Uncovering new Firmicutes species in vertebrate hosts through metagenome-assembled genomes with potential for sporulation.

Metagenome-assembled genomes (MAGs) have contributed to identifying non-culturable microorganisms and understanding their ecological functions. MAGs offer an advantage in investigating sporulation-associated genes, especially given the difficulty of isolating many species residing in the gut microbiota of multiple hosts. Bacterial sporulation is a key survival mechanism with implications for pathogenicity and biotechnology. Here, we investigate MAGs from vertebrate hosts, emphasizing taxonomic identification and identifying sporulation-associated genes in potential novel species within the Firmicutes phylum. We identified potential new species in the classes Clostridia (Borkfalkiaceae, Lachnospiraceae, Monoglobaceae, and Oscillospiraceae families) and Bacilli (Bacillaceae and Erysipelotrichaceae families) through phylogenetic and functional pathway analyses, highlighting their sporulation potential. Our study covers 146 MAGs, 124 of them without refined taxonomic assignments at the family level. We found that Clostridia and Bacilli have unique sporulation gene profiles in the refined family MAGs for cattle, swine, poultry, and human hosts. The presence of genes related to Spo0A regulon, engulfment, and spore cortex in MAGs underscores fundamental mechanisms in sporulation processes in currently uncharacterized species with sporulation potential from metagenomic dark matter. Furthermore, genomic analyses predict sporulation potential based on gene presence, genome size, and metabolic pathways involved in spore formation. We emphasize MAGs covering families not yet characterized through the phylogenetic analysis, and with extensive potential for spore-forming bacteria within Clostridia, Bacilli, UBA4882, and UBA994 classes. These findings contribute to exploring spore-forming bacteria, which provides evidence for novel species diversity in multiple hosts, their adaptive strategies, and potential applications in biotechnology and host health.IMPORTANCESpores are essential for bacterial survival in harsh environments, facilitating their persistence and adaptation. Exploring sporulation-associated genes in metagenome-assembled genomes (MAGs) from different hosts contributes to clinical and biotechnological domains. Our study investigated the extent of genes associated with bacterial sporulation in MAGs from poultry, swine, cattle, and humans, revealing these genes in uncultivated bacteria. We identified potential novel Firmicutes species with sporulation capabilities through phylogenetic and functional analyses. Notably, MAGs belonging to Clostridia, Bacilli, and unknown classes, namely UBA4882 and UBA994, remained uncharacterized at the family level, which raises the hypothesis that sporulation would also be present in these genomes. These findings contribute to our understanding of microbial adaptation and have implications for microbial ecology, underlining the importance of sporulation in Firmicutes across different hosts. Further studies into novel species and their sporulation capability can contribute to bacterial maintenance mechanisms in various organisms and their applications in biotechnology studies.

The draft genomes of Crassostrea gasar and Crassostrea rhizophorae: key resources for leveraging oyster cultivation in the Southwest Atlantic.

OBJECTIVES: The two oyster species studied hold considerable economic importance for artisanal harvest (Crassostrea rhizophorae) and aquaculture (Crassostrea gasar). Their draft genomes will play an important role in the application of genomic methods such as RNAseq, population-based genomic scans aiming at addressing expression responses to pollution stress, adaptation to salinity and temperature variation, and will also permit investigating the genetic bases and enable marker-assisted selection of economically important traits like shell and mantle coloration and resistance to temperature and disease. DATA DESCRIPTION: The draft assembly size of Crassostrea gasar is 506 Mbp, and of Crassostrea rhizophorae is 584 Mbp with scaffolds N50 of 11,3 Mbp and 4,9 Mbp, respectively. The general masked bases by RepeatMasker in both genomes were highly similar using different datasets. The masked bases varied from 9.41% in C. gasar to 10.05% in C. rhizophorae and 42.85% in C. gasar to 44.44% in C. rhizophorae using Dfam and RepeatModeler datasets, respectively. Functional annotation with eggNog resulted in 34,693 annotated proteins in C. rhizophorae and 26,328 in C. gasar. BUSCO analysis shows that almost 99% of genes (5,295) are complete in relation to the mollusk orthologous genes dataset (mollusca_odb10).

Transcriptional and Post-Translational Roles of Calcineurin in Cationic Stress and Glycerol Biosynthesis in Cryptococcus neoformans.

Stress management is an adaptive advantage for survival in adverse environments. Pathogens face this challenge during host colonization, requiring an appropriate stress response to establish infection. The fungal pathogen Cryptococcus neoformans undergoes thermal, oxidative, and osmotic stresses in the environment and animal host. Signaling systems controlled by Ras1, Hog1, and calcineurin respond to high temperatures and osmotic stress. Cationic stress caused by Na+, K+, and Li+ can be overcome with glycerol, the preferred osmolyte. Deleting the glycerol phosphate phosphatase gene (GPP2) prevents cells from accumulating glycerol due to a block in the last step of its biosynthetic pathway. Gpp2 accumulates in a phosphorylated form in a cna1Δ strain, and a physical interaction between Gpp2 and Cna1 was found; moreover, the gpp2Δ strain undergoes slow growth and has attenuated virulence in animal models of infection. We provide biochemical evidence that growth in 1 M NaCl increases glycerol content in the wild type, whereas gpp2Δ, cna1Δ, and cnb1Δ mutants fail to accumulate it. The deletion of cnb1Δ or cna1Δ renders yeast cells sensitive to cationic stress, and the Gfp-Gpp2 protein assumes an abnormal localization. We suggest a mechanism in which calcineurin controls Gpp2 at the post-translational level, affecting its localization and activity, leading to glycerol biosynthesis. Also, we showed the transcriptional profile of glycerol-deficient mutants and established the cationic stress response mediated by calcineurin; among the biological processes differentially expressed are carbon utilization, translation, transmembrane transport, glutathione metabolism, oxidative stress response, and transcription regulation. To our knowledge, this is the first time that this transcriptional profile has been described. These results have implications for pathogen stress adaptability.

Predicting novel mosquito-associated viruses from metatranscriptomic dark matter.

The exponential growth of metatranscriptomic studies dedicated to arboviral surveillance in mosquitoes has yielded an unprecedented volume of unclassified sequences referred to as the virome dark matter. Mosquito-associated viruses are classified based on their host range into Mosquito-specific viruses (MSV) or Arboviruses. While MSV replication is restricted to mosquito cells, Arboviruses infect both mosquito vectors and vertebrate hosts. We developed the MosViR pipeline designed to identify complex genomic discriminatory patterns for predicting novel MSV or Arboviruses from viral contigs as short as 500 bp. The pipeline combines the predicted probability score from multiple predictive models, ensuring a robust classification with Area Under ROC (AUC) values exceeding 0.99 for test datasets. To assess the practical utility of MosViR in actual cases, we conducted a comprehensive analysis of 24 published mosquito metatranscriptomic datasets. By mining this metatranscriptomic dark matter, we identified 605 novel mosquito-associated viruses, with eight putative novel Arboviruses exhibiting high probability scores. Our findings highlight the limitations of current homology-based identification methods and emphasize the potentially transformative impact of the MosViR pipeline in advancing the classification of mosquito-associated viruses. MosViR offers a powerful and highly accurate tool for arboviral surveillance and for elucidating the complexities of the mosquito RNA virome.

SARS-CoV-2 Research in Dogs (Canis lupus familiaris) and Felines (Felis silvestris catus) Domiciled in an International Border Region (Paraguay and Brazil).

Introduction: COVID-19 is an infectious disease caused by SARS-CoV-2 that has become a serious threat to public health owing to its rapid spread from aerosols from infected people. Despite being considered a strictly human disease, there are reports in the literature about animals with confirmed presence of the virus. Aim: Owing to the scarcity of scientific literature on the potential for infection of animals and their importance for One Health, the objective of this work was to research SARS-CoV-2 RNA in felines (Felis silvestris catus) and dogs (Canis lupus familiaris) domiciled. Materials and Methods: Oropharyngeal swabs were collected from domestic dogs and cats belonging to patients diagnosed with COVID-19 from August to October 2021 and residents of the northwest and west regions of Paraná, Brazil. Results: Of the 34 samples collected, 14 were from dogs and 20 from cats. Three of these samples tested positive in real-time PCR, and two of them were also positive in the immunochromatographic test. After testing positive in real-time PCR, the samples underwent genetic sequencing using the Illumina COVIDSeq test. Of the 34 samples collected, three (9%), all of them female and from the feline species, tested positive in real-time PCR, with two of these (67%) also testing positive in the immunochromatographic test. Regarding sequencing, it was possible to sequence the three samples aligned with the AY.101 lineage, corresponding to the Delta variant. Conclusion: The occurrence of SARS-CoV-2 infection in dogs and cats is seen as an unintended event with significant implications for public health, including its potential transmission to other animal species. Further research is required to enhance our understanding of how this disease spreads among these animals and its broader impact on One Health initiatives.

Co-occurrence of PRKN and SYNJ1 variants in Early-Onset Parkinson's disease.

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease globally, with a fast-growing prevalence. The etiology of PD exhibits a multifactorial complex nature and remains challenging. Herein, we described clinical, molecular, and integrative bioinformatics findings from a Brazilian female affected by Early-Onset PD (EOPD) harboring a recurrent homozygous pathogenic deletion in the parkin RBR E3 ubiquitin protein ligase gene (PRKN; NM_004562.3:c.155delA; p.Asn52Metfs*29; rs754809877), along with a novel heterozygous variant in the synaptojanin 1 gene (SYNJ1; NM_003895.3:c.62G > T; p.Cys21Phe; rs1486511197) found by Whole Exome Sequencing. Uncommon or unreported PRKN-related clinical features in the patient include cognitive decline, auditory and visual hallucinations, REM sleep disorder, and depression, previously observed in SYNJ1-related conditions. Moreover, PRKN interacts with endophilin A1, which is a major binding partner of SYNJ1. This protein plays a pivotal role in regulating the dynamics of synaptic vesicles, particularly in the context of endocytosis and recycling processes. Altogether, our comprehensive analyses underscore a potential synergistic effect between the PRKN and SYNJ1 variants over the pathogenesis of EOPD.

Living in mangroves: a syntrophic scenario unveiling a resourceful microbiome.

BACKGROUND: Mangroves are complex and dynamic coastal ecosystems under frequent fluctuations in physicochemical conditions related to the tidal regime. The frequent variation in organic matter concentration, nutrients, and oxygen availability, among other factors, drives the microbial community composition, favoring syntrophic populations harboring a rich and diverse, stress-driven metabolism. Mangroves are known for their carbon sequestration capability, and their complex and integrated metabolic activity is essential to global biogeochemical cycling. Here, we present a metabolic reconstruction based on the genomic functional capability and flux profile between sympatric MAGs co-assembled from a tropical restored mangrove. RESULTS: Eleven MAGs were assigned to six Bacteria phyla, all distantly related to the available reference genomes. The metabolic reconstruction showed several potential coupling points and shortcuts between complementary routes and predicted syntrophic interactions. Two metabolic scenarios were drawn: a heterotrophic scenario with plenty of carbon sources and an autotrophic scenario with limited carbon sources or under inhibitory conditions. The sulfur cycle was dominant over methane and the major pathways identified were acetate oxidation coupled to sulfate reduction, heterotrophic acetogenesis coupled to carbohydrate catabolism, ethanol production and carbon fixation. Interestingly, several gene sets and metabolic routes similar to those described for wastewater and organic effluent treatment processes were identified. CONCLUSION: The mangrove microbial community metabolic reconstruction reflected the flexibility required to survive in fluctuating environments as the microhabitats created by the tidal regime in mangrove sediments. The metabolic components related to wastewater and organic effluent treatment processes identified strongly suggest that mangrove microbial communities could represent a resourceful microbial model for biotechnological applications that occur naturally in the environment.

Understanding the (epi)genetic dysregulation in Parkinson's disease through an integrative brain competitive endogenous RNA network.

Parkinson's disease (PD) is a rapidly growing neurodegenerative disorder characterized by dopaminergic neuron loss in the substantia nigra pars compacta (SN) and aggregation of α-synuclein. Its aetiology involves a multifaceted interplay among genetic, environmental, and epigenetic factors. We integrated brain gene expression data from PD patients to construct a comprehensive regulatory network encompassing messenger RNAs (mRNAs), microRNAs (miRNAs), circular RNAs (circRNAs) and, for the first time, RNA binding proteins (RBPs). Expression data from the SN of PD patients and controls were systematically selected from public databases to identify combined differentially expressed genes (DEGs). Brain co-expression analysis revealed modules comprising significant DEGs that function cooperatively. The relationships among co-expressed DEGs, miRNAs, circRNAs, and RBPs revealed an intricate competitive endogenous RNA (ceRNA) network responsible for post-transcriptional dysregulation in PD. Many genes in the ceRNA network, including the TOMM20 and HMGCR genes, overlap with the most relevant genes in our previous Alzheimer's disease-associated ceRNA network, suggesting common underlying mechanisms between both conditions. Moreover, in the ceRNA subnetwork, the RBP Aly/REF export factor (ALYREF), which acts as an RNA 5-methylcytosine(m5C)-binding protein, stood out. Our data sheds new light on the potential role of brain ceRNA networks in PD pathogenesis.

Immune response stability to the SARS-CoV-2 mRNA vaccine booster is influenced by differential splicing of HLA genes.

Many molecular mechanisms that lead to the host antibody response to COVID-19 vaccines remain largely unknown. In this study, we used serum antibody detection combined with whole blood RNA-based transcriptome analysis to investigate variability in vaccine response in healthy recipients of a booster (third) dose schedule of the mRNA BNT162b2 vaccine against COVID-19. The cohort was divided into two groups: (1) low-stable individuals, with antibody concentration anti-SARS-CoV IgG S1 below 0.4 percentile at 180 days after boosting vaccination; and (2) high-stable individuals, with antibody values greater than 0.6 percentile of the range in the same period (median 9525 [185-80,000] AU/mL). Differential gene expression, expressed single nucleotide variants and insertions/deletions, differential splicing events, and allelic imbalance were explored to broaden our understanding of the immune response sustenance. Our analysis revealed a differential expression of genes with immunological functions in individuals with low antibody titers, compared to those with higher antibody titers, underscoring the fundamental importance of the innate immune response for boosting immunity. Our findings also provide new insights into the determinants of the immune response variability to the SARS-CoV-2 mRNA vaccine booster, highlighting the significance of differential splicing regulatory mechanisms, mainly concerning HLA alleles, in delineating vaccine immunogenicity.

Whole genomes show contrasting trends of population size changes and genomic diversity for an Amazonian endemic passerine over the late quaternary.

The "Amazon tipping point" is a global change scenario resulting in replacement of upland terra-firme forests by large-scale "savannization" of mostly southern and eastern Amazon. Reduced rainfall accompanying the Last Glacial Maximum (LGM) has been proposed to have acted as such a tipping point in the past, with the prediction that terra-firme inhabiting species should have experienced reductions in population size as drier habitats expanded. Here, we use whole-genomes of an Amazonian endemic organism (Scale-backed antbirds - Willisornis spp.) sampled from nine populations across the region to test this historical demography scenario. Populations from southeastern Amazonia and close to the Amazon-Cerrado ecotone exhibited a wide range of demographic patterns, while most of those from northern and western Amazonia experienced uniform expansions between 400 kya and 80-60 kya, with gradual declines toward 20 kya. Southeastern populations of Willisornis were the last to diversify and showed smaller heterozygosity and higher runs of homozygosity values than western and northern populations. These patterns support historical population declines throughout the Amazon that affected more strongly lineages in the southern and eastern areas, where historical "tipping point" conditions existed due to the widespread replacement of humid forest by drier and open vegetation during the LGM.

Finding microbial composition and biological processes as predictive signature to access the ongoing status of mangrove preservation.

Mangroves are complex land-sea transition ecosystems whose microbiota are essential for their nutrient recycling and conservation. Brazil is the third-largest estuarine area in the world and "Baía de Todos os Santos" (BTS) is one of the largest bays of the country, with wide anthropogenic exploration. Using a metagenomic approach, we investigated composition and functional adaptability as signatures of the microbiome of pristine and anthropized areas of BTS, including those under petroleum refinery influence. The taxonomic analysis showed dominance of sulfate-reducing Desulfobacteraceae, Rhodobacteraceae, and Flavobacteriaceae. Taxa were significantly diverse between pristine and disturbed areas. Disturbed mangroves showed a notary increase in abundance of halophilic, sulfur-related, and hydrocarbon-degrading genera and a decrease in diatoms compared to pristine area. The metabolic profile of BTS mangroves was correlated with the differentially abundant microbiota. Two ecological scenarios were observed: one marked by functions of central metabolism associated with biomass degradation and another by mechanisms of microbial adaptability to pollution conditions and environmental degradation. Part of the microbiome was distinct and not abundant in Brazilian estuarine soils. The microbiome signature observed in each BTS mangrove reflects how human actions impact the diversity of these ecosystems and also emphasize their role in attempting to restore disturbed mangroves. The microbiome may act as a potential biological indicator of the preservation status of these soils, despite the limitation of soil property conditions. Additionally, our data pointed to metagenomics as an additional tool for environmental assessment and reinforced the need for protective measures for the mangroves under study.

Mitochondrial genome structure and composition in 70 fishes: a key resource for fisheries management in the South Atlantic.

BACKGROUND: Phylogenetic gaps of public databases of reference sequences are a major obstacle for comparative genomics and management of marine resources, particularly in the Global South, where economically important fisheries and conservation flagship species often lack closely-related references. We applied target-enrichment to obtain complete mitochondrial genomes of marine ichthyofauna from the Brazilian coast selected based on economic significance, conservation status and lack of phylogenetically-close references. These included sardines (Dorosomatidae, Alosidae), mackerels (Scombridae) croakers (Sciaenidae), groupers (Epinephelidae) and snappers (Lutjanidae). RESULTS: Custom baits were designed to enrich mitochondrial DNA across a broad phylogenetic range of fishes. Sequencing generated approximately 100k reads per sample, which were assembled in a total of 70 complete mitochondrial genomes and include fifty-two new additions to GenBank, including five species with no previous mitochondrial data. Departures from the typical gene content and order occurred in only three taxa and mostly involved tRNA gene duplications. Start-codons for all genes, except Cytochrome C Oxidase subunit I (COI), were consistently ATG, whilst a wide range of stop-codons deviated from the prevailing TAA. Phylogenetic analysis confirmed assembly accuracy and revealed signs of cryptic diversification within the Mullus genus. Lineage delimitation methods using Sardinella aurita and S. brasiliensis mitochondrial genomes support a single Operational Taxonomic Unit. CONCLUSIONS: Target enrichment was highly efficient, providing complete novel mitochondrial genomes with little sequencing effort. These sequences are deposited in public databases to enable subsequent studies in population genetics and adaptation of Latin American fish species and serve as a vital resource for conservation and management programs that rely on molecular data for species and genus-level identification.

Differential Type-I Interferon Response in Buffy Coat Transcriptome of Individuals Infected with SARS-CoV-2 Gamma and Delta Variants.

The innate immune system is the first line of defense against pathogens such as the acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The type I-interferon (IFN) response activation during the initial steps of infection is essential to prevent viral replication and tissue damage. SARS-CoV and SARS-CoV-2 can inhibit this activation, and individuals with a dysregulated IFN-I response are more likely to develop severe disease. Several mutations in different variants of SARS-CoV-2 have shown the potential to interfere with the immune system. Here, we evaluated the buffy coat transcriptome of individuals infected with Gamma or Delta variants of SARS-CoV-2. The Delta transcriptome presents more genes enriched in the innate immune response and Gamma in the adaptive immune response. Interactome and enriched promoter analysis showed that Delta could activate the INF-I response more effectively than Gamma. Two mutations in the N protein and one in the nsp6 protein found exclusively in Gamma have already been described as inhibitors of the interferon response pathway. This indicates that the Gamma variant evolved to evade the IFN-I response. Accordingly, in this work, we showed one of the mechanisms that variants of SARS-CoV-2 can use to avoid or interfere with the host Immune system.

Multi-layered transcriptomic analysis reveals a pivotal role of FMR1 and other developmental genes in Alzheimer's disease-associated brain ceRNA network.

Alzheimer's disease (AD) is an increasingly neurodegenerative disorder that causes progressive cognitive decline and memory impairment. Despite extensive research, the underlying causes of late-onset AD (LOAD) are still in progress. This study aimed to establish a network of competing regulatory interactions involving circular RNAs (circRNAs), microRNAs (miRNAs), RNA-binding proteins (RBPs), and messenger RNAs (mRNAs) connected to LOAD. A systematic analysis of publicly available expression data was conducted to identify integrated differentially expressed genes (DEGs) from the hippocampus of LOAD patients. Subsequently, gene co-expression analysis identified modules comprising highly expressed DEGs that act cooperatively. The competition between co-expressed DEGs and miRNAs/RBPs and the simultaneous interactions between circRNA and miRNA/RBP revealed a complex ceRNA network responsible for post-transcriptional regulation in LOAD. Hippocampal expression data for miRNAs, circRNAs, and RBPs were used to filter relevant relationships for AD. An integrated topological score was used to identify the highly connected hub gene, from which a brain core ceRNA subnetwork was generated. The Fragile X Messenger Ribonucleoprotein 1 (FMR1) coding for the RBP FMRP emerged as the prominent driver gene in this subnetwork. FMRP has been previously related to AD but not in a ceRNA network context. Also, the substantial number of neurodevelopmental genes in the ceRNA subnetwork and their related biological pathways strengthen that AD shares common pathological mechanisms with developmental conditions. Our results enhance the current knowledge about the convergent ceRNA regulatory pathways underlying AD and provide potential targets for identifying early biomarkers and developing novel therapeutic interventions.

Genetic screening in a Brazilian cohort with inborn errors of immunity.

BACKGROUND: Inherited genetic defects in immune system-related genes can result in Inborn Errors of Immunity (IEI), also known as Primary Immunodeficiencies (PID). Diagnosis of IEI disorders is challenging due to overlapping clinical manifestations. Accurate identification of disease-causing germline variants is crucial for appropriate treatment, prognosis, and genetic counseling. However, genetic sequencing is challenging in low-income countries like Brazil. This study aimed to perform genetic screening on patients treated within Brazil's public Unified Health System to identify candidate genetic variants associated with the patient's phenotype. METHODS: Thirteen singleton unrelated patients from three hospitals in Rio de Janeiro were enrolled in this study. Genomic DNA was extracted from the peripheral blood lymphocytes of each patient, and whole exome sequencing (WES) analyses were conducted using Illumina NextSeq. Germline genetic variants in IEI-related genes were prioritized using a computational framework considering their molecular consequence in coding regions; minor allele frequency ≤ 0.01; pathogenicity classification based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines gathered from the VarSome clinical database; and IEI-related phenotype using the Franklin tool. The genes classification into IEI categories follows internationally recognized guidelines informed by the International Union of Immunological Societies Expert Committee. Additional methods for confirmation of the variant included Sanger sequencing, phasing analysis, and splice site prediction. RESULTS: A total of 16 disease-causing variants in nine genes, encompassing six different IEI categories, were identified. X-Linked Agammaglobulinemia, caused by BTK variations, emerged as the most prevalent IEI disorder in the cohort. However, pathogenic and likely pathogenic variants were also reported in other known IEI-related genes, namely CD40LG, CARD11, WAS, CYBB, C6, and LRBA. Interestingly, two patients with suspected IEI exhibited pathogenic variants in non-IEI-related genes, ABCA12 and SLC25A13, potentially explaining their phenotypes. CONCLUSIONS: Genetic screening through WES enabled the detection of potentially harmful variants associated with IEI disorders. These findings contribute to a better understanding of patients' clinical manifestations by elucidating the genetic basis underlying their phenotypes.

(m, n)-mer-a simple statistical feature for sequence classification.

Summary: The (m, n)-mer is a simple alternative classification feature based on conditional probability distributions. In this application note, we compared k-mer and (m, n)-mer frequency features in 11 distinct datasets used for binary, multiclass and clustering classifications. Our findings show that the (m, n)-mer frequency features are related to the highest performance metrics and often statistically outperformed the k-mers. Here, the (m, n)-mer frequencies improved performance for classifying smaller sequence lengths (as short as 300 bp) and yielded higher metrics when using short values of k (ranging from 2 to 4). Therefore, we present the (m, n)-mers frequencies to the scientific community as a feature that seems to be quite effective in identifying complex discriminatory patterns and classifying polyphyletic sequence groups. Availability and implementation: The (m, n)-mer algorithm is released as an R package within the CRAN project (https://cran.r-project.org/web/packages/mnmer) and is also available at https://github.com/labinfo-lncc/mnmer. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

PPIntegrator: semantic integrative system for protein-protein interaction and application for host-pathogen datasets.

Summary: Semantic web standards have shown importance in the last 20 years in promoting data formalization and interlinking between the existing knowledge graphs. In this context, several ontologies and data integration initiatives have emerged in recent years for the biological area, such as the broadly used Gene Ontology that contains metadata to annotate gene function and subcellular location. Another important subject in the biological area is protein-protein interactions (PPIs) which have applications like protein function inference. Current PPI databases have heterogeneous exportation methods that challenge their integration and analysis. Presently, several initiatives of ontologies covering some concepts of the PPI domain are available to promote interoperability across datasets. However, the efforts to stimulate guidelines for automatic semantic data integration and analysis for PPIs in these datasets are limited. Here, we present PPIntegrator, a system that semantically describes data related to protein interactions. We also introduce an enrichment pipeline to generate, predict and validate new potential host-pathogen datasets by transitivity analysis. PPIntegrator contains a data preparation module to organize data from three reference databases and a triplification and data fusion module to describe the provenance information and results. This work provides an overview of the PPIntegrator system applied to integrate and compare host-pathogen PPI datasets from four bacterial species using our proposed transitivity analysis pipeline. We also demonstrated some critical queries to analyze this kind of data and highlight the importance and usage of the semantic data generated by our system. Availability and implementation: https://github.com/YasCoMa/ppintegrator, https://github.com/YasCoMa/ppi_validation_process and https://github.com/YasCoMa/predprin.

Assessing whole-exome sequencing data from undiagnosed Brazilian patients to improve the diagnostic yield of inborn errors of immunity.

OBJECTIVES: Inborn error of immunity (IEI) comprises a broad group of inherited immunological disorders that usually display an overlap in many clinical manifestations challenging their diagnosis. The identification of disease-causing variants from whole-exome sequencing (WES) data comprises the gold-standard approach to ascertain IEI diagnosis. The efforts to increase the availability of clinically relevant genomic data for these disorders constitute an important improvement in the study of rare genetic disorders. This work aims to make available WES data of Brazilian patients' suspicion of IEI without a genetic diagnosis. We foresee a broad use of this dataset by the scientific community in order to provide a more accurate diagnosis of IEI disorders. DATA DESCRIPTION: Twenty singleton unrelated patients treated at four different hospitals in the state of Rio de Janeiro, Brazil were enrolled in our study. Half of the patients were male with mean ages of 9 ± 3, while females were 12 ± 10 years old. The WES was performed in the Illumina NextSeq platform with at least 90% of sequenced bases with a minimum of 30 reads depth. Each sample had an average of 20,274 variants, comprising 116 classified as rare pathogenic or likely pathogenic according to American College of Medical Genetics and Genomics and the Association (ACMG) guidelines. The genotype-phenotype association was impaired by the lack of detailed clinical and laboratory information, besides the unavailability of molecular and functional studies which, comprise the limitations of this study. Overall, the access to clinical exome sequencing data is limited, challenging exploratory analyses and the understanding of genetic mechanisms underlying disorders. Therefore, by making these data available, we aim to increase the number of WES data from Brazilian samples despite contributing to the study of monogenic IEI-disorders.

The Omicron Lineages BA.1 and BA.2 (Betacoronavirus SARS-CoV-2) Have Repeatedly Entered Brazil through a Single Dispersal Hub.

Brazil currently ranks second in absolute deaths by COVID-19, even though most of its population has completed the vaccination protocol. With the introduction of Omicron in late 2021, the number of COVID-19 cases soared once again in the country. We investigated in this work how lineages BA.1 and BA.2 entered and spread in the country by sequencing 2173 new SARS-CoV-2 genomes collected between October 2021 and April 2022 and analyzing them in addition to more than 18,000 publicly available sequences with phylodynamic methods. We registered that Omicron was present in Brazil as early as 16 November 2021 and by January 2022 was already more than 99% of samples. More importantly, we detected that Omicron has been mostly imported through the state of São Paulo, which in turn dispersed the lineages to other states and regions of Brazil. This knowledge can be used to implement more efficient non-pharmaceutical interventions against the introduction of new SARS-CoV variants focused on surveillance of airports and ground transportation.

Inference of differentially expressed genes using generalized linear mixed models in a pairwise fashion.

Background: Technological advances involving RNA-Seq and Bioinformatics allow quantifying the transcriptional levels of genes in cells, tissues, and cell lines, permitting the identification of Differentially Expressed Genes (DEGs). DESeq2 and edgeR are well-established computational tools used for this purpose and they are based upon generalized linear models (GLMs) that consider only fixed effects in modeling. However, the inclusion of random effects reduces the risk of missing potential DEGs that may be essential in the context of the biological phenomenon under investigation. The generalized linear mixed models (GLMM) can be used to include both effects. Methods: We present DEGRE (Differentially Expressed Genes with Random Effects), a user-friendly tool capable of inferring DEGs where fixed and random effects on individuals are considered in the experimental design of RNA-Seq research. DEGRE preprocesses the raw matrices before fitting GLMMs on the genes and the derived regression coefficients are analyzed using the Wald statistical test. DEGRE offers the Benjamini-Hochberg or Bonferroni techniques for P-value adjustment. Results: The datasets used for DEGRE assessment were simulated with known identification of DEGs. These have fixed effects, and the random effects were estimated and inserted to measure the impact of experimental designs with high biological variability. For DEGs' inference, preprocessing effectively prepares the data and retains overdispersed genes. The biological coefficient of variation is inferred from the counting matrices to assess variability before and after the preprocessing. The DEGRE is computationally validated through its performance by the simulation of counting matrices, which have biological variability related to fixed and random effects. DEGRE also provides improved assessment measures for detecting DEGs in cases with higher biological variability. We show that the preprocessing established here effectively removes technical variation from those matrices. This tool also detects new potential candidate DEGs in the transcriptome data of patients with bipolar disorder, presenting a promising tool to detect more relevant genes. Conclusions: DEGRE provides data preprocessing and applies GLMMs for DEGs' inference. The preprocessing allows efficient remotion of genes that could impact the inference. Also, the computational and biological validation of DEGRE has shown to be promising in identifying possible DEGs in experiments derived from complex experimental designs. This tool may help handle random effects on individuals in the inference of DEGs and presents a potential for discovering new interesting DEGs for further biological investigation.