Sequence Annotation Research Articles

Research on Medical Text Parsing Method Based on BiGRU-BiLSTM Multi-Task Learning

With the development of technology, the popularity of online medical treatment is becoming more and more widespread. However, the accuracy and credibility of online medical treatment are affected by model design and semantic understanding. In particular, there are still some problems in the accurate understanding of complex structured texts, which affects the accuracy of judging users’ intentions and needs. Therefore, this paper proposes a new method for medical text parsing, which realizes core tasks such as named entity recognition, intention recognition, and slot filling through a multi-task learning framework; uses BERT to obtain contextual semantic information; and combines BiGRU and BiLSTM neural networks, and uses CRF to realize sequence annotation and DPCNN to realize classification prediction. Thus, the task of entity recognition and intention recognition can be accomplished. On this basis, this paper builds a multi-task learning model based on BiGRU-BiLSTM, and uses CBLUE and CMID databases to verify the method. The verification results show that the accuracy of named entity recognition and intention recognition reaches 86% and 89%, respectively, which improves the performance of various tasks. The ability of the model to process complex text is enhanced. This method can improve the text generalization ability and improve the accuracy of online medical intelligent dialogue when it is used to analyze medical texts.

How Trustworthy Are the Genomic Sequences of SARS-CoV-2 in GenBank?

Well-annotated gene and genomic sequences serve as a foundation for making inferences in molecular biology and evolution and can directly impact public health. The first SARS-CoV-2 genome was submitted to the GenBank database hosted by the U.S. National Center for Biotechnology Information and used to develop the two successful vaccines. Conserved protein domains are often chosen as targets for developing antiviral medicines or vaccines. Mutation and substitution patterns provide crucial information not only on functional motifs and genome/protein interactions but also for characterizing phylogenetic relationships among viral strains. These patterns, together with the collection time of viral samples, serve as the basis for addressing the question of when and where the host-switching event occurred. Unfortunately, viral genomic sequences submitted to GenBank undergo little quality control, and critical information in the annotation is frequently changed without being recorded. Researchers often have no choice but to hold blind faith in the authenticity of the sequences. There have been reports of incorrect genome annotation but no report that casts doubt on the genomic sequences themselves because it seems theoretically impossible to identify genomic sequences that may not be authentic. This paper takes an innovative approach to show that some SARS-CoV-2 genomes submitted to GenBank cannot possibly be authentic. Specifically, some SARS-CoV-2 genomic sequences deposited in GenBank with collection times in 2023 and 2024, isolated from saliva, nasopharyngeal, sewage, and stool, are identical to the reference genome of SARS-CoV-2 (NC_045512). The probability of such occurrence is effectively 0. I also compile SARS-CoV-2 genomes with changed sample collection times. One may be led astray in bioinformatic analysis without being aware of errors in sequences and sequence annotation.

BakRep - a searchable large-scale web repository for bacterial genomes, characterizations and metadata.

Bacteria are fascinating research objects in many disciplines for countless reasons, and whole-genome sequencing (WGS) has become the paramount methodology to advance our microbiological understanding. Meanwhile, access to cost-effective sequencing platforms has accelerated bacterial WGS to unprecedented levels, introducing new challenges in terms of data accessibility, computational demands, heterogeneity of analysis workflows and, thus, ultimately its scientific usability. To this end, a previous study released a uniformly processed set of 661 405 bacterial genome assemblies obtained from the European Nucleotide Archive as of November 2018. Building on these accomplishments, we conducted further genome-based analyses like taxonomic classification, multilocus sequence typing and annotation of all genomes. Here, we present BakRep, a searchable large-scale web repository of these genomes enriched with consistent genome characterizations and original metadata. The platform provides a flexible search engine combining taxonomic, genomic and metadata information, as well as interactive elements to visualize genomic features. Furthermore, all results can be downloaded for offline analyses via an accompanying command line tool. The web repository is accessible via https://bakrep.computational.bio.

Maternal consumption of yoghurt activating the aryl hydrocarbon receptor increases group 3 innate lymphoid cells in murine offspring

ABSTRACT Indole derivatives are microbial metabolites of the tryptophan pathway involved in gut immune homeostasis. They bind to the aryl hydrocarbon receptor (AhR), thereby modulating development of intestinal group 3 innate lymphoid cells (ILC3) and subsequent interleukin-22 production. In mice, indole derivatives of the maternal microbiota can reach the milk and drive early postnatal ILC3 development. Apart from the gut microbiota, lactic acid bacteria (LAB) also produce indole compounds during milk fermentation. Using germ-free mice, the aim of our study was to test if maternal intake of a dairy product enriched in AhR-activating indoles produced by fermentation could boost maturation of the intestinal innate immune system in the offspring. A set of 631 LAB strains were genetically screened for their potential to produce indole compounds. Among these, 125 strains were tested in combination with standard strains to produce yoghurts that were screened for their ability to activate AhR in vitro using the HepG2–AhR–Luc cell line. The most active yoghurt and a control yoghurt were formulated as pellets and fed to germ-free dams during pregnancy and lactation. Analysis of the offspring on postnatal day 14 using flow cytometry revealed an increase in the frequency of small intestinal lamina propria NKp46 +ILC3 s in the pups born to dams that had consumed the purified diet containing an AhR-active yoghurt (AhrY-diet) compared to control yoghurt (ConY-diet). Selection of LABs based on their ability to produce a fermented dairy able to activate AhR appears to be an effective approach to produce a yoghurt with immunomodulatory properties. IMPORTANCE Key progresses in the sequencing and functional annotation of microbial organisms have revolutionized research in the fields of human metabolism and food biotechnology. In particular, the gut microbiome is now recognized as an important mediator of the impact of nutrition on human metabolism. Annotated genomes of a large number of bacteria are now available worldwide, which selectively transform food through fermentation to produce specific bioactive compounds with the potential to modulate human health. A previous research has demonstrated that the maternal microbiota shapes the neonatal immune system. Similarly, this report shows that lactic acid bacteria can be selected to produce fermented food that can also modulate postnatal intestinal immunity.

Anti-quorum sensing and anti-biofilm activities of Pasteurella multocida strains

A total of 52 Pasteurella multocida strains of capsular serogroups (A, B and D) were screened for anti-quorum sensing activity against Chromobacterium violaceum. Of which, 12 strains of serogroups A were found to possess anti-quorum sensing activity. Inhibition activity was highest for strain NIVEDIPm9 and lowest for strain NIVEDIPm30 based on zone of pigment inhibition. Further, cell free extract of NIVEDIPm9 strain showed highest anti-biofilm activity in reference E. coli strain and concentration dependent degradation activity of C6-AHL molecule. In whole genome sequence annotation of NIVEDIPm9 strain predicted the presence of four metallo-β-lactamases (MBL) fold metallo-hydrolase proteins. In docking studies, MBL1 and MBL3 proteins showed high binding affinity with autoinduce signalling molecules AHL compound of OH-C10, binding energy value were −6.3 and −6.2 kcal/mol. Interaction study of VAF and quorum sensing molecules showed that OmpA and HgbA proteins were stimulated by all the ten molecules (C4-AHLs, C6-AHLs, C10-AHLs, C14-AHLs, 3-oxo-C10-AHLs, 3OH-C10-HSL, C8-HSL, C10-HSL, C12-HSL, C14-HSL), while toxA gene was stimulated by OH-C10-AHL molecule, sodC gene was stimulated by none. In conclusion, we described the anti-quorum sensing activities of diverse P. multocida strains causing Pasteurellosis in livestock.

Alternative transcripts recode human genes to express overlapping, frameshifted microproteins.

Overlapping genes were thought to be essentially absent from the human genome until the discovery of abundant, frameshifted internal open reading frames (iORFs) nested within annotated protein coding sequences. However, it is currently unclear how many functional human iORFs exist and how they are expressed. We demonstrate that, in hundreds of cases, alternative transcript variants that bypass the start codon of annotated coding sequences (CDSs) can recode a human gene to express the iORF-encoded microprotein. While many human genes generate such non- coding alternative transcripts, they are poorly annotated. Here we develope a new analysis pipeline enabling the assignment of translated human iORFs to alternative transcripts, and provide long- read sequencing and molecular validation of their expression in dozens of cases. Finally, we demonstrate that a conserved DEDD2 iORF switches the function of this gene from pro- to anti- apoptotic. This work thus demonstrates that alternative transcript variants can broadly reprogram human genes to express frameshifted iORFs, revealing new levels of complexity in the human transcriptome and proteome.

Improving viral annotation with artificial intelligence.

Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community structure and function. Additionally, their dependence on hosts for replication positions phages as unique sensors of ecosystem features and environmental pressures. High-throughput sequencing approaches have begun to give us access to the diversity and range of phage populations in complex microbial community samples, and metagenomics is currently the primary tool with which we study phage populations. The study of phages by metagenomic sequencing, however, is fundamentally limited by viral diversity, which results in the vast majority of viral genomes and metagenome-annotated genomes lacking annotation. To harness bacteriophages for applications in human and environmental health and disease, we need new methods to organize and annotate viral sequence diversity. We recently demonstrated that methods that leverage self-supervised representation learning can supplement statistical sequence representations for remote viral protein homology detection in the ocean virome and propose that consideration of the functional content of viral sequences allows for the identification of similarity in otherwise sequence-diverse viruses and viral-like elements for biological discovery. In this review, we describe the potential and pitfalls of large language models for viral annotation. We describe the need for new approaches to annotate viral sequences in metagenomes, the fundamentals of what protein language models are and how one can use them for sequence annotation, the strengths and weaknesses of these models, and future directions toward developing better models for viral annotation more broadly.

Regulatory genome annotation of 33 insect species

Annotation of newly sequenced genomes frequently includes genes, but rarely covers important non-coding genomic features such as the cis-regulatory modules—e.g., enhancers and silencers—that regulate gene expression. Here, we begin to remedy this situation by developing a workflow for rapid initial annotation of insect regulatory sequences, and provide a searchable database resource with enhancer predictions for 33 genomes. Using our previously developed SCRMshaw computational enhancer prediction method, we predict over 2.8 million regulatory sequences along with the tissues where they are expected to be active, in a set of insect species ranging over 360 million years of evolution. Extensive analysis and validation of the data provides several lines of evidence suggesting that we achieve a high true-positive rate for enhancer prediction. One, we show that our predictions target specific loci, rather than random genomic locations. Two, we predict enhancers in orthologous loci across a diverged set of species to a significantly higher degree than random expectation would allow. Three, we demonstrate that our predictions are highly enriched for regions of accessible chromatin. Four, we achieve a validation rate in excess of 70% using in vivo reporter gene assays. As we continue to annotate both new tissues and new species, our regulatory annotation resource will provide a rich source of data for the research community and will have utility for both small-scale (single gene, single species) and large-scale (many genes, many species) studies of gene regulation. In particular, the ability to search for functionally related regulatory elements in orthologous loci should greatly facilitate studies of enhancer evolution even among distantly related species.

Regulatory genome annotation of 33 insect species.

Annotation of newly sequenced genomes frequently includes genes, but rarely covers important non-coding genomic features such as the cis-regulatory modules-e.g., enhancers and silencers-that regulate gene expression. Here, we begin to remedy this situation by developing a workflow for rapid initial annotation of insect regulatory sequences, and provide a searchable database resource with enhancer predictions for 33 genomes. Using our previously developed SCRMshaw computational enhancer prediction method, we predict over 2.8 million regulatory sequences along with the tissues where they are expected to be active, in a set of insect species ranging over 360 million years of evolution. Extensive analysis and validation of the data provides several lines of evidence suggesting that we achieve a high true-positive rate for enhancer prediction. One, we show that our predictions target specific loci, rather than random genomic locations. Two, we predict enhancers in orthologous loci across a diverged set of species to a significantly higher degree than random expectation would allow. Three, we demonstrate that our predictions are highly enriched for regions of accessible chromatin. Four, we achieve a validation rate in excess of 70% using in vivo reporter gene assays. As we continue to annotate both new tissues and new species, our regulatory annotation resource will provide a rich source of data for the research community and will have utility for both small-scale (single gene, single species) and large-scale (many genes, many species) studies of gene regulation. In particular, the ability to search for functionally related regulatory elements in orthologous loci should greatly facilitate studies of enhancer evolution even among distantly related species.

Integrated Transcriptomics and Metabolomics Studies Reveal Steroid Biosynthesis Pathway and BCL2 Inhibitory Diazo-Progesterone of Drimia indica for Conservation and Sustainable Utilization.

This study is the first report on the sequence of the transcriptome of Drimia indica, a non-model plant with medicinal properties found in a forest tribal belt, using the Illumina NovaSeq platform. The primary objectives of this study were to elucidate the gene expression profiles in different tissues, identify key regulatory genes and pathways involved in secondary metabolite biosynthesis, and explore the plant's potential pharmacological properties. The study generated 670087 unigenes from both leaves and roots and identified putative homologs of annotated sequences against UniProt/Swiss-Prot and KEGG databases. The functional annotation of the identified unigenes revealed the secondary metabolite biosynthetic process as the most prominent pathway, with gene enrichment analysis predominantly accounting for secondary metabolite pathways, such as terpenoid, steroid, flavonoid, alkaloid, selenocompound, and cortisol synthesis. The study also identified regulatory genes NAC, Bhlh, WRKY, and C2H2 on the transcriptome dataset. The functionally annotated unigenes suggested phytocompounds in Drimia indica to have multi-potent properties, such as anti-cancer, anti-inflammatory, and anti-diabetic activities, which has been further validated by GC-MS-based metabolite profiling. Notably, we have identified two novel molecules, di-azo progesterone and 4H-pyran-4-one 2,3-dihydro-3,5-dihydroxy- 6-methyl, with potential BCL2 inhibitory anticancer properties, supported by stable binding interactions observed in molecular docking and dynamics simulations. Additionally, an abundance of mono-nucleotide SSR markers has been identified, useful for genetic diversity studies. This study provides a foundational understanding of the molecular mechanisms in Drimia indica, highlighting its potential as a source for novel therapeutic agents and contributing valuable insights for future pharmacological and agricultural applications. However, further in vivo studies are warranted to confirm these findings and validate their pharmacological efficacy and therapeutic potential. The SSR markers identified also offer valuable tools for molecular genetics, plant breeding, and sustainable drug development.

Chromosome-level genome assembly of American sweetgum (Liquidambar styraciflua, Altingiaceae)

The deciduous American sweetgum (Liquidambar styraciflua, Altingiaceae) is a popular ornamental and economically valuable tree renowned for its sweet-smelling bark resin, abundant volatile substances, and spectacular fall leaf color. However, the absence of a reference genome hinders thorough investigations into the mechanisms underlying phenotypic variation, secondary metabolite synthesis and adaptation, both in this species and other Liquidambar members. In this study, we sequenced and constructed a chromosome-level assembly of the L. styraciflua genome, covering 662.48 Mb with a scaffold N50 of 39.54 Mb, by integrating PacBio, Illumina and chromosome conformation capture data. We identified 58.83% of the genome sequences as repetitive elements and 25,713 protein-coding genes, 97.28% of which were functionally annotated. The genome sequencing reads, assembly and annotation data have been deposited in publicly available repositories. This high-quality genome assembly provides valuable resources for further evolutionary and functional genomic studies in American sweetgum and other Liquidambar species.

Influenza sequence validation and annotation using VADR

Abstract Tens of thousands of influenza sequences are deposited into the GenBank database each year. The software tool FLu ANnotation tool (FLAN) has been used by GenBank since 2007 to validate and annotate incoming influenza sequence submissions and has been publicly available as a webserver but not as a standalone tool. Viral Annotation DefineR (VADR) is a general sequence validation and annotation software package used by GenBank for norovirus, dengue virus and SARS-CoV-2 virus sequence processing that is available as a standalone tool. We have created VADR influenza models based on the FLAN reference sequences and adapted VADR to accurately annotate influenza sequences. VADR and FLAN show consistent results on the vast majority of influenza sequences, and when they disagree, VADR is usually correct. VADR can also accurately process influenza D sequences as well as influenza A H17, H18, H19, N10 and N11 subtype sequences, which FLAN cannot. VADR 1.6.3 and the associated influenza models are now freely available for users to download and use. Database URL: https://bitbucket.org/nawrockie/vadr-models-flu.

Genome-Wide Identification and Expression Analysis of MYB Transcription Factor Family in Response to Various Abiotic Stresses in Coconut (Cocos nucifera L.).

Abiotic stresses such as nitrogen deficiency, drought, and salinity significantly impact coconut production, yet the molecular mechanisms underlying coconut's response to these stresses are poorly understood. MYB proteins, a large and diverse family of transcription factors (TF), play crucial roles in plant responses to various abiotic stresses, but their genome-wide characterization and functional roles in coconut have not been comprehensively explored. This study identified 214 CnMYB genes (39 1R-MYB, 171 R2R3-MYB, 2 3R-MYB, and 2 4R-MYB) in the coconut genome. Phylogenetic analysis revealed that these genes are unevenly distributed across the 16 chromosomes, with conserved consensus sequences, motifs, and gene structures within the same subgroups. Synteny analysis indicated that segmental duplication primarily drove CnMYB evolution in coconut, with low nonsynonymous/synonymous ratios suggesting strong purifying selection. The gene ontology (GO) annotation of protein sequences provided insights into the biological functions of the CnMYB gene family. CnMYB47/70/83/119/186 and CnMYB2/45/85/158/195 were identified as homologous genes linked to nitrogen deficiency, drought, and salinity stress through BLAST, highlighting the key role of CnMYB genes in abiotic stress tolerance. Quantitative analysis of PCR showed 10 CnMYB genes in leaves and petioles and found that the expression of CnMYB45/47/70/83/85/119/186 was higher in 3-month-old than one-year-old coconut, whereas CnMYB2/158/195 was higher in one-year-old coconut. Moreover, the expression of CnMYB70, CnMYB2, and CnMYB2/158 was high under nitrogen deficiency, drought, and salinity stress, respectively. The predicted secondary and tertiary structures of three key CnMYB proteins involved in abiotic stress revealed distinct inter-proteomic features. The predicted interaction between CnMYB2/158 and Hsp70 supports its role in coconut's drought and salinity stress responses. These results expand our understanding of the relationships between the evolution and function of MYB genes, and provide valuable insights into the MYB gene family's role in abiotic stress in coconut.

Chromosome-scale genome assembly and annotation of the tetraploid potato cultivar Diacol Capiro adapted to the Andean region.

Potato (Solanum tuberosum) is an essential crop for food security and is ranked as the third most important crop worldwide for human consumption. The Diacol Capiro cultivar holds the dominant position in Colombian cultivation, primarily catering to the food processing industry. This highly heterozygous, autotetraploid cultivar belongs to the Andigenum group and it stands out for its adaptation to a wide variety of environments spanning altitudes from 1,800 to 3,200 meters above sea level. Here, a chromosome-scale assembly, referred to as DC, is presented for this cultivar. The assembly was generated by combining circular consensus sequencing with proximity ligation Hi-C for the scaffolding and represents 2.369 Gb with 48 pseudochromosomes covering 2,091 Gb and an anchor rate of 88.26%. The reference genome metrics, including an N50 of 50.5 Mb, a BUSCO (Benchmarking Universal Single-Copy Orthologue) score of 99.38%, and an Long Terminal Repeat Assembly Index score of 13.53, collectively signal the achieved high assembly quality. A comprehensive annotation yielded a total of 154,114 genes, and the associated BUSCO score of 95.78% for the annotated sequences attests to their completeness. The number of predicted NLR (Nucleotide-Binding and Leucine-Rich-Repeat genes) was 2107 with a large representation of NBARC (for nucleotide binding domain shared by Apaf-1, certain R gene products, and CED-4) containing domains (99.85%). Further comparative analysis of the proposed annotation-based assembly with high-quality known potato genomes, showed a similar genome metrics with differences in total gene numbers related to the ploidy status. The genome assembly and annotation of DC presented in this study represent a valuable asset for comprehending potato genetics. This resource aids in targeted breeding initiatives and contributes to the creation of enhanced, resilient, and more productive potato varieties, particularly beneficial for countries in Latin America.

Real-Time Extraction of News Events Based on BERT Model

Abstract For the large number of news reports generated every day, in order to obtain effective information from these unstructured news text data more efficiently. In this paper, we study the real-time crawling of news data from news websites through crawling techniques and propose a BERT model-based approach to extract events from news long text. In this study, NetEase news website is selected as an example for real-time extraction to crawl the news data of this website. BERT model as a pre-trained model based on two-way encoded representation of transformer performs well on natural language understanding and natural language generation tasks. In this study, we will fine-tune the training based on BERT model on news corpus related dataset and perform sequence annotation through CRF layer to finally complete the event extraction task. In this paper, the DUEE dataset is chosen to train the model, and the experiments show that the overall performance of the BERT model is better than other network models. Finally, the model of this paper is further optimised, using the ALBERT and RoBERTa models improved on the basis of the BERT model, experiments were conducted, the results show that both models are improved compared to the BERT model, the ALBERT model algorithm performs the best, the model algorithm's F1 value is 1% higher than that of BERT. The results show that the performance is optimised.

Whole-genome sequence of Sclerotium delphinii, a pathogenic fungus of Dendrobium officinale southern blight

Dendrobium officinale is a rare and precious medicinal plant. Southern blight is a destructive disease in the artificial cultivation of D. officinale, and one of its pathogens is Sclerotium delphinii. S. delphinii is a phytopathogenic fungus with a wide host range with extremely strong pathogenicity. In this study, S. delphinii was isolated from D. officinale with southern blight. Subsequently, this specific strain underwent thorough whole-genome sequencing using the PacBio Sequel II platform, which employed single-molecule real-time (SMRT) technology. Comprehensive annotations were obtained through functional annotation of protein sequences using various publicly available databases. The genome of S. delphinii measures 73.66 Mb, with an N90 contig size of 2,707,110 bp, and it contains 18,506 putative predictive genes. This study represents the first report on the genome size assembly and annotation of S. delphinii, making it the initial species within the Sclerotium genus to undergo whole-genome sequencing, which can provide solid data and a theoretical basis for further research on the pathogenesis, omics of S. delphinii.

Identification of a Major QTL for Seed Protein Content in Cultivated Peanut (Arachis hypogaea L.) Using QTL-Seq.

Peanut (Arachis hypogaea L.) is a great plant protein source for human diet since it has high protein content in the kernel. Therefore, seed protein content (SPC) is considered a major agronomic and quality trait in peanut breeding. However, few genetic loci underlying SPC have been identified in peanuts, and the underlying regulatory mechanisms remain unknown, limiting the effectiveness of breeding for high-SPC peanut varieties. In this study, a major QTL (qSPCB10.1) controlling peanut SPC was identified within a 2.3 Mb interval in chromosome B10 by QTL-seq using a recombinant inbred line population derived from parental lines with high and low SPCs, respectively. Sequence comparison, transcriptomic analysis, and annotation analysis of the qSPCB10.1 locus were performed. Six differentially expressed genes with sequence variations between two parents were identified as candidate genes underlying qSPCB10.1. Further locus interaction analysis revealed that qSPCB10.1 could not affect the seed oil accumulation unless qOCA08.1XH13 was present, a high seed oil content (SOC) allele for a major QTL underlying SOC. In summary, our study provides a basis for future investigation of the genetic basis of seed protein accumulation and facilitates marker-assisted selection for developing high-SPC peanut genotypes.

Exploring Levansucrase Operon Regulating Levan-Type Fructooligosaccharides (L-FOSs) Production in Priestia koreensis HL12.

Levan biopolymer and levan-type fructooligosaccharides (L-FOSs) are β-2,6-linked fructans that have been used as non-digestible dietary fiber and prebiotic oligosaccharides in food and cosmeceutical applications. In this study, we explore the operon responsible for levan and L-FOSs production in Priestia koreensis HL12. Presented is the first genomic perspective on sucrose utilization and the levan biosynthesis pathway in this bacterium. Regarding sequence annotation, the putative levansucrase operon responsible for β-2,6-linked fructan was identified in the genome of strain HL12, and comprises sacB levansucrase gene belonging to GH68, located adjacent to levB endo-levanase gene, which belongs to GH32. Importantly, sugars related with the levan biosynthesis pathway are proposed to be transported via 3 types of transportation systems, including multiple ABCSugar and glucose/H+ transporters, as well as glucose- and fructose-specific PTS systems. Based on product profile analysis, the HL12 strain exhibited high efficiency in levan production from high sucrose concentration (300 g/l), achieving the highest yield of 127 g/l (equivalent to 55% conversion based on sucrose consumption), together with short-chain L-FOSs (DP3-5) and long-chain L-FOSs with respective size larger than DP6 after 48 h incubation. These findings highlight the potential of P. koreensis HL12 as a whole-cell biocatalyst for producing levan and L-FOSs, and underscore its novelty in converting sugars into high-value-added products for diverse commercial and industrial applications.

Adaptive Evolution Signatures in Prochlorococcus: Open Reading Frame (ORF)eome Resources and Insights from Comparative Genomics.

Prochlorococcus, a cyanobacteria genus of the smallest and most abundant oceanic phototrophs, encompasses ecotype strains adapted to high-light (HL) and low-light (LL) niches. To elucidate the adaptive evolution of this genus, we analyzed 40 Prochlorococcus marinus ORFeomes, including two cornerstone strains, MED4 and NATL1A. Employing deep learning with robust statistical methods, we detected new protein family distributions in the strains and identified key genes differentiating the HL and LL strains. The HL strains harbor genes (ABC-2 transporters) related to stress resistance, such as DNA repair and RNA processing, while the LL strains exhibit unique chlorophyll adaptations (ion transport proteins, HEAT repeats). Additionally, we report the finding of variable, depth-dependent endogenous viral elements in the 40 strains. To generate biological resources to experimentally study the HL and LL adaptations, we constructed the ORFeomes of two representative strains, MED4 and NATL1A synthetically, covering 99% of the annotated protein-coding sequences of the two species, totaling 3976 cloned, sequence-verified open reading frames (ORFs). These comparative genomic analyses, paired with MED4 and NATL1A ORFeomes, will facilitate future genotype-to-phenotype mappings and the systems biology exploration of Prochlorococcus ecology.

The compositional and functional imbalance of the gut microbiota in CKD linked to disease patterns

BackgroundThe prevalence of chronic kidney disease (CKD) is on the rise, posing a significant public health challenge. Although gut microbiome dysbiosis has been implicated in the impairment of kidney functions, the existence of pathological subtypes-linked differences remains largely unknown. We aimed to characterize the intestinal microbiota in patients with membranous nephropathy (MN), IgA nephropathy (IgAN), minimal change disease (MCD), and ischemic renal injury (IRI) in order to investigate the intricate relationship between intestinal microbiota and CKD across different subtypes.MethodsWe conducted a cross-sectional study involving 94 patients with various pathological patterns of CKD and 54 healthy controls (HCs). The clinical parameters were collected, and stool samples were obtained from each participant. Gut microbial features were analyzed using 16S rRNA sequencing and taxon annotation to compare the HC, CKD, MN, IgAN, MCD, and IRI groups.ResultsThe CKD subjects exhibited significantly reduced alpha diversity, modified community structures, and disrupted microbial composition and potential functions compared to the control group. The opportunistic pathogen Klebsiella exhibited a significant enrichment in patients with CKD, whereas Akkermansia showed higher abundance in HCs. The study further revealed the presence of heterogeneity in intestinal microbial signatures across diverse CKD pathological types, including MN, IgAN, MCD, and IRI. The depression of the family Lachnospiraceae and the genus Bilophila was prominently observed exclusively in patients with MN, while suppressed Streptococcus was detected only in individuals with MCD, and a remarkable expansion of the genus Escherichia was uniquely found in cases of IRI. The study also encompassed the development of classifiers employing gut microbial diagnostic markers to accurately discriminate between distinct subtypes of CKD.ConclusionsThe dysregulation of gut microbiome was strongly correlated with CKD, exhibiting further specificity towards distinct pathological patterns. Our study emphasizes the significance of considering disease subtypes when assessing the impact of intestinal microbiota on the development, diagnosis, and treatment of CKD.