Automated "Cells-To-Peptides" Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes.

Mass spectrometry-based quantitative proteomic analysis has proven valuable for clinical and biotechnology-related research and development. Improvements in sensitivity, resolution, and robustness of mass analyzers have also added value. However, manual sample preparation protocols are often a bottleneck for sample throughput and can lead to poor reproducibility, especially for applications where thousands of samples per month must be analyzed. To alleviate these issues, we developed a "cells-to-peptides" automated workflow for Gram-negative bacteria and fungi that includes cell lysis, protein precipitation, resuspension, quantification, normalization, and tryptic digestion. The workflow takes 2 h to process 96 samples from cell pellets to the initiation of the tryptic digestion step and can process 384 samples in parallel. We measured the efficiency of protein extraction from various amounts of cell biomass and optimized the process for standard liquid chromatography-mass spectrometry systems. The automated workflow was tested by preparing 96 Escherichia coli samples and quantifying over 600 peptides that resulted in a median coefficient of variation of 15.8%. Similar technical variance was observed for three other organisms as measured by highly multiplexed LC-MRM-MS acquisition methods. These results show that this automated sample preparation workflow provides robust, reproducible proteomic samples for high-throughput applications.

Integrated LAMP and immunoassay platform for diarrheal disease detection.

The challenges of diagnosing infectious disease, especially in the developing world, and the shortcomings of available instrumentation have exposed the need for portable, easy-to-use diagnostic tools capable of detecting the wide range of causative microbes while operating in low resource settings. We present a centrifugal microfluidic platform that combines ultrasensitive immunoassay and isothermal amplification-based screening for the orthogonal detection of both protein and nucleic acid targets at the point-of-care. A disposable disc with automatic aliquoting inlets is paired with a non-contact heating system and precise rotary control system to yield an easy-to-use, field-deployable platform with versatile screening capabilities. The detection of three enterotoxins (cholera toxin, Staphylococcal enterotoxin B, and Shiga-like toxin 1) and three enteric bacteria (C. jejuni, E. coli, and S. typhimurium) were performed independently and shown to be highly sensitive (limit of detection = 1.35-5.50 ng/mL for immunoassays and 1-30 cells for isothermal amplification), highly exclusive in the presence of non-specific targets, and capable of handling a complex sample matrix like stool. The full panel of toxins and bacteria were reliably detected simultaneously on a single disc at clinically relevant sample concentrations in less than an hour. The ability of our technology to detect multiple analyte types in parallel at the point-of-care can serve a variety of needs, from routine patient care to outbreak triage, in a variety of settings to reduce disease impact and expedite effective treatment.

Engineering glycoside hydrolase stability by the introduction of zinc binding.

The development of robust enzymes, in particular cellulases, is a key step in the success of biological routes to `second-generation' biofuels. The typical sources of the enzymes used to degrade biomass include mesophilic and thermophilic organisms. The endoglucanase J30 from glycoside hydrolase family 9 was originally identified through metagenomic analyses of compost-derived bacterial consortia. These studies, which were tailored to favor growth on targeted feedstocks, have already been shown to identify cellulases with considerable thermal tolerance. The amino-acid sequence of J30 shows comparably low identity to those of previously analyzed enzymes. As an enzyme that combines a well measurable activity with a relatively low optimal temperature (50°C) and a modest thermal tolerance, it offers the potential for structural optimization aimed at increased stability. Here, the crystal structure of wild-type J30 is presented along with that of a designed triple-mutant variant with improved characteristics for industrial applications. Through the introduction of a structural Zn2+ site, the thermal tolerance was increased by more than 10°C and was paralleled by an increase in the catalytic optimum temperature by more than 5°C.

Plant cell wall glycosyltransferases: High-throughput recombinant expression screening and general requirements for these challenging enzymes.

Molecular characterization of plant cell wall glycosyltransferases is a critical step towards understanding the biosynthesis of the complex plant cell wall, and ultimately for efficient engineering of biofuel and agricultural crops. The majority of these enzymes have proven very difficult to obtain in the needed amount and purity for such molecular studies, and recombinant cell wall glycosyltransferase production efforts have largely failed. A daunting number of strategies can be employed to overcome this challenge, including optimization of DNA and protein sequences, choice of expression organism, expression conditions, co-expression partners, purification methods, and optimization of protein solubility and stability. Hence researchers are presented with thousands of potential conditions to test. Ultimately, the subset of conditions that will be sampled depends on practical considerations and prior knowledge of the enzyme(s) being studied. We have developed a rational approach to this process. We devise a pipeline comprising in silico selection of targets and construct design, and high-throughput expression screening, target enrichment, and hit identification. We have applied this pipeline to a test set of Arabidopsis thaliana cell wall glycosyltransferases known to be challenging to obtain in soluble form, as well as to a library of cell wall glycosyltransferases from other plants including agricultural and biofuel crops. The screening results suggest that recombinant cell wall glycosyltransferases in general have a very low soluble:insoluble ratio in lysates from heterologous expression cultures, and that co-expression of chaperones as well as lysis buffer optimization can increase this ratio. We have applied the identified preferred conditions to Reversibly Glycosylated Polypeptide 1 from Arabidopsis thaliana, and processed this enzyme to near-purity in unprecedented milligram amounts. The obtained preparation of Reversibly Glycosylated Polypeptide 1 has the expected arabinopyranose mutase and autoglycosylation activities.

Computational protein design enables a novel one-carbon assimilation pathway.

We describe a computationally designed enzyme, formolase (FLS), which catalyzes the carboligation of three one-carbon formaldehyde molecules into one three-carbon dihydroxyacetone molecule. The existence of FLS enables the design of a new carbon fixation pathway, the formolase pathway, consisting of a small number of thermodynamically favorable chemical transformations that convert formate into a three-carbon sugar in central metabolism. The formolase pathway is predicted to use carbon more efficiently and with less backward flux than any naturally occurring one-carbon assimilation pathway. When supplemented with enzymes carrying out the other steps in the pathway, FLS converts formate into dihydroxyacetone phosphate and other central metabolites in vitro. These results demonstrate how modern protein engineering and design tools can facilitate the construction of a completely new biosynthetic pathway.

A targeted proteomics toolkit for high-throughput absolute quantification of Escherichia coli proteins.

Transformation of engineered Escherichia coli into a robust microbial factory is contingent on precise control of metabolism. Yet, the throughput of omics technologies used to characterize cell components has lagged far behind our ability to engineer novel strains. To expand the utility of quantitative proteomics for metabolic engineering, we validated and optimized targeted proteomics methods for over 400 proteins from more than 20 major pathways in E. coli metabolism. Complementing these methods, we constructed a series of synthetic genes to produce concatenated peptides (QconCAT) for absolute quantification of the proteins and made them available through the Addgene plasmid repository (www.addgene.org). To facilitate high sample throughput, we developed a fast, analytical-flow chromatography method using a 5.5-min gradient (10 min total run time). Overall this toolkit provides an invaluable resource for metabolic engineering by increasing sample throughput, minimizing development time and providing peptide standards for absolute quantification of E. coli proteins.

Cellulosic biomass pretreatment and sugar yields as a function of biomass particle size.

Three lignocellulosic pretreatment techniques (ammonia fiber expansion, dilute acid and ionic liquid) are compared with respect to saccharification efficiency, particle size and biomass composition. In particular, the effects of switchgrass particle size (32-200) on each pretreatment regime are examined. Physical properties of untreated and pretreated samples are characterized using crystallinity, surface accessibility measurements and scanning electron microscopy (SEM) imaging. At every particle size tested, ionic liquid (IL) pretreatment results in greater cell wall disruption, reduced crystallinity, increased accessible surface area, and higher saccharification efficiencies compared with dilute acid and AFEX pretreatments. The advantages of using IL pretreatment are greatest at larger particle sizes (>75 µm).

Improved activity of a thermophilic cellulase, Cel5A, from Thermotoga maritima on ionic liquid pretreated switchgrass.

Ionic liquid pretreatment of biomass has been shown to greatly reduce the recalcitrance of lignocellulosic biomass, resulting in improved sugar yields after enzymatic saccharification. However, even under these improved saccharification conditions the cost of enzymes still represents a significant proportion of the total cost of producing sugars and ultimately fuels from lignocellulosic biomass. Much of the high cost of enzymes is due to the low catalytic efficiency and stability of lignocellulolytic enzymes, especially cellulases, under conditions that include high temperatures and the presence of residual pretreatment chemicals, such as acids, organic solvents, bases, or ionic liquids. Improving the efficiency of the saccharification process on ionic liquid pretreated biomass will facilitate reduced enzyme loading and cost. Thermophilic cellulases have been shown to be stable and active in ionic liquids but their activity is typically at lower levels. Cel5A_Tma, a thermophilic endoglucanase from Thermotoga maritima, is highly active on cellulosic substrates and is stable in ionic liquid environments. Here, our motivation was to engineer mutants of Cel5A_Tma with higher activity on 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]) pretreated biomass. We developed a robotic platform to screen a random mutagenesis library of Cel5A_Tma. Twelve mutants with 25-42% improvement in specific activity on carboxymethyl cellulose and up to 30% improvement on ionic-liquid pretreated switchgrass were successfully isolated and characterized from a library of twenty thousand variants. Interestingly, most of the mutations in the improved variants are located distally to the active site on the protein surface and are not directly involved with substrate binding.

Coupled high-throughput functional screening and next generation sequencing for identification of plant polymer decomposing enzymes in metagenomic libraries.

Recent advances in sequencing technologies generate new predictions and hypotheses about the functional roles of environmental microorganisms. Yet, until we can test these predictions at a scale that matches our ability to generate them, most of them will remain as hypotheses. Function-based mining of metagenomic libraries can provide direct linkages between genes, metabolic traits and microbial taxa and thus bridge this gap between sequence data generation and functional predictions. Here we developed high-throughput screening assays for function-based characterization of activities involved in plant polymer decomposition from environmental metagenomic libraries. The multiplexed assays use fluorogenic and chromogenic substrates, combine automated liquid handling and use a genetically modified expression host to enable simultaneous screening of 12,160 clones for 14 activities in a total of 170,240 reactions. Using this platform we identified 374 (0.26%) cellulose, hemicellulose, chitin, starch, phosphate and protein hydrolyzing clones from fosmid libraries prepared from decomposing leaf litter. Sequencing on the Illumina MiSeq platform, followed by assembly and gene prediction of a subset of 95 fosmid clones, identified a broad range of bacterial phyla, including Actinobacteria, Bacteroidetes, multiple Proteobacteria sub-phyla in addition to some Fungi. Carbohydrate-active enzyme genes from 20 different glycoside hydrolase (GH) families were detected. Using tetranucleotide frequency (TNF) binning of fosmid sequences, multiple enzyme activities from distinct fosmids were linked, demonstrating how biochemically-confirmed functional traits in environmental metagenomes may be attributed to groups of specific organisms. Overall, our results demonstrate how functional screening of metagenomic libraries can be used to connect microbial functionality to community composition and, as a result, complement large-scale metagenomic sequencing efforts.

Identification of pathogen and host-response markers correlated with periodontal disease.

BACKGROUND: Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, such as cardiovascular disease and stroke. The development of rapid point-of-care (POC) chairside diagnostics has the potential for the early detection of periodontal infection and progression to identify incipient disease and reduce health care costs. However, validation of effective diagnostics requires the identification and verification of biomarkers correlated with disease progression. This clinical study sought to determine the ability of putative host- and microbially derived biomarkers to identify periodontal disease status from whole saliva and plaque biofilm. METHODS: One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitis population. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levels of multiple proinflammatory cytokines and bone resorptive/turnover markers. RESULTS: Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbial plaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of models for periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9 were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, respectively. The generation of receiver operating characteristic curves demonstrated that permutations of salivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple combinations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex anaerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highly accurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levels displayed robust combinatorial characteristics in predicting periodontal disease severity (area under the curve = 0.88; odds ratio = 24.6; 95% confidence interval: 5.2 to 116.5). CONCLUSIONS: Using qPCR and sensitive immunoassays, we identified host- and bacterially derived biomarkers correlated with periodontal disease. This approach offers significant potential for the discovery of biomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemic diseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.

Integrated microfluidic platform for oral diagnostics.

While many point-of-care (POC) diagnostic methods have been developed for blood-borne analytes, development of saliva-based POC diagnostics is in its infancy. We have developed a portable microfluidic device for detection of potential biomarkers of periodontal disease in saliva. The device performs rapid microfluidic chip-based immunoassays (<3-10 min) with low sample volume requirements (10 microL) and appreciable sensitivity (nM-pM). Our microfluidic method facilitates hands-free saliva analysis by integrating sample pretreatment (filtering, enrichment, mixing) with electrophoretic immunoassays to quickly measure analyte concentrations in minimally pretreated saliva samples. The microfluidic chip has been integrated with miniaturized electronics, optical elements, such as diode lasers, fluid-handling components, and data acquisition software to develop a portable, self-contained device. The device and methods are being tested by detecting potential biomarkers in saliva samples from patients diagnosed with periodontal disease. Our microchip-based analysis can readily be extended to detection of biomarkers of other diseases, both oral and systemic, in saliva and other oral fluids.

Microfluidic immunoassays as rapid saliva-based clinical diagnostics.

At present, point-of-care (POC) diagnostics typically provide a binary indication of health status (e.g., home pregnancy test strip). Before anticipatory use of diagnostics for assessment of complex diseases becomes widespread, development of sophisticated bioassays capable of quantitatively measuring disease biomarkers is necessary. Successful translation of new bioassays into clinical settings demands the ability to monitor both the onset and progression of disease. Here we report on a clinical POC diagnostic that enables rapid quantitation of an oral disease biomarker in human saliva by using a monolithic disposable cartridge designed to operate in a compact analytical instrument. Our microfluidic method facilitates hands-free saliva analysis by integrating sample pretreatment (filtering, enrichment, mixing) with electrophoretic immunoassays to quickly measure analyte concentrations in minimally pretreated saliva samples. Using 20 microl of saliva, we demonstrate rapid (<10 min) measurement of the collagen-cleaving enzyme matrix metalloproteinase-8 (MMP-8) in saliva from healthy and periodontally diseased subjects. In addition to physiologically measurable indicators of periodontal disease, conventional measurements of salivary MMP-8 were used to validate the microfluidic assays described in this proof-of-principle study. The microchip-based POC diagnostic demonstrated is applicable to rapid, reliable measurement of proteinaceous disease biomarkers in biological fluids.