Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases.

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequence- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (logistic regression, random forest, gradient-boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset, although random forest offers some advantages. This approach is intended to be highly modular with respect to physicochemical property calculations and software used for structural modeling and docking.

Proteomics-Based Tools for Evaluation of Cell-Free Protein Synthesis.

Cell-free protein synthesis (CFPS) has the potential to produce enzymes, therapeutic agents, and other proteins, while circumventing difficulties associated with in vivo heterologous expression. However, the contents of the cell-free extracts used to carry out synthesis are generally not characterized, which hampers progress toward enhancing yield or functional activity of the target protein. We explored the utility of mass spectrometry (MS)-based proteomics for characterizing the bacterial extracts used for transcribing and translating gene sequences into proteins as well as the products of CFPS reactions. Full proteome experiments identified over 1000 proteins per reaction. The complete set of proteins necessary for transcription and translation were found, demonstrating the ability to define potential metabolic capabilities of the extract. Further, MS-based techniques allowed characterization of the CFPS product and provided insight into the synthesis reaction and potential functional activity of the product. These capabilities were demonstrated using two different CFPS products, the commonly used standard green fluorescent protein (GFP, 27 kDa) and the polyketide synthase DEBS1 (394 kDa). For the large, multidomain DEBS1, substantial premature termination of protein translation was observed. Additionally, MS/MS analysis, as part of a conventional full proteomics workflow, identified post-translational modifications, including the chromophore in GFP, as well as the three phosphopantetheinylation sites in DEBS1. A hypothesis-driven approach focused on these three sites identified that all were correctly modified for DEBS1 expressed in vivo but with less complete coverage for protein expressed in CFPS reactions. These post-translational modifications are essential for functional activity, and the ability to identify them with mass spectrometry is valuable for judging the success of the CFPS reaction. Collectively, the use of MS-based proteomics will prove advantageous for advancing the application of CFPS and related techniques.

Toward Microfluidic Reactors for Cell-Free Protein Synthesis at the Point-of-Care.

Cell-free protein synthesis (CFPS) is a powerful technology that allows for optimization of protein production without maintenance of a living system. Integrated within micro and nanofluidic architectures, CFPS can be optimized for point-of-care use. Here, the development of a microfluidic bioreactor designed to facilitate the production of a single-dose of a therapeutic protein, in a small footprint device at the point-of-care, is described. This new design builds on the use of a long, serpentine channel bioreactor and is enhanced by integrating a nanofabricated membrane to allow exchange of materials between parallel "reactor" and "feeder" channels. This engineered membrane facilitates the exchange of metabolites, energy, and inhibitory species, and can be altered by plasma-enhanced chemical vapor deposition and atomic layer deposition to tune the exchange rate of small molecules. This allows for extended reaction times and improved yields. Further, the reaction product and higher molecular weight components of the transcription/translation machinery in the reactor channel can be retained. It has been shown that the microscale bioreactor design produces higher protein yields than conventional tube-based batch formats, and that product yields can be dramatically improved by facilitating small molecule exchange within the dual-channel bioreactor.

Identifying Candidate Biomarkers of Ionizing Radiation in Human Pulmonary Microvascular Lumens Using Microfluidics-A Pilot Study.

The microvasculature system is critical for the delivery and removal of key nutrients and waste products and is significantly damaged by ionizing radiation. Single-cell capillaries and microvasculature structures are the primary cause of circulatory dysfunction, one that results in morbidities leading to progressive tissue and organ failure and premature death. Identifying tissue-specific biomarkers that are predictive of the extent of tissue and organ damage will aid in developing medical countermeasures for treating individuals exposed to ionizing radiation. In this pilot study, we developed and tested a 17 µL human-derived microvascular microfluidic lumen for identifying candidate biomarkers of ionizing radiation exposure. Through mass-spectrometry-based proteomics, we detected 35 proteins that may be candidate early biomarkers of ionizing radiation exposure. This pilot study demonstrates the feasibility of using humanized microfluidic and organ-on-a-chip systems for biomarker discovery studies. A more elaborate study of sufficient statistical power is needed to identify candidate biomarkers and test medical countermeasures of ionizing radiation.

A Microbe Associated with Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice.

The microbiome influences health and disease through complex networks of host genetics, genomics, microbes, and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in laboratory mice (Mus musculus) enables data-driven discovery of biological network components and mechanisms of host-microbial interactions underlying disease phenotypes. To examine the interplay among the whole host genome, transcriptome, and microbiome, we mapped QTL and correlated the abundance of cecal messenger RNA, luminal microflora, physiology, and behavior in a highly diverse Collaborative Cross breeding population. One such relationship, regulated by a variant on chromosome 7, was the association of Odoribacter (Bacteroidales) abundance and sleep phenotypes. In a test of this association in the BKS.Cg-Dock7m +/+ Leprdb/J mouse model of obesity and diabetes, known to have abnormal sleep and colonization by Odoribacter, treatment with antibiotics altered sleep in a genotype-dependent fashion. The many other relationships extracted from this study can be used to interrogate other diseases, microbes, and mechanisms.

Efficient gene-driven germ-line point mutagenesis of C57BL/6J mice.

BACKGROUND: Analysis of an allelic series of point mutations in a gene, generated by N-ethyl-N-nitrosourea (ENU) mutagenesis, is a valuable method for discovering the full scope of its biological function. Here we present an efficient gene-driven approach for identifying ENU-induced point mutations in any gene in C57BL/6J mice. The advantage of such an approach is that it allows one to select any gene of interest in the mouse genome and to go directly from DNA sequence to mutant mice. RESULTS: We produced the Cryopreserved Mutant Mouse Bank (CMMB), which is an archive of DNA, cDNA, tissues, and sperm from 4,000 G1 male offspring of ENU-treated C57BL/6J males mated to untreated C57BL/6J females. Each mouse in the CMMB carries a large number of random heterozygous point mutations throughout the genome. High-throughput Temperature Gradient Capillary Electrophoresis (TGCE) was employed to perform a 32-Mbp sequence-driven screen for mutations in 38 PCR amplicons from 11 genes in DNA and/or cDNA from the CMMB mice. DNA sequence analysis of heteroduplex-forming amplicons identified by TGCE revealed 22 mutations in 10 genes for an overall mutation frequency of 1 in 1.45 Mbp. All 22 mutations are single base pair substitutions, and nine of them (41%) result in nonconservative amino acid substitutions. Intracytoplasmic sperm injection (ICSI) of cryopreserved spermatozoa into B6D2F1 or C57BL/6J ova was used to recover mutant mice for nine of the mutations to date. CONCLUSIONS: The inbred C57BL/6J CMMB, together with TGCE mutation screening and ICSI for the recovery of mutant mice, represents a valuable gene-driven approach for the functional annotation of the mammalian genome and for the generation of mouse models of human genetic diseases. The ability of ENU to induce mutations that cause various types of changes in proteins will provide additional insights into the functions of mammalian proteins that may not be detectable by knockout mutations.

Light Chain Amyloid Fibrils Cause Metabolic Dysfunction in Human Cardiomyocytes.

Light chain (AL) amyloidosis is the most common form of systemic amyloid disease, and cardiomyopathy is a dire consequence, resulting in an extremely poor prognosis. AL is characterized by the production of monoclonal free light chains that deposit as amyloid fibrils principally in the heart, liver, and kidneys causing organ dysfunction. We have studied the effects of amyloid fibrils, produced from recombinant λ6 light chain variable domains, on metabolic activity of human cardiomyocytes. The data indicate that fibrils at 0.1 µM, but not monomer, significantly decrease the enzymatic activity of cellular NAD(P)H-dependent oxidoreductase, without causing significant cell death. The presence of amyloid fibrils did not affect ATP levels; however, oxygen consumption was increased and reactive oxygen species were detected. Confocal fluorescence microscopy showed that fibrils bound to and remained at the cell surface with little fibril internalization. These data indicate that AL amyloid fibrils severely impair cardiomyocyte metabolism in a dose dependent manner. These data suggest that effective therapeutic intervention for these patients should include methods for removing potentially toxic amyloid fibrils.

Volume labeling with Alexa Fluor dyes and surface functionalization of highly sensitive fluorescent silica (SiO2) nanoparticles.

A new synthesis approach is described that allows the direct incorporation of fluorescent labels into the volume or body of SiO2 nanoparticles. In this process, fluorescent Alexa Fluor dyes with different emission wavelengths were covalently incorporated into the SiO2 nanoparticles during their formation by the hydrolysis of tetraethoxysilane. The dye molecules were homogeneously distributed throughout the SiO2 nanoparticles. The quantum yields of the Alexa Fluor volume-labeled SiO2 nanoparticles were much higher than nanoparticles labeled using conventional organic dyes. The size of the resulting nanoparticles was controlled using microemulsion reaction media with sizes in the range of 20-100 nm and a polydispersity of <15%. In comparison with conventional surface tagged particles created by post-synthesis modification, this process maintains the physical and surface chemical properties that have the most pronounced effect on colloidal stability and interactions with their surroundings. These volume-labeled nanoparticles have proven to be extremely robust, showing excellent signal strength, negligible photobleaching, and minimal loss of functional organic components. The native or "free" surface of the volume-labeled particles can be altered to achieve a specific surface functionality without altering fluorescence. Their utility was demonstrated for visualizing the association of surface-modified fluorescent particles with cultured macrophages. Differences in particle agglomeration and cell association were clearly associated with differences in observed nanoparticle toxicity. The capacity to maintain particle fluorescence while making significant changes to surface chemistry makes these particles extremely versatile and useful for studies of particle agglomeration, uptake, and transport in environmental and biological systems.

Dynamic development of the protein corona on silica nanoparticles: composition and role in toxicity.

The formation and composition of the protein corona on silica (SiO2) nanoparticles (NP) with different surface chemistries was evaluated over time. Native SiO2, amine (-NH2) and carboxy (-COO(-)) modified NP were examined following incubation in mammalian growth media containing fetal bovine serum (FBS) for 1, 4, 24 and 48 hours. The protein corona transition from its early dynamic state to the later more stable corona was evaluated using mass spectrometry. The NP diameter was 22.4 ± 2.2 nm measured by scanning transmission electron microscopy (STEM). Changes in hydrodynamic diameter and agglomeration kinetics were studied using dynamic light scattering (DLS). The initial surface chemistry of the NP played an important role in the development and final composition of the protein corona, impacting agglomeration kinetics and NP toxicity. Particle toxicity, indicated by changes in membrane integrity and mitochondrial activity, was measured by lactate dehydrogenase (LDH) release and tetrazolium reduction (MTT), respectively, in mouse alveolar macrophages (RAW264.7) and mouse lung epithelial cells (C10). SiO2-COO(-) NP had a slower agglomeration rate, formed smaller aggregates, and exhibited lower cytotoxicity compared to SiO2 and SiO2-NH2. Composition of the protein corona for each of the three NP was unique, indicating a strong dependence of corona development on NP surface chemistry. This work underscores the need to understand all aspects of NP toxicity, particularly the influence of agglomeration on effective dose and particle size. Furthermore, the interplay between materials and local biological environment is emphasized and highlights the need to conduct toxicity profiling under physiologically relevant conditions that provide an appropriate estimation of material modifications that occur during exposure in natural environments.

Analysis of tight junction formation and integrity.

In this paper, we study segmentation of tight junctions and analyze the formation and integrity of tight junctions in large-scale confocal image stacks, a challenging biological problem because of the low spatial resolution images and the presence of breaks in tight junction structure. We present an automated, three-step processing approach for tight junction analysis. In our approach, we first localize each individual nucleus in the image by using thresholding, morphological filters and active contours. By using each nucleus position as a seed point, we automatically segment the cell body based on the active contour. We then use an intensity-based skeletonization algorithm to generate the boundary regions for each cell, and features are extracted from tight junctions associated with each cell to assess tight junction continuity. Based on qualitative results and quantitative comparisons, we show that we are able to automatically segment tight junctions and compute relevant features that provide a quantitative measure of tight junction formation to which the permeability of the cell monolayer can ultimately be correlated.

Host genetic and environmental effects on mouse intestinal microbiota.

The mammalian gut harbors complex and variable microbial communities, across both host phylogenetic space and conspecific individuals. A synergy of host genetic and environmental factors shape these communities and account for their variability, but their individual contributions and the selective pressures involved are still not well understood. We employed barcoded pyrosequencing of V1-2 and V4 regions of bacterial small subunit ribosomal RNA genes to characterize the effects of host genetics and environment on cecum assemblages in 10 genetically distinct, inbred mouse strains. Eight of these strains are the foundation of the Collaborative Cross (CC), a panel of mice derived from a genetically diverse set of inbred founder strains, designed specifically for complex trait analysis. Diversity of gut microbiota was characterized by complementing phylogenetic and distance-based, sequence-clustering approaches. Significant correlations were found between the mouse strains and their gut microbiota, reflected by distinct bacterial communities. Cohabitation and litter had a reduced, although detectable effect, and the microbiota response to these factors varied by strain. We identified bacterial phylotypes that appear to be discriminative and strain-specific to each mouse line used. Cohabitation of different strains of mice revealed an interaction of host genetic and environmental factors in shaping gut bacterial consortia, in which bacterial communities became more similar but retained strain specificity. This study provides a baseline analysis of intestinal bacterial communities in the eight CC progenitor strains and will be linked to integrated host genotype, phenotype and microbiota research on the resulting CC panel.