Identification Of Sequences Research Articles

Superior Resolution Profiling of the Coleofasciculus Microbiome by Amplicon Sequencing of the Complete 16S rRNA Gene and ITS Region.

The filamentous cyanobacterium Coleofasciculus chthonoplastes is the key primary producer of marine microbial mats. We elucidated the microbiomes of 32 non-axenic Coleofasciculus isolates using PacBio-based amplicon sequencing of the complete 16S rRNA gene and the internally transcribed spacer (16S-ITS). The length of authentic amplicon sequence variants (ASVs) ranged from 1827 to 3044 nucleotides (median: 2267 nt). The results, which were complemented by metagenome analyses and cultivation approaches, revealed the presence of more than 70 associated heterotrophs in the culture of Coleofasciculus sp. WW12. The great bacterial diversity in the cyanosphere is dominated by Pseudomonadota (59%) and Bacteroidota (23%). Allelic ribosomal operon variants were detected in 18 Coleofasciculus strains and our analyses proposed the presence of at least four different species. A comparative analysis of cyanobacterial microbiomes documented complementary advantages of amplicon sequencing versus metagenomics with an individual strength of the 16S-ITS approach in terms of (i) ribosomal target sequence quality, (ii) contaminant detection and (iii) identification of rare bacteria. The characterisation of the Coleofasciculus microbiome showed that long-read amplicon sequencing of the 16S-ITS region is the method of choice for rapid profiling of non-axenic cyanobacteria. Its superior resolution allows a reliable differentiation of even very closely related strains.

Identification of the shortest species-specific oligonucleotide sequences.

Despite the exponential increase in sequencing information driven by massively parallel DNA sequencing technologies, universal and succinct genomic fingerprints for each organism are still missing. Identifying the shortest species-specific nucleotide sequences offers insights into species evolution and holds potential practical applications in agriculture, wildlife conservation, and healthcare. We propose a new method for sequence analysis termed nucleic "quasi-primes," the shortest occurring sequences in each of 45,076 organismal reference genomes, present in one genome and absent from every other examined genome. In the human genome, we find that the genomic loci of nucleic quasi-primes are most enriched for genes associated with brain development and cognitive function. In a single-cell case study focusing on the human primary motor cortex, nucleic quasi-prime genes account for a significantly larger proportion of the variation based on average gene expression. Nonneuronal cell types, including astrocytes, endothelial cells, microglia perivascular-macrophages, oligodendrocytes, and vascular and leptomeningeal cells, exhibit significant activation of quasi-prime-containing gene associations related to cancer, whereas simultaneously suppressing quasi-prime-containing genes are associated with cognitive, mental, and developmental disorders. We also show that human disease-causing variants, eQTLs, mQTLs, and sQTLs are 4.43-fold, 4.34-fold, 4.29-fold, and 4.21-fold enriched at human quasi-prime loci, respectively. These findings indicate that nucleic quasi-primes are genomic loci linked to the evolution of species-specific traits, and in humans, they provide insights in the development of cognitive traits and human diseases, including neurodevelopmental disorders.

P-2120. Clinical significance of 16S rRNA sequencing identification of Legionella species

Abstract Background Incorporation of 16S rRNA sequencing into clinical diagnostics has improved the ability of clinicians to diagnose fastidious bacteria and facilitates the identification of causative organisms in culture-negative infections. However, its clinical utility is unclear, with estimates of antimicrobial management changes from 16S identification ranging from only 4-15%. Legionella species are fastidious bacteria that can be difficult to identify without prior clinical suspicion, and thus can cause culture-negative infections that lead to 16S sequencing. However, Legionella are found ubiquitously in aquatic environments and its identification on 16S could represent a clinically significant infection, a nonpathogenic sample isolate, or a contaminant from sample processing or analysis. In this study, we reviewed 16S Legionella species results from our institution and determined whether they represented a clinical infection. Methods 16S results from our institution were queried for Legionella species and a retrospective analysis of the resulting 10 cases was conducted. Multiple factors from the cases were assessed including demographics, comorbidities, type of 16S specimen, and antibiotic regimen change in response to 16S results. Additionally, we identified whether the 16S results represented clinically significant infections or contaminants. Results 70% of the Legionella identifications were indicative of a clinically relevant infection. Specimens from a pulmonary source were much more likely to represent a true infection, while identifications from extrapulmonary sources were more likely to be a contaminant. The species of Legionella identified on 16S did not impact the likelihood of a true causative agent. The 16S results affected antimicrobial regiments in 60% of the cases and were often the only diagnostic test to point towards Legionella as a causative agent. Conclusion Legionella species identification on 16S can be an important diagnostic clue to the etiology of a patient's infection, but various clinical factors should be taken into account when assessing whether the result represents a true infection or contaminant. Disclosures All Authors: No reported disclosures

Egyptian Novel Goose Parvovirus in Immune Organs of Naturally Infected Ducks: Next-Generation Sequencing, Immunohistochemical Signals, and Comparative Analysis of Pathological Changes Using Multiple Correspondence and Hierarchical Clustering Approach.

The present study aims to better understand the nature of currently circulating GPV strains and their pathological impact on the immune system during natural outbreaks among different duck breeds in Egypt. For this purpose, 99 ducks (25 flocks) of different breeds, aged 14-75 days, were clinically examined, and 75 tissue pools from the thymus, bursa of Fabricius, and spleen were submitted for virus detection and identification. Clinical and postmortem findings were suggestive of GPV infection. Concerning the immune system organs, atrophy in the thymus (60.6%), bursa (45.5%), and spleen (38.3%) was the most common gross lesion. Microscopically, the pathological impact of the virus was exhibited by a necrotic thymic cortex with Hassall's corpuscle disintegration, the disappearance of normal bursal histological morphology accompanied by atrophied follicles and lymphocytic depletion, and apoptosis of B-lymphocytes in lymphoid follicles of the spleen. Furthermore, immunohistochemical examination revealed positive signals of the parvovirus detected in thymic lymphocytes in the cortex, bursa-dependent lymphoid follicle of the medulla, and diffuse positive expression of viral antigens in the spleen. GPV was detected in ducks using polymerase chain reaction, with the highest percentage of positive detection in the bursa of Fabricius (76%). Next-generation sequencing and phylogenetic analysis revealed that the detected virus was a variant of GPV, globally named novel GPV (NGPV), and closely related to Chinese NGPV isolates. To our knowledge, the current study is pioneering to address the immunopathological impact of NGPV among naturally infected ducks confirmed with full genome sequencing and immunohistochemical identification worldwide.

Development of avian influenza A(H5) virus datasets for Nextclade enables rapid and accurate clade assignment.

The ongoing panzootic of highly pathogenic avian influenza (HPAI) A(H5) viruses is the largest in history, with unprecedented transmission to multiple mammalian species. Avian influenza A viruses of the H5 subtype circulate globally among birds and are classified into distinct clades based on their hemagglutinin (HA) genetic sequences. Thus, the ability to accurately and rapidly assign clades to newly sequenced isolates is key to surveillance and outbreak response. Co-circulation of endemic, low pathogenic avian influenza (LPAI) A(H5) lineages in North American and European wild birds necessitates the ability to rapidly and accurately distinguish between infections arising from these lineages and epizootic HPAI A(H5) viruses. However, currently available clade assignment tools are limited and often require command line expertise, hindering their utility for public health surveillance labs. To address this gap, we have developed datasets to enable A(H5) clade assignments with Nextclade, a drag-and-drop tool originally developed for SARS-CoV-2 genetic clade classification. Using annotated reference datasets for all historical A(H5) clades, clade 2.3.2.1 descendants, and clade 2.3.4.4 descendants provided by the Food and Agriculture Organization/World Health Organization/World Organisation for Animal Health (FAO/WHO/WOAH) H5 Working Group, we identified clade-defining mutations for every established clade to enable tree-based clade assignment. We then created three Nextclade datasets which can be used to assign clades to A(H5) HA sequences and call mutations relative to reference strains through a drag-and-drop interface. Nextclade assignments were benchmarked with 19,834 unique sequences not in the reference set using a pre-released version of LABEL, a well-validated and widely used command line software. Prospective assignment of new sequences with Nextclade and LABEL produced very well-matched assignments (match rates of 97.8% and 99.1% for the 2.3.2.1 and 2.3.4.4 datasets, respectively). The all-clades dataset also performed well (94.8% match rate) and correctly distinguished between all HPAI and LPAI strains. This tool additionally allows for the identification of polybasic cleavage site sequences and potential N-linked glycosylation sites. These datasets therefore provide an alternative, rapid method to accurately assign clades to new A(H5) HA sequences, with the benefit of an easy-to-use browser interface.

Identification of Gallbladder-Specific Distal Regulatory Sequence of Murine Sox17.

Sox17 is a key transcriptional regulator of endoderm formation and function in the gallbladder, blood vessels and reproductive organs. Although multiple transcript variants of Sox17 have been suggested, the precise mechanisms underlying their time- and tissue-specific expression remain unclear. In this study, we discovered two putative regulatory sequences (R1 and R2) adjacent to different transcription start sites of mouse Sox17 exon 1 and generated deletion mice for these regions (Sox17Δdr/Δdr). Sox17Δdr/Δdr mice were alive and fertile, and they possessed a normal-sized gallbladder. However, semiquantitative analysis of immunostaining showed that the expression levels of SOX17 in Sox17Δdr/Δdr embryos were reduced to less than 50% of the wild-type in the gallbladder epithelium. Furthermore, the bile ductal epithelium marker SOX9 was abnormally upregulated, and PAS/DBA-positive mucin secretion-like epithelial cells were induced in the Sox17Δdr/Δdr gallbladder. Our results demonstrate that the distal sequence of Sox17, including R1 and R2, is important for the regulation of Sox17 gene expression in the embryonic gallbladder and is crucial for normal gallbladder epithelial development.

A ML Framework for Genetic Sequence Identification using 2D Electrical Conductance Probability Distributions from Mixed Data Sets

A ML Framework for Genetic Sequence Identification using 2D Electrical Conductance Probability Distributions from Mixed Data Sets

Molecular detection of Enterobacter hormaechei in bovine respiratory disease.

Bovine respiratory disease (BRD) develops from complex interactions among environmental, host and pathogenic factors. This study aimed to phenotypically identify Enterobacter hormaechei isolated from cattle with BRD and assess antimicrobial susceptibility and determining the molecular phylogeny of local E. hormaechei strains. Between November 2023 and March 2024, nasal swabs were collected from 93 cattle with BRD, before culturing for phenotypic analysis, and performing the polymerase chain reaction (PCR) for molecular characterisation. Of the 93 samples evaluated, 15.79% and 24.56% tested positive for E. hormaechei isolates on culture and PCR, respectively. The local isolates exhibited high resistance to amoxicillin, ampicillin, amikacin, nalidixic acid and ceftazidime; high susceptibility to azithromycin, levofloxacin, gentamicin, ofloxacin, cefepime, ceftriaxone, cefotaxime, nitrofurantoin, ceftazidime and ciprofloxacin; and moderate susceptibility to ciprofloxacin, colistin, imipenem and meropenem. Multiple sequence alignment, phylogenetic tree analysis and homology sequence identification, showed that the five positive isolates were similar to the reference isolate. To the best of our knowledge, this is the first time that E. hormaechei has been isolated in cattle with BRD in Iraq. Because phenotype-based assays show limited accuracy to identify species, we recommend molecular and phylogenetic analysis be included in all similar studies in the future.

Identification of novel tick-associated RNA virus sequences from questing ticks collected in Ishikawa and Ehime Prefectures, Japan

Identification of novel tick-associated RNA virus sequences from questing ticks collected in Ishikawa and Ehime Prefectures, Japan

A genomic signal processing approach for identification and classification of coronavirus sequences

A genomic signal processing approach for identification and classification of coronavirus sequences

Identification, characterization, and design of plant genome sequences using deep learning.

Due to its excellent performance in processing large amounts of data and capturing complex non-linear relationships, deep learning has been widely applied in many fields of plant biology. Here we first review the application of deep learning in analyzing genome sequences to predict gene expression, chromatin interactions, and epigenetic features (open chromatin, transcription factor binding sites, and methylation sites) in plants. Then, current motif mining and functional component design and synthesis based on generative adversarial networks, large models, and attention mechanisms are elaborated in detail. The progress of protein structure and function prediction, genomic prediction, and large model applications based on deep learning is also discussed. Finally, this work provides prospects for the future development of deep learning in plants with regard to multiple omics data, algorithm optimization, large language models, sequence design, and intelligent breeding.

A gut commensal protozoan determines respiratory disease outcomes by shaping pulmonary immunity.

The underlying mechanisms used by the intestinal microbiota to shape disease outcomes of the host are poorly understood. Here, we show that the gut commensal protozoan, Tritrichomonas musculis (T.mu), remotely shapes the lung immune landscape to facilitate perivascular shielding of the airways by eosinophils. Lung-specific eosinophilia requires a tripartite immune network between gut-derived inflammatory group 2 innate lymphoid cells and lung-resident Tcells and B cells. This network exacerbates the severity of allergic airway inflammation while hindering the systemic dissemination of pulmonary Mycobacterium tuberculosis. The identification of protozoan DNA sequences in the sputum of patients with severe allergic asthma further emphasizes the relevance of commensal protozoa in human disease. Collectively, these findings demonstrate that a commensal protozoan tunes pulmonary immunity via a gut-operated lung immune network, promoting both beneficial and detrimental disease outcomes in response to environmental airway allergens and pulmonary infections.

Investigating the Phylogenetic Relationships of the Iranian Honey Bee with Other Bee Breeds Worldwide Using the Cytochrome Oxidase I Region

Background: Honey bees, classified within the insect class and widely distributed globally, consist of 26 identified subspecies across five evolutionary lines. Among these, the Iranian honey bee (Apis mellifera meda) is notable for its presence in Iran and neighboring regions. This subspecies exhibits unique biological traits, including a high reproductive capacity and effective propolis collection, distinguishing it from other local bee populations. Understanding genetic diversity within these populations is crucial for conservation and breeding efforts. Objectives: The aim of this study is to determine the phylogenetic relationships and natural variations of the Iranian honey bee in comparison to other bee breeds worldwide using the cytochrome oxidase I (COI) region. Methods: The study focuses on the identification of COI gene sequences in honeybees. The mitochondrial COI gene sequences related to the Iranian honey bee and eight populations of other honey bee breeds from around the world (24 ecotypes) were extracted and aligned from the genome database (NCBI). BLAST was used for sequence retrieval, and Clustal W was employed for alignment among species. Phylogenetic analysis was performed using MEGA software, applying the Neighbor Joining method to construct a phylogenetic tree based on the edited sequences. The percentage of nucleotide substitutions and replacements was calculated using the maximum likelihood method. Additionally, molecular diversity indices were computed using DnaSP software to assess genetic variation and conservation parameters among populations. Results: The bioinformatics analysis of biological data revealed that transfer substitution occurred more frequently than crossover substitution. Additionally, the percentage of substitution in pyrimidine bases was higher than in purine bases. The dN/dS substitution ratio in the gene locus sequence across the examined ecotypes was estimated at 0.08, indicating purifying selection during the evolution of this gene locus. Furthermore, examination of the COI region of the mitochondrial genome identified a total of 4 haplotypes, 20 mutations, and 195 polymorphic loci within the entire studied population. The neutrality values, based on Tajima's test, indicated effects related to genetic drift, genetic bottlenecks, or balancing selection during the evolutionary history of the studied population. Phylogenetic analysis revealed nine distinct categories of evolutionary paths for the COI gene in the studied ecotypes. In the phylogenetic tree, the Iranian honey bee was placed in a separate cluster, exhibiting the highest and lowest phylogenetic distances relative to Apis koschevnikovi and Apis mellifera, respectively. Conclusions: This research indicates that the conserved region of the mitochondrial cytochrome oxidase gene among various bee species is minimal, highlighting significant polymorphism and susceptibility to mutations. A total of 20 mutations and 195 polymorphic sites were identified, suggesting purifying selection processes that contribute to the gene's biological functions. The study also demonstrates that the COI region can effectively differentiate Iranian honey bee populations from others globally. Overall, these findings enhance our understanding of genetic diversity and evolutionary relationships within bee species, underscoring the importance of continued research for conservation efforts.

Polysaccharide sulfotransferases: the identification of putative sequences and respective functional characterisation.

The vast structural diversity of sulfated polysaccharides demands an equally diverse array of enzymes known as polysaccharide sulfotransferases (PSTs). PSTs are present across all kingdoms of life, including algae, fungi and archaea, and their sulfation pathways are relatively unexplored. Sulfated polysaccharides possess anti-inflammatory, anticoagulant and anti-cancer properties and have great therapeutic potential. Current identification of PSTs using Pfam has been predominantly focused on the identification of glycosaminoglycan (GAG) sulfotransferases because of their pivotal roles in cell communication, extracellular matrix formation and coagulation. As a result, our knowledge of non-GAG PSTs structure and function remains limited. The major sulfotransferase families, Sulfotransfer_1 and Sulfotransfer_2, display broad homology and should enable the capture of a wide assortment of sulfotransferases but are limited in non-GAG PST sequence annotation. In addition, sequence annotation is further restricted by the paucity of biochemical analyses of PSTs. There are now high-throughput and robust assays for sulfotransferases such as colorimetric PAPS (3'-phosphoadenosine 5'-phosphosulfate) coupled assays, Europium-based fluorescent probes for ratiometric PAP (3'-phosphoadenosine-5'-phosphate) detection, and NMR methods for activity and product analysis. These techniques provide real-time and direct measurements to enhance the functional annotation and subsequent analysis of sulfated polysaccharides across the tree of life to improve putative PST identification and characterisation of function. Improved annotation and biochemical analysis of PST sequences will enhance the utility of PSTs across biomedical and biotechnological sectors.

Regulatory role of exosomal proteins MIF and PEBP1 in sperm storage in black rockfish (Sebastes schlegelii) ovary

Sperm entry into the female reproductive tract triggers the production of exosomes that play a vital role in regulating sperm storage, release, and viability. Exosomal proteins are considered to be key factors influencing these processes. In this study, we focused on macrophage migration inhibitory factor (MIF) and phosphatidylethanolamine-binding protein 1 (PEBP1) to investigate their amino acid sequence identification, expression patterns, and functional roles in post-mating ovarian tissues of black rockfish (Sebastes schlegelii). Phylogenetic analysis revealed that MIF and PEBP1 cluster separately across species, with distinct groupings for fish and mammals, underscoring their evolutionary conservation and essential biological roles. We observed significant upregulation of mif and pebp1 gene expression during various stages of post-mating sperm storage, which was reflected in corresponding increases in protein levels. Exosomes were successfully isolated from the ovarian fluid of black rockfish, with particle sizes ranging from 40 to 220 nm, and exhibiting typical exosomal morphological characteristics. More importantly, the presence of MIF and PEBP1 was confirmed in these exosomes. Both proteins were localized in ovarian follicular and epithelial cells. Functional analysis revealed that recombinant Sebastes schlegelii MIF (rSsMIF) and PEBP1 (rSsPEBP1) were capable of transferring into sperm after incubation, suggesting their binding interaction. Both proteins effectively preserved sperm integrity, including intact heads and undamaged flagella. After 24 h of incubation with rSsMIF and rSsPEBP1, sperm viability was maintained at 88 % and 85 %, respectively, compared to only 58 % in the control group. Additionally, sperm motility was also significantly improved following treatment with both proteins, with the proportion of motile sperm increasing by 14 % and 20 %, respectively. Moreover, the present study found that the regulation of sperm viability and motility by two types of exosomal proteins may accompanied by intracellular reactive oxygen species (ROS) and calcium ions. The levels of ROS in sperm decreased to varying extents after incubation with the two proteins, whereas intracellular calcium ion concentrations increased. These findings provide new insights into the roles of MIF and PEBP1 in sperm storage and fertility, suggesting potential applications in reproductive biotechnology.

Identification of responsible sequences which mutations cause maternal H19-ICR hypermethylation with Beckwith–Wiedemann syndrome-like overgrowth

Beckwith-Wiedemann syndrome (BWS) is caused by a gain of methylation (GOM) at the imprinting control region within the Igf2-H19 domain on the maternal allele (H19-ICR GOM). Mutations in the binding sites of several transcription factors are involved in H19-ICR GOM and BWS. However, the responsible sequence(s) for H19-ICR GOM with BWS-like overgrowth has not been identified in mice. Here, we report that a mutation in the SOX-OCT binding site (SOBS) causes partial H19-ICR GOM, which does not extend beyond CTCF binding site 3 (CTS3). Moreover, simultaneously mutating both SOBS and CTS3 causes complete GOM of the entire H19-ICR, leading to the misexpression of the imprinted genes, and frequent BWS-like overgrowth. In addition, CTS3 is critical for CTCF/cohesin-mediated chromatin conformation. These results indicate that SOBS and CTS3 are the sequences in which mutations cause H19-ICR GOM leading to BWS-like overgrowth and are essential for maintaining the unmethylated state of maternal H19-ICR.

Structure and identification of the native PLP synthase complex from Methanosarcina acetivorans lysate.

Many protein-protein interactions behave differently in biochemically purified forms as compared to their in vivo states. As such, determining native protein structures may elucidate structural states previously unknown for even well-characterized proteins. Here, we apply the bottom-up structural proteomics method, cryoID, toward a model methanogenic archaeon. While they are keystone organisms in the global carbon cycle and active members of the human microbiome, there is a general lack of characterization of methanogen enzyme structure and function. Through the cryoID approach, we successfully reconstructed and identified the native Methanosarcina acetivorans pyridoxal 5'-phosphate (PLP) synthase (PdxS) complex directly from cryogenic electron microscopy (cryo-EM) images of fractionated cellular lysate. We found that the native PdxS complex exists as a homo-dodecamer of PdxS subunits, and the previously proposed supracomplex containing both the synthase (PdxS) and glutaminase (PdxT) was not observed in cellular lysate. Our structure shows that the native PdxS monomer fashions a single 8α/8β TIM-barrel domain, surrounded by seven additional helices to mediate solvent and interface contacts. A density is present at the active site in the cryo-EM map and is interpreted as ribose 5-phosphate. In addition to being the first reconstruction of the PdxS enzyme from a heterogeneous cellular sample, our results reveal a departure from previously published archaeal PdxS crystal structures, lacking the 37-amino-acid insertion present in these prior cases. This study demonstrates the potential of applying the cryoID workflow to capture native structural states at atomic resolution for archaeal systems, for which traditional biochemical sample preparation is nontrivial.IMPORTANCEArchaea are one of the three domains of life, classified as a phylogenetically distinct lineage. There is a paucity of known enzyme structures from organisms of this domain, and this is often exacerbated by characteristically difficult growth conditions and a lack of readily available molecular biology toolkits to study proteins in archaeal cells. As a result, there is a gap in knowledge concerning the mechanisms governing archaeal protein behavior and their impacts on both the environment and human health; case in point, the synthesis of the widely utilized cofactor pyridoxal 5'-phosphate (PLP; a vitamer of vitamin B6, which humans cannot produce). By leveraging the power of single-particle cryo-EM and map-to-primary sequence identification, we determine the native structure of PLP synthase from cellular lysate. Our workflow allows the (i) rapid examination of new or less characterized systems with minimal sample requirements and (ii) discovery of structural states inaccessible by recombinant expression.

High-Throughput Discovery of Substrate Peptide Sequences for E3 Ubiquitin Ligases Using a cDNA Display Method.

Cells utilize ubiquitin as a posttranslational protein modifier to convey various signals such as proteasomal degradation. The dysfunction of ubiquitylation or following proteasomal degradation can give rise to the accumulation and aggregation of improperly ubiquitylated proteins, which is known to be a general causation of many neurodegenerative diseases. Thus, the characterization of substrate peptide sequences of E3 ligases is crucial in biological and pharmaceutical sciences. In this study, we developed a novel high-throughput screening system for substrate peptide sequences of E3 ligases using a cDNA display method, which enables covalent conjugation between peptide sequences and their corresponding cDNA sequences. First, we focused on the MDM2 E3 ligase and its known peptide substrate as a model to establish the screening method, and confirmed that cDNA display method was compatible with in vitro ubiquitylation. Then, we demonstrated identification of MDM2 substrate sequences from random libraries to identify a novel motif (VKFTGGQLA). Bioinformatics analysis of the hit sequences was performed to gain insight about endogenous substrate proteins.

A protein fitness predictive framework based on feature combination and intelligent searching.

Machine learning (ML) constructs predictive models by understanding the relationship between protein sequences and their functions, enabling efficient identification of protein sequences with high fitness values without falling into local optima, like directional evolution. However, how to extract the most pertinent functional feature information from a limited number of protein sequences is vital for optimizing the performance of ML models. Here, we propose scut_ProFP (Protein Fitness Predictor), a predictive framework that integrates feature combination and feature selection techniques. Feature combination offers comprehensive sequence information, while feature selection searches for the most beneficial features to enhance model performance, enabling accurate sequence-to-function mapping. Compared to similar frameworks, scut_ProFP demonstrates superior performance and is also competitive with more complex deep learning models-ECNet, EVmutation, and UniRep. In addition, scut_ProFP enables generalization from low-order mutants to high-order mutants. Finally, we utilized scut_ProFP to simulate the engineering of the fluorescent protein CreiLOV and highly enriched mutants with high fluorescence based on only a small number of low-fluorescence mutants. Essentially, the developed method is advantageous for ML in protein engineering, providing an effective approach to data-driven protein engineering. The code and datasets for scut_ProFP are available at https://github.com/Zhang66-star/scut_ProFP.

A mapping-free natural language processing-based technique for sequence search in nanopore long-reads

BackgroundIn unforeseen situations, such as nuclear power plant’s or civilian radiation accidents, there is a need for effective and computationally inexpensive methods to determine the expression level of a selected gene panel, allowing for rough dose estimates in thousands of donors. The new generation in-situ mapper, fast and of low energy consumption, working at the level of single nanopore output, is in demand. We aim to create a sequence identification tool that utilizes natural language processing techniques and ensures a high level of negative predictive value (NPV) compared to the classical approach.ResultsThe training dataset consisted of RNA sequencing data from 6 samples. Multiple natural language processing models were examined, differing in the type of dictionary components (word length, step, context) as well as the encoding length and number of sequences required for algorithm training. The best configuration analyses the entire sequence and uses a word length of 3 base pairs with one-word neighbor on each side. For the considered FDXR gene, the achieved mean balanced accuracy (BACC) was 98.29% and NPV was 99.25%, compared to minimap2’s performance in a cross-validation scenario. The next stage focused on exploring the dictionary components and attempting to optimize it, employing statistical techniques as well as those relying on the explainability of the decisions made. Reducing the dictionary from 1024 to 145 changed BACC to 96.49% and the NPV to 98.15%. Obtained model, validated on an external independent genome sequencing dataset, gave NPV of 99.64% for complete and 95.87% for reduced dictionary. The salmon-estimated read counts differed from the classical approach on average by 3.48% for the complete dictionary and by 5.82% for the reduced one.ConclusionsWe conclude that for long Oxford nanopore reads, a natural language processing-based approach can reliably replace classical mapping when there is a need for fast, reliable and energy and computationally efficient targeted mapping of a pre-defined subset of transcripts. The developed model can be easily retrained to identify selected transcripts and/or work with various long-read sequencing techniques. Our results of the study clearly demonstrate the potential of applying techniques known from classical text processing to nucleotide sequences.