Sequence Bias Research Articles

Optimized Construction of a Yeast SICLOPPS Library for Unbiased In Vivo Selection of Cyclic Peptides.

DNA-encoded libraries hold great potential for discovering small, cyclized peptides with drug potential. Split-intein circular ligation of peptides and proteins (SICLOPPS) is a well-established method for in vivo selection of cyclic peptides targeting specific intracellular components. However, the method has mainly been used in prokaryotic cells. In contrast, selection studies performed directly in eukaryotic cells allow for the identification of cyclic peptides promoting a functional outcome, without the need to define a specific cellular target. Here, we report the construction of a Saccharomyces cerevisiae-specific SICLOPPS library of 80 million members, via careful optimization of several steps to increase the size of the library. Individual library members were shown to be correctly expressed and processed in yeast. High-throughput sequencing was conducted on the randomized primer used for library construction and the pure yeast SICLOPPS library isolated from Escherichia coli. A distinct guanine insertion bias was observed in the peptide-encoding, randomized sequence, which was primarily attributed to the degenerate primer used to introduce the randomized sequence. Moreover, high-throughput sequencing was performed on the library before and after the induction of cyclic peptide expression in yeast. Importantly, expression of the SICLOPPS library in S. cerevisiae caused only a marginal further sequence bias. Our work paves the way for selection studies using a large and diverse library to identify cyclic peptides of therapeutic interest that promote a specific phenotypic outcome in eukaryotic organisms, with yeast representing a beneficial model system due to its high transformation efficiency.

RecombiCraft library construction: A novel method for DNA library cloning and expansion using non-enzymatic single-step DNA recombination and liquid culture

In this study, we introduce RecombiCraft, an innovative, rapid, and cost-efficient method for constructing DNA libraries in E. coli. This method uses seamless ligation cloning extract (SLiCE) coupled with liquid culture amplification to effectively minimize sequence biases. The technique capitalizes on the natural homologous recombination capabilities of E. coli cell lysates, eliminating the need for multiple purified enzymes and reducing costs. We first synthesized the library backbone and inserts via PCR, employing high-fidelity polymerase to minimize sequence bias. The SLiCE technique was then used to assemble the DNA fragments introduced into E. coli through electroporation. To ensure the integrity of the library, we optimized culture times based on next-generation sequencing analysis which confirmed the minimal sequence bias. The RecombiCraft method demonstrates that this approach is economical and maintains the library’s uniformity. By using liquid culture, this method can complete DNA library generation in about 12 hours and final extraction is simple, making it a promising tool for genetic research and biotechnology applications.

Overcoming nucleotide bias in the nonenzymatic copying of RNA templates.

The RNA World hypothesis posits that RNA was the molecule of both heredity and function during the emergence of life. This hypothesis implies that RNA templates can be copied, and ultimately replicated, without the catalytic aid of evolved enzymes. A major problem with nonenzymatic template-directed polymerization has been the very poor copying of sequences containing rA and rU. Here, we overcome that problem by using a prebiotically plausible mixture of RNA mononucleotides and random-sequence oligonucleotides, all activated by methyl isocyanide chemistry, that direct the uniform copying of arbitrary-sequence templates, including those harboring rA and rU. We further show that the use of this mixture in copying reactions suppresses copying errors while also generating a more uniform distribution of mismatches than observed for simpler systems. We find that oligonucleotide competition for template binding sites, oligonucleotide ligation and the template binding properties of reactant intermediates work together to reduce product sequence bias and errors. Finally, we show that iterative cycling of templated polymerization and activation chemistry improves the yields of random-sequence products. These results for random-sequence template copying are a significant advance in the pursuit of nonenzymatic RNA replication.

The quality and detection limits of mitochondrial heteroplasmy by long read nanopore sequencing

This study evaluates long-read and short-read sequencing for mitochondrial DNA (mtDNA) heteroplasmy detection. 592,315 bootstrapped datasets generated from two single-nucleotide mismatched ultra-deep sequenced mtDNA samples were used to assess basecalling error and accuracy, limit of heteroplasmy detection, and heteroplasmy detection across various coverage depths. Results showed high Phred scores of data with GC-rich sequence bias for long reads. Limit of detection of 12% heteroplasmy was identified, showing strong correlation (R2 ≥ 0.955) with expected heteroplasmy but underreporting tendency of high-level variants. Nanopore sequencing shows potential for direct applicability in mitochondrial diseases diagnostics, but stringent validation processes to ensure diagnostic result quality are required.

Scalable log-ratio lasso regression for enhanced microbial feature selection with FLORAL

Identifying predictive biomarkers of patient outcomes from high-throughput microbiome data is of high interest, while existing computational methods do not satisfactorily account for complex survival endpoints, longitudinal samples, and taxa-specific sequencing biases. We present FLORAL, an open-source tool to perform scalable log-ratio lasso regression and microbial feature selection for continuous, binary, time-to-event, and competing risk outcomes, with compatibility for longitudinal microbiome data as time-dependent covariates. The proposed method adapts the augmented Lagrangian algorithm for a zero-sum constraint optimization problem while enabling a two-stage screening process for enhanced false-positive control. In extensive simulation and real-data analyses, FLORAL achieved consistently better false-positive control compared to other lasso-based approaches and better sensitivity over popular differential abundance testing methods for datasets with smaller sample sizes. In a survival analysis of allogeneic hematopoietic cell transplant recipients, FLORAL demonstrated considerable improvement in microbial feature selection by utilizing longitudinal microbiome data over solely using baseline microbiome data.

Enhancing RNA-seq bias mitigation with the Gaussian self-benchmarking framework: towards unbiased sequencing data

BackgroundRNA sequencing is a vital technique for analyzing RNA behavior in cells, but it often suffers from various biases that distort the data. Traditional methods to address these biases are typically empirical and handle them individually, limiting their effectiveness. Our study introduces the Gaussian Self-Benchmarking (GSB) framework, a novel approach that leverages the natural distribution patterns of guanine (G) and cytosine (C) content in RNA to mitigate multiple biases simultaneously. This method is grounded in a theoretical model, organizing k-mers based on their GC content and applying a Gaussian model for alignment to ensure empirical sequencing data closely match their theoretical distribution.ResultsThe GSB framework demonstrated superior performance in mitigating sequencing biases compared to existing methods. Testing with synthetic RNA constructs and real human samples showed that the GSB approach not only addresses individual biases more effectively but also manages co-existing biases jointly. The framework’s reliance on accurately pre-determined parameters like mean and standard deviation of GC content distribution allows for a more precise representation of RNA samples. This results in improved accuracy and reliability of RNA sequencing data, enhancing our understanding of RNA behavior in health and disease.ConclusionsThe GSB framework presents a significant advancement in RNA sequencing analysis by providing a well-validated, multi-bias mitigation strategy. It functions independently from previously identified dataset flaws and sets a new standard for unbiased RNA sequencing results. This development enhances the reliability of RNA studies, broadening the potential for scientific breakthroughs in medicine and biology, particularly in genetic disease research and the development of targeted treatments.

Codon Usage Analysis Reveals Distinct Evolutionary Patterns and Host Adaptation Strategies in Duck Hepatitis Virus 1 (DHV-1) Phylogroups.

Duck hepatitis virus 1 (DHV-1) is a major threat to the global poultry industry, causing significant economic losses due to high mortality rates in young ducklings. To better understand the evolution and host adaptation strategies of DHV-1, we conducted a comprehensive codon usage analysis of DHV-1 genomes. Our phylogenetic analysis revealed three well-supported DHV-1 phylogroups (Ia, Ib, and II) with distinct genetic diversity patterns. Comparative analyses of the codon usage bias and dinucleotide abundance uncovered a strong preference for A/U-ended codons and a biased pattern of dinucleotide usage in the DHV-1 genome, with CG dinucleotides being extremely underrepresented. Effective number of codons (ENC) analysis indicated a low codon usage bias in the DHV-1 ORF sequences, suggesting adaptation to host codon usage preferences. PR2 bias, ENC plot, and neutrality analyses revealed that both mutation pressure and natural selection influence the codon usage patterns of DHV-1. Notably, the three DHV-1 phylogroups exhibited distinct evolutionary trends, with phylogroups Ia and Ib showing evidence of neutral evolution accompanied by selective pressure, while the phylogroup II evolution was primarily driven by random genetic drift. Comparative analysis of the codon usage indices (CAI, RCDI, and SiD) among the phylogroups highlighted significant differences between subgroups Ia and Ib, suggesting distinct evolutionary pressures or adaptations influencing their codon usage. These findings contribute to our understanding of DHV-1 evolution and host adaptation, with potential implications for the development of effective control measures and vaccines.

NucMACC: An MNase-seq pipeline to identify structurally altered nucleosomes in the genome.

Micrococcal nuclease sequencing is the state-of-the-art method for determining chromatin structure and nucleosome positioning. Data analysis is complex due to the AT-dependent sequence bias of the endonuclease and the requirement for high sequencing depth. Here, we present the nucleosome-based MNase accessibility (nucMACC) pipeline unveiling the regulatory chromatin landscape by measuring nucleosome accessibility and stability. The nucMACC pipeline represents a systematic and genome-wide approach for detecting unstable ("fragile") nucleosomes. We have characterized the regulatory nucleosome landscape in Drosophila melanogaster, Saccharomyces cerevisiae, and mammals. Two functionally distinct sets of promoters were characterized, one associated with an unstable nucleosome and the other being nucleosome depleted. We show that unstable nucleosomes present intermediate states of nucleosome remodeling, preparing inducible genes for transcriptional activation in response to stimuli or stress. The presence of unstable nucleosomes correlates with RNA polymerase II proximal pausing. The nucMACC pipeline offers unparalleled precision and depth in nucleosome research and is a valuable tool for future nucleosome studies.

Comparative analysis the chloroplast genomes of Celastrus (Celastraceae) species: Provide insights into molecular evolution, species identification and phylogenetic relationships

BackgroundThe genus Celastrus is an important medicinal plant resource. The similarity of morphology and the lack of complete chloroplast genome analysis have significantly impeded the exploration of species identification, molecular evolution and phylogeny of Celastrus. PurposeIn order to resolve the phylogenic controversy of Celastrus species, the chloroplast genome comparative analysis was performed to provide genetic evidence. MethodsIn this study, we collected and sequenced ten chloroplast genomes of Celastrus species from China and downloaded three chloroplast genomes from the databases. The chloroplast genomes were compared and analyzed to explore their characteristics and evolution. Furthermore, the phylogenetic relationships of Celastrus species were inferred based on the whole chloroplast genomes and protein-coding genes. ResultsAll the 13 Celastrus species chloroplast genomes showed a typical quadripartite structure with genome sizes ranging from 155,113 to 157,366 bp. The intron loss of the rps16 gene occurred in all the 13 Celastrus species. The GC content, gene sequence, repeat types and codon bias pattern were highly conserved. Ten highly variation regions were identified, which can be used as potential DNA markers in molecular identification of Celastrus species. Eight genes, including accD, atp4, ndhB, rpoC1, rbcL, rpl2, rpl20 and ycf1, were detected to experience positive selection. Phylogenetic analysis showed that Celastrus was a monophyletic group and Tripterygium was the closest sister-group. Noteworthy, C. gemmatus Loes. and C. orbiculatus Thunb. can be discriminated using the chloroplast genome as a super barcode. The comparative and phylogenetic analysis results proposed that C. tonkinensis Pitard. was the synonym of C. hindsii Benth. ConclusionThe comparative analysis of the Celastrus chloroplast genomes can provide comprehensive genetic evidence for molecular evolution, species identification and phylogenetic relationships.

Variability and bias in microbiome metagenomic sequencing: an interlaboratory study comparing experimental protocols.

Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

A systematic review and multivariate meta-analysis of the physical and mental health benefits of touch interventions

Receiving touch is of critical importance, as many studies have shown that touch promotes mental and physical well-being. We conducted a pre-registered (PROSPERO: CRD42022304281) systematic review and multilevel meta-analysis encompassing 137 studies in the meta-analysis and 75 additional studies in the systematic review (n = 12,966 individuals, search via Google Scholar, PubMed and Web of Science until 1 October 2022) to identify critical factors moderating touch intervention efficacy. Included studies always featured a touch versus no touch control intervention with diverse health outcomes as dependent variables. Risk of bias was assessed via small study, randomization, sequencing, performance and attrition bias. Touch interventions were especially effective in regulating cortisol levels (Hedges’ g = 0.78, 95% confidence interval (CI) 0.24 to 1.31) and increasing weight (0.65, 95% CI 0.37 to 0.94) in newborns as well as in reducing pain (0.69, 95% CI 0.48 to 0.89), feelings of depression (0.59, 95% CI 0.40 to 0.78) and state (0.64, 95% CI 0.44 to 0.84) or trait anxiety (0.59, 95% CI 0.40 to 0.77) for adults. Comparing touch interventions involving objects or robots resulted in similar physical (0.56, 95% CI 0.24 to 0.88 versus 0.51, 95% CI 0.38 to 0.64) but lower mental health benefits (0.34, 95% CI 0.19 to 0.49 versus 0.58, 95% CI 0.43 to 0.73). Adult clinical cohorts profited more strongly in mental health domains compared with healthy individuals (0.63, 95% CI 0.46 to 0.80 versus 0.37, 95% CI 0.20 to 0.55). We found no difference in health benefits in adults when comparing touch applied by a familiar person or a health care professional (0.51, 95% CI 0.29 to 0.73 versus 0.50, 95% CI 0.38 to 0.61), but parental touch was more beneficial in newborns (0.69, 95% CI 0.50 to 0.88 versus 0.39, 95% CI 0.18 to 0.61). Small but significant small study bias and the impossibility to blind experimental conditions need to be considered. Leveraging factors that influence touch intervention efficacy will help maximize the benefits of future interventions and focus research in this field.

BEERS2: RNA-Seq simulation through high fidelity in silico modeling.

Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully length messenger RNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in polymerase chain reaction (PCR) amplification, barcode read errors and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm.

Principles and Limitations of miRNA Purification and Analysis in Whole Blood Collected during Ablation Procedure from Patients with Atrial Fibrillation.

Background: MicroRNA (miRNA) have the potential to be non-invasive and attractive biomarkers for a vast number of diseases and clinical conditions; however, a reliable analysis of miRNA expression in blood samples meets a number of methodological challenges. In this report, we presented and discussed, specifically, the principles and limitations of miRNA purification and analysis in blood plasma samples collected from the left atrium during an ablation procedure on patients with atrial fibrillation (AF). Materials and Methods: Consecutive patients hospitalized in the First Department of Cardiology for pulmonary vein ablation were included in this study (11 with diagnosed paroxysmal AF, 14 with persistent AF, and 5 without AF hospitalized for left-sided WPW ablation-control group). Whole blood samples were collected from the left atrium after transseptal puncture during the ablation procedure of AF patients. Analysis of the set of miRNA molecules was performed in blood plasma samples using the MIHS-113ZF-12 kit and miScript microRNA PCR Array Human Cardiovascular Disease. Results: The miRNS concentrations were in the following ranges: paroxysmal AF: 7-23.1 ng/µL; persistent AF: 4.9-66.8 ng/µL; controls: 6.3-10.6 ng/µL. The low A260/280 ratio indicated the protein contamination and the low A260/A230 absorbance ratio suggested the contamination by hydrocarbons. Spectrophotometric measurements also indicated low concentration of nucleic acids (<10 ng/µL). Further steps of analysis revealed that the concentration of cDNA after the Real-Time PCR (using the PAXgene RNA Blood kit) reaction was higher (148.8 ng/µL vs. 68.4 ng/µL) and the obtained absorbance ratios (A260/A280 = 2.24 and A260/A230 = 2.23) indicated adequate RNA purity. Conclusions: Although developments in miRNA sequencing and isolation technology have improved, detection of plasma-based miRNA, low RNA content, and sequencing bias introduced during library preparation remain challenging in patients with AF. The measurement of the quantity and quality of the RNA obtained is crucial for the interpretation of an efficient RNA isolation.

Abstract 869: Single-cell DNA replication dynamics in genomically unstable cancers

Abstract Background: DNA replication and cell cycle regulation are frequently disrupted as part of a cancer’s progression toward uncontrolled proliferation, generating somatic copy number alterations (CNAs) and producing intratumoral heterogeneity that drives subsequent evolution. Structural variation and CNAs have been shown to impact epigenetic and chromatin states, but our ability to assess their impact on DNA replication timing (RT) and cell proliferation rates remains limited. Single-cell whole genome sequencing (scWGS) is a powerful method for studying clonal heterogeneity and CNAs, and has the potential to provide greater insight into DNA replication dynamics in aneuploid populations. However, computational identification of S-phase cells and distinguishing inherited somatic CNAs from transient DNA replication changes remain challenging. Methods: We present a new method, PERT, which uses a Bayesian framework to model read depth as a combination of somatic copy number, replication, and sequencing bias, enabling estimation of DNA replication profiles and cell cycle phase from scWGS data. Unlike previous approaches, PERT provides unbiased estimates of RT and cell cycle phase which allows for analysis of previously uncharacterized cell types using any scWGS platform. These unique properties enable PERT to perform novel analysis such as estimating clone-specific proliferation rates and studying the interplay between RT and somatic CNAs during tumor evolution. We applied PERT to a cohort of &amp;gt;50,000 scWGS cells obtained from a collection of genomically unstable breast and ovarian cell lines, xenografts and primary cancer tissues. Results: Clone RT profiles correlated with future copy number changes in serially passaged cell lines. Cell type was the strongest determinant of RT heterogeneity, while whole genome doubling (WGD) and mutational signature had weaker RT associations but were associated with accumulation of late S-phase cells. Recurrent CNAs affecting chromosome X had striking impact on RT, with loss of the inactive X allele shifting replication earlier, and loss of inactive Xq resulting in reactivation of Xp. Analysis of time series xenografts illustrated that cell cycle distributions approximate clone proliferation. This relationship enabled us to observe that highly proliferative clones were the most chemosensitive in cisplatin-treated xenografts and, separately, present novel evidence that WGD leads to slower proliferation. Conclusions: Our analysis implicates cell type as the strongest determinant of RT with chrX being the locus of highest RT variation due to X-inactivation. Separately, quantification of S-phase cells enables interrogation of the on- and off-treatment fitness of genetically distinct subclones. This work leads to better understanding of how DNA replication dynamics drive and are further modulated by genomic instability. Citation Format: Adam C. Weiner, Marc Williams, Hongyu Shi, Ignacio Vazquez-Garcia, Sohrab Salehi, Nicole Rusk, Sohrab P. Shah, Andrew McPherson. Single-cell DNA replication dynamics in genomically unstable cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 869.

Abstract 7022: Whole genome and reduced representation enzymatic methyl-seq enable cost effective methylomes

Abstract DNA methylation is an epigenetic regulator of gene expression with important functions in development and diseases such as cancer. Traditionally, sodium bisulfite conversion was used to distinguish 5-methylcytosines (5mC) and 5-hydroxymethylcytosines (5hmC) from cytosines. However, this method damages DNA and introduces significant sequencing bias. NEBNext® Enzymatic Methyl-seq (EM-seq™) is an enzymatic conversion approach that minimizes DNA damage therefore enabling longer insert sizes, lower duplication rates and a more accurate quantification of methylation in DNA samples with inputs ranging from 10 ng to 200 ng. An improved enzymatic conversion method, EM-seq v2, has a more streamlined workflow and an expanded DNA input range of 100 pg to 200 ng. Libraries made using NA12878 genomic DNA show improved yields, consistent global methylation and an even GC bias representation. The increased library yields subsequently reduces sequencing duplications and costs. Sequencing costs are an important consideration when performing whole genome methylome analysis as this often needs high sequencing depth to attain meaningful coverage to accurately call methylation. Reduced representation libraries, a commonly used method to investigate DNA methylation, relies on enrichment of CpGs within libraries digested using MspI. These CpGs are commonly found in regulatory regions. Although lacking comprehensive CpG coverage, for many researchers this method provides enough cost effective CpG methylation coverage for their studies. Reduced Representation EM-seq libraries (RREM-seq) and Reduced Representation Bisulfite libraries (RRBS) were made using 200 ng to 100 pg of NA12878 DNA. EM-seq adaptors were ligated to MspI digested DNA followed by conversion using either EM-seq v2 or sodium bisulfite. Libraries were PCR amplified and sequenced on an Illumina NovaSeq platform. RREM-seq resulted in higher yields and reproducible results regardless of input amounts compared to RRBS libraries. RREM-seq libraries also identified a higher number of CpGs with even coverage facilitating accurate methylation calling. RREM-seq libraries have superior sequencing metrics resulting in robust methylation profiling. Focusing on a subset of the genome generates higher coverage DNA methylation data at a lower DNA sequencing cost. Citation Format: Vaishnavi Panchapakesa, Chaithanya Ponnaluri, Daniel Evanich, Ariel Erijman, Bradley Langhorst, Louise Williams. Whole genome and reduced representation enzymatic methyl-seq enable cost effective methylomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7022.

A Detailed Protocol for Constructing a Human Single-Chain Variable Fragment (scFv) Library and Downstream Screening via Phage Display.

The development of monoclonal antibodies (mAbs) represents a significant milestone in both basic research and clinical applications due to their target specificity and versatility in therapeutic and diagnostic applications. The innovative strategy of mAb screening, utilizing phage display, facilitates the in vitro screening of antibodies with high affinity to target antigens. The single-chain variable fragment (scFv) is a subset of mAb derivatives, known for its high binding affinity and smaller size-just one-third of that of human IgG. This report outlines a detailed and comprehensive procedure for constructing a scFv phagemid library derived from human patients, followed by screening via phage display affinity selection. The protocol utilizes 348 primer combinations spanning the entire human antibody repertoire to minimize sequence bias and maintain library diversity during polymerase chain reaction (PCR) for scFv generation, resulting in a library size greater than 1 × 108. Furthermore, we describe a high-throughput phage display screening protocol using enzyme-linked immunosorbent assay (ELISA) to evaluate more than 1200 scFv candidates. The generation of a highly diverse scFv library, coupled with the implementation of a phage display screening methodology, is expected to provide a valuable resource for researchers in pursuit of scFvs with high affinity for target antigens, thus advancing both research and clinical endeavors.

The pan-microbiome profiling system Taxa4Meta identifies clinical dysbiotic features and classifies diarrheal disease.

Targeted metagenomic sequencing is an emerging strategy to survey disease-specific microbiome biomarkers for clinical diagnosis and prognosis. However, this approach often yields inconsistent or conflicting results owing to inadequate study power and sequencing bias. We introduce Taxa4Meta, a bioinformatics pipeline explicitly designed to compensate for technical and demographic bias. We designed and validated Taxa4Meta for accurate taxonomic profiling of 16S rRNA amplicon data acquired from different sequencing strategies. Taxa4Meta offers significant potential in identifying clinical dysbiotic features that can reliably predict human disease, validated comprehensively via reanalysis of individual patient 16S data sets. We leveraged the power of Taxa4Meta's pan-microbiome profiling to generate 16S-based classifiers that exhibited excellent utility for stratification of diarrheal patients with Clostridioides difficile infection, irritable bowel syndrome, or inflammatory bowel diseases, which represent common misdiagnoses and pose significant challenges for clinical management. We believe that Taxa4Meta represents a new "best practices" approach to individual microbiome surveys that can be used to define gut dysbiosis at a population-scale level.

Identification, comparative and phylogenetic analysis of eight Vitis species based on the chloroplast genome revealed their contribution to heat tolerance in grapevines

The chloroplast genome plays an important role in exploring the origin and evolution of grapes. In this study, the chloroplast genomes of eight grape germplasms were analyzed. The results show that the sequence arrangement was highly conserved and has a typical annular quadripartite structure. At the same time, GC content, gene sequence, repeat type and codon bias pattern are highly conserved. Whereas, 19 mutation hotspot regions were identified by the comparative analysis, including 9 protein-coding genes (atpF, rpoC2, rps18, psbC, atpB, rbcL, rps20, ycf1 and ycf15) and 10 non-coding regions (trnK – rps16, rps16 – trnQ, trnE – trnT, psbZ - trnG, ndhC – trnV, accD – psaI, ycf2 – trnL, ndhF – rpl32, ccsA - ndhD, trnL - ycf2). Most of these highly variable genes were involved in the physiological process of photosynthesis. Further examination of photosynthetic fluorescence showed an obvious difference among those species under high-temperature conditions. In addition, maximum likelihood (ML) evolutionary trees depend on the chloroplast genome and CDS sequences suggest that heat tolerance may be related to the phylogeny of grapevine. In the future, the highly variable sequences and SSR loci were also identified by the chloroplast genome comparison, and those results may be used for the DNA molecular marker in taxonomic studies and contribute to the heat stress resistance breeding of grapevine.

Human PKD1 sequences form R-loop structures in vitro.

Autosomal dominant polycystic kidney disease results from the loss of the PKD1 gene product, polycystin 1. Regulatory mechanisms are unresolved, but an apparent G/C sequence bias in the gene is consistent with co-transcriptional R-loop formation. R-loops regulate gene expression and stability, and they form when newly synthesized RNA extensively pairs with the template DNA to displace the non-template strand. In this study, we tested two human PKD1 sequences for co-transcriptional R-loop formation in vitro. We observed RNase H-sensitive R-loop formation in intron 1 and 22 sequences, but only in one transcriptional orientation. Therefore, R-loops may participate in PKD1 expression or stability.

The Video Manipulation Effect (VME): A quantification of the possible impact that the ordering of YouTube videos might have on opinions and voting preferences.

Recent research has identified a number of powerful new forms of influence that the internet and related technologies have made possible. Randomized, controlled experiments have shown, for example, that when results generated by search engines are presented to undecided voters, if those search results favor one political candidate over another, the opinions and voting preferences of those voters can shift dramatically-by up to 80% in some demographic groups. The present study employed a YouTube simulator to identify and quantify another powerful form of influence that the internet has made possible, which we have labeled the Video Manipulation Effect (VME). In two randomized, controlled, counterbalanced, double-blind experiments with a total of 1,463 politically-diverse, eligible US voters, we show that when a sequence of videos displayed by the simulator is biased to favor one political candidate, and especially when the "up-next" video suggested by the simulator favors that candidate, both the opinions and voting preferences of undecided voters shift dramatically toward that candidate. Voting preferences shifted by between 51.5% and 65.6% overall, and by more than 75% in some demographic groups. We also tested a method for masking the bias in video sequences so that awareness of bias was greatly reduced. In 2018, a YouTube official revealed that 70% of the time people spend watching videos on the site, they are watching content that has been suggested by the company's recommender algorithms. If the findings in the present study largely apply to YouTube, this popular video platform might have unprecedented power to impact thinking and behavior worldwide.