DEAttentionDTA: protein-ligand binding affinity prediction based on dynamic embedding and self-attention.

MOTIVATION: Predicting protein-ligand binding affinity is crucial in new drug discovery and development. However, most existing models rely on acquiring 3D structures of elusive proteins. Combining amino acid sequences with ligand sequences and better highlighting active sites are also significant challenges. RESULTS: We propose an innovative neural network model called DEAttentionDTA, based on dynamic word embeddings and a self-attention mechanism, for predicting protein-ligand binding affinity. DEAttentionDTA takes the 1D sequence information of proteins as input, including the global sequence features of amino acids, local features of the active pocket site, and linear representation information of the ligand molecule in the SMILE format. These three linear sequences are fed into a dynamic word-embedding layer based on a 1D convolutional neural network for embedding encoding and are correlated through a self-attention mechanism. The output affinity prediction values are generated using a linear layer. We compared DEAttentionDTA with various mainstream tools and achieved significantly superior results on the same dataset. We then assessed the performance of this model in the p38 protein family. AVAILABILITY AND IMPLEMENTATION: The resource codes are available at https://github.com/whatamazing1/DEAttentionDTA.

A hydrogel-modified electrochemical biosensor for the rapid detection of ammonia­nitrogen-resistant bacteria.

Ammonia­nitrogen wastewater is one of the main pollutants in the current environment. Rapid detection of microorganisms resistant to ammonia­nitrogen provides a basis for bioremediation of ammonia­nitrogen contaminated sites. This study uses electrochemical analysis for efficiently detecting of ammonia-resistant bacteria, utilizing a commercially available, low-cost screen-printed electrode (SPE) modified with agarose-based hydrogel (gel) or graphene oxide (GO). At the same time, the study employed electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV) to monitor bacterial growth, revealing Escherichia coli (E. coli) inhibition upon ammonia­nitrogen addition, while Raoultella terrigena (RN1) and Pseudomonas (RN2) exhibit tolerance. The method provides sensitivity results in <45 min, which is significantly faster than traditional methods. RN1 and RN2 exhibit promising ammonia­nitrogen removal rates, reaching up to 81 % and 92 %, respectively. This study aimed to develop an effective electrochemical method for rapidly detecting the sensitivity of microorganisms to ammonia­nitrogen. The method offers advantages such as high speed, efficiency, and cost-effectiveness, potentially providing valuable microbial resources for mitigating ammonia nitrogen wastewater pollution.

A miniprotein receptor electrochemical biosensor chip based on quantum dots.

Recently protein binders have emerged as a promising substitute for antibodies due to their high specificity and low cost. Herein, we demonstrate an electrochemical biosensor chip through the electronic labelling strategy using lead sulfide (PbS) colloidal quantum dots (CQDs) and the unnatural SARS-CoV-2 spike miniprotein receptor LCB. The unnatural receptor can be utilized as a molecular probe for the construction of CQD-based electrochemical biosensor chips, through which the specific binding of LCB and the spike protein is transduced to sensor electrical signals. The biosensor exhibits a good linear response in the concentration range of 10 pg mL-1 to 1 µg mL-1 (13.94 fM to 1.394 nM) with the limit of detection (LOD) being 3.31 pg mL-1 (4.607 fM for the three-electrode system) and 9.58 fg mL-1 (0.013 fM for the HEMT device). Due to the high sensitivity of the electrochemical biosensor, it was also used to study the binding kinetics between the unnatural receptor LCB and spike protein, which has achieved comparable results as those obtained with commercial equipment. To the best of our knowledge, this is the first example of using a computationally designed miniprotein receptor based on electrochemical methods, and it is the first kinetic assay performed with an electrochemical assay alone. The miniprotein receptor electrochemical biosensor based on QDs is desirable for fabricating high-throughput, large-area, wafer-scale biochips.

A review on machine learning-powered fluorescent and colorimetric sensor arrays for bacteria identification.

Biosensors have been widely used for bacteria determination with great success. However, the "lock-and-key" methodology used by biosensors to identify bacteria has a significant limitation: it can only detect one species of bacteria. In recent years, optical (fluorescent and colorimetric) sensor arrays are gradually gaining attention from researchers as a new type of biosensor. They can acquire multiple features of a target simultaneously, form a feature pattern, and determine the bacteria species with the help of pattern recognition/machine learning algorithms. Previous reviews in this area have focused on the interaction between the sensor array and bacteria or the materials used to make the sensors. This review, on the other hand, will provide researchers with a better understanding of the field by discussing fluorescent and colorimetric sensor arrays based on the mechanism of optical signal generation. These sensor arrays will be compared based on the identified species. Finally, we will discuss the limitations of these sensor arrays and explore possible solutions.

Recent advances in the peptide-based biosensor designs.

Biosensors have rapidly emerged as a high-sensitivity and convenient detection method. Among various types of biosensors, optical and electrochemical are the most commonly used. Conventionally, antibodies have been employed to ensure specific interaction between the transmission material and analytes. However, there has been increasing recognition of peptides as a promising recognition element for biosensor development in recent years. The use of peptides as recognition elements provides high level of specificity, sensitivity, and stability for the detection process. The combination of peptide designs and optical or electrochemical detection methods has significantly improved biosensor efficacy. These advancements present opportunities for developing biosensors with diverse functions that can be used to lay a strong scientific foundation for the development of personalized medicine and various other fields. This paper reviews the recent advancements in the development and application of peptide-based optical and electrochemical biosensors, as well as their prospects as a sensor type.

Development of a novel ultrasound- and biocrosslinking-enhanced immobilization strategy with application to food enzymes.

The increasing demand for greener food production makes biocatalysts more desirable than traditional production approaches. One limiting factor for biocatalyst efficiency is the immobilization strategy. In this work, a novel immobilization method was developed with the tyrosine-tag crosslinking mechanism. The immobilization efficiency was further enhanced with ultrasound treatment. Such a strategy was proven to be efficient with food enzyme lipase, d-amino acid oxidase and glucose dehydrogenase when they were immobilized on macroporous resins, amino resins, epoxy resins, and multiwalled carbon nanotubes. For lipase, glucose dehydrogenase and d-amino acid oxidase, the immobilization yield on macroporous resins increased by 20.4%, 21.1% and 24.1%, respectively. In addition, the immobilized enzymes had enhanced reusability, with a high degree of activity (more than 85%) detected after six cycles. Furthermore, the enzyme electrochemical sensors constructed by enzyme crosslinking have higher sensitivity, with peak currents 4-8 times those of sensors with uncrosslinked enzymes. The enzyme immobilization strategy developed in this study paves the way for better application of biocatalysts in the food industry.

Rapid saline-alkali sensitivity testing using hydrogel/gold nanoparticles-modified screen-printed electrodes.

Rapid screening of microorganisms with good saline-alkali tolerance is of great significance for the improvement of saline-alkali land. In this study, a novel electrochemical method was developed for the rapid screening of saline-alkali-tolerant bacteria using a hydrogel/gold nanoparticles-modified screen-printed electrode. Monitoring bacterial growth using electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV) yielded a new method to measure saline-alkali sensitivity. The strains were deposited on agarose hydrogel-AuNPs composite-modified electrodes with saline-alkali treatment control at a concentration of 50 mM. The electrochemical-derived growth curve of each bacterial strain was established to monitor the effect of saline-alkaline conditions on bacterial growth. The results showed that E. coli could grow on the hydrogel-AuNPs composite-modified electrodes without saline and alkali, while the growth of E. coli was inhibited after adding saline and alkali to the modified electrodes. In contrast, Paenibacillus lautus (HC_A) and Lysinibacillus fusiformis (HC_B) were able to grow on electrodes containing saline-alkali hydrogel-AuNPs composite modification. This fast growth curves of the strains derived from electrochemical analysis indicate that the possible time for salinity sensitivity results is <45 min. Compared to the traditional bacterial culture method lasting at least 1-2 days, this method has the clear advantages of rapidity, high efficiency, and low cost.

Electrochemical analysis for the rapid screening of copper-tolerant bacteria.

Environmental pollution caused by heavy metals such as copper is quite severe nowadays. Therefore, screening for strains with solid tolerance to copper is of great importance for the microbial treatment of heavy metal pollution in the environment. Traditional methods of testing copper tolerance rely on bacterial growth on agar plates or liquid cultures. These time-consuming and cumbersome assays use strain growth as an indicator of cellular respiration. In this study, we explored mediated extracellular electron transfer as a rapid and straightforward method to sort copper-tolerant or copper-sensitive bacteria. We tested strains Paenibacillus lautus A (HC_A), Lysinibacillus fusiformis B (HC_B) and Escherichia coli BL21, as well as two microbial consortiums, Natural Consortium and Enriched Consortium. Bacterial cultures were added to a designed three-electrode electrochemical cell with a glassy carbon working electrode and a growth medium supplemented with soluble electron transfer mediators, phenazine methyl sulfate (PMS), or resazurin. The oxidoreduction of the mediators was measured as an electric current and used to monitor cell respiration. Compared with the control without copper treatment, copper-sensitive strains show a reduced current upon copper treatment. Using this new method, we could classify strains as copper tolerant or sensitive in <90 min.

A Single-Component Blue Light-Induced System Based on EL222 in Yarrowia lipolytica.

Optogenetics has the advantages of a fast response time, reversibility, and high spatial and temporal resolution, which make it desirable in the metabolic engineering of chassis cells. In this study, a light-induced expression system of Yarrowia lipolytica was constructed, which successfully achieved the synthesis and functional verification of Bleomycin resistance protein (BleoR). The core of the blue light-induced system, the light-responsive element (TF), is constructed based on the blue photosensitive protein EL222 and the transcription activator VP16. The results show that the light-induced sensor based on TF, upstream activation sequence (C120)5, and minimal promoter CYC102 can respond to blue light and initiate the expression of GFPMut3 report gene. With four copies of the responsive promoter and reporter gene assembled, they can produce a 128.5-fold higher fluorescent signal than that under dark conditions after 8 h of induction. The effects of light dose and periodicity on this system were investigated, which proved that the system has good spatial and temporal controllability. On this basis, the light-controlled system was used for the synthesis of BleoR to realize the expression and verification of functional protein. These results demonstrated that this system has the potential for the transcriptional regulation of target genes, construction of large-scale synthetic networks, and overproduction of the desired product.

Microbial Consortia Are Needed to Degrade Soil Pollutants.

Soil pollution is one of the most serious environmental problems globally due to the weak self-purification ability, long degradation time, and high cost of cleaning soil pollution. The pollutants in the soil can be transported into the human body through water or dust, causing adverse effects on human health. The latest research has shown that the clean-up of soil pollutants through microbial consortium is a very promising method. This review provides an in-depth discussion on the efficient removal, bio-adsorption, or carbonated precipitation of organic and inorganic pollutants by the microbial consortium, including PAHs, BPS, BPF, crude oil, pyrene, DBP, DOP, TPHP, PHs, butane, DON, TC, Mn, and Cd. In view of the good degradation ability of the consortium compared to single strains, six different synergistic mechanisms and corresponding microorganisms are summarized. The microbial consortium obtains such activities through enhancing synergistic degradation, reducing the accumulation of intermediate products, generating the crude enzyme, and self-regulating, etc. Furthermore, the degradation efficiency of pollutants can be greatly improved by adding chemical materials such as the surfactants Tween 20, Tween 80, and SDS. This review provides insightful information regarding the application of microbial consortia for soil pollutant removal.

Biological Nitrogen Removal Database: A Manually Curated Data Resource.

Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and function of BNR microbial communities and optimizing BNR treatment systems to enhance nitrogen removal efficiency. The literature on BNR microbial communities and experimental datasets is not unified across various repositories, while a uniform resource for the collection, annotation, and structuring of these BNR datasets is still unavailable. Herein, we present the Biological Nitrogen Removal Database (BNRdb), an integrated resource containing various manually curated BNR-related data. At present, BNRdb contains 23,308 microbial strains, 46 gene families, 24 enzymes, 18 reactions, 301 BNR treatment datasets, 860 BNR-associated next-generation sequencing datasets, and 6 common BNR bioreactor systems. BNRdb provides a user-friendly interface enabling interactive data browsing. To our knowledge, BNRdb is the first BNR data resource that systematically integrates BNR data from archaeal, bacterial, and fungal communities. We believe that BNRdb will contribute to a better understanding of BNR process and nitrogen bioremediation research.

Analysis of antibiotic resistance genes reveals their important roles in influencing the community structure of ocean microbiome.

Antibiotic resistance gene (ARG) content is a well-established driver of microbial abundance and diversity in an environment. By reanalyzing 132 metagenomic datasets from the Tara Oceans project, we aim to unveil the associations between environmental factors, the ocean microbial community structure and ARG contents. We first investigated the structural patterns of microbial communities including both prokaryotes such as bacteria and eukaryotes such as protists. Additionally, several ARG-dominant horizontal gene transfer events between Protist and Prokaryote have been identified, indicating the potential roles of ARG in shaping the ocean microbial communities. For a deeper insight into the role of ARGs in ocean microbial communities on a global scale, we identified 1926 unique types of ARGs and discovered that the ARGs are more abundant and diverse in the mesopelagic zone than other water layers, potentially caused by limited resources. Finally, we found that ARG-enriched genera were often more abundant compared to their ARG-less neighbors in the same environment (e.g. coastal oceans). A deeper understanding of the ARG-microbiome relationships could help in the conservation of the oceanic ecosystem.

Design and Characterization of an Optogenetic System in Pichia pastoris.

Pichia pastoris (P. pastoris) is the workhorse in the commercial production of many valuable proteins. Traditionally, the regulation of gene expression in P. pastoris is achieved through induction by methanol which is toxic and flammable. The emerging optogenetic technology provides an alternative and cleaner gene regulation method. Based on the photosensitive protein EL222, we designed a novel "one-component" optogenetic system. The highest induction ratio was 79.7-fold under blue light compared to the group under darkness. After switching cells from dark to blue illumination, the system induced expression in just 1 h. Only 2 h after the system was switched back to the darkness from blue illumination, the target gene expression was inactivated 5-fold. The induction intensity of the optogenetic system is positively correlated with the dose and periodicity of blue illumination, and it has good spatial control. These results provide the first credible case of optogenetically induced protein expression in P. pastoris.

Construction of an enzyme-based all-fiber SPR biosensor for detection of enantiomers.

Chiral analysis of amino acids (AAs) is of great importance in medical science due to the distinctive effect of AA isomers on human health. Although various chiral recognition techniques have been developed, the quantitative chiral recognition of low-level AA isomers remains challenging. Here, we combined the fiber optic SPR with an enzyme-substrate recognition mechanism to construct a direct-assay-type chiral AA biosensor. As a proof-of-concept attempt, a recently discovered Rasamsonia emersonii D-amino acid oxidase (ReDAAO) with a wide substrate spectrum and high stability was immobilized on the graphene oxide and gold nanorods composites (GO-AuNRs), using both EDC/NHS coupling and the gold-binding peptide (GBP) method. Such a biosensor can distinguish two AA isomers at the same concentration. It achieved specific detection of D-amino acids (D-AAs) with a linear range from 5x10-4 mM to 30 mM. Furthermore, it showed good resistance to enantiomeric interference. When the percentage of D-AA increases in the isomer mixture, a good linear relationship between the D/(D + L)-AA ratio and SPR spectral shift was obtained. This unique combination of the enzyme, nanocomposite, and SPR taps into the rich reservoir of proteins for chiral receptors. It lays the foundation for protein-based chiral recognition of other clinically important small molecules in future biosensor designs.

Employing Engineered Enolase Promoter for Efficient Expression of Thermomyces lanuginosus Lipase in Yarrowia lipolytica via a Self-Excisable Vector.

Yarrowia lipolytica is progressively being employed as a workhouse for recombinant protein expression. Here, we expanded the molecular toolbox by engineering the enolase promoter (pENO) and developed a new self-excisable vector, and based on this, a combined strategy was employed to enhance the expression of Thermomyces lanuginosus lipase (TLL) in Y. lipolytica. The strength of 11 truncated enolase promoters of different length was first identified using eGFP as a reporter. Seven of the truncated promoters were selected to examine their ability for driving TLL expression. Then, a series of enolase promoters with higher activities were developed by upstream fusing of different copies of UAS1B, and the recombinant strain Po1f/hp16e100-tll harboring the optimal promoter hp16e100 obtained a TLL activity of 447 U/mL. Additionally, a new self-excisable vector was developed based on a Cre/loxP recombination system, which achieved efficient markerless integration in Y. lipolytica. Subsequently, strains harboring one to four copies of the tll gene were constructed using this tool, with the three-copy strain Po1f/3tll showing the highest activity of 579 U/mL. The activity of Po1f/3tll was then increased to 720 U/mL by optimizing the shaking flask fermentation parameters. Moreover, the folding-related proteins Hac1, Pdi, and Kar2 were employed to further enhance TLL expression, and the TLL activity of the optimal recombinant strain Po1f/3tll-hac1-pdi-kar2 reached 1197 U/mL. By using this combined strategy, TLL activity was enhanced by approximately 39.9-fold compared to the initial strain. Thus, the new vector and the combined strategy could be a useful tool to engineer Y. lipolytica for high-level expression of heterologous protein.

mibPOPdb: An online database for microbial biodegradation of persistent organic pollutants.

Microbial biodegradation of persistent organic pollutants (POPs) is an attractive, ecofriendly, and cost-efficient clean-up technique for reclaiming POP-contaminated environments. In the last few decades, the number of publications documenting POP-degrading microbes, enzymes, and experimental data sets has continuously increased, necessitating the development of a dedicated web resource that catalogs consolidated information on POP-degrading microbes and tools to facilitate integrative analysis of POP degradation data sets. To address this knowledge gap, we developed the Microbial Biodegradation of Persistent Organic Pollutants Database (mibPOPdb) by accumulating microbial POP degradation information from the public domain and manually curating published scientific literature. Currently, in mibPOPdb, there are 9215 microbial strain entries, including 184 gene (sub)families, 100 enzymes, 48 biodegradation pathways, and 593 intermediate compounds identified in POP-biodegradation processes, and information on 32 toxic compounds listed under the Stockholm Convention environmental treaty. Besides the standard database functionalities, which include data searching, browsing, and retrieval of database entries, we provide a suite of bioinformatics services to facilitate comparative analysis of users' own data sets against mibPOPdb entries. Additionally, we built a Graph Neural Network-based prediction model for the biodegradability classification of chemicals. The predictive model exhibited a good biodegradability classification performance and high prediction accuracy. mibPOPdb is a free data-sharing platform designated to promote research in microbial-based biodegradation of POPs and fills a long-standing gap in environmental protection research. Database URL: http://mibpop.genome-mining.cn/.

A Novel Cre/lox-Based Genetic Tool for Repeated, Targeted and Markerless Gene Integration in Yarrowia lipolytica.

The unconventional yeast Yarrowia lipolytica is extensively applied in bioproduction fields owing to its excellent metabolite and protein production ability. Nonetheless, utilization of this promising host is still restricted by the limited availability of precise and effective gene integration tools. In this study, a novel and efficient genetic tool was developed for targeted, repeated, and markerless gene integration based on Cre/lox site-specific recombination system. The developed tool required only a single selection marker and could completely excise the unnecessary sequences. A total of three plasmids were created and seven rounds of marker-free gene integration were examined in Y. lipolytica. All the integration efficiencies remained above 90%, and analysis of the protein production and growth characteristics of the engineered strains confirmed that genome modification via the novel genetic tool was feasible. Further work also confirmed that the genetic tool was effective for the integration of other genes, loci, and strains. Thus, this study significantly promotes the application of the Cre/lox system and presents a powerful tool for genome engineering in Y. lipolytica.

Site-Specific Biofunctionalization of Cellulose and Poly(dimethylsiloxane): A Chemoenzymatic Approach for Surface Engineering.

Site-specific, covalent immobilization of protein is of great importance in the design of bioanalytical devices. User-defined covalent coupling of protein onto the surface has been primarily limited to a noncanonical amino acid or cysteine residues. It is desirable to develop a new approach for site-specific biofunctionalization. Herein, we demonstrate a robust and modular chemoenzymatic approach for site-specific, covalent grafting of proteins onto a surface. The synthetic strategy relies on the combination of surface amine functionalization, followed by sortase-mediated coupling. The developed method was validated by site-specific immobilization of two model proteins (glutathione S-transferase and green fluorescent protein) on cellulose and polydimethylsiloxane surfaces via a short recognition motif (LPETG). The covalent coupling of immobilized proteins at the interface was characterized by Fourier Transform Infrared Spectroscopy in attenuated total reflectance mode, X-ray photoelectron spectroscopy, atomic force microscope, and fluorescent microscopy. This enzymatic surface functionalization approach could permit an oriented, homogeneous, and site-specific covalent tethering of LPETG-tag proteins to other materials under mild conditions.

A De Novo Designed Esterase with p-Nitrophenyl Acetate Hydrolysis Activity.

Esterases are a large family of enzymes with wide applications in the industry. However, all esterases originated from natural sources, limiting their use in harsh environments or newly- emerged reactions. In this study, we designed a new esterase to develop a new protocol to satisfy the needs for better biocatalysts. The ideal spatial conformation of the serine catalytic triad and the oxygen anion hole at the substrate-binding site was constructed by quantum mechanical calculation. The catalytic triad and oxygen anion holes were then embedded in the protein scaffold using the new enzyme protocol in Rosetta 3. The design results were subsequently evaluated, and optimized designs were used for expression and purification. The designed esterase had significant lytic activities towards p-nitrophenyl acetate, which was confirmed by point mutations. Thus, this study developed a new protocol to obtain novel enzymes that may be useful in unforgiving environments or novel reactions.

Construction of a hydrocarbon-degrading consortium and characterization of two new lipopeptides biosurfactants.

Apparent solubility and bioavailability of hydrophobic compounds are the major problems in the bioremediation process, which could be overcome by the bacteria capable of biosurfactant production and concurrent hydrocarbon degradation. In this work, we constructed an artificial bacterial consortium containing Lysinibacillus, Paenibacillus, Gordonia and Cupriavidus spp. from glyceryl tributyrate enriched bacteria collected from the non-contaminated site. The consortium was capable of using common raw materials (olive oil, paraffin oil, and glycerol) and polyaromatic hydrocarbons pollutants (naphthalene and anthracene) as the sole carbon source with simultaneous biosurfactant production. Two new lipopeptide isoforms, containing heptapeptide and lipid moieties, were structurally elucidated by LC-MS/MS, FTIR, NMR and molecular networking analysis. Our findings indicate that hydrocarbons degradation and biosurfactant production is an intrinsic property of non-contaminated soil community. Interestingly, we observed the hyper chemotactic activity of Lysinibacillus strains towards glyceryl tributyrate, which has not been reported before. The study may deepen our understanding of microbial strains and consortium with the potential to be used for bioremediation of hydrocarbons contaminated environments.