Transcriptomics-based approaches, particularly in human-derived cell systems, are emerging as key New Approach Methods (NAMs). These methods offer high-throughput, high-content, and human-relevant analyses of DNA damage. Transcriptomic profiling, which tracks gene expression changes resulting from chemical exposure, provides insights into both adverse and adaptive biological responses. This chapter gives an insight into the methodology (Wet Lab and Dry Lab) to be followed for the RNA sequencing and RNA data analysis, which can be used for identifying the biomarkers/signatures for the genotoxicity-based studies. RNA sequencing is a useful next-generation sequencing (NGS) technique, which has wide variety of applications which include studying altered gene expression, alternative spliced transcripts, gene fusion, post-transcriptional modifications, and mutations/single nucleotide polymorphisms (SNPs). Not only mRNA, RNA-Seq is used to study small RNAs as well as long non-coding RNA profiles in a cell or tissues. The basic steps for RNA-Seq include RNA isolation, cDNA synthesis, attachment of adapters, cDNA library preparation, followed by sequencing and bioinformatic data analysis workflow. The depth to which the library is sequenced depends on the usage of the output data. The sequencing usually follows either single-read or paired-end sequencing methods. Once the data is generated, it can be processed using R-programming, which is briefly discussed here as well.

Wild plant-associated rhizospheric microbiomes represent largely unexplored reservoirs of carbohydrate-active enzymes (CAZymes) that have significant biotechnological potential. This metagenomic investigation examined glycoside hydrolase (GH) family distribution within rhizospheric microbial assemblages of two native Saudi Arabian plants: Moringa oleifera and Abutilon fruticosum. High-throughput shotgun sequencing revealed pronounced plant species-specific CAZyme specialization. Moringa oleifera rhizospheres exhibited exclusive enrichment in five GH families (GH105, GH106, GH25, GH28, and GH38), while A. fruticosum supported three distinct families (GH17, GH32, and GH33). Taxonomic analysis revealed differential microbial composition: M. oleifera communities were dominated by Actinobacteria (Streptomyces, Micromonospora) with significant eukaryotic representation, whereas A. fruticosum microbiomes showed bacterial predominance, primarily Proteobacteria (Pseudomonas, Bradyrhizobium). CAZyme-encoding sequences frequently exceeded 120 per GH family, indicating extensive catalytic potential. These specialized enzymes offer multifaceted applications across pharmaceutical glycoprotein synthesis, lignocellulosic biomass degradation for biofuels, food preservation systems, and biomaterial fabrication for tissue regeneration. The rhizosphere-specific enrichment of highly specialized CAZyme consortia positions these microbial communities as scalable biocatalytic platforms, providing eco-sustainable alternatives to conventional industrial methodologies across pharmaceutical, energy, food, and environmental sectors.

Background/Objectives: We conducted an untargeted metabolomic study in serum, urine, and fecal water in colorectal cancer (CRC) patients compared to healthy controls. The aim was to define the interactions between metabolites and microbiota. Methods: Effluents were collected before colonoscopy. Metabolites were analyzed using LC-HRMS. Bioinformatics analyses included Limma test, along with spectral house and public databases for annotations. Whole-genome shotgun sequencing was performed on fecal samples. Species–metabolite interactions were calculated using Spearman correlation. Interleukins and inflammatory proteins were measured. Results: Fifty-three patients (11 stage I, 10 stage II, 10 stage III, and 22 stage IV) and twenty controls were included. Derivatives of deoxycholic acid, cholic acid, and fatty acids were lower in serum, while urinary bile acids were higher in stage IV CRC patients (versus controls). Metabolites related to tryptophan and glutamate were found significantly altered in stage IV: upregulation of kynurenine and downregulation of indole pathways. This was linked to increased inflammatory protein and microbial metabolites and to the imbalance between virulent pro-inflammatory bacteria (Escherichia and Desulfovibrio) and symbiotic (Ruminococcus and Bifidobacterium) bacteria. Conclusions: E. coli-related tryptophan catabolism shift is shown through stage IV CRC as compared to controls. As a consequence, tryptophan/kynurenine metabolite may become a promising marker for detecting the failure to immune response during therapy.

The physical structure of pulse cotyledon cells modulates gut microbiota by controlling starch and protein availability for colonic fermentation, yet the mechanisms governing the interplay between saccharolytic and proteolytic fermentation remain unclear. Here, enzymatically treated white kidney bean cotyledon cells with weakened cell walls (CWs) underwent in vitro fecal fermentations and shotgun sequencing. Impaired CWs enhanced fermentation, increased acetate and propionate production, and reduced branched-chain fatty acids (BCFAs) and ammonia. Damaged CWs upregulated CAZymes encoding genes GH4, GH15, GH126, CBM20, and CBM26, which are associated with amylase, α-glucosidases, and amyloglucosidase activities involved in starch degradation. Furthermore, amino acid pathway enrichment revealed that IhgO and csiD, involved in lysine degradation, as well as astA-E, PRODH, putA and E1.2.1.88, involved in the conversion of arginine and proline to glutamate, were upregulated. Instead, isolated protein showed the highest ammonia and BCFAs production, accompanied by elevated glutamate dehydrogenase (gudB, GLUD1_2, and E1.4.1.4), soxA and soxB, involved in serine metabolism, and DBT, involved in branched-chain amino acid degradation. These findings provide metagenomic insights into how pulse CW integrity regulates saccharolytic and proteolytic fermentation, deepening our understanding of whole pulse foods in supporting gut health.

Antibiotics disrupt mucosal microbial communities, yet the effects on microbiomes infected with Chlamydia trachomatis (Ct) remain poorly understood. Some data exist on vaginal microbiomes, but none exist for the endocervix or rectum that are primary sites of infection. We applied metagenomic shotgun sequencing to vaginal, endocervical and rectal samples collected longitudinally from women who cleared their infection post-treatment (n = 10), had persistent infection (n = 11), or remained uninfected (n = 18) to evaluate azithromycin-induced changes in microbial composition, function, and the resistome over time. Our results show shifts in composition and function post-treatment that support persistent Ct, nonsynonymous Ct L22 amino acid substitutions that may be linked to azithromycin resistance, and significant endocervical increases in azithromycin resistance genes in Lactobacillus iners and Gardnerella vaginalis strains with moderate/high biofilm formation potential. These findings highlight the unintended ecological consequences of azithromycin treatment, including likely resistance gene propagation, emphasizing the need for novel treatment and microbiome-preserving strategies.

Formalin-fixed paraffin-embedded (FFPE) tissue preservation, while cost-effective and stable in ambient conditions, induces DNA damage manifesting as C:G > T:A transition artifacts through cytosine deamination. These artifacts can dominate low-frequency variant calls and obscure true somatic mutations, which are critical for clinical interpretation. Here, we present MOBSNVF, a statistical tool to distinguish genuine variants from FFPE-induced artifacts by leveraging orientation bias, which is the preferential appearance of artifactual variants in Read 1 versus Read 2 during paired-end sequencing due to single-strand DNA damage. We comprehensively evaluated MOBSNVF against established FFPE artifact filters using simulated data spanning varying tumor purities, damage levels, and sequencing depths, as well as four real clinical datasets with matched FFPE and fresh-frozen samples. MOBSNVF achieved near-perfect classification on simulated data with an AUROC and AUPRC of 0.999, maintaining robust performance across all tested conditions. On clinical samples, MOBSNVF consistently delivered superior precision-recall trade-offs and exhibited greater AUROC and AUPRC, effectively correcting the characteristic C:G > T:A mutational skew in FFPE samples while preserving non-artifactual mutation contexts. Our tool also demonstrates broad applicability to any paired-end sequencing data while extending to other single-strand lesions, including oxidative damage, thereby establishing MOBSNVF as a robust component for clinical and research sequencing workflows requiring accurate somatic variant detection from FFPE specimens.

BackgroundMetagenomics offers a culture-independent framework for comprehensively characterizing microbial communities by directly extracting and sequencing DNA from environmental samples. In this study, we employed high-throughput metagenomic sequencing to explore microbial communities inhabiting fungal-rich environments, emphasizing taxonomic composition, functional potential, and antibiotic resistance gene (ARG) dynamics.MethodsSix samples from two distinct groups (HFJ and QFJ) were subjected to Illumina-based shotgun sequencing, followed by rigorous quality control, taxonomic classification, KEGG-based functional annotation, and ARG identification via the CARD database. Comparative analysis revealed stark contrasts between the two groups.ResultsHFJ samples were dominated by eukaryotic taxa, particularly Saccharomyces cerevisiae, and exhibited elevated carbohydrate metabolism, aligning with the ecological role of fermentative fungi. Conversely, QFJ samples displayed higher bacterial diversity, particularly Firmicutes and Proteobacteria, and were enriched in lipid and amino acid metabolism pathways. Striking differences were also observed in ARG profiles. QFJ samples harbored greater ARG abundance, particularly genes conferring resistance to beta-lactams, aminoglycosides, and tetracyclines, indicating higher resistance potential and possible horizontal gene transfer activity.ConclusionOur results reveal distinct microbial, functional and resistome profiles in fungal-rich versus bacterial-rich fermentation environments. Fungal dominance correlated with lower bacterial diversity and a reduced abundance of certain ARGs, whereas bacterial-rich samples exhibited higher diversity and ARG prevalence. These correlations generate the hypothesis that fungal dominance may suppress bacterial growth or ARG dissemination; however, causal relationships cannot be inferred from our cross-sectional data. The study highlights the potential of metagenomic surveillance to elucidate ecological niches that influence bacterial diversity and resistance dynamics.

PurposeTo investigate the microbial profiles in the retina and RPE/choroid, and how they respond to retinal injury.MethodsAdult C57BL/6J mice were subjected to retinal laser burns using a photocoagulator. One and 24h later, the retina and RPE/choroid were collected under strict sterile conditions and processed for 16S rRNA paired-end sequencing (2×250). The data were analyzed using R software, GraphPad Prism, OmicShare, and Wekemo Bioincloud.ResultsMicrobiota were detected in the retina and RPE/choroid under normal physiological conditions. The alpha diversity was higher in the retina than in the RPE/choroid. All retinal microbiotas at the phylum level and 12 out of 14 at the genus level were shared with those of RPE/choroid. The top phyla were Firmicutes, Proteobacteria, and Actinobacteria. Retinal laser injury reduced the alpha diversity but did not affect beta diversity. In the RPE/choroid, the abundance of Actinomyces and Roseburia decreased, and the abundance of Lactobacillus increased significantly after laser injury. The abundance of Sphingomonas in the retina decreased, and the abundance of Faecalibacterium and Bifidobacterium increased (P<0.05) after laser injury in the retina. Faecalibacterium and Bifidobacterium are positively linked to Th17/IL-17 signaling and RIG-I-like receptor signaling pathways, as well as antigen processing and presentation.ConclusionsThe neuroretina and RPE/choroid have diverse microbiomes under normal conditions. Their richness and evenness are relatively stable in the retina compared to those in the RPE/choroid. Retinal laser injury enriches Faecalibacterium and Bifidobacterium in ocular tissues, and these microbiotas may participate in retinal wound healing through modulating inflammation.

Background: Periodontitis is a chronic inflammatory disease mostly associated with Porphyromonas gingivalis infection and characterized by progressive destruction of the supporting structures of the tooth, including the gingiva, periodontal ligament and alveolar bone. However, the impact of other members of the periodontal microbiome on stage of the severity of the periodontitis remains largely uncharacterized. Methods: This exploratory study employs whole-genome shotgun (WGS) metagenomics to characterize the periodontal microbiome in patients suffering from mild and severe periodontitis, aiming to identify microbial signatures linked to disease severity via analysis of taxonomic composition, predicted metabolic pathways and metagenome-assembled genomes (MAGs). After initial selection, 28 adult patients with a computer tomography (CT)-confirmed diagnosis of mild and severe stage of periodontitis from 2 clinics were included in the research project. Results: Taxonomic analysis confirms the presence of various commensal and pathogenic bacteria detectable at the species level, especially belonging to so-called "red, orange and green periodontal complexes"-P. gingivalis, T. forsythia, C. rectus, and Capnocytophaga spp. that may contribute to disease heterogeneity. The conducted investigation suggests that non-microbial factors such as cardiovascular diseases and antibiotic usage in the last 6 months prior to the hospital admission could explain variance of disease progression and impact on severity. Analysis of microbial functional composition revealed metabolic traits showing positive correlations with severe stage of periodontitis. Robust network analysis suggested interactions between pathogenic bacteria of the red complex and other members of the periodontal microbiome. Conclusions: These findings underscore the multifactorial nature of periodontitis pathogenesis, highlighting the need for integrated approaches combining microbial, host, and environmental data to unravel drivers of disease progression. The study provides a foundation for future large-scale investigations into personalized diagnostic or therapeutic strategies.

Ancient metagenomic studies using capture or shotgun sequencing often perform pairwise alignment of individual reads against large reference databases followed by lowest common ancestor assignment for taxonomic identification. Here, we present bamdam, a lightweight post-mapping, post lowest common ancestor toolkit for eukaryotic or microbial metagenomics. Bamdam can shrink large metagenomics bam files, often by a factor of 10x or more, while retaining all informative reads and alignments, compute a suite of authentication metrics for each taxonomic node including k-mer duplicity, postmortem damage, and mean read complexity, and generate various visualizations including multi-sample deamination plots and damage-colored interactive Krona plots.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13059-025-03879-x.

Black cumin, turmeric root, and Ceylon cinnamon bark are spices that have been used for both culinary purposes and in traditional medicine practices. These spices are frequently connected with providing antidiabetic, antimicrobial, anti-inflammatory, and gastroprotective properties. However, most studies on potential health effects have not been performed in humans. Since many of the health effect claims relate to gastrointestinal health, we explored the impact of black cumin extract (BCE), turmeric root extract (TRE), and Ceylon cinnamon extract (CCE) on the human gut microbiota ex vivo using the SIFR® technology. The impact on the gut microbiota were determined using shotgun sequencing and flow cytometry, while the health-related short-chain fatty acids (SCFA) were analyzed to assess the metabolic output. While TRE and CCE had very little effect on the gut microbiota, BCE significantly increased acetate (+ 8.7mM), butyrate (+1.3mM), and propionate (+3mM) production. This related to specific increases of Alistipes onderdonkii, Alistipes shahii and particularly Candidatus Cibiobacter qucibialis, CCE and TRE increased the health related Faecalibacterium prausnitzii and Dysosmobacter welbionis, respectively, with CCE also increasing Enterococcus and Veillonella species. Overall, these findings indicate these spices may have an impact on the human gut microbiome that could explain their purported health effects.

Background and aimCurrent efforts to characterize the circulating microbiome are constrained by the lack of standardized protocols for isolating and sequencing microbial communities in blood. To address this challenge, our study compared 16S rRNA (V3-V4 region) and shotgun metagenomic sequencing for circulating microbiome detection.Materials and methodsAfter obtaining ethics committee approval and informed consent, samples were aseptically collected from 10 patients undergoing transjugular intrahepatic portosystemic shunt (TIPS) procedures. Shotgun metagenomic reads were taxonomically classified using the Kraken2-Bracken pipeline. 16S rRNA (V3-V4) data were analyzed through an ASV-based approach, with USEARCH for denoising and VSEARCH for taxonomic annotation. The results from both sequencing methods were then systematically compared.ResultsShotgun metagenomic sequencing generated 7,024,580,376 raw reads (mean depth: 234,152,679.2 reads/sample), while 16S rRNA sequencing produced 6,612,678 raw reads (mean depth: 220,422.6 reads/sample). 16S rRNA amplicon sequencing captured a broader range of microbial signals. Although the taxonomic profiles from both sequencing methods showed limited overlap, the core microbiota common to both were still identified. These conserved core microbial communities exhibited stable α- and β-diversity indices across separate vascular compartments.ConclusionIn our study, 16S rRNA amplicon sequencing captured more diverse microbial signals than shotgun metagenomics. A stable microbial community structure was observed across vascular compartments, suggesting a homogeneous microbial composition throughout the circulatory system.

Feline immunodeficiency virus (FIV) is a retrovirus that causes lifelong infections in cats and may lead to immune dysfunction. Despite its importance for feline health, there is limited FIV data from France. This study investigated samples collected from stray and owned cats with outdoor access across France between December 2023 and January 2025 to estimate FIV seroprevalence, identify seropositivity predictors and analyse the genetic diversity of circulating strains. Serological screening was performed using a commercial ELISA. Polymerase chain reaction (PCR) was conducted on ELISA-positive sera, with selected samples analysed by Sanger sequencing for phylogenetic inference. One sample underwent metagenomic shotgun sequencing using Oxford Nanopore technology. The national seroprevalence, estimated using a Bayesian hierarchical model, was 16% (95% credible interval: 8.4–20%) overall, then 31% (21–42%) among intact male cats, 18% (CrI: 10.6–25.2%) among neutered male cats and 8.4% (CrI: 1.8–14%) among female cats. Outdoor exposure, sex and neuter status were strong predictors of seropositivity. Among strays, predicted probability of seropositivity exceeded 50% by 5 years of age. All sequenced viruses were classified as subtype A. However, the phylogenetic analysis revealed notable genetic variability, indicating at least two independent introductions of FIV into France. While related to other European strains, several isolates appeared to share distinct ancestral lineages. The metagenomic dataset yielded approximately 100,000 FIV reads among 2 million total reads, enabling full genome recovery. These findings highlight the ongoing circulation of FIV in France and provide valuable data for veterinary practitioners and future surveillance efforts in Europe.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13567-025-01672-z.

BackgroundZoonotic pathogens pose a serious threat to public health, and are often acquired from foods of animal origin, including livestock and poultry, where they may occur as pathogens or commensals. For example, Klebsiella pneumoniae, one of the ESKAPEE organisms, occurs in the gastrointestinal tract of cattle and poultry, and causes mastitis in dairy cows, creating potential routes of transmission via contaminated meat or milk. The occurrence of antimicrobial resistance (AMR) and MDR in ESKAPEE pathogens from animals in high antimicrobial use environments is well-known but there is a limited information available on the occurrence of AMR K. pneumoniae in livestock and poultry production systems with restricted antimicrobial use, such as in Australia, which has long limited the use of highest priority critically important antimicrobials in livestock and has very limited use of in-feed antimicrobials.ObjectiveThis study aimed to investigate the phenotypic and genomic AMR profiles of bovine and poultry K. pneumoniae, which may contribute to the spread of AMR to human and other animals via direct contact, contaminated food and environment, even in the absence of dietary antimicrobial growth promoters.MethodsBovine Klebsiella isolates were obtained from milk of cows with clinical mastitis, using routine bacteriological culture methods and interpretation criteria. Samples were obtained from 2022 to 2024 and originated from 7 herds in New South Wales and Victoria. Only isolates obtained in pure culture, indicative of intramammary infection, and with 500 colony forming units/ml were included. Poultry Klebsiella isolates originated from cloacal swabs from broiler chickens. Swabs were collected post-mortem at the end of antimicrobial-free nutrition trials and isolates were obtained from the mixed bacterial population present in such samples using selective agars with and without breakpoint concentrations of antimicrobial compounds. MALDI ToF MS was used for species confirmation of isolates from both host species. Antimicrobial susceptibility testing (AST) was conducted using the disc diffusion method for three antimicrobial agents each of human and veterinary importance (tetracycline, ciprofloxacin, cefotaxime, gentamicin, meropenem and trimethoprim/sulfamethoxazole). Genome sequencing was conducted by Macrogen using the Nextera DNA XT kit for library preparation and NovaseqX (150 bp paired end reads) for sequencing.ResultsAST showed that among all K. pneumoniae isolates from poultry (90, obtained from media with and without antimicrobials), 29% showed AMR and 64% showed MDR. Among the MDR isolates, the most common MDR phenotype was observed at 58% to five different antimicrobial compounds having the same MDR profile i.e. tetracycline, ciprofloxacin, cefotaxime, gentamicin and trimethoprim/sulfamethoxazole. While almost all isolates from cattle (52 of 53) were susceptible to all antimicrobial compounds, and none of the bovine isolates were MDR.ConclusionsOur results show the absence of AMR from bovine Klebsiella, despite the use of antimicrobials for control of mastitis on dairy farms, and the presence of AMR and MDR K. pneumoniae in poultry in the absence of antimicrobial selection pressure. Thus, factors other than antimicrobial use need to be considered as possible drivers of AMR prevalence and transmission.

Native cattle breeds in Europe are vital to agricultural heritage and livestock production, combining adaptation to diverse environments with desirable traits such as high-quality beef and milk. To investigate genetic diversity, local adaptation, and productivity-related characteristics, we generated whole-genome sequences from 289 cattle representing 11 native breeds and the commercial Holstein-Friesian breed across Finland, the Netherlands, and Portugal. These breeds span diverse climates and management systems, from cold northern regions to Mediterranean environments in southern Europe. The dataset comprises over 11 terabytes of paired-end Illumina NovaSeq6000 sequencing data, with an average depth of ~10 × and an alignment rate of ~99.7% against the ARS-UCD1.2 and 2.0 cattle reference genomes. Variant calling identified about 30 million SNPs and 2.7 million small indels distributed unevenly across the genome. Annotation linked many variants to known genes. This genomic resource provides an important foundation for studying genomic diversity, environmental adaptation, small structural variants discovery, and genomic mapping of economically important traits, offering insights for future breeding and conservation programs in European cattle.

Background: Early-life gut microbiota colonization plays a significant role in the neurodevelopment of infants and young children. However, the causal relationship between early-life gut microbiota colonization and neurodevelopment in preterm infants has not yet been conclusively established. Our research will initiate the PIGMAN (Premature Infants Gut Microbiota Assembly and Neurodevelopment) cohort study to systematically examine the dynamic interplay between gut microbiota developmental trajectories and neurodevelopmental processes in preterm infants. Methods: This study will employ a longitudinal cohort design and utilize data from the PIGMAN cohort, examining the interplay between gut microbiota metabolism and neurodevelopmental outcomes. The study design incorporates longitudinal stool sample collection, which will be analyzed through 16S rRNA gene sequencing and metagenomic shotgun sequencing, enabling comprehensive characterization of microbial community dynamics and functional metabolic pathways. Anticipated Results: Advanced analytical approaches incorporating causal inference methodologies will be implemented to identify significant microbial and metabolic biomarkers associated with neurodevelopmental outcomes in preterm neonates, and to establish causal pathways between these biomarkers and neurodevelopment. These analytical advancements will facilitate the construction of predictive models that utilize temporal microbial signatures and metabolite trajectories as prognostic indicators for neurodevelopmental outcomes. Causal inference method evaluations will further reveal that specific gut-derived metabolites, particularly those involved in cholesterol metabolism and neural signaling pathways—such as bile acids and GABA (gamma-aminobutyric acid)—exhibit superior predictive capacity for cognitive development trajectories. Anticipated Conclusions: The findings will collectively suggest that longitudinal metabolic profiling of the gut ecosystem, when combined with causal network analysis, provides a novel paradigm for developing clinically actionable predictive models of neurodevelopment in vulnerable preterm populations.

Selective serotonin reuptake inhibitors are widely prescribed during pregnancy. Their main route of administration is through the gut. However, their impact on the maternal and offspring gut microbiome and microbial metabolic pathways remains poorly understood. This study used metagenomic shotgun sequencing to examine the effects of perinatal citalopram exposure in rat dams and their offspring on gut composition and downstream metabolic pathways. We treated pregnant and nursing rat dams with either citalopram or vehicle (water). Their feces were collected, DNA from these samples was extracted and then sequenced using shotgun metagenomic sequencing. The BioBakery suite of microbiome analysis tools was utilized in tandem with RStudio to analyze the gut composition and microbial metabolic pathways of the rat dams and their offspring. Pregnant and nursing dams treated with citalopram exhibited marked shifts in microbial community structure, including phylum-level alterations in Proteobacteria and Defferibacteria. Citalopram treated dams displayed significantly altered beta diversity. Species level alterations due to treatment were composed of five significantly altered microbes, two of which belong to the Proteobacteria phylum. These changes were highly diverse and were not congruent with microbe-level alterations observed in offspring. Alpha diversity of microbial metabolic pathways was compared using the Gini-Simpson index, which was significantly increased in dams suggesting greater metabolic functional diversity with age. Female offspring perinatally exposed to citalopram showed significant changes in gut beta diversity, with seven significant alterations at the microbe level. These microbial shifts were accompanied by twenty-one significantly altered microbial metabolic pathways. In contrast, male offspring showed no significant differences in microbial composition or beta diversity and only minor metabolic changes. These findings demonstrate that maternal citalopram exposure during pregnancy and lactation has lasting, sex-specific impacts on the offspring's gut microbiome and microbial metabolic pathways. The pronounced alterations in female, but not male offspring, suggest that host sex may be a critical determinant in the developmental response to citalopram exposure. This work underscores the value of metagenomic approaches in uncovering complex host-microbiome interactions and highlights the need to consider offspring sex in evaluating the safety and long-term effects of antidepressant use during pregnancy.

BackgroundGut bacterial variations and dysbiosis may influence cognitive function via the microbiome‐gut‐brain‐axis. Gut viruses may also, directly or indirectly, impact cognitive function by modulating the gut bacteria. Hispanics/Latinos, who may have unique microbiome characteristics, are at a higher risk of Alzheimer's disease and related dementia. There is a lack of research on the gut microbiome and, especially, the virome in Hispanics/Latinos. Here, we examined variations in the gut bacteriome and virome associated with cognitive function in the Boston Puerto Rican Health Study (BPRHS), a prospective cohort of older Puerto Rican adults residing in the Boston area.MethodThis study was conducted in 316 BPRHS participants with fecal metagenomic sequencing and cognitive assessments, summarized as a composite global cognitive score (GCS). Taxonomic profiling of the gut bacteriome was performed using MetaPhlAN 4.0. Gut virome profiles from shotgun sequencing were generated using BAQLaVa 1.0. Cross‐sectional associations between bacterial and viral composition and GCS were assessed using alpha (Shannon) and beta (Bray‐Curtis) diversity indices. Feature‐wise testing was performed using multivariate linear regression (MaAsLin2) to identify bacterial and viral taxa associated with the GCS.ResultAmong 316 participants (mean age 68.7 years, 70.9% female), there were no differences in overall bacterial or viral composition, measured by alpha and beta diversity, based on GCS. In feature‐wise analyses, adjusted for age, sex, and BMI, among participants with higher GCS (better cognitive function), we observed an enrichment of Faecalibacterium prausnitzii bacterium (β = 0.78, p = 0.01, FDR p = 0.22), and depletion of the phage Carjivirus communis (β = ‐1.07, p < 0.01, FDR p = 0.09).ConclusionThe observed results suggest an enrichment of F. prausnitzii, a beneficial butyrate producing taxa, among participants with better cognitive function, and enrichment of Carjivirus communis, a Crassvirales dsDNA Bacteroidetes phage, among participants with worse cognitive function. A recent study reported an association between Bacteroidetes phages and amyloid β and Alzheimer's disease pathology. Gut viral variations may modulate gut bacteria, impacting cognitive function. Future work will test interactions of the gut bacteriome, virome and their functional pathways, as related to cognitive function in Puerto Rican adults.

Shotgun sequencing of camel milk microbiome

The rapid emergence of large-scale next-generation sequencing (NGS) data has created a growing demand for efficient preprocessing tools. Removal of polymerase chain reaction (PCR) duplicates is a critical step in many NGS data processing pipelines to reduce amplification bias. Currently, numerous de novo-based PCR duplicate removal tools are available, which cluster identical or highly similar reads without reference genome alignment. Practical application of such programs to large-scale NGS data (100 GB and more) is hampered by significant computational requirements, particularly high computer short-term memory usage comparable to the original file sizes. Processing large datasets generated by modern high-throughput techniques such as Hi-C or RNA-chromatin interaction sequencing can require hundreds of gigabytes of RAM, posing an exceptionally high computational demand. Here, we present Fastq-dupaway as a new tool for efficient PCR duplicate removal from both single-end and paired-end sequencing data ( https://github.com/AndrewSigorskih/fastq-dupaway ). Its key innovation lies in its primary operational modes, which are designed to use a small, parameterizable amount of RAM (2-10 GB) independent of input data size, at the cost of requiring approximately 2× the input file size in disk space. This enables the processing of very large datasets even on standard personal computers. Fastq-dupaway matches or exceeds (by up to threefold) the processing speed of major de novo deduplication tools, while maintaining the same level of duplicate removal.