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bioRxiv2024

Expanding the biotechnological scope of metabolic sensors through computation-aided designs

Metabolic sensors are microbial strains modified so that biomass formation correlates with the availability of specific metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled designs) but creating them is often a time-consuming and low-throughput process that can potentially be streamlined by in silico analysis. Here, we present the systematic workflow of designing, implementing, and testing versatile Escherichia coli metabolic sensor strains. Glyoxylate, a key metabolite in (synthetic) CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic model, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with a wide sensitivity range for glyoxylate, spanning three orders of magnitude in detected concentrations. We further adapted these E. coli strains for sensing glycolate and demonstrated their utility in both pathway engineering (testing a key metabolic module via glyoxylate) and applications in environmental monitoring (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications. TeaserA streamlined workflow enables the rapid design of versatile E. coli metabolic sensors for detecting key metabolites in bioengineering and monitoring.

synthetic biology↗

bioRxiv2024

Surface display of proximity labeling enzymes on extracellular vesicles for surfaceome and target cell mapping

Extracellular vesicles (EV) surface proteins have important extracellular functions and determine cellular tropism; however, characterizing the EV surfaceome remains challenging with available methods. EV-mediated intercellular communication takes place primarily through interactions at the recipient cell membrane, underscoring the importance of methodological advances to map this interplay. Here, we leverage the proximity labeling enzyme APEX2 (Apurinic/Apyrimidinic Endodeoxyribonuclease 2) for high-fidelity analysis of the EV surfaceome and cellular tropism. Surface display of APEX2 on EVs is achieved through its genetic fusion with EV-sorting domains, such as CD63 and TSPAN2. Upon adding the substrates biotin-phenol and hydrogen peroxide, vesicle surface APEX2 enables biotinylation of EV integral and corona proteins as well as target cells in vitro. Further data mining of the EV surfaceome reveals potential scaffolds for the bioengineering of EVs. Altogether, we introduce a robust tool for EV surfaceome and target cell mapping and uncover novel EV-sorting domains for bioengineering.

synthetic biology↗

bioRxiv2025

Survival and Spread of Engineered Mycobacterium smegmatis and Associated Mycobacteriophage in Soil Microcosms

The inoculation of microbes into soil environments has numerous applications for improving soil quality and crop health; however, the ability of exogenous and engineered microbes to survive and spread in soil remains uncertain. To address this challenge, we assayed the survival and spread of Mycobacterium smegmatis, engineered with either plasmid transformation or genome integration, as well as its mycobacteriophage Kampy, in both sterilized and non-sterilized soil microcosms over a period of 49 days. While engineered M. smegmatis and Kampy persisted in all soil microcosms, there was minimal evidence of spread to 5 cm away from the inoculation site. There was a higher prevalence of Kampy observed in sterilized soil than non-sterilized soil, suggesting a detrimental effect of the native soil biotic and viral community on the ability of this phage to proliferate in the soil microcosm. Additionally, higher abundance of the genome-integrated bacteria relative to the plasmid-carrying bacteria as well as evidence for loss of plasmid over the duration of the experiment suggest a burden associated with bacteria harboring plasmids, although plasmids were still retained across 49 days. To our knowledge, this is the first study to simultaneously measure the persistence and spread of bacteria and their associated phage in both sterilized and non-sterilized soil microcosms, employing bacteria with plasmid-based and genome-integrated engineered circuits. As such, this study provides a novel understanding of challenges associated with the deployment of bioengineered microbes into soil environments. ImportanceHealthy soil is essential to sustain life, as it provides habitable land, enables food production, promotes biodiversity, sequesters and cycles nutrients, and filters water. Given the prevalence of soil degradation, treatment of soil with microbes that promote soil and crop health could improve global soil sustainability; furthermore, the application of bioengineering and synthetic biology to these microbes allows fine-tunable and robust control of gene-of-interest expression. These solutions require the successful deployment of bacteria into the soil, an environment in which abundant competition and often limited nutrients can result in bacterial death or dormancy. This study employs Mycobacterium smegmatis as a chassis alongside its bacteriophage Kampy in soil microcosms to assess the ability of non-native microbes to survive and spread in soil. Insights from this experiment highlight important challenges which must be overcome for successful deployment of engineered microbes in the field.

microbiology↗

bioRxiv2025

Thermal Adaptation of Extremozymes: Temperature-Sensitive Contact Analysis of Serine Proteases

Enzyme thermal adaptation reflects a delicate interplay between sequence, structure, and dynamics of proteins, fine-tuning the catalytic activity to environmental demands. Understanding these evolutionary relationships can drive bioengineering advances, including industrial enzyme design, biocatalysts for extreme conditions, and novel therapeutics. This work explores sequence-dynamics connections in subtilisin-like serine protease homologs using a recently developed computational methodology that uses expanded ensemble simulations and temperature-sensitive contact analysis. We reveal that thermophilic enzymes achieve thermal stability through extensive salt bridges and hydrophobic networks, while psychrophilic enzymes rely on targeted interaction stability for cold adaptation. An unsupervised cluster analysis of residue conservation, flexibility, and hydrophobic interactions provides a comprehensive view of residue-specific contributions to thermal adaptation. These findings underscore the coordinated roles of conserved and variable regions in enzyme stability and offer a framework for tailoring enzymes to specific thermal properties for biotechnological applications. SIGNIFICANCEThis study reveals how subtilisin-like serine proteases adapt to extreme temperatures by balancing sequence, structure, and dynamics. Through multi-ensemble simulations, we demonstrate that conserved catalytic regions and specific residue variations allow fine-tuned thermal adaptation. The analysis of simulations reveals the importance of salt bridges and hydrophobic interactions in enhancing thermophilic enzyme stability. We find that psychrophilic enzymes exhibit unique stability mechanisms for cold environments. The approach used in this study provides a comprehensive framework for understanding enzyme thermal adaptation and offers valuable insights for bioengineering enzymes with tailored properties for industrial and medical applications.

biophysics↗

bioRxiv2025

Modulating gene expression and protein secretion in the bacterial predator Bdellovibrio bacteriovorus

The predatory bacterium Bdellovibrio bacteriovorus kills and consumes other bacteria, thrives in diverse environments and holds great potential to address major challenges in medicine, agriculture, and biotechnology. As a bacterial predator it represents an alternative to traditional antimicrobial strategies to combat multidrug-resistant bacterial pathogens and prevent food waste, while the multitude of predatory enzymes it produces hold potential for biotechnological applications. However, the limited availability of versatile genetic tools and secretion assays constrain both fundamental studies and bioengineering of B. bacteriovorus. Here, we developed a molecular toolbox for B. bacteriovorus by systematically tuning gene expression and secretion of a reporter protein. We investigated functional native and synthetic promoters from the Anderson library with varying expression levels and demonstrated their efficacy in driving expression of the fluorescent reporter protein mScarletI3 at both the population and single-cell level. Additionally, we evaluated different ribosomal binding sites (RBS) to fine-tune gene expression. To examine secretion, we established a novel protocol to quantify extracellular release of a Nanoluc luciferase reporter protein in B. bacteriovorus using different native Sec-dependent signal sequences. We anticipate that the newly developed genetic toolkit and techniques will advance research on this fundamental predator-prey system, laying the foundation for its broader application and future bioengineering efforts. This work will pave the way for tailored applications of B. bacteriovorus in microbial ecology, agriculture, biotechnology, and medicine.

microbiology↗

bioRxiv2025

AI-Guided Resetting of Memories in Gene Regulatory Network Models: biomedical and evolutionary implications

Molecular pathways such as gene-regulatory networks regulate numerous functions in cells and tissues that impact embryonic development, regenerative repair, aging, cancer, and many other aspects of health and disease. One important aspect of such networks is experience-dependent plasticity: their activity changes after repeated exposures to external and internal physiological stimuli. This kind of functional plasticity gives rise to habituation to pharmacological interventions (resulting in loss of efficacy over time), sensitization (resulting in unacceptable side effects after repeated use), or canalizing of undesired dynamics that recur even when the original problem has been resolved (persistent disease states). Our in silico analyses reveal that memories formed in gene regulatory networks can be erased by specific further experiences without any changes of network topology (leaving the connectivity in place). We present a method for discovery of stimuli that can be used to selectively delete physiological memories, which can be used to remove unwanted behaviors in biomedical and bioengineering contexts without gene therapy or genomic editing. Remarkably, not only are the training-induced gains in causal emergence not lost after stimuli that wipe memories, but we also find a positive relationship between the causal emergence and learning ability of a network, suggesting a deep asymmetry (ratchet) in the relationship between learning/forgetting and integration of collective intelligence which may have implications for evolution. Significance StatementWe present an AI-driven method for discovering signals that can be used to induce physiological networks to forget specific behaviors, which can be used for applications in biomedicine and bioengineering.

biophysics↗

bioRxiv2025

Physical, chemical, and structural properties of human gastric organoid-derived mucus

The gastric mucus layer protects the epithelium from gastric acid and ingested pathogens. However, studies of human gastric mucus have been limited due to poor accessibility of native human mucus and the abundance of contaminants in these samples. Here, we explored the potential of human gastric organoids as models for mucus production. Immunofluorescence staining confirmed that the organoids produced mucus containing MUC5AC and MUC6. The luminal mucus had viscoelastic properties similar to those of native human gastric mucus, as determined by particle tracking microrheology. To collect organoid-produced gastric mucus, termed bioengineered gastric mucus (BGM), organoids were cultured as monolayers at the air-liquid interface (ALI), and apically-secreted mucus was harvested and analyzed by MUC5AC ELISA, proteomics, CryoFE-SEM, and bulk rheometry. BGM contained high-molecular weight molecules also found in native gastric mucus, including MUC5AC. Proteomic analysis confirmed that BGM contained MUC5AC, MUC6, MUC1, and other stomach-specific molecules such as gastricsin, olfactomedin 4, and gastrokine. CryoFE-SEM showed that both BGM and native mucus had a porous structure and a characteristic honeycomb scaffold. Bulk rheometry confirmed that BGM exhibited shear thinning and predominantly elastic behavior, consistent with native mucus. Collectively, these findings indicate that BGM is an accessible alternative to native gastric mucus that can be produced on-demand for in vitro studies. New and NoteworthyWe demonstrate the structural and functional similarities of organoid-derived gastric mucus and native mucus collected from human patients. The bioengineered gastric mucus mimics its native counterpart in its proteomic profile, physical architecture, and viscoelasticity. This work highlights the translational potential of organoid-derived mucus for functional investigations of the human gastric mucus layer.

cell biology↗

bioRxiv2026

A transcriptional regulator gene TRG1 of Trichoderma longibrachiatum is involved in the regulation of peptaibols synthesis

Trichoderma species are recognized for their robust biocontrol capacity, primarily due to the production of peptaibols, potent secondary metabolites that exhibit antibacterial properties, induce cell apoptosis, and enhance plant disease resistance. To elucidate the regulatory mechanism of peptaibol synthesis, we investigated the role of a transcription regulator gene TRG1 (designated as TLTRG1), which we identified within a non-ribosomal peptide synthetase (NRPS) gene cluster of T. longibrachiatum SMF2. We successfully created a{Delta} TRG1 gene knockout mutantusing homologous recombination. Phenotypic analysis indicated that the{Delta} TRG1 mutant maintained wild-type growth rate, colony morphology, and spore production. However,{Delta} TRG1 exhibited a significantly reduced inhibition rate against the plant pathogen Botrytis cinerea and a lower efficacy in controlling gray mold on detached rose leaves. High-performance liquid chromatography (HPLC) analysis provided direct molecular evidence, showing that peptaibol production in the mutant was 2.5 times lower than that of the wild-type strain. These findings conclusively establish that TRG1 functions as a key positive transcriptional regulator essential for high-yield peptaibol biosynthesis by modulating NRPS gene expression. This gene represents a critical molecular target for bioengineering strategies aimed at enhancing the biocontrol efficacy of Trichoderma strains. The Importance sectionTrichoderma species are known to produce peptaibols, which exhibit antibacterial properties, induce cell apoptosis, and enhance plant disease resistance. However, the mechanisms underlying the biosynthesis and regulation of peptaibols remain unclear. In this study, we investigated the role of a transcription regulator gene located within a non-ribosomal peptide synthetase (NRPS) gene cluster of T. longibrachiatum SMF2, which we designated as TLTRG1 (TRG1). Phenotypic analysis indicated the inhibition rate of {Delta}TRG1 against Botrytis cinerea and its effectiveness in controlling gray mold were significantly reduced compared to the WT strain. High-performance liquid chromatography (HPLC) analysis revealed that the production of peptaibols in the mutant was significantly decreased. These findings suggest that the TRG1 gene may play a crucial role in regulating the expression of NRPS genes, thereby affecting the biosynthesis of peptaibols. Therefore, it can be concluded that the gene TRG1 is a molecular target for bioengineering strains with enhanced biocontrol efficacy.

microbiology↗

bioRxiv2026

Behavioral, Physiological, and Transcriptional Mechanisms of Memory in a Synthetic Living Construct

Synthetic living constructs, which lack the long histories of selection in ecological contexts that shape behaviors of conventional organisms, offer an important complement to traditional studies of learning. Could novel biobots exhibit sensing and memory of experiences? Here, we investigated the effects of chemical stimuli on basal Xenobots - autonomously motile entities derived from Xenopus embryonic ectodermal explants (with no additional sculpting or bioengineering). We quantified and characterized the coordinated ciliary activity that generates fluid flow fields guiding the trajectory of Xenobot motion. We also show distinct and specific changes in Xenobot behavior after brief exposure to Xenopus embryonic cell extract and to ATP. These two experiences produced distinct, long-term, stimulus-specific memories, detectable through both transcriptional and physiological signatures. Exposure to specific environmental stimuli induced alterations in the spatiotemporal patterns of calcium signaling across Xenobots. Together, these data lay a foundation for characterizing the capabilities of synthetic cellular collectives to sense and discriminate among stimuli, as well as store functional information in a non-neural context. Understanding behavioral competencies in novel, non-neural systems have broad implications across evolutionary biology, behavioral science, bioengineering, and bio/hybrid robotics.

synthetic biology↗

bioRxiv2026

A conserved structural logic underlies sensor-helper NLR communication in the NRC immune receptor network

NLR immune receptor networks consist of expanded disease resistance proteins (sensor NLRs) that signal via core executors of immunity known as helper NLRs. Although some sensor NLRs are thought to activate their cognate helpers via an activation-and-release mechanism, the structural basis of sensor-helper communication remains poorly understood. Here, we identify and validate sensor-helper NLR interfaces that are critical for immune activation in the NRC network of coiled-coil NLR immune receptors. Using AlphaFold 3 we predicted a high confidence model between the virus resistance protein Rx and its helper NLR NRC2. We validated the interfaces by loss and gain-of-function mutagenesis, including reconstituting a critical salt bridge through reciprocal mutations. We showed that these interfaces are conserved across the NRC network of asterid plants despite over 120 million years of divergence and validated the sensor-NRC interfaces within the common lettuce network. Structure-guided bioengineering of a lettuce sensor NLR enabled expansion of its NRC helper compatibility profile. These results are consistent with the activation-and-release model and point to bioengineering sensor- helper specificity in economically important crop species.

plant biology↗

bioRxiv2026

Accurate de novo design of peptides from programming biophysical landscape

Peptides regulate virtually every cellular process and emerge as transformative modalities in bioengineering and therapeutics. However, the de novo design of functional peptides remains challenging, as peptide-protein interactions are governed by delicate and dynamic biophysics that are difficult to model, and experimental datasets are scarce. Here we present NeoPep, a generative deep-learning framework that encodes biophysical principles to accurately design functional peptides de novo. By integrating over 5 million peptide-protein complexes spanning experimentally determined, sequence mimics, and structure ensembles, NeoPep learns the complex biophysical landscape governing peptide function and enables its programmable control. In prospective application across 10 diverse and challenging targets, NeoPep generated potent peptide binders, agonists, and antagonists with hit rates of 12.5-66.7%, even in the absence of defined binding sites or structure information. Beyond de novo co-design, NeoPep supports standalone structure or sequence redesign, readily discriminating subtle context differences. In the structure redesign mode, it generates highly selective peptides with atomic-level conformational accuracy (C RMSD < 2.0 [A] to our solved cryo-EM structure). This structural precision circumvents the need for experimental structure determination, further accelerating iterative sequence redesign to yield a 43.3-fold improvement in potency. These findings establish a general framework for translating biophysical principles into actionable peptide functions, with broad implications for basic research, bioengineering, and medicine.

molecular biology↗

bioRxiv2026

Testing Reversibility of Endosymbiotic Gene Transfer between Chloroplast and Nucleus

Most proteins targeted to the organelles of endosymbiotic origin are encoded in the nuclear genome, placing them under the regulatory dominance of the nucleus. For photosynthetic eukaryotes, nuclear-encoded chloroplast proteins arise via two routes: First, genes of cyanobacterial origin were relocated to the nucleus through endosymbiotic gene transfer (EGT). Second, proteins of eukaryotic origin emerged to support chloroplast function and structure. These proteins are reimported into the chloroplast via an import machinery. Reversing the transfer of such genes from the nucleus to the chloroplast genome may offer insights into chloroplast regulation and evolution. In this study, we established a highly efficient and accessible electroporation protocol for chloroplast transformation in the green alga Chlamydomonas reinhardtii, and used it to reverse-transfer two nuclear-encoded genes encoding proteins arising via the two routes described above: the cyanobacteria-derived chloroplast division protein FtsZ1 and the Rubisco-linker EPYC1 of eukaryotic origin. Regardless of origin, both chloroplast-encoded FtsZ1 and EPYC1 showed proper localization and functionality comparable to their nuclear-encoded counterparts. Together, our study provides a robust protocol for chloroplast transformation, a platform for investigating the evolutionary drivers of EGT, and a foundation for advancing chloroplast bioengineering. SIGNIFICANCE STATEMENTO_LIEndosymbiotic gene transfer has resulted in the mass migration of genes from the chloroplast genome to the nuclear genome. Reversing the gene transfer could reveal the evolutionary significance of genome partitioning. C_LIO_LIUsing the green alga Chlamydomonas reinhardtii, this study developed an efficient, electroporation-based protocol for chloroplast transformation. Relocating the genes encoding two chloroplast-targeted proteins, FTSZ1 and EPYC1, to the chloroplast genome showed that the proteins maintained normal localization and function. C_LIO_LIThe established transformation protocol facilitates systematic testing of reverse gene transfer to elucidate the potential evolutionary advantages of genome partitioning and opens new avenues for chloroplast bioengineering. C_LI

cell biology↗

bioRxiv2026

Computational design of de novo integrated domains enables rational control of pathogen effector recognition in plant NLR immune receptors.

The rapid evolution of plant pathogens poses a persistent threat to global agricultural sustainability, often outpacing the discovery and deployment of natural disease resistance genes. While bioengineering of plant intracellular immune receptors (NLRs) offers a potential solution, developing bespoke immune recognition remains constrained by the laborious characterisation of natural receptors and plant-pathogen interactions. Here, we describe a programmable framework that leverages generative AI protein design tools, RFdiffusion and ProteinMPNN, to design de novo integrated domains (IDs) against diverse pathogen effectors. By integrating these bespoke binders into the modular rice blast Pik-1/Pik-2 NLR receptor chassis, we successfully engineer recognition of a non-cognate virulence factor (effector) from the Panama disease pathogen, Fusarium oxysporum f. sp. cubense Tropical Race 4. Functional assays in Nicotiana benthamiana demonstrate that these de novo domains facilitate specific effector perception and initiate immune signalling, while structural and biophysical analyses confirm that de novo integrated domains maintain high structural fidelity to the initial designs and associate with their targets via the predicted interaction interfaces. Additionally, our findings provide orthogonal evidence for the role of integrated domains in regulation of NLR signalling, demonstrating integration of de novo IDs can either trigger autoactivity or, in some cases, lead to effector-mediated repression of cell death. By decoupling immune perception from natural evolutionary history through deploying AI-designed sensory domains, this work establishes a design-lead framework for generation of programmable plant immune receptors, providing a new avenue for bioengineering crops against emerging pathogens.

plant biology↗

bioRxiv2016

A Pilot Study: Development of a Reference Spatiotemporal Gait Data Set for Indian Subjects.

1.Interpretation of pathological gait has, for decades, offered insight into amputee anomalies and diseases such as cerebral palsy. Gait analysis has been actively used at the Bhagwan Mahaveer Viklang Sahatya Samiti for such purposes. The normative gait data used to compare data obtained from amputees, however, has been collected from laboratories under dissimilar conditions, skewing interpretation. Spatiotemporal gait parameters were extractedfrom 43 male Indian subjects using a 7.5m walkway and the BTS Bioengineering GAITLAB setup. Working under the hypothesis that a lack of cross-cultural validity was somewhat responsible for variations in normative gait, we attempted to develop a region-specific data set for use at the headquarters of the Jaipur Foot Organization Bhagwan Mahaveer Viklang Sahatya Samiti (BMVSS). Stratified random sampling was used to recruit subjects and measures were taken to ensure minimal effects of extraneous variables. Statistical analysis was performed on obtained data using one-way analysis of variance (ANOVA) to gauge the effect age and ethnicity had on normative values of the parameters investigated. We found statistically significant p-values for a few spatiotemporal parameters in the analysis of variance for both age and ethnicity. While the results were much less significant than initially hypothesized, the study proved an efficient way to create a normative gait data set exclusively for use at the gait laboratory of the Jaipur Foot Organization, thereby eliminating potential erroneous interpretation of pathological gait when comparing said gait to normative gait data obtained in laboratories under dissimilar conditions.

bioengineering↗

bioRxiv2017

Refactoring the Genetic Code for Increased Evolvability

The standard genetic code is robust to mutations and base-pairing errors during transcription and translation. Point mutations are most likely to be synonymous or preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best performing mutant requires a replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyper-evolvable organism serving as an ideal platform for directed evolution experiments. We then conclude by evaluating potential applications for recoded organisms within the synthetic biology field.\n\nSignificance StatementThe conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene using common error-prone methods. Here we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transition to a larger pool of amino acids and with a greater degree of chemical differences, using a single nucleotide replacement within the codon, thus increasing evolvability both at the single gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation and fitness maximization.

bioengineering↗

bioRxiv2020

An in vitro human-based fracture gap model - Mimicking the crosstalk between bone and immune cells

The interaction between the bone and immune cells plays a crucial role in bone pathologies such as disturbed fracture healing. After a trauma, the initially formed fracture hematoma in the fracture gap contains all important components (immune/stem cells, mediators) to directly induce bone regeneration and is therefore of great importance but most susceptible to negative influences. Thus, reliable in vitro models are needed to study the underlying mechanisms and to predict the efficiency of novel therapeutic approaches. Since common bioengineering approaches exclude the immune component, we introduce an in vitro 3D fracture gap model which combines scaffold-free bone-like constructs with a fracture hematoma model consisting of human peripheral blood (immune cells) and bone marrow-derived mesenchymal stromal cells. Our in vitro 3D fracture gap model provides all osteogenic cues to induce the initial bone healing processes, which were further promoted by applying the osteoinductive deferoxamine (DFO). Thus, we were able to distinctly mimic processes of the initial fracture phase and demonstrated the importance of including the crosstalk between bone and immune cells.

bioengineering↗

bioRxiv2020

A combined microphysiological-computational omics approach in dietary protein evaluation

The ever-growing world population puts pressure on food security. To tackle this, waste stream proteins and novel protein sources need to be evaluated for nutritional value, which requires information on digesta peptide composition in comparison to established protein sources and coupling to biological parameters. Here, we present a novel combined experimental and computational approach comparing seventeen protein sources with cows whey protein (WPC) as benchmark. In vitro digestion was followed by proteomics analysis and statistical model clustering based on Bayesian Information Criterion. Next, we incorporated functional protein data after evaluating the effects of eighteen protein digests on intestinal barrier integrity, viability, brush border enzyme activity and immune parameters using a bioengineered intestine. Our data show that a holistic approach allows evaluating a dietary proteins potential for delivery of bioactive peptides, where protein source (animal, plant or novel source-derived) does not seem to be the driving force for clustering.

bioengineering↗

bioRxiv2020

A human disease model of SARS-CoV-2-induced lung injury and immune responses with a microengineered organ chip

Coronavirus disease 2019 (COVID-19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that seriously endangers human health. There is an urgent need to build physiological relevant human models for deep understanding the complex organ-level disease processes and facilitating effective therapeutics for COVID-19. Here, we first report the use of microengineered alveolus chip to create a human disease model of lung injury and immune responses induced by native SARS-CoV-2 at organ-level. This biomimetic system is able to reconstitute the key features of human alveolar-capillary barrier by co-culture of alveolar epithelial and microvascular endothelial cells under microfluidic flow. The epithelial cells on chip showed higher susceptibility to SARS-CoV-2 infection than endothelial cells identified by viral spike protein expression. Transcriptional analysis showed distinct responses of two cell types to SARS-CoV-2 infection, including activated type I interferon (IFN-I) signaling pathway in epithelium and activated JAK-STAT signaling pathway in endothelium. Notably, in the presence of circulating immune cells, a series of alveolar pathological changes were observed, including the detachment of endothelial cells, recruitment of immune cells, and increased production of inflammatory cytokines (IL-6, IL-8, IL-1{beta} and TNF-). These new findings revealed a crucial role of immune cells in mediating lung injury and exacerbated inflammation. Treatment with antiviral compound remdesivir could suppress viral copy and alleviate the disruption of alveolar barrier integrity induced by viral infection. This bioengineered human organ chip system can closely mirror human-relevant lung pathogenesis and immune responses to SARS-CoV-2 infection, not possible by other in vitro models, which provides a promising and alternative platform for COVID-19 research and preclinical trials.

bioengineering↗