Human biomonitoring without in-person interaction: public health engagements during the COVID-19 pandemic and future implications.

BACKGROUND: Public health initiatives, including human biomonitoring, have been impacted by unique challenges since the onset of the COVID-19 pandemic, compounding a decades-long trend of declining public participation. To combat low public participation rates, public health professionals often employ extensive engagement approaches including in-person interactions related to enrollment and sampling, success of which is an essential component of a statistically defensible study. The onset of the COVID-19 pandemic challenged public health programs to diversify engagement and sampling approaches, limiting direct interactions for the health and safety of the population. This study explores biomonitoring recruitment strategies through non-contact mechanisms and evaluate the application feasibility for population-based studies. METHODS: The Iowa Biomonitoring Program at the State Hygienic Laboratory developed a human biomonitoring study that utilized a multifaceted, distance-based approach. Traditional techniques, such as mailed recruitment invitations and phone-based discussions, were coupled with internet-based surveys and self-collected, shipped urine and water samples. Participation rates were evaluated by employing different mailing methods, and the demographics of enrolled participants were examined. RESULTS: This non-human contact approach achieved a nearly 14% participation rate among a rural population, well above our target rates. Our improved mailing strategy for targeting initially unresponsive participants yielded a significantly increase in the participation rates. The respondents were predominantly individuals with educational attainment of at least high school level. Among all the eligible participants, 83% submitted self-collected samples, a rate comparable to the National Health and Nutrition Examination Survey which involved in-person interviews. CONCLUSIONS: The practice of engaging a rural population during the COVID-19 pandemic by transitioning from face-to-face interactions to a combination of mailing and internet-based approaches resulted in higher-than-expected participant recruitment and sample collection rates. Given the declining trend in the response rates for population-based survey studies, our results suggest conducting human biomonitoring without direct human interaction is feasible, which provides further opportunity to improve response rates and the relevance and reach of public health initiatives.

Enhanced limonene production in cyanobacteria reveals photosynthesis limitations.

Terpenes are the major secondary metabolites produced by plants, and have diverse industrial applications as pharmaceuticals, fragrance, solvents, and biofuels. Cyanobacteria are equipped with efficient carbon fixation mechanism, and are ideal cell factories to produce various fuel and chemical products. Past efforts to produce terpenes in photosynthetic organisms have gained only limited success. Here we engineered the cyanobacterium Synechococcus elongatus PCC 7942 to efficiently produce limonene through modeling guided study. Computational modeling of limonene flux in response to photosynthetic output has revealed the downstream terpene synthase as a key metabolic flux-controlling node in the MEP (2-C-methyl-d-erythritol 4-phosphate) pathway-derived terpene biosynthesis. By enhancing the downstream limonene carbon sink, we achieved over 100-fold increase in limonene productivity, in contrast to the marginal increase achieved through stepwise metabolic engineering. The establishment of a strong limonene flux revealed potential synergy between photosynthate output and terpene biosynthesis, leading to enhanced carbon flux into the MEP pathway. Moreover, we show that enhanced limonene flux would lead to NADPH accumulation, and slow down photosynthesis electron flow. Fine-tuning ATP/NADPH toward terpene biosynthesis could be a key parameter to adapt photosynthesis to support biofuel/bioproduct production in cyanobacteria.

A Versatile Approach for Site-Specific Lysine Acylation in Proteins.

Using amber suppression in coordination with a mutant pyrrolysyl-tRNA synthetase-tRNAPyl pair, azidonorleucine is genetically encoded in E. coli. Its genetic incorporation followed by traceless Staudinger ligation with a phosphinothioester allows the convenient synthesis of a protein with a site-specifically installed lysine acylation. By simply changing the phosphinothioester identity, any lysine acylation type could be introduced. Using this approach, we demonstrated that both lysine acetylation and lysine succinylation can be installed selectively in ubiquitin and synthesized histone H3 with succinylation at its K4 position (H3K4su). Using an H3K4su-H4 tetramer as a substrate, we further confirmed that Sirt5 is an active histone desuccinylase. Lysine succinylation is a recently identified post-translational modification. The reported technique makes it possible to explicate regulatory functions of this modification in proteins.

A Genetically Encoded Allysine for the Synthesis of Proteins with Site-Specific Lysine Dimethylation.

Using the amber suppression approach, Nϵ -(4-azidobenzoxycarbonyl)-δ,ϵ-dehydrolysine, an allysine precursor is genetically encoded in E. coli. Its genetic incorporation followed by two sequential biocompatible reactions allows convenient synthesis of proteins with site-specific lysine dimethylation. Using this approach, dimethyl-histone H3 and p53 proteins have been synthesized and used to probe functions of epigenetic enzymes including histone demethylase LSD1 and histone acetyltransferase Tip60. We confirmed that LSD1 is catalytically active toward H3K4me2 and H3K9me2 but inert toward H3K36me2, and methylation at p53 K372 directly activates Tip60 for its catalyzed acetylation at p53 K120.

JAZ7 negatively regulates dark-induced leaf senescence in Arabidopsis.

JASMONATE ZIM-domain (JAZ) proteins play important roles in plant defence and growth by regulating jasmonate signalling. Through data mining, we discovered that the JAZ7 gene was up-regulated in darkness. In the dark, the jaz7 mutant displayed more severe leaf yellowing, quicker chlorophyll degradation, and higher hydrogen peroxide accumulation compared with wild-type (WT) plants. The mutant phenotype of dark-induced leaf senescence could be rescued in the JAZ7-complemented and -overexpression lines. Moreover, the double mutants of jaz7 myc2 and jaz7 coi1 exhibited delayed leaf senescence. We further employed GeneChip analysis to study the molecular mechanism. Some key genes down-regulated in the triple mutant myc2 myc3 myc4 were up-regulated in the jaz7 mutant under darkness. The Gene Ontology terms 'leaf senescence' and 'cell death' were significantly enriched in the differentially expressed genes. Combining the genetic and transcriptomic analyses together, we proposed a model whereby darkness can induce JAZ7, which might further block MYC2 to suppress dark-induced leaf senescence. In darkness, the mutation of JAZ7 might partially liberate MYC2/MYC3/MYC4 from suppression, leading the MYC proteins to bind to the G-box/G-box-like motifs in the promoters, resulting in the up-regulation of the downstream genes related to indole-glucosinolate biosynthesis, sulphate metabolism, callose deposition, and JA-mediated signalling pathways. In summary, our genetic and transcriptomic studies established the JAZ7 protein as an important regulator in dark-induced leaf senescence.

Application of an improved proteomics method for abundant protein cleanup: molecular and genomic mechanisms study in plant defense.

High abundance proteins like ribulose-1,5-bisphosphate carboxylase oxygenase (Rubisco) impose a consistent challenge for the whole proteome characterization using shot-gun proteomics. To address this challenge, we developed and evaluated Polyethyleneimine Assisted Rubisco Cleanup (PARC) as a new method by combining both abundant protein removal and fractionation. The new approach was applied to a plant insect interaction study to validate the platform and investigate mechanisms for plant defense against herbivorous insects. Our results indicated that PARC can effectively remove Rubisco, improve the protein identification, and discover almost three times more differentially regulated proteins. The significantly enhanced shot-gun proteomics performance was translated into in-depth proteomic and molecular mechanisms for plant insect interaction, where carbon re-distribution was used to play an essential role. Moreover, the transcriptomic validation also confirmed the reliability of PARC analysis. Finally, functional studies were carried out for two differentially regulated genes as revealed by PARC analysis. Insect resistance was induced by over-expressing either jacalin-like or cupin-like genes in rice. The results further highlighted that PARC can serve as an effective strategy for proteomics analysis and gene discovery.

Artificial intelligence-based HDX (AI-HDX) prediction reveals fundamental characteristics to protein dynamics: Mechanisms on SARS-CoV-2 immune escape.

Three-dimensional structure and dynamics are essential for protein function. Advancements in hydrogen-deuterium exchange (HDX) techniques enable probing protein dynamic information in physiologically relevant conditions. HDX-coupled mass spectrometry (HDX-MS) has been broadly applied in pharmaceutical industries. However, it is challenging to obtain dynamics information at the single amino acid resolution and time consuming to perform the experiments and process the data. Here, we demonstrate the first deep learning model, artificial intelligence-based HDX (AI-HDX), that predicts intrinsic protein dynamics based on the protein sequence. It uncovers the protein structural dynamics by combining deep learning, experimental HDX, sequence alignment, and protein structure prediction. AI-HDX can be broadly applied to drug discovery, protein engineering, and biomedical studies. As a demonstration, we elucidated receptor-binding domain structural dynamics as a potential mechanism of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody efficacy and immune escape. AI-HDX fundamentally differs from the current AI tools for protein analysis and may transform protein design for various applications.

Genomic Diversity and Phenotypic Variation in Fungal Decomposers Involved in Bioremediation of Persistent Organic Pollutants.

Fungi work as decomposers to break down organic carbon, deposit recalcitrant carbon, and transform other elements such as nitrogen. The decomposition of biomass is a key function of wood-decaying basidiomycetes and ascomycetes, which have the potential for the bioremediation of hazardous chemicals present in the environment. Due to their adaptation to different environments, fungal strains have a diverse set of phenotypic traits. This study evaluated 320 basidiomycetes isolates across 74 species for their rate and efficiency of degrading organic dye. We found that dye-decolorization capacity varies among and within species. Among the top rapid dye-decolorizing fungi isolates, we further performed genome-wide gene family analysis and investigated the genomic mechanism for their most capable dye-degradation capacity. Class II peroxidase and DyP-type peroxidase were enriched in the fast-decomposer genomes. Gene families including lignin decomposition genes, reduction-oxidation genes, hydrophobin, and secreted peptidases were expanded in the fast-decomposer species. This work provides new insights into persistent organic pollutant removal by fungal isolates at both phenotypic and genotypic levels.

Lytic polysaccharide monooxygenase synergized with lignin-degrading enzymes for efficient lignin degradation.

Even though the discovery of lytic polysaccharide monooxygenases (LPMOs) has fundamentally shifted our understanding of biomass degradation, most of the current studies focused on their roles in carbohydrate oxidation. However, no study demonstrated if LPMO could directly participate to the process of lignin degradation in lignin-degrading microbes. This study showed that LPMO could synergize with lignin-degrading enzymes for efficient lignin degradation in white-rot fungi. The transcriptomics analysis of fungi Irpex lacteus and Dichomitus squalens during their lignocellulosic biomass degradation processes surprisingly highlighted that LPMOs co-regulated with lignin-degrading enzymes, indicating their more versatile roles in the redox network. Biochemical analysis further confirmed that the purified LPMO from I. lacteus CD2 could use diverse electron donors to produce H2O2, drive Fenton reaction, and synergize with manganese peroxidase for lignin oxidation. The results thus indicated that LPMO might uniquely leverage the redox network toward dynamic and efficient degradation of different cell wall components.

Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses.

BACKGROUND: Multidimensional protein identification technology (MudPIT)-based shot-gun proteomics has been proven to be an effective platform for functional proteomics. In particular, the various sample preparation methods and bioinformatics tools can be integrated to improve the proteomics platform for applications like target organelle proteomics. We have recently integrated a rapid sample preparation method and bioinformatics classification system for comparative analysis of plant responses to two plant hormones, zeatin and brassinosteroid (BR). These hormones belong to two distinct classes of plant growth regulators, yet both can promote cell elongation and growth. An understanding of the differences and the cross-talk between the two types of hormone responses will allow us to better understand the molecular mechanisms and to identify new candidate genes for plant engineering. RESULTS: As compared to traditional organelle proteomics, the organelle-enrichment method both simplifies the sample preparation and increases the number of proteins identified in the targeted organelle as well as the entire sample. Both zeatin and BR induce dramatic changes in signaling and metabolism. Their shared-regulated protein components indicate that both hormones may down-regulate some key components in auxin responses. However, they have shown distinct induction and suppression of metabolic pathways in mitochondria and chloroplast. For zeatin, the metabolic pathways in sucrose and starch biosynthesis and utilization were significantly changed, yet the lipid biosynthesis remained unchanged. For BR, lipid biosynthesis and ß-oxidation were both down-regulated, yet the changes in sucrose and starch metabolism were minor. CONCLUSIONS: We present a rapid sample preparation method and bioinformatics classification for effective proteomics analysis of plant hormone responses. The study highlighted the largely differing response to zeatin and brassinosteroid by the metabolic pathways in chloroplast and mitochondria.

Design of biomass-based renewable materials for environmental remediation.

Various materials have been used to remove environmental contaminants for decades and have been an effective strategy for environmental cleanups. The current nonrenewable materials used for this purpose could impose secondary hazards and challenges in further downstream treatments. Biomass-based materials present viable, renewable, and sustainable solutions for environmental remediation. Recent biotechnology advances have developed biomaterials with new capacities, such as highly efficient biodegradation and treatment train integration. This review systemically discusses how biotechnology has empowered biomass-derived and bioinspired materials for environmental remediation sustainably and cost-effectively.

Altered Carbon Partitioning Enhances CO2 to Terpene Conversion in Cyanobacteria.

Photosynthetic terpene production represents one of the most carbon and energy-efficient routes for converting CO2 into hydrocarbon. In photosynthetic organisms, metabolic engineering has led to limited success in enhancing terpene productivity, partially due to the low carbon partitioning. In this study, we employed systems biology analysis to reveal the strong competition for carbon substrates between primary metabolism (e.g., sucrose, glycogen, and protein synthesis) and terpene biosynthesis in Synechococcus elongatus PCC 7942. We then engineered key "source" and "sink" enzymes. The "source" limitation was overcome by knocking out either sucrose or glycogen biosynthesis to significantly enhance limonene production via altered carbon partitioning. Moreover, a fusion enzyme complex with geranyl diphosphate synthase (GPPS) and limonene synthase (LS) was designed to further improve pathway kinetics and substrate channeling. The synergy between "source" and "sink" achieved a limonene titer of 21.0 mg/L. Overall, the study demonstrates that balancing carbon flux between primary and secondary metabolism can be an effective approach to enhance terpene bioproduction in cyanobacteria. The design of "source" and "sink" synergy has significant potential in improving natural product yield in photosynthetic species.

Microbial lignin valorization through depolymerization to aromatics conversion.

Lignin is the most abundant source of renewable aromatic biopolymers and its valorization presents significant value for biorefinery sustainability, which promotes the utilization of renewable resources. However, it is challenging to fully convert the structurally complex, heterogeneous, and recalcitrant lignin into high-value products. The in-depth research on the lignin degradation mechanism, microbial metabolic pathways, and rational design of new systems using synthetic biology have significantly accelerated the development of lignin valorization. This review summarizes the key enzymes involved in lignin depolymerization, the mechanisms of microbial lignin conversion, and the lignin valorization application with integrated systems and synthetic biology. Current challenges and future strategies to further study lignin biodegradation and the trends of lignin valorization are also discussed.

Sustainable environmental remediation via biomimetic multifunctional lignocellulosic nano-framework.

Chemical pollution threatens human health and ecosystem sustainability. Persistent organic pollutants (POPs) like per- and polyfluoroalkyl substances (PFAS) are expensive to clean up once emitted. Innovative and synergistic strategies are urgently needed, yet process integration and cost-effectiveness remain challenging. An in-situ PFAS remediation system is developed to employ a plant-derived biomimetic nano-framework to achieve highly efficient adsorption and subsequent fungal biotransformation synergistically. The multiple component framework is presented as Renewable Artificial Plant for In-situ Microbial Environmental Remediation (RAPIMER). RAPIMER exhibits high adsorption capacity for the PFAS compounds and diverse adsorption capability toward co-contaminants. Subsequently, RAPIMER provides the substrates and contaminants for in situ bioremediation via fungus Irpex lacteus and promotes PFAS detoxification. RAPIMER arises from cheap lignocellulosic sources, enabling a broader impact on sustainability and a means for low-cost pollutant remediation.

Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity.

Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning to inform the design of a semi-continuous algal cultivation (SAC) to sustain optimal cell growth and minimize mutual shading. An aggregation-based sedimentation (ABS) strategy is then designed to achieve low-cost biomass harvesting and economical SAC. The ABS is achieved by engineering a fast-growing strain, Synechococcus elongatus UTEX 2973, to produce limonene, which increases cyanobacterial cell surface hydrophobicity and enables efficient cell aggregation and sedimentation. SAC unleashes cyanobacterial growth potential with 0.1 g/L/hour biomass productivity and 0.2 mg/L/hour limonene productivity over a sustained period in photobioreactors. Scaling-up the SAC with an outdoor pond system achieves a biomass yield of 43.3 g/m2/day, bringing the minimum biomass selling price down to approximately $281 per ton.

HDX-analyzer: a novel package for statistical analysis of protein structure dynamics.

BACKGROUND: HDX mass spectrometry is a powerful platform to probe protein structure dynamics during ligand binding, protein folding, enzyme catalysis, and such. HDX mass spectrometry analysis derives the protein structure dynamics based on the mass increase of a protein of which the backbone protons exchanged with solvent deuterium. Coupled with enzyme digestion and MS/MS analysis, HDX mass spectrometry can be used to study the regional dynamics of protein based on the m/z value or percentage of deuterium incorporation for the digested peptides in the HDX experiments. Various software packages have been developed to analyze HDX mass spectrometry data. Despite the progresses, proper and explicit statistical treatment is still lacking in most of the current HDX mass spectrometry software. In order to address this issue, we have developed the HDXanalyzer for the statistical analysis of HDX mass spectrometry data using R, Python, and RPY2. IMPLEMENTATION AND RESULTS: HDXanalyzer package contains three major modules, the data processing module, the statistical analysis module, and the user interface. RPY2 is employed to enable the connection of these three components, where the data processing module is implemented using Python and the statistical analysis module is implemented with R. RPY2 creates a low-level interface for R and allows the effective integration of statistical module for data processing. The data processing module generates the centroid for the peptides in form of m/z value, and the differences of centroids between the peptides derived from apo and ligand-bound protein allow us to evaluate whether the regions have significant changes in structure dynamics or not. Another option of the software is to calculate the deuterium incorporation rate for the comparison. The two types of statistical analyses are Paired Student's t-test and the linear combination of the intercept for multiple regression and ANCOVA model. The user interface is implemented with wxpython to facilitate the data visualization in graphs and the statistical analysis output presentation. In order to evaluate the software, a previously published xylanase HDX mass spectrometry analysis dataset is processed and presented. The results from the different statistical analysis methods are compared and shown to be similar. The statistical analysis results are overlaid with the three dimensional structure of the protein to highlight the regional structure dynamics changes in the xylanase enzyme. CONCLUSION: Statistical analysis provides crucial evaluation of whether a protein region is significantly protected or unprotected during the HDX mass spectrometry studies. Although there are several other available software programs to process HDX experimental data, HDXanalyzer is the first software program to offer multiple statistical methods to evaluate the changes in protein structure dynamics based on HDX mass spectrometry analysis. Moreover, the statistical analysis can be carried out for both m/z value and deuterium incorporation rate. In addition, the software package can be used for the data generated from a wide range of mass spectrometry instruments.

Determination of aflatoxins in animal feeds by liquid chromatography/tandem mass spectrometry with isotope dilution.

The objective of the present study is to develop a simple, fast method for detection of aflatoxins in animal feeds. Simultaneous quantitation of four aflatoxins (AFB(1), AFB(2), AFG(1) and AFG(2)) in animal feeds was achieved in a single liquid chromatography/tandem mass spectrometry (LC/MS/MS) run. The solid-phase extraction cleanup step is eliminated with the stable isotope dilution method. Matrix effects were observed and overcome by isotope dilution. The method was tested in a variety of animal feed matrices and proved to be accurate and reliable. Method ruggedness tests resulted in recoveries of 78% to 122% with an intra-day assay precision of 2% to 15% and an inter-day assay precision of 3% to 17%. These results indicate that this method is suitable for quantitation of aflatoxins in animal feeds.

Prediction of the tissue-specificity of selective estrogen receptor modulators by using a single biochemical method.

Here, we demonstrate that a single biochemical assay is able to predict the tissue-selective pharmacology of an array of selective estrogen receptor modulators (SERMs). We describe an approach to classify estrogen receptor (ER) modulators based on dynamics of the receptor-ligand complex as probed with hydrogen/deuterium exchange (HDX) mass spectrometry. Differential HDX mapping coupled with cluster and discriminate analysis effectively predicted tissue-selective function in most, but not all, cases tested. We demonstrate that analysis of dynamics of the receptor-ligand complex facilitates binning of ER modulators into distinct groups based on structural dynamics. Importantly, we were able to differentiate small structural changes within ER ligands of the same chemotype. In addition, HDX revealed differentially stabilized regions within the ligand-binding pocket that may contribute to the different pharmacology phenotypes of the compounds independent of helix 12 positioning. In summary, HDX provides a sensitive and rapid approach to classify modulators of the estrogen receptor that correlates with their pharmacological profile.

Phototunable Lignin Plastics to Enable Recyclability.

The accumulation of non-degradable petrochemical plastics imposes a significant threat to the environment and ecosystems. We addressed this challenge by designing a new type of phototunable plastics based on the unique lignin chemistry to enable readily end-life recycling. The advanced material design leveraged the efficient photocatalytic lignin depolymerization by ZnO nanoparticles to build lignin-polymethyl methacrylate (PMMA)-ZnO blends. We first demonstrated the highly effective phototunable lignin depolymerization in the complex polymer blend matrix and explored the molecular mechanisms. The technical barriers of mechanical property and recycling processing were then addressed by a new blend design with lignin core grafted with PMMA polymer. The new process has resulted in a new type of PMMA-g-lignin blend, which significantly improved the mechanical properties, making it comparable to PMMA alone. More importantly, the mechanical properties of the UV-treated blend decreased drastically in the new design, whereas the properties did not reduce in the non-grafted blends upon UV exposure. The results highlighted that the new blend design based on graftization maximized the impact of lignin depolymerization on blend structure and recyclability. Based on the results, we developed a process integrating UV and alkaline treatments to recycle PMMA for plastics and fractionated lignin for bioconversion or other applications in the new phototunable plastics.

Enzyme structure dynamics of xylanase I from Trichoderma longibrachiatum.

BACKGROUND: Enzyme dynamics has recently been shown to be crucial for structure-function relationship. Among various structure dynamics analysis platforms, HDX (hydrogen deuterium exchange) mass spectrometry stands out as an efficient and high-throughput way to analyze protein dynamics upon ligand binding. Despite the potential, limited research has employed the HDX mass spec platform to probe regional structure dynamics of enzymes. In particular, the technique has never been used for analyzing cell wall degrading enzymes. We hereby used xylanase as a model to explore the potential of HDX mass spectrometry for studying cell wall degrading enzymes. RESULTS: HDX mass spectrometry revealed significant intrinsic dynamics for the xylanase enzyme. Different regions of the enzymes are differentially stabilized in the apo enzyme. The comparison of substrate-binding enzymes revealed that xylohexaose can significantly stabilize the enzyme. Several regions including those near the reaction centres were significantly stabilized during the xylohexaose binding. As compared to xylohexaose, xylan induced relatively less protection in the enzyme, which may be due to the insolubility of the substrate. The structure relevance of the enzyme dynamics was discussed with reference to the three dimensional structure of the enzyme. HDX mass spectrometry revealed strong dynamics-function relevance and such relevance can be explored for the future enzyme improvement. CONCLUSION: Ligand-binding can lead to the significant stabilization at both regional and global level for enzymes like xylanase. HDX mass spectrometry is a powerful high-throughput platform to identify the key regions protected during the ligand binding and to explore the molecular mechanisms of the enzyme function. The HDX mass spectrometry analysis of cell wall degrading enzymes has provided a novel platform to guide the rational design of enzymes.