Sequence Overlap Research Articles

Activated single nucleotide mismatch determination through toehold-embedded hairpin-mediated strand displacement reaction alongside CRISPR-Cas12a for detection of TP53 point mutation

The CRISPR-Cas12a-based diagnostic platform is renowned for its high sensitivity and, when coupled with the toehold-mediated strand displacement (TMSD) reaction, enables the detection of single nucleotide mismatch (SNM). However, conventional TMSD with the CRISPR-Cas12a system suffers from signal leakage due to overlapping activator sequences and low displacement efficiency. Here, we propose a toehold-embedded hairpin-mediated strand displacement (THMSD) method and leverage the magnesium attenuation effect of CRISPR-Cas12a for selective single-point mutation detection in the TP53 gene. This approach effectively mitigates signal leakage as the hairpin DNA retains partial crRNA targeting sequences within its loop, preventing sequence overlap with the trigger and direct Cas12a activation. Additionally, the magnesium attenuation effect reduces background signal and enhances selectivity. We investigated toehold length and mismatch position to detect SNM with a high discrimination factor (DF). This high DF allows the THMSD/CRISPR-Cas12a system to differentiate between TP53 R273H mutant and TP53 wildtype genes for cancer screening at low abundances, down to 0.1 % with a concentration of 20 pM. When used for screening between H1975 and WI38 cells, the statistically significant difference was attainable with polymerase chain reaction (PCR) template loading as low as 4 ng. These results pave the way for developing CRISPR-Cas12a-based methods to effectively detect TP53 mutations as lung cancer biomarkers.

Structural requirements for the specific binding of CRABP2 to cyclin D3.

Cellular retinoic acid binding protein 2 (CRABP2) transports retinoic acid from the cytoplasm to the nucleus where it then transfers its cargo to retinoic acid receptor-containing complexes leading to activation of gene transcription. We demonstrate using purified proteins that CRABP2 is also a cyclin D3-specific binding protein and that the CRABP2 cyclin D3 binding site and the proposed CRABP2 nuclear localization sequence overlap. Both sequences are within the helix-loop-helix motif that forms a lid to the retinoic acid binding pocket. Mutations within this sequence that block both cyclin D3 and retinoic acid binding promote formation of a CRABP2 structure in which the retinoic acid binding pocket is occupied by an alternative lid conformation. Structural and functional analysis of CRABP2 and cyclin D3 mutants combined with AlphaFold models of the ternary CDK4/6-cyclin D3-CRABP2 complex supports the identification of an α-helical protein binding site on the cyclin D3 C-terminal cyclin box fold.

Packaging of alphavirus-based self-amplifying mRNA yields replication-competent virus through a mechanism of aberrant homologous RNA recombination.

Messenger (m)RNA has taken center stage in vaccine development, gene therapy, and cancer immunotherapy. A next-generation of mRNA is the self-amplifying (sa)mRNA, which induces broad and long-lasting immunity at a lower dose which provides better clinical outcomes in conjunction with fewer adverse effects. SamRNA, also known as "replicon" RNA, encodes the replication machinery of an alphavirus together with an antigen. Efficient delivery of replicon RNA to target tissues can be accomplished by packaging the replicon RNA in virus-like replicon particles (VRPs) via co-transfection of producer cells with defective helper RNA(s) encoding the alphavirus structural proteins. During the manufacture of VRPs, however, there is a potential risk of RNA recombination, which may lead to the formation of replication-competent virus (RCV). To investigate the factors influencing the unwanted RCV formation, we evaluated how sequence homology orchestrates alphavirus RNA recombination. Several combinations of complementing alphavirus replicon and helper RNAs varying in length of sequences overlap were co-transfected in mammalian cells. The culture fluid was serially passaged to detect RCV. Nanopore sequencing of cells after the first passage in combination with amplicon-based Sanger sequencing of RCV in the culture fluid after four passages led to the detection of RNA recombination. RCV was generated between replicon and helper RNAs with sequence homology in either the non-structural or structural genes, whereas RNAs without overlapping gene regions did not generate RCV. Remarkably, no sequence overlap was detected at the recombination junction sites in the RCV genome, suggesting a mechanism of "aberrant homologous RNA recombination." Accordingly, we conclude that the alphavirus RNA recombination process leading to the formation of RCV is homology-assisted and can be prevented by avoiding sequence homology between replicon and helper RNAs.IMPORTANCEThere is a growing interest in the use of self-amplifying (sa)mRNA vectors for next-generation vaccine development, gene therapy, and cancer immunotherapy. The delivery of samRNA in the form of virus-like replicon particles (VRPs) enables efficient delivery of samRNA to target tissue. The production of these VRPs, however, suffers from contamination with replication-competent virus (RCV) that is thought to arise from recombination events between samRNA and helper RNAs for VRP packaging. The presence of RCV in samRNA in the clinical product is undesirable as alphaviruses may cause serious disease in humans. However, the underlying recombination mechanism leading to RCV is currently unknown. In our work, we demonstrate a detailed evaluation of the recombination sites, which indicates that RCV is formed through an unusual mechanism of "aberrant homologous RNA recombination." The results are useful for researchers in the field of RNA vaccine manufacture and delivery.

Soil diazotrophs sustain nitrogen fixation under high nitrogen enrichment via adjustment of community composition.

This study examined the changes in soil diazotroph community under different loads of simulated N deposition and analyzed its relationship with N fixation rates in in five forests using high-throughput sequencing. The magnitudes of N fixation rates reduced by low N loads were higher than those by high N loads. Low N loads decreased richness and diversity of diazotroph community, whereas diazotroph community structure remained stable under high N loads. Compared with low N loads, high N loads resulted in a less similarity and overlap of nifH gene sequences among the treatments and a larger adjustment of diazotroph community. Low N loads increased soil NH4+ concentrations, which decreased diazotroph community richness, diversity, and N fixation rates, whereas the increased soil NH4+ under high N loads did not have negative impacts on diazotroph community structure and N fixation. Based on these findings, it is urgently needed to incorporate the loads of N deposition and the composition of diazotroph community into terrestrial N-cycling models for accurate understanding of N inputs in forest ecosystems.

Germline-like TCR-α chains shared between autoreactive T cells in blood and pancreas

Human type 1 diabetes (T1D) is caused by autoimmune attack on the insulin-producing pancreatic beta cells by islet antigen-reactive T cells. How human islet antigen-reactive (IAR) CD4+ memory T cells from peripheral blood affect T1D progression in the pancreas is poorly understood. Here, we aim to determine if IAR T cells in blood could be detected in pancreas. We identify paired αβ (TRA/TRB) T cell receptors (TCRs) in IAR T cells from the blood of healthy, at-risk, new-onset, and established T1D donors, and measured sequence overlap with TCRs in pancreata from healthy, at risk and T1D organ donors. We report extensive TRA junction sharing between IAR T cells and pancreas-infiltrating T cells (PIT), with perfect-match or single-mismatch TRA junction amino acid sequences comprising ~29% total unique IAR TRA junctions (942/3,264). PIT-matched TRA junctions were largely public and enriched for TRAV41 usage, showing significant nucleotide sequence convergence, increased use of germline-encoded versus non-templated residues in epitope engagement, and a potential for cross-reactivity. Our findings thus link T cells with distinctive germline-like TRA chains in the peripheral blood with T cells in the pancreas.

Principles of peptide selection by the transporter associated with antigen processing

Our ability to fight pathogens relies on major histocompatibility complex class I (MHC-I) molecules presenting diverse antigens on the surface of diseased cells. The transporter associated with antigen processing (TAP) transports nearly the entire repertoire of antigenic peptides into the endoplasmic reticulum for MHC-I loading. How TAP transports peptides specific for MHC-I is unclear. In this study, we used cryo-EM to determine a series of structures of human TAP, both in the absence and presence of peptides with various sequences and lengths. The structures revealed that peptides of eight or nine residues in length bind in a similarly extended conformation, despite having little sequence overlap. We also identified two peptide-anchoring pockets on either side of the transmembrane cavity, each engaging one end of a peptide with primarily main chain atoms. Occupation of both pockets results in a global conformational change in TAP, bringing the two halves of the transporter closer together to prime it for isomerization and ATP hydrolysis. Shorter peptides are able to bind to each pocket separately but are not long enough to bridge the cavity to bind to both simultaneously. Mutations that disrupt hydrogen bonds with the N and C termini of peptides almost abolish MHC-I surface expression. Our findings reveal that TAP functions as a molecular caliper that selects peptides according to length rather than sequence, providing antigen diversity for MHC-I presentation.

Droplet Digital PCR for the Detection and Quantification of Bona Fide CircRNAs.

CircRNAs are covalently closed RNA molecules gaining increasing attention over the years. Initially considered mere splicing errors, circRNAs are now recognized as a novel class of endogenous, conserved RNAs, expressed in many different species. The unique structure, the low levels of expression, and the almost complete sequence overlap with the cognate linear RNA make their detection and quantification challenging. Moreover, it has become crucial to prove the circular nature of the targeted transcript and unequivocally distinguish the circRNA from its linear counterpart. Nowadays, the most widely used technique to quantify circRNA expression is real-time quantitative PCR (qPCR). However, in the particular case of quantification of circles, it shows several technical shortcomings which affect the accuracy of the quantification. To precisely assess circRNA expression level, droplet digital PCR (ddPCR) is rapidly taking over for the more popular qPCR. In this chapter, we describe the detailed procedure based on droplets partitioning to quantify both linear and circRNA abundancy and demonstrate the circularity of the transcript under study with high precision, in a single experiment.

Leveraging museum specimens, genomics and legacy datasets to unravel the phylogeny and biogeography of cryptin wasps (Hymenoptera, Ichneumonidae, Cryptini)

AbstractModern genomic techniques have enabled the generation of phylogenetic datasets of unprecedented scale. However, there are also troves of molecular data accumulated from past studies using Sanger sequencing, often at fine taxonomic scales. Combining both sources of data is an obviously appealing possibility, but it can also lead to inconsistency due to high levels of missing data, disparities in the scale of Sanger versus genomic datasets, and little overlap in sequences across terminals. To provide an empirical investigation of the potential of such ‘hybrid’ datasets, we combined data from ultraconserved elements (UCEs) for 183 species of Cryptini (Ichneumonidae, Hymenoptera) with a previously existing dataset of 7 loci and morphological data including 308 species plus outgroup taxa. Bioinformatics pipelines allowed recovery of ‘legacy’ markers from the bycatch of UCE sequencing, reducing the problem of limited character overlap. The resulting tree combining Sanger and UCE data is highly supported and includes dense taxon sampling of the group, allowing for a better understanding of the global radiation of Cryptini. The Neotropical region had the highest phylogenetic diversity but the lowest level of phylogenetic dispersion when corrected for standardized effect size, while the Oriental fauna showed the highest level of phylogenetic dispersion. Our results highlight the potential of hybrid datasets to produce a more complete picture of the Tree of Life combining affordability, robust support and deep taxonomic sampling.

Multimodal Single-Cell Sequencing of B Cells in Primary Sjögren's Syndrome.

B cells are important in the pathogenesis of primary Sjögren's syndrome (pSS). Patients positive for Sjögren's syndrome antigen A/Sjögren syndrome antigen B (SSA/SSB) autoantibodies are more prone to systemic disease manifestations and adverse outcomes. We aimed to determine the role of B cell composition, gene expression, and B cell receptor usage in pSS subgroups stratified for SSA/SSB antibodies. Over 230,000 B cells were isolated from peripheral blood of patients with pSS (n=6 SSA-, n=8 SSA+ single positive and n=10 SSA/SSB+ double positive) and four healthy controls and processed for single-cell RNA sequencing (scRNA-seq) and single-cell variable, diversity, and joining (VDJ) gene sequencing (scVDJ-seq). We show that SSA/SSB+ patients present the highest and lowest proportion of naïve and memory B cells, respectively, and the highest up-regulation of interferon-induced genes across all B cell subtypes. Differential usage of IGHV showed that IGHV1-69 and IGHV4-30-4 were more often used in all pSS subgroups compared with controls. Memory B cells from SSA/SSB+ patients displayed a higher proportion of cells with unmutated VDJ transcripts compared with other pSS patient groups and controls, indicating altered somatic hypermutation processes. Comparison with previous studies revealed heterogeneous clonotype pools, with little overlap in CDR3 sequences. Joint analysis using scRNA-seq and scVDJ-seq data allowed unsupervised stratification of patients with pSS and identified novel parameters that correlated to disease manifestations and antibody status. We describe heterogeneity and molecular characteristics in B cells from patients with pSS, providing clues to intrinsic differences in B cells that affect the phenotype and outcome and allowing stratification of patients with pSS at improved resolution.

Functional Involvement of circRNAs in the Innate Immune Responses to Viral Infection.

Effective viral clearance requires fine-tuned immune responses to minimize undesirable inflammatory responses. Circular RNAs (circRNAs) are a class of non-coding RNAs that are abundant and highly stable, formed by backsplicing pre-mRNAs, and expressed ubiquitously in eukaryotic cells, emerging as critical regulators of a plethora of signaling pathways. Recent progress in high-throughput sequencing has enabled a better understanding of the physiological and pathophysiological functions of circRNAs, overcoming the obstacle of the sequence overlap between circRNAs and their linear cognate mRNAs. Some viruses also encode circRNAs implicated in viral replication or disease progression. There is increasing evidence that viral infections dysregulate circRNA expression and that the altered expression of circRNAs is critical in regulating viral infection and replication. circRNAs were shown to regulate gene expression via microRNA and protein sponging or via encoding small polypeptides. Recent studies have also highlighted the potential role of circRNAs as promising diagnostic and prognostic biomarkers, RNA vaccines and antiviral therapy candidates due to their higher stability and lower immunogenicity. This review presents an up-to-date summary of the mechanistic involvement of circRNAs in innate immunity against viral infections, the current understanding of their regulatory roles, and the suggested applications.

DCServCG: A data-centric service code generation using deep learning

Modern software development paradigms, including Service-Oriented Architecture (SOA), tend to make use of available services e.g., web service Application Programming Interfaces (APIs) to generate new software. Thus, for the further advancement of SOA, the development of accurate automatic tasks, such as service discovery and composition, is necessary. Most of these automated tasks rely heavily on web service metadata annotation. The lack of machine-readable documentation and structured metadata reduces the accuracy and volume of automatic data annotation, negatively affecting the performance of automated SOA tasks. This study aims to propose automatic code completion for improving web service-based systems by identifying and capturing service usage collected from public repositories that share Open Source Software (OSS). To this end, a Data-Centric Service Code Generation (DCServCG) model is proposed to improve old-fashioned, general-purpose code generators that neglect essential service-based code characteristics e.g., sequence overlap and bias issues. DCServCG takes advantage of the data-centric concept, i.e., conditional text generation, to overcome the mentioned issues. We have evaluated the approach from the point of view of language modeling metrics. The obtained results indicate that the usage of the data-centric approach reduces perplexity by 1.125. Moreover, the DCServCG model uses de-noising and conditional text generation, which is trained on the transformer by distilling the knowledge, DistilGPT2 (82M parameters) trained faster and its perplexity is 0.363 lower than ServCG (124M parameters) without de-noising and conditional text generation, which lower perplexity value indicates better model generalization performance.

Spatial-temporal analysis of coal fire risk identification and suppression assessment with satellite time series mapping 2013-2020 in Midong coalfield, Xinjiang, China

ABSTRACT Spontaneous combustion of underground coal seam leads to significant loss of coal resource while causing serious geological disasters, environmental degradation and social security problems. The Midong Coalfield in Urumqi was selected to conduct research on dynamic detection and assessment of underground coal fires from 2013 to 2020 based on time series satellite imagery of Landsat-8. The land surface temperature (LST) was retrieved using RTE. The hotspot SFSE was proposed to map the spatial-temporal distribution of coal fires. The CTIR was also established to solve how to comprehensively evaluate the intensity and spatial variations of coal fire thermal island effect. Based on Sequence Overlap Analysis the integrated dynamic interpretation of thermal anomaly intensity, area and migration of coal fire hazard has been provided. In addition, the TADC was proposed to effectively reflect the active fire centre and aggregation tendency. The results show that: The RTE inversion error is within 4.6 °C, verified with the surveyed LST. The overall accuracy of fire thermal anomaly extraction by HSA by field-tested exceeds 65%. A feature can be judged to be a fire pixel when its recurrence reaches 75% or more of the total number of observation frequency. The maximum and minimum extent extracted of the total fire area is 65.6×105 and 46.6×105 m2, respectively. And the overall expansion rate is 1.29×105 m2 year−1, in 82% agreement with the measurement. The burning intensity of CTIR first increases 0.024 year−1 averagely, but then decreases at a rate of 0.0055 year−1. Fractures and faults in the fire-affected area play a critical role in fire induction and distribution. Frequent mining and excavation activities are confirmed to accelerate the further fire production and propagation. After suppression, the relevant fire area has shrunken by up to 60%, while the overall CTIR is reduced by more than 70%.

Spike-specific T cells are enriched in breastmilk following SARS-CoV-2 mRNA vaccination

Human breastmilk is rich in T cells; however, their specificity and function are largely unknown. We compared the phenotype, diversity, and antigen specificity of T cells in breastmilk and peripheral blood of lactating individuals who received SARS-CoV-2 messenger RNA (mRNA) vaccination. Relative to blood, breastmilk contained higher frequencies of T effector and central memory populations that expressed mucosal-homing markers. T cell receptor sequence overlap was limited between blood and breastmilk. Overabundant breastmilk clones were observed in all individuals, were diverse, and contained complementarity-determining regions in three sequences with known epitope specificity, including to SARS-CoV-2 spike. SARS-CoV-2 spike-specific T cell receptors were more frequent in breastmilk compared to blood and expanded in breastmilk following a 3rd mRNA vaccine dose. Our observations indicate that the lactating breast contains a distinct T cell population that can be modulated by maternal vaccination with potential implications for passive infant protection.

First Report of Muskmelon Fruit Rot Caused by Fusarium nanum in China.

Muskmelon(Cucumis meloL.) is one of the most widely cultivated and economically important fruit crops in the world.However, many pathogens can cause decay ofmuskmelon fruit, including Fusarium asiaticum, F. equiseti, F. incarnatum and F. lateritium (Hao et al. 2021; Wang et al. 2019). Fusarium spp. are the most important pathogens affecting muskmelon fruit yield and quality (Wang et al. 2011). In August 2020, fruitrot symptoms were observed on ripening muskmelons (cv. Tianbao) in several fields in Jiyang District, Jinan City of Shandong Province, China. The incidences of infected muskmelon ranged from 15% to 30% and caused an average 20% yield loss. Symptoms appeared as pale brown, water-soaked lesions that were irregular in shape, with the lesion sizes ranging from a small spot (1 to 2 cm) to decay of the entire fruit. The core and surface of infected fruit were colonized and covered with white mycelia. Two infected muskmelons were collected from two fields, 7 km apart. Tissues removed from inside the infected fruit were surface disinfected with 75% ethanol for 30 s, and cultured on potato dextrose agar (PDA) at 25°C in the dark for 5 days. Four purified cultures were obtained using the single spore method.On carnation leaf agar (CLA), macroconidia were 1 to 5 septate, falcate, with a pronounced dorsiventral curvature with blunt to papillate apical cell, and barely to distinctly notched basal cell, measuring 12 to 35 × 3.5 to 6 μm. Microconidia and chlamydospores were not observed. These morphological characteristics were consistent with the description of Fusarium sp. Because these isolates had similar morphology, two representative isolates (XP9 and XP10) were selected for multilocus phylogenetic analyses. DNA was extracted from the representative isolates using a CTAB method. Nucleotide sequences of the internal transcribed spacers (ITS) (White et al. 1990), calmodulin (CAM), RNA polymerase II second largest subunit (RPB2), translation elongation factor 1-α gene (TEF1) (Xia et al. 2019) were amplified using specific primers, sequenced, and deposited in GenBank (ITS: MW391507 and MW391508, CAM: MW392787 and MW392788, RPB2: MW392795 and MW392796, TEF1: MW392791 and MW392792). The Fusarium MLST database pairwise alignment of ITS (546 bp), CAM (628 bp), RPB2 (902 bp) and TEF1 (718 bp) sequences from isolate XP9 showed 99.63%, 99.33%, 100.00% and 99.71% similarity with the corresponding sequences (GQ505685, GQ505508, GQ505774 and GQ505596) of the reference strain of F. nanum (NRRL 22244), respectively. The overlap of ITS, CAM, RPB2 and TEF1 sequences from XP9 and NRRL 22244 were 100.00%, 95.06%, 97.45% and 94.99%, respectively. Alignments of a combined dataset of ITS, CAM, RPB2 and TEF1 were made using MAFFT v. 7, and phylogenetic analyses were conducted in MEGA v. 7.0 using the maximum likelihood method. The muskmelon isolates (XP9 and XP10) clustered together with theF. nanum reference strain CGMCC3.19498 and NRRL 22244 (100% bootstrap) (Wang et al., 2019). To perform a pathogenicity test, 10 μl of conidial suspensions (1 × 106 conidia/ml) were injected into each muskmelon fruit using a syringe, and the control fruit was inoculated with 10 μl of sterile distilled water. There were ten replicated fruits for each treatment. The test was repeated three times. After 7 days at 25°C, the interior of the inoculated muskmelons begun to rot, and the rot lesion expanded from the core towards the surface of the fruit, then white mycelia were produced on the surface. Ten isolations were re-isolated from the infected tissues and identified by morphological and phylogenetic analyses and confirmed to fulfill Koch's postulates. No symptoms were observed on the control muskmelons. To our knowledge, this is the first report of muskmelon fruit rot caused by F. nanum in China. Considering the economic value of the muskmelon crop, correct identification can help farmers select appropriate field management measures for control of this disease.

SimAIRR: simulation of adaptive immune repertoires with realistic receptor sequence sharing for benchmarking of immune state prediction methods.

Machine learning (ML) has gained significant attention for classifying immune states in adaptive immune receptor repertoires (AIRRs) to support the advancement of immunodiagnostics and therapeutics. Simulated data are crucial for the rigorous benchmarking of AIRR-ML methods. Existing approaches to generating synthetic benchmarking datasets result in the generation of naive repertoires missing the key feature of many shared receptor sequences (selected for common antigens) found in antigen-experienced repertoires. We demonstrate that a common approach to generating simulated AIRR benchmark datasets can introduce biases, which may be exploited for undesired shortcut learning by certain ML methods. To mitigate undesirable access to true signals in simulated AIRR datasets, we devised a simulation strategy (simAIRR) that constructs antigen-experienced-like repertoires with a realistic overlap of receptor sequences. simAIRR can be used for constructing AIRR-level benchmarks based on a range of assumptions (or experimental data sources) for what constitutes receptor-level immune signals. This includes the possibility of making or not making any prior assumptions regarding the similarity or commonality of immune state-associated sequences that will be used as true signals. We demonstrate the real-world realism of our proposed simulation approach by showing that basic ML strategies perform similarly on simAIRR-generated and real-world experimental AIRR datasets. This study sheds light on the potential shortcut learning opportunities for ML methods that can arise with the state-of-the-art way of simulating AIRR datasets. simAIRR is available as a Python package: https://github.com/KanduriC/simAIRR.

Assessment of AlphaFold2 for Human Proteins via Residue Solvent Exposure.

As only 35% of human proteins feature (often partial) PDB structures, the protein structure prediction tool AlphaFold2 (AF2) could have massive impact on human biology and medicine fields, making independent benchmarks of interest. We studied AF2's ability to describe the backbone solvent exposure as a functionally important and easily interpretable "natural coordinate" of protein conformation, using human proteins as test case. After screening for appropriate comparative sets, we matched 1818 human proteins predicted by AF2 against 7585 unique experimental PDBs, and after curation for sequence overlap, we assessed 1264 comparative pairs comprising 115 unique AF2 structures and 652 unique experimental structures. AF2 performed markedly worse for multimers, whereas ligands, cofactors, and experimental resolution were interestingly not very important for performance. AF2 performed excellently for monomer proteins. Challenges relating to specific groups of residues and multimers were analyzed. We identified larger deviations for lower-confidence scores (pLDDT), and exposed residues and polar residues (e.g., Asp, Glu, Asn) being less accurately described than hydrophobic residues. Proline conformations were the hardest to predict, probably due to a common location in dynamic solvent-accessible parts. In summary, using solvent exposure as a metric, we quantified the performance of AF2 for human proteins and provided estimates of the expected agreement as a function of ligand presence, multimer/monomer status, local residue solvent exposure, pLDDT, and amino acid type. Overall performance was found to be excellent.

Comprehensive analysis of TCR repertoire of COVID-19 patients in different infected stage.

BackgroundThe current pandemic of coronavirus disease 2019 (COVID-19), transmitted person-to-person by the severe acute respiratory syndrome of coronavirus 2 (SARS-CoV-2), poses a threat to global public health.ObjectiveIn this study, we performed the comprehensive analysis of the T cell receptor (TCR) repertoire may contribute to a more in-depth understanding of the pathogenesis of COVID-19.MethodsA comprehensive immunological analysis was performed to explore the features of the TCR repertoire and identified TCR sequences correlated with SARS-CoV-2 viral antigens.Resultswe analyzed the COVID-19 patients’ TCR repertoires in peripheral blood mononuclear cells (PBMC) which obtained before (baseline), during (acute), and after rehabilitation (convalescent) by ImmunoSEQ-technology, and found that repertoire features of TCRβ-chain (TCRβ) complementary-determining region 3 (CDR3) in COVID-19 patients were remarkable difference, including decreased TCR diversity, abnormal CDR3 length, difference of TRBV/J gene usage and higher TCR sequence overlap. Besides, we identified some COVID-19 disease-associated TCRβ clones, and the abundance of them changed with the progression of the disease. Importantly, these disease-associated TCRβ clones could be used to distinguish COVID-19 patients from healthy controls with high accuracy.ConclusionsWe provide a clear understanding of the TCR repertoire of COVID-19 patients, which lays the foundation for better diagnosis and treatment of COVID-19 patients.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13258-022-01261-w.

DRUMMER-rapid detection of RNA modifications through comparative nanopore sequencing.

MotivationThe chemical modification of ribonucleotides regulates the structure, stability and interactions of RNAs. Profiling of these modifications using short-read (Illumina) sequencing techniques provides high sensitivity but low-to-medium resolution i.e. modifications cannot be assigned to specific transcript isoforms in regions of sequence overlap. An alternative strategy uses current fluctuations in nanopore-based long read direct RNA sequencing (DRS) to infer the location and identity of nucleotides that differ between two experimental conditions. While highly sensitive, these signal-level analyses require high-quality transcriptome annotations and thus are best suited to the study of model organisms. By contrast, the detection of RNA modifications in microbial organisms which typically have no or low-quality annotations requires an alternative strategy. Here, we demonstrate that signal fluctuations directly influence error rates during base-calling and thus provides an alternative approach for identifying modified nucleotides.ResultsDRUMMER (Detection of Ribonucleic acid Modifications Manifested in Error Rates) (i) utilizes a range of statistical tests and background noise correction to identify modified nucleotides with high confidence, (ii) operates with similar sensitivity to signal-level analysis approaches and (iii) correlates very well with orthogonal approaches. Using well-characterized DRS datasets supported by independent meRIP-Seq and miCLIP-Seq datasets we demonstrate that DRUMMER operates with high sensitivity and specificity.Availability and implementationDRUMMER is written in Python 3 and is available as open source in the GitHub repository: https://github.com/DepledgeLab/DRUMMER.Supplementary information Supplementary data are available at Bioinformatics online.

CiLiQuant: Quantification of RNA Junction Reads Based on Their Circular or Linear Transcript Origin.

Distinguishing circular RNA reads from reads derived from the linear host transcript is a challenging task because of sequence overlap. We developed a computational approach, CiLiQuant, that determines the relative circular and linear abundance of transcripts and gene loci using back-splice and unambiguous forward-splice junction reads generated by existing mapping and circular RNA discovery tools.

In Silico Characterisation of Putative Prophages in Lactobacillaceae Used in Probiotics for Vaginal Health.

While live biotherapeutics offer a promising approach to optimizing vaginal microbiota, the presence of functional prophages within introduced Lactobacillaceae strains could impact their safety and efficacy. We evaluated the presence of prophages in 895 publicly available Lactobacillaceae genomes using Phaster, Phigaro, Phispy, Prophet and Virsorter. Prophages were identified according to stringent (detected by ≥4 methods) or lenient criteria (detected by ≥2 methods), both with >80% reciprocal sequence overlap. The stringent approach identified 448 prophages within 359 genomes, with 40.1% genomes harbouring at least one prophage, while the lenient approach identified 1671 prophages within 83.7% of the genomes. To confirm our in silico estimates in vitro, we tested for inducible prophages in 57 vaginally-derived and commercial Lactobacillaceae isolates and found inducible prophages in 61.4% of the isolates. We characterised the in silico predicted prophages based on weighted gene repertoire relatedness and found that most belonged to the Siphoviridae or Myoviridae families. ResFam and eggNOG identified four potential antimicrobial resistance genes within the predicted prophages. Our results suggest that while Lactobacillaceae prophages seldomly carry clinically concerning genes and thus unlikely a pose a direct risk to human vaginal microbiomes, their high prevalence warrants the characterisation of Lactobacillaceae prophages in live biotherapeutics.