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bioRxiv2023

Configurable Full Subtractor and Adder by Lego-like Mixing and Matching of Engineered Bacteria

One of the long-term goals of synthetic bioengineering is to create configurable and programmable biological systems by just mixing and matching "LEGO"-like bio-modules. Here, we introduce a configurable and modular multi-cellular system where, from a small library of nine discrete engineered bacterial cells, a full subtractor and a full adder can be built on demand by just mixing and matching seven appropriate cell types in a culture. Here, each set of engineered bacteria was modelled as an artificial neuro-synapse that, in a co-culture, formed a single layer artificial neural network (ANN) type architecture that worked as a biochemical full subtractor or full adder. The system is configurable with interchangeable cellular modules, whereby through simply interchanging two cell types in the subtractor culture, a full adder can be built and vice versa. This Lego-like mix and match system is mathematically predictive, and provide a flexible and scalable means to build complex cellular functions. This work may have significance in biocomputer technology development, multi-cellular synthetic biology, and cellular hardware for ANN.

synthetic biology↗

bioRxiv2023

Microenvironmental Stiffness Induces Metabolic Reprogramming in Glioblastoma

The mechanical properties of solid tumors influence tumor cell phenotype and ability to invade into surrounding tissues. Using bioengineered scaffolds to provide a matrix microenvironment for patient-derived glioblastoma (GBM) spheroids, this study demonstrates that a soft, brain-like matrix induces GBM cells to shift to a glycolysis-weighted metabolic state which supports invasive behavior. We first show that orthotopic murine GBM tumors are stiffer than peri-tumoral brain tissues, but tumor stiffness is heterogenous where tumor edges are softer than the tumor core. Then, we developed three-dimensional scaffolds with {micro}-compressive moduli resembling either stiffer, tumor core or softer, peri-tumoral brain tissue. We demonstrate that the softer matrix microenvironment induces a shift in GBM cell metabolism toward glycolysis which manifests in lower proliferation rate and increased migration activities. Finally, we show that these mechanical cues are transduced from the matrix via CD44 and integrin receptors to induce metabolic and phenotypic changes in cancer cells.

cancer biology↗

bioRxiv2023

Emergent digital bio-computation through spatial diffusion and engineered bacteria

Building computationally capable biological systems has long been an aim of synthetic biology. The potential utility of biocomputing devices ranges from biosafety and environmental applications to diagnosis and personalised medicine. Here we present work for the design of bacterial computers which use spatial patterning to process information. Our computers are composed of bacterial colonies which, inspired by patterning in embryo development, receive information in the form of diffusible morphogen-like signals. A computation is encoded by the physical locations of the input sources of morphogen and the output receiver colonies. We demonstrate, mathematically and with engineered Escherichia coli, the simple digital logic capability of single bacterial colonies and show how additional colonies are required to build complex functions. Inspired by electronic design automation, an algorithm for designing optimal spatial circuits computing two-level digital functions is presented. This enhances the capability of our system to complex digital functions without increasing the biological complexity. We extend our experimental system to incorporate biosensing colonies as morphogen sources, demonstrating how a diagnostic device might be constructed. Our approach will open up new ways to perform biological computation, with applications in bioengineering, biomaterials and biosensing. Ultimately, these computational bacterial communities will help us explore information processing in natural biological systems.

synthetic biology↗

bioRxiv2023

Harnessing the power of whole human liver ex situ normothermic perfusion for preclinical AAV vector evaluation

Developing clinically predictive model systems for evaluating gene transfer and gene editing technologies has become increasingly important in the era of personalized medicine. Liver-directed gene therapies present a unique challenge due to the complexity of the human liver. In this work, we describe the application of whole human liver explants in an ex situ normothermic perfusion system to evaluate a set of fourteen natural and bioengineered adeno-associated viral (AAV) vectors directly in human liver, in the presence and absence of neutralizing human sera. Under non-neutralizing conditions, the recently developed AAV variants, AAV-SYD12 and AAV-LK03, emerged as the most functional variants in terms of cellular uptake and transgene expression. However, when assessed in the presence of human plasma containing anti-AAV neutralizing antibodies (NAbs), vectors of human origin, specifically those derived from AAV2/AAV3b, were extensively neutralized, whereas AAV8-derived variants performed efficiently. This study establishes the use of normothermic liver perfusion as an invaluable preclinical model for evaluating liver-targeted gene therapies and providing guidance for making essential decisions that promote the most effective translational programs.

molecular biology↗

bioRxiv2023

Spatiotemporal dynamics and emergent ordering in a mixture of morphologically distinct bacteria having different cell motility

Microbial communities exhibit complex behaviors driven by species interactions and individual characteristics. In this study, we delve into the dynamics of a mixed bacterial population comprising two distinct species with different morphology and motility aspects. Employing agent-based modeling and computer simulations, we analyze the impacts of size ratios and packing fractions on dispersal patterns, aggregate formation, clustering, and spatial ordering. Notably, we find that motility and anisotropy of elongated bacteria significantly influence the distribution and spatial organization of nonmotile spherical species. Passive spherical cells display superdiffusive behavior, particularly at smaller size ratios, while active rod-like cells exhibit normal diffusive behavior in the diffusion regime. As the size ratio increases, clustering of passive cells is observed, accompanied by enhanced alignment and closer packing of active cells in the presence of higher passive cell area fractions. As the size ratio increases, clustering of passive cells is observed, accompanied by enhanced alignment and closer packing of active cells in the presence of higher passive cell area fractions. Additionally, we identify the pivotal role of passive cell area fraction in influencing the response of active cells toward nematicity, with its dependence on size ratio. These findings shed light on the significance of morphology and motility in shaping the collective behavior of microbial communities, providing valuable insights into complex microbial behaviors with implications for ecology, biotechnology, and bioengineering.

biophysics↗

bioRxiv2023

A Novel Milli-fluidic Liver Tissue Chip with continuous Recirculation for Predictive pharmacokinetics Applications

A crucial step in lead selection during drug development is accurate estimation and optimization of hepatic clearance using in vitro methods. However, current methods are limited by factors such as lack of physiological relevance, short culture/incubation times that are not consistent with drug exposure patterns in patients, use of drug absorbing materials, and evaporation during long-term incubation. To address these technological needs, we developed a novel milli-fluidic human liver tissue chip (LTC) that was designed with continuous media recirculation and optimized for hepatic cultures using human primary hepatocytes. Here, we characterized the LTC using a series of physiologically relevant metrics and test compounds to demonstrate that we could accurately predict the PK of both low and high clearance compounds. The non-biological characterization indicated that the cyclic olefin copolymer (COC)-based LTC exhibited negligible evaporation and minimal non-specific binding of drugs of varying ionic states and lipophilicity. Biologically, the LTC exhibited functional and polarized hepatic culture with sustained metabolic CYP activity for at least 15 days. This long-term culture was then used for drug clearance studies for low and high-clearance compounds for at least 12 days and clearance was estimated for a range of compounds with high in vitro in vivo correlation (IVIVC). We also demonstrated that LTC can be induced by rifampicin, and the culture age had insignificant effect on depletion kinetic and predicted clearance value. Thus, we used advances in bioengineering to develop a novel purpose-built platform with high reproducibility and minimal variability to address unmet needs for PK applications.

pharmacology and toxicology↗

bioRxiv2023

Strategic engineering unlocks in vitro type II polyketide biosynthesis

Microbial polyketides represent a structurally diverse class of secondary metabolites with medicinally relevant properties and are synthesized by polyketide synthases (PKS). While Type I PKSs are large biosynthetic machineries composed of a single polypeptide chain, type II PKSs are minimally composed of a ketosynthase-chain length factor (KS-CLF) and a phosphopantetheinylated acyl carrier protein (holo-ACP) expressed separately. Although type II PKSs are found throughout the bacterial kingdom, and despite their importance to strategic bioengineering, type II PKSs have not been well-studied in vitro: In cases where the KS-CLF can be accessed via E. coli heterologous expression, the cognate ACPs are not activatable by the broad specificity Bacillus subtilis surfactin-producing phosphopantetheinyl transferase (PPTase) Sfp and, conversely, in systems where the ACP can be activated by Sfp, the corresponding KS-CLF is typically not readily obtained. Here, we report the high-yield heterologous expression of both cyanobacterial Gloeocapsa sp. PCC 7428 minimal type II PKS (gloPKS) components in E. coli, which allowed us to functionally reconstitute this minimal type II PKS in vitro. Initially, neither the cognate PPTase nor Sfp converted gloACP to its active holo state. However, by examining sequence differences between Sfp-compatible and -incompatible ACPs, we identified two conserved residues in gloACP that, when mutated, enabled high-yield phosphopantetheinylation of gloACP by Sfp. Using analogous mutations, other previously Sfp-incompatible type II PKS ACPs from different bacterial phyla were also rendered activatable by Sfp. This demonstrates the generalizability of our approach and breaks down a longstanding barrier to type II PKS studies and the exploration of complex biosynthetic pathways.

biochemistry↗

bioRxiv2023

Highly accurate and robust protein sequence design with CarbonDesign

Protein sequence design, the inverse problem of protein structure prediction, plays a crucial role in protein engineering. Although recent deep learning-based methods have shown promising advancements, achieving accurate and robust protein sequence design remains an ongoing challenge. Here, we present CarbonDesign, a new approach that draws inspiration from successful ingredients of AlphaFold for protein structure prediction and makes significant and novel developments tailored specifically for protein sequence design. At its core, CarbonDesign explores Inverseformer, a novel network architecture adapted from AlphaFolds Evoformer, to learn representations from backbone structures and an amortized Markov Random Fields model for sequence decoding. Moreover, we incorporate other essential AlphaFold concepts into CarbonDesign: an end-to-end network recycling technique to leverage evolutionary constraints in protein language models and a multi-task learning technique to generate side chain structures corresponding to the designed sequences. Through rigorous evaluations on independent testing data sets, including the CAMEO and recent CASP15 data sets, as well as the predicted structures from AlphaFold, we show that CarbonDesign outperforms other published methods, achieving high accuracy in sequence generation. Moreover, it exhibits superior performance on de novo backbone structures obtained from recent diffusion generative models such as RFdiffusion and FrameDiff, highlighting its potential for enhancing de novo protein design. Notably, CarbonDesign also supports zero-shot prediction of the functional effects of sequence variants, indicating its potential application in directed evolution-based design. In summary, our results illustrate CarbonDesigns accurate and robust performance in protein sequence design, making it a promising tool for applications in bioengineering.

bioinformatics↗

bioRxiv2023

Molecular basis for short-chain thioester hydrolysis by acyl hydrolase domains in trans-acyltransferase polyketide synthases

Polyketide synthases (PKSs) are multi-domain enzymatic assembly lines that biosynthesise a wide selection of bioactive natural products from simple building blocks. In contrast to their cis-acyltransferase (AT) counterparts, trans-AT PKSs rely on stand-alone AT domains to load extender units onto acyl carrier protein (ACP) domains embedded in the core PKS machinery. Trans-AT PKS gene clusters also encode acyl hydrolase (AH) domains, which are predicted to share the overall fold of AT domains, but hydrolyse aberrant acyl chains from ACP domains, thus ensuring efficient polyketide biosynthesis. How such domains specifically target short acyl chains, in particular acetyl groups, tethered as thioesters to the substrate-shuttling ACP domains, with hydrolytic rather than acyl transfer activity, has remained unclear. To answer these questions, we solved the first structure of an AH domain and performed structure-guided activity assays on active site variants. Our results offer key insights into chain length control and selection against coenzyme A-tethered substrates, and clarify how the interaction interface between AH and ACP domains contributes to recognition of cognate and non-cognate ACP domains. Combining our experimental findings with molecular dynamics simulations allowed for the production of a data-driven model of an AH:ACP domain complex. Our results advance the currently incomplete understanding of polyketide biosynthesis by trans-AT PKSs, and provide foundations for future bioengineering efforts.

biochemistry↗

bioRxiv2023

Characterisation of the butyrate production pathway in probiotic MIYAIRI588 by a combined whole genome-proteome approach.

Butyrate is a short chain fatty acid with important industrial applications produced by chemical synthesis. With consumer demand for green products, the fermentative production of butyric acid by microorganisms such as Clostridium is attracting interest. Clostridium butyricum ferments non-digested dietary fibre in the colon to produce butyrate which has multiple health benefits, and certain strains are exploited as probiotics, such as MIYAIRI588 (CBM588). Knowledge of the genes encoding enzymes involved in butyrate production and determining those that are rate-limiting due to low concentrations, could enable strain engineering for higher yields. To this end whole genome sequencing of CBM588 was performed and a circular chromosome, a megaplasmid and the previously reported cryptic plasmid, pCBM588, identified. All genes involved in the butyrate production pathway were found on the chromosome. To identify rate-limiting steps, the relative abundance of the encoded enzymes was assessed by liquid chromatography-mass spectrometry (LC-MS) of total cytosolic proteins. Phosphotransbutyrylase (Ptb) was the least abundant closely followed by butyrate kinase (Buk) and crotonase (Crt). Analysis of upstream regulatory sequences revealed the potential importance of an intact Shine-Dalgarno sequence. Results of this study can now guide bioengineering experiments to improve butyrate yields and enhance the performance of CBM588 as a probiotic.

microbiology↗

bioRxiv2023

Comparative omics reveals unanticipated metabolic rearrangements in a high-oil mutant of plastid acetyl-CoA carboxylase

Heteromeric acetyl-CoA carboxylase (ACCase) catalyzes the ATP-dependent carboxylation of acetyl-CoA to produce malonyl-CoA, the committed step for de novo fatty acid synthesis. In plants, ACCase activity is controlled at multiple levels, including negative regulation by biotin attachment domain-containing (BADC) proteins, of which the badc1/3 double mutant leads to increased seed triacylglycerol accumulation. Unexpectedly, the Arabidopsis badc1/3 mutant also accumulates more protein. The metabolic consequences from both higher oil and protein was investigated in developing badc1/3 seed using global transcriptomics, translatomics, proteomics, and metabolomics. Changes include: reduced plastid pyruvate dehydrogenase; increased acetyl-CoA synthetase; increased storage and lipid-droplet packaging proteins; increased lipases; and increased {beta}-oxidation fatty acid catabolism. We present a model of how Arabidopsis adapted to deregulated ACCase, limiting total oil accumulation, and altering flux through pathways of carbon accumulation that presents possible targets for future bioengineering of valuable seed storage reserves.

plant biology↗

bioRxiv2023

In Vivo Biorthogonal Antibody Click for Dual Targeting and Augmented Efficacy in Cancer Treatment

Antibody-drug conjugates (ADCs) have emerged as promising therapeutics for cancer treatment; however, their effectiveness has been limited by single antigen targeting, potentially leading to resistance mechanisms triggered by tumor compensatory pathways or reduced expression of the target protein. Here, we present antibody-ADC click, an approach that harnesses bioorthogonal click chemistry for in vivo dual receptor targeting, irrespective of the levels of the tumors expression of the ADC-targeting antigen. Antibody-ADC click enables targeting heterogeneity and enhances antibody internalization and drug delivery inside cancer cells, resulting in potent toxicity. We conjugated antibodies and ADCs to the bioorthogonal click moieties tetrazine (Tz) and trans-cyclooctene (TCO). Through sequential antibody administration in living biological systems, we achieved dual receptor targeting by in vivo clicking of antibody-TCO with antibody-Tz. We show that the clicked antibody therapy outperformed conventional ADC monotherapy or antibody combinations in preclinical models mimicking ADC-eligible, ADC-resistant, and ADC-ineligible tumors. Antibody-ADC click enables in vivo dual-antigen targeting without extensive antibody bioengineering, sustains tumor treatment, and enhances antibody-mediated cytotoxicity.

cancer biology↗

bioRxiv2023

Integration of Patient-Derived Organoids and Organ-on-Chip Systems: Investigating Colorectal Cancer Invasion within the Mechanical and GABAergic Tumor Microenvironment

Three-dimensional (3D) in vitro models are essential in cancer research, but they often neglect physical forces. In our study, we combined patient-derived tumor organoids with a microfluidic organ-on-chip system to investigate colorectal cancer (CRC) invasion in the tumor microenvironment (TME). This allowed us to create patient-specific tumor models and assess the impact of physical forces on cancer biology. Our findings showed that the organoid-on-chip models more closely resembled patient tumors at the transcriptional level, surpassing organoids alone. Using omics methods and live-cell imaging, we observed heightened responsiveness of KRAS mutant tumors to TME mechanical forces. These tumors also utilized the {gamma}-aminobutyric acid (GABA) neurotransmitter as an energy source, increasing their invasiveness. This bioengineered model holds promise for advancing our understanding of cancer progression and improving CRC treatments. HighlightsO_LIMicrofluidic organ-on-chip system integrated with patient-derived CRC organoids C_LIO_LIPhysical forces influence invasion, particularly in KRAS mutant tumor cells C_LIO_LIGABAergic signaling contributes to increased invasion within a dynamic TME C_LIO_LIThis model explores patient heterogeneity, TME interactions, and cancer progression C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC="FIGDIR/small/557797v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@1b181bborg.highwire.dtl.DTLVardef@bc5b6eorg.highwire.dtl.DTLVardef@16b4fcorg.highwire.dtl.DTLVardef@c43b9f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

Structural phylogenetics unravels the evolutionary diversification of communication systems in gram-positive bacteria and their viruses

Recent advances in AI-based protein structure modeling have yielded remarkable progress in predicting protein structures. Since structures are constrained by their biological function, their geometry tends to evolve more slowly than the underlying amino acids sequences. This feature of structures could in principle be used to reconstruct phylogenetic trees over longer evolutionary timescales than sequence-based approaches, but until now a reliable structure-based tree building method has been elusive. Here, we introduce a rigorous framework for empirical tree accuracy evaluation and tested multiple approaches using sequence and structure information. The best results were obtained by inferring trees from sequences aligned using a local structural alphabet--an approach robust to conformational changes that confound traditional structural distance measures. We illustrate the power of structure-informed phylogenetics by deciphering the evolutionary diversification of a particularly challenging family: the fast-evolving RRNPPA quorum sensing receptors. We were able to propose a more parsimonious evolutionary history for this critical protein family which enables gram-positive bacteria, plasmids and bacteriophages to communicate and coordinate key behaviors. The advent of high-accuracy structural phylogenetics enables a myriad of applications across biology, such as uncovering deeper evolutionary relationships, elucidating unknown protein functions, or refining the design of bioengineered molecules.

bioinformatics↗

bioRxiv2023

ProteinFlow: a Python Library to Pre-Process Protein Structure Data for Deep Learning Applications

Over the past few years, deep learning tools for protein design have made significant advances in the field of bioengineering, opening up new opportunities for drug discovery, disease prevention or industrial biotechnology. However, despite the growing interest and excitement surrounding these tools, progress in the field is hindered by a lack of standardized datasets for benchmarking. Most models are trained on data from the Protein Data Bank (PDB), the largest repository of experimentally determined biological macromolecular structures. But filtering and processing this data involves many hyperparameter choices that are often not harmonized across the research community. Moreover, the task of splitting protein data into training and validation subsets with minimal data leakage is not trivial and often overlooked. Here we present ProteinFlow, a computational pipeline to pre-process protein sequence and structural data for deep learning applications. The pipeline is fully configurable and allows the extraction of all levels of protein organization (primary to quaternary), allowing end-users to cater the dataset for a multitude of downstream tasks, such as protein sequence design, protein folding modeling or protein-protein interaction prediction. In addition, we curate a feature-rich benchmarking dataset based on the latest annual release of the PDB and a selection of preprocessing parameters that are widely used across the research community. We showcase its utility by benchmarking a state-of-the-art (SOTA) deep learning model for protein sequence design. The open source code is packaged as a python library and can be accessed on https://github.com/adaptyvbio/ProteinFlow.

bioinformatics↗

bioRxiv2023

Criticality and partial synchronization analysis in Wilson-Cowan and Jansen-Rit neural mass models

Synchronization is a phenomenon observed in neuronal networks involved in diverse brain activities. Neural mass models such as Wilson-Cowan (WC) and Jansen-Rit (JR) manifest synchronized states. Although they have been studied for decades, their ability to demonstrate second-order phase transition (SOPT) and criticality has not received enough attention, which serves as candidates for the development of healthy brain networks. In this study, two networks of coupled WC and JR nodes with small-world topologies were constructed and Kuramoto order parameter (KOP) was used to quantify the amount of synchronization. In addition, we investigated the presence of SOPT using the synchronization coefficient of variation. Both networks reached high synchrony by changing the coupling weight between their nodes. Moreover, they exhibited abrupt changes in the synchronization at certain values of the control parameter not necessarily related to a phase transition. While SOPT was observed only in JR model, neither WC nor JR model showed power-law behavior. Our study further investigated the global synchronization phenomenon that is known to exist in pathological brain states, such as seizure. JR model showed global synchronization, while WC model seemed to be more suitable in producing partially synchronized patterns. Corresponding author summaryYousef Jamali received his M.Sc. degree in physics from Sharif University, Tehran, Iran, in 2004, and his Ph.D. degree in physics from Sharif University, Tehran, Iran, in 2009. After finishing his Ph.D. thesis, in 2009, he got two years postdoctoral research associate position at the University of California at Berkeley, Department of Bioengineering. He is currently an Associate Professor in the Applied Mathematics Department (Biomathematics division), at Tarbiat Modares University, Tehran, Iran. His current research interests include the interdisciplinary area of the complex system especially on the modeling of brain. In fact, his interests are how the brain works at the critical state and how this complex system synchronized under different conditions.

neuroscience↗

bioRxiv2023

Programming dynamic division of labor using horizontal gene transfer

The metabolic engineering of microbes has broad applications, including in biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multi-step pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is division of labor (DOL), in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted inter-strain population dynamics. Through modeling, we show that dynamic division of labor (DDOL) mediated by horizontal gene transfer (HGT) can overcome these limitations and enable the robust maintenance of burdensome, multi-step pathways. We also use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.

synthetic biology↗

bioRxiv2023

Multidimensional Analysis of the Adult Human Heart in Health and Disease using Hierarchical Phase-Contrast Tomography (HiP-CT)

Cardiovascular diseases (CVDs) are a leading cause of death worldwide. Current clinical imaging modalities provide resolution adequate for diagnosis but are unable to provide detail of structural changes in the heart, across length-scales, necessary for understanding underlying pathophysiology of disease. Hierarchical Phase-Contrast Tomography (HiP-CT), using new (4th) generation synchrotron sources, potentially overcomes this limitation, allowing micron resolution imaging of intact adult organs with unprecedented detail. In this proof of principle study (n=2), we show the utility of HiP-CT to image whole adult human hearts ex-vivo: one control without known cardiac disease and one with multiple known cardiopulmonary pathologies. The resulting multiscale imaging was able to demonstrate exemplars of anatomy in each cardiac segment along with novel findings in the cardiac conduction system, from gross (20 um/voxel) to cellular scale (2.2 um/voxel), non-destructively, thereby bridging the gap between macroscopic and microscopic investigations. We propose that the technique represents a significant step in virtual autopsy methods for studying structural heart disease, facilitating research into abnormalities across scales and age-groups. It opens up possibilities for understanding and treating disease; and provides a cardiac blueprint with potential for in-silico simulation, device design, virtual surgical training, and bioengineered heart in the future.

pathology↗