Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation

Identification of a novel monocyclic carotenoid and prediction of its biosynthetic genes in Algoriphagus sp. oki45

Bacteria belonging to the genus Algoriphagus have been isolated from various sources, such as Antarctic sea ice, seawater, and sediment, and some strains are known to produce orange to red pigments. However, the pigment composition and biosynthetic genes have not been fully elucidated. A new red-pigmented Algoriphagus sp. strain, oki45, was isolated from the surface of seaweed collected from Senaga-Jima Island, Okinawa, Japan. Genome comparison revealed oki45's average nucleotide identity of less than 95% to its closely related species, Algoriphagus confluentis NBRC 111222 T and Algoriphagus taiwanensis JCM 19755 T. Comprehensive chemical analyses of oki45's pigments, including 1H and 13C nuclear magnetic resonance and circular dichroism spectroscopy, revealed that the pigments were mixtures of monocyclic carotenoids, (3S)-flexixanthin ((3S)-3,1'-dihydroxy-3',4'-didehydro-1',2'-dihydro-β,ψ-caroten-4-one) and (2R,3S)-2-hydroxyflexixanthin ((2R,3S)-2,3,1'-trihydroxy-3',4'-didehydro-1',2'-dihydro-β,ψ-caroten-4-one); in particular, the latter compound was new and not previously reported. Both monocyclic carotenoids were also found in A. confluentis NBRC 111222 T and A. taiwanensis JCM 19755 T. Further genome comparisons of carotenoid biosynthetic genes revealed the presence of eight genes (crtE, crtB, crtI, cruF, crtD, crtYcd, crtW, and crtZ) for flexixanthin biosynthesis. In addition, a crtG homolog gene encoding 2,2'-β-hydroxylase was found in the genome of the strains oki45, A. confluentis NBRC 111222 T, and A. taiwanensis JCM 19755 T, suggesting that the gene is involved in 2-hydroxyflexixanthin synthesis via 2-hydroxylation of flexixanthin. These findings expand our knowledge of monocyclic carotenoid biosynthesis in Algoriphagus bacteria. KEY POINTS: • Algoriphagus sp. strain oki45 was isolated from seaweed collected in Okinawa, Japan. • A novel monocyclic carotenoid 2-hydroxyflexixanthin was identified from strain oki45. • Nine genes for 2-hydroxyflexixanthin biosynthesis were found in strain oki45 genome.

A comparative assessment of reference genes in mouse brown adipocyte differentiation and thermogenesis in vitro

Adipogenic differentiation and thermogenesis in brown adipose tissue (BAT) undergo dynamic processes, altering phenotypes and gene expressions. Proper reference genes in gene expression analysis are crucial to mitigate experimental variances and ensure PCR efficacy. Unreliable reference genes can lead to erroneous gene expression quantification, resulting in data misinterpretation. This study focused on identifying suitable reference genes for mouse brown adipocyte research, utilizing brown adipocytes from the Ucp1-luciferase ThermoMouse model. Comparative analysis of gene expression data under adipogenesis and thermogenesis conditions was conducted, validating 13 housekeeping genes through various algorithms, including DeltaCq, BestKeeper, geNorm, Normfinder, and RefFinder. Tbp and Rer1 emerged as optimal references for Ucp1 and Pparg expression in brown adipogenesis, while Tbp and Ubc were ideal for the expression analysis of these target genes in thermogenesis. Conversely, certain conventional references, including Actb, Tubb5, and Gapdh, proved unstable as reference genes under both conditions. These findings stress the critical consideration of reference gene selection in gene expression analysis within specific biological systems to ensure accurate conclusions.

kmerDB: A database encompassing the set of genomic and proteomic sequence information for each species

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

GeTeSEPdb: A comprehensive database and online tool for the identification and analysis of gene profiles with temporal-specific expression patterns

Gene expression is dynamic and varies at different stages of processes. The identification of gene profiles with temporal-specific expression patterns can provide valuable insights into ongoing biological processes, such as the cell cycle, cell development, circadian rhythms, or responses to external stimuli such as drug treatments or viral infections. However, currently, no database defines, identifies or archives gene profiles with temporal-specific expression patterns. Here, using a high-throughput regression analysis approach, eight linear and nonlinear parametric models were fitted to gene expression profiles from time-series experiments to identify eight types of gene profiles with temporal-specific expression patterns. We curated 2684 time-series transcriptome datasets and identified 2644,370 gene profiles exhibiting temporal-specific expression patterns. The results were stored in the database GeTeSEPdb (gene profiles with temporal-specific expression patterns database, http://www.inbirg.com/GeTeSEPdb/). Moreover, we implemented an online tool to identify gene profiles with temporal-specific expression patterns from user-submitted data. In summary, GeTeSEPdb is a comprehensive web service that can be used to identify and analyse gene profiles with temporal-specific expression patterns. This approach facilitates the exploration of transcriptional changes and temporal patterns of responses. We firmly believe that GeTeSEPdb will become a valuable resource for biologists and bioinformaticians.

Latent Dirichlet allocation mixture models for nucleotide sequence analysis

Strings of nucleotides carrying biological information are typically described as sequence motifs represented by weight matrices or consensus sequences. However, many signals in DNA or RNA are recognized by multiple factors in temporal sequence, consist of distinct alternative motifs, or are best described by base composition. Here we apply the latent Dirichlet allocation (LDA) mixture model to nucleotide sequences. Using positions in an alignment of human or Drosophila splice sites as samples, we show that LDA readily identifies motifs, including such elusive cases as the intron branch site. Using whole sequences with positional k-mers as features, LDA can identify sequence subtypes enriched in long vs. short introns. LDA with bulk k-mers can reliably distinguish reading frame and species of origin in coding sequences from humans and Drosophila. We find that LDA is a useful model for describing heterogeneous signals, for assigning individual sequences to subtypes, and for identifying and characterizing sequences that do not fit recognized subtypes. Because LDA topic models are interpretable, they also aid the discovery of new motifs, even those present in a small fraction of samples. In summary, LDA can identify and characterize signals in nucleotide sequences, including candidate regulatory factors involved in biological processes.

An exploratory study investigating the impact of the bladder tumor microbiome on Bacillus Calmette Guerin (BCG) response in non-muscle invasive bladder cancer

PURPOSE

Intravesical Bacillus Calmette-Guerin (BCG) is standard of care for intermediate- and high-risk non-muscle invasive bladder cancer (NMIBC). The effect of the bladder microbiome on response to BCG is unclear. We sought to characterize the microbiome of bladder tumors in BCG-responders and non-responders and identify potential mechanisms that drive treatment response.

MATERIALS AND METHODS

Patients with archival pre-treatment biopsy samples (2012-2018) were identified retrospectively. Prospectively, urine and fresh tumor samples were collected from individuals with high-risk NMIBC (2020-2023). BCG response was defined as tumor-free 2 years from induction therapy. Extracted DNA was sequenced for 16S rRNA and shotgun metagenomics. Primary outcomes were species richness (α-diversity) and microbial composition (β-diversity). Paired t-tests were performed for α-diversity (Observed species/Margalef). Statistical analysis for β-diversity (weighted and unweighted UniFrac distances, weighted Bray-Curtis dissimilarity) were conducted through Permanova, with 999 permutations.

RESULTS

Microbial species richness (P < 0.001) and composition (P = 0.001) differed between BCG responders and non-responders. Lactobacillus spp. were significantly enriched in BCG-responders. Shotgun metagenomics identified possible mechanistic pathways such as assimilatory sulfate reduction.

CONCLUSION

A compositional difference exists in the tumor microbiome of BCG responders and non-responders with Lactobacillus having increased abundance in BCG responders.

A pilot study on the detection of microsatellite instability using long mononucleotide repeats in solid tumors

Microsatellite instability (MSI) status is a prognostic biomarker for immunotherapy in certain types of cancers, such as colorectal cancers (CRCs) and endometrial cancers (ECs). Tumors that are categorized as having high MSI (MSI-H) express high levels of neoantigens for immune recognition. The typical MSI test measures the length of short mononucleotide repeats (SMR) poly(A) 21-27; however, a limitation of this test is the difficulty in determining the shift size, particularly in endometrial cancer. To investigate an MSI detection assay with improved performance, the present study analyzed the use of poly(A) 40-44 mononucleotide repeats to detect the MSI status of 100 patients with either CRC (n=50) or EC (n=50). Capillary electrophoresis was used to evaluate five long mononucleotide repeat (LMR) markers, including poly(A) 40-A, 40-B, 40-C, 40-D and 44. The concordance rate of the LMR-MSI assay compared with an immunohistochemistry MSI detection assay was 96.0 and 95.1% for CRCs and ECs respectively, with the detection limit of the LMR-MSI assay demonstrated to be 2.5% MSI-H in HCT116 colorectal carcinoma cell lines. The LMR-MSI assay yielded a 95.1% concordance rate in ECs compared with that in the SMR-MSI test (87.8%). The LMR-MSI test identified a significantly higher mean shift size (13 bp) in MSI-H tumors compared with the SMR-MSI test (10 bp), in both EC and CRC tissue samples. Together, the present study suggested that the LMR-MSI test could potentially be a sensitive and practical technology for molecular laboratory testing, particularly in the use of immunotherapy for patients with CRCs and ECs.

Three-dimensional matrix stiffness modulates mechanosensitive and phenotypic alterations in oral squamous cell carcinoma spheroids

Extracellular biophysical cues such as matrix stiffness are key stimuli tuning cell fate and affecting tumor progression in vivo. However, it remains unclear how cancer spheroids in a 3D microenvironment perceive matrix mechanical stiffness stimuli and translate them into intracellular signals driving progression. Mechanosensitive Piezo1 and TRPV4 ion channels, upregulated in many malignancies, are major transducers of such physical stimuli into biochemical responses. Most mechanotransduction studies probing the reception of changing stiffness cues by cells are, however, still limited to 2D culture systems or cell-extracellular matrix models, which lack the major cell-cell interactions prevalent in 3D cancer tumors. Here, we engineered a 3D spheroid culture environment with varying mechanobiological properties to study the effect of static matrix stiffness stimuli on mechanosensitive and malignant phenotypes in oral squamous cell carcinoma spheroids. We find that spheroid growth is enhanced when cultured in stiff extracellular matrix. We show that the protein expression of mechanoreceptor Piezo1 and stemness marker CD44 is upregulated in stiff matrix. We also report the upregulation of a selection of genes with associations to mechanoreception, ion channel transport, extracellular matrix organization, and tumorigenic phenotypes in stiff matrix spheroids. Together, our results indicate that cancer cells in 3D spheroids utilize mechanosensitive ion channels Piezo1 and TRPV4 as means to sense changes in static extracellular matrix stiffness, and that stiffness drives pro-tumorigenic phenotypes in oral squamous cell carcinoma.

Benchmarking bacterial taxonomic classification using nanopore metagenomics data of several mock communities

Taxonomic classification is crucial in identifying organisms within diverse microbial communities when using metagenomics shotgun sequencing. While second-generation Illumina sequencing still dominates, third-generation nanopore sequencing promises improved classification through longer reads. However, extensive benchmarking studies on nanopore data are lacking. We systematically evaluated performance of bacterial taxonomic classification for metagenomics nanopore sequencing data for several commonly used classifiers, using standardized reference sequence databases, on the largest collection of publicly available data for defined mock communities thus far (nine samples), representing different research domains and application scopes. Our results categorize classifiers into three categories: low precision/high recall; medium precision/medium recall, and high precision/medium recall. Most fall into the first group, although precision can be improved without excessively penalizing recall with suitable abundance filtering. No definitive 'best' classifier emerges, and classifier selection depends on application scope and practical requirements. Although few classifiers designed for long reads exist, they generally exhibit better performance. Our comprehensive benchmarking provides concrete recommendations, supported by publicly available code for reassessment and fine-tuning by other scientists.

Transposition with Tn3-family elements occurs through interaction with the host β-sliding clamp processivity factor

Tn3 family transposons are a widespread group of replicative transposons, notorious for contributing to the dissemination of antibiotic resistance, particularly the global prevalence of carbapenem resistance. The transposase (TnpA) of these elements catalyzes DNA breakage and rejoining reactions required for transposition. However, the molecular mechanism for target site selection with these elements remains unclear. Here, we identify a QLxxLR motif in N-terminal of Tn3 TnpAs and demonstrate that this motif allows interaction between TnpA of Tn3 family transposon Tn1721 and the host β-sliding clamp (DnaN), the major processivity factor of the DNA replication machinery. The TnpA-DnaN interaction is essential for Tn1721 transposition. Our work unveils a mechanism whereby Tn3 family transposons can bias transposition into certain replisomes through an interaction with the host replication machinery. This study further expands the diversity of mobile elements that use interaction with the host replication machinery to bias integration.

qPrimerDB 2.0: an updated comprehensive gene-specific qPCR primer database for 1172 organisms

High-quality primer design is essential for the success of all polymerase chain reaction (PCR)-based experiments. We previously developed a thermodynamics-based gene-specific quantitative PCR (qPCR) primer database for 147 organisms, which has been used extensively in gene expression studies. However, the number of organisms and the imperfection of function in the database limits its potential applications. Here, we improved the functionality of qPrimerDB to create a more comprehensive primer resource. Specifically, we (i) developed an improved primer design tool, qPrimer, building upon the previous qPrimerDB pipeline, to enhance the efficiency and simplicity of genome-scale qPCR primer design; (ii) pre-computed qPCR primer resources from 1 308 genomes of 1172 organisms and (iii) introduced a complete system for identifying, designing, checking, marking, and submitting qPCR primers. qPrimerDB 2.0 is freely available at https://qprimerdb.biodb.org. The qPrimer source code is available at https://github.com/swu1019lab/qPrimer.

Transcriptional and epigenetic characterization of a new in vitro platform to model the formation of human pharyngeal endoderm

BACKGROUND

The Pharyngeal Endoderm (PE) is an extremely relevant developmental tissue, serving as the progenitor for the esophagus, parathyroids, thyroids, lungs, and thymus. While several studies have highlighted the importance of PE cells, a detailed transcriptional and epigenetic characterization of this important developmental stage is still missing, especially in humans, due to technical and ethical constraints pertaining to its early formation.

RESULTS

Here we fill this knowledge gap by developing an in vitro protocol for the derivation of PE-like cells from human Embryonic Stem Cells (hESCs) and by providing an integrated multi-omics characterization. Our PE-like cells robustly express PE markers and are transcriptionally homogenous and similar to in vivo mouse PE cells. In addition, we define their epigenetic landscape and dynamic changes in response to Retinoic Acid by combining ATAC-Seq and ChIP-Seq of histone modifications. The integration of multiple high-throughput datasets leads to the identification of new putative regulatory regions and to the inference of a Retinoic Acid-centered transcription factor network orchestrating the development of PE-like cells.

CONCLUSIONS

By combining hESCs differentiation with computational genomics, our work reveals the epigenetic dynamics that occur during human PE differentiation, providing a solid resource and foundation for research focused on the development of PE derivatives and the modeling of their developmental defects in genetic syndromes.

OrthoPhyl-streamlining large-scale, orthology-based phylogenomic studies of bacteria at broad evolutionary scales

There are a staggering number of publicly available bacterial genome sequences (at writing, 2.0 million assemblies in NCBI's GenBank alone), and the deposition rate continues to increase. This wealth of data begs for phylogenetic analyses to place these sequences within an evolutionary context. A phylogenetic placement not only aids in taxonomic classification but informs the evolution of novel phenotypes, targets of selection, and horizontal gene transfer. Building trees from multi-gene codon alignments is a laborious task that requires bioinformatic expertise, rigorous curation of orthologs, and heavy computation. Compounding the problem is the lack of tools that can streamline these processes for building trees from large-scale genomic data. Here we present OrthoPhyl, which takes bacterial genome assemblies and reconstructs trees from whole genome codon alignments. The analysis pipeline can analyze an arbitrarily large number of input genomes (>1200 tested here) by identifying a diversity-spanning subset of assemblies and using these genomes to build gene models to infer orthologs in the full dataset. To illustrate the versatility of OrthoPhyl, we show three use cases: E. coli/Shigella, Brucella/Ochrobactrum and the order Rickettsiales. We compare trees generated with OrthoPhyl to trees generated with kSNP3 and GToTree along with published trees using alternative methods. We show that OrthoPhyl trees are consistent with other methods while incorporating more data, allowing for greater numbers of input genomes, and more flexibility of analysis.

The reference genome of an endangered Asteraceae, Deinandra increscens subsp. villosa, endemic to the Central Coast of California

We present a reference genome for the federally endangered Gaviota tarplant, Deinandra increscens subsp. villosa (Madiinae, Asteraceae), an annual herb endemic to the Central California coast. Generating PacBio HiFi, Oxford Nanopore Technologies, and Dovetail Omni-C data, we assembled a haploid consensus genome of 1.67 Gb as 28.7 K scaffolds with a scaffold N50 of 74.9 Mb. We annotated repeat content in 74.8% of the genome. Long terminal repeats (LTRs) covered 44.0% of the genome with Copia families predominant at 22.9% followed by Gypsy at 14.2%. Both Gypsy and Copia elements were common in ancestral peaks of LTRs, and the most abundant element was a Gypsy element containing nested Copia/Angela sequence similarity, reflecting a complex evolutionary history of repeat activity. Gene annotation produced 33,257 genes and 68,942 transcripts, of which 99% were functionally annotated. BUSCO scores for the annotated proteins were 96.0% complete of which 77.6% was single copy and 18.4% duplicates. Whole genome duplication synonymous mutation rates of Gaviota tarplant and sunflower (Helianthus annuus) shared peaks that correspond to the last Asteraceae polyploidization event and subsequent divergence from a common ancestor at ∼27 MYA. Regions of high-density tandem genes were identified, pointing to potentially important loci of environmental adaptation in this species.

PM-profiler: a high-resolution and fast tool for taxonomy annotation of amplicon-based microbiome

Amplicon sequencing stands as a cornerstone in microbiome profiling, yet concerns persist regarding its resolution and accuracy. The enhancement of reference databases and annotations marks a new era for 16S rRNA-based profiling. Capitalizing on this potential, we introduce PM-profiler, a novel tool for profiling amplicon short reads. PM-profiler is implemented by C++-based advanced algorithms, such as pre-allocated hash for reference construction, hybrid and dynamic short-read matching, big-data-guided dual-mode hierarchical taxonomy annotation strategy, and full-procedure parallel computing. This tool delivers species-level resolution and ultrafast speed for large-scale microbiomes, surpassing alignment-based approaches and the Naïve-Bayesian model. Furthermore, recognizing the global uneven distribution of microbes, we delineate optimal annotation strategies for each sampling habitat based on microbial patterns over 270,000 microbiomes. Integrated with the established workflow of Parallel-Meta Suite and the latest curated reference databases, this endeavor offers a swift and dependable solution for high-precision microbiome surveys.IMPORTANCEOur study introduces PM-profiler, a new tool that deciphers the complexity of microbial communities. With advanced algorithms, flexible annotation strategies, and well-organized big-data, PM-profiler provides a faster and more accurate way to study on microbiomes, paving the way for discoveries that could improve our understanding of microbiomes and their impact on the world.

Differential Conservation and Loss of Chicken Repeat 1 (CR1) Retrotransposons in Squamates Reveal Lineage-Specific Genome Dynamics Across Reptiles

Transposable elements (TEs) are repetitive DNA sequences which create mutations and generate genetic diversity across the tree of life. In amniote vertebrates, TEs have been mainly studied in mammals and birds, whose genomes generally display low TE diversity. Squamates (Order Squamata; including ∼11,000 extant species of lizards and snakes) show as much variation in TE abundance and activity as they do in species and phenotypes. Despite this high TE activity, squamate genomes are remarkably uniform in size. We hypothesize that novel, lineage-specific genome dynamics have evolved over the course of squamate evolution. To understand the interplay between TEs and host genomes, we analyzed the evolutionary history of the chicken repeat 1 (CR1) retrotransposon, a TE family found in most tetrapod genomes which is the dominant TE in most reptiles. We compared 113 squamate genomes to the genomes of turtles, crocodilians, and birds and used ancestral state reconstruction to identify shifts in the rate of CR1 copy number evolution across reptiles. We analyzed the repeat landscapes of CR1 in squamate genomes and determined that shifts in the rate of CR1 copy number evolution are associated with lineage-specific variation in CR1 activity. We then used phylogenetic reconstruction of CR1 subfamilies across amniotes to reveal both recent and ancient CR1 subclades across the squamate tree of life. The patterns of CR1 evolution in squamates contrast other amniotes, suggesting key differences in how TEs interact with different host genomes and at different points across evolutionary history.

A metagenomics-based approach to decipher the resistome and mobilome of two seahorse species, Hippocampus barbouri and Hippocampus comes

This study aimed to explore the abundance and diversity of antibiotic resistance genes (ARGs) in seahorses (Hippocampus barbouri and Hippocampus comes) and their surrounding environment. The combination of shotgun metagenomics and bioinformatics demonstrated a higher abundance of ARGs in seahorse-associated microbiomes, particularly in skin and gut samples, compared to water and sediment. Interestingly, genes conferring multidrug resistance (e.g., acrB, acrF, cpxA, msbA, and oqxB) were highly prevalent in all samples, especially in skin and gut samples. High levels of genes conferring resistance to fluoroquinolones (e.g., mfd and emrB), β-lactam (e.g., blaCMY-71, blaOXA-55, and penA), aminocoumarin (e.g., mdtB and mdtC), and peptide antibiotics (arnA, pmrE, and rosA) were also observed in skin and gut samples. An enrichment of mobile genetic elements (MGEs) was also observed in the analyzed samples, highlighting their potential role in facilitating the acquisition and spread of ARGs. In fact, the abundance of mobilization (MOB) relaxases (e.g., MOBF, MOBP, MOBT, and MOBV) in gut and skin samples suggests a high potential for conjugation events. The occurrence of ARGs and MGEs in seahorses and the surrounding environment raises concerns about their transmission to humans, either through direct contact or the consumption of contaminated seafood. To the best of our knowledge, this study represents the first comprehensive analysis of ARGs in seahorse-associated microbiomes, and its results emphasize the need for monitoring and controlling the spread of ARGs in environmental settings.

PLEKv2: predicting lncRNAs and mRNAs based on intrinsic sequence features and the coding-net model

BACKGROUND

Long non-coding RNAs (lncRNAs) are RNA transcripts of more than 200 nucleotides that do not encode canonical proteins. Their biological structure is similar to messenger RNAs (mRNAs). To distinguish between lncRNA and mRNA transcripts quickly and accurately, we upgraded the PLEK alignment-free tool to its next version, PLEKv2, and constructed models tailored for both animals and plants.

RESULTS

PLEKv2 can achieve 98.7% prediction accuracy for human datasets. Compared with classical tools and deep learning-based models, this is 8.1%, 3.7%, 16.6%, 1.4%, 4.9%, and 48.9% higher than CPC2, CNCI, Wen et al.'s CNN, LncADeep, PLEK, and NcResNet, respectively. The accuracy of PLEKv2 was > 90% for cross-species prediction. PLEKv2 is more effective and robust than CPC2, CNCI, LncADeep, PLEK, and NcResNet for primate datasets (including chimpanzees, macaques, and gorillas). Moreover, PLEKv2 is not only suitable for non-human primates that are closely related to humans, but can also predict the coding ability of RNA sequences in plants such as Arabidopsis.

CONCLUSIONS

The experimental results illustrate that the model constructed by PLEKv2 can distinguish lncRNAs and mRNAs better than PLEK. The PLEKv2 software is freely available at https://sourceforge.net/projects/plek2/ .

Evolution of retrocopies in the context of HUSH silencing

Retrotransposition is one of the main factors responsible for gene duplication and thus genome evolution. However, the sequences that undergo this process are not only an excellent source of biological diversity, but in certain cases also pose a threat to the integrity of the DNA. One of the mechanisms that protects against the incorporation of mobile elements is the HUSH complex, which is responsible for silencing long, intronless, transcriptionally active transposed sequences that are rich in adenine on the sense strand. In this study, broad sets of human and porcine retrocopies were analysed with respect to the above factors, taking into account evolution of these molecules. Analysis of expression pattern, genomic structure, transcript length, and nucleotide substitution frequency showed the strong relationship between the expression level and exon length as well as the protective nature of introns. The results of the studies also showed that there is no direct correlation between the expression level and adenine content. However, protein-coding retrocopies, which have a lower adenine content, have a significantly higher expression level than the adenine-rich non-coding but expressed retrocopies. Therefore, although the mechanism of HUSH silencing may be an important part of the regulation of retrocopy expression, it is one component of a more complex molecular network that remains to be elucidated.

The importance of DNA sequence for nucleosome positioning in transcriptional regulation

Nucleosome positioning is a key factor for transcriptional regulation. Nucleosomes regulate the dynamic accessibility of chromatin and interact with the transcription machinery at every stage. Influences to steer nucleosome positioning are diverse, and the according importance of the DNA sequence in contrast to active chromatin remodeling has been the subject of long discussion. In this study, we evaluate the functional role of DNA sequence for all major elements along the process of transcription. We developed a random forest classifier based on local DNA structure that assesses the sequence-intrinsic support for nucleosome positioning. On this basis, we created a simple data resource that we applied genome-wide to the human genome. In our comprehensive analysis, we found a special role of DNA in mediating the competition of nucleosomes with cis-regulatory elements, in enabling steady transcription, for positioning of stable nucleosomes in exons, and for repelling nucleosomes during transcription termination. In contrast, we relate these findings to concurrent processes that generate strongly positioned nucleosomes in vivo that are not mediated by sequence, such as energy-dependent remodeling of chromatin.

Single-housing-induced islet epigenomic changes are related to polymorphisms in diabetic KK mice

A lack of social relationships is increasingly recognized as a type 2 diabetes (T2D) risk. To investigate the underlying mechanism, we used male KK mice, an inbred strain with spontaneous diabetes. Given the association between living alone and T2D risk in humans, we divided the non-diabetic mice into singly housed (KK-SH) and group-housed control mice. Around the onset of diabetes in KK-SH mice, we compared H3K27ac ChIP-Seq with RNA-Seq using pancreatic islets derived from each experimental group, revealing a positive correlation between single-housing-induced changes in H3K27ac and gene expression levels. In particular, single-housing-induced H3K27ac decreases revealed a significant association with islet cell functions and GWAS loci for T2D and related diseases, with significant enrichment of binding motifs for transcription factors representative of human diabetes. Although these H3K27ac regions were preferentially localized to a polymorphic genomic background, SNVs and indels did not cause sequence disruption of enriched transcription factor motifs in most of these elements. These results suggest alternative roles of genetic variants in environment-dependent epigenomic changes and provide insights into the complex mode of disease inheritance.

From molecular variations to behavioral adaptations: Unveiling adaptive epistasis in primate oxytocin system

OBJECTIVE

Our primary objective was to investigate the variability of oxytocin (OT) and the GAMEN binding motif within the LNPEP oxytocinase in primates.

MATERIALS AND METHODS

We sequenced the LNPEP segment encompassing the GAMEN motif in 34 Platyrrhini species, with 21 of them also sequenced for the OT gene. Our dataset was supplemented with primate sequences of LNPEP, OT, and the oxytocin receptor (OTR) sourced from public databases. Evolutionary analysis and coevolution predictions were made followed by the macroevolution analysis of relevant amino acids associated with phenotypic traits, such as mating systems, parental care, and litter size. To account for phylogenetic structure, we utilized two distinct statistical tests. Additionally, we calculated binding energies focusing on the interaction between Callithtrix jacchus VAMEN and Pro8OT.

RESULTS

We identified two novel motifs (AAMEN and VAMEN), challenging the current knowledge of motif conservation in placental mammals. Coevolution analysis demonstrated a correlation between GAMEN, AAMEN, and VAMEN and their corresponding OTs and OTRs. Callithrix jacchus exhibited a higher binding energy between VAMEN and Pro8OT than orthologous molecules found in humans (GAMEN and Leu8OT).

DISCUSSION

The coevolution of AAMEN and VAMEN with their corresponding OTs and OTRs suggests a functional relationship that could have contributed to specific reproductive and adaptive behaviors, including paternal care, social monogamy, and twin births, prominent traits in Cebidae species, such as marmosets and tamarins. Our findings underscore the coevolution of taxon-specific amino acids among the three studied molecules, shedding light on the oxytocinergic system as an adaptive epistatic repertoire in primates.

Geneapp: A web application for visualizing alternative splicing for biomedicine

Alternative Splicing (AS) is an essential mechanism for eukaryotes. However, the consequences of deleting a single exon can be dramatic for the organism and can lead to cancer in humans. Additionally, alternative 5' and 3' splice sites, which define the boundaries of exons, also play key roles to human disorders. Therefore, Investigating AS events is crucial for understanding the molecular basis of human diseases and developing therapeutic strategies. Workflow for AS event analysis can be sampling followed by data analysis with bioinformatics to identify the different AS events in the control and case samples, data visualization for curation, and selection of relevant targets for experimental validation. The raw output of the analysis software does not favor the inspection of events by bioinformaticians requiring custom scripts for data visualization. In this work, we propose the Geneapp application with three modules: GeneappScript, GeneappServer, and GeneappExplorer. GeneappScript is a wrapper that assists in identifying AS in samples compared in two different approaches, while GeneappServer integrates data from AS analysis already performed by the user. In GeneappExplorer, the user visualizes the previous dataset by exploring AS events in genes with functional annotation. This targeted screens that Geneapp allows to perform helps in the identification of targets for experimental validation to confirm the hypotheses under study. The Geneapp is freely available for non-commercial use at https://geneapp.net to advance research on AS for bioinformatics.

Algal methylated compounds shorten the lag phase of Phaeobacter inhibens bacteria

The lag phase is key in resuming bacterial growth, but it remains underexplored particularly in environmental bacteria. Here we use transcriptomics and 13C-labelled metabolomics to show that the lag phase of the model marine bacterium Phaeobacter inhibens is shortened by methylated compounds produced by the microalgal partner, Emiliania huxleyi. Methylated compounds are abundantly produced and released by microalgae, and we show that their methyl groups can be collected by bacteria and assimilated through the methionine cycle. Our findings underscore the significance of methyl groups as a limiting factor during the lag phase and highlight the adjustability of this growth phase. In addition, we show that methylated compounds, typical of photosynthetic organisms, prompt diverse reductions in lag times in bacteria associated with algae and plants, potentially favouring early growth in some bacteria. These findings suggest ways to accelerate bacterial growth and underscore the significance of studying bacteria within an environmental context.

Integrative genomics identifies SHPRH as a tumor suppressor gene in lung adenocarcinoma that regulates DNA damage response

BACKGROUND

Identification of driver mutations and development of targeted therapies has considerably improved outcomes for lung cancer patients. However, significant limitations remain with the lack of identified drivers in a large subset of patients. Here, we aimed to assess the genomic landscape of lung adenocarcinomas (LUADs) from individuals without a history of tobacco use to reveal new genetic drivers of lung cancer.

METHODS

Integrative genomic analyses combining whole-exome sequencing, copy number, and mutational information for 83 LUAD tumors was performed and validated using external datasets to identify genetic variants with a predicted functional consequence and assess association with clinical outcomes. LUAD cell lines with alteration of identified candidates were used to functionally characterize tumor suppressive potential using a conditional expression system both in vitro and in vivo.

RESULTS

We identified 21 genes with evidence of positive selection, including 12 novel candidates that have yet to be characterized in LUAD. In particular, SNF2 Histone Linker PHD RING Helicase (SHPRH) was identified due to its frequency of biallelic disruption and location within the familial susceptibility locus on chromosome arm 6q. We found that low SHPRH mRNA expression is associated with poor survival outcomes in LUAD patients. Furthermore, we showed that re-expression of SHPRH in LUAD cell lines with inactivating alterations for SHPRH reduces their in vitro colony formation and tumor burden in vivo. Finally, we explored the biological pathways associated SHPRH inactivation and found an association with the tolerance of LUAD cells to DNA damage.

CONCLUSIONS

These data suggest that SHPRH is a tumor suppressor gene in LUAD, whereby its expression is associated with more favorable patient outcomes, reduced tumor and mutational burden, and may serve as a predictor of response to DNA damage. Thus, further exploration into the role of SHPRH in LUAD development may make it a valuable biomarker for predicting LUAD risk and prognosis.

The alternative enzymes-bearing tunicates lack multiple widely distributed genes coding for peripheral OXPHOS subunits

The respiratory chain alternative enzymes (AEs) NDX and AOX from the tunicate Ciona intestinalis (Ascidiacea) have been xenotopically expressed and characterized in human cells in culture and in the model organisms Drosophila melanogaster and mouse, with the purpose of developing bypass therapies to combat mitochondrial diseases in human patients with defective complexes I and III/IV, respectively. The fact that the genes coding for NDX and AOX have been lost from genomes of evolutionarily successful animal groups, such as vertebrates and insects, led us to investigate if the composition of the respiratory chain of Ciona and other tunicates differs significantly from that of humans and Drosophila, to accommodate the natural presence of AEs. We have failed to identify in tunicate genomes fifteen orthologous genes that code for subunits of the respiratory chain complexes; all of these putatively missing subunits are peripheral to complexes I, III and IV in mammals, and many are important for complex-complex interaction in supercomplexes (SCs), such as NDUFA11, UQCR11 and COX7A. Modeling of all respiratory chain subunit polypeptides of Ciona indicates significant structural divergence that is consistent with the lack of these fifteen clear orthologous subunits. We also provide evidence using Ciona AOX expressed in Drosophila that this AE cannot access the coenzyme Q pool reduced by complex I, but it is readily available to oxidize coenzyme Q molecules reduced by glycerophosphate oxidase, a mitochondrial inner membrane-bound dehydrogenase that is not involved in SCs. Altogether, our results suggest that Ciona AEs might have evolved in a mitochondrial inner membrane environment much different from that of mammals and insects, possibly without SCs; this correlates with the preferential functional interaction between these AEs and non-SC dehydrogenases in heterologous mammalian and insect systems. We discuss the implications of these findings for the applicability of Ciona AEs in human bypass therapies and for our understanding of the evolution of animal respiratory chain.

vAMPirus: A versatile amplicon processing and analysis program for studying viruses

Amplicon sequencing is an effective and increasingly applied method for studying viral communities in the environment. Here, we present vAMPirus, a user-friendly, comprehensive, and versatile DNA and RNA virus amplicon sequence analysis program, designed to support investigators in exploring virus amplicon sequencing data and running informed, reproducible analyses. vAMPirus intakes raw virus amplicon libraries and, by default, performs nucleotide- and amino acid-based analyses to produce results such as sequence abundance information, taxonomic classifications, phylogenies and community diversity metrics. The vAMPirus analytical framework leverages 16 different opensource tools and provides optional approaches that can increase the ratio of biological signal-to-noise and thereby reveal patterns that would have otherwise been masked. Here, we validate the vAMPirus analytical framework and illustrate its implementation as a general virus amplicon sequencing workflow by recapitulating findings from two previously published double-stranded DNA virus datasets. As a case study, we also apply the program to explore the diversity and distribution of a coral reef-associated RNA virus. vAMPirus is streamlined within Nextflow, offering straightforward scalability, standardization and communication of virus lineage-specific analyses. The vAMPirus framework is designed to be adaptable; community-driven analytical standards will continue to be incorporated as the field advances. vAMPirus supports researchers in revealing patterns of virus diversity and population dynamics in nature, while promoting study reproducibility and comparability.

Metatranscriptomics: A Tool for Clinical Metagenomics

In the field of bioinformatics, amplicon sequencing of 16S rRNA genes has long been used to investigate community membership and taxonomic abundance in microbiome studies. As we can observe, shotgun metagenomics has become the dominant method in this field. This is largely owing to advancements in sequencing technology, which now allow for random sequencing of the entire genetic content of a microbiome. Furthermore, this method allows profiling both genes and the microbiome's membership. Although these methods have provided extensive insights into various microbiomes, they solely assess the existence of organisms or genes, without determining their active role within the microbiome. Microbiome scholarship now includes metatranscriptomics to decipher how a community of microorganisms responds to changing environmental conditions over a period of time. Metagenomic studies identify the microbes that make up a community but metatranscriptomics explores the diversity of active genes within that community, understanding their expression profile and observing how these genes respond to changes in environmental conditions. This expert review article offers a critical examination of the computational metatranscriptomics tools for studying the transcriptomes of microbial communities. First, we unpack the reasons behind the need for community transcriptomics. Second, we explore the prospects and challenges of metatranscriptomic workflows, starting with isolation and sequencing of the RNA community, then moving on to bioinformatics approaches for quantifying RNA features, and statistical techniques for detecting differential expression in a community. Finally, we discuss strengths and shortcomings in relation to other microbiome analysis approaches, pipelines, use cases and limitations, and contextualize metatranscriptomics as a tool for clinical metagenomics.

Measuring air metagenomic diversity in an agricultural ecosystem

All species shed DNA during life or in death, providing an opportunity to monitor biodiversity via environmental DNA (eDNA). In recent years, combining eDNA, high-throughput sequencing technologies, bioinformatics, and increasingly complete sequence databases has promised a non-invasive and non-destructive environmental monitoring tool. Modern agricultural systems are often large monocultures and so are highly vulnerable to disease outbreaks. Pest and pathogen monitoring in agricultural ecosystems is key for efficient and early disease prevention, lower pesticide use, and better food security. Although the air is rich in biodiversity, it has the lowest DNA concentration of all environmental media and yet is the route for windborne spread of many damaging crop pathogens. Our work suggests that ecosystems can be monitored efficiently using airborne nucleic acid information. Here, we show that the airborne DNA of microbes can be recovered, shotgun sequenced, and taxonomically classified, including down to the species level. We show that by monitoring a field growing key crops we can identify the presence of agriculturally significant pathogens and quantify their changing abundance over a period of 1.5 months, often correlating with weather variables. We add to the evidence that aerial eDNA can be used as a source for biomonitoring in terrestrial ecosystems, specifically highlighting agriculturally relevant species and how pathogen levels correlate with weather conditions. Our ability to detect dynamically changing levels of species and strains highlights the value of airborne eDNA in agriculture, monitoring biodiversity changes, and tracking taxa of interest.

Rheumatoid arthritis patients harbour aberrant enteric bacteriophages with autoimmunity-provoking potential: a paired sibling study

OBJECTIVES

Viruses have been considered as important participants in the development of rheumatoid arthritis (RA). However, the profile of enteric virome and its role in RA remains elusive. This study aimed to investigate the atlas and involvement of virome in RA pathogenesis.

METHODS

Faecal samples from 30 pairs of RA and healthy siblings that minimise genetic interferences were collected for metagenomic sequencing. The α and β diversity of the virome and the virome-bacteriome interaction were analysed. The differential bacteriophages were identified, and their correlations with clinical and immunological features of RA were analysed. The potential involvement of these differential bacteriophages in RA pathogenesis was further investigated by auxiliary metabolic gene annotation and molecular mimicry study. The responses of CD4+ T cells and B cells to the mimotopes derived from the differential bacteriophages were systemically studied.

RESULTS

The composition of the enteric bacteriophageome was distorted in RA. The differentially presented bacteriophages correlated with the immunological features of RA, including anti-CCP autoantibody and HLA-DR shared epitope. Intriguingly, the glycerolipid and purine metabolic genes were highly active in the bacteriophages from RA. Moreover, peptides of RA-enriched phages, in particular Prevotella phage and Oscillibacter phage could provoke the autoimmune responses in CD4+ T cells and plasma cells via molecular mimicry of the disease-associated autoantigen epitopes, especially those of Bip.

CONCLUSIONS

This study provides new insights into enteric bacteriophageome in RA development. In particular, the aberrant bacteriophages demonstrated autoimmunity-provoking potential that would promote the occurrence of the disease.

Investigating copy number variants in schizophrenia pedigrees using a new consensus pipeline called PECAN

Copy number variants (CNVs) have been implicated in many human diseases, including psychiatric disorders. Whole genome sequencing offers advantages in CNV calling compared to previous array-based methods. Here we present a robust and transparent CNV calling pipeline, PECAN (PEdigree Copy number vAriaNt calling), for short-read, whole genome sequencing data, comprised of a novel combination of four calling methods and structural variant genotyping. This method is scalable and can incorporate pedigree information to retain lower-confidence CNVs that would otherwise be discarded. We have robustly benchmarked PECAN using gold-standard CNV calls for two well-established evaluation samples, NA12878 and HG002, showing that PECAN performs with high precision and recall on both datasets, outperforming another pedigree-based CNV calling pipeline. As part of this work, we provide a list of high-confidence gold standard CNVs for the NA12878 reference sample, curated from multiple studies. We applied PECAN to a collection of pedigrees multiply affected with schizophrenia and identified a rare deletion that perfectly co-segregates with schizophrenia in one of the pedigrees. The CNV overlaps the gene PITRM1, which has been implicated in a complex phenotype including ataxia, developmental delay, and schizophrenia-like episodes in affected adults.

Comparison among different preclinical models derived from the same patient with a non-functional pancreatic neuroendocrine tumor

Pancreatic neuroendocrine tumors are the second most common tumors of the pancreas, and approximately half of patients are diagnosed with liver metastases. Currently, the improvement in the efficacy of relevant treatment methods is still limited. Therefore, there is an urgent need for in-depth research on the molecular biological mechanism of pancreatic neuroendocrine tumors. However, due to their relatively inert biology, preclinical models are extremely scarce. Here, the patient-derived organoid, and patient-derived xenograft were successfully constructed. These two models and the previously constructed cell line named SPNE1 all derived from the same patient with a grade 3 non-functional pancreatic neuroendocrine tumor, providing new tumor modeling platforms, and characterized using immunohistochemistry, whole-exome sequencing, and single-cell transcriptome sequencing. Combined with a tumor formation experiment in immunodeficient mice, we selected the model that most closely recapitulated the parental tumor. Overall, the patient-derived xenograft model most closely resembled human tumor tissue.

Whole genome sequencing study of identical twins discordant for psychosis

Monozygotic (MZ) twins are often thought to have identical genomes, but recent work has shown that early post-zygotic events can result in a spectrum of DNA variants that are different between MZ twins. Such variants may explain phenotypic discordance and contribute to disease etiology. Here we performed whole genome sequencing in 17 pairs of MZ twins discordant for a psychotic disorder (schizophrenia, schizoaffective disorder or bipolar disorder). We examined various classes of rare variants that are discordant within a twin pair. We identified four genes harboring rare, predicted deleterious missense variants that were private to an affected individual in the cohort. Variants in FOXN1 and FLOT2 would have been categorized as damaging from recent schizophrenia and bipolar exome sequencing studies. Additionally, we identified four rare genic copy number variants (CNVs) private to an affected sample, two of which overlapped genes that have shown evidence for association with schizophrenia or bipolar disorder. One such CNV was a 3q29 duplication previously implicated in autism and developmental delay. We have performed the largest MZ twin study for discordant psychotic phenotypes to date. These findings warrant further investigation using other analytical approaches.

Electrode-based floating treatment wetlands: Insights into design operation factors influencing bioenergy generation and treatment performance

Exponential increases in energy consumption and wastewater have often irreversible environmental impacts. As a result, bio-electrochemical devices like microbial fuel cells (MFCs), which convert chemical energy in organic matter to electricity using exoelectrogenic bacteria, have gained interest. However, operational factors affecting efficiency and energy output need further study. This research investigated bioenergy production and COD, TN, and TP removal in mesoscale floating treatment wetlands (FTW-MFC) using Phragmites australis, Iris pseudacorus, and a mix of both. The Iris FTW-MFC achieved a high voltage peak of 2100 mV. The maximum power densities of 484 mW/m2, 1196 mW/m2, and 441 mW/m2 were observed for Phragmites, Iris, and mixed FTW-MFCs, respectively. Despite promising bioenergy yields, pollutant removal was unsatisfactory. A low area/height ratio (0.38 m2/0.8 m) and high loading rate (18.1 g/m2·d COD) boosted bioenergy output but hindered treatment performance and stressed plants, causing root decay. No significant pollutant removal differences were found between FTW-MFC and FTW. Higher relative plant growth rates occurred in the FTW-MFC. Microbial analysis shown that representatives of Pseudomonas and Clostridium species were consistently found across all samples, involved in both organic compound transformation and electricity generation, contributed to successful microscale results. A supporting microscale MFC experiment showed wastewater composition's impact on bioenergy yield and pollutant removal. Pre-inoculated reactors improved organic matter transformation and electricity generation, while aeration increased voltage and treatment performance. The role of plants requires further verification in future experiments.

Unveiling errors in soil microbial community sequencing: a case for reference soils and improved diagnostics for nanopore sequencing

The sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories.

Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA

RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.

Improving the gold standard in NCBI GenBank and related databases: DNA sequences from type specimens and type strains

Scientific names permit humans and search engines to access knowledge about the biodiversity that surrounds us, and names linked to DNA sequences are playing an ever-greater role in search-and-match identification procedures. Here, we analyze how users and curators of the National Center for Biotechnology Information (NCBI) are flagging and curating sequences derived from nomenclatural type material, which is the only way to improve the quality of DNA-based identification in the long run. For prokaryotes, 18,281 genome assemblies from type strains have been curated by NCBI staff and improve the quality of prokaryote naming. For Fungi, type-derived sequences representing over 21,000 species are now essential for fungus naming and identification. For the remaining eukaryotes, however, the numbers of sequences identifiable as type-derived are minuscule, representing only 739 species of arthropods, 1542 vertebrates, and 125 embryophytes. An increase in the production and curation of such sequences will come from (i) sequencing of types or topotypic specimens in museum collections, (ii) the March 2023 rule changes at the International Nucleotide Sequence Database Collaboration requiring more metadata for specimens, and (iii) efforts by data submitters to facilitate curation, including informing NCBI curators about a specimen's type status. We illustrate different type-data submission journeys and provide best-practice examples from a range of organisms. Expanding the number of type-derived sequences in DNA databases, especially of eukaryotes, is crucial for capturing, documenting, and protecting biodiversity.

Ecological Predictors of Organelle Genome Evolution: Phylogenetic Correlations with Taxonomically Broad, Sparse, Unsystematized Data

Comparative analysis of variables across phylogenetically linked observations can reveal mechanisms and insights in evolutionary biology. As the taxonomic breadth of the sample of interest increases, challenges of data sparsity, poor phylogenetic resolution, and complicated evolutionary dynamics emerge. Here, we investigate a cross-eukaryotic question where all these problems exist: which organismal ecology features are correlated with gene retention in mitochondrial and chloroplast DNA (organelle DNA or oDNA). Through a wide palette of synthetic control studies, we first characterize the specificity and sensitivity of a collection of parametric and non-parametric phylogenetic comparative approaches to identify relationships in the face of such sparse and awkward datasets. This analysis is not directly focused on oDNA, and so provides generalizable insights into comparative approaches with challenging data. We then combine and curate ecological data coupled to oDNA genome information across eukaryotes, including a new semi-automated approach for gathering data on organismal traits from less systematized open-access resources including encyclopedia articles on species and taxa. The curation process also involved resolving several issues with existing datasets, including enforcing the clade-specificity of several ecological features and fixing incorrect annotations. Combining this unique dataset with our benchmarked comparative approaches, we confirm support for several known links between organismal ecology and organelle gene retention, identify several previously unidentified relationships constituting possible ecological contributors to oDNA genome evolution, and provide support for a recently hypothesized link between environmental demand and oDNA retention. We, with caution, discuss the implications of these findings for organelle evolution and of this pipeline for broad comparative analyses in other fields.

Two novel genomes of fireflies with different degrees of sexual dimorphism reveal insights into sex-biased gene expression and dosage compensation

Sexual dimorphism arises because of divergent fitness optima between the sexes. Phenotypic divergence between sexes can range from mild to extreme. Fireflies, bioluminescent beetles, present various degrees of sexual dimorphism, with species showing very mild sexual dimorphism to species presenting female-specific neoteny, posing a unique framework to investigate the evolution of sexually dimorphic traits across species. In this work, we present novel assembled genomes of two firefly species, Lamprohiza splendidula and Luciola italica, species with different degrees of sexual dimorphism. We uncover high synteny conservation of the X-chromosome across ~ 180 Mya and find full X-chromosome dosage compensation in our two fireflies, hinting at common mechanism upregulating the single male X-chromosome. Different degrees of sex-biased expressed genes were found across two body parts showing different proportions of expression conservation between species. Interestingly, we do not find X-chromosome enrichment of sex-biased genes, but retrieve autosomal enrichment of sex-biased genes. We further uncover higher nucleotide diversity in the intronic regions of sex-biased genes, hinting at a maintenance of heterozygosity through sexual selection. We identify different levels of sex-biased gene expression divergence including a set of genes showing conserved sex-biased gene expression between species. Divergent and conserved sex-biased genes are good candidates to test their role in the maintenance of sexually dimorphic traits.

Sex-specific DNA-replication in the early mammalian embryo

The timing of DNA replication in mammals is crucial for minimizing errors and influenced by genome usage and chromatin states. Replication timing in the newly formed mammalian embryo remains poorly understood. Here, we have investigated replication timing in mouse zygotes and 2-cell embryos, revealing that zygotes lack a conventional replication timing program, which then emerges in 2-cell embryos. This program differs from embryonic stem cells and generally correlates with transcription and genome compartmentalization of both parental genomes. However, consistent and systematic differences existed between the replication timing of the two parental genomes, including considerably later replication of maternal pericentromeric regions compared to paternal counterparts. Moreover, maternal chromatin modified by Polycomb Repressive Complexes in the oocyte, undergoes early replication, despite belonging to the typically late-replicating B-compartment of the genome. This atypical and asynchronous replication of the two parental genomes may advance our understanding of replication stress in early human embryos and trigger strategies to reduce errors and aneuploidies.

CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations

Biological databases serve as critical basics for modern research, and amid the dynamic landscape of biology, the COVID-19 database has emerged as an indispensable resource. The global outbreak of Covid-19, commencing in December 2019, necessitates comprehensive databases to unravel the intricate connections between this novel virus and cancer. Despite existing databases, a crucial need persists for a centralized and accessible method to acquire precise information within the research community. The main aim of the work is to develop a database which has all the COVID-19-related data available in just one click with auto global notifications. This gap is addressed by the meticulously designed COVID-19 Pandemic Database (CO-19 PDB 2.0), positioned as a comprehensive resource for researchers navigating the complexities of COVID-19 and cancer. Between December 2019 and June 2024, the CO-19 PDB 2.0 systematically collected and organized 120 datasets into six distinct categories, each catering to specific functionalities. These categories encompass a chemical structure database, a digital image database, a visualization tool database, a genomic database, a social science database, and a literature database. Functionalities range from image analysis and gene sequence information to data visualization and updates on environmental events. CO-19 PDB 2.0 has the option to choose either the search page for the database or the autonotification page, providing a seamless retrieval of information. The dedicated page introduces six predefined charts, providing insights into crucial criteria such as the number of cases and deaths', country-wise distribution, 'new cases and recovery', and rates of death and recovery. The global impact of COVID-19 on cancer patients has led to extensive collaboration among research institutions, producing numerous articles and computational studies published in international journals. A key feature of this initiative is auto daily notifications for standardized information updates. Users can easily navigate based on different categories or use a direct search option. The study offers up-to-date COVID-19 datasets and global statistics on COVID-19 and cancer, highlighting the top 10 cancers diagnosed in the USA in 2022. Breast and prostate cancers are the most common, representing 30% and 26% of new cases, respectively. The initiative also ensures the removal or replacement of dead links, providing a valuable resource for researchers, healthcare professionals, and individuals. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://www.co-19pdb.habdsk.org/. Database URL: https://www.co-19pdb.habdsk.org/.

Solving genomic puzzles: computational methods for metagenomic binning

Metagenomics involves the study of genetic material obtained directly from communities of microorganisms living in natural environments. The field of metagenomics has provided valuable insights into the structure, diversity and ecology of microbial communities. Once an environmental sample is sequenced and processed, metagenomic binning clusters the sequences into bins representing different taxonomic groups such as species, genera, or higher levels. Several computational tools have been developed to automate the process of metagenomic binning. These tools have enabled the recovery of novel draft genomes of microorganisms allowing us to study their behaviors and functions within microbial communities. This review classifies and analyzes different approaches of metagenomic binning and different refinement, visualization, and evaluation techniques used by these methods. Furthermore, the review highlights the current challenges and areas of improvement present within the field of research.

Comprehensive analysis of insertion sequences within rRNA genes of CPR bacteria and biochemical characterization of a homing endonuclease encoded by these sequences

The Candidate Phyla Radiation (CPR) represents an extensive bacterial clade comprising primarily uncultured lineages and is distinguished from other bacteria by a significant prevalence of insertion sequences (ISs) within their rRNA genes. However, our understanding of the taxonomic distribution and characteristics of these ISs remains limited. In this study, we used a comprehensive approach to systematically determine the nature of the rRNA ISs in CPR bacteria. The analysis of hundreds of rRNA gene sequences across 65 CPR phyla revealed that ISs are present in 48% of 16S rRNA genes and 82% of 23S rRNA genes, indicating a broad distribution across the CPR clade, with exceptions in the 16S and 23S rRNA genes of Candidatus (Ca.) Saccharibacteria and the 16S rRNA genes of Ca. Peregrinibacteria. Over half the ISs display a group-I-intron-like structure, whereas specific 16S rRNA gene ISs display features reminiscent of group II introns. The ISs frequently encode proteins with homing endonuclease (HE) domains, centered around the LAGLIDADG motif. The LAGLIDADG HE (LHE) proteins encoded by the rRNA ISs of CPR bacteria predominantly have a single-domain structure, deviating from the usual single- or double-domain configuration observed in typical prokaryotic LHEs. Experimental analysis of one LHE protein, I-ShaI from Ca. Shapirobacteria, confirmed that its endonuclease activity targets the DNA sequence of its insertion site, and chemical cross-linking experiments demonstrated its capacity to form homodimers. These results provide robust evidence supporting the hypothesis that the explosive proliferation of rRNA ISs in CPR bacteria was facilitated by mechanisms involving LHEs.

IMPORTANCE

Insertion sequences (ISs) in rRNA genes are relatively limited and infrequent in most bacterial phyla. With a comprehensive bioinformatic analysis, we show that in CPR bacteria, these ISs occur in 48% of 16S rRNA genes and 82% of 23S rRNA genes. We also report the systematic and biochemical characterization of the LAGLIDADG homing endonucleases (LHEs) encoded by these ISs in the first such analysis of the CPR bacteria. This study significantly extends our understanding of the phylogenetic positions of rRNA ISs within CPR bacteria and the biochemical features of their LHEs.

Absence of farnesol salvage in Candida albicans and probably in other fungi

Farnesol salvage, a two-step pathway converting farnesol to farnesyl pyrophosphate (FPP), occurs in bacteria, plants, and animals. This paper investigates the presence of this pathway in fungi. Through bioinformatics, biochemistry, and physiological analyses, we demonstrate its absence in the yeasts Saccharomyces cerevisiae and Candida albicans, suggesting a likely absence across fungi. We screened 1,053 fungal genomes, including 34 from C. albicans, for potential homologs to four genes (Arabidopsis thaliana AtFOLK, AtVTE5, AtVTE6, and Plasmodium falciparum PfPOLK) known to accomplish farnesol/prenol salvage in other organisms. Additionally, we showed that 3H-farnesol was not converted to FPP or any other phosphorylated prenol, and exogenous farnesol was not metabolized within 90 minutes at any phase of growth and did not rescue cells from the toxic effects of atorvastatin, but it did elevate the levels of intracellular farnesol (Fi). All these experiments were conducted with C. albicans. In sum, we found no evidence for farnesol salvage in fungi.

IMPORTANCE

The absence of farnesol salvage constitutes a major difference in the metabolic capabilities of fungi. In terms of fungal physiology, the lack of farnesol salvage pathways relates to how farnesol acts as a quorum-sensing molecule in Candida albicans and why farnesol should be investigated for use in combination with other known antifungal antibiotics. Its absence is essential for a model (K. W. Nickerson et al., Microbiol Mol Biol Rev 88:e00081-22, 2024), wherein protein farnesylation, protein chaperones, and the unfolded protein response are combined under the unifying umbrella of a cell's intracellular farnesol (Fi). In terms of human health, farnesol should have at least two different modes of action depending on whether those cells have farnesol salvage. Because animals have farnesol salvage, we can now see the importance of dietary prenols as well as the potential importance of farnesol in treating neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and multiple sclerosis.

Microbiological survey and genomic analysis of Cronobacter sakazakii strains isolated from US households and retail foods

Cronobacter species are opportunistic pathogens that are capable of causing morbidity and mortality, particularly in infants. Although the transmission dynamics involved in Cronobacter infections remain largely unknown, contaminated powdered infant formula (PIF) has been linked to 30% of Cronobacter sakazakii cases involving invasive illness in infants. As several lines of evidence have implicated the domestic environment in PIF contamination, we undertook a microbiological survey of homes (N = 263) across the US. Cronobacter spp. and C. sakazakii were isolated from 36.1% and 24.7% of US homes, respectively, with higher recovery rates observed for floor and kitchen surfaces. Multi-locus sequence typing indicated that the dominant strain was C. sakazakii ST4, the sequence type most commonly associated with neonatal meningitis. For comparison purposes, retail foods (N = 4,009) were also surveyed, with the highest contamination frequencies (10.1%-26.3%) seen for nut products, seeds, and grains/baked goods/flours. The sequence type profile of isolates recovered from homes mirrored that of isolates recovered from retail foods, with increased representation of ST1, ST4, ST13, ST17, and ST40. Analysis of 386 whole genomic sequences revealed significant diversity. Redundancies were only observed for isolates recovered from within the same domicile, and there were no identical matches with sequences archived at the NCBI pathogen database. Genes coding for putative virulence and antibiotic resistance factors did not segregate with clinically significant sequence types. Collectively, these findings support the possibility that contamination events occurring within the home should not be overlooked as a contributor to community-onset Cronobacter infections.

IMPORTANCE

Cronobacter sakazakii is an opportunistic pathogen that can cause significant morbidity and mortality in neonates. Its transmission dynamics are poorly understood, though powered infant formula (PIF) is thought to be the major transmission vehicle. How the PIF becomes contaminated remains unknown. Our survey shows that roughly 1/4 of US homes are contaminated with Cronobacter sakazakii, particularly in the kitchen setting. Our analyses suggest that the domestic environment may contribute to contamination of PIF and provides insights into mitigating the risk of transmission.

A gene-rich mitochondrion with a unique ancestral protein transport system

Mitochondria originated from an ancient endosymbiosis involving an alphaproteobacterium.1,2,3 Over time, these organelles reduced their gene content massively, with most genes being transferred to the host nucleus before the last eukaryotic common ancestor (LECA).4 This process has yielded varying gene compositions in modern mitogenomes, including the complete loss of this organellar genome in some extreme cases.5,6,7,8,9,10,11,12,13,14 At the other end of the spectrum, jakobids harbor the most gene-rich mitogenomes, encoding 60-66 proteins.8 Here, we introduce the mitogenome of Mantamonas sphyraenae, a protist from the deep-branching CRuMs supergroup.15,16 Remarkably, it boasts the most gene-rich mitogenome outside of jakobids, by housing 91 genes, including 62 protein-coding ones. These include rare homologs of the four subunits of the bacterial-type cytochrome c maturation system I (CcmA, CcmB, CcmC, and CcmF) alongside a unique ribosomal protein S6. During the early evolution of mitochondria, gene transfer from the proto-mitochondrial endosymbiont to the nucleus became possible thanks to systems facilitating the transport of proteins synthesized in the host cytoplasm back to the mitochondrion. In addition to the universally found eukaryotic protein import systems, jakobid mitogenomes were reported to uniquely encode the SecY transmembrane protein of the Sec general secretory pathway, whose evolutionary origin was however unclear. The Mantamonas mitogenome not only encodes SecY but also SecA, SecE, and SecG, making it the sole eukaryote known to house a complete mitochondrial Sec translocation system. Furthermore, our phylogenetic and comparative genomic analyses provide compelling evidence for the alphaproteobacterial origin of this system, establishing its presence in LECA.

Sexual size dimorphism in mammals is associated with changes in the size of gene families related to brain development

In mammals, sexual size dimorphism often reflects the intensity of sexual selection, yet its connection to genomic evolution remains unexplored. Gene family size evolution can reflect shifts in the relative importance of different molecular functions. Here, we investigate the associate between brain development gene repertoire to sexual size dimorphism using 124 mammalian species. We reveal significant changes in gene family size associations with sexual size dimorphism. High levels of dimorphism correlate with an expansion of gene families enriched in olfactory sensory perception and a contraction of gene families associated with brain development functions, many of which exhibited particularly high expression in the human adult brain. These findings suggest a relationship between intense sexual selection and alterations in gene family size. These insights illustrate the complex interplay between sexual dimorphism, gene family size evolution, and their roles in mammalian brain development and function, offering a valuable understanding of mammalian genome evolution.

Viral and Bacterial Community Dynamics in Food Waste and Digestate from Full-Scale Biogas Plants

Anaerobic digestion (AD) is commonly used in food waste treatment. Prokaryotic microbial communities in AD of food waste have been comprehensively studied. The role of viruses, known to affect microbial dynamics and metabolism, remains largely unexplored. This study employed metagenomic analysis and recovered 967 high-quality viral bins within food waste and digestate derived from 8 full-scale biogas plants. The diversity of viral communities was higher in digestate. In silico predictions linked 20.8% of viruses to microbial host populations, highlighting possible virus predators of key functional microbes. Lineage-specific virus-host ratio varied, indicating that viral infection dynamics might differentially affect microbial responses to the varying process parameters. Evidence for virus-mediated gene transfer was identified, emphasizing the potential role of viruses in controlling the microbiome. AD altered the specific process parameters, potentially promoting a shift in viral lifestyle from lysogenic to lytic. Viruses encoding auxiliary metabolic genes (AMGs) were involved in microbial carbon and nutrient cycling, and most AMGs were transcriptionally expressed in digestate, meaning that viruses with active functional states were likely actively involved in AD. These findings provided a comprehensive profile of viral and bacterial communities and expanded knowledge of the interactions between viruses and hosts in food waste and digestate.

A broad survey of choanoflagellates revises the evolutionary history of the Shaker family of voltage-gated K+ channels in animals

The Shaker family of voltage-gated K+ channels has been thought of as an animal-specific ion channel family that diversified in concert with nervous systems. It comprises four functionally independent gene subfamilies (Kv1-4) that encode diverse neuronal K+ currents. Comparison of animal genomes predicts that only the Kv1 subfamily was present in the animal common ancestor. Here, we show that some choanoflagellates, the closest protozoan sister lineage to animals, also have Shaker family K+ channels. Choanoflagellate Shaker family channels are surprisingly most closely related to the animal Kv2-4 subfamilies which were believed to have evolved only after the divergence of ctenophores and sponges from cnidarians and bilaterians. Structural modeling predicts that the choanoflagellate channels share a T1 Zn2+ binding site with Kv2-4 channels that is absent in Kv1 channels. We functionally expressed three Shakers from Salpingoeca helianthica (SheliKvT1.1-3) in Xenopus oocytes. SheliKvT1.1-3 function only in two heteromultimeric combinations (SheliKvT1.1/1.2 and SheliKvT1.1/1.3) and encode fast N-type inactivating K+ channels with distinct voltage dependence that are most similar to the widespread animal Kv1-encoded A-type Shakers. Structural modeling of the T1 assembly domain supports a preference for heteromeric assembly in a 2:2 stoichiometry. These results push the origin of the Shaker family back into a common ancestor of metazoans and choanoflagellates. They also suggest that the animal common ancestor had at least two distinct molecular lineages of Shaker channels, a Kv1 subfamily lineage predicted from comparison of animal genomes and a Kv2-4 lineage predicted from comparison of animals and choanoflagellates.

ProteinFlow: An advanced framework for feature engineering in protein data analysis

In the burgeoning field of proteins, the effective analysis of intricate protein data remains a formidable challenge, necessitating advanced computational tools for data processing, feature extraction, and interpretation. This study introduces ProteinFlow, an innovative framework designed to revolutionize feature engineering in protein data analysis. ProteinFlow stands out by offering enhanced efficiency in data collection and preprocessing, along with advanced capabilities in feature extraction, directly addressing the complexities inherent in multidimensional protein data sets. Through a comparative analysis, ProteinFlow demonstrated a significant improvement over traditional methods, notably reducing data preprocessing time and expanding the scope of biologically significant features identified. The framework's parallel data processing strategy and advanced algorithms ensure not only rapid data handling but also the extraction of comprehensive, meaningful insights from protein sequences, structures, and interactions. Furthermore, ProteinFlow exhibits remarkable scalability, adeptly managing large-scale data sets without compromising performance, a crucial attribute in the era of big data.