Library Construction Research Articles

Nanopore sequencing improves construction of customized CRISPR-based gene activation libraries.

Clustered regularly interspaced short palindromic repeats (CRISPR)-based screening has emerged as a powerful tool for identifying new gene targets for desired cellular phenotypes. The construction of guide RNA (gRNA) pools largely determines library quality and is usually performed using Golden Gate assembly or Gibson assembly. To date, library construction methods have not been systematically compared, and the quality check of each batch has been slow. In this study, an in-house nanopore sequencing workflow was established for assessing the current methods of gRNA pool construction. The bias of pool construction was reduced by employing the polymerase-mediated non-amplifying method. Then, a small gRNA pool was utilized to characterize stronger activation domains, specifically MED2 (a subunit of mediator complex) and HAP4 (a heme activator protein), as well as to identify better gRNA choices for dCas12a-based gene activation in Saccharomyces cerevisiae. Furthermore, based on the better CRISPRa tool identified in this study, a custom gRNA pool, which consisted of 99 gRNAs targeting central metabolic pathways, was designed and employed to screen for gene targets that could improve ethanol utilization in S. cerevisiae. The nanopore sequencing-based workflow demonstrated here should provide a cost-effective approach for assessing the quality of customized gRNA library, leading to faster and more efficient genetic and metabolic engineering in S. cerevisiae.

Establishment of an indirect competitive immunoassay for the detection of dicamba based on a highly specific nanobody

Dicamba, a traditional highly effective and low toxicity herbicide, has gained new life with the development of dicamba-tolerant transgenic crops in recent years. However, dicamba is highly volatile and therefore easy to cause drift damage to sensitive crops. The development of efficient and sensitive detection methods is essential for monitoring of trace dicamba in the environment. Nanobody-based immunoassay plays an important role in on-site detection of pesticides. However, now rapid and sensitive immunoassay methods based on nanobody for dicamba detection were lacking. In this study, the nanobodies specifically recognizing dicamba were successfully obtained by immunising camels and phage display library construction, and then an indirect competitive immunoassay based on Nb-242 was constructed with IC50 of 0.93 μg/mL and a linear range of 0.11–8.01 μg/mL. Nb-242 had good specificity with no cross-reactivities against the dicamba analogs other than 2,3,6-trichlorobenzoic acid and the developed immnoassay had a good correlation with the standard HPLC in the spike-recovery studies. Finally, the key amino acid Ala 123, Tyr 55, Tyr 59 and Arg 72 of Nb-242 that specifically recognizing and binding with dicamba were identified by homologous modeling and molecular docking, laying an important foundation for further structural modification of Nb-242. This study has important guiding significance for constructing immunoassay method of dicamba based on nanobody and provides a sensitive, specific, and reliable detection method that is suitable for the detection of dicamba in the environment.

Nanobodies: a promising approach to treatment of viral diseases.

Since their discovery in the 1990s, heavy chain antibodies have garnered significant interest in the scientific community. These antibodies, found in camelids such as llamas and alpacas, exhibit distinct characteristics from conventional antibodies due to the absence of a light chain in their structure. Furthermore, they possess a single antigen-binding domain known as VHH or Nanobody (Nb). With a small size of approximately 15 kDa, these Nbs demonstrate improved characteristics compared to conventional antibodies, including greater physicochemical stability and enhanced biodistribution, enabling them to bind inaccessible epitopes more effectively. As a result, Nbs have found numerous applications in various medical and veterinary fields, particularly in diagnostics and therapeutics. Advances in biotechnology have made the production of recombinant antibodies feasible and compatible with large-scale manufacturing. Through the construction of immune phage libraries that display VHHs and subsequent selection through biopanning, it has become possible to isolate specific Nbs targeting pharmaceutical targets of interest, such as viruses. This review describes the processes involved in nanobody production, from hyperimmunization to purification, with the aim of their application in the pharmaceutical industry.

Targeted genomic sequencing of avian influenza viruses in wetland sediment from wild bird habitats.

Diverse influenza A viruses (IAVs) circulate in wild birds, including highly pathogenic strains that infect poultry and humans. Consequently, surveillance of IAVs in wild birds is a cornerstone of agricultural biosecurity and pandemic preparedness. Surveillance is traditionally done by testing wild birds directly, but obtaining these specimens is labor intensive, detection rates can be low, and sampling is often biased toward certain avian species. As a result, local incursions of dangerous IAVs are rarely detected before outbreaks begin. Testing environmental specimens from wild bird habitats has been proposed as an alternative surveillance strategy. These specimens are thought to contain diverse IAVs deposited by a broad range of avian hosts, including species that are not typically sampled by surveillance programs. To enable this surveillance strategy, we developed a targeted genomic sequencing method for characterizing IAVs in these challenging environmental specimens. It combines custom hybridization probes, unique molecular index-based library construction, and purpose-built bioinformatic tools, allowing IAV genomic material to be enriched and analyzed with single-fragment resolution. We demonstrated our method on 90 sediment specimens from wetlands around Vancouver, Canada. We recovered 2,312 IAV genome fragments originating from all eight IAV genome segments. Eleven hemagglutinin subtypes and nine neuraminidase subtypes were detected, including H5, the current global surveillance priority. Our results demonstrate that targeted genomic sequencing of environmental specimens from wild bird habitats could become a valuable complement to avian influenza surveillance programs.IMPORTANCEIn this study, we developed genome sequencing tools for characterizing avian influenza viruses in sediment from wild bird habitats. These tools enable an environment-based approach to avian influenza surveillance. This could improve early detection of dangerous strains in local wild birds, allowing poultry producers to better protect their flocks and prevent human exposures to potential pandemic threats. Furthermore, we purposefully developed these methods to contend with viral genomic material that is diluted, fragmented, incomplete, and derived from multiple strains and hosts. These challenges are common to many environmental specimens, making these methods broadly applicable for genomic pathogen surveillance in diverse contexts.

GLORI for absolute quantification of transcriptome-wide m6A at single-base resolution.

N6-methyladenosine (m6A) is the most abundant posttranscriptional chemical modification in mRNA, involved in regulating various physiological and pathological processes throughout mRNA metabolism. Recently, we developed GLORI, a sequencing method that enables the production of a globally absolute-quantitative m6A map at single-base resolution. Our technique utilizes the glyoxal- and nitrite-based chemical reaction, which selectively deaminates unmethylated adenosines while leaving m6A intact. The RNA library can then be prepared using a modified library construction protocol from enhanced UV crosslinking and immunoprecipitation (eCLIP) or commercial kits. Here we provide a detailed protocol for proper RNA sample handling and provide further guidelines for the use of a tailored bioinformatics pipeline (GLORI-tools) for subsequent data analysis. Compared with current methods, this new method is both exceptionally sensitive and robust, capable of identifying ~80,000 m6A sites with 50 Gb sequencing data in mammalian cells. It also provides a quantitative readout for m6A sites at single-base resolution. We hope the technique will provide a precise and unbiased tool for investigating m6A biology across various fields. Basic expertise in molecular biology and knowledge of bioinformatics are required for the protocol. The entire procedure can be completed within a week, with the library construction process taking ~4 d.

Research on Coal and Rock Recognition in Coal Mining Based on Artificial Neural Network Models

In the process of coal mining, one of the main reasons for the high labor intensity of workers and the frequent occurrence of casualties is the low level of intelligence of coal mining equipment. As the core equipment in the process of coal mining, the intelligence level of shearers directly affects the safety production and mining efficiency of coal mines. Coal and rock recognition technology is the core technology used to realize the intelligentization of shearers, which is an urgent technical problem to be solved in the field of coal mining. In this paper, coal seam images, rock stratum images, and coal–rock mixed-layer images of a coal mining area are taken as the research object, and key technologies such as the construction of a sample image library, classification and recognition, and semantic segmentation are studied by using the relevant theoretical knowledge of artificial neural network models. Firstly, the BP neural network is used to classify and identify coal seam images, rock stratum images, and coal–rock mixed-layer images, so as to distinguish which of the current mining targets of a shearer is the coal seam, rock stratum, or coal–rock mixed layer. Because different mining objectives will lead to different working modes of a shearer, it is necessary to maintain normal power to cut coal when encountering a coal seam, to stop working when encountering rock stratum, and to cut coal along the boundary between a coal seam and rock stratum when encountering a coal–rock mixed stratum. Secondly, the DeepLabv3+ model is used to perform semantic segmentation experiments on the coal–rock mixed-layer images. The purpose is to find out the distribution of coal and rocks in the coal–rock mixed layer in the coal mining area, so as to provide technical support for the automatic adjustment height of the shearer. Finally, the research in this paper achieved a 97.16% recognition rate in the classification and recognition experiment of the coal seam images, rock stratum images, and coal–rock mixed-layer images and a 91.2% accuracy in the semantic segmentation experiment of the coal–rock mixed-layer images. The research results of the two experiments provide key technical support for improving the intelligence level of shearers.

Construction and characterization of a promoter library with varying strengths to enhance acetoin production from xylose in Serratia marcescens.

Serratia marcescens is utilized as a significant enterobacteria in the production of various high-value secondary metabolites. Acetoin serves as a crucial foundational compound of development and finds application in a broad range of fields. Furthermore, S. marcescens HBQA-7 is capable of utilizing xylose as its exclusive carbon source for acetoin production. The objective of this study was to utilize a constitutive promoter screening strategy to enhance both xylose utilization and acetoin production in S. marcescens HBQA-7. By utilizing RNA-seq, we identified the endogenous constitutive promoter P6 that is the most robust, which facilitated the overexpression of the sugar transporter protein GlfL445I , α-acetyl lactate synthase, and α-acetyl lactate decarboxylase, respectively. The resultant recombinant strains exhibited enhanced xylose utilization rates and acetoin yields. Subsequently, a recombinant plasmid, denoted as pBBR1MCS-P6-glfL445I alsSalsD, was constructed, simultaneously expressing the aforementioned three genes. The resulting recombinant strain, designated as S3, demonstrated a 1.89-fold boost in xylose consumption rate compared with the original strain during shake flask fermentation. resulting in the accumulation of 7.14g/L acetoin in the final fermentation medium. Subsequently, in a 5 L fermenter setup, the acetoin yield reached 48.75g/L, corresponding to a xylose-to-acetoin conversion yield of 0.375g/g.

Construction of a smart face recognition model for university libraries based on FaceNet-MMAR algorithm.

The continuous development of science and technology has led to the gradual digitization and intelligence of campus construction. To apply facial recognition technology to construct smart libraries in higher education, this study optimizes traditional facial recognition algorithm models. Firstly, a smart management system for university libraries is designed with facial recognition as the core, and secondly, the traditional FaceNet network is optimized. Combined with MobileNet, Attention mechanism, Receptive field module and Mish activation function, the improved multitask face recognition convolutional neural network is built and used in the construction of university smart library. The performance verification of the constructed model shows that the feature matching error value of the model in a stable state is only 0.04. The recognition accuracy in the dataset is as high as 99.05%, with a recognition error as low as 0.51%. The facial recognition model used in university smart libraries can achieve 97.6% teacher satisfaction and 96.8% student satisfaction. In summary, the facial recognition model constructed by this paper has good recognition performance and can provide effective technical support for the construction of smart libraries.

Candidate biomarkers of EV-microRNA in detecting REM sleep behavior disorder and Parkinson’s disease

Parkinson’s disease (PD) lacks reliable, non-invasive biomarker tests for early intervention and management. Thus, a minimally invasive test for the early detection and monitoring of PD and REM sleep behavior disorder (iRBD) is a highly unmet need for developing drugs and planning patient care. Extracellular vehicles (EVs) are found in a wide variety of biofluids, including plasma. EV-mediated functional transfer of microRNAs (miRNAs) may be viable candidates as biomarkers for PD and iRBD. Next-generation sequencing (NGS) of EV-derived small RNAs was performed in 60 normal controls, 56 iRBD patients and 53 PD patients to profile small non-coding RNAs (sncRNAs). Moreover, prospective follow-up was performed for these 56 iRBD patients for an average of 3.3 years. Full-scale miRNA profiles of plasma EVs were evaluated by machine-learning methods. After optimizing the library construction method for low RNA inputs (named EVsmall-seq), we built a machine learning algorithm that identified diagnostic miRNA signatures for distinguishing iRBD patients (AUC 0.969) and PD patients (AUC 0.916) from healthy individuals; and PD patients (AUC 0.929) from iRBD patients. We illustrated all the possible expression patterns across healthy-iRBD-PD hierarchy. We also showed 20 examples of miRNAs with consistently increasing or decreasing expression levels from controls to iRBD to PD. In addition, four miRNAs were found to be correlated with iRBD conversion. Distinct characteristics of the miRNA profiles among normal, iRBD and PD samples were discovered, which provides a panel of promising biomarkers for the identification of PD patients and those in the prodromal stage iRBD.

Quality assessment of enzymatic methyl-seq library constructed using crude cell lysate

Enzymatic methyl-seq (EM-seq), an enzyme-based method, identifies genome-wide DNA methylation, which enables us to obtain reliable methylome data from purified genomic DNA by avoiding bisulfite-induced DNA damage. However, the loss of DNA during purification hinders the methylome analysis of limited samples. The crude DNA extraction method is the quickest and minimal sample loss approach for obtaining useable DNA without requiring additional dissolution and purification. However, it remains unclear whether crude DNA can be used directly for EM-seq library construction. In this study, we aimed to assess the quality of EM-seq libraries prepared directly using crude DNA. The crude DNA-derived libraries provided appropriate fragment sizes and concentrations for sequencing similar to those of the purified DNA-derived libraries. However, the sequencing results of crude samples exhibited lower reference sequence mapping efficiencies than those of the purified samples. Additionally, the lower-input crude DNA-derived sample exhibited a marginally lower cytosine-to-thymine conversion efficiency and hypermethylated pattern around gene regulatory elements than the higher-input crude DNA- or purified DNA-derived samples. In contrast, the methylation profiles of the crude and purified samples exhibited a significant correlation. Our findings indicate that crude DNA can be used as a raw material for EM-seq library construction.

Ultrafast bisulfite sequencing detection of 5-methylcytosine in DNA and RNA

Bisulfite sequencing (BS-seq) to detect 5-methylcytosine (5mC) is limited by lengthy reaction times, severe DNA damage, overestimation of 5mC level and incomplete C-to-U conversion of certain DNA sequences. We present ultrafast BS-seq (UBS-seq), which uses highly concentrated bisulfite reagents and high reaction temperatures to accelerate the bisulfite reaction by ~13-fold, resulting in reduced DNA damage and lower background noise. UBS-seq allows library construction from small amounts of purified genomic DNA, such as from cell-free DNA or directly from 1 to 100 mouse embryonic stem cells, with less overestimation of 5mC level and higher genome coverage than conventional BS-seq. Additionally, UBS-seq quantitatively maps RNA 5-methylcytosine (m5C) from low inputs of mRNA and allows the detection of m5C stoichiometry in highly structured RNA sequences. Our UBS-seq results identify NSUN2 as the major ‘writer’ protein responsible for the deposition of ~90% of m5C sites in HeLa mRNA and reveal enriched m5C sites in 5′-regions of mammalian mRNA, which may have functional roles in mRNA translation regulation.

Integrated post-acquisition data processing strategy for rapid steroid sulfate characterization in Toad gall-bladder

LC–MS serves as a workhorse for chemical profile characterization of Chinese medicinal materials (CMMs) attributing to the ability of measuring fruitful MS/MS spectral information. However, it is laborious to extract the information belonging to the compounds-of-interest from the massive data matrixes even employing those well-defined post-acquisition data processing strategies. Here, efforts were devoted to propose an integrated strategy allowing rapid chemical homologs-focused data filtering through integrating the fit-for-purpose existing strategies, such as molecular weight imprinting (MWI), diagnostic fragment ion filtering (DFIF), neutral loss filtering (NLF), and isotope pattern filtering (IPF). Homologs-focused chemical characterization of a precious CMM namely Toad gall-bladder (Chinese name: Chandan) that is rich of diverse effective steroid sulfates, particularly bufogenin sulfates, bile acid sulfates and bilichol sulfates, was employed as a proof-of-concept. Recombinant human SULT2A1-catalyzed in vitro metabolism was undertaken to generate eight bufogenin sulfates to facilitate summarizing MS/MS spectral behaviors. After in-house data library construction and MS1 and MS2 spectral acquisition, data filtering was conducted as follows: 1) MWI and IPF was utilized in combination to capture deprotonated molecular ions and the 34S isotopic ions for the sulfates of those reported steroids; 2) m/z 79.9568 (SO3−·) and 96.9596 (HSO4−) were applied to DFIF; and 3) SO3 (79.9568 Da) served as the feature to achieve NLF. Those captured MS/MS information subsequently participated in tentatively structural annotation through applying those empirical mass fragmentation rules. As a result, 71 compounds including 7 bufogenin sulfates, 17 bile acid sulfates, 13 bilichol sulfates and a C-23 steroid sulfate were detected from Toad gall-bladder and thereof, 39 ones received plausible identities assignment. Above all, the steroid sulfates in Toad gall-bladder were profiled in depth, and more importantly, the proposed strategy should be a meaningful option for, but not limited to, submetabolome characterization in CMMs.

Construction of a digital library of vocal music resources based on second-order data decomposition algorithm

Abstract In this paper, in order to solve the modal aliasing problem of the EMD decomposition algorithm and EEMD decomposition algorithm and optimize the vocal audio data decomposition on the basis of the adaptive VMD algorithm, the EEMD-VMD second-order data decomposition algorithm is proposed to decompose the digitized time series of vocal music resources, and to update the construction of the digital library of vocal music resources. Combined with the decomposition steps of the second-order data decomposition algorithm in the vocal resources digitized library, the overall framework of the vocal resources digitized library is designed and constructed with the main line of vocal resource types and the secondary line of content categories. Design the experimental environment, preprocess the vocal audio signal features, explore the modal number K value size of the EEMD-VMD second-order data decomposition algorithm, analyze the vocal audio denoising performance of the algorithm, and compare the correlation coefficients of the IMF components of the decomposition algorithms with the original audio signals. Explore the second-order data decomposition algorithm’s emotional classification of vocal resources and the performance of vocal signal enhancement, add noise sources, and use subjective and objective evaluation methods to assess the quality of vocal PESQ and STOI after decomposition processing. The EEMD-VMD second-order data decomposition algorithm performs the most prominently in street noise environments. The enhancement results in the case of signal-to-noise ratios of -5, -10, and -15 are 3.59, respectively, 4.36, 4.29, and the mean value of the enhancement performance reaches 4.08. The second-order data decomposition algorithm’s precise processing of vocal resources provides better quality digital resources for the construction of a digital library of vocal resources.

Research on the construction of MEM “project bidding and contract management” teaching case library

Case teaching is an important way to strengthen the training of practical ability of professional degree graduate students. With the rapid development of Master of Engineering Management (MEM) in China in recent years, the cases for the teaching of MEM curriculum need constantly renewed, further excavation, more collection and application, to form a systematic case library. Pushing forward the construction of case library in teaching of MEM professional degree graduate students help case teaching play full advantage. Taking the case library of “Project bidding and contract management” course for example, the paper expounds the relevant theoretical basis of teaching case library construction of professional degree postgraduate courses. And the paper puts forward some design principles and strategies of the construction of case library. Finally, the paper presents the application effects of “Project bidding and contract management” case library. It is hoped that the paper can provide some reference for improving the training quality of MEM professional degree graduate students.

A facile strategy for the construction of a phage display cyclic peptide library for the selection of functional macrocycles.

Cyclic peptides represent invaluable scaffolds in biological affinity, providing diverse collections for discovering functional molecules targeting challenging biological entities and protein-protein interactions. The field increasingly focuses on developing cyclization strategies and chemically modified combinatorial libraries in conjunction with M13 phage display, to identify macrocyclic peptide inhibitors for traditionally challenging targets. Here, we introduce a cyclization strategy utilizing ortho-phthalaldehyde (OPA) for the discovery of active macrocycles characterized by asymmetric scaffolds with side-chain cyclization. Through this approach, aldehyde groups attached to free molecules sequentially attack the ε-amine of lysine and the thiol of cysteine, facilitating the rapid cyclization of genetically encoded linear precursor libraries displayed on phage particles. The construction of a 109-member library and subsequent screening successfully identified cyclic peptide binders targeting three therapeutically relevant proteins: PTP1B, NEK7, and hKeap1. The results confirm the efficacy in rapidly obtaining active ligands with micromolar potency. This work provides a fast and efficient operable high-throughput platform for screening functional peptide macrocycles, which hold promise for broad application in therapeutics, chemically biological probes, and disease diagnosis.

Construction of Case Library for the Course of “Theory and Application of Geotechnical Engineering”

Construction of Case Library for the Course of “Theory and Application of Geotechnical Engineering”

CRISPRi-Driven Genetic Screening for Designing Novel Microbial Phenotypes.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system has enabled rapid advances in genomic engineering and transcriptional regulation. Specifically, CRISPR interference (CRISPRi) system has been used to systematically investigate the gene functions of microbial strains in a high-throughput manner. This method involves growth profiling using cells that have been transformed with the deactivated Cas9 (dCas9) and single-guide RNA (sgRNA) libraries that target individual genes. The fitness scores of each gene are calculated by measuring the abundance of individual sgRNAs during cell growth and represent gene essentiality. In this chapter, a process is described for functional genetic screening using CRISPRi at the whole-genome scale, starting from the synthesis of sgRNA libraries, construction of CRISPRi libraries, and identification of essential genes through growth profiling. The commensal bacterium Bacteroides thetaiotaomicron was used to implement the protocol. This method is expected to be applicable to a broader range of microorganisms to explore the novel phenotypic characteristics of microorganisms.

Construction of Online Course Resource Library Based on MEA-BP Neural Networks

Abstract In this paper, the MEA algorithm is applied to the initial optimization of the weight threshold of BP neural network, which improves the stability of the classification of course resources through a two-stage optimization search process. Secondly, the effective recognition of knowledge point entities of teaching resources is realized by combining the LSTM-CRF entity recognition model, the BERT pre-trained language model and the text data enhancement technique based on the maximum bi-directional matching algorithm. In addition, the article proposes a candidate knowledge point entity generation method based on Levenshtein Distance and an entity characterization method based on BERT-TextCNN, which helps to alleviate the noise problem of the text data of curriculum resources and enhance the entity linking effect. The results of the study show that this newly constructed online course resource repository can significantly improve the allocation level of educational resources and reduce the variability of resource allocation among colleges and universities. The coefficient of educational resource allocation variation for SN217 in the university district was reduced from 0.764 to 0.518.In addition, the mean values of this repository in terms of learning path, perceived usefulness, course resources, and intention to use ranged from 1.45 to 1.66.The study in this paper provides valuable methods and insights for optimizing online educational resources.

Analysis of mechanism and optimal value of urban built environment resilience in response to stormwater flooding

The concept of urban resilience focuses on understanding the process and mechanisms of disaster occurrence, providing innovative approaches to address stormwater flooding. However, existing studies primarily concentrate on enhancing overall system resilience, with limited research examining the temporal progression from stormwater disturbance to flood generation. To fill this gap, this study categorizes the development process of stormwater flooding into three periods: disturbance resistance (DR), adjustment and adaptation (AA), and rapid recovery (RR). Using the SWMM (Storm Water Management Model) software, 27 representative parcels in the Beijing-Tianjin-Hebei region of China were simulated. By sequentially considering single-indicator control variables, resilience indicators that significantly impact the three periods were identified through the construction of a stormwater flooding resilience indicator library. Subsequently, resilience models for each disaster phase were constructed using the BP (Back Propagation) neural network, and genetic algorithms were employed to optimize the models and determine the optimal values of resilience indicators for each period. Finally, the research findings were summarized into a resilience design method for the built environment to address stormwater flooding, accompanied by a guide for improving stormwater flooding resilience.The study reveals the following key findings: (1) the influence of physical and spatial elements in the built environment on stormwater flooding formation varies across different stages of the disaster process; (2) distinct resilience indicators operate at different times and in different ways throughout the entire stormwater flooding resilience process; (3) enhancing stormwater flooding resilience in the built environment does not necessarily require setting specific threshold values for each influencing indicator; instead, an optimal single value emerges when multiple indicators interact. Moreover, when multiple indicators interact, an optimal combination module with the best value for a single indicator exists. This study investigates the complete cycle from storm disturbance to flood disaster formation, offering both solutions for cities to mitigate storm flood disasters and advancing theoretical research on urban storm flood resilience while fostering interdisciplinary integration.

Research on the Construction of Case Library for Middle School Mathematics Teaching Design

Research on the Construction of Case Library for Middle School Mathematics Teaching Design