these atmospheric changes favour C3-to-CAM transition will help in bioengineering CAM into crop plants to tackle the threat of global climate change and ensure food security. Our simulations of plant cellular metabolism under the changing atmospheric conditions of ancient times observe C3-to-CAM transition, capture possible temporal alterations of active metabolic pathways and further confirm that both the reduced [CO2]a and increased water scarcity associated with higher aridity, can act as evolutionary agents, driving the C3-to-CAM transition. Although the predicted elevated [CO2]a of future reveals a reversion towards C3-like behaviour, drought always favours CAM regardless of [CO2]a and temperature levels. Moreover, a minimum oxygen concentration is required to sustain elevated nocturnal respiration necessary for CAM, reflected by the increased activities of enzymes involved in the TCA cycle and the mitochondrial electron transport chain.

plant biology↗

bioRxiv2025

Expression screening and functional verification of recombinant hirudin from novel chassis cell Chlamydomonas reinhardtii

Hirudin is a potent anticoagulant peptide whose clinical application is limited by scarce natural supplies and the suboptimal activity of recombinant versions from conventional microbial hosts lacking key post-translational modifications. Here, for the first time, we establish the "Generally Regarded as Safe" (GRAS) microalga, Chlamydomonas reinhardtii, as a novel biological chassis for producing fully functional hirudin. Using high-density heterotrophic fermentation, we generated a bioactive lyophilized algal powder suitable for oral delivery. Crucially, the algal-derived hirudin underwent proper tyrosine sulfation--a key modification absent in prokaryotic hosts--conferring exceptionally high thrombin-inhibitory activity (up to 20,000 ATU/mg). When orally administered to a murine thrombosis model, this hirudin-loaded alga demonstrated potent antithrombotic efficacy. It also exhibited a superior safety profile, showing no signs of the thrombocytopenia or bleeding associated with traditional anticoagulants. This study establishes a green, scalable biomanufacturing and oral delivery platform for therapeutics, highlighting transformative potential at the nexus of agricultural bioengineering, functional foods, and biomedicine.

synthetic biology↗

bioRxiv2025

Recombinant Lactococcus lactis-based multivalent vaccine targeting Campylobacter jejuni colonisation and modulating cecal microbiota in poultry

BackgroundDiarrhoeal diseases remain the second leading cause of preventable death globally, particularly among children under the age of five in developing countries, accounting for an estimated 2-3 million deaths annually. Among the bacterial pathogens causing diarrheal illness, Campylobacter jejuni (C. jejuni) remains one of the major contributors, particularly in LMICs. As a common gut pathogen, C. jejuni expresses several secretory or surface-expressed colonisation proteins, namely Hcp, VgrG, CadF, FlpA, and JlpA. Most of these proteins play pivotal roles in bacterial self-survival, host-cell adhesion, and invasion in avian and non-avian hosts. MethodsTo minimise the C. jejuni adhesion and subsequent colonisation in the avian gut, we explored the potential of a multivalent mucosal vaccine composition using these putative subunits of C. jejuni. For this purpose, we bioengineered a food-grade Lactic Acid-producing Bacterium, Lactococcus lactis (L. lactis), to express three key immunogenic subunits, Hcp, CadF and JlpA. Utilising this live vector-based multi-component mucosal vaccine platform, we investigated the immunoprotective potential of these antigens in chickens. Since the particular strain of L. lactis is non-colonising, we used chitosan as a natural mucoadhesive, biodegradable polymer to microencapsulate the engineered bacteria to increase their gut retention time for optimal interaction with local immune cells. ResultsOur in vivo immunisation study demonstrated that oral administration of this multivalent vaccine formulation elicited a strong local antibody response (sIgA) and upregulated key pro-inflammatory cytokines, leading to robust mucosal immune protection against the cecal colonisation of C. jejuni. Moreover, gut metagenomic analysis of vaccinated birds revealed a marked reduction in the phylum Campylobacterota, accompanied by an increased abundance of the phyla Bacillota and Bacteroidota, as part of a beneficial microbial community. ConclusionsTogether, this study underscores the potential of a live vector-based, multivalent mucosal vaccine as a promising, cost-effective strategy to reduce the risk of foodborne transmission of C. jejuni, particularly in poultry production systems.

immunology↗

bioRxiv2025

Genotype-phenotype modeling of light ecotypes in Prochlorococcusreveals genomic signatures of ecotypic divergence

Prochlorococcus species are the most abundant marine photosynthetic bacteria. Despite broadly shared phenotypic traits and marine habitats, they exhibit remarkable genomic diversity. We ask what genomic signatures underlie its ecotypic divergence into high- and low-light adapted lineages, and whether these signatures can still be recovered from incomplete assemblies. From [~]1,000 publicly available Prochlorococcus genomes, we focused on those with information on their light adaptation ecotype (high-light/low-light), phylogenetic clades, and depth of isolation. Across these divisions, we calculated average nucleotide identity and constructed pangenomes to assess cyanobacterial core genes vs. those that separate ecotypes. Despite scant conservation, we observe a sharp taxon separation by light ecotypes. Classical machine learning models trained to predict ecotype achieve near-perfect binary classification accuracy even when predicting on partial genomes (Matthews Correlation Coefficient = 0.86 - 1.00), while regression models trained to predict the depth of isolation performed poorly, with high root mean square error values (37.6 - 42.0m). For ecotype prediction, we analyzed top gene features across model runs and classes; these features included photosynthesis-associated genes and pathways, as well as many novel markers of unknown function. When separating ecotypes further by previously described phylogenetic clades, genomic content and composition show even clearer separation among clades, supporting the taxonomic breadth of the Prochlorococcus collective. These results emphasize the genomic specialization underlying ecotypic divergence and support the utility of ML approaches for cyanobacterial ecotype prediction from metagenomic data. Expanded sampling will yield novel clade-specific biology. All data, models, and results are available on GitHub: https://github.com/JRaviLab/cyano_adaptation. ImportanceProchlorococcus are common aquatic cyanobacteria that can derive energy from light. They can be classified into high-/low-light ecotypes depending on how they use light. Prochlorococcus have small genomes compared to other bacteria, but the gene sets they carry are also remarkably flexible, which may help them survive and adapt to their harsh oceanic environment. We studied hundreds of Prochlorococcus genomes from around the world in an effort to predict ecotypes from partial genome sequences. We used comparative genomics, machine learning, and other statistical methods to identify genomic features associated with ecotypes. These statistical approaches predicted ecotypes accurately, reliably, and according to large differences in gene content and genome structure. Our results support that Prochlorococcus can be divided into different species or genera based on clades, and provide many gene targets for further research to understand cyanobacterial circadian rhythms or improve their bioengineering potential as chassis organisms.

bioinformatics↗

bioRxiv2025

Tumor cell dissemination is facilitated through regulatory T cell-driven extracellular matrix remodeling

Regulatory T (Treg) cells function to enforce peripheral tolerance and are potent suppressors of tumor immunity. In breast cancer, we have shown that Treg cells promote tumor growth by favoring alternative activation of macrophages via suppression of IFN-{gamma}. The tumor-associated extracellular matrix (ECM) is a key regulator of metastatic dissemination and is emerging as a critical regulator of tumor immunity. However, the reciprocal effects of the immune system on the ECM remain elusive. Using a combination of murine in vivo, ex vivo and bioengineering models we describe Treg cell-dependent changes in the tumor ECM that facilitate tumor cell migration and metastatic dissemination. Importantly, Treg cell-dependent matrisome signatures correlate with delayed survival advantage in human breast cancer samples, and are upregulated in tumor-associated macrophages (TAMs). Further, both IFN-{gamma} and IFN-{gamma}-sensitivity in TAMs contribute to structural and functional changes of the ECM. This work underscores a previously unrecognized role of Treg cells on the ECM that facilitates metastasis and is consistent with tissue Treg cell emergent function as critical regulators of tissue repair and cancer.

cancer biology↗

bioRxiv2025

A Genetic Algorithm to scour protein sequence space: A novel framework for protein engineering using protein language models and force fields

The optimization of protein sequences for enhanced binding and stability remains a formidable challenge in bioengineering due to the vastness of sequence space. Existing state-of-the-art methods, including traditional structure-based design and protein language models, use fitness estimators as objective functions to guide search algorithms that scour sequence space for optimal sequences. However, effective exploration requires search strategies that balance diversity and computational efficiency, as both are paramount for effective exploration. This work presents GAPO (Genetic Algorithm for Protein Optimization), a novel flexible framework that integrates evolutionary computing, protein language models, and structure-based design to efficiently explore sequence space. GAPO employs genetic algorithms to iteratively refine protein sequences based on user-defined objective functions, using either force field-derived information or protein language models to assess fitness, it also allows users to define custom objective functions, including multi-objective ones. We detail GAPOs implementation, highlighting features such as customizable initialization methods, diverse selection strategies, and mutation techniques informed by evolutionary scale modeling (ESM).IIn a case study using Hen-egg lysozyme, GAPO outperformed simulated annealing (SA) in both protein language model and energy-based objectives, converging to higher average ESM2 probabilities (0.98 vs. WT 0.89 and SA 0.88) and more favorable REF2015 energies (-510 REU vs. WT -415 REU and SA -405 REU), while maintaining reproducible behavior across independent runs. GAPO is available at https://github.com/izzetbiophysicist/GAPO.

bioinformatics↗

bioRxiv2025

ProteinSight: A Volumetric Deep Learning Model for Carotenoid-Binding Site Prediction

Carotenoproteins play essential roles across all domains of life, yet identifying them from sequence or structure remains a significant challenge due to the lack of conserved motifs. To address this gap, we present ProteinSight, a deep learning pipeline that identifies potential binding sites for carotenoids and related isoprenoids. Our approach, which utilizes a 3D U-Net architecture for semantic segmentation of physicochemical property maps, serves as a proof-of-concept for a new generation of structure-based protein function predictors. On a rigorously curated test set, ProteinSight functions as a highly sensitive and specific detector, reliably distinguishing positive from negative control proteins. Furthermore, we demonstrate its utility for hypothesis generation by predicting previously uncharacterized, plausible interaction sites on Human Serum Albumin. ProteinSight presents a scalable framework with the potential to aid in accelerating the discovery of novel carotenoproteins from large-scale structural data, potentially opening new avenues for functional annotation and bioengineering.

bioinformatics↗

bioRxiv2025

Co-opting the bacterial lipoprotein pathway in the biosynthesis of a lipidated macrocyclic peptide

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are structurally diverse natural products that possess a range of bioactivities, often acting as antibiotics, antifungals, or metallophores. In RiPP biosynthesis, different modifying enzymes install an array of chemical motifs onto a precursor peptide. A recently described RiPP-modifying enzyme, ChrH, catalyzes a remarkably complex reaction on its precursor peptide that results in a macrocycle, heterocycle, and S-methyl group. By leveraging comparative genomics, we demonstrate that the products from a subfamily of enzymes related to ChrH display unexpected structural diversity, including the production of unmethylated macrocyclic congeners and C-terminally modified proteins over 30 kDa in size. Several of these precursors contain a signal peptide, sending them for downstream maturation by the bacterial lipoprotein biosynthetic pathway. Like bacterial lipoproteins, such peptides are modified by addition of a diacylglycerol (DAG) group to the N-terminal cysteine residue along with acylation of the N-terminal amine. Genome mining reveals that these RiPP-lipoprotein hybrids, which we term DAG-RiPPs, are widespread across bacterial phyla and are likely involved in different biological roles. Together, these results highlight a novel maturation paradigm for membrane-bound RiPPs and lay the foundation for the discovery and bioengineering of other RiPP-lipoprotein hybrids. SignificanceRibosomally synthesized and post-translationally modified peptides (RiPPs) are a superfamily of natural products that display antibiotic, antifungal, anticancer, and metal-binding activities. Their biosynthesis typically follows a common logic in which modifying enzymes install chemical motifs onto a precursor peptide, followed by proteolytic processing and export from the cell. Herein, we describe the discovery and biochemical characterization of a new class of lipid-RiPP hybrid products. These RiPPs contain a signal peptide that exploits the endogenous bacterial lipoprotein biosynthesis pathway for lipidation, membrane localization, and potential secretion. Genome mining shows that these lipid-peptide hybrids are widespread across bacterial phyla.

biochemistry↗

bioRxiv2025

Deep Learning for RNA Secondary Structure Determination: Gauging Generalizability and Broadening the Scope of Traditional Methods

The diverse regulatory functions, protein production capacity, and stability of natural and synthetic RNAs are closely tied to their ability to fold into intricate structures. Determining RNA structure is thus fundamental to RNA biology and bioengineering. Among existing approaches to structure determination, computational secondary structure prediction offers a rapid and low-cost strategy and is thus widely used, especially when seeking to identify functional RNA elements in large transcriptomes or screen massive libraries of novel designs. While traditional approaches rely on detailed measurements of folding energetics and/or probabilistic modeling of structural data, recent years have witnessed a surge in deep learning methods, inspired by their tremendous success in protein structure prediction. However, the limited diversity and volume of known RNA structures can impede their ability to accurately predict structures markedly different from the ones they have seen. This is known as the generalization gap and currently poses a major barrier to progress in the field. In this Perspective article, we gauge method generalizability using a new benchmark dataset of structured RNAs we curated from the Protein Data Bank. We also discuss the emergence of deep learning methods for predicting structure probing data and use a new dataset to underscore generalization challenges unique to this domain along with directions for future improvement. Expanding beyond improving predictive accuracy, we review how advances in deep learning have recently enabled scalable and accessible optimization of traditional structure prediction methods and their seamless integration with modern neural networks.

bioinformatics↗

bioRxiv2025

Integration of Hematopoietic and Thymus-like Niches in a Human iPSC-derived Bone Marrow Organoid

Human bone marrow generates blood cells but critically lacks the thymic environment required for T cell development. Developing an integrated in vitro platform that reconstitutes both functions simultaneously remains a major challenge in regenerative and immune medicine. We asked whether a synthetic marrow could be engineered to provide both capacities. Using human induced pluripotent stem cells, we created self-organizing bone marrow organoids (iBMOs) that faithfully reproduced native stromal and vascular structures and, remarkably, supported robust thymus-like T cell differentiation. iBMOs directed hematopoietic progenitors toward functional T and dendritic cells. When engrafted into immunodeficient mice, they autonomously sustained human erythropoiesis and de novo bone formation in vivo. Single-cell transcriptomics revealed a complex niche architecture, including a hybrid cluster co-expressing stem, endothelial, and stromal markers, key to understanding this dual functionality. This bioengineered organoid-stromal system unifies bone marrow and thymic functions in a single human-derived platform, offering a scalable source of immune cells for adoptive cell therapies and regenerative applications, as well as a versatile model for studying human hematopoiesis and immunity.

systems biology↗

bioRxiv2025

Two-Year Field Trial of Genetically Engineered American Chestnut Reveals Greater Fungal Blight Tolerance Compared to Wild-Type Full-Sibling Trees

The American chestnut (Castanea dentata [Marsh.] Borkh.) was a foundational forest canopy species in eastern North America until an accidentally imported fungal blight (caused by Cryphonectria parasitica [Murr.] Barr.) rendered it functionally extinct across its native range. Biotechnological approaches, such as the bioengineered Darling 54 line, have potential for future restoration of American chestnut, but field-based evaluations of blight tolerance have been limited. Progress has been slowed by the many years it takes for seedlings to grow to saplings, then to full-fledged trees. Current regulatory restrictions also constrain the testing of transgenic chestnuts to within permitted orchards. This research reports on a two-year field trial of Darling 54, their non-transgenic wild-type siblings and Chinese chestnut (Castanea mollissima Blume) controls deployed a randomized block design to test for blight tolerance. In the two years, three replicates each of 261 trees were branch-inoculated with EP-155, a highly virulent isolate of the fungal blight. Based on canker length, Darling 54 trees consistently outperformed their non-transgenic wild-type siblings and Chinese chestnut. To our knowledge, this is the first report of a multi-year field trial of fungal blight inoculations comparing advanced generation Darling 54 families. This field-based evaluation suggests that reintroduction programs using Darling 54 American chestnuts, which can commence after federal approval, may offer a promising path to success.

synthetic biology↗

bioRxiv2025

Canonical transcription termination mechanisms explain a minority of operons in cyanobacteria

Cyanobacteria are the most abundant phototrophs and hold potential as a carbon-negative platform for bioengineering applications. However, these efforts have been hampered by limited mechanistic understanding of their gene expression, including transcription termination. Unlike most bacteria, cyanobacteria lack the transcription termination factor Rho, raising the speculation that all transcription ends with intrinsic terminators. Here we show that most transcription units (TUs) in Synechococcus elongatus PCC 7942 are not terminated by known termination pathways. Although many TUs (52%) have unique, well-defined 3' ends, only a small fraction have features that resemble canonical intrinsic terminators (22%). The noncanonical 3' ends broadly lacked strong secondary structure, making it unclear how these ends are protected against 3'-5' exonucleolytic decay. Furthermore, many TUs (46%) have diverse positions of mRNA 3' ends, suggesting a potentially diffuse termination signal. Finally, we observed a moderate increase in RNA levels downstream of most defined 3' ends in the absence of the transcription-repair coupling factor Mfd. This finding indicates that Mfd plays a limited, but widespread, role in RNA end formation, potentially through termination of stalled RNAPs. Together, our work reveals unique end architectures of the cyanobacterial transcriptome and suggests that undescribed transcription termination mechanisms are active in the phylum. ImportanceOur understanding of bacterial transcription regulation is largely based on model organisms like Escherichia coli and Bacillus subtilis, yet many of these mechanisms appear absent or divergent in cyanobacteria. These differences limit our fundamental understanding of gene regulation and the applied potential of cyanobacteria in sustainable biomanufacturing. To address this gap, we characterized transcription termination in the model cyanobacterium Synechococcus elongatus PCC 7942. We resolve a longstanding question by showing that intrinsic termination alone cannot account for most termination events in this organism. Pervasive transcript ends lacking intrinsic terminator features and the absence of Rho suggest the existence of novel termination mechanism(s) and highlight a largely unexplored regulatory landscape. Simultaneously, our work expands the repertoire of functionally characterized cyanobacterial intrinsic terminators, offering a new toolkit to fine-tune gene expression using terminators of defined strengths. These findings pave the way for more predictable and powerful applications of cyanobacteria in green biotechnology.

microbiology↗

bioRxiv2025

Engineering an Anaerobic Microenvironment to Empower Hydrogenase-Catalyzed Hydrogen Therapy for Diabetic Wound Healing

The inherent oxygen sensitivity of hydrogenases has long restricted their applications to anaerobic systems. Here, we present a hybrid peptide-nanocluster hydrogel that establishes a self-sustaining anaerobic microenvironment to enable hydrogenase-catalyzed hydrogen therapy under aerobic conditions. This system integrates a custom-designed Fmoc-KYF peptide hydrogel with integrated silver nanoclusters (AgNCs), which host an engineered [NiFe]-hydrogenase (3S1C-Hyd-2). Mechanistic studies combining molecular dynamics simulations and spectroscopic analysis revealed that hydrophobic pockets within the peptide network trap oxygen molecules, while photoexcited AgNCs rapidly deplete invasive O2. Our design ensures stable hydrogen evolution, effectively overcoming the oxygen sensitivity that has long restricted hydrogenase applications in biomedical contexts. In vitro, the in-situ-generated hydrogen effectively scavenges reactive oxygen species, suppresses pro-inflammatory cytokine production. In a diabetic mouse model, this light-activated system markedly accelerates wound closure (87% by day 11), reduces oxidative stress, promotes macrophage polarization toward a reparative phenotype, enhances angiogenesis, and upregulates tissue repair pathways, as confirmed by transcriptomic profiling. Our work establishes a new bioengineering paradigm for constructing anaerobic microenvironments through synergistic material-enzyme-light interactions, offering a versatile platform for hydrogenase-enabled therapeutic interventions in oxidative stress-related diseases.

biochemistry↗

bioRxiv2017

The response to selection in Glycoside Hydrolase Family 13 structures: A comparative quantitative genetics approach

The Glycoside Hydrolase Family 13 (GH13) is both evolutionary diverse and relevant to many industrial applications. Its members perform the hydrolysis of starch into smaller carbohydrates. Members of the family have been bioengineered to improve catalytic function under industrial environments. We introduce a framework to analyze the response to selection of GH13 protein structures given some phylogenetic and simulated dynamic information. We found that the TIM-barrel is not selectable since it is under purifying selection. We also show a method to rank important residues with higher inferred response to selection. These residues can be altered to effect change in properties. In this work, we define fitness as inferred thermodynamic stability. We show that under the developed framework, residues 112Y, 122K, 124D, 125W, and 126P are good candidates to increase the stability of the truncated protein 4E2O. Overall, this paper demonstrate the feasibility of a framework for the analysis of protein structures for any other fitness landscape.

bioinformatics↗

bioRxiv2017

Spin coated chitin films for biosensors and its analysis are depended on chitin-surface interactions

Chitin, abundant in nature, is a renewable resource with many possible applications in bioengineering. Biosensors, capable of label-free and in-line evaluation, play an important role in the investigation of chitin synthesis, degradation and interaction with other materials. This work presents a comparative study of the usefulness of a chitin surface preparation, either on gold (Au) or on polystyrene (PS). In both cases the most common method to dissolve chitin was used, followed by a simple spin-coating procedure. Multi-parametric surface plasmon resonance (MP-SPR), modeling of the optical properties of the chitin layers, scanning electron microscopy, and contact angle goniometry were used to confirm: the thickness of the layers in air and buffer, the refractive indices of the chitin layers in air and buffer, the hydrophobicity, the binding properties of the chitin binding domain (CBD) of Bacillus circulans, and the split-intein capture process. Binding of the CBD differed between chitin on Au versus chitin on PS in terms of binding strength and binding specificity due to a less homogenous structured chitin-surface on Au in comparison to chitin on PS, despite a similar thickness of both chitin layers in air and after running buffer over the surfaces. The use of the simple method to reproduce chitin films on a thin polystyrene layer to study chitin as a biosensor and for chitin binding studies was obvious from the SPR studies and the binding studies of CBD as moiety of chitinases or as protein fusion partner. In conclusion, stable chitin layers for SPR studies can be made from chitin in a solution of dimethylacetamide (DMA) and lithium chloride (LiCl) followed by spin-coating if the gold surface is protected with PS.

biophysics↗

bioRxiv2017

Peripheral infrastructure vectors and an extended set of plant parts for the modular cloning system

Standardized DNA assembly strategies facilitate the generation of multigene constructs from collections of building blocks in plant synthetic biology. A common syntax for hierarchical DNA assembly following the Golden Gate principle employing Type IIs restriction endonucleases was recently developed, and underlies the Modular Cloning and GoldenBraid systems. In these systems, transcriptional units and/or multigene constructs are assembled from libraries of standardized building blocks, also referred to as phytobricks, in several hierarchical levels and by iterative Golden Gate reactions. This combinatorial assembly strategy meets the increasingly complex demands in biotechnology and bioengineering, and also represents a cost-efficient and versatile alternative to previous molecular cloning techniques. For Modular Cloning, a collection of commonly used Plant Parts was previously released together with the Modular Cloning toolkit itself, which largely facilitated the adoption of this cloning system in the research community. Here, a collection of approximately 80 additional phytobricks is provided. These phytobricks comprise e.g. modules for inducible expression systems, different promoters or epitope tags, which will increase the versatility of Modular Cloning-based DNA assemblies. Furthermore, first instances of a \"peripheral infrastructure\" around Modular Cloning are presented: While available toolkits are designed for the assembly of plant transformation constructs, vectors were created to also use coding sequence-containing phytobricks directly in yeast two hybrid interaction or bacterial infection assays. Additionally, DNA modules and assembly strategies for connecting Modular Cloning with Gateway Cloning are presented, which may serve as an interface between available resources and newly adopted hierarchical assembly strategies. The presented material will be provided as a toolkit to the plant research community and will further enhance the usefulness and versatility of Modular Cloning.

plant biology↗

bioRxiv2018

Investigation of Electrical Stimulation Effect on Intracellular Calcium Dynamics Using Locally Uniform Mesh Refinement

Modeling-based methods are conventionally exploited to simulate and predict the dynamics of a system in various fields of engineering. However, due to the intricacy of biological systems, these methods were rarely utilized in bioengineering until recently. By developing advanced computers with the ability to cope with enormous calculations and extending our knowledge about biological systems, modeling-based approaches have been adopted to manipulate biological systems. While utilizing the models to investigate the behavior of a system has some advantages including lower cost and time consumption, such methods were used for tissue engineering scarcely. Exploiting modeling-based methods to tissue engineering field requires developing and utilizing efficient computational methods to model gene regulation and signaling networks, which determine cell response to environmental changes and cellular fate.\n\nIn the present work, a novel spatio-temporal method was proposed, predicated on locally uniform mesh refinement. A benchmark comparison was performed with the previously used method and the results indicated the better performance of the incipiently adopted method. Besides, the model was utilized to investigate the effect of a popular differentiating stimulator, namely electrical stimulation, on mesenchymal stem cells as a type of stem cells widely used in tissue engineering. The results of the simulations demonstrated the puissance of such computational models in analyzing and predicting the effect of biochemical and biophysical perturbations on the cells and hence, their potential utility in tissue engineering.

systems biology↗